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1. Aetiology of tinea capitis in China: a multicentre prospective study*

Author

J.-S. Zeng, F.-Q. Li, Y. Zhang, J.-X. Yang, B. Yin, C.-W. Cao, G.-Z. Chen, Yuping Ran, Aibo Wang, Y.-Y. Xiao, Jiahong Yu, Xue Qi Chen, L.-Y. Xi, W.-H. Pan, M. Zhu, B.-L. Dong, N. Yu, Y.-P. Jiang, H.-Q. Huang, W.-W. Wu, P. Abliz, Y. Guo, H. Sang, R. Li, L. Ma, X.-F. Li, Y. Jin, H.-F. Liu, Z.-H. Liu, Z.-S. Tong, D.-M. Shi, D.-Y. Zheng, X.-C. Xiong, M. Fu, Zhe Wan, Y. Wang, and W. Chen

Subjects
China, medicine.medical_specialty, Dermatology, medicine.disease_cause, Trichophyton, Risk Factors, Epidemiology, medicine, Animals, Humans, Microsporum, Prospective Studies, Microsporum canis, Prospective cohort study, Tinea Capitis, biology, business.industry, Transmission (medicine), biology.organism_classification, medicine.disease, Canis, Dermatophyte, Etiology, Female, Tinea capitis, business
Abstract

Tinea capitis is still common in developing countries, such as China. Its pathogen spectrum varies across regions and changes over time.This study aimed to clarify the current epidemiological characteristics and pathogen spectrum of tinea capitis in China.A multicentre, prospective descriptive study involving 29 tertiary hospitals in China was conducted. From August 2019 to July 2020, 611 patients with tinea capitis were enrolled. Data concerning demography, risk factors and fungal tests were collected. When necessary, the pathogens were further identified by morphology or molecular sequencing in the central laboratory.Among all enrolled patients, 74·1% of the cases were in patients aged 2-8 years. The children with tinea capitis were mainly boys (56·2%) and were more likely than adults to have a history of animal contact (57·4% vs. 35·3%, P = 0·012) and zoophilic dermatophyte infection (73·5% vs. 47%). The adults were mainly female (83%) and were more likely than children to have anthropophilic agent infection (53% vs. 23·9%). The most common pathogen was zoophilic Microsporum canis (354, 65·2%), followed by anthropophilic Trichophyton violaceum (74, 13·6%). In contrast to the eastern, western and northeastern regions, where zoophilic M. canis predominated, anthropophilic T. violaceum predominated in central China (69%, P 0·001), where the patients had the most tinea at other sites (20%) and dermatophytosis contact (26%) but the least animal contact (39%). Microsporum ferrugineum was the most common anthropophilic agent in the western area, especially in Xinjiang province.Boys aged approximately 5 years were the most commonly affected group. Dermatologists are advised to pay more attention to the different transmission routes and pathogen spectra in different age groups from different regions.

Published
2021

3. The Combined Effect of Hearing Impairment and Cognitive Impairment with Health-Related Outcomes in Chinese Older People

Author

Wanyu Zhao, Y. Xiao, R. Qiao, Birong Dong, L. Hou, Y. Zhang, Xuyang Xia, and S. Jia

Subjects
China, medicine.medical_specialty, 030309 nutrition & dietetics, Medicine (miscellaneous), Audiology, Logistic regression, 03 medical and health sciences, 0302 clinical medicine, Intervention (counseling), otorhinolaryngologic diseases, medicine, Humans, Cognitive Dysfunction, Multiple morbidities, 030212 general & internal medicine, Hearing Loss, Cognitive impairment, Geriatric Assessment, Depression (differential diagnoses), Aged, 0303 health sciences, Nutrition and Dietetics, business.industry, Cognition, Middle Aged, medicine.disease, Cross-Sectional Studies, Anxiety, Geriatrics and Gerontology, medicine.symptom, business, Older people
Abstract

To determine the risk of poor health-related outcomes in older adults with cooccurring hearing impairment and cognitive impairment, and to compare the risk of hearing impairment only, cognitive impairment only, and multiple morbidities. Cross-sectional study. Community-dwelling older adults aged 60 years and older were included. The data of missing hearing and cognitive status were excluded, and 3770 older people participated in the study. The hearing function evaluation was conducted by questionnaire survey. Assessment of cognitive function was completed using the SPMSQ scale. The subjects were divided into hearing impairment and cognitive impairment group, hearing impairment only group, cognitive impairment only group and neither group. Multiple logistic regression was used to analyze the risks of hearing and cognitive impairment and health-related condition. The prevalence of hearing impairment and cognitive impairment, hearing impairment only, cognitive impairment only, and neither were 9.4%, 8.3%, 29.9% and 52.4%, respectively. Compared with the control group, the individuals with hearing impairment and cognitive impairment were associated with depression (OR=3.48, 95% CI=2.66, 4.56), anxiety (OR=2.35, 95% CI=1.92, 3.33), frailty (OR=4.30, 95% CI=2.89, 6.40), and ADL impairment (OR=2.77, 95% CI=2.03, 3.77). The studies shows that hearing impairment combined with cognitive impairment is significantly associated with anxiety, depression, frailty, and ADL impairment. Comprehensive management and intervention should be provided for older people to reduce the occurrence of adverse health consequences.

Published
2021

4. Development of structural testing equipment for impact and complex loading

Author

Y. Xiao

Subjects
Truck, Impact testing, Engineering, Work (electrical), business.industry, Mechanical Engineering, Structural testing, Testing equipment, General Materials Science, Building and Construction, business, Construction engineering, Civil and Structural Engineering
Abstract

This paper summarizes the author’s work of developing various impact testing equipment and equipment for simulating complex earthquake loading for structural research. The equipment include large d...

Published
2020

5. Seismic performance of seawater and sea sand concrete-filled ultra-high performance concrete tubes under low-cycle reversed lateral loading

Author

B. Shan, Fucai Liu, Dade Lai, Gang Liu, and Y. Xiao

Subjects
Cement, Materials science, business.industry, Composite number, Seawater, Tube (fluid conveyance), Building and Construction, Structural engineering, Fibre-reinforced plastic, Composite material, Ultra high performance, business, Civil and Structural Engineering
Abstract

Seawater and sea sand concrete (SWSSC) filled ultra-high performance concrete (UHPC) tube (SFUHPC tube) column is a cement-based tubular composite column, which combines the excellent compressive strength and toughness of UHPC and lateral confining action from fiber reinforced polymer (FRP) hoops. The novel composite system has the potential to be used in marine engineering. The aims of this paper focus on evaluating the seismic performance of SFUHPC tube columns for being designed in costal and marine engineering. A series of low-cycle reversed lateral loading tests were conducted on five relatively large-scale specimens. FRP hoop volumetric ratio, compressive strength of filling SWSSC, and the types of FRP bar were selected as test parameters in this investigation. The failure modes, hysteretic responses and effects of main parameters were studied and discussed. SFUHPC tube columns exhibited flexural failure mode without visible spalling of the UHPC cover. It is noteworthy that the limit plastic drift ratios of all SFUHPC tube columns exceed the specified limits (0.02) in accordance to the rare earthquake requirement in seismic design code. The current study reveals that the proposed composite columns have acceptable ductility and relatively reliable lateral resistant performance for being used in the marine engineering. From the point of view of seismic performance, filling high strength SWSSC in UHPC tube is acceptable for the proposed composite system.

Published
2020

6. Finite Element Analysis of Viscoelastic/Damage Behaviors of Composite Solid Propellant for Underwater Intelligent Equipment

Author

Jie Li, H. Y. Xiao, Pengfei Liu, and S. F. Gong

Subjects
Propellant, Materials science, business.industry, 020209 energy, Mechanical Engineering, Composite number, 02 engineering and technology, Structural engineering, Viscoelasticity, Finite element method, Stress (mechanics), 020303 mechanical engineering & transports, 0203 mechanical engineering, Mechanics of Materials, Solid mechanics, Ultimate tensile strength, 0202 electrical engineering, electronic engineering, information engineering, General Materials Science, Safety, Risk, Reliability and Quality, business, Displacement (fluid)
Abstract

This paper studies viscoelastic behaviors of composite solid propellant for multiple material layers of underwater intelligent equipment by theoretical modeling and finite element analysis (FEA). First, the viscoelasticity/damage coupled model is developed for hydroxyl-butyrate composite propellant layer, based on the Schapery integral-type viscoelastic model. Second, FEA by using ABAQUS-UMAT subroutine is performed to implement the model based on the recursive algorithm, and the tensile load–displacement curve by FEA is compared with the experimental results of solid propellant. Finally, distributions of the stress, strain and damage variable with increasing displacement loads are obtained. It is shown that the viscoelastic damage feature of solid propellant can be represented by the developed model and numerical technique well.

Published
2020

7. Progression of proliferative glomerulonephritis with monoclonal IgG deposits in pediatric patients

Author

Richard K. Sibley, Neiha Arora, Andrew Y. Xiao, Neeraja Kambham, Amanda M Uber, Colin R. Lenihan, John P. Higgins, Zoltan Laszik, Megan L. Troxell, Vivek Charu, Vanderlene L. Kung, Vighnesh Walavalkar, Elizabeth M. Talley, Paul Miller, and Cynthia C. Nast

Subjects
Nephrology, medicine.medical_specialty, Pathology, Proteinuria, business.industry, Glomerular deposits, 030232 urology & nephrology, Renal function, Glomerulonephritis, 030204 cardiovascular system & hematology, medicine.disease, Transplantation, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Pediatrics, Perinatology and Child Health, Membranoproliferative glomerulonephritis, Monoclonal, medicine, medicine.symptom, business
Abstract

Proliferative glomerulonephritis with monoclonal IgG deposits (PGNMID) is a glomerular disease defined by non-organized glomerular deposits of heavy and light chain–restricted immunoglobulin and is rarely reported in children. We characterized a series of nine pediatric patients from two academic centers with biopsy-proven PGNMID and additionally describe two patients with monotypic IgG in the setting of IgM deposition. Each patient presented with hematuria and/or proteinuria; however, only five had elevated serum creatinine. Prodromal or concurrent infection was identified in six patients, low C3 in five, and alternate complement pathway gene variants in two. No monoclonal serum proteins were identified in five tested patients. Seven patients had monotypic deposits composed of IgG3-λ, two showed IgG3-κ, and one each IgG1 and IgG3 with lambda dominance in the setting of IgM deposition. The glomerular pattern was predominantly mesangial proliferative or membranoproliferative glomerulonephritis (MPGN). Treatment and outcomes were variable; four patients have recent PGNMID diagnoses and therefore minimal follow up, one had relatively stable kidney function for over a decade, and six experienced kidney failure, with four receiving transplants. Recurrent deposits of the same isotype were identified in five of six transplanted kidneys, corresponding to three of four transplanted patients. One of these patients developed PGNMID recurrences in three separate kidney allografts over a 20-year disease course. Our study emphasizes the need for upfront IgG subclass investigation in pediatric mesangial or MPGN with IgG deposition and monotypic or biased light-chain staining. Furthermore, this pediatric experience suggests expanded pathogenic considerations in PGNMID.

Published
2020

10. A review of experimental results on structural performance of reinforced recycled aggregate concrete beams and columns

Author

YeongAe Heo, Jinjun Xu, Y. Xiao, Simret Tesfaye Deresa, Zhi Li, Cristoforo Demartino, Deresa, S. T., Xu, J., Demartino, C., Heo, Y., Li, Z., and Xiao, Y.

Subjects
Materials science, Concrete beams, Aggregate (composite), seismic performance, compressive behavior, flexural behavior, business.industry, shear behavior, 0211 other engineering and technologies, 020101 civil engineering, reinforced recycled aggregate concrete, 02 engineering and technology, Building and Construction, Structural engineering, 0201 civil engineering, 021105 building & construction, business, Civil and Structural Engineering
Abstract

This article presents a comprehensive and critical review of the structural performances of reinforced recycled aggregate concrete beams and columns based on experimental results reported in the literature. Extensive data sets collected from the literature are categorized to investigate the effects on the local and global structural behavior. First, the flexural and shear response of reinforced recycled aggregate concrete beams is discussed. The structural performances are reviewed focusing on the main geometric and material variables such as the recycled concrete aggregate replacement ratio, the longitudinal reinforcement ratio, the transverse reinforcement ratio, and the shear span-to-depth ratio. Then, the behavior of reinforced recycled aggregate concrete columns under concentric and eccentric compressive loads and the seismic performance under low cyclic loading are discussed. The similarities and the differences between reinforced recycled aggregate concrete and reinforced natural aggregate concrete beams and columns are highlighted. The need for further research is pointed out at the end of the article. The results reported in this review clearly indicate that reinforced recycled aggregate concrete beams and columns with various recycled concrete aggregate replacement ratios have comparable or slightly lower structural performances to the reinforced natural aggregate concrete ones indicating the feasibility of recycled concrete aggregate for structural applications.

Published
2020

11. Successful management of anesthesia complications in a child with Crouzon syndrome

Author

Z Xu, Xin Wang, G Chen, and Y Xiao

Subjects
Male, medicine.medical_specialty, medicine.medical_treatment, Perioperative Care, Adenoidectomy, 03 medical and health sciences, 0302 clinical medicine, 030202 anesthesiology, medicine, Humans, Anesthesia, Tonsillectomy, business.industry, Craniofacial Dysostosis, Anesthesia complication, Tracheal intubation, Crouzon syndrome, 030208 emergency & critical care medicine, General Medicine, Perioperative, medicine.disease, Hypoplasia, Surgery, Airway Obstruction, Anesthesiology and Pain Medicine, Child, Preschool, Airway Extubation, Airway, business
Abstract

Crouzon syndrome (CS) is a rare autosomal dominant inherited disorder caused by mutations in the fibroblast growth factor receptor 2 (FGFR2) gene. The disease is characterized by premature fusion of the coronal and sagittal sutures of the skull, resulting in clinical manifestations of midfacial hypoplasia, shallow orbit, maxillary dysplasia, and occasional upper respiratory obstruction. This article presents the case of a child aged 2 years and 7 months with CS scheduled for bilateral tonsillectomy and adenoidectomy. The patient had a difficult procedure of extubation and was reintubated and the tracheal intubation was removed 2 days after surgery. The CS is a rare condition with physical characteristics that can result in difficult airway manipulation. It is important for anesthesiologists to recognize and avoid potential airway complications in the management of such patients through detailed preoperative evaluation and careful observation after surgery to reduce perioperative risks.

Published
2020

12. Ultrasonic excitation induced nanocrystallization and toughening of Zr46.75Cu46.75Al6.5 bulk metallic glass

Author

Wei Zhai, Tiantian Wang, Xidong Hui, B. Wei, Y. Xiao, and L.H. Nie

Subjects
Toughness, Amorphous metal, Materials science, Polymers and Plastics, business.industry, Mechanical Engineering, Ultrasound, Metals and Alloys, 02 engineering and technology, Plasticity, 010402 general chemistry, 021001 nanoscience & nanotechnology, Microstructure, 01 natural sciences, 0104 chemical sciences, Shear (sheet metal), Amplitude, Nanocrystal, Mechanics of Materials, Materials Chemistry, Ceramics and Composites, Composite material, 0210 nano-technology, business
Abstract

Intensive power ultrasound is introduced to Zr46.75Cu46.75Al6.5 bulk metallic glass (BMG) as an easy-procurable, non-destructive physical method to modulate its atomic rearrangement and shear deformation behavior. The microstructure after ultrasonic excitation with amplitude about 15 μm in 20 kHz for 2 h is characterized by large amount of Cu10Zr7 nanocrystals with size of 20–50 nm embedded in the glass matrix. This leads to a sharp increase in the critical stress for the first pop-in event of shear banding, and thus simultaneously improves both compressive plasticity and yield strength. Our findings provide a novel approach for overcoming the strength-ductility trade-off dilemma.

