Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic implication of the neoadjuvant rectal score and other biomarkers of clinical outcome in Hong Kong Chinese patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy.

BACKGROUND Neoadjuvant chemoradiotherapy is a standard treatment for locally advanced rectal cancer, for which pathological complete response is typically used as a surrogate survival endpoint. Neoadjuvant rectal score is a new biomarker that has been shown to correlate with survival. The main objectives of this study were to investigate factors contributing to pathological complete response, to validate the prognostic significance of neoadjuvant rectal score, and to investigate factors associated with a lower neoadjuvant rectal score in a cohort of Hong Kong Chinese. METHODS Data of patients with locally advanced rectal cancer who received neoadjuvant chemoradiotherapy from August 2006 to October 2018 were retrieved from hospital records and retrospectively analysed. RESULTS Of 193 patients who had optimal response to neoadjuvant chemoradiotherapy and surgery, tumour down-staging was the only independent prognostic factor that predicted pathological complete response (P<0.0001). Neoadjuvant rectal score was associated with overall survival (hazard ratio [HR]=1.042, 95% confidence interval [CI]=1.021-1.064; P<0.0001), disease-free survival (HR=1.042, 95% CI=1.022-1.062; P<0.0001), locoregional recurrence-free survival (HR=1.070, 95% CI=1.039-1.102; P<0.0001) and distant recurrence-free survival (HR=1.034, 95% CI=1.012-1.056; P=0.002). Patients who had pathological complete response were associated with a lower neoadjuvant rectal score (P<0.0001), but pathological complete response was not associated with survival. For patients with intermediate neoadjuvant rectal scores, late recurrences beyond 72 months from diagnosis were observed. CONCLUSION Neoadjuvant rectal score is an independent prognostic marker of survival and disease recurrence in a cohort of Hong Kong Chinese patients who received neoadjuvant chemoradiotherapy for locally advanced rectal cancer.
A New Bandstop Cascaded Defected Microstrip Structure (CDMS) Filter with 10GHz Symmetrical Bandwidth

This paper presents a new bandstop fllter to obtaining the broad-bandwidth rejec- tion in microstrip transmission line. This structure is a cascaded defected microstrip structure (CDMS). To this property, two defects with similar directions and connecting line between them is designed and simulated. Then, its performance is investigated and discussed.
Deep Learning Based Real-Time Semantic Segmentation of Cerebral Vessels and Cranial Nerves in Microvascular Decompression Scenes

Automatic extraction of cerebral vessels and cranial nerves has important clinical value in the treatment of trigeminal neuralgia (TGN) and hemifacial spasm (HFS). However, because of the great similarity between different cerebral vessels and between different cranial nerves, it is challenging to segment cerebral vessels and cranial nerves in real time on the basis of true-color microvascular decompression (MVD) images. In this paper, we propose a lightweight, fast semantic segmentation Microvascular Decompression Network (MVDNet) for MVD scenarios which achieves a good trade-off between segmentation accuracy and speed. Specifically, we designed a Light Asymmetric Bottleneck (LAB) module in the encoder to encode context features. A Feature Fusion Module (FFM) was introduced into the decoder to effectively combine high-level semantic features and underlying spatial details. The proposed network has no pretrained model, fewer parameters, and a fast inference speed. Specifically, MVDNet achieved 76.59% mIoU on the MVD test set, has 0.72 M parameters, and has a 137 FPS speed using a single GTX 2080Ti card.
Palaeogeography and provenance transition of Precambrian–Cambrian unconformity at the southern margin of the North China Craton

