Search

Unknown surface material classification can inform a robot about material properties, enabling it to interact with environments appropriately. Recent research has leveraged multimodal data using deep learning to improve the performance of surface material classification. In this paper, we present a deep learning model, multimodal temporal convolutional neural network (MTCNN), which integrates energy spectrum, dilated convolutions, and sequence poolings into a unified network architecture. The proposed model can learn material representations from auditory and multi-tactile (i.e., acceleration, normal force, and friction force) data generated by dragging a tool along surfaces, and distinguish unknown object surface materials into categories. For surface material data collection, a tool is also designed to detect different object surfaces. The performance of MTCNN is evaluated on a public dataset and the highest classification accuracy is 87.55%. A robotic curling example is provided to illustrate how the presented model helps the robot in manipulation.

We propose and demonstrate a photonic delay line based carrier suppression interferometer system for measuring the phase noise of microwave sources. We show both theoretically and experimentally for the first time that carrier suppression is capable of suppressing the effects of the residual phase noise of the microwave amplifiers and the relative intensity noise of light in the system by up to 70 dB, and therefore effectively eliminates the contributions of these noise sources to the noise floor of the phase noise measurement system. Using a 2-km photonic delay line, we achieved phase noise measurement floors of −126 dBc/Hz at 1 kHz and −152 dBc/Hz at 10 kHz around a 10 GHz carrier, respectively, which are 15 and 20 dB lower than those of a frequency discriminator based phase noise measurement system using the same length of fiber delay and the same optical and microwave components. The noise floor of −152 dBc/Hz at 10 kHz is also 8 dB and 17 dB lower than those of a Keysight E5052B phase noise measurement system with 100-times cross-correlation and without cross-correlation, respectively. Even lower phase noise floors are expected for such a carrier suppression system if microwave phase shifters with lower residual phase noise or a longer photonics delay line are used.

Tubular thin-walled structure has attracted more and more attention because of its light weight and energy absorption characteristic, and has been widely applied to the fields of aerospace and auto...

STUDY OBJECTIVES This study aimed to establish a population pharmacokinetic (PPK) model of intravenous voriconazole (VRC) in critically ill patients with liver dysfunction and to explore the optimal dosing strategies in specific clinical scenarios for invasive fungal infections (IFIs) caused by common Aspergillus and Candida species. DESIGN Prospective pharmacokinetics study. SETTING The intensive care unit in a tertiary-care medical center. PATIENTS A total of 297 plasma VRC concentrations from 26 critically ill patients with liver dysfunction were included in the PPK analysis. METHODS Model-based simulations with therapeutic range of 2-6 mg/L as the plasma trough concentration (Cmin ) target and the free area under the concentration-time curve from 0 to 24 h (ƒAUC24 ) divided by the minimum inhibitory concentration (MIC) (ie, ƒAUC24 /MIC) ≥25 as the effective target were performed to optimize VRC dosing regimens for Child-Pugh class A and B (CP-A/B) and Child-Pugh class C (CP-C) patients. RESULTS A two-compartment model with first-order elimination adequately described the data. Significant covariates in the final model were body weight on both central and peripheral distribution volume and Child-Pugh class on clearance. Intravenous VRC loading dose of 5 mg/kg every 12 h (q12h) for the first day was adequate for CP-A/B and CP-C patients to attain the Cmin target at 24 h. The maintenance dose regimens of 100 mg q12h or 200 mg q24h for CP-A/B patients and 50 mg q12h or 100 mg q24h for CP-C patients could obtain the probability of effective target attainment of >90% at an MIC ≤0.5 mg/L and achieve the cumulative fraction of response of >90% against C. albicans, C. parapsilosis, C. glabrata, C. krusei, A. fumigatus, and A. flavus. Additionally, the daily VRC doses could be increased by 50 mg for CP-A/B and CP-C patients at an MIC of 1 mg/L, with plasma Cmin monitored closely to avoid serious adverse events. It is recommended that an appropriate alternative antifungal agent or a combination therapy could be adopted when an MIC ≥2 mg/L is reported, or when the infection is caused by C. tropicalis but the MIC value is not available. CONCLUSIONS For critically ill patients with liver dysfunction, the loading dose of intravenous VRC should be reduced to 5 mg/kg q12h. Additionally, based on the types of fungal pathogens and their susceptibility to VRC, the adjusted maintenance dose regimens with lower doses or longer dosing intervals should be considered for CP-A/B and CP-C patients.

Wearable pressure sensors have drawn significant attention because of their extensive applications in motion detection, tactile sensing, and health monitoring. However, the complex manufacturing process and high cost of active materials make low-cost, large-scale production elusive. In this work, we report a flexible piezoresistive pressure sensor assembled with two 3D laser-induced graphene (LIG) foam electrodes on a polyimide thin film from a simple laser scribing process in the ambient environment. The design of the air gap between the two foam electrodes allows the sensor to showcase a low limit of detection of 0.274 Pa, which provides favorable sensing performance in motion detection and wrist pulse monitoring. The addition of spherical MoS2 nanoparticles between the two foam electrodes further enhances the sensitivity to 88 kPa−1 and increases the sensing range to significantly outperform the previous literature reports. The demonstrated LIG pressure sensors also exhibit fast response/recovery rates and excellent durability/repeatability.