Published
2020

13. DATA QUALITY CHECK AND VISUAL ANALYSIS OF CORS STATION BASED ON ANUBIS SOFTWARE

Author

Y. Xiao, M. H. Yao, S. H. Tang, H. F. Liu, P. W. Xing, and Y. Zhang

Subjects
lcsh:Applied optics. Photonics, business.industry, Computer science, lcsh:T, media_common.quotation_subject, Real-time computing, Satellite constellation, lcsh:TA1501-1820, lcsh:Technology, Visualization, Software, lcsh:TA1-2040, Data quality, Quality (business), business, Anubis, lcsh:Engineering (General). Civil engineering (General), media_common
Abstract

Aiming at the observation data of CORS multi-mode data quality and inspection in CORS station, based on the observation data of a CORS station in Guilin, Guangxi, the paper used TEQC and Anubis software to check the data quality from data utilization, cycle slip ratio and multipath. The results show that the three quality inspection indicators of Anubis software are better than TEQC software, which proves that Anubis' data quality inspection results are effective and reliable. On this basis, using Anubis drawing tools to perform quality inspection and visual analysis from satellite constellation, signal band and observation data itself, it shows that Anubis' visual content is more elaborate than TEQC, and users can more intuitively understand and control the data quality of CORS station.

Published
2020

14. NON-CONTROLLED CLOSE-RANGE PHOTOGRAMMETRY METHOD BASED ON PHOTOMODELER SCANNER

Author

Yuli Zhang, C. C. Huang, S. H. Tang, Y. Xiao, and You Li

Subjects
lcsh:Applied optics. Photonics, Scanner, business.product_category, 010504 meteorology & atmospheric sciences, Computer science, business.industry, lcsh:T, 0211 other engineering and technologies, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, lcsh:TA1501-1820, 02 engineering and technology, 01 natural sciences, lcsh:Technology, Photogrammetry, Position (vector), lcsh:TA1-2040, Computer vision, Point (geometry), Artificial intelligence, business, lcsh:Engineering (General). Civil engineering (General), 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Digital camera
Abstract

Aiming at the high demand of close-range photogrammetry for the object control points and the inconvenient carrying of digital camera to take photogrammetry in the field, a method of detail survey based on PhotoModeler Scanner software is proposed. USB camera combines with the centering rod, USB camera captures image data, Total station obtains the coordinates of the centering rod, the coordinate of projective center is calculated by using the coordinate of the centering rod, PhotoModeler Scanner software processes image data and coordinate data. Ultimately, image stereo measurement of the no object control point was realized. The experimental results showed that the error of the plane position of the solved target point was less than 10cm at a shooting distance of about 10m, and it met the accuracy requirements of detail survey. Therefore, the method can reduce the workload of field detail survey, reduce the cost and volume of the photographic equipment, and has certain application value.

Published
2020

15. Modeling Nonstationary Non-Gaussian Hurricane Wind Velocity and Gust Factor

Author

M. Y. Xiao and H.P. Hong

Subjects
Meteorology, business.industry, Astrophysics::High Energy Astrophysical Phenomena, Mechanical Engineering, Gaussian, Building and Construction, Structural engineering, Wind speed, symbols.namesake, Gust factor, Mechanics of Materials, Wind gust, Physics::Space Physics, Turbulence kinetic energy, symbols, Astrophysics::Solar and Stellar Astrophysics, Environmental science, General Materials Science, business, Physics::Atmospheric and Oceanic Physics, Civil and Structural Engineering
Abstract

This study estimated the wind gust factor and turbulence intensity for hurricane winds that are modeled as a nonstationary non-Gaussian process. The estimation considered the time-varying m...

Published
2022

16. CNN-based few-mode fiber modal decomposition method using digital holography

Author

Y.-Y. Xiao, R.-M. Yao, and Z.-H. Zhu

Subjects
Physics, Optical fiber, Computer simulation, business.industry, Acoustics, Phase (waves), Physics::Optics, Atomic and Molecular Physics, and Optics, law.invention, Superposition principle, Modal, Amplitude, Optics, law, Normal mode, Electrical and Electronic Engineering, business, Engineering (miscellaneous), Digital holography
Abstract

Modal decomposition (MD) has become an indispensable analysis approach for revealing the modal characteristics of optical fibers. A new MD approach based on the convolutional neural network (CNN) is presented to retrieve the exact superposition of eigenmodes of few-mode fibers. Using the near-field beam intensity and phase patterns obtained from digital holography, not only the amplitude of each eigenmode but also the exact phase difference between the higher-order modes and the fundamental mode can be predicted. Numerical simulations validate the reliability and feasibility of the approach. When ten modes in the few-mode fiber are considered, the similarities of the intensity and phase pattern between the reconstructed fields and the given fields can achieve to 97.0% and 85.6%, respectively.

Published
2021

17. Latent class cluster analysis of knowledge on acute myocardial infarction symptoms and risk factors in community residents

Author

Y Liu, J Ma, N Zhang, J.-Y Xiao, J.-X Wang, X.-W Li, J Wang, Y Zhang, M.-D Gao, X Zhang, Y Wang, S.-B Xu, and J Gao

Subjects
medicine.medical_specialty, business.industry, Family medicine, medicine, Community resident, Myocardial infarction, Cardiology and Cardiovascular Medicine, Disease cluster, medicine.disease, business, Class (biology)
Abstract

Background Knowledge of Acute Myocardial Infarction (AMI) symptoms and risk factors (RF) have been studied worldwide in various populations. However, the studied specific symptom and RF of different surveys varies, the number of surveyed symptom and RF varies, and the criteria for judging good/high knowledge and bad/low knowledge are different (group classification criteria include the number, the percentages or the scores), which makes the results difficult to compare. Purpose The aim was to identify clusters of knowledge on symptoms and modifiable RFs using Latent Cluster Analysis, and to further compare characteristics and the awareness of the need for prompt treatment among different clusters. Methods A structured questionnaire was used to interview 4122 community residents over 35 years old on their knowledge about AMI symptoms and RFs. Latent GOLD Statistical Package was used to identify and classify the respondent subtypes (latent classes) of the knowledge on AMI symptoms or modifiable RFs. An individual's class membership probabilities are computed from the estimated model parameters and the observed scores. The multivariable logistic regression was performed in order to identify factors that predicted High knowledge membership. Results Two and three distinct clusters were identified in terms of knowledge of symptoms and RFs. 62.7% (Symptom High Knowledge Cluster) and 39.5% (RF High Knowledge Cluster) of the respondents were able to identify most symptoms and modifiable RFs. A number of common differences were observed with respect to higher probability of having high knowledge on symptom and RF, which was mostly better among those with higher education and average monthly income, insured, having annual physical examination, have disease history of AMI RFs, AMI history in immediate family member or acquaintance and have been exposed to AMI related public education. There was also significant difference in awareness of the prompt treatment in case of AMI occurs among different symptom or RF clusters. Conclusions A moderate or relatively low knowledge regarding AMI symptoms and modifiable RFs was observed in our study. Identification of Symptom or RF knowledge clusters can be a way to detect specific targeted groups that are most likely to possess lower knowledge of AMI with readily identifiable characteristics, which may facilitate health education and further reduce the pre-hospital delay and improve patient outcomes. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Key Project of Scientific and Technological Support Plan of Tianjin in 2020 Cluster category chartProfile plot

Published
2021

18. Public awareness of acute myocardial infarction symptoms and emergency response in community residents

Author

N Zhang, Yong Liu, Jianxun Wang, Peng Han, J Ma, Xu Zhang, Y.-N Yang, Y Zhang, S.-Y Zhao, Junzhi Wang, J Gao, M.-D Gao, X.-W Li, J.-Y Xiao, and Q.-X Zheng

Subjects
medicine.medical_specialty, Emergency response, business.industry, Emergency medicine, Medicine, Community resident, Myocardial infarction, Cardiology and Cardiovascular Medicine, business, medicine.disease, Public awareness
Abstract

Background Patient delay in seeking help has been reported to be a major factor that related to delay in care of acute myocardial infarction (AMI). Lack the knowledge of symptoms may translate to behavioral deficiencies which lead up to failing to seek medical assistant at early stage of AMI. Purpose The aim of present study is to investigate the awareness of AMI symptoms and the emergency responses among community residents over 35 years old. Methods The sample was proportionally distributed by age according to the national census data. The sex ratio was 1:1. The sample size is calculated according to the significance level of 0.05, the allowable error of 0.1, and the estimated Excellent awareness level of 10%. The final sample size is adjusted to 4200, considering non-response rate of 20%. Multi-stage stratified random sampling was used. On the first stage, two districts each in urban and rural regions were randomly selected. On the second stage, 3–10 community health service centers were randomly selected in each district. On the third stage, residents over 35 managed by the community health service center were proportionally sampled to be interviewed. A structured questionnaire was used and the survey was conducted in a face-to-face interview by clinical physicians. Logistic regression was applied to analyze factors related to Good knowledge. Results The top three symptom recognized by public is “pain or discomfort in the chest” (71.3%), followed by “difficulty breathing” (65.1%) and “pain or discomfort in the jaw, neck, or back” (60.9%). 85.0% chose to call an ambulance as first response when witness others having an AMI. Those who lives alone (OR=1.408; 95% CI, 1.005–1.972) and whose immediate family had been diagnosed with AMI (OR=1.510; 95% CI, 1.040–2.192) has better knowledge. A significant positive correlation was observed for those with hypertension (OR=1.199; 95% CI, 1.007–1.429), while a negative correlation was observed for those with diabetes (OR=0.788; 95% CI, 0.626–0.992). Public education could improve Good knowledge (OR=1.662; 95% CI, 1.388–1.990), while doctoral advise has been shown negative impact (OR=0.824; 95% CI, 0.691–0.984). Conclusions Our data provide first population-based estimates of public awareness in our country. Further promotional strategies to increase overall awareness in general public are seriously needed. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Major Science and Technology Projects of Tianjin Science and Technology Commission Multivariable logistic regression

Published
2021

19. Prognostic value of PCSK9 Levels in Non-ST elevation myocardial infarction patients undergoing percutaneous coronary intervention

Author

Yong Liu, M.-D Gao, N Zhang, X.-W Li, Yang Chen, Tingting Yao, J.-Y Xiao, Peng Han, J Gao, J Ma, Zhuang Cui, and Jiao Wang

Subjects
medicine.medical_specialty, business.industry, St elevation myocardial infarction, PCSK9, Internal medicine, medicine.medical_treatment, medicine, Cardiology, Percutaneous coronary intervention, Cardiology and Cardiovascular Medicine, business, Value (mathematics)
Abstract

Background The role of proprotein convertase subtilisin/kexin type 9 (PCSK9) in predicting major adverse cardiovascular events (MACEs) in Non-ST elevation myocardial infarction (NSTEMI) patients is still an open question and the PCSK9 concentration of clinical usefulness remains unknown in guiding treatment. Purpose To explore the role of PCSK9 in predicting major adverse cardiovascular events (MACEs) in Non-ST elevation myocardial infarction patients. Methods 272 patients with NSTEMI were included in our study, all patients received PCI therapy after admission. Patients were followed up for 1 year and MACEs were recored. Their baseline plasma PCSK9 levels were determined by ELISA. Patients were divided into high, medium and low PCSK9 groups and the associations of PCSK9 with other biomarkers and MACEs were evaluated. Results The results showed that PCSK9 levels was related to levels of lipoproteins, high-sensitivity C-reactive protein (r=0.162, P=0.008), platelet volume distribution width (r=0.299, P Conclusions In a NSTEMI setting, the concentration of PCSK9 is associated with hypercoagulability and hyper-inflammation. High levels of PCSK9 independently predict future MACEs in NSTEMI patients, particularly those classified by the GRACE score as high risk. Funding Acknowledgement Type of funding sources: None.

Published
2021

20. Experimental and numerical assessment of the thermal insulation performances of bamboo shear walls

Author

J.S. Wang, Y. Xiao, Cristoforo Demartino, Y Xiao, Z Li, K.W. Liu, Demartino, C., Xiao, Y., and Wang, J. S.

Subjects
Thermal transmittance, Bamboo, Hot box, Materials science, Thermal insulation, business.industry, Thermal resistance, Frame (networking), Shear wall, Composite material, business, Finite element method
Abstract

Four light frame shear walls representing one wood-based wall, one hybrid bamboo/wood-based wall and two full bamboo-based walls were studied by using a guard hot box testing apparatus to obtain the thermal resistance and thermal transmittance. The method proposed by ISO 6946 and the finite element method were used to analyze the thermal insulation performance of the light frame walls. The reliability of these two simulation methods was verified by comparison between them and with the experimental results. The results show that the thermal insulation performance of light frame bamboo and wood walls are similar allowing for the feasible substitution of wood by bamboo in real light frame constructions.

Published
2020

21. On the form of the Musmeci’s bridge over the Basento river

Author

Ivo Vanzi, Y. Xiao, Roberto Spagnuolo, Gabriele Candela, Francesco Marmo, Bruno Briseghella, Concetta Sulpizio, Luciano Rosati, Cristoforo Demartino, Marmo, F., Demartino, C., Candela, G., Sulpizio, C., Briseghella, B., Spagnuolo, R., Xiao, Y., Vanzi, I., Rosati, L., and Demartino, Cristoforo

Subjects
Musmeci, Computer science, 0211 other engineering and technologies, Shell (structure), 020101 civil engineering, 02 engineering and technology, Bending, 0201 civil engineering, Nonlinear programming, Stress (mechanics), 021105 building & construction, Civil and Structural Engineering, Force density, Form finding, business.industry, Bridge over the Basento river, Force density method, Optimal form, RC shell, UAV geometric survey, Structural engineering, Finite element method, Engineering design process, business, Geometric modeling
Abstract

The bridge over the Basento river in Potenza, Italy, designed by Sergio Musmeci, is supported by a continuous double-curvature RC shell optimized to reduce bending forces. This 300 m long bridge can be considered as a unique representative example of pioneering research on the design and construction of optimized structures. First, the design process employed for determining the form of the shell and the relevant constructive issues are described. A refined 3D geometric model of the shell is then obtained through an aerial survey carried out by a commercial UAV and a photogrammetric image-based reconstruction. A recent formulation of the Force Density Method allowing for non-isotropic stress state is exploited to numerically derive the form of the supporting shell; it is validated versus the surveyed geometry of the shell by employing a nonlinear optimization procedure in order to identify forces and stresses to be used as input parameters. Finally, the derived form of the shell is tested by a Finite Element analysis to verify its funicular efficiency, i.e., whether it is capable to withstand design loads by pure membrane actions.

Published
2019

22. Axial impact behaviors of stub concrete-filled square steel tubes

Author

Y. T. Zhang, Y. Xiao, and B. Shan

Subjects
High strain rate, Materials science, business.industry, Cyclic loading, Building and Construction, Structural engineering, LS-DYNA, business, Civil and Structural Engineering, Stub (electronics)
Abstract

Existing research on the widely used concrete-filled steel tubes is mainly focused on static or cyclic loading, and the studies on effects of high strain rate are relatively rare. In this article, seven stub concrete-filled steel tubular columns with square section were tested under both static and impact loads, using a large-capacity drop-weight testing machine. The research parameters were variable height of the drop-weight and different load types. The experimental results show that the failure modes of the concrete-filled steel tube columns from the impact tests are similar with those under static load, characterized by the local buckling of the steel tube. The time history curves of impact force and steel strain were investigated. The results indicate that with increasing impact energy, the concrete-filled steel tube stub columns had a stronger impact-resistant behavior. The dynamic analysis software LS-DYNA was employed to simulate the impact behaviors of the concrete-filled steel tube specimens, and the finite element results were reasonable compared with the test results. The parameter analysis on the impact behavior of concrete-filled steel tube columns was performed using the finite element model as well. A simple method was proposed to calculate the impact strength of square concrete-filled steel tube columns and compared favorably with experimental results.

