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Introduction Combined chemotherapy and radiotherapy increases long term survival in patients with nasopharyngeal carcinoma. However, radiotherapy of the carotid sinus or brain stem can evolve labile hypertension and orthostatic intolerance from chronic baroreflex failure. Diabetes would also cause this neuropathy. Management of patients with Supine hypertension-Orthostatic hypotension can be very challenging. Methods A case report was done on a 71-year-old man with metastatic nasopharyngeal carcinoma status post radiation therapy who was admitted with severe supine hypertension-orthostatic hypotension. Patient was managed with both non-pharmacological and pharmacological methods, and monitored for postural symptoms, complications of severe supine hypertension—which has been linked to left ventricular hypertrophy and kidney dysfunction, and placed on 24 hour ambulatory blood pressure monitoring to aid in management so as to prevent hypertension induced organ damage. Results This review outlines the pathophysiology of Supine hypertension-Orthostatic hypotension, treatment complications and potential management strategies recommendations for this group of patients. It revealed the benefit of having a 24 hour ambulatory blood pressure monitoring, which provides insight on the timing and magnitude of an individual’s blood pressure fluctuations throughout the day so as to further guide management. Conclusion Chronic baroreflex failure is a late sequela of neck irradiation for naso-pharyngeal carcinoma due to accelerated atherosclerosis in the region of the carotid sinus baroreceptor. Treatment goal is achieved with adequate control of pre-syncopal symptoms and prevention of long term complications. Non-pharmacological interventions remain the first line of therapy, followed by pharmacological interventions as necessary. Nonetheless, management of blood pressure in these elderly patients with baroreflex dysfunction remains challenging and should be individualized. Moving forward, a prospective study on the incidence of late onset, iatrogenic baroreflex failure as a late complication of neck irradiation and its particular relationship to carotid arterial rigidity should be conducted to increase awareness, timely diagnosis and management of the condition among physicians.

Klebsiella pneumoniae carbapenemases (KPC-2 and KPC-3) present a global clinical threat, as these β-lactamases confer resistance to carbapenems and oxyimino-cephalosporins. Recent clinically identified KPC variants with substitutions at Ambler position D179, located in the Ω loop, are resistant to the β-lactam/β-lactamase inhibitor combination ceftazidime-avibactam, but susceptible to meropenem-vaborbactam. To gain insights into ceftazidime-avibactam resistance conferred by D179N/Y variants of KPC-2, crystal structures of these variants were determined. The D179N KPC-2 structure revealed that the change of the carboxyl to an amide moiety at position 179 disrupted the salt bridge with R164 present in wild-type KPC-2. Additional interactions were disrupted in the Ω loop, causing a decrease in the melting temperature. Shifts originating from N179 were also transmitted toward the active site, including ∼1-Å shifts of the deacylation water and interacting residue N170. The structure of the D179Y KPC-2 β-lactamase revealed more drastic changes, as this variant exhibited disorder of the Ω loop, with other flanking regions also being disordered. We postulate that the KPC-2 variants can accommodate ceftazidime because the Ω loop is displaced in D179Y or can be more readily displaced in D179N KPC-2. To understand why the β-lactamase inhibitor vaborbactam is less affected by the D179 variants than avibactam, we determined the crystal structure of D179N KPC-2 in complex with vaborbactam, which revealed wild-type KPC-2-like vaborbactam-active site interactions. Overall, the structural results regarding KPC-2 D179 variants revealed various degrees of destabilization of the Ω loop that contribute to ceftazidime-avibactam resistance, possible substrate-assisted catalysis of ceftazidime, and meropenem and meropenem-vaborbactam susceptibility.