As a non-destructive buckling experimental technique, the vibration correlation technique (VCT) is extensively applied in buckling load prediction of columns, plates and shells under axial compression load. Following the experimental steps of VCT, the VCT can be numerically implemented and used as a numerical prediction method for buckling load. The effectiveness and efficiency of the numerical-based VCT in buckling load prediction of cylindrical shells under combined loading conditions are studied. Firstly, VCT formulas are presented for cylindrical shells under combined loading conditions. Then, a concurrent computing framework is established for the numerical implementation of VCT, which is able to improve the repeated eigenvalue analysis efficiency in VCT. Three illustrative examples are carried out to verify the effectiveness of the concurrent VCT, including the cylindrical shell under external pressure and axial compression, the cylindrical shell under internal pressure and axial compression, and the cylindrical shell under torque and axial compression. Compared with results of buckling tests, explicit dynamic method and Riks method, the proposed concurrent VCT is verified to have high computational efficiency and prediction accuracy. In conclusion, the concurrent VCT is verified to be an efficient and promising numerical method for buckling analysis of cylindrical shells under combined loading conditions.

X-ray diffractometer, field emission scanning electron microscope (SEM, Hitachi S-4800), laser confocal micro-region Raman spectrometer and vibration sample magnetometer were used to systematically study the effects of polyethyleneimine concentrations and exposure time on the morphology and size of ZnO nanowire arrays. The photoelectric property and the relationship between the morphology of nanowire arrays and ferromagnetism at room temperature were also analyzed. Under 15 min exposure time, when the polyethyleneimine concentration is 2.25 g / L, the obtained ZnO nanowire array film exhibits the smallest size, the optimal density and vertical orientation. According to the study of luminescence and room temperature magnetism, it is shown that the optical and ferromagnetic property are related to the variation tendency of oxygen defects and surface defects of the ZnO nanowires.

Yes-associated protein (YAP), as a co-activator of transcription factors, is a downstream protein in the Hippo signaling pathway with important functions in cell proliferation, apoptosis, invasion and migration. YAP also plays a key role in the development of CCl4-induced liver fibrosis. However, the mechanism of YAP during hepatic fibrosis progression and reversion is still unclear. Mild liver fibrosis was developed after 4 months of high-fat diet (HFD) stimulation, and we found that the YAP signaling pathway was activated. Here, we aim to reveal whether specific knockout of Yap gene in the liver can improve liver fibrosis induced by insulin resistance (IR) stimulated by HFD, and further explain its specific mechanism. We found that liver-specific Yap gene knockout improved IR-induced liver fibrosis and liver dysfunction, and this mechanism is related to the inhibition of the insulin signal pathway at the FoxO1 level. These findings provide a new insight, and Yap is expected to be a new target to reverse the early stage of liver fibrosis induced by IR.

Aeronautical Engineering Technology (AET) of Purdue University’s School of Aviation and Transportation Technology offers its students a comprehensive and holistic approach to engineering in an applied fashion. Students’ learning outcome includes an application of technical knowledge and hands-on skills in areas of aerospace design, operations, and manufacturing. The curriculum of the program includes a course in which students must learn advanced maintenance concepts and practices including the overhaul of reciprocating engines. This study examined the relationship between engine operational vs. non-operational statuses, time spent to finish a task, and student perceived workloads regarding the maintenance procedures. The tests followed the Federal Aviation Administration (FAA) requirements for the practical test questions from the Airframe and Powerplant Certificate (A&P) Exam. Students were also required to fill out a task perceived load index developed and used by NASA.

We demonstrate luminescent solar concentrators (LSCs) based on colloidal silicon quantum dots (SiQDs) as UV-selective fluorophores and coupled with front-facing silicon photovoltaic cells for the solar window application. The visibly transparent LSC composed of a thin layer of liquid SiQD suspension sandwiched between two thin glass slabs constitutes the windowpane, while strips of silicon photovoltaic cells with their front surfaces adhering to the LSC rear surface form the window frame. Furthermore, the LSC perimeter is surrounded by reflecting mirrors for preventing the fluorescence from leaking out through the edges. The SiQDs dispersed in 1-octadecene selectively absorb UV light and re-emit red fluorescence with quantum efficiency about 40%. Owing to the negligible overlap between the absorbance and photoluminescence spectra, the reabsorption effect is insignificant. The front-facing silicon photovoltaic strips located at the window frame can produce electricity by harvesting not only solar radiation but also the SiQD-generated fluorescence propagating from the windowpane. For the SiQD-LSC with the total light absorbing area equal to 12 cm × 12 cm and the reflecting mirrors tilted 45°, an overall power conversion efficiency of 2.47% under simulated sunlight can be obtained of which about 6% is contributed by the SiQD fluorescence. Meanwhile, the SiQD-LSC retains high spectral quality with average visible transmission and color rendering index through the windowpane equal to 86% and 94, respectively.

Preferable treatments for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) with brain metastasis are elusive. The study intended to estimate the relative efficacy and safety of systemic therapies. Clinical trials about therapies for EGFR-mutant, brain-metastatic NSCLC were identified. Progression-free survival (PFS) and overall survival (OS) were analysed using random effects Bayesian network meta-analyses (NMAs) on the hazard ratio (HR)-scale. Nomogram and Kaplan-Meier plots based on clinical or individual factors are displayed using data obtained from the Surveillance Epidemiology and End Results (SEER) database. Third-generation EGFR- tyrosine kinase inhibitors (EGFR-TKI) (osimertinib), EGFR-TKIs + stereotactic radiosurgery (SRS)/whole brain radiotherapy (WBRT) (gefitinib/erlotinib + SRS/WBRT), and EGFR-TKIs (erlotinib) + anti-vascular endothelial growth factor receptor (anti-VEGFR) (bevacizumab) achieved superior PFS (HR: 0.30 (0.15-0.59); HR: 0.47 (0.31-0.72); HR: 0.50 (0.21-1.21) vs. deferring SRS/WBRT) and acceptability; EGFR-TKIs + SRS/WBRT was top ranking (vs. others) for OS followed by third-generation EGFR-TKI. In the dataset cohort of 1173 brain-metastatic NSCLC patients, the 6-month, 1-year, and 3-year survival rates were 59.8%, 41.3%, and 5.6%, respectively. Race and origin, and year of diagnosis were independent predictors of OS. Survival curves showed that the OS of patients varied significantly by histology and race. Third-generation EGFR-TKI and EGFR-TKIs + SRS/WBRT are more effective and potentially acceptable for EGFR-mutant NSCLC with brain metastases balancing OS and PFS. Surgeries without adjuvant therapies cannot significantly improve the OS of brain-metastatic NSCLC patients. The study highlights importance of osimertinib in these patients and provide a reference for clinical treatments.