Published
2019

23. Performance of connection system used in lightweight glubam shear wall

Author

Zheng Li, Y. Xiao, Ruipan Wang, and Shuaifei Wei

Subjects
Materials science, Yield (engineering), Deformation (mechanics), business.industry, Connection (vector bundle), 0211 other engineering and technologies, Stiffness, 020101 civil engineering, 02 engineering and technology, Building and Construction, Structural engineering, Displacement (vector), Finite element method, 0201 civil engineering, Structural element, 021105 building & construction, medicine, Shear wall, General Materials Science, medicine.symptom, business, Civil and Structural Engineering
Abstract

Industrial-produced laminated bamboo panel is a new type of eco-friendly material used for glubam structures in construction industry. This type of panel can be further cold-glued with different orientation combinations to form various types of glubam structural elements and to meet different structural and architectural requirements. The lightweight glubam frame structure is one of the popular forms of glubam structures which can be produced in factory and installed on site with few labor forces and transportation equipment, making it potentially possible to be widely used in urban or rural areas. Like the lightweight wood-frame structures, the governing structural element determining the lateral resistance capacity of lightweight glubam structures is the frame shear wall, as well as that the shear wall’s lateral resistance strength is determined through the metal connections used. Thus, this study is focused on the performance of connection system used in lightweight glubam shear walls made with thick strip ply-bamboo boards, the connection system includes panel-frame nail connections, frame-frame connections and hold-down devices, respectively. Yield moment and curves of nails used in lightweight glubam structures were experimentally obtained according to ASTM F1575 standard. The monotonic and cyclic loading tests of panel-frame connections and frame-frame connections with different nail connectors were performed following ASTM D1761 standard. Mechanical parameters (such as elastic stiffness ke, maximum force Fmax, ultimate displacement Δu) are obtained. Tests of hold-down connection with two different capacities under monotonic and cyclic loading are also presented in this research. A finite element model of lightweight shear wall based on metal connections information is validated through previous research in literature, and is used to predict the performance of lightweight frame shear walls with various combination of connections and studs, to find a suitable type of glubam or timber-glubam hybrid shear wall corresponding to certain load bearing and deformation requirements.

Published
2019

24. Abstract P4-13-08: Time to treatment discontinuation of second-line fulvestrant monotherapy for HR+/HER2− metastatic breast cancer in the real-world setting

Author

Patricia Luhn, TG Ton, Y Xiao, T Sanglier, Leisha A. Emens, C O'Hear, D Oliveri, A Hsieh, and J Chuo

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Fulvestrant, business.industry, medicine.medical_treatment, Cancer, Palbociclib, medicine.disease, Metastatic breast cancer, Discontinuation, Breast cancer, Refractory, Internal medicine, medicine, Hormone therapy, business, medicine.drug
Abstract

Background: Current treatment guidelines recommend sequential hormone therapy for patients with hormone receptor–positive (HR+) metastatic breast cancer (mBC) who are not in visceral crisis or who are not refractory to endocrine treatment. Second-line (2L) fulvestrant monotherapy is one option for patients with HR+ mBC that is human epidermal growth factor receptor 2 negative (HER2–) who progress on first-line (1L) treatment that may have included palbociclib. Using real-world data, we evaluated the differences in time to treatment discontinuation (TTD) of 2L fulvestrant monotherapy between groups of patients with HR+/HER2− mBC who did and did not receive 1L palbociclib. Methods: Using a Flatiron Health EHR-derived database, we examined TTD of 2L fulvestrant monotherapy among 188 patients who progressed on 1L endocrine therapy. Eligibility criteria included a confirmed diagnosis of HR+/HER2− mBC between 1 Jan 2015 and 31 Oct 2017 and treatment with single-agent fulvestrant in the 2L metastatic setting. 2L fulvestrant monotherapy treatment was considered discontinued if (1) third-line (3L) treatment was initiated, (2) death occurred within 60 days of the last administration of 2L fulvestrant monotherapy, or (3) the duration between last administration of 2L fulvestrant monotherapy and last visit date was ≥ 60 days. Patients who did not meet this definition were censored. TTD was defined as the time from the first to the last administration of 2L fulvestrant monotherapy, the day before the 3L start date, death date, or the end of study (30 Apr 2018), whichever came first.TTD was estimated by Kaplan-Meier methods and stratified by previous use of 1L palbociclib. Log-rank test was used to test for differences. Results: Overall, the median TTD of 2L fulvestrant monotherapy was 114 days (95% CI: 102, 127). For patients who previously received 1L palbociclib, the median TTD of 2L fulvestrant monotherapy was 102 days (95% CI: 85, 119) compared with 127 days (95% CI: 112, 141) for those who did not receive 1L palbociclib (log-rank P = 0.006). Patients who received 2L fulvestrant monotherapy and who had been previously treated with 1L palbociclib (n = 88) were more likely to be White (72.7% vs. 68.0%), younger (mean: 65.0 vs. 72.1 years), treated in an academic institution (9.1% vs. 4.0%), and experience longer median duration of 1L treatment (290.5 days vs. 211.0 days) compared with patients receiving 2L fulvestrant monotherapy who did not previously receive 1L palbociclib (n = 100). Conclusions: In general, half of patients on 2L fulvestrant monotherapy discontinued treatment in < 4 months. Patients who previously received 1L palbociclib had shorter TTD of 2L fulvestrant monotherapy. Our data identify a potential area of unmet medical need for patients with HR+/HER2− mBC who are treated with fulvestrant monotherapy in the 2L setting and who previously received 1L palbociclib. Further investigation is warranted to examine whether observed results are driven by endocrine resistance or by confounding, selection, or channeling effects of new drugs. Citation Format: Luhn P, O'Hear C, Ton TG, Sanglier T, Hsieh A, Oliveri D, Chuo J, Xiao Y, Emens L. Time to treatment discontinuation of second-line fulvestrant monotherapy for HR+/HER2− metastatic breast cancer in the real-world setting [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-13-08.

Published
2019

25. Experimental study on the behavior of mismatched butt welded joints of high strength steel

Author

Guo-Qiang Li, Ming-Ming Ran, Yan-Bo Wang, Amit Kanvinde, Fei-Fei Sun, and Robert Y. Xiao

Subjects
Digital image correlation, Materials science, business.industry, Metals and Alloys, High strength steel, 020101 civil engineering, 02 engineering and technology, Building and Construction, Structural engineering, Welding, Load carrying, Strength of materials, 0201 civil engineering, law.invention, Failure zone, 020303 mechanical engineering & transports, 0203 mechanical engineering, Mechanics of Materials, law, Hardening (metallurgy), Butt joint, business, Civil and Structural Engineering
Abstract

An experimental study on the load carrying capacity and deformation capacity of 108 mismatched butt welded joints of high strength steel (HSS) under tension load is performed, to investigate the strain distribution development over the specimen along the whole loading process by using digital image correlation technique (DIC). Three simplified hardness distribution patterns were identified based on the existence of hardened HAZ zone (HHZ) and softened HAZ zone (SHZ). For butt joints with Pattern I or Pattern II hardness distribution (92 specimens), the maximum load increases almost linearly with increasing values of mismatch ratio until mismatch ratio reaches 1.0, while for the specimens (42 specimens) with Pattern III hardness distribution, the strength are significantly lower than the estimated value from EC3, which shows the unsafety of EC3 with wide SHZ. In almost all the cases, mismatch (undermatch or overmatch) leads to a decrease in joint ductility because of strain localization inside the weaker zone, which varies depending on the failure location and the hardening properties in these failure zone. It is noted that the loss of material strength in SHZ can only be mitigated with thin SHZ due to the constraint provided by the unyielded adjacent material.

Published
2019

26. PI3Kγ (Phosphoinositide 3-Kinase-γ) Inhibition Attenuates Tissue-Type Plasminogen Activator–Induced Brain Hemorrhage and Improves Microvascular Patency After Embolic Stroke

Author

Jarvis Li, Adam Y. Xiao, Rong Jin, Min Wang, and Guohong Li

Subjects
Intracerebral hemorrhage, Endothelium, business.industry, 030204 cardiovascular system & hematology, Pharmacology, Blood–brain barrier, medicine.disease, Neuroprotection, Thrombosis, Tissue plasminogen activator, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, Internal Medicine, medicine, 030212 general & internal medicine, business, Stroke, Plasminogen activator, medicine.drug
Abstract

Genetic and pharmacological inhibition of the PI3Kγ (phosphoinositide 3-kinase-γ) exerts anti-inflammatory and protective effects in a number of inflammatory and autoimmune diseases. SHRs (spontaneously hypertensive rats) subjected to embolic middle cerebral occlusion were treated with AS605240 (30 mg/kg) at 2 or 4 hours, tPA (tissue-type plasminogen activator; 10 mg/kg) at 2 or 6 hours, or AS605240 at 4 hours plus tPA at 6 hours. Infarct volume, brain hemorrhage, neurological function, microvascular thrombosis, and cerebral microvessel patency were examined. We found that treatment with AS605240 alone at 2 hours or the combination treatment with AS605240 at 4 hours and tPA at 6 hours significantly reduced infarct volume and neurological deficits at 3 days after stroke compared with ischemic rats treated with saline, AS605240 alone at 4 hours, and tPA alone at 6 hours. Moreover, the combination treatment effectively prevented the delayed tPA-induced cerebral hemorrhage. These protective effects are associated with reduced disruption of the blood-brain barrier, reduced downstream microvascular thrombosis, and improved microvascular patency by AS605240. Inhibition of the NF-κB (nuclear transcription factor-κB)–dependent MMP (matrix metalloproteinase)-9 and PAI-1 (plasminogen activator inhibitor-1) in the ischemic brain endothelium may underlie the neurovascular protective effect of AS605240. In addition, the combination treatment significantly reduced circulating platelet P-selectin expression and platelet-leukocyte aggregation compared with ischemic rats treated with saline or tPA alone at 6 hours. In conclusion, inhibition of PI3Kγ with AS605240 reduces delayed tPA-induced intracerebral hemorrhage and improves microvascular patency, which likely contributes to neuroprotective effect of the combination treatment.

Published
2019

28. A Pilot Study on Cross-Laminated Bamboo and Timber Beams

Author

Y. Xiao, S. Y. Dong, and H. Cai

Subjects
Bamboo, business.industry, Mechanical Engineering, 0211 other engineering and technologies, Stiffness, 020101 civil engineering, Technical note, 02 engineering and technology, Building and Construction, Bending, Structural engineering, Slip (materials science), 0201 civil engineering, Flexural strength, Mechanics of Materials, 021105 building & construction, medicine, General Materials Science, medicine.symptom, business, Geology, Civil and Structural Engineering
Abstract

This technical note reports the results from a pilot testing program on the flexural behavior of cross-laminated bamboo and timber (CLBT) beams. The testing parameters include the combinati...

Published
2021

29. Accurate diagnosis of colorectal cancer based on histopathology images using artificial intelligence

Author

Joseph Luttrell, Weihua Zhou, J. Qi, Kuan-Song Wang, Y. Li, X. Fan, J. Huang, C. Zheng, Chong Wu, J. Li, K. Zhang, Gang Yu, L. Y. Huang, Hui Shen, L. Chen, X. Yan, Z. Song, Jeffrey Deng, Z. Li, S. Su, Q. Li, L. Shang, Bo-Yang Li, Jun-Ting Yang, Jun Wang, Chao Xu, R. Liu, Y. Gu, Y. Xiao, X. Zhou, H.M. Xiao, C. Liang, Z.C. Huang, Xiang Qiu, Z. Deng, Hong-Wen Deng, P. Tang, H. Ren, Chaoyang Zhang, Wen-Di Shen, D. Huang, Xiang-He Meng, Zhi Hu, Yu-Ping Wang, K. Ma, Hong-Mei Xiao, J.P. Yun, Z. C. Yang, S. C. Wang, Ru-Ping Quan, Jian Zhou, C. Yi, and W. Guo

Subjects
0301 basic medicine, medicine.medical_specialty, Colorectal cancer, lcsh:Medicine, Convolutional neural network, 03 medical and health sciences, 0302 clinical medicine, Cohen's kappa, Deep Learning, Artificial Intelligence, medicine, Humans, 030304 developmental biology, 0303 health sciences, Receiver operating characteristic, business.industry, Deep learning, lcsh:R, Cancer, Workload, Cancer diagnosis, General Medicine, medicine.disease, 3. Good health, Histopathology image, 030104 developmental biology, Pathology diagnosis, ROC Curve, 030220 oncology & carcinogenesis, Whole slide image, Histopathology, Artificial intelligence, Neural Networks, Computer, business, Colorectal Neoplasms, Research Article
Abstract

Background Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients’ treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. Methods Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany. Results Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. Conclusions This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

Published
2021

30. Deep Learning Auto-Segmentation Model for HN005 Contour Quality Assurance

Author

H. Geng, K. Men, Ping Xia, Sue S. Yom, and Y. Xiao

Subjects
Larynx, Cancer Research, Radiation, business.industry, Deep learning, Dice, Pattern recognition, Convolutional neural network, medicine.anatomical_structure, Oncology, Sørensen–Dice coefficient, Medicine, Radiology, Nuclear Medicine and imaging, Segmentation, Artificial intelligence, Pyramid (image processing), business, Quality assurance
Abstract

Purpose/Objective(s) Ensuring the quality of radiotherapy is essential for the successful conduct of clinical trials. The accurate delineation of organs at risks and targets compliance with protocol definitions is critical and historically time-consuming. We established a workflow utilizing deep learning-based AI auto-segmentation models for automated quality assurances (QA) for a head and neck multi-center clinical trial. Both in-house developed and commercially available AI models are tested. We report on the preliminary results. Materials/Methods Radiotherapy digital data of one-hundred-eighty-four patients enrolled in NRG-HN002 were used for this study. One-hundred-eighty-four CT and RT structures were reviewed and used for model training. Auto-segmentation models were trained for the mandible, brain stem, spinal cord, oral cavity, parotids, LarynxGSL, lips, esophagus submandibular glands, and pharynx with cascaded astrous convolution (CAC) and spatial pyramid pooling (SPP) module enhance convolutional neural networks (CNN). Twenty patients submitted to HN005 were selected for model testing to establish the QA workflow. AI (CNN) segmentation tools trained with separate sets of data from Mirada (DLCExpertTM) were also included in the testing process. Dice coefficient thresholds were established for detecting submitted segmentations with major variations with a 95% confidence interval. Results Both in-house and commercial auto-segmentations demonstrated high consensus; and, when compared with submitted segmentations, achieved a higher than 0.7 Dice similarity coefficient for the mandible, brain stem, spinal cord, parotid, and submandibular glands; higher than 0.5 dice for esophagus, oral cavity, larynx, and lips. Submitted segmentation with the dice coefficient lower than the established threshold often has missing slices, redundant slices, or erroneous overlapping with other structures. The detection specificity was found to be higher than 0.9. Due to the irregular shape of the pharynx and its overlapping with the target volume, the auto-segmentations have not achieved sufficient accuracy (with dice below 0.2). Conclusion Both commercial and in-house models demonstrate high specificity for submitted contour error detection for all the HN005 required OARs except for the pharynx. Comparison between AI and expert reviews will be included in future studies.

Published
2021

31. Can Omics Help in Prognostic Machine Learning Interpretability?

Author

Rich Caruana, C.Z. Uche, H. Geng, Christopher M. Wright, Y. Xiao, and S.H. Lee

Subjects
Cancer Research, Radiation, business.industry, Missing data, Omics, medicine.disease, Machine learning, computer.software_genre, Primary tumor, law.invention, Oncology, Randomized controlled trial, law, Feature (machine learning), Medicine, Radiology, Nuclear Medicine and imaging, Artificial intelligence, Personalized medicine, Stage (cooking), business, computer, Interpretability
Abstract

Purpose/Objective(s) This study aims to address a question on the potential role of omics in machine learning (ML) interpretability. Materials/Methods We performed a retrospective study to investigate the association between clinical features and overall survival (OS) in 778 patients with stage III or IV head and neck squamous cell carcinoma (HNSCC), who participated in the RTOG 0522 randomized trial, by using an interpretable ML model known as the Explainable Boosting Machine (EBM). By extracting and adding omics (radiomics and dosiomics) features to the clinical features, we attempted to determine the potential role of omics with respect to the interpretability of the ML model for predicting OS. Results The EBM model showed clear details of the contribution of each feature to OS prediction and supported the primary findings in RTOG 0522 that the primary tumor site, N2b-3 category, T4 tumor, smoking history ≥ 10 pack-years of cigarette, age > 50 years, and Zubrod performance status are strong predictors of poor OS. The interpretable model also predicted a 2-year survival with 69% and a 5-year survival with 72% in accuracy in the test dataset, despite not having certain critical features such as human papillomavirus status due to significant missing values. The performance of the EBM model for predicting 2-year and 5-year survival achieved the area under the curve of 0.69 and 0.73, respectively. When dosiomics information was added to the dose-volume histogram parameters, we observed a clearer trend in the model's explanations on risk scores for clinical features, illustrating that omics could promote the development of personalized medicine. Conclusion Our findings contribute to the evidence that the addition of omics in prognostic models can improve ML interpretability.