Introduction'Real-world' data for mold-active triazoles (MATs) in the treatment of invasive fungal infections (IFIs) are lacking. This study evaluated usage of MATs in a disease registry for the management of IFIs.MethodsData were collected for this multicenter, observational, prospective study from 55 US centers, between March 2017 and April 2020. Eligible patients received isavuconazole, posaconazole, or voriconazole as MAT monotherapy (one MAT) or multiple/sequenced MAT therapy (more than one MAT) for prophylaxis or treatment. Patients were enrolled within 60days of MAT initiation. The primary objective was to characterize patients receiving a MAT and their patterns of therapy. The full analysis set (FAS) included eligible patients for the relevant enrollment protocol, and the safety analysis set (SAF) included patients who received ≥ 1 MAT dose.ResultsOverall, 2009 patients were enrolled in the SAF. The FAS comprised 1993 patients (510 isavuconazole; 540 posaconazole; 491 voriconazole; 452 multiple/sequenced MAT therapies); 816 and 1177 received treatment and prophylaxis at study index/enrollment, respectively. Around half (57.8%) of patients were male, and median age was 59years. Among patients with IFIs during the study, the most common pathogens were Aspergillus fumigatus in the isavuconazole (18.2% [10/55]) and voriconazole (25.5% [12/47]) groups and Candida glabrata in the posaconazole group (20.9% [9/43]); the lungs were the most common infection site (58.2% [166/285]). Most patients were maintained on MAT monotherapy (77.3% [1541/1993]), and 79.4% (1520/1915) completed their MAT therapies. A complete/partial clinical response was reported in 59.1% (591/1001) of patients with a clinical response assessment. Breakthrough IFIs were reported in 7.1% (73/1030) of prophylaxis patients. Adverse drug reactions (ADRs) were reported in 14.7% (296/2009) of patients (3.9% [20/514] isavuconazole; 11.3% [62/547] posaconazole; 14.2% [70/494] voriconazole).ConclusionsIn this 'real-world' study, most patients remained on their initial therapy and completed their MAT therapy. Over half of patients receiving MATs for IFIs had a successful response, and most receiving prophylaxis did not develop breakthrough IFIs. ADRs were uncommon.

The kinetic characteristics of the process of synthesis of Ni nanopowder (NP) by the chemical metallurgy method are studied. Nickel NP is obtained by reduction of NiO nanopowder with hydrogen in a tubular furnace at temperatures in the range from 240 to 280°C. Nickel oxide nanopowder is prepared by thermal decomposition of nickel hydroxide Ni(OH)2 at 300°C, which has been synthesized in advance by chemical precipitation from aqueous solutions of nickel nitrate 10 wt % and alkali NaOH 10 wt % with pH 9 at room temperature. It is found that NiO NP is more readily reduced at temperatures above 250°C. The rate constant of the reduction process at 280°C is about 2.5 times higher than in the case of reduction at 240°C. The duration of the reduction process at 280°C is shorter by a factor of more than two in comparison with the case of reduction at 240°C. Based on the results of calculation of the activation energy of the reduction process from isothermal data, an assumption is made about the kinetically controlled rate-limiting regime of the reduction of NiO NP. It is revealed that Ni nanoparticles obtained by hydrogen reduction of nickel oxide have an average size in the range of 60–120 nm, and each of them is connected to several adjacent particles by necks.

Objectives To assess the impact of gestational antibiotics on the risk of preterm birth, since a healthy maternal microbiome may be protective. Methods Population-based cohort study including all first pregnancies in Sweden (2006–16). The association between gestational and recent pre-conception systemic antibiotics and preterm birth was assessed by multivariable logistic regression presented as ORs and 95% CIs, adjusted for comorbidities (hypo- and hyperthyroidism, hypertension, or diabetes mellitus pre-gestation), trimester, antibiotic class and treatment duration. Results Compared with non-users, antibiotic exposure was associated with increased risks of preterm birth in mothers with comorbidities (OR = 1.32, 95% CI 1.18–1.48) and without (OR = 1.09, 95% CI 1.06–1.13). Pre-conception use showed no association, while risk was increased for first and second trimester use and decreased for third trimester use. The increased risks were seen for the following antibiotic groups in mothers without and with comorbidities, respectively: macrolides, lincosamides and streptogramins (OR = 1.63, 95% CI 1.45–1.83; OR = 2.48, 95% CI 1.72–3.56); quinolones (OR = 1.60, 95% CI 1.32–1.94; OR = 2.11, 95% CI 1.12–4.03); non-penicillin β-lactams (OR = 1.15, 95% CI 1.07–1.24; OR = 1.39, 95% CI 1.07–1.83); other antibacterials (OR = 1.09, 95% CI 1.03–1.14; 1.38, 95% CI 1.16–1.63); and penicillins (OR = 1.04, 95% CI 1.01–1.08; 1.23, 95% CI 1.09–1.40). Antibiotic indications were not available, which could also affect preterm birth. Conclusions Antibiotic use during pregnancy was associated with an increased risk of preterm birth, especially in mothers with chronic diseases.