Gliomas are infiltrative neoplasms with a highly invasive nature. Due to its distinct genomic, genetic and epigenetic features, the immune prognostic signature (IPS) and immune microenvironment of glioblastoma (GBM) merit further research. We aimed to explore prognosis-related immune genes and develop an IPS model for predicting prognosis in GBM. RNA-sequencing data, as well as clinical information, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) public cohorts were analyzed. To develop the IPS, least absolute shrinkage and selection operator (LASSO) Cox analysis was performed for immune-related genes that were differentially expressed between GBM and normal tissues. Then, interaction effects of the IPS on the immune microenvironment were systematically analyzed; the precise prognostic model was developed based on the IPS and clinical data and was then further validated. A total of 21 immune prognostic genes were identified based on GBM microenvironment status. An 8-gene IPS was established, and the GBM patients were effectively stratified into low- and high-risk groups in the TCGA cohort as a training set. Univariate and multivariate Cox analyses revealed that IPS was an independent prognostic factor, and the prognostic performance of individual IPS genes was systematically illustrated. In addition, a comprehensive and novel nomogram model was initially established to estimate overall survival in TCGA-GBM patients, and high-risk patients had higher levels of dendritic cell and neutrophil infiltration. Furthermore, the nomogram model was developed and validated in the CGGA validation set. The low-risk IPS was linked to a stronger response to anti-PD-L1 immunotherapy and clinical advantages in the IMvigor210 cohort. This novel IPS with promising biomarkers classifies GBM patients into subgroups with distinct clinical outcomes and immunophenotypes. Our findings and this resource may help to characterize the immune microenvironment, inform cancer immunotherapy and facilitate the development of precision immuno-oncology.

In practical engineering, the design scheme is generally a compromise solution that meets various requirements. In most cases, the traditional optimization method provides a single optimized solution, which may be prone to fail during the subsequent design stage because some unpredictable requirements may be not considered in the preliminary optimization process. For example, maximizing fundamental frequency is generally regarded as the optimization objective for aerospace structures under the vibration environment in the preliminary design stage. However, the optimized solution may fail for strength, buckling, or other requirements during the subsequent detailed design stage. Therefore, it is crucial to provide multiple alternative solutions for insurance. In this paper, a diverse discrete material optimization (DDMO) framework is proposed for multi-patch laminates. It can optimize the material topology layout and fiber orientations of composite structures simultaneously and provide multiple alternative solutions that have diversity in design space and different potential performance. In this paper, a diversity index for discrete variables is proposed and the discrete material optimization (DMO) method with the diversity index constraint is employed to perform the DDMO. Two illustrative examples are used to verify the effectiveness of the proposed optimization framework, including a simple example of a composite plate and a complex engineering example of an S-shaped curved shell. Results indicate that, the proposed method can provide multiple diverse alternative solutions with similar performance in the optimization objective, which are verified to have better potential performance than the single solution by the traditional single design method. Moreover, multiple design options by the diverse optimization method can contribute to reducing the probability of redesign and shortening the design cycle.

Objective The current study aims to explore the establishment of the patient-derived tumor xenograft (PDTX) model. Materials and methods Twenty patients with gastric cancer, 10 males and 10 females, were enrolled in the current study. Firstly, the volume, invasion and metastasis of the xenografts were observed. Subsequently, the correlation between tumor tissues of the PDTX mouse model and the patients' primary tumor tissues was evaluated by pathological H&E staining and immunohistochemistry. Results The results showed that the PDTX models corresponding to 15 of the 20 patients were successfully established, and the success rate of PDTX model establishment was 75%. Furthermore, the PDTX models maintained the differentiation degree, morphological characteristics and structural characteristics of tumor cells. Conclusion A PDTX model can be used as a substitute for cancer patients in clinical practice and may be suitable for clinical pharmacodynamic screening and new drug development.

In recent years, deep learning has greatly improved the ability of wheatear detection. However, there are still three main problems in wheatear detection based on unmanned aerial vehicle (UAV) platforms. First, dense wheat plants often overlap, and the wind direction will blur the pictures, which obviously interferes with the detection of wheatears; second, due to the different maturity, color, genotype, and head orientation, the appearance will also be different; third, UAV needs to take images in the field and conduct real-time detection, which requires the embedded module to detect wheatears quickly and accurately. Given the above problems, we studied and improved YoloV4, and proposed a robust method for wheatear detection using UAV in natural scenes. For the first problem, we modified the network structure, deleted the feature map with a size of $19\times 19$ , and used k-means algorithm to re-cluster the anchors, and we proposed a method of prediction box fusion. For the second problem, we used the pseudo-labeling method and data augmentation methods to improve the generalization ability of the model. For the third problem, we simplified the network structure, replaced the original network convolution with the improved depthwise separable convolution, and proposed an adaptive ReLU activation function to reduce the amount of calculation and speed up the calculation. The experimental results showed that our method can effectively mark the bounding of wheatears. In test sets, our method achieves 96.71% in f1-score, which is 9.61% higher than the state of the art method, and the detection speed is 23% faster than the original method. It can be concluded that our method can effectively solve the problems of wheatear detection based on the UAV platform in natural scenes.