Published
2021

32. Acquisition and Management of Data for Translational Science in Oncology

Author

Y. Xiao, James Shen, Maryann Bishop-Jodoin, Sandra Kessel, Maria Giulia Cicchetti, Matthew Iandoli, Janaki Moni, Joel Saltz, Richard Hanusik, David S Followill, Fred W. Prior, Kathryn Karolczuk, Ameer L. Elaimy, Jeff Michalski, Ashish Sharma, Peter L. Lee, T.J. FitzGerald, Mark A. Rosen, Michael V. Knopp, and Fran Laurie

Subjects
0301 basic medicine, 03 medical and health sciences, medicine.medical_specialty, 030104 developmental biology, 0302 clinical medicine, business.industry, 030220 oncology & carcinogenesis, Medicine, Medical physics, Translational science, business
Abstract

Oncology clinical trials provide opportunity to advance care for patients with cancer. Bridging basic science with bedside care, cancer clinical trials have brought new and updated scientific knowledge at a rapid pace. Managing subject data in translation science requires a sophisticated informatics infrastructure that will enable harmonized datasets across all areas that could influence outcomes. Successful translational science requires that all relevant information be made readily available in a digital format that can be queried in a facile manner. Through a translational science prism, we look at past issues in cancer clinical trials and the new National Institutes of Health/National Cancer Institute initiative to address the need of database availability at an enterprise level.

Published
2021

33. Impact Behavior of Unbonded Post-Tensioned Concrete Beams

Author

Andrew Nghiem, Thomas H.-K. Kang, Cristoforo Demartino, Y. Xiao, Nghiem, A, Demartino, C, Xiao, Y, and Kang, Thk

Subjects
Materials science, Concrete beams, failure mechanism, business.industry, Failure mechanism, Building and Construction, Structural engineering, Impact test, reinforced concrete, Reinforced concrete, unbonded post-tensioning, Service life, impact test, business, dynamic response, Civil and Structural Engineering
Abstract

This study experimentally investigates the effects of the unbonded post-tensioning on the response of reinforced concrete (RC) beams under impact loads. A total of fifteen specimens were cast and tested. All specimens had identical longitudinal reinforcement, but varying shear rein forrement ratios designed to be both flexural-and shear-deficient in static conditions according to the ACI code. In particular; thirteen unbonded post-tensioned (PT) beams were tested under drop weight impact applied at the midspan in simply supported conditions and compared with conventional type RC beams. The main variables investigated include increasing levels of PT force and the application of two different impact energies per each specimen type, shear- or flexural-deficient. The experimental results showed that the levels of PT force and shear reinforcements of the specimens played an important role in their overall behavior: With respect to beneficial design recommendations, relationships between the impact resistance and the static capacity are provided; a general increase in strength of around three times that of the static capacity is observed when impacted. Additionally, relationships between the ratio of the impact energy to static capacity are developed with regard to the maximum and residual member displacements.

Published
2021

35. Experimental studies on glubam columns under axial compression

Author

F.Z. Chu, X.H. Lv, Y. Xiao, and S.C. Zhou

Subjects
Structural material, Materials science, business.industry, Building and Construction, Structural engineering, symbols.namesake, Buckling, Mechanics of Materials, Axial compression, Architecture, Glued laminated timber, Tangent modulus, Euler's formula, symbols, Safety, Risk, Reliability and Quality, business, Failure mode and effects analysis, Column design, Civil and Structural Engineering
Abstract

Glubam is a new type of structural material or bamboo based glulam. Understanding the compressive performance of glubam columns under axial compression is crucial for its application in construction field. Experimental and analytical investigations were conducted to study the mechanical performance of 45 columns fabricated by two types of glubam with different slenderness ratios. The failure modes in terms of various slenderness ratios were reported and evaluated: strength failure was the main failure mode of the short columns while buckling was typically observed for long and slender columns. For the intermediately slender columns, buckling was also accompanied by the material damage. The experimental results were compared with the column design curves specified in Chinese, American and European timber structural design codes for glued laminated timber, showing all the codes can provide adequately conservative prediction to the test results. Euler's equation, Newlin-Gahagan approach, Yoshihara et al.’s approach and tangent modulus theory were adopted to analyze the critical buckling of the columns under both elastic and inelastic conditions. A model is proposed to explain the buckling of intermediate glubam columns with partial splitting.

Published
2022

36. A case study in bamboo construction education: The experience of the Sino-Italian 'bamboo pavilion contest-A contest for a pavilion in bamboo technology'

Author

Y. Xiao, A. De Capua, Cristoforo Demartino, M. Tornatora, Z. Li, Y Xiao, Z Li, K.W. Liu, De Capua, A., Tornatora, . M., Demartino, C., Li, Z., and Xiao, Y.

Subjects
Engineering, Bamboo, business.industry, media_common.quotation_subject, Pavilion, CONTEST, Bamboo construction, Ceremony, Technical design, Visual arts, Exhibition, China, business, media_common
Abstract

This manuscript summarizes the experience of the Sino-Italian “Bamboo #Pavillon Contest_A contest for a Pavilion in Bamboo Technology” held between the Mediterranea University of Reggio Calabria (Italy) and the College of Civil Engineering of Nanjing Tech University (China) in 2018. The contest for the pavilion to be realized with bamboo technology was divided into three phases. The first one was aimed at identifying the best project idea among those presented from students of Mediterranea University of Reggio Calabria. The second phase was comprised of both the technical design and the construction of the bamboo pavilion by the students of Nanjing Tech University. The last phase consisted in the closing ceremony of the contest held at the Zhejiang University - University of Illinois at Urbana Champaign Institute. Particularly, the goal was the design of a temporary exhibition pavilion to be realized with bamboo structures, such as GluBam, an eco-sustainable building material also light and flexible but solid and resistant. The bamboo pavilion was realized and completed during the summer of 2018 and now it is a good example of a temporary structure made of engineered bamboo.

Published
2019

37. Assessing adherence to objective disease monitoring and outcomes with adalimumab in a real-world IBD cohort

Author

Jonathan Wyse, Andrew Szilagyi, Polymnia Galiatsatos, Albert Cohen, R Kohen, A. Al Khoury, Waqqas Afif, Alain Bitton, Gad Friedman, Peter L. Lakatos, Nir Hilzenrat, Petra Anna Golovics, Talat Bessissow, Y Xiao, and Gary Wild

Subjects
Adult, Male, medicine.medical_specialty, Adolescent, Disease, Kaplan-Meier Estimate, Medication Adherence, 03 medical and health sciences, Feces, Young Adult, 0302 clinical medicine, Crohn Disease, Internal medicine, medicine, Adalimumab, Humans, Retrospective Studies, Crohn's disease, Hepatology, business.industry, Gastroenterology, Disease monitoring, Middle Aged, medicine.disease, Ulcerative colitis, C-Reactive Protein, Treatment Outcome, 030220 oncology & carcinogenesis, Cohort, Biomarker (medicine), 030211 gastroenterology & hepatology, Colitis, Ulcerative, Female, Calprotectin, Drug Monitoring, business, Leukocyte L1 Antigen Complex, Biomarkers, medicine.drug
Abstract

Background Data suggests that tight objective monitoring may improve clinical outcomes in IBD. Aim To assess the adherence to serial tight objective monitoring(clinical and biomarkers) and its effect on clinical outcomes. Methods We retrospectively reviewed the chart of 428 consecutive IBD patients started on adalimumab between January 1,2015–January 1,2019 [338 Crohn's disease(CD), 90 ulcerative colitis(UC)]. Clinical symptoms(assessed by Harvey-Bradshaw-Index,partial Mayo),C-Reactive Protein(CRP), and fecal calprotectin(FCAL) assessments were captured at treatment initiation and at 3,6,9, and12 months. Dose optimization and drug sustainability curves were plotted by Kaplan-Meier method. Results Clinical evaluation was available in nearly all patients at 3(CD-UC:95–94%), 6(90–83%), 9(86–85%) and 12(96–89%) months. CRP testing frequency decreased in CD patients over time. Compliance to serial FCAL testing was low. Clinical remission at one-year was higher in patients adherent to early assessment visit at 3 months(p = 0.001 for CD and UC). Adherence to early follow-up resulted in earlier dose optimization in CD and UC patients(pLogrank=0.026 for UC & p = 0.09 for CD). Overall drug sustainability did not differ. Conclusion Clinical & CRP, but not FCAL, were frequently assessed in patients starting adalimumab. Adherence to early objective combined follow-up visits resulted in earlier dose optimization, improved one-year clinical outcomes but did not change drug sustainability.

Published
2020

38. Remote Digital Psychiatry: MindLogger for Mobile Mental Health Assessment and Therapy

Author

Michael P. Milham, Joel Swendsen, K. Konishcheva, A. Badioli, Kathleen R. Merikangas, N. Acuna, W. Van Auken, I. Sabram, Jon Clucas, Arno Klein, Sanu Ann Abraham, Anirudh Krishnakumar, H. Rossiter, A. Keshavan, B. Thonet, S. Semenuta, Lindsay Alexander, Ariel B. Lindner, Satrajit S. Ghosh, and Y. Xiao

Subjects
education.field_of_study, End user, Computer science, business.industry, Population, Psychological intervention, Mental health assessment, computer.software_genre, Mental health, World Wide Web, Software deployment, Health care, Web application, education, business, Java applet, computer, Mobile device, Healthcare system
Abstract

BackgroundUniversal access to assessment and treatment of mental health and learning disorders remains a significant and unmet need. There is a vast number of people without access to care because of economic, geographic, and cultural barriers as well as limited availability of clinical experts who could help advance our understanding of mental health.ObjectiveTo create an open, configurable software platform to build clinical measures, mobile assessments, tasks, and interventions without programming expertise. Specifically, our primary requirements include: an administrator interface for creating and scheduling recurring and customized questionnaires where end users receive and respond to scheduled notifications via an iOS or Android app on a mobile device. Such a platform would help relieve overwhelmed health systems, and empower remote and disadvantaged subgroups in need of accurate and effective information, assessment, and care. This platform has potential to advance scientific research by supporting the collection of data with instruments tailored to specific scientific questions from large, distributed, and diverse populations.MethodsWe conducted a search for tools that satisfy the above requirements. We designed and developed a new software platform called “MindLogger” that exceeds the above requirements. To demonstrate the tool’s configurability, we built multiple “applets” (collections of activities) within the MindLogger mobile application and deployed several, including a comprehensive set of assessments underway in a large-scale, longitudinal, mental health study.ResultsOf the hundreds of products we researched, we found 10 that met our primary requirements above with 4 that support end-to-end encryption, 2 that enable restricted access to individual users’ data, 1 that provides open source software, and none that satisfy all three. We compared features related to information presentation and data capture capabilities, privacy and security, and access to the product, code, and data. We successfully built MindLogger mobile and web applications, as well as web browser-based tools for building and editing new applets and for administering them to end users. MindLogger has end-to-end encryption, enables restricted access, is open source, and supports a variety of data collection features. One applet is currently collecting data from children and adolescents in our mental health study, and other applets are in different stages of testing and deployment for use in clinical and research settings.ConclusionsWe have demonstrated the flexibility and applicability of the MindLogger platform through its deployment in a large-scale, longitudinal, mobile mental health study, and by building a variety of other mental health-related applets. With this release, we encourage a broad range of users to apply the MindLogger platform to create and test applets to advance health care and scientific research. We hope that increasing availability of applets designed to assess and administer interventions will facilitate access to health care in the general population.

Published
2020

39. Imaging and Neuro-Oncology Clinical Trials of the National Clinical Trials Network (NCTN)

Author

Matthew Iandoli, Jeff Michalski, Richard Hanusik, Maryann Bishop-Jodoin, Mark A. Rosen, Kathryn Karolczuk, Fred W. Prior, M. Giulia Cicchetti, Michael V. Knopp, Sandra Kessel, Y. Xiao, Ashish Sharma, David S Followill, Fran Laurie, Janaki Moni, Joel Saltz, and T.J. FitzGerald

Subjects
Clinical trial, medicine.medical_specialty, business.industry, Neuro oncology, Medicine, Medical physics, business
Published
2020

40. Models for Acute on Chronic Liver Failure Development and Mortality in a Veterans Affairs Cohort

Author

David E. Kaplan, Karen Y Xiao, Rebecca A. Hubbard, Nadim Mahmud, David S. Goldberg, and Tamar H. Taddei

Subjects
Male, medicine.medical_specialty, Concordance, Logistic regression, Sensitivity and Specificity, Article, Cohort Studies, 03 medical and health sciences, Liver disease, 0302 clinical medicine, Risk Factors, Internal medicine, medicine, Humans, Veterans Affairs, Aged, Retrospective Studies, Veterans, Hepatology, Receiver operating characteristic, business.industry, Acute-On-Chronic Liver Failure, Retrospective cohort study, Middle Aged, Models, Theoretical, medicine.disease, United States, ROC Curve, 030220 oncology & carcinogenesis, Cohort, 030211 gastroenterology & hepatology, Female, business
Abstract

The diagnosis of acute on chronic liver failure (ACLF) carries a high short-term mortality, making early identification of at-risk patients crucial. To date, there are no models that predict which patients with compensated cirrhosis will develop ACLF, and limited models exist to predict ACLF mortality. We sought to create novel risk prediction models using a large North American cohort. We performed a retrospective study of 75,922 patients with compensated cirrhosis from the Veterans Outcomes and Costs Associated with Liver Disease (VOCAL) dataset. Using 70% derivation/30% validation sets, we identified ACLF patients using the Asian Pacific Association of Liver (APASL) definition. Multivariable logistic regression was used to derive prediction models (called VOCAL-Penn) for developing ACLF at 3, 6, and 12 months. We then created prediction models for ACLF mortality at 28 and 90 days. The VOCAL-Penn models for ACLF development had very good discrimination [concordance (C) statistics of 0.93, 0.92, and 0.89 at 3, 6, and 12 months, respectively] and calibration. The mortality models also had good discrimination at 28 and 90 days (C statistics 0.89 and 0.88, respectively), outperforming the Model for End-stage Liver Disease (MELD), MELD-sodium, and the APASL ACLF Research Consortium ACLF scores. We have developed novel tools for predicting development of ACLF in compensated cirrhosis patients, as well as for ACLF mortality. These tools may be used to proactively guide patient follow-up, prognostication, escalation of care, and transplant evaluation. Receiver operating characteristic (ROC) curves for predicting development of APASL ACLF at 3 months (a), 6 months (b), and 1 year (c)

Published
2020

41. Post-Earthquake Fire Resistance of Circular Concrete-Filled Steel Tubular Columns

Author

J. He, Sashi K. Kunnath, Y. Xiao, and Junhua Wang

Subjects
business.industry, Mechanical Engineering, 0211 other engineering and technologies, 020101 civil engineering, 02 engineering and technology, Building and Construction, Structural engineering, 0201 civil engineering, Mechanics of Materials, 021105 building & construction, General Materials Science, Fire resistance, business, Seismic resistance, Geology, Civil and Structural Engineering
Abstract

An experimental study was conducted to investigate the mechanical behavior and residual capacity of concrete-filled steel tubular (CFST) columns subjected to a post-earthquake fire. Nine ci...

Published
2020

44. Design Embedment Strength of Plybamboo Panels Used for GluBam

Author

Y. Xiao, Zhi Li, Giorgio Monti, Jinyuan Zhang, and Rui Wang

Subjects
Bamboo, Materials science, Embedment, business.industry, 0211 other engineering and technologies, 020101 civil engineering, 02 engineering and technology, Building and Construction, Structural engineering, 0201 civil engineering, Mechanics of Materials, 021105 building & construction, General Materials Science, business, Design values, Civil and Structural Engineering
Abstract

The embedment behavior of plybamboo panels under dowel-type connections used for glued, laminated bamboo (GluBam) structures, was experimentally studied, following the half-hole loading met...