Phenomenological models are popular for describing the epidemic curve. We present how they can be used at different phases in the epidemic, by modelling the daily number of new hospitalisations (or cases). As real-time prediction of the hospital capacity is important, a joint model of the new hospitalisations, number of patients in hospital and in intensive care unit (ICU) is proposed. This model allows estimation of the length of stay in hospital and ICU, even if no (or limited) individual level information on length of stay is available. Estimation is done in a Bayesian framework. In this framework, real-time alarms, defined as the probability of exceeding hospital capacity, can be easily derived. The methods are illustrated using data from the COVID-19 pandemic in March–June 2020 in Belgium, but are widely applicable.

Variational Bayes (VB) has become a widely-used tool for Bayesian inference in statistics and machine learning. Nonetheless, the development of the existing VB algorithms is so far generally restricted to the case where the variational parameter space is Euclidean, which hinders the potential broad application of VB methods. This paper extends the scope of VB to the case where the variational parameter space is a Riemannian manifold. We develop an efficient manifold-based VB algorithm that exploits both the geometric structure of the constraint parameter space and the information geometry of the manifold of VB approximating probability distributions. Our algorithm is provably convergent and achieves a convergence rate of order $\mathcal O(1/\sqrt{T})$ and $\mathcal O(1/T^{2-2\epsilon})$ for a non-convex evidence lower bound function and a strongly retraction-convex evidence lower bound function, respectively. We develop in particular two manifold VB algorithms, Manifold Gaussian VB and Manifold Neural Net VB, and demonstrate through numerical experiments that the proposed algorithms are stable, less sensitive to initialization and compares favourably to existing VB methods., Comment: 30 pages, 5 figures

The paper presents a numerical simulation for fluid-structure interaction (FSI) of unsteady blood flow interacting with the vessel wall. The present work aims to provide a simple approach for very large deformation of the wall. The implementation of the method is straightforward and can be employed for a large scale problem with a cheap computational cost. The classical finite element discretization is adopted both for fluid and solid domains on tetrahedral elements. The monolithic scheme is used for the strong coupling of fluid and structure to satisfy kinematic and dynamic equilibrium conditions at the interface. The Navier-Stokes equations of an incompressible flow are solved by using the integrated method based on the Arbitrary Lagrangian-Eulerian (ALE) formula for the moving grid, and the total Lagrangian formulation is used for the non-linear hyper-elastic material of the vessel wall with the Mooney-Rivlin material model adopted as a constitutive equation for the solid domain. The numerical solutions for the FSI of blood vessel problem are quite similar to the experimental data. After validation the code, two problems of the blood vessel walls are considered: The carotid bifurcation and the aortic valve problems. The simulation results can be used for predicting the risk of cardiovascular diseases.

Using Khovanov’s categorification of the Weyl algebra, we investigate categorical structures arising from spherical harmonics. We categorify the $\mathfrak {s}\mathfrak {l}(2,\mathbb {C})$ -action on the polynomial ring in n variables, and use this to categorify certain simple Verma modules. On the way we also categorify the standard action of matrix units $E_{ij}\in \mathfrak {g}\mathfrak {l}(n,\mathbb {C})$ on the polynomial ring.