Automatic license plate recognition has a wide range of applications in intelligent transportation systems and is of great significance. However, most of the current work on license plate recognition focuses on the images on the front of license plates. license plate recognition in natural scenes and arbitrary perspective is still a huge challenge. To solve this problem, this work mainly studies the detection and recognition of inclined Chinese license plates in natural scenes. We propose a robust method that can detect and correct multiple license plates with severe distortion or skewing in one image and input them into the license plate recognition module to obtain the final result. Different from the existing methods of license plate detection and recognition, our method performs affine transformation during license plate detection to rectify the distorted license plate image. It can not only avoid the accumulation of intermediate errors but also improve the accuracy of recognition. As an additional contribution, we put forward a challenging Chinese license plate recognition data set, including images obtained from different scenes under a variety of weather conditions. Through a large number of comparative experiments, we have proved the effectiveness of our proposed method.

Oxygen-consuming fuel tank inerting technology is a novel technology with a simple structure and a high efficiency for tank explosion suppression based on flameless catalytic combustion. To...

Recent literature has demonstrated the improved data discovery and delivery efficiency gained through applying named data networking (NDN) to a variety of information-centric Internet of things (IoT) applications. However, from a data security perspective, the development of NDN-IoT raises several new authentication challenges. In particular, NDN-IoT authentication may require per-packet-level signatures, thus imposing intolerably high computational and time costs on the resource-poor IoT end devices. This paper proposes an effective solution by seamlessly integrating the lightweight and unforgeable physical-layer identity (PHY-ID) into the existing NDN signature scheme for the mobile edge computing (MEC)-enabled NDN-IoT networks. The PHY-ID generation exploits the inherent signal-level device-specific radio-frequency imperfections of IoT devices, including the in-phase/quadrature-phase imbalance, and thereby avoids adding any implementation complexity to the constrained IoT devices. We derive the offline maximum entropy-based quantization rule and propose an online two-step authentication scheme to improve the accuracy of the authentication decision making. Consequently, a cooperative MEC device can securely execute the costly signing task on behalf of the authenticated IoT device in an optimal manner. The evaluation results demonstrate 1) elevated authentication time efficiency, 2) robustness to several impersonation attacks including the replay attack and the computation-based spoofing attack, and 3) increased differentiation rate and correct authentication probability by applying our integration design in MEC-enabled NDN-IoT networks.

The thermal design of detectors can effectively reduce problems caused by high-power consumption, such as shortened detector life, accuracy reduction, and chip damage. However, the traditional numerical model for the thermal design of detector arrays is difficult to construct and solve accurately, requiring a complex model structure, massive grid division, and considerable computation. In this study, a novel thermal design method, called the unit–array equivalent method (UAEM), is proposed for the thermal design of detector arrays consisting of multiple complex repetitive detector units. The method can simplify the detector unit structure in an array by using an equivalent approach for ensuring model accuracy. The effectiveness of the method is verified through numerical experiments on heat conductivity, surface gas, and surface radiation. Meanwhile, this method is used to study the ALICE Inner Tracking System, and the equivalence and correlation of UAEM are examined. Compared with the model constructed by traditional methods, this method saves 95% of the calculation time. At the same time, the average error between the equivalent model and the experiment is within 0.35 °C. This method solves the contradiction between model accuracy and computation. Thus, an accurate and fast numerical approach for the thermal analysis of detector arrays is provided.

Background It is very difficult to predict the early response to NAC only on the basis of change in tumor size. ADC value derived from DWI promises to be a valuable parameter for evaluating the early response to treatment. This study aims to establish the optimal time window of predicting the early response to neoadjuvant chemotherapy (NAC) for different subtypes of locally advanced breast carcinoma using diffusion-weighted imaging (DWI). Methods We conducted an institutional review board-approved prospective clinical study of 142 patients with locally advanced breast carcinoma. All patients underwent conventional MR and DW examinations prior to treatment and after first, second, third, fourth, sixth and eighth cycle of NAC. The response to NAC was classified into a pathologic complete response (pCR) and a non-pCR group. DWI parameters were compared between two groups, and the optimal time window for predicting tumor response was established for each chemotherapy regimen. Results For all the genomic subtypes, there were significant differences in baseline ADC value between pCR and non-pCR group (p

ObjectiveTo establish a radiomics signature and a nomogram model based on enhanced CT images to predict the Ki-67 index of lung cancer.MethodsFrom January 2014 to December 2018, 282 patients with lung cancer who had undergone enhanced CT scans and Ki-67 examination within 2 weeks were retrospectively enrolled and analyzed. The clinical data of the patients were collected, such as age, sex, smoking history, maximum tumor diameter and serum tumor markers. Our primary cohort was randomly divided into a training group (n=197) and a validation group (n=85) at a 7:3 ratio. A Ki-67 index ≤ 40% indicated low expression, and a Ki-67 index > 40% indicated high expression. In total, 396 radiomics features were extracted using AK software. Feature reduction and selection were performed using the lasso regression model. Logistic regression analysis was used to establish a multivariate predictive model to identify high and low Ki-67 expression in lung cancer. A nomogram integrating the radiomics score was established based on multiple logistic regression analysis. Area under the curve (AUC) was used to evaluate the prediction efficiency of the radiomics signature and nomogram.ResultsThe AUC,sensitivity, specificity and accuracy of the radiomics signature in the training and validation groups were 0.88 (95% CI: 0.82~0.93),79.2%,84.3%,81.2% and 0.86 (95% CI: 0.78~0.94),74.6%,88.1%,79.8%, respectively. A nomogram combining radiomics features and clinical risk factors (smoking history and NSE) was developed. The AUC, sensitivity, specificity and accuracy were 0.87 (95% CI: 0.80~0.95), 75.0%, 90.2% and 83.5% in the validation group, respectively.ConclusionThe radiomics signature and nomogram based on enhanced CT images provide a way to predict the Ki-67 expression level in lung cancer.