Published
2020

45. Volume IV The DUNE far detector single-phase technology

Author

L. Di Giulio, J. Martin-Albo, S. Ravat, W. Mu, D. Marfatia, T. Kosc, D. Autiero, Poonam Mehta, A. Borkum, N. McConkey, G. Karagiorgi, Robert Wilson, L. M. Cremaldi, Stephen P. Gent, T. Young, Julián Félix, D. MacFarland, Andrew Smith, M. Manrique Plata, J. Freestone, D. Rivera, B. Stillwell, Marco Verzocchi, A. Lambert, Orlando L. G. Peres, K. Gollwitzer, E. Kemp, G. Yang, I. Kreslo, F. Varanini, M. Chalifour, A. Holin, S. J. Patton, R. J. Nichol, Giovanni Bellettini, V. A. Kudryavtsev, M. Sorel, E. Church, S. Kasai, H. O. Back, A. Lister, S. Santana, C. Mariani, Carlos Escobar, J. C. Freeman, Kaushik De, M. J. Rodriguez Alonso, M. A. Acero, A. Christensen, G. S. Varner, S. Sacerdoti, D. Shooltz, Seodong Shin, M. Santos-Maldonado, T. Schaffer, Jeremy Wolcott, J. Vasel, J. A. Gonzalez-Cuevas, J. Franc, C. Mossey, Jonas Rademacker, G. P. Zeller, Joshua Barrow, John Marshall, Alessandro Thea, H. A. Tanaka, W. C. Louis, E. Hazen, Armin Karcher, D. Smargianaki, Christopher L. Marshall, M. Soderberg, A. C. Weber, Christopher J. Milne, E. Brianne, A. Aranda-Fernandez, J. Calcutt, K. Warburton, M. Nalbandyan, Dave Sankey, J. Asaadi, F. Diaz, E. Valencia, B. Kirby, A. Bross, K. Koehler, M. A. Uchida, Y. Bezawada, D. Warner, C. E. Thorn, Srubabati Goswami, Z. Williams, Gregory Iles, A. Friedland, K. M. Heeger, V. P. Luzio, G. C. Blazey, J. Barranco Monarca, Carl Grace, A. M. Gago, E. James, M. Newcomer, H. W. Sobel, Roberto Gutiérrez, C. Vignoli, R. Hatcher, M. Zhao, F. Cavalier, M. A. Hernandez Morquecho, N. Poonthottathil, Ara Ioannisian, W. Metcalf, T. Wongjirad, H. T. Rakotondramanana, D. Cherdack, M. A. Ramirez Delgado, R. Diurba, G. Christodoulou, S. Calvez, T. Durkin, H. Y. Wei, M. Muether, S. Roy, A. Caminata, A. Scarpelli, Christopher Brew, Pavel Snopok, Y. Rigaut, L. Escudero Sanchez, K. Kothekar, W. Flanagan, V. Papadimitriou, S. J. Brice, Nicolas Lurkin, M. V. Diwan, Andrew White, S. Berkman, H. Muramatsu, Z. Pavlovic, A. A. Machado, Christian Farnese, A. Mastbaum, Alfredo G. Cocco, G. Zhu, S. Centro, S. Henry, J. Rout, P. de Jong, H. Carranza, Milos Lokajicek, K. Nishimura, A. Delbart, N. J. C. Spooner, C. McGrew, E. Pantic, Mario Campanelli, David Cussans, B. T. Fleming, K. Negishi, F. Spagliardi, J. Nesbit, André Rubbia, Akitaka Ariga, Marvin L Marshak, F. Pietropaolo, F. D. M. Blaszczyk, T. Hasegawa, Kate Scholberg, O. Gogota, R. Poling, Simon Jones, A. Tonazzo, M. P. Andrews, R. Petti, S. Bertolucci, M. Bonesini, A. F. Moor, C. Barnes, A. S. Hesam, S. H. Kettell, M. Bongrand, M. R. While, D. J. Payne, C. Gotti, A. Chiriacescu, Paul Keener, Leigh H. Whitehead, James Stewart, A. Mazzacane, L. W. Koerner, T. Rehak, C. Andreopoulos, F. Terranova, Jaroslaw Pasternak, E. Raguzin, L. C. J. Rice, J. L. Bazo Alba, S. Li, J. Hartnell, M. Potekhin, N. Moggi, D. J. Summers, J. Berger, L. Cremonesi, Katsuya Yonehara, T. E. Coan, Claire Shepherd-Themistocleous, B. Radics, Karol Hennessy, S. Söldner-Rembold, C. S. Lin, L. Greenler, B. Guo, Frank Filthaut, R. B. Patterson, E. Pennacchio, E. Zhivun, C. Cuesta, T. Loew, G. Prior, D. Duchesneau, Lina Necib, S. Rescia, W. Gu, Andrés Castillo, N. Kazaryan, O. G. Miranda, C. Patrick, Robert Shrock, José W. F. Valle, J. Reichenbacher, D. A. Sanders, John F. Beacom, S. Tufanli, S. Ventura, Riccardo Papaleo, J. Zennamo, A. De Roeck, M. Calin, P. Ding, Alessandro Menegolli, B. V. K. S. Potukuchi, T. Le, T. Wachala, L. O. Arnold, J. R. Macier, A. M. Teklu, E. Blucher, L. Hertel, F. W. Sippach, S. Childress, T. Miao, P. Fernandez Menendez, J. Han, R. Gandrajula, C. Y. Chi, Marzio Nessi, Aldo Penzo, Ina Sarcevic, Kendall Mahn, Jorge Molina, F. Bonini, Eric W. Hoppe, M. Groh, Barry King, R. Mazza, Keith Rielage, Patrick Dunne, M. Mellinato, D. Lorca, R. Guenette, F. Bento Neves, L. Pickering, Manuel Alejandro Segura Delgado, J. J. Russell, H. R. Gallagher, J. Zuklin, Steven Gardiner, P. Madigan, D. Douglas, Daniel Gastler, S. Manly, P. Hamilton, L. Montaño Zetina, R. G. Van de Water, S. Dennis, M. Tenti, N. Dokania, Kim Siyeon, E. Fernandez-Martinez, P. P. Koller, D. Whittington, T. Li, M. C. Sanchez, S. Biagi, C. Sarasty, Juraj Bracinik, A. N. Khotjantsev, N. Tsverava, Yasaman Farzan, M. Tzanov, J. G. Boissevain, J. Smolik, Andrew Brandt, J. Hoff, D. A. Harris, C. Distefano, Ornella Palamara, H. S. Budd, Alastair Grant, A. K. Giri, Thorsten Lux, C. E. Lane, J. Marteau, Irakli Lomidze, E. Kearns, Zviad Tsamalaidze, L. S. Gomez Fajardo, H. da Motta, J. S. Real, Sukalyan Chattopadhyay, B. Viren, J. Mousseau, Ihn Sik Seong, C. M. Sutera, A. C. Ezeribe, F. Ferraro, Marco Adinolfi, Nikolaos Simos, A. Stuart, D. Brailsford, N. Solomey, Laura Manenti, L. V. Gomez Bermeo, Andrea Zani, Kristian Harder, Timothy M. Shaw, J. Hewes, Sandro Palestini, D. Braga, D. Garcia-Gamez, J. Stock, S. Bolognesi, D. Belver, Laura Paulucci, J. Ahmed, Narendra Sahu, Sandip Pakvasa, L. Pasqualini, D. Mladenov, M. Kordosky, S. Zucchelli, L. Stanco, M. Torti, B. Jargowsky, E. Smith, C. J. Solano Salinas, N.V. Mokhov, D. Vanegas Forero, C. Jesús-Valls, Andrew Blake, L. Jiang, F. Andrianala, W. Ketchum, Matthaeus Leitner, K. Fahey, Marco Pallavicini, Bindu A. Bambah, K. Francis, M. H. Shaevitz, N. Barros, I. Caro Terrazas, R. Itay, G. Sirri, H. Steiner, Laura Dominé, S. Lockwitz, G. Savage, N. Bostan, J. A. Nowak, A. Scarff, Konstantinos Manolopoulos, R. K. Plunkett, B. Morgan, A. Rafique, Cari L. Johnson, M. Parvu, L. Patrizii, James A. Anderson, L. Corwin, A. Hourlier, S. L. Mufson, S. Martynenko, V. J. Guarino, B. Carlus, D. Boyden, F. Marinho, David Delepine, J. Bremer, Paola Sala, P. Cotte, J.V. Dawson, G. Mandrioli, O. Goodwin, Jitendra Kumar, Ph. Lebrun, J. Soto-Oton, K. K. Guthikonda, Evgueni Goudzovski, Gabriella Carini, S. Gao, M. Dabrowski, Sudarshan Paramesvaran, G. Pessina, S. Davini, R. L. Talaga, Francesco Gonnella, A. Joglekar, G. Sinev, S. Gwon, A. Surdo, M. O. Wascko, R. Bajou, Pedro A. N. Machado, Massimo Rossella, G. S. Davies, I. De Bonis, K. S. McFarland, C. T. Macias, T. Alion, O. V. Mineev, M. Bishai, R. Northrop, Chao Zhang, R. Van Berg, L. Di Noto, Kam-Biu Luk, J. Chaves, J. Wang, K. Qi, W. E. Sondheim, Sergei Striganov, B. Paulos, Janice L. Thompson, M. Rai, P. N. Ratoff, T. Kutter, D. Totani, J. A. B. Coelho, F. Stocker, T. Gamble, J. J. Grudzinski, I. Gil-Botella, T. Yang, Wayne A. Barkhouse, C. E. Tull, H. Mendez, Z. Ghorbani-Moghaddam, Y.-J. Jwa, F. Cavanna, F. Kamiya, V. Basque, R. Sipos, V. Bellini, C. Alt, Sandhya Choubey, B. Abi, A. Mefodiev, V. A. Kostelecky, A. L. Renshaw, Giuseppe Benedetto Cerati, S. Balasubramanian, M. Biassoni, D. Pershey, J. Maricic, K. Lande, A. Muir, L.S. Rochester, A. Papanestis, A. Aurisano, F. Bay, R. Nandakumar, T. L. Usher, Bo Yu, A. V. Waldron, A. Filkins, Y. Cui, P. A. Rodrigues, Daijin Kim, G.D. Barr, Junwei Huang, V. De Romeri, H.E. Rogers, Andrea Dell'Acqua, A. Cervera Villanueva, Robert Svoboda, Yu. Onishchuk, T. Hamernik, A. P. Furmanski, M. Wetstein, P.T. Smith, G. Brunetti, Mariam Tórtola, Matthew L Strait, G. Barenboim, P. Guzowski, J. D. Eisch, N. Gallice, D. Newhart, A. J. Roeth, H. Berns, E. Granados, A. Weinstein, A. Falcone, D. Caratelli, L. Bellantoni, Wei Wu, J. Mills, A. Hackenburg, D. Caiulo, Chia-Chan Chang, Dave M Newbold, C. K. Jung, F. Krennrich, G. Testera, S. Rosauro-Alcaraz, A. Sitraka, L. Bagby, J. M. LoSecco, S. Tariq, C. Mauger, J. J. Back, J. Yu, R. Acciarri, B. Behera, P. Lasorak, Karol Lang, Irina Mocioiu, H. Schellman, Han Wang, Sergey A. Kulagin, A. Bashyal, Beatriz B. Siffert, C. N. Booth, L. Zambelli, M. T. Graham, A. Mann, Rakesh Kumar, Y. Xiao, Gregory J Pawloski, T. Prakash, Arsen Khvedelidze, A.S. Dyshkant, Paolo Carniti, C. Rubbia, M. Reggiani-Guzzo, M. M. Khabibullin, D. Wenman, S. C. Timm, R. Sharma, R. Saakyan, Marcelo M. Guzzo, P. Baesso, M. Pozzato, T. R. Junk, C. Morris, A. Cervelli, A. Heavey, Grzegorz Deptuch, M. Á. García-Peris, B. Bhuyan, M. Kabirnezhad, Pierre Baldi, M. Mooney, E. Tyley, A. Hahn, V. Susic, S. D. Reitzner, M. P. Decowski, V. Galymov, E. Chardonnet, B. R. Littlejohn, B. Ramson, B. Russell, M. Vagins, L. Fields, V. Zutshi, Sandeep Miryala, Enrique Calvo, V. Radeka, P. Debbins, J. Sinclair, B. Bilki, C. Touramanis, J. I. Crespo-Anadón, J. M. Paley, Antonio Ereditato, N. Yershov, C. J. Densham, D. W. Schmitz, A. Gallego-Ros, N. Buchanan, N. Mauri, A. Lawrence, K. Cho, S. Narita, X. Luo, A. Booth, D. A. Dwyer, S. Prince, J. Haiston, Jianbei Liu, T. J. Langford, E. Gamberini, Matheus Hostert, Dario Gnani, P. Vahle, G. A. Horton-Smith, A. Marchionni, I. K. Furic, John Matthews, K. Mason, M. Bhattacharjee, Randall P. Johnson, Amelia Maio, E. Motuk, C. Castromonte, Paolo Calafiura, Q. David, T. Miedema, S. Magill, Z. Ahmad, John Evans, Yi Chen, E. Ewart, S. Gollapinni, K. V. Tsang, J. Maneira, R.A. Rameika, A. de Gouvea, M. A. Vermeulen, R. M. Berner, J. J. De Vries, S. Shafaq, L. Da Silva Peres, A. McNab, G. Vasseur, A. Verdugo, C. Petta, Kenneth Long, H. S. Chen, K. Mavrokoridis, M. J. Dolinski, Yu. Kudenko, D. Gratieri, Alexandru Jipa, J. R. T. de Mello Neto, Olga Beltramello, J. T. Haigh, B. Gelli, Gregory J. Michna, A. M. Iliescu, Alex Reynolds, K. Biery, Yanchu Wang, V. Aushev, J. Zalesak, L. Simard, Ionel Lazanu, L. Pagani, J. Rodriguez Rondon, Alec Habig, M. Nebot-Guinot, R. Illingworth, G. Petrillo, J. S. Díaz, P. Novella, K. Grzelak, A. Gendotti, A. Himmel, M. Rajaoalisoa, P. Bour, L. Mualem, D. Pugnere, E. Niner, C. A. Moura, A. D. Marino, S. Bordoni, James Mueller, W. Fox, Jordan Ott, Niki Saoulidou, M. Oberling, E. Mazzucato, Silvia Pascoli, K. Herner, Hem Raj Sharma, M. Betancourt, T. Lord, L. Zazueta, Alexander Deisting, B. Rebel, Joleen Pater, David H. Adams, I. L. De Icaza Astiz, Stefan Antusch, M. Worcester, A. Higuera Pichardo, C. Kuruppu, Janet Conrad, Z. Parsa, Francesco Tortorici, L. Suter, J. Moon, P. E. L. Clarke, C. Palomares, Sofia Andringa, F. Jediny, J. Urheim, D. Montanari, Giorgio Riccobene, A. Rappoldi, J. Migenda, S. Matsuno, Y. Karyotakis, Jürgen Pozimski, Artur M. Ankowski, D. Edmunds, T. Safford, E. Tatar, Utku Kose, Z. Djurcic, D. Vargas, C. Wret, F. Sergiampietri, Rex Tayloe, F. Barao, I. Rakhno, Rukmani Mohanta, Andrew Norman, V. N. Solovov, X. Pons, V. Paolone, V. Pec, J. Pillow, S. Vergani, V. Savinov, P. Melas, Simon Lin, K. Wood, E. D. Zimmerman, M. A. Leigui de Oliveira, A. Olivier, Kevin J. Kelly, D. Sgalaberna, M. Gold, M. Spanu, Xiaolu Ji, A. M. Szelc, Gareth J. Barker, C. Cattadori, J. Fowler, S. J. M. Peeters, Raj Gandhi, M. Masud, R. LaZur, C. Grant, A. Olivares Del Campo, Joshua R. Klein, Vasundhara Singh, Ranjan Dharmapalan, Lynn Wood, E. Bechetoille, Patrick Green, Gustaaf Brooijmans, R. Howell, K. Moffat, J. G. Learned, J. Spitz, E. McCluskey, T. Patzak, M. D. Messier, J. A. Musser, R. Raboanary, P. Schlabach, C. Lastoria, D. Naples, Kazuhiro Terao, A. Paudel, Michael Mulhearn, S. B. Boyd, T. Hill, G. A. Valdiviesso, S. Emery, M. C. Goodman, D. C. Christian, S. Alonso Monsalve, B. Howard, G. Ge, Alexander Tapper, Thomas Strauss, J. Hugon, M. Kirby, K. Zeug, A. Laundrie, B. Szczerbinska, R. Flight, H. Vieira de Souza, D. M. DeMuth, A. Chatterjee, S. Kohn, F. Drielsma, A. Bitadze, B. Zamorano, Warner A. Miller, Yichen Li, Wladyslaw Henryk Trzaska, F. Piastra, C. Wilkinson, M. Greenwood, C. Girerd, R.J. Staley, R. Cross, S. Di Domizio, G. Meng, A. Mislivec, A. Sousa, K. Spurgeon, R. Gran, M. Roda, G.L. Raselli, R. S. Fitzpatrick, L. Rakotondravohitra, A. C. Kaboth, Matthew Mewes, Kai Loo, J. Trevor, T. Vrba, S. P. Kasetti, Y. Penichot, M. J. Wilking, M. Zito, S. Pordes, P. Weatherly, James John Brooke, M. Wallbank, F. F. Wilson, Nektarios Benekos, Renato Potenza, M. Toups, H. Y. Liao, Haleh Khani Hadavand, D. Redondo, S. R. Mishra, R. A. Gomes, E. Gramellini, S. Menary, P. C. de Holanda, D. Gibin, M. Stancari, B. J. P. Jones, C. Vilela, B. Tapia Oregui, N. Nayak, Sofia Vallecorsa, K. E. Duffy, E. Segreto, Xin