The Precambrian–Cambrian unconformity boundary is ubiquitous and globally documented, which is of great significance to studying major global scientific issues such as environmental transition, positions of the supercontinent, Cambrian explosion, and global geochemical cycle. However, few studies have been on the palaeogeographic features and provenance changes of the Precambrian–Cambrian unconformity boundary at the southern margin of North China Craton (NCC). This uncertainty hampers us from further understanding the early climate change and plate evolutionary history of the NCC. To improve the knowledge of the palaeogeographic features and provenance changes of the Precambrian–Cambrian unconformity boundary on the southern margin of the NCC, the Luoquan and Xinji formations at the southern margin of the NCC were selected as the research object integrated with sedimentary petrology, trace elements, and detrital zircon geochronology investigation. The results suggest a depositional gap between the Luoquan and Xinji formations. The former is glacial to deglaciation deposits, while the latter is shallow to coastal sediments. Compared with the sedimentary stratum of the South China Craton, the Luoquan Formation lacks at least one transgression and regression cycle. The Xinji Formation has detrital zircon age peaks of 1200, 1100, and 950 Ma, unavailable in the Luoquan Formation. The provenance areas of the Luoquan and Xinji formations have changed, indicating that the provenances of the Luoquan Formation belong to the NCC and part of the provenances of the Xinji Formation belong to the North Qinling Terrane (NQT). The trace element data indicate that the tectonic setting of the Luoquan and Xinji formations has changed from a continental island arc to a passive continental margin. It is suggested that the NCC be involved in the evolution of Rodinia supercontinent, which leads to the change of the provenance and tectonic setting. This research provides an explanation for the Precambrian–Cambrian tectonic history, basin development, stratigraphic correlation, and palaeogeographic reconstruction of NCC.
Self-Powered Flexible Sensor Based on Triboelectric Nanogenerators for Noncontact Motion Sensing

Flexible sensors with surface suitability for complex-shaped objects generally sense object motion through a contact mode, which limits their application range and shortens their service life. The development of flexible sensors with noncontact working modes can overcome these shortcomings. Herein, superhydrophobic and self-powered flexible sensors based on a triboelectric nanogenerator (TENG) were fabricated by a step-by-step swelling-permeation method to prepare natural latex films with carbon black and silica nanoparticles embedded on their inner and outer surfaces, respectively. In addition to sensing object motion through contact, the TENG-based sensor can also sense charged object motion in noncontact mode based on the principle of electrostatic induction. The TENG-based sensor can sense horizontal and vertical movements of objects above it and can even detect the movement of objects with speeds as low as 0.04 $\text{m}/\text{s}$ . Interestingly, the sensor’s ability to monitor object motion in noncontact mode remains unchanged even at 70% strain. The TENG-based sensor can also be used to distinguish the type and amount of charge carried by an object and can harvest energy from moving objects in noncontact mode. Combining a single-electrode TENG with a freestanding TENG allows monitoring of the motion direction of an object loading an unknown type of charge in a noncontact mode. Based on the characteristics of our TENG-based flexible sensors to sense moving objects in both contact and noncontact modes, they have potential applications for human-machine interfaces, smart wearable devices, and flexible robots.
Continuing Professional Development among Nurses in Specialist Hospital, Akure, Ondo State

The study examined the continuing professional development among nurses in Specialist Hospital, Akure, Ondo State. The study specifically identified if professional nurses in the hospital agree with the introduction of mandatory continuing professional development training by the nursing and midwifery council of Nigeria; and evaluated the uptake of participation of nurses in continuing professional training in State Specialist Hospital, Akure. The population of the study consisted of 225 nurses working in the hospital. Stratified random sampling technique was used to select the sample size for the study which consisted of 94 nurses. The data collected includes the demographic data of the sample, views and participation in compulsory CPD organized by the Nursing and Midwifery Council of Nigeria and past CPD programmes attended by the nurses. The instrument was given to tests and measurement expert and nurse educators to determine its face and content validity. Internal consistency method was used to determine the reliability of the instrument and coefficient value of 0.81 was derived. The research objectives were analyzed descriptively with frequency counts and simple percentages. The findings of the study revealed that that majority of the respondents supported making CPD training mandatory and they are even ready to sacrifice their off duties to attend the programme. However, greater percentage of them have only attended CPD programmes sometimes while others have not attended at all. The anticipated outcome of the study was found positive because nurses in the hospital are found to be aware of their need of lifelong learning to improve their knowledge and skills. It was recommended among others that the NMCN should include CPD training for special nursing fields, use experts to handle the teaching and make the cost affordable to encourage self-sponsoring.
Failure prediction for high-performance computing systems