BackgroundChronic rejection characterized by chronic allograft vasculopathy (CAV) remains a major obstacle to long-term graft survival. Due to multiple complicated mechanisms involved, a novel therapy for CAV remains exploration. Although mesenchymal stromal cells (MSCs) have been ubiquitously applied to various refractory immune-related diseases, rare research makes a thorough inquiry in CAV. Meanwhile, melatonin (MT), a wide spectrum of immunomodulator, plays a non-negligible role in transplantation immunity. Here, we have investigated the synergistic effects of MT in combination with MSCs in attenuation of CAV.MethodsC57BL/6 (B6) mouse recipients receiving BALB/c mouse donor aorta transplantation have been treated with MT and/or adipose-derived MSCs. Graft pathological changes, intragraft immunocyte infiltration, splenic immune cell populations, circulating donor-specific antibodies levels, cytokine profiles were detected on post-operative day 40. The proliferation capacity of CD4+ and CD8+ T cells, populations of Th1, Th17, and Tregs were also assessed in vitro.ResultsGrafts in untreated recipients developed a typical pathological feature of CAV characterized by intimal thickening 40 days after transplantation. Compared to untreated and monotherapy groups, MT in combination with MSCs effectively ameliorated pathological changes of aorta grafts indicated by markedly decreased levels of intimal hyperplasia and the infiltration of CD4+ cells, CD8+ cells, and macrophages, but elevated infiltration of Foxp3+ cells. MT either alone or in combination with MSCs effectively inhibited the proliferation of T cells, decreased populations of Th1 and Th17 cells, but increased the proportion of Tregs in vitro. MT synergized with MSCs displayed much fewer splenic populations of CD4+ and CD8+ T cells, Th1 cells, Th17 cells, CD4+ central memory T cells (Tcm), as well as effector memory T cells (Tem) in aorta transplant recipients. In addition, the percentage of splenic Tregs was substantially increased in the combination therapy group. Furthermore, MT combined with MSCs markedly reduced serum levels of circulating allospecific IgG and IgM, as well as decreased the levels of pro-inflammatory IFN-γ, TNF-α, IL-1β, IL-6, IL-17A, and MCP-1, but increased the level of IL-10 in the recipients.ConclusionsThese data suggest that MT has synergy with MSCs to markedly attenuate CAV and provide a novel therapeutic strategy to improve the long-term allograft acceptance in transplant recipients.

Background. Circulating tumor cells (CTCs) have been regarded as an independent prognostic marker for metastatic castration-resistant prostate cancer (mCRPC). Its prognostic value, however, in nonmetastatic prostate cancer (NMPC) is still unclear. Purpose. To elucidate whether CTCs can predict the biochemical recurrence (BCR) in NMPC patients following radical prostatectomy (RP) or radiotherapy (RT). Methods. PubMed, Cochrane Database, and Embase and the references in relevant studies were systematically searched. Studies that investigated the correlation of CTCs and BCR in NMPC patients after RP or RT were identified and reviewed. Overall odds ratio (OR) of BCR in such patients with/without CTCs was pooled. We also calculated and pooled overall prevalence of BCR in such CTC-positive patients. Results. In total, 12 studies comprising 1917 participants were eligible for the meta-analysis and showed that the presence of secondary circulating tumor cells (SCTCs) is associated with a higher BCR rate of 59% (95% CI: 22%-88%) in patients with NMPC after RP or RT ( OR = 6.12 ; 95% CI: 2.22-16.85; P < 0.001 ). However, regardless of the presence of primary circulating tumor cells (PCTCs), it has not been shown to be associated with higher BCR. Conclusions. Our research demonstrated that SCTC-positive patients are associated with higher BCR compared to SCTC-negative patients in NMPC. Therefore, it is recommended that NMPC patients undergo CTC surveillance intensively after RP or RT.

The existing micro-motion stage based on flexure hinge can hardly meet the requirements of a high-precision stage with large stroke and variable operating conditions (especially variable frequency operation). In this paper, a flexible hinge micro-motion stage with adjustable stiffness is presented. A wide range of stiffness and frequency adjustments are realized by changing the length of the flexure hinge through the movement of the support. However, the change on the stiffness of the flexure hinge is non-linear when is in large deformation. It is difficult to use the traditional PID algorithm to control such nonlinear system without the complete mathematical model, and much more complicated control strategies are required to deal with the condition of large deformation of the flexure hinge. In this paper, the active disturbance rejection control (ADRC) strategy is adopted to solve the above non-linear control problem without relying on the complete system model. A novel model-compensated ADRC based on the dynamic characteristics is proposed to further improve the performance of the micro-motion stage. Experiments show that the ADRC with model compensation (MADRC) can achieve high positioning and tracking precision faster than the conventional ADRC. The presented micro-motion stage based on stiffness-adjustable flexure hinges and MADRC design is capable to meet the industrial application requirements of large stroke or variable working conditions.