Interleukin (IL)-1 beta (IL-1β), IL-2, Interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α) in the pleural fluid are valuable biomarkers in early diagnosis of Tuberculous Pleural Effusion (TPE). This study aimed to analyze the diagnostic values of some cytokines (IFN-γ, TNF-α, IL-1β, and IL-2) in pleural fluid for identifying TPE in Vietnam. We performed a cross-sectional study on tuberculosis (TB) patients with pleural effusion. Pleural IFN-γ, TNF-α, IL-1β, IL-2 were measured by ELISA® Kit (Abcam, USA) on Biotek system. Receiver operating characteristic curves (ROC), an area under the curve (AUC), sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) of IFN-γ, TNF-α, IL-1β, IL-2 in identifying TBE were assessed. Among 386 patients, 234 (60,6%) had TPE, and 152 (39,4%) did not have TPE. The median of IL-2, TNF-α, and IFN-γ levels were significantly higher in TPE compared to the non-TPE group (p0.05). AUC for IL-1β, IL-2, TNF-α, and IFN-γ were 0.54, 0.57, 0.62. 0.84 (p0.05), respectively. The sensitivity of IL-1β, IL-2, TNF-α, and IFN-γ in the diagnosis of TPE were 82.1, 53.4, 77.8, and 80.3, while the specificity was 28,4, 69.7, 47.4, and 80.9, respectively. IFN-γ and TNF-α are potential biomarkers in diagnosing TPE.

Link prediction in Knowledge Graph, also called knowledge completion, is a significant problem in graph mining and has many applications for large companies. The more accurate the link prediction results will bring satisfaction, reduce and avoid risks, and commercial benefits. Almost all state-of-the-art models focus on the deep learning approach, especially using convolutional neural networks (CNN). By analysing the strengths and weaknesses of the CNN based models, we proposed a better model to improve the performance of the link prediction task. Specifically, we apply a CNN with specific filters generated through the Hypernetwork architecture. Moreover, we increase the depth of the model more than baseline models to help learn more helpful information. Experimental results show that the proposed model gets better results when compared to CNN-base models.

The utilization of chemical fertilizers in agriculture production could cause harmful effects on human health and the environment, therefore the development and application of biofertilizers produced from beneficial microorganisms like plant growth-promoting rhizobacteria have been increasingly encouraged. The present study investigated the effects of the inoculation of the two Rhizobium pusense strains (R. pusense GCB108 and R. pusense GCB117) on the growth of the young rice plant (Oryza sativa L.) and white radish (Raphanus sativus L.). The results showed that the inoculation of the two R. pusense strains affected the growth of rice and white radish considerably. On day 7, the shoot length of Oryza sativa L. grown on the medium inoculated with the R. pusense GCB108 and GCB117 was 22.3 ± 0.42 cm and 21.6 ± 2.26 cm, respectively, while that recorded in the control sample (without bacterial inoculation) was only 18.25 ± 1.06 cm. On day 9, the shoot length of Raphanus sativus L. grown under the hydroponic condition and inoculated with the R. pusense GCB108 and GCB117 was 12.68 ± 1.22 cm and 13.69 ± 1.47 cm, respectively, while that recorded in the control sample was much lower (9.04 ± 1.86 cm). Moreover, the inoculation of R. pusense GCB108 and GCB117 also restricted the growth of the rice pathogen Pseudomonas oryzihabitans RL01 in the rice rhizosphere. Furthermore, the results from the biophysiological assay showed that both two strains R. pusense GCB108 and GCB117 could grow under a salinity environment (salt concentration of 3%) and a wide range of pH conditions (pH 5 – 11). The study demonstrates the importance of the R. pusense GCB108 and GCB117 inoculation in the growth of rice and white radish and suggests the potential application of those two strains in biofertilizer production to improve soil quality and stimulate plant growth, contributing to sustainable agriculture development.