The failure rate in high-performance computing (HPC) systems continues to escalate as the number of components in these systems increases. This affects the scalability and the performance of parallel applications in large-scale HPC systems. Fault tolerance (FT) mechanisms help mitigating the impact of failures on parallel applications. However, utilizing such mechanisms requires additional overhead. Besides, the overuse of FT mechanisms results in unnecessarily large overhead in the parallel applications. Knowing when and where failures will occur can greatly reduce the excessive overhead. As such, failure prediction is critical in order to effectively utilize FT mechanisms. In addition, it also helps in system administration and management, as the predicted failure can be handled beforehand with limited impact to the running systems. This dissertation proposes new proficiency metrics for failure prediction based on failure impact in UPC environment that the existing proficiency metrics tire unable to reflect. Furthermore, an efficient log message clustering algorithm is proposed for system event log data preprocessing and analysis. Then, two novel association rule mining approaches are introduced and employed for HPC failure prediction. Finally, the performances of the existing and the proposed association rule mining methods are compared and analyzed.
Characterizing and synthesizing the workflow structure of microservices in ByteDance Cloud

Modern Cloud applications have evolved from monolithic systems to numerous distributed microservices whose workflows interact via Remote Procedure Calls (RPCs). The benchmarks focusing on individual microservice components are insufficient because the reference relationships between components, which form the microservice workflow structure, are another critical aspect of microservice applications. Unfortunately, understanding the characteristics of microservice workflow in the production Cloud remains a missing piece in the literature, which prevents the representative of microservice benchmarks. In this paper, we fill this gap by characterizing and synthesizing the microservice workflows based on the trace data of the Toutiao application that is running on ByteDance Cloud. We examine the microservice workflows starting from DAG graphs, introduce observed properties that are easy to ignore but important, show the artificiality of the workflow by statistic description, and explore the high cost of network overhead. We further synthesize the workflow following the characteristics observed. The extensive evaluations show that the synthesized microservice workflows have consistent statistical characteristics as the production ones. A case study applying the synthesized workflows proves its usability.
Understanding Precipitate Growth Kinetics at Ultra-High Hydrostatic Pressures

In this work, we have studied the precipitate growth behavior of a metal matrix when subjected to hydrostatic pressure. We utilized Zenner-Frank phase field kinetics with integrated free energy density functional based on volumetric strain energy. We studied the precipitate growth up to 2 GPa under varying bulk modulus of the precipitate phase. We observed that subjecting to hydrostatic pressure influences the growth kinetics by reducing the precipitate growth under time evolution. In addition, the bulk modulus of the precipitate has shown an abnormality in the growth behavior compared to general observations under hydrostatic pressure. This work contributes to the smart tailoring of novel materials to reduce detrimental impacts on holistic material properties, used in large hydrostatic pressure applications.
Design and Implementation of a Multidimensional Visualization Reconstruction System for Old Urban Spaces Based on Neural Networks

This article presents an in-depth study and analysis of the construction of a convolutional neural network model and multidimensional visualization system of old urban space and proposes the design of a multifaceted visualization reconstruction system of old urban space based on a neural network. It also quantitatively analyzes the essential spatial attribute characteristics of urban shadow areas as nodes of the overall urban dynamic network in three dimensions—spatial connection strength, spatial connection distance, and spatial connection direction—summarizes the characteristics of urban old spatial structure from the perspective of a dynamic network, and then proposes the model of urban old spatial design from the perspective of an active network. The shallow depth of the network structure is used to reduce the parameters in the learning process of reconfigurable convolutional neural networks using data sets so that the model learns more general features. For the situation where the number of data sets is small, data augmentation is used to expand the size of the data sets and improve the recognition accuracy of the reconfigurable convolutional neural network. A real-time update method of multifaceted data visualization for big data scenarios is proposed and implemented to reduce the network load and network latency caused by charts of multidimensional data changes, reduce the data error rate, and maintain the system stability in the old urban space concurrency scenario.
One-Year Report of COVID-19 Impact on Geriatric Patients: a Bio-Psycho-Social Approach