BackgroundThere have been reports of increasing azole resistance in Candida tropicalis, especially in the Asia-Pacific region. Here we report on the epidemiology and antifungal susceptibility of C. tropicalis causing invasive candidiasis in China, from a 9-year surveillance study.MethodsFrom August 2009 to July 2018, C. tropicalis isolates (n = 3702) were collected from 87 hospitals across China. Species identification was carried out by mass spectrometry or rDNA sequencing. Antifungal susceptibility was determined by Clinical and Laboratory Standards Institute disk diffusion (CHIF-NET10–14, n = 1510) or Sensititre YeastOne (CHIF-NET15–18, n = 2192) methods.ResultsOverall, 22.2% (823/3702) of the isolates were resistant to fluconazole, with 90.4% (744/823) being cross-resistant to voriconazole. In addition, 16.9 (370/2192) and 71.7% (1572/2192) of the isolates were of non-wild-type phenotype to itraconazole and posaconazole, respectively. Over the 9 years of surveillance, the fluconazole resistance rate continued to increase, rising from 5.7 (7/122) to 31.8% (236/741), while that for voriconazole was almost the same, rising from 5.7 (7/122) to 29.1% (216/741), with no significant statistical differences across the geographic regions. However, significant difference in fluconazole resistance rate was noted between isolates cultured from blood (27.2%, 489/1799) and those from non-blood (17.6%, 334/1903) specimens (P-value < 0.05), and amongst isolates collected from medical wards (28.1%, 312/1110) versus intensive care units (19.6%, 214/1092) and surgical wards (17.9%, 194/1086) (Bonferroni adjusted P-value < 0.05). Although echinocandin resistance remained low (0.8%, 18/2192) during the surveillance period, it was observed in most administrative regions, and one-third (6/18) of these isolates were simultaneously resistant to fluconazole.ConclusionThe continual decrease in the rate of azole susceptibility among C. tropicalis strains has become a nationwide challenge in China, and the emergence of multi-drug resistance could pose further threats. These phenomena call for effective efforts in future interventions.

This chapter summarizes the presentations of speakers addressing such issues during the Automated Vehicles Symposium 2020 (AVS20) held virtually on July 27–30, 2020. These speakers participated in the break-out session titled “Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities”. The corresponding discussion and recommendations are presented in terms of the lessons learned and the future research directions to be adopted to benefit from AI in order to develop safer and more efficient connected and automated vehicles (CAV). This session was organized by the Transportation Research Board (TRB) Committee on Traffic Flow Theory and Characteristics (ACP50) and the TRB Committee on Artificial Intelligence and Advanced Computing Applications (AED50).

Composite shells with complex geometry are widely used in aerospace structures. Due to the complexity of geometry and curvilinear fiber path, the analysis and optimization based on finite element analysis (FEA) for complex variable-stiffness (VS) shells is extremely time-consuming. By comparing with FEA, isogeometric analysis (IGA) exhibits higher prediction efficiency of buckling load. In this work, the formula of geometric stiffness matrix for complex VS shells is derived for the first time based on degenerated shell method using IGA, which is the basis of performing linear buckling analysis. Then, a new variable curvature quasi-linear function (VCQLF) to describe curvilinear fiber path is proposed, which can further expand the design space of VS shells. After that, two frameworks for shape optimization of complex shells are put forward and then compared, and it is found that the one based on LOFT function can provide representative control variables of shape and effectively reduces the number of design variables for complex shells. Finally, a novel collaborative optimization framework of fiber path and shell shape using IGA is established. By comparison of traditional methods, it is demonstrated that the proposed framework can greatly improve the efficiency of optimization and fully explore the buckling load of complex VS shells.

The surrogate-based optimization of hierarchical stiffened composite shells against buckling is a typical multimodal and multivariables optimization problem. To improve the computational efficiency...

Background Kawasaki disease (KD) is an acute multisystem vasculitic syndrome that predominantly affects infants and young children. Neurological complications are rare in patients with KD and the diagnosis is challenging. We report a case of KD that manifested as bilateral facial nerve palsy and meningitis. Case report A 6-month-old boy presented with a 10-day history of fever. Four days before admission, the patient developed a rash, conjunctival injection, perioral and perianal excoriation, and bilateral facial nerve palsy. Brain magnetic resonance imaging was normal. Echocardiography showed dilated coronary arteries and coronary artery aneurysms. A cerebrospinal fluid examination showed an elevated leukocyte count. A diagnosis of KD was made, and the patient was treated with gamma globulin and aspirin. The patient’s fever subsided on the following day and the right-sided facial nerve palsy was relieved 1 month later. An 18-month follow-up showed that the left-sided facial nerve palsy persisted and the patient’s condition remained stable. Conclusion KD manifesting as bilateral facial nerve palsy and meningitis is extremely rare. Clinicians should be aware of this condition, and early diagnosis and appropriate treatment should be emphasized.

Compared with traditional composite panels, the modeling, analysis and design of variable-stiffness panels with curvilinear fibers are much more complicated. Although the design flexibility is greatly enhanced, the design of variable-stiffness structures must meet manufacturing constraints to ensure that the designed structures can be fabricated finally. In order to design variable-stiffness composite panels that is very challenging due to its nonlinearity and non-convexity, a novel multi-stage design method for variable-stiffness panels is developed based on lamination parameters. First, lamination parameters are taken as design variables, and the stiffness distribution is obtained efficiently by few iterations. Next, the lamination parameters are transformed into actual layups. Finally, the realistic fiber path is regenerated by considering manufacturing constraints. In addition, the isogeometric analysis, which is more suitable for variable-stiffness structure, is used instead of the traditional finite element analysis to improve the analysis accuracy. Illustrative example demonstrates the high computational efficiency and optimization capacity of proposed method, compared to gradient-based algorithm and evolutionary algorithm.