We show that spheroidal wave functions viewed as the essential part of the joint eigenfunction of two commuting operators of $L_2(S^2)$ has a defect in the joint spectrum that makes a global labelling of the joint eigenfunctions by quantum numbers impossible. To our knowledge this is the first explicit demonstration that quantum monodromy exists in a class of classically known special functions. Using an analogue of the Laplace-Runge-Lenz vector we show that the corresponding classical Liouville integrable system is symplectically equivalent to the C. Neumann system. To prove the existence of this defect we construct a classical integrable system that is the semi-classical limit of the quantum integrable system of commuting operators. We show that this is a semi-toric system with a non-degenerate focus-focus point, such that there is monodromy in the classical and the quantum system., 26 pages, 11 figures

In this work, we propose a new approach to automatically predict the locations of visual dermoscopic attributes for Task 2 of the ISIC 2018 Challenge. Our method is based on the Attention U-Net with multi-scale images as input. We apply a new strategy based on transfer learning, i.e., training the deep network for feature extraction by adapting the weights of the network trained for segmentation. Our tests show that, first, the proposed algorithm is on par or outperforms the best ISIC 2018 architectures (LeHealth and NMN) in the extraction of two visual features. Secondly, it uses only 1/30 of the training parameters; we observed less computation and memory requirements, which are particularly useful for future implementations on mobile devices. Finally, our approach generates visually explainable behaviour with uncertainty estimations to help doctors in diagnosis and treatment decisions.

Summary Background The past two decades have seen expansion of childhood vaccination programmes in low-income and middle-income countries (LMICs). We quantify the health impact of these programmes by estimating the deaths and disability-adjusted life-years (DALYs) averted by vaccination against ten pathogens in 98 LMICs between 2000 and 2030. Methods 16 independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever. Using standardised demographic data and vaccine coverage, the impact of vaccination programmes was determined by comparing model estimates from a no-vaccination counterfactual scenario with those from a reported and projected vaccination scenario. We present deaths and DALYs averted between 2000 and 2030 by calendar year and by annual birth cohort. Findings We estimate that vaccination of the ten selected pathogens will have averted 69 million (95% credible interval 52–88) deaths between 2000 and 2030, of which 37 million (30–48) were averted between 2000 and 2019. From 2000 to 2019, this represents a 45% (36–58) reduction in deaths compared with the counterfactual scenario of no vaccination. Most of this impact is concentrated in a reduction in mortality among children younger than 5 years (57% reduction [52–66]), most notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 120 million (93–150) deaths will be averted by vaccination, of which 58 million (39–76) are due to measles vaccination and 38 million (25–52) are due to hepatitis B vaccination. We estimate that increases in vaccine coverage and introductions of additional vaccines will result in a 72% (59–81) reduction in lifetime mortality in the 2019 birth cohort. Interpretation Increases in vaccine coverage and the introduction of new vaccines into LMICs have had a major impact in reducing mortality. These public health gains are predicted to increase in coming decades if progress in increasing coverage is sustained. Funding Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.

We report a dynamic kinetic resolution (DKR) of chiral 4-pentenals by olefin hydroacylation. A primary amine racemizes the aldehyde substrate via enamine formation and hydrolysis. Then, a cationic rhodium catalyst promotes hydroacylation to generate α,γ-disubstituted cyclopentanones with high enantio- and diastereoselectivities.

Building an intelligent system for automatically composing music like human beings has been actively investigated during the last decade. In this work, we propose a new approach for automatically creating hymns by training a variational attention model from a large collection of religious songs. We compare our method with two other techniques by using Seq2Seq and attention models and measure the corresponding performance by BLEU-N scores, the entropy, and the edit distance. Experimental results show that the proposed method can achieve a promising performance that is able to give an additional contribution to the current study of music formulation. Finally, we publish our dataset online for further research related to the problem.