Background Since December of 2019, coronavirus 19 (COVID-19) has spread rapidly around the world. Our understanding of the infection has grown over the past year, and its impact on older adults is particularly significant. Apart from the direct impacts of COVID-19 infections, it has also led to lockdowns which, in turn, result in isolation and loneliness. Method We conducted a literature review of publicly available articles of the COVID-19 pandemic impact on the geriatric population between December 2019 and April 2021, a total of 748 articles. Results The review will be presented with the Bio-Psycho-Social model, covering how the biological, psychological, and sociological aspects of health are intertwined and impact older adults. Early studies have also highlighted the prevalence of post-COVID infection symptoms that typically fall under geriatric medicine care. We highlight the bidirectional impact of isolation and COVID-19 infections on geriatric health, as well as discuss pertinent topics such as vaccine efficacy, long-term sequelae of COVID-19 infections, and ageism. Conclusion This review seeks to present a one-year report of what is known about COVID-19 and geriatric medicine, as well as provide guidance to practitioners who care for older adults based on the most up-to-date literature.
Experimental investigation, numerical modelling and multi-objective optimisation of composite wind turbine blades

Abstract Static load and modal testing of two blades from a 15 kW wind turbine is presented. The two blades are made from glass fibre-reinforced polypropylene, one of which has been reinforced with additional carbon fibre plies. Static testing is performed with a Whiffle tree test rig to determine the structural response of the blades. Blade mass, deflections, strains and natural frequencies are reported. The following objectives are undertaken: (i) evaluate and compare the test results of the two wind turbine blade designs, (ii) use the results to validate finite element models of the blades and (iii) utilise the validated models in a design optimisation study. Parametric blade models are generated using the Python programming language and are based on manufacturing specifications for the blades. The models show good correspondence with the experimental results. The goal of the optimisation study is to maximise the stiffness and reduce the mass of the glass fibre blade. A multi-objective genetic algorithm is used to determine the optimum laminate thicknesses along the length of the blades. The optimisation study produced a set of Pareto efficient blade designs with up to 17% improvement in stiffness and 30% reduction in mass for the glass fibre blade design.
Characterization of antibiotic resistance genes and bacteria in a municipal water resource recovery facility

Municipal water resource recovery facilities (WRRFs) are important sources of antibiotic‐resistant bacteria and genes (ARB and ARGs). In this study, antibiotic‐resistant total heterotrophic bacteria (THBR) counts (CFU/ml) cultivated from influent, effluent of activated sludge process, and outflow of disinfection unit of an urban WRRF were investigated for the presence of 16, 32, 64, and 128 μg/ml of nine antibiotics. The isolates of Pseudomonas spp. , Acinetobacter spp. , and Escherichia coli obtained from effluent of activated sludge process were subjected for molecular identification by detecting the 16S rRNA gene sequences. Additionally, using the polymerase chain reaction method (PCR), the isolates were investigated for the presence of blaSHV, blaTEM, blaCTX‐M, blaVIM, sul1, and qnrS genes. According to the results, the abundance of THBR counts was not significantly reduced by the biological treatment except for cefixime and sulfamethoxazole; it also increased for some antibiotics after disinfection unit. The average removal efficiency of THBR resistant to ciprofloxacin, sulfamethoxazole, and ceftazidime were 7.9 ± 1.7%, 41.8 ± 2.1%, and 14.4 ± 6.2%, respectively. Also, all the tested isolates were resistant to at least four antibiotics. For all antibiotics, the resistance ratio (THBR/THB) significantly increased in the effluent and after chlorination unit. Among 12 resistant isolates, blaTEM and sul1 genes were the most frequently detected ones involved in 92% and 83% of the isolates, respectively. Both blaTEM and sul1 genes were found in 100% of E. coli, and 83% and 67% of Pseudomonas spp. isolates, respectively. Further efforts are necessary to limit the transmission of ARB and ARGs from WRRFs into the environment and prevent human health threats.
Blocking Metabotropic Glutamate Receptor Subtype 7 via the Venus Flytrap Domain Promotes a Chronic Stress-Resilient Phenotype in Mice