For cylindrical shells under axial compression, the essence of initial geometric imperfections is the superposition of local out-of-plane deformations of various forms, which may facilitate the development of buckling deformations, thus leading to a significant knockdown of the load-carrying capacity. It is very challenging for existing methods to provide an accurate prediction of the lower bound on a load-carrying capacity before the structure is fabricated. Therefore, it is crucial to find a type of assumed imperfection that will allow us to approximate lower bounds for shells in the design stage. Five 1-m-diameter unstiffened shells, termed W1-W5, are designed, analysed and tested. The measured imperfection approach, single-perturbation load approach (SPLA), worst multiple-perturbation load approach (WMPLA), and a Combined Approach for measured imperfections and superimposed radial point load imperfections are compared with test results. The results show that the SPLA-based methods produce higher KDFs than the test results and are sensitive to the distribution of the measured imperfections. In contrast, the KDFs predicted by the WMPLA and the Combined Approach are similar to one another and very close to the test results. From the comparison results, it can preliminarily be concluded that the WMPLA is able to envelop the small- and large-amplitude measured imperfections, which has the potential to predict a rational lower bound on the buckling loads of unstiffened cylindrical shells. The WMPLA should be extended to the design of other types of thin-walled structures with caution, because the manufacturing signature may be distinctly changed for different processes, and the buckling tests of other types of structures would be carried out in future study.

To resist external pressure, stiffened spherical domes have been widely used in underwater vehicles. In traditional design of these thin-walled structures, uniform stiffeners are usually utilized and overly conservative safety factor method is employed to envelop the multi-source uncertainties mainly caused by manufacturing. In this study, a concept of non-uniformly stiffened spherical dome (NUSPD) is developed to improve the structural buckling capacity. Furthermore, an efficient reliability-based design optimization (RBDO) framework is established for NUSPD, which includes a deterministic optimization loop to fix the stiffener layout, and subsequently followed by a RBDO loop to determine the detailed stiffener dimensions and decrease the structural weight under geometric and material property uncertainties. Since the RBDO of stiffened spherical domes is very complex, an improved enhanced chaos control method together with surrogate model is proposed to improve the convergence rate. Finally, the efficiency of the proposed RBDO framework is demonstrated by the NUSPD example.

For cylindrical shell structures under axial compression, it is crucial to provide high-fidelity knockdown factors (KDFs) in preliminary design for aerospace and civil structures. In this paper, numerical studies of buckling response for composite cylindrical shell with geometric imperfections and embedded delamination imperfections are performed to predict the lower-bound buckling loads. Results indicate that composite shells with single dimple-shape geometric imperfection exhibit similar lower bound trend and buckling behavior as those with embedded delamination imperfection. It is found that the lower-bound buckling loads are much less conservative than the corresponding design recommendation from NASA SP-8007. And the effect of geometric imperfections can envelope that of delamination imperfections. Therefore, the worst multiple perturbation load approach (WMPLA) is performed to find the worst combination of dimple-shape geometric imperfections to predict the lower-bound buckling load, and the efficient global optimization (EGO) is employed to improve the computational efficiency of WMPLA. It is demonstrated that the improved WMPLA can provide an improved KDF by examples in open literature. Based on the improved KDFs, it is possible to increase the load-bearing efficiency of composite structures in practical engineering.

A full understand of the influential mechanism concerning electricity consumption has a crucial political reference significance for the implementation of energy conservation and consumption reduction policies. To solve the lack of correlation between the empirical results of the research regions in present researches, this paper takes China's electricity consumption from 1995 to 2016 as the research subject, uses Multi-period ST-LMDI model by setting a unified reference province as a benchmark for different regions in China to completely decompose the changes in China's electricity consumption, and further analyzes the influence mechanism of China's electricity consumption changes by combining the characteristics of the departments and regions. As the result, it's found that the economic growth has a strong impetus for power consumption while the technological progress can effectively curb it. Meanwhile, results of studying electricity consumption from the perspective of industry and region show that the economic structure and consumption intensity have obviously different influences in the eastern, central and western regions. So when it comes to formulate the policy for electricity development and reform, the characteristics of industrial structure as well as the regional differences must be taken into consideration.

BACKGROUND The aim of this study was to assess the correlations of Twist expression with pathological and computed tomography (CT) characteristics and prognosis of non-small cell lung cancer (NSCLC). MATERIAL AND METHODS We enrolled 120 patients with lung cancer who underwent CT examination. The Twist protein expression level was detected in 120 cases of cancer tissues and a control group using immunohistochemical method. The survival curve was plotted using the Kaplan-Meier method and analyzed via log-rank test. RESULTS The Twist expression was associated with tumor stage, differentiation degree, and presence or absence of lymph node metastasis, but had no correlations with sex, age, or histological type. Grade-3 bronchial involvement, pleural indentation, and hilar and mediastinal lymph node enlargement occurred more frequently in the high-expression Twist group compared with the low-expression Twist group. The overall survival rate of patients with Twist overexpression was significantly lower than that of patients with normal Twist expression. The mean survival time was 69.8 months in Twist protein expression-negative patients and 45.8 months in Twist protein expression-positive patients. Finally, the positive expression of Twist protein was significantly correlated with the long-term survival and prognosis of patients. CONCLUSIONS The Twist gene might be involved in the occurrence and development of NSCLC, which is correlated with patient prognosis.