The factors controlling estuarine phytoplankton diversity and production are relatively well known in temperate systems. Less however is known about the factors affecting phytoplankton community distribution in tropical estuaries. This is surprising given the economic and ecological importance of these large, deltaic ecosystems, such as are found in South East Asia. Here we present the results from an investigation into the factors controlling phytoplankton distribution and phytoplankton-bacterial coupling in the Bach Dang Estuary, a sub-estuary of the Red River system, in Northern Vietnam. Phytoplankton diversity and primary and bacterial production, nutrients and metallic contaminants (mercury and organotin) were measured during two seasons: wet (July 2008) and dry (March 2009). Phytoplankton community composition differed between the two seasons with only a 2% similarity between July and March. The large spatial extent and complexity of defining the freshwater sources meant that simple mixing diagrams could not be used in this system. We therefore employed multivariate analyses to determine the factors influencing phytoplankton community structure. Salinity and suspended particulate matter were important factors in determining phytoplankton distribution, particularly during the wet season. We also show that phytoplankton community structure is probably influenced by the concentrations of mercury species (inorganic mercury and methyl mercury in both the particulate and dissolved phases) and of tri-, di, and mono-butyl tin species found in this system. Freshwater phytoplankton community composition was associated with dissolved methyl mercury and particulate inorganic mercury concentrations during the wet season, whereas, during the dry season, dissolved methyl mercury and particulate butyl tin species were important factors for the discrimination of the phytoplankton community structure. Phytoplankton-bacterioplankton coupling was also investigated during both seasons. In the inshore, riverine stations the ratio between bacterial production and dissolved primary production was high supporting the hypothesis that bacterial carbon demand is supported by allochthonous riverine carbon sources. The inverse was true in the offshore stations, where BP:DPP values were less than 1, potentially reflecting differences in primary production due to shifting phytoplankton community diversity.

Set inversion is a classical problem in control theory that has many important applications in various fields of science and engineering. The state-of-the-art method for solving this problem, Set Inverter Via Interval Analysis (SIVIA), usually does not work well in high dimensions and often fails to recover sets with complicated structures. In this work, we propose a new approach to the problem of set inversion, which employs techniques from machine learning to resolve these issues. Our algorithm can handle problems in high dimensions and achieve the same level of accuracy with fewer data points compared to SIVIA. We illustrate the performance of our method in various simulation studies and apply it to investigate the dynamics of the 17th-century plague in Eyam village, England.

The pediatric perforated appendix rate is a quality metric measured by the Agency for Healthcare Research and Quality (AHRQ) that reflects access to care. The association of health care utilization prior to presentation with appendicitis is unknown.To determine whether increased health care utilization prior to presentation with appendicitis is associated with lower perforated appendicitis rates in children.Retrospective cohort study of privately insured children drawn from large employer and insurance company administrative data found in the Truven MarketScan national insurance claims database. Cases of appendicitis were identified among 38 348 children 18 years or younger from January 1, 2010, through December 31, 2013, with corresponding primary health care encounters from January 1, 2009, through December 31, 2012. In all, 19 109 eligible children were identified using International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes for appendicitis after excluding those patients who did not have continuous insurance coverage during the study period. Statistical analysis was performed from September 1, 2016, to October 15, 2017.Health care utilization was determined by the number of outpatient clinic encounters for each patient in the 1 to 12 months before presentation with appendicitis.Perforated appendicitis was defined according to the AHRQ by using ICD-9 codes for perforation and hospital length of stay of 3 or more days. Logistic regression models were used for perforated appendicitis after adjustment for age, sex, income, gastrointestinal comorbidities, geographic region, and insurance type.We identified 38 348 children 18 years or younger with ICD-9 diagnosis codes for appendicitis, and 19 109 children remained for analysis after applying exclusion criteria. Of these, 11 422 were boys (59.8%); the mean (SD) age was 12.4 (3.9) years. Of the 19 109 children identified who underwent appendectomy, 5509 (28.8%) presented with perforated appendicitis. Children with perforation had lower outpatient health care utilization in the year before presentation compared with those diagnosed with acute appendicitis (4554 of 5509 children [82.7%] vs 11 937 of 13 600 [87.8%]; P .001). In the adjusted model, outpatient health care utilization before presentation was associated with lower odds of perforated appendicitis (odds ratio [OR], 0.63; 95% CI, 0.58-0.69; P .001). This association increased with visit frequency in the year before presentation (OR, 0.86; 95% CI, 0.77-0.95 for 1-2 visits, P = .003; OR, 0.61; 95% CI, 0.55-0.67 for 3-6 visits, P .001; and OR, 0.43; 95% CI, 0.38-0.48 for ≥7 visits [5-18 years], P .001). Covariates associated with perforation included younger age, geographic region, family income, and higher out-of-pocket insurance plans.Among insured children 18 years or younger, increased health care utilization was associated with lower rates of perforated appendicitis. Primary health care relationships may facilitate timely presentation or serve as a marker for health-related self-efficacy, thereby contributing to outcomes for acute surgical conditions.