Chronic psychosocial stress participates prominently in the etiology of various psychiatric conditions and comorbid somatic pathologies; however, suitable pharmacotherapy of these disorders is still of high medical need. During the last few decades, research on mGlu receptors advanced remarkably and much attention was given to the mGlu7 subtype. Here, genetic mGlu7 ablation, short-term pharmacological mGlu7 blockade, as well as siRNA-mediated knockdown of mGlu7 were shown to result in an acute anti-stress, antidepressant- and anxiolytic-like phenotype in mice. Moreover, we recently revealed a prominent stress-protective effect of genetic mGlu7 ablation also with respect to chronic psychosocial stress. In addition, we are able to demonstrate in the present study that the chronic pharmacological blockade of mGlu7 interferes with various chronic stress-induced alterations. For this, we used the chronic subordinate colony housing (CSC), a mouse model of chronic male subordination, in combination with chronic treatment with the mGlu7-selective orthosteric-like antagonist XAP044 (7-hydroxy-3-(4-iodophenoxy)-4H-chromen-4-one). Interestingly, XAP044 dose-dependently ameliorates hypothalamic–pituitary–adrenal axis dysfunctions, thymus atrophy, as well as the CSC-induced increase in innate anxiety. Taken together, our findings provide further evidence for the role of mGlu7 in chronic psychosocial stress-induced alterations and suggests the pharmacological blockade of mGlu7 as a promising therapeutic approach for the treatment of chronic stress-related pathologies in men.
Gems, buds and slippers or what a series of visualisation tells us about the Learning and Teaching in Higher Education tweetchat (#LTHEchat)

This article is an inquiry into what the professional development initiative Learning and Teaching in Higher Education tweetchat or short #LTHEchat means to some of its participants as expressed through their visualisations provided during the 200th tweetchat on the 17 March 2021. These provide insights what the weekly tweetchat means to them. The findings suggest that the #LTHEchat is experienced as a caring and inclusive community of diverse individuals who come together to connect, support each other, experiment and develop themselves and their practice.
Low-Energy Electron Induced Reactions in Metronidazole at Different Solvation Conditions

Metronidazole belongs to the class of nitroimidazole molecules and has been considered as a potential radiosensitizer for radiation therapy. During the irradiation of biological tissue, secondary electrons are released that may interact with molecules of the surrounding environment. Here, we present a study of electron attachment to metronidazole that aims to investigate possible reactions in the molecule upon anion formation. Another purpose is to elucidate the effect of microhydration on electron-induced reactions in metronidazole. We use two crossed electron/molecular beam devices with the mass-spectrometric analysis of formed anions. The experiments are supported by quantum chemical calculations on thermodynamic properties such as electron affinities and thresholds of anion formation. For the single molecule, as well as the microhydrated condition, we observe the parent radical anion as the most abundant product anion upon electron attachment. A variety of fragment anions are observed for the isolated molecule, with NO2− as the most abundant fragment species. NO2− and all other fragment anions except weakly abundant OH− are quenched upon microhydration. The relative abundances suggest the parent radical anion of metronidazole as a biologically relevant species after the physicochemical stage of radiation damage. We also conclude from the present results that metronidazole is highly susceptible to low-energy electrons.