Qian, T. A. Mohayai, Olga Mena, N. Martinez, O.V. Dvornikov, Filippo Resnati, M. B. Smy, K. Soustruznik, Diana Navas-Nicolas, S. Jiménez, R. Zwaska, William J. Marciano, C. Hohl, R. Haenni, Piera Sapienza, M. Shamma, N. P. Samios, H. Duyang, G. Lehmann Miotto, H. Meyer, A. Schukraft, C. S. Mishra, Vlastimil Kus, S. Murphy, Jianming Bian, C. Backhouse, Stephen J. Parke, J. Perry, Stephen Hillier, A. Guglielmi, D. Franco, M. Soares Nunes, A. Maddalena, M. Antonova, T. Boschi, J. L. Raaf, J. Singh, Alan Watson, F. Muheim, R. Milincic, P. Bernardini, Ralf Lehnert, T. A. Bolton, J. Greer, Y. T. Tsai, Mafalda Dias, L. Camilleri, S. Nagu, J. A. Maloney, Z. Vallari, J. Sensenig, I. Kadenko, D. Waters, S. Prakash, D. Ruterbories, Antonino Sergi, L. Kashur, M. Eads, C. Montanari, E. Conley, A. Scaramelli, S. Fuess, E. Cristaldo, H. Razafinime, Alessandro Montanari, T. Stokes, L. Li, Marc Weber, C. Bromberg, M. Leyton, M. E. Convery, S. Green, Jack Fried, P. De Lurgio, George Adamov, C. A. Ternes, Jane Nachtman, Y. A. Ramachers, D. A. Martinez Caicedo, E. T. Worcester, R. M. de Almeida, Yasar Onel, Mingshui Chen, A. Izmaylov, Claudia Brizzolari, C. Griffith, J. K. Nelson, K. Vaziri, M. A. Arroyave, F. Azfar, M. Karolak, Deywis Moreno, L. Molina Bueno, Science and Technology Facilities Council (STFC), Abi, B, Acciarri, R, Acero, M, Adamov, G, Adams, D, Adinolfi, M, Ahmad, Z, Ahmed, J, Alion, T, Monsalve, S, Alt, C, Anderson, J, Andreopoulos, C, Andrews, M, Andrianala, F, Andringa, S, Ankowski, A, Antonova, M, Antusch, S, Aranda-Fernandez, A, Ariga, A, Arnold, L, Arroyave, M, Asaadi, J, Aurisano, A, Aushev, V, Autiero, D, Azfar, F, Back, H, Back, J, Backhouse, C, Baesso, P, Bagby, L, Bajou, R, Balasubramanian, S, Baldi, P, Bambah, B, Barao, F, Barenboim, G, Barker, G, Barkhouse, W, Barnes, C, Barr, G, Monarca, J, Barros, N, Barrow, J, Bashyal, A, Basque, V, Bay, F, Alba, J, Beacom, J, Bechetoille, E, Behera, B, Bellantoni, L, Bellettini, G, Bellini, V, Beltramello, O, Belver, D, Benekos, N, Neves, F, Berger, J, Berkman, S, Bernardini, P, Berner, R, Berns, H, Bertolucci, S, Betancourt, M, Bezawada, Y, Bhattacharjee, M, Bhuyan, B, Biagi, S, Bian, J, Biassoni, M, Biery, K, Bilki, B, Bishai, M, Bitadze, A, Blake, A, Siffert, 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D., Zito, M., Zucchelli, S., Zuklin, J., Zutshi, V., Zwaska, R., Abi B., Acciarri R., Acero M.A., Adamov G., Adams D., Adinolfi M., Ahmad Z., Ahmed J., Alion T., Monsalve S.A., Alt C., Anderson J., Andreopoulos C., Andrews M., Andrianala F., Andringa S., Ankowski A., Antonova M., Antusch S., Aranda-Fernandez A., Ariga A., Arnold L.O., Arroyave M.A., Asaadi J., Aurisano A., Aushev V., Autiero D., Azfar F., Back H., Back J.J., Backhouse C., Baesso P., Bagby L., Bajou R., Balasubramanian S., Baldi P., Bambah B., Barao F., Barenboim G., Barker G., Barkhouse W., Barnes C., Barr G., Monarca J.B., Barros N., Barrow J.L., Bashyal A., Basque V., Bay F., Alba J.B., Beacom J.F., Bechetoille E., Behera B., Bellantoni L., Bellettini G., Bellini V., Beltramello O., Belver D., Benekos N., Neves F.B., Berger J., Berkman S., Bernardini P., Berner R.M., Berns H., Bertolucci S., Betancourt M., Bezawada Y., Bhattacharjee M., Bhuyan B., Biagi S., Bian J., Biassoni M., Biery K., Bilki B., Bishai M., Bitadze A., Blake A., Siffert B.B., Blaszczyk F., Blazey G., Blucher E., Boissevain J., Bolognesi S., Bolton T., Bonesini M., Bongrand M., Bonini F., Booth A., Booth C., Bordoni S., Borkum A., Boschi T., Bostan N., Bour P., Boyd S., Boyden D., Bracinik J., Braga D., Brailsford D., Brandt A., Bremer J., Brew C., Brianne E., Brice S.J., Brizzolari C., Bromberg C., Brooijmans G., Brooke J., Bross A., Brunetti G., Buchanan N., Budd H., Caiulo D., Calafiura P., Calcutt J., Calin M., Calvez S., Calvo E., Camilleri L., Caminata A., Campanelli M., Caratelli D., Carini G., Carlus B., Carniti P., Terrazas I.C., Carranza H., Castillo A., Castromonte C., Cattadori C., Cavalier F., Cavanna F., Centro S., Cerati G., Cervelli A., Villanueva A.C., Chalifour M., Chang C., Chardonnet E., Chatterjee A., Chattopadhyay S., Chaves J., Chen H., Chen M., Chen Y., Cherdack D., Chi C., Childress S., Chiriacescu A., Cho K., Choubey S., Christensen A., Christian D., Christodoulou G., Church E., Clarke P., Coan T.E., 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C., Farzan Y., Felix J., Fernandez-Martinez E., Menendez P.F., Ferraro F., Fields L., Filkins A., Filthaut F., Fitzpatrick R.S., Flanagan W., Fleming B., Flight R., Fowler J., Fox W., Franc J., Francis K., Franco D., Freeman J., Freestone J., Fried J., Friedland A., Fuess S., Furic I., Furmanski A.P., Gago A., Gallagher H., Gallego-Ros A., Gallice N., Galymov V., Gamberini E., Gamble T., Gandhi R., Gandrajula R., Gao S., Garcia-Gamez D., Garcia-Peris M.A., Gardiner S., Gastler D., Ge G., Gelli B., Gendotti A., Gent S., Ghorbani-Moghaddam Z., Gibin D., Gil-Botella I., Girerd C., Giri A., Gnani D., Gogota O., Gold M., Gollapinni S., Gollwitzer K., Gomes R.A., Bermeo L.G., Fajardo L.S.G., Gonnella F., Gonzalez-Cuevas J., Goodman M.C., Goodwin O., Goswami S., Gotti C., Goudzovski E., Grace C., Graham M., Gramellini E., Gran R., Granados E., Grant A., Grant C., Gratieri D., Green P., Green S., Greenler L., Greenwood M., Greer J., Griffith C., Groh M., Grudzinski J., Grzelak K., Gu W., Guarino V., Guenette R., Guglielmi A., Guo B., Guthikonda K., Gutierrez R., Guzowski P., Guzzo M.M., Gwon S., Habig A., Hackenburg A., Hadavand H., Haenni R., Hahn A., Haigh J., Haiston J., Hamernik T., Hamilton P., Han J., Harder K., Harris D.A., Hartnell J., Hasegawa T., Hatcher R., Hazen E., Heavey A., Heeger K.M., Hennessy K., Henry S., Morquecho M.H., Herner K., Hertel L., Hesam A.S., Hewes J., Pichardo A.H., Hill T., Hillier S.J., Himmel A., Hoff J., Hohl C., Holin A., Hoppe E., Horton-Smith G.A., Hostert M., Hourlier A., Howard B., Howell R., Huang J., Hugon J., Iles G., Iliescu A.M., Illingworth R., Ioannisian A., Itay R., Izmaylov A., James E., Jargowsky B., Jediny F., Jesus-Valls C., Ji X., Jiang L., Jimenez S., Jipa A., Joglekar A., Johnson C., Johnson R., Jones B., Jones S., Jung C., Junk T., Jwa Y., Kabirnezhad M., Kaboth A., Kadenko I., Kamiya F., Karagiorgi G., Karcher A., Karolak M., Karyotakis Y., Kasai S., Kasetti S.P., Kashur L., Kazaryan N., Kearns E., Keener P., Kelly K.J., Kemp E., Ketchum W., Kettell S., Khabibullin M., Khotjantsev A., Khvedelidze A., Kim D., King B., Kirby B., Kirby M., Klein J., Koehler K., Koerner L.W., Kohn S., Koller P.P., Kordosky M., Kosc T., Kose U., Kostelecky V., Kothekar K., Krennrich F., Kreslo I., Kudenko Y., Kudryavtsev V., Kulagin S., Kumar J., Kumar R., Kuruppu C., Kus V., Kutter T., Lambert A., Lande K., Lane C.E., Lang K., Langford T., Lasorak P., Last D., Lastoria C., Laundrie A., Lawrence A., Lazanu I., Lazur R., Le T., Learned J., Lebrun P., Miotto G.L., Lehnert R., De Oliveira M.L., Leitner M., Leyton M., Li L., Li S., Li T., Li Y., Liao H., Lin C., Lin S., Lister A., Littlejohn B.R., Liu J., Lockwitz S., Loew T., Lokajicek M., Lomidze I., Long K., Loo K., Lorca D., Lord T., Losecco J., Louis W.C., Luk K., Luo X., Lurkin N., Lux T., Luzio V.P., MacFarland D., MacHado A., MacHado P., MacIas C., MacIer J., Maddalena A., Madigan P., Magill S., Mahn K., Maio A., Maloney J.A., Mandrioli G., Maneira J.C., 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Motuk E., Moura C.A., Mousseau J., Mu W., Mualem L., Mueller J., Muether M., Mufson S., Muheim F., Muir A., Mulhearn M., Muramatsu H., Murphy S., Musser J., Nachtman J., Nagu S., Nalbandyan M., Nandakumar R., Naples D., Narita S., Navas-Nicolas D., Nayak N., Nebot-Guinot M., Necib L., Negishi K., Nelson J.K., Nesbit J., Nessi M., Newbold D., Newcomer M., Newhart D., Nichol R., Niner E., Nishimura K., Norman A., Northrop R., Novella P., Nowak J.A., Oberling M., Campo A.O.D., Olivier A., Onel Y., Onishchuk Y., Ott J., Pagani L., Pakvasa S., Palamara O., Palestini S., Paley J.M., Pallavicini M., Palomares C., Pantic E., Paolone V., Papadimitriou V., Papaleo R., Papanestis A., Paramesvaran S., Parke S., Parsa Z., Parvu M., Pascoli S., Pasqualini L., Pasternak J., Pater J., Patrick C., Patrizii L., Patterson R.B., Patton S., Patzak T., Paudel A., Paulos B., Paulucci L., Pavlovic Z., Pawloski G., Payne D., Pec V., Peeters S.J., Penichot Y., Pennacchio E., Penzo A., Peres O.L., Perry J., Pershey D., Pessina G., Petrillo G., Petta C., Petti R., Piastra F., Pickering L., Pietropaolo F., Pillow J., Plunkett R., Poling R., Pons X., Poonthottathil N., Pordes S., Potekhin M., Potenza R., Potukuchi B.V., Pozimski J., Pozzato M., Prakash S., Prakash T., Prince S., Prior G., Pugnere D., Qi K., Qian X., Raaf J., Raboanary R., Radeka V., Rademacker J., Radics B., Rafique A., Raguzin E., Rai M., Rajaoalisoa M., Rakhno I., Rakotondramanana H., Rakotondravohitra L., Ramachers Y., Rameika R., Delgado M.R., Ramson B., Rappoldi A., Raselli G., Ratoff P., Ravat S., Razafinime H., Real J., Rebel B., Redondo D., Reggiani-Guzzo M., Rehak T., Reichenbacher J., Reitzner S.D., Renshaw A., Rescia S., Resnati F., Reynolds A., Riccobene G., Rice L.C., Rielage K., Rigaut Y., Rivera D., Rochester L., Roda M., Rodrigues P., Alonso M.R., Rondon J.R., Roeth A., Rogers H., Rosauro-Alcaraz S., Rossella M., Rout J., Roy S., Rubbia A., Rubbia C., Russell B., Russell J., Ruterbories D., Saakyan R., Sacerdoti S., Safford T., Sahu N., Sala P., Samios N., Sanchez M., Sanders D.A., Sankey D., Santana S., Santos-Maldonado M., Saoulidou N., Sapienza P., Sarasty C., Sarcevic I., Savage G., Savinov V., Scaramelli A., Scarff A., Scarpelli A., Schaffer T., Schellman H., Schlabach P., Schmitz D., Scholberg K., Schukraft A., Segreto E., Sensenig J., Seong I., Sergi A., Sergiampietri F., Sgalaberna D., Shaevitz M., Shafaq S., Shamma M., Sharma H.R., Sharma R., Shaw T., Shepherd-Themistocleous C., Shin S., Shooltz D., Shrock R., Simard L., Simos N., Sinclair J., Sinev G., Singh J., Singh V., Sipos R., Sippach F., Sirri G., Sitraka A., Siyeon K., Smargianaki D., Smith A., Smith E., Smith P., Smolik J., Smy M., Snopok P., Nunes M.S., Sobel H., Soderberg M., Salinas C.J.S., Soldner-Rembold S., Solomey N., Solovov V., Sondheim W.E., Sorel M., Soto-Oton J., Sousa A., Soustruznik K., Spagliardi F., Spanu M., Spitz J., Spooner N.J., Spurgeon K., Staley R., Stancari M., Stanco L., Steiner H., Stewart J., Stillwell B., Stock J., Stocker F., Stokes T., Strait M., Strauss T., Striganov S., Stuart A., Summers D., Surdo A., Susic V., Suter L., Sutera C., Svoboda R., Szczerbinska B., Szelc A., Talaga R., Tanaka H., Oregui B.T., Tapper A., Tariq S., Tatar E., Tayloe R., Teklu A., Tenti M., Terao K., Ternes C.A., Terranova F., Testera G., Thea A., Thompson J.L., Thorn C., Timm S., Tonazzo A., Torti M., Tortola M., Tortorici F., Totani D., Toups M., Touramanis C., Trevor J., Trzaska W.H., Tsai Y.T., Tsamalaidze Z., Tsang K., Tsverava N., Tufanli S., Tull C., Tyley E., Tzanov M., Uchida M.A., Urheim J., Usher T., Vagins M., Vahle P., Valdiviesso G., Valencia E., Vallari Z., Valle J.W., Vallecorsa S., Berg R.V., De Water R.G.V., Forero D.V., Varanini F., Vargas D., Varner G., Vasel J., Vasseur G., Vaziri K., Ventura S., Verdugo A., Vergani S., Vermeulen M.A., Verzocchi M., De Souza H.V., Vignoli C., Vilela C., Viren B., Vrba T., Wachala T., Waldron A.V., Wallbank M., Wang H., Wang J., Wang Y., Warburton K., Warner D., Wascko M., Waters D., Watson A., Weatherly P., Weber A., Weber M., Wei H., Weinstein A., Wenman D., Wetstein M., While M.R., White A., Whitehead L.H., Whittington D., Wilking M.J., Wilkinson C., Williams Z., Wilson F., Wilson R.J., Wolcott J., Wongjirad T., Wood K., Wood L., Worcester E., Worcester M., Wret C., Wu W., Xiao Y., Yang G., Yang T., Yershov N., Yonehara K., Young T., Yu B., Yu J., Zalesak J., Zambelli L., Zamorano B., Zani A., Zazueta L., Zeller G., Zennamo J., Zeug K., Zhang C., Zhao M., Zhivun E., Zhu G., Zimmerman E.D., Zito M., Zucchelli S., Zuklin J., Zutshi V., and Zwaska R.