It was previously reported that a tube holding chitosan carriers loaded with neurotrophin-3 (NT-3), after insertion into a 5 mm long transection gap in the adult rat spinal cord, triggered de novo neural tissue generation and functional recovery. Here, we report an effort to validate these findings using stringent blinding methodologies, which are crucial for robustness in reproducing biomedical studies. Radio frequency identification (RFID) chips were utilized to label rats that were randomly assigned into three experimental groups: transection with chitosan-NT-3 implant (C-NT3), transection only (T-controls), and laminectomy only (S-controls), blinding the experimenters to the treatments. Three months after surgery, animals only known by their RFID were functionally, electrophysiologically, and anatomically assessed. The data were then collected into the proper groups and statistically analyzed. Neural tissue with nestin-, Tuj1-, and NeuN-positive cells was found bridging the transection gap in C-NT3 rats, but not in T-controls. Motor- and somatosensory-evoked potentials were detected in C-NT3 rats and S-controls, but not in T-controls. Hind limb movement was significantly better in C-NT3 rats compared with T-controls. Our validation study indicates that C-NT3 implants facilitate neural tissue generation, at least in part, by eliciting endogenous neurogenesis. Our data support the use of C-NT3 implants for tissue remodeling in the injured spinal cord.

The dynamic evolution characteristic of the bond strength at the interface of a bolt and a rock mass under an axial tensile load and the mechanical behavior of fully grouted bolts in situ were investigated considering the non-uniform stress of the surrounding rock along the bolts. A new dynamic bond-slip model was first proposed to describe the dynamic evolution characteristic of the bond strength at bolt-rock interfaces. Based on the proposed dynamic bond-slip model, analytical solutions of the shear stress distribution along the bolts, load-displacement relationship, and relative displacement considering the slip of the free end were developed. Then, incorporating the non-uniform normal stress of the surrounding rock along the bolts, the shear stress distribution and load-displacement behavior of the fully grouted bolts were presented. Moreover, analytical approaches were also proposed for determining the stress distribution along the bolt and rock deformation in cases of in situ prestressed and non-prestressed bolts. The proposed model and analytical solution were validated by published results from laboratory model tests and in situ tests , respectively. The new analytical solution completes the theoretical framework for addressing the fundamental problem of fully grouted bolts in pull-out tests and in situ rock masses and provides a useful theoretical tool that can potentially be applied to bolt design and laboratory and in situ testing .

For composite panels with cutouts, curvilinear fiber path can adjust the in-plane stiffness distribution to increase the buckling resistance, but it results in huge computational cost for the buckling analysis when FEA is employed. In this study, variable-stiffness panels with cutouts are analyzed via isogeometric method, where cutouts are represented by the level set method . The method for suppressing artificial buckling modes is proposed to improve the prediction accuracy. Moreover, the analytical sensitivity is derived to facilitate fiber path optimization, and a new bi-level optimization framework considering manufacturing constraints is established. Finally, the proposed method is verified by variable-stiffness aircraft panel with multiple cutouts, which can not only provide an accurate prediction of buckling load, but also exhibit high convergence rate and low computational cost for fiber path optimization.

Most special-use freeway lanes, such as High Occupancy Vehicle (HOV) lanes, have traditionally been designed with either limited access or continuous access control from the adjacent general-purposed (GP) lanes. Studies have shown the advantages and disadvantages of each design in terms of safety, mobility, environment, and enforcement, among other factors. With a focus on improving the operational performance of HOV facilities, this paper proposes a new design called partially limited access control where the continuous access is mostly designated along the freeway to achieve higher travel speed while buffers between the HOV lane(s) and the adjacent GP lanes are strategically placed on selected freeway segments to accommodate higher throughput on those segments. The placement of buffers primarily aims to reduce the impact of HOV cross-weave flow on the capacity of GP lanes. In this research paper, a methodology for determining the location and length of buffers in the partially limited access control has been developed. A case study is performed along a 13-mile section of HOV facility on SR-210 E in Southern California, which is coded and evaluated in traffic microsimulation. The results show that the partially limited access control increases the throughput (represented by total vehicle miles traveled or VMT) and decreases the delay (represented by total vehicle hours traveled or VHT) of the freeway as compared with either the limited access or continuous access control. As a result, the overall efficiency (represented by average travel speed calculated as VMT/VHT) of the freeway with partially limited access HOV facility is 21% and 6% higher than that of the freeway with limited access and continuous access HOV facility, respectively, under the baseline traffic demand.

A new design strategy through the synergy of Mo(VI)–Mo(V) intervalence charge transfer and π(radical)–π(radical/cation) interactions is proposed to obtain semiconductors with photoresponsive ranges covering the whole UV–SWIR (ultraviolet–shortwave near-infrared; ca. 250–3000 nm) region. With this strategy, a viologen-based molybdate semiconductor with a UV–SWIR photoresponsive range was obtained through UV/X-ray irradiation or thermal annealing. The thermally annealed semiconductor has the highest conversion and the best photocurrent response in the range of 355–2400 nm.

Aiming at the problem of low utilization rate and low intelligent degree of agricultural irrigation water, this paper proposes a water-saving agricultural adaptive irrigation system based on WSN and intelligent communication technology. The scheme integrates the embedded system technology, ZigBee wireless networking, GPRS transmission and automatic control technology, etc. From the overall system architecture, hardware application and software design, and the operation mechanism of the whole system are explained. Then, the key technologies of each function module design, such as data acquisition, wireless transmission, Zibee development, remote monitoring and so on, are provided. Finally, the simulation test of each part of the system is performed in the laboratory environment. The test results show that the intelligent farmland irrigation water-saving control system designed in this paper has good adaptability and stability, and greatly saves agricultural water consumption.