A cell-based smoothed discrete shear gap method (CS-FEM-DSG3) was recently proposed and proven to be robust for free vibration analyses of Reissner-Mindlin shell. The method improves significantly the accuracy of the solution due to softening effect of the cell-based strain smoothing technique. In addition, due to using only three-node triangular elements generated automatically, the CS-FEM-DSG3 can be applied flexibly for arbitrary complicated geometric domains. However so far, the CS-FEM-DSG3 has been only developed for analyzing intact structures without possessing internal cracks. The paper hence tries to extend the CS-FEM-DSG3 for free vibration analysis of cracked Reissner-Mindlin shells by integrating the original CS-FEM-DSG3 with discontinuous and crack–tip singular enrichment functions of the extended finite element method (XFEM) to give a so-called extended cell-based smoothed discrete shear gap method (XCS-FEM-DSG3). The accuracy and reliability of the novel XCS-FEM-DSG3 for free vibration analysis of cracked Reissner-Mindlin shells are investigated through solving three numerical examples and comparing with commercial software ANSYS.

A discrete variable technique is integrated into ICDE to give Discrete-ICDE.Discrete-ICDE is then applied for the truss layout optimization problems.Numerical results show that Discrete-ICDE is robust, effective and reliable. Recently, an improved (µ+λ) constrainted differential evolution (ICDE) has been proposed and proven to be robust and effective for solving constrainted optimization problems. However, so far, the ICDE has been developed mainly for continuous design variables, and hence it becomes inappropriate for solving layout truss optimization problems which contain both discrete and continuous variables. This paper hence fills this gap by proposing a novel discrete variables handling technique and integrating it into original ICDE to give a so-called Discrete-ICDE (D-ICDE) for solving layout truss optimization problems. Objective functions of the optimization problems are minimum weights of the whole truss structures and constraints are stress, displacement and buckling limitations. Numerical examples of five classical truss problems are carried out and compared to other state-of-the-art optimization methods to illustrate the reliability and effectiveness of the proposed method. The D-ICDE's performance shows that it not only successfully handles discrete variables but also significantly improves the convergence of layout truss optimization problem. The D-ICDE is promising to extend for determining the optimal solution of other structural optimization problems which contain both discrete and continuous variables.

The paper presents a numerical procedure for kinematic limit analysis of Mindlin plate governed by von Mises criterion. The cell-based smoothed discrete shear gap method (CS-DSG3) is combined with a second-order cone optimization programming (SOCP) for determining the upper bound limit load of the Mindlin plates. The limit analysis problem of Mindlin plates is formulated by minimizing the dissipation power subjected to a set of constraints of boundary conditions and unitary external work. This minimization problem is then transformed into an explicit form suitable for the solution using the SOCP. The numerical results of some benchmark problems show that the proposal procedure can provide the reliable upper bound collapse multipliers for the Mindlin plates. CS-DSG3 is combined with SOCP for determining upper bound limit load of Mindlin plates.Limit analysis problem is transformed into an explicit form suitable for solution using SOCP and CS-DSG3.Numerical results show that CS-DSG3 is free of shear locking and can provide reliable upper bound collapse multipliers for Mindlin plates.