Subjects
Technology, 530 Physics, media_common.quotation_subject, Neutrino oscillations, liquid Argon TPC, DUNE technical design report, single phase LArTPC, Electrons, FREE-ELECTRONS, 01 natural sciences, 7. Clean energy, 09 Engineering, 030218 nuclear medicine & medical imaging, Standard Model, 03 medical and health sciences, neutrino, 0302 clinical medicine, LIQUID ARGON, 0103 physical sciences, Grand Unified Theory, High Energy Physics, Aerospace engineering, Instrumentation, Instruments & Instrumentation, Mathematical Physics, media_common, Physics, Science & Technology, 02 Physical Sciences, 010308 nuclear & particles physics, business.industry, Detector, Lıquıd Argonfree, Nuclear & Particles Physics, Symmetry (physics), Universe, Long baseline neutrino experiment, CP violation, Antimatter, Neutrino, business, Event (particle physics)
Abstract

This document was prepared by the DUNE collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by Fermi Research Alliance, LLC (FRA), acting under Contract No. DE-AC02-07CH11359. The DUNE collaboration also acknowledges the international, national, and regional funding agencies supporting the institutions who have contributed to completing this Technical Design Report., The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. DUNE is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. Central to achieving DUNE's physics program is a far detector that combines the many tens-of-kiloton fiducial mass necessary for rare event searches with sub-centimeter spatial resolution in its ability to image those events, allowing identification of the physics signatures among the numerous backgrounds. In the single-phase liquid argon time-projection chamber (LArTPC) technology, ionization charges drift horizontally in the liquid argon under the influence of an electric field towards a vertical anode, where they are read out with fine granularity. A photon detection system supplements the TPC, directly enhancing physics capabilities for all three DUNE physics drivers and opening up prospects for further physics explorations. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume IV presents an overview of the basic operating principles of a single-phase LArTPC, followed by a description of the DUNE implementation. Each of the subsystems is described in detail, connecting the high-level design requirements and decisions to the overriding physics goals of DUNE., Fermi Research Alliance, LLC (FRA) DE-AC02-07CH11359

Published
2020

46. Experimental Study on Axial Pull-Out Behavior of Steel Rebars Glued-In Glubam

Author

Y. Xiao and Z. W. He

Subjects
Bamboo, Materials science, business.industry, 0211 other engineering and technologies, Rebar, 020101 civil engineering, 02 engineering and technology, Building and Construction, Structural engineering, 0201 civil engineering, law.invention, Mechanics of Materials, law, 021105 building & construction, General Materials Science, business, Joint (geology), Civil and Structural Engineering
Abstract

This paper presents an experimental study on glued-in rebar glubam (glued laminated bamboo) joints. The main experimental parameters were anchorage length, glue-line thickness, and the angl...

Published
2020

47. Experimental and Analytical Investigations on Short-Term Behavior of Glubam-Concrete Composite Beams

Author

Y. Xiao, T. Y. Li, Z. Y. Wang, and B. Shan

Subjects
Materials science, business.industry, Mechanical Engineering, Composite number, 0211 other engineering and technologies, 020101 civil engineering, 02 engineering and technology, Building and Construction, Bending, Structural engineering, Composite beams, 0201 civil engineering, Mechanics of Materials, 021105 building & construction, General Materials Science, business, Beam (structure), Civil and Structural Engineering
Abstract

This paper describes the results of short-term bending tests on glued laminated bamboo (glubam) and concrete composite (BCC) beams. Four types of connection details were designed and tested...

Published
2020

48. Copeptin and Nesfatin-1 are interesting interrelated biomarkers playing a role in the pathogenesis of insulin resistance in Chinese obese children

Author

Qi Lu, LV Weicheng, Erdi Xu, Chunyan Yin, Weihua Liu, and yanfeng y xiao

Subjects
Pathogenesis, Insulin resistance, Copeptin, business.industry, medicine, medicine.disease, Bioinformatics, business
Abstract

Background Recently, copeptin and nesfatin-1 have been identified as interesting novel peptides playing a role in the pathogenesis of obesity-related insulin resistance in adults, respectively. However, the relationship between them has not been elucidated; and their circulating levels in obese children have not been adequately studied. Therefore, the current study aimed to investigate whether their levels are altered in Chinese obese children and to study the correlation of these two peptides with each other and with insulin resistance and other biochemical parameters. Methods A total of 120 children were enrolled in this study, including 80 obese children and 40 lean controls. Anthropometric parameters and clinical data of all subjects were collected and circulating TNF-α, adiponectin, leptin, copeptin and nesfatin-1 levels were detected using enzyme-linked immunosorbent assays. Results Serum copeptin and nesfatin-1 levels were significantly elevated in obese children and children with insulin resistance compared to control subjects. In addition, nesfatin-1 and copeptin levels were found to be significantly positively correlated with one another in pearson’s correlation and partial correlation. More importantly, multiple regression analysis used nesfatin-1or copeptin as the dependent parameters and significant correlation between nesfatin-1 and copeptin with each other and the associations between each of them with HOMA-IR were detected. Conclusion These findings are novel and shed light on the possible interplay role of these two molecules in obesity-related insulin resistance.

Published
2020

49. Volume I. Introduction to DUNE

Author

E. Hazen, Armin Karcher, D. Smargianaki, Christopher L. Marshall, K. Spurgeon, M. Gold, C. Vignoli, C. J. Solano Salinas, M. J. Wilking, K. Kothekar, G. Sirri, Evgueni Goudzovski, H. Mendez, W. Flanagan, V. Papadimitriou, D. Redondo, S. R. Mishra, Y.-J. Jwa, G. Petrillo, M. Spanu, Xiaolu Ji, O. V. Mineev, M. Bishai, S. Menary, L. Molina Bueno, P. C. de Holanda, H. Berns, A. Gendotti, A. M. Szelc, R. Gandhi, A. Himmel, M. Rajaoalisoa, P. Bour, N. Kazaryan, L. Mualem, Gareth J. Barker, C. Cattadori, S. Ravat, W. Mu, D. Marfatia, T. Miedema, Kendall Mahn, Jorge Molina, Filippo Resnati, S. Magill, E. Niner, D. Autiero, Poonam Mehta, John Evans, J. S. Díaz, P. Novella, J. Fowler, G. Karagiorgi, S. J. M. Peeters, William J. Marciano, S. Bordoni, James Mueller, J. Martín-Albo, W. Fox, K. Grzelak, C. Hohl, R. Haenni, S. Alonso Monsalve, B. Howard, G. Ge, Alexander Tapper, Thomas Strauss, Silvia Pascoli, B. Stillwell, A. Lambert, A. Holin, K. V. Tsang, J. Maneira, R.A. Rameika, Juraj Bracinik, C. Wret, M. Tenti, Alberto Cervelli, Sukalyan Chattopadhyay, Laura Dominé, K. Herner, Hem Raj Sharma, S. Kasai, A. Higuera Pichardo, M. Betancourt, A. Scarff, R. Northrop, M. V. Diwan, D. J. Payne, C. Gotti, M. A. Vermeulen, R. M. Berner, J. J. De Vries, S. Shafaq, Yu. G. Kudenko, L. Pickering, B. Bhuyan, C. Kuruppu, Janet Conrad, D. Brailsford, R. Van Berg, J. Chaves, B. Paulos, R. Sipos, E. Pennacchio, F. W. Sippach, T. Li, S. Striganov, Laura Paulucci, S. Manly, P. Hamilton, R. G. Van de Water, R. Nandakumar, B. Szczerbinska, D. Cherdack, H. Carranza, Milos Lokajicek, K. Nishimura, E. Kearns, A. C. Ezeribe, J. Hoff, A. McNab, A. Stuart, G. Vasseur, C. Petta, M. Wetstein, M. M. Khabibullin, A. Bitadze, Yichen Li, G. Brunetti, L. Suter, L. Pasqualini, S. Martynenko, Ph. Lebrun, B. Morgan, L. Patrizii, A. Guglielmi, D. Wenman, S. C. Timm, R. Sharma, R. Saakyan, R. Gran, C. McGrew, C. Andreopoulos, A. Mann, F. Terranova, C. Cuesta, O. G. Miranda, C. Patrick, José W. F. Valle, A. Booth, G. Mandrioli, J. A. Nowak, S. Tufanli, R. Bajou, J. Urheim, J. Bian, Yasaman Farzan, M. Roda, J. G. Boissevain, J. Smolik, Thorsten Lux, L. Fields, D. Franco, S. P. Kasetti, M. Soares Nunes, A. Maddalena, M. Antonova, E. Kemp, N. Solomey, Laura Manenti, K. Francis, M. H. Shaevitz, N. Barros, C. Booth, I. Caro Terrazas, R. Itay, E. Ewart, R. J. Nichol, D. Totani, P. Snopok, M. Sorel, Kaushik De, M. Soderberg, A. C. Weber, Jonas Rademacker, E. Brianne, M. J. Rodriguez Alonso, T. Boschi, Sandhya Choubey, D. Montanari, Giorgio Riccobene, A. Mefodiev, M. A. Acero, A. Rappoldi, F. F. Wilson, Nektarios Benekos, Piera Sapienza, V. Savinov, P. Melas, Kenneth Long, Jianbei Liu, C. Mossey, Renato Potenza, M. Shamma, N. P. Samios, Y. Penichot, C. Bromberg, W. C. Louis, V. Paolone, V. Pec, J. Pillow, S. Vergani, S. Balasubramanian, B. Carlus, D. Boyden, Kam-Biu Luk, Simon Lin, Sofia Andringa, F. Jediny, K. Qi, K. Wood, M. Toups, Haleh Khani Hadavand, B. Tapia Oregui, G. P. Zeller, Gregory Iles, S. Gollapinni, A. Friedland, K. M. Heeger, P. Debbins, R. LaZur, J. A. B. Coelho, Jeremy Wolcott, Kevin J. Kelly, D. Sgalaberna, Joshua Barrow, John Marshall, M. Zito, K. Koehler, S. Pordes, P. Weatherly, E. D. Zimmerman, M. A. Leigui de Oliveira, N. Nayak, J. Sinclair, J. I. Crespo-Anadón, H. S. Chen, James John Brooke, A. Olivier, R. Milincic, P. Bernardini, Jim Freeman, L. Kashur, L.S. Rochester, Dario Gnani, Andrea Zani, M. Wallbank, Giuseppe Benedetto Cerati, T. Kosc, Dave Sankey, Patrick Green, Olga Mena, N. Martinez, F. Pietropaolo, S. Narita, A. Scaramelli, C. Grant, T. L. Usher, A. Marchionni, D. A. Dwyer, S. Prince, J. Haiston, T. J. Langford, A. M. Gago, Artur M. Ankowski, E. Gamberini, J. Asaadi, E. Valencia, Roberto Gutiérrez, T. Hasegawa, T. R. Junk, Y. A. Ramachers, D. A. Martinez Caicedo, R. Howell, R. M. de Almeida, Yasar Onel, Matheus Hostert, D. Duchesneau, J. A. Musser, F. Sergiampietri, D. W. Schmitz, E. Zhivun, Marzio Nessi, D. Lorca, Dave M Newbold, C. K. Jung, A. Olivares Del Campo, F. Krennrich, G. Testera, Alexandru Jipa, S. Rescia, Andrés Castillo, Joshua R. Klein, Olga Beltramello, Srubabati Goswami, Z. Williams, Vasundhara Singh, C. Mauger, J. Yu, M. Bonesini, Jack Fried, P. De Lurgio, C. A. Ternes, H. Y. Liao, K. Mason, N. Poonthottathil, A. Scarpelli, E. T. Worcester, J. T. Haigh, H. Muramatsu, G. C. Blazey, Rex Tayloe, R. Diurba, G. Christodoulou, F. Barao, S. Calvez, H. Duyang, L. M. Cremaldi, E. Motuk, H. Meyer, R. Guenette, C. Castromonte, A. Schukraft, Julián Félix, D. MacFarland, K. Gollwitzer, F. Varanini, Ranjan Dharmapalan, Lynn Wood, M. Pozzato, G. Zhu, S. Centro, Francesco Tortorici, S. Henry, R. A. Gomes, E. Gramellini, D. Vanegas Forero, Z. Pavlovic, D. A. Sanders, Christian Farnese, John F. Beacom, P. Vahle, G. A. Horton-Smith, T. Durkin, H. Y. Wei, L. Escudero Sanchez, Mingshui Chen, I. K. Furic, J. Moon, T. Young, John Matthews, E. James, B. Gelli, Gregory J. Michna, Steven Gardiner, P. Madigan, A. Izmaylov, D. Douglas, D. Gibin, M. Stancari, Shibaji Roy, I. Rakhno, J. Barranco Monarca, Paolo Calafiura, Q. David, Akitaka Ariga, Marvin L Marshak, Rukmani Mohanta, P. E. L. Clarke, C. Palomares, K. Cho, M. A. Arroyave, Andrew Norman, Claudia Brizzolari, J. Nachtman, Daniel Gastler, J. Hugon, M. Karolak, H. O. Back, Z. Ahmad, Gabriella Carini, M. Dabrowski, Paul Keener, Leigh H. Whitehead, Karol Hennessy, S. Söldner-Rembold, C. S. Lin, D. Edmunds, A. Chiriacescu, M. Oberling, T. Rehak, Katsuya Yonehara, T. E. Coan, L. V. Gomez Bermeo, F. Andrianala, Francesco Gonnella, T. Safford, E. Tatar, Utku Kose, M. Bhattacharjee, F. Cavanna, A. Muir, A. L. Renshaw, Orlando L. G. Peres, Amelia Maio, Carl Grace, J. Migenda, B. Viren, M. Muether, A. Mastbaum, Alfredo G. Cocco, C. Griffith, J. Mousseau, Paolo Carniti, L. Greenler, J. Rout, W. Ketchum, B. Radics, Ionel Lazanu, A. Laundrie, V. N. Solovov, David Cussans, X. Pons, N. Gallice, J. G. Learned, R. Flight, M. Nebot-Guinot, H. Vieira de Souza, S. Sacerdoti, J. Calcutt, K. Warburton, M. Nalbandyan, A. P. Furmanski, P. de Jong, B. T. Fleming, R. Poling, P.T. Smith, M. Worcester, Wei Wu, B. Guo, Frank Filthaut, J. Reichenbacher, S. Ventura, M. Graham, Riccardo Papaleo, A. M. Teklu, D. Newhart, P. Fernandez Menendez, J. Han, Deywis Moreno, C. Densham, Matthaeus Leitner, K. Fahey, Bindu A. Bambah, E. Blucher, S. Childress, T. Miao, Shiroman Prakash, Jason Kumar, Yi Chen, M. Kirby, P. Cotte, A. J. Roeth, R. Acciarri, E. Bechetoille, Gustaaf Brooijmans, K. Moffat, B. V. K. S. Potukuchi, S. Li, K. Vaziri, Sudarshan Paramesvaran, Seodong Shin, M. Santos-Maldonado, J.V. Dawson, Aldo Penzo, Ara Ioannisian, S. Rosauro-Alcaraz, H. T. Rakotondramanana, F. Piastra, N.V. Mokhov, S. Davini, R. L. Talaga, A. Caminata, G. Bellettini, J. Hartnell, C. Y. Chi, M. Groh, Karol Lang, C. Girerd, F. Diaz, F. Azfar, Alastair Grant, R. Hatcher, M. Zhao, J. Marteau, Irakli Lomidze, F. Stocker, T. Gamble, J. J. Grudzinski, L. Montaño Zetina, A. Heavey, Grzegorz Deptuch, F. Cavalier, R. Illingworth, I. Gil-Botella, N. Bostan, A. Gallego-Ros, T. Schaffer, N. Buchanan, G. Lehmann Miotto, Robert Shrock, J. Zennamo, Zviad Tsamalaidze, N. Mauri, H. da Motta, David Delepine, M. Torti, A. De Roeck, M. Calin, A. Lawrence, P. N. Ratoff, T. Kutter, B. Jargowsky, J. K. Nelson, Cari L. Johnson, C. S. Mishra, Vlastimil Kus, R.J. Staley, R. Cross, S. Murphy, S. Dennis, P. P. Koller, D. Whittington, D. Garcia-Gamez, K. Lande, R. B. Patterson, Anjan K. Giri, Wayne A. Barkhouse, A. Filkins, Daijin Kim, G.D. Barr, Junwei Huang, V. De Romeri, A. Mislivec, Manuela Campanelli, Y. Rigaut, Matthew L Strait, G. Barenboim, G. Prior, P. Guzowski, A. Cervera Villanueva, Robert Svoboda, C. Backhouse, A. Falcone, M. R. While, V. Bellini, C. Alt, J. Spitz, Stephen J. Parke, E. McCluskey, M. Mellinato, Jürgen Pozimski, D. Caratelli, L. Bellantoni, M. Rai, D. Mladenov, J. Stock, T. Lord, L. Zazueta, Alexander Deisting, R. Raboanary, T. Patzak, B. Rebel, M. D. Messier, B. Abi, A. de Gouvea, V. A. Kostelecky, K. Zeug, Joleen Pater, A. Hackenburg, K. Negishi, M. A. Hernandez Morquecho, J. Perry, Stephen Hillier, David H. Adams, D. Caiulo, S. Bolognesi, D. Belver, S. Zucchelli, F. Marinho, R. Petti, G.L. Raselli, Han Wang, Sergey A. Kulagin, A. Bashyal, J. Berger, A. Papanestis, A. Aurisano, F. Bay, Beatriz B. Siffert, E. Granados, B. Behera, H.E. Rogers, A. Rafique, J. Nesbit, Chris Brew, A. C. Kaboth, T. Vrba, P. Lasorak, Kim Siyeon, Andrea Dell'Acqua, Timothy M. Shaw, D. Braga, J. Ahmed, Yu. Onishchuk, Kate Scholberg, Alessandro Menegolli, T. Hamernik, Konstantinos Manolopoulos, R. K. Plunkett, V. Susic, Pedro A. N. Machado, T. Alion, N. Simos, O. Gogota, I. L. De Icaza Astiz, Narendra Sahu, F. Muheim, Ralf Lehnert, S. Gao, Andrew White, S. Berkman, André Rubbia, J. L. Raaf, J. Singh, C. Barnes, A. S. Hesam, S. D. Reitzner, T. Le, L. Hertel, R. Gandrajula, D. Vargas, L. Corwin, S. L. Mufson, B. J. P. Jones, C. Vilela, S. H. Kettell, B. Ramson, Chia-Chan Chang, P. Schlabach, C. Lastoria, Alan Watson, Z. Ghorbani-Moghaddam, Marcelo M. Guzzo, P. Baesso, S. Gwon, A. Surdo, Ina Sarcevic, Eric W. Hoppe, M. O. Wascko, T. A. Bolton, J. Greer, Y. T. Tsai, L. Camilleri, Sofia Vallecorsa, K. E. Duffy, S. Nagu, J. A. Maloney, Z. Vallari, J. Sensenig, L. Da Silva Peres, Manuel Alejandro Segura Delgado, A. Joglekar, M. P. Andrews, K. S. McFarland, C. T. Macias, D. Naples, Chao Zhang, D. M. DeMuth, Kazuhiro Terao, A. Paudel, M. Biassoni, D. Pershey, Rakesh Kumar, M. Bongrand, Michael Mulhearn, N. Moggi, E. Segreto, Xin Qian, Mafalda Dias, Claire Shepherd-Themistocleous, A. Chatterjee, S. Kohn, T. A. Mohayai, O.V. Dvornikov, L. Di Giulio, T. Yang, V. Zutshi, Sandeep Miryala, Enrique Calvo, V. Radeka, B. Bilki, I. Kadenko, D. Waters, D. Ruterbories, Antonino Sergi, M. Tzanov, C. Touramanis, F. Drielsma, Y. Xiao, A. Verdugo, J. M. Paley, Antonio Ereditato, C. E. Lane, M. J. Dolinski, C. Rubbia, A. Borkum, N. McConkey, J. Wang, X. Luo, Y. Karyotakis, M. Eads, S. Biagi, L. O. Arnold, J. J. Back, C. Morris, S. Bertolucci, V. Basque, A. Mazzacane, C. Montanari, E. Conley, N. Yershov, Marco Adinolfi, M. B. Smy, S. Fuess, M. Kordosky, T. Stokes, J. J. Russell, H. R. Gallagher, D. Pugnere, D. Gratieri, J. R. T. de Mello Neto, L. Li, K. Soustruznik, M. E. Convery, L. Stanco, B. Zamorano, Warner A. Miller, C. A. Moura, A. D. Marino, Wladyslaw Henryk Trzaska, C. Jesús-Valls, Andrew Blake, S. B. Boyd, T. Hill, L. Jiang, Diana Navas-Nicolas, G. A. Valdiviesso, S. Emery, S. Jiménez, E. Cristaldo, H. Razafinime, Stephen P. Gent, Alessandro Montanari, R. Zwaska, S. Green, D. C. Christian, F. Bonini, J. Zuklin, M. Masud, Kristian Harder, J. Hewes, Sandro Palestini, Marc Weber, D. A. Harris, C. Distefano, Ornella Palamara, George Adamov, Andrew Smith, M. Manrique Plata, V. J. Guarino, C. Sarasty, J. Bremer, R. A. Johnson, H. S. Budd, G. Yang, I. Kreslo, M. Parvu, James A. Anderson, V. A. Kudryavtsev, G. S. Davies, I. De Bonis, L. Di Noto, W. E. Sondheim, C. E. Tull, M. Leyton, C. Wilkinson, M. Greenwood, O. Goodwin, K. K. Guthikonda, Simon Jones, S. Di Domizio, G. Meng, A. Lister, A. Christensen, Mariam Tórtola, J. Mills, A. Sousa, Irina Mocioiu, L. Zambelli, A. F. Moor, A. M. Iliescu, Alex Reynolds, K. Biery, Yanchu Wang, Christopher J. Milne, A. Aranda-Fernandez, M. Potekhin, R. S. Fitzpatrick, V. Aushev, L. Rakotondravohitra, J. Zalesak, L. Simard, L. Pagani, Matthew Mewes, J. Rodriguez Rondon, Kai Loo, J. Trevor, Alec Habig, S. Matsuno, D. J. Summers, L. Cremonesi, A. Tonazzo, J. R. Macier, F. Ferraro, J. Freestone, D. Rivera, K. Mavrokoridis, S. Santana, C. Mariani, Carlos Escobar, J. Vasel, J. A. Gonzalez-Cuevas, J. Franc, H. A. Tanaka, B. Kirby, A. Bross, D. Warner, C. E. Thorn, Robert Wilson, Marco Verzocchi, S. J. Patton, E. Church, Sandip Pakvasa, G. S. Varner, A. Hourlier, Paola Sala, D. Shooltz, Zelimir Djurcic, Alessandro Thea, Y. Bezawada, V. P. Luzio, Janice L. Thompson, F. Kamiya, E. Raguzin, L. C. J. Rice, Bo Yu, A. V. Waldron, J. L. Bazo Alba, Y. Cui, P. A. Rodrigues, M. C. Goodman, T. Loew, P. Ding, J. D. Eisch, A. Weinstein, A. Sitraka, L. Bagby, J. M. LoSecco, F. Bento Neves, Andrew Brandt, Ihn Sik Seong, C. M. Sutera, E. Smith, W. Metcalf, T. Wongjirad, A. Delbart, N. J. C. Spooner, E. Pantic, James Stewart, L. W. Koerner, T. Wachala, Barry King, R. Mazza, Keith Rielage, N. Dokania, L. S. Gomez Fajardo, M. P. Decowski, V. Galymov, E. Chardonnet, B. R. Littlejohn, B. Russell, M. Vagins, Jordan Ott, Niki Saoulidou, E. Mazzucato, S. Tariq, Gregory J Pawloski, T. Prakash, Arsen Khvedelidze, A.S. Dyshkant, M. A. Uchida, M. Reggiani-Guzzo, M. Á. García-Peris, M. Kabirnezhad, Pierre Baldi, M. Mooney, E. Tyley, A. Hahn, F. Spagliardi, M. Newcomer, H. W. Sobel, F. D. M. Blaszczyk, Lina Necib, Enrique Fernandez-Martinez, J. S. Real, M. A. Ramirez Delgado, H. Steiner, S. Lockwitz, G. Sinev, Massimo Rossella, S. J. Brice, Nicolas Lurkin, A. A. Machado, Jaroslaw Pasternak, W. Gu, J. Maricic, H. Schellman, Stefan Antusch, Z. Parsa, Patrick Dunne, M. C. Sanchez, A. N. Khotjantsev, N. Tsverava, Marco Pallavicini, G. Savage, J. Soto-Oton, G. Pessina, M. Chalifour, Abi B., Acciarri R., Acero M.A., Adamov G., Adams D., Adinolfi M., Ahmad Z., Ahmed J., Alion T., Monsalve S.A., Alt C., Anderson J., Andreopoulos C., Andrews M., Andrianala F., Andringa S., Ankowski A., Antonova M., Antusch S., Aranda-Fernandez A., Ariga A., Arnold L.O., Arroyave M.A., Asaadi J., Aurisano A., Aushev V., Autiero D., Azfar F., Back H., Back J.J., Backhouse C., Baesso P., Bagby L., Bajou R., Balasubramanian S., Baldi P., Bambah B., Barao F., Barenboim G., Barker G., Barkhouse W., Barnes C., Barr G., Monarca J.B., Barros N., Barrow J.L., Bashyal A., Basque V., Bay F., Alba J.B., Beacom J.F., Bechetoille E., Behera B., Bellantoni L., Bellettini G., Bellini V., Beltramello O., Belver D., Benekos N., Neves F.B., Berger J., Berkman S., Bernardini P., Berner R.M., Berns H., Bertolucci S., Betancourt M., Bezawada Y., Bhattacharjee M., Bhuyan B., Biagi S., Bian J., Biassoni M., Biery K., Bilki B., Bishai M., Bitadze A., Blake A., Siffert B.B., Blaszczyk F., Blazey G., Blucher E., Boissevain J., Bolognesi S., Bolton T., Bonesini M., Bongrand M., Bonini F., Booth A., Booth C., Bordoni S., Borkum A., Boschi T., Bostan N., Bour P., Boyd S., Boyden D., Bracinik J., Braga D., Brailsford D., Brandt A., Bremer J., Brew C., Brianne E., Brice S.J., Brizzolari C., Bromberg C., Brooijmans G., Brooke J., Bross A., Brunetti G., Buchanan N., Budd H., Caiulo D., Calafiura P., Calcutt J., Calin M., Calvez S., Calvo E., Camilleri L., Caminata A., Campanelli M., Caratelli D., Carini G., Carlus B., Carniti P., Terrazas I.C., Carranza H., Castillo A., Castromonte C., Cattadori C., Cavalier F., Cavanna F., Centro S., Cerati G., Cervelli A., Villanueva A.C., Chalifour M., Chang C., Chardonnet E., Chatterjee A., Chattopadhyay S., Chaves J., Chen H., Chen M., Chen Y., Cherdack D., Chi C., Childress S., Chiriacescu A., Cho K., Choubey S., Christensen A., Christian D., Christodoulou G., Church E., Clarke P., Coan T.E., Cocco A.G., Coelho J., Conley E., Conrad J., Convery M., 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Khotjantsev A., Khvedelidze A., Kim D., King B., Kirby B., Kirby M., Klein J., Koehler K., Koerner L.W., Kohn S., Koller P.P., Kordosky M., Kosc T., Kose U., Kostelecky V., Kothekar K., Krennrich F., Kreslo I., Kudenko Y., Kudryavtsev V., Kulagin S., Kumar J., Kumar R., Kuruppu C., Kus V., Kutter T., Lambert A., Lande K., Lane C.E., Lang K., Langford T., Lasorak P., Last D., Lastoria C., Laundrie A., Lawrence A., Lazanu I., Lazur R., Le T., Learned J., Lebrun P., Miotto G.L., Lehnert R., De Oliveira M.L., Leitner M., Leyton M., Li L., Li S., Li T., Li Y., Liao H., Lin C., Lin S., Lister A., Littlejohn B.R., Liu J., Lockwitz S., Loew T., Lokajicek M., Lomidze I., Long K., Loo K., Lorca D., Lord T., Losecco J., Louis W.C., Luk K., Luo X., Lurkin N., Lux T., Luzio V.P., MacFarland D., MacHado A., MacHado P., MacIas C., MacIer J., Maddalena A., Madigan P., Magill S., Mahn K., Maio A., Maloney J.A., Mandrioli G., Maneira J.C., Manenti L., Manly S., Mann A., Manolopoulos K., Plata M.M., 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Subjects
detector: technology, deep underground detector [neutrino], 530 Physics, Physics::Instrumentation and Detectors, Data management, media_common.quotation_subject, far detector, Long baseline neutrino experiment CP violation, 01 natural sciences, 030218 nuclear medicine & medical imaging, Neutrino oscillations. Neutrino Detectors. CP violation. Matter stability, design [detector], 03 medical and health sciences, neutrino, neutrino: deep underground detector, 0302 clinical medicine, near detector, 0103 physical sciences, Deep Underground Neutrino Experiment, ddc:610, Neutrino oscillation, Instrumentation, detector: design, Mathematical Physics, activity report, media_common, 010308 nuclear & particles physics, business.industry, Detector, Volume (computing), Modular design, time projection chamber: liquid argon, Universe, technology [detector], liquid argon [time projection chamber], Systems engineering, High Energy Physics::Experiment, Neutrino oscillations, DUNE technical design report, executive summary, detector technologies, data management, Neutrino, business
Abstract

Journal of Instrumentation 15(08), T08008 (1-228) (2020). doi:10.1088/1748-0221/15/08/T08008, The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE's physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology., Published by Inst. of Physics, London

Published
2020

50. Experimental investigation on performance of cantilever CFRP-wrapped circular RC columns under lateral low-velocity impact

Author

Cristoforo Demartino, Y. Xiao, Jinjun Xu, B. Shan, YeongAe Heo, Xu, J. J., Demartino, C., Shan, B., Heo, Y. A., and Xiao, Y.

Subjects
Pier, Materials science, Cantilever, Impact response, Seismic retrofit, business.industry, Cantilever column, 02 engineering and technology, Structural engineering, Bending, 021001 nanoscience & nanotechnology, Bridge pier, Shear (sheet metal), Reinforced concrete, Transverse plane, 020303 mechanical engineering & transports, Brittleness, 0203 mechanical engineering, Ceramics and Composites, CFRP, 0210 nano-technology, business, Reduction (mathematics), Civil and Structural Engineering
Abstract

The main goal of this study is to investigate the effectiveness of seismic retrofit using CFRP wrapping in reducing the damage and preventing the failure of RC bridge piers under vehicular impacts. This paper reports the results of an experimental investigation on the performance of cantilever CFRP-wrapped circular RC columns under lateral low-velocity impact. To this aim, a total of nine 1/3-scale cantilever columns without axial load, comprising three types of shear-deficient RC columns with different reinforcement layout, were tested in a horizontal collision facility at two different impact velocities. The columns were tested in plain configuration (0 plies) and two wrapped configurations with 2 and 4 plies of CFRP. Generally, for plain columns, brittle shear-type damage was observed. Larger damage was obtained by increasing the impact velocity and decreasing the amount of transverse reinforcements while the variation of the amount of longitudinal steel bars has a negligible effect. The experimental results demonstrate that seismic retrofit using CFRP can provide an effective solution to convert the failure mechanism under lateral impact loading, from shear- to flexural-dominated, with a reduction of the impact damage. This strategy has a beneficial effect given sufficient bending capacity of the plain RC column.

Published
2020

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