This paper presents a study on Vane Tidal Turbine (VTT) focusing on analysis of two types of blade arrangement originated from the previous studies where the original design was examined and performance-tested for different numbers of blades (six, eight and twelve). Compared to conventional tidal turbines, VTT has several special features and potential advantages which have been being thoroughly developed. The purpose of this study is to analyze VTT’s capability of extracting and converting the hydrokinetic energy of tidal currents into electricity at given arrangement of blades (single and double rows, six and twelve blades) using CFD. From the calculation results, the six-blade single row turbine shows the best performance, in which the highest power and torque coefficients reach up to about 34 % and 36 %, respectively, at TSR=0.94. However, despite of lower power coefficient, by adding more blades, the torque’s extraction of twelve-blade turbine, especially the double row type, is less fluctuate than that of the six-blade setups.

Using touchscreens has largely limited user inputs to small form-factor devices. To address this constraint, we explore a novel input mechanism, dubbed PaperKey, that enables users to interact with mobile devices by performing multi-finger typing gestures on a surface where the device is placed. Using acceleration signals on the device, PaperKey infers the user's type events and then leverages a vision based technique for detecting the exact typing locations on a paper keyboard layout. Compared to single audio, image, or vibration sensing, this work accurately localizes keystrokes with faster processing speed. Additionally, this mechanism keeps the mobility of devices by working without external sensors.

Automatic segmentation of major brain tissues from high-resolution magnetic resonance images (MRIs) plays an important role in clinical diagnostics and neuroscience research. In this paper, we present a novel approach to extract brain tissues including gray matter, white matter and cerebrospinal fluid by using Gaussian mixture models (GMMs), Convolution neural networks (CNNs) and Deep neural networks (DNNs). GMMs are applied to classify voxels which have distinct intensity information and are easy to recognize while DNNs and CNNs are treating voxels which are similar in appearance and usually recognized insufficiently by traditional approaches. The empirical results on IBSR 18 dataset show that the proposed method outperforms 13 state-of-the-art algorithms, surpassing all other methods by a significant margin.

GATE (Geant4 Application for Tomographic Emission) is an open-source Monte-Carlo simulation platform based on Geant4 (GEometry And Tracking) simulation toolkit, widely used for many medical physics applications. Since the Geant4-DNA physical models have been integrated into the version GATE v7.0, the applications of GATE are extended to the field of radiobiology. The latest version GATE v7.2 is based on the Geant4.10.02.p01 version. However, the new Geant4-DNA Physics List with different options (opt1, opt2, opt3, opt4, opt5) of the Geant4.10.02.p01 version have not been incorporated in GATE v7.2; therefore we implemented the integration of the new Geant4-DNA Physics Lists into GATE v7.3-beta based on Geant4.10.02.p01. Also, we combined two different Physics List (Mixed Physics List) in GATE v7.3-beta which can be used in the same simulation. GATE v7.3-beta is a version of GATE that we developed in our work. In order to validate and verify the correct implementation of the Geant4-DNA physical models into GATE v7.3-beta, we used two benchmarks : DPKs (Dose Point Kernels) of 50000 particles of 10 keV electron point source in spherical water phantom with the diameter of 400 mm; and Example_DNA for 3000 particles of 8 MeV proton point source in three different targets made of liquid water with the thickness of 50 pm. A good agreement is found for the DPK calculation in case of 10 keV electrons where differences for eighteen shells are below 5 % between GATE and Geant4.10.02. The conclusions are : the validation of Geant4-DNA physical models by comparing of GATE v7.3-beta DPKs with Geant4.10.02.p01 and EGSnrc, the spectrum of the secondary electrons generated in three targets demonstrated the successful operation of the new Mixed Physics List in GATE v7.3-beta.