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The use of IoT and modern technologies has boosted the expansion of e-health solutions significantly and allowed access to better health services and remote monitoring of patients. Every service provider usually implements its information system to manage and access patient data for its unique purpose. Hence, the interoperability among independent e-health service providers is still a major challenge. From the structure of stored data to its large volume, the design of each such big data system varies, hence the cooperation among different e-health systems is impossible. In addition to this, the security and privacy of patient information is a challenging task. Building a unified solution for all creates significant business and economic issues. In this work, we present a solution to migrate existing e-health systems to a unified Blockchain-based model, where access to large scale medical data of patients can be achieved seamlessly by any service provider. A core blockchain network connects individual & independent e-health systems without requiring them to modify their internal processes. Access to patient data in the form of digital assets stored in off-chain storage is controlled through patient-centric channels and policy transactions. e show that the proposed solution can interconnect different e-health systems efficiently.

Background: To assess the prophylactic effect of simultaneous placement of mesh and incidence of parastomal hernia (PSH) after abdominoperineal resection of rectal cancer. Methods: This study included real world data of 56 surgically resected colorectal cancer (CRC) patients who were consecutively assigned to 2 groups: control (no mesh, n=32) and experimental (received mesh, n=24). An artificial patch was placed under the tunica vaginalis of rectus abdominis for patients in experimental group whereas the control group received routine sigmoidostomy. The median follow-up time was >20 months. Difference in hazards function was analyzed by cox regression analysis and results were expressed as hazard ratio (HR) and 95% confidence interval (CI). A P-value < 0.05 was considered as significant. Results: Post-operative incidence rate of PSH was lower in experimental (41.7 %) than in control group (71.9 %; P=0.045). PSH postoperative time in experimental group was significantly delayed than control group (48 months vs 10 months; PConclusions: Prophylactic mesh placement significantly prolonged post-operative time to recurrence and incidence rate of PSH. The incidence of recurrence of H2 (severe PSH) requiring secondary surgical repair was reduced.

Object tracking is a fundamental task for the visual perception system on the intelligent unmanned aerial vehicle (UAV). The high efficiency of correlation filter (CF) based trackers has advanced the widespread development of online UAV object tracking. This kind of method can effectively train a filter to discriminate the target from the background. However, most CF-based methods require a fixed label function over all the previous samples, leading to over-fitting and filter degradation, especially in complex drone scenarios. To address this problem, a novel adaptive response reasoning approach is proposed for CF learning. It can leverage temporal information in filter training and significantly promote the robustness of the tracker. Specifically, the proposed response reasoning method goes beyond the standard response consistency requirement and constructs an auxiliary label of the current sample. Besides, it helps learn a generic relationship between the previous and current filters, thereby realizing self-regulated filter updating and enhancing the discriminability of the filter. Extensive experiments on four well-known challenging UAV tracking benchmarks with 278 videos sequences show that the presented method yields superior results to 40 state-of-the-art trackers with real-time performance on a single CPU, which is suitable for UAV online tracking missions.

The ever-increasing diversity and dynamic of cloud environment pose many challenges on QoS prediction in service recommendation. One such challenge is how to extract and learn deep features of users/services from multi-source information to improve prediction accuracy. In this paper, we propose a novel Joint Deep Networks based Multi-source Feature Learning(JDNMFL) framework for QoS prediction. JDNMFL has two parts: Multi-source Feature Extraction and Feature Interaction Learning. In the first part, a latent factor embedding method is first proposed to capture implicit features from QoS matrix, and then the multi-source features, combined by explicit features from WSDL(Web Services Description Language) document and contextual data as well as implicit features, are extracted based on the combination of matrix factorization and neural networks. In the second part, the CNN(Convolutional Neural Network)-based joint deep networks are built to learn both local and global high-order feature interactions, and to complete the final QoS prediction based on mixed features. Experimental results demonstrate that our JDNMFL approach can not only extract and integrate implicit and explicit features of various multi-source data, but also can learn feature sequence and feature interactions, so that it is very effective in improving the accuracy of QoS prediction with sparse data.

Driver drowsiness is one of the main factors leading to road fatalities and hazards in the transportation industry. Electroencephalography (EEG) has been considered as one of the best physiological signals to detect drivers' drowsy states, since it directly measures neurophysiological activities in the brain. However, designing a calibration-free system for driver drowsiness detection with EEG is still a challenging task, as EEG suffers from serious mental and physical drifts across different subjects. In this paper, we propose a compact and interpretable Convolutional Neural Network (CNN) to discover shared EEG features across different subjects for driver drowsiness detection. We incorporate the Global Average Pooling (GAP) layer in the model structure, allowing the Class Activation Map (CAM) method to be used for localizing regions of the input signal that contribute most for classification. Results show that the proposed model can achieve an average accuracy of 73.22% on 11 subjects for 2-class cross-subject EEG signal classification, which is higher than conventional machine learning methods and other state-of-art deep learning methods. It is revealed by the visualization technique that the model has learned biologically explainable features, e.g., Alpha spindles and Theta burst, as evidence for the drowsy state. It is also interesting to see that the model uses artifacts that usually dominate the wakeful EEG, e.g., muscle artifacts and sensor drifts, to recognize the alert state. The proposed model illustrates a potential direction to use CNN models as a powerful tool to discover shared features related to different mental states across different subjects from EEG signals. National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore under its International Research Centres in Singapore Funding Initiative.

Reducing the risk of death due to cardiovascular disease (CVD) is an important direction for diabetes prevention and treatment. The Chinese population with type 2 diabetes (T2D) has a high risk of developing CVD at relatively low body mass index (BMI) levels. Currently, no studies have evaluated the effect of bariatric surgery versus medical therapy on long-term CVD risk in patients with T2D and low BMI.To compare bariatric surgery versus medical therapy for long-term CVD risk in Chinese patients with T2D and low BMI by using the China Prediction for ASCVD Risk equations and the United Kingdom Prospective Diabetes Study risk engine.University hospital, China.Medical records of patients with T2D with a BMI35 kg/mA total of 684 patients with T2D underwent bariatric surgery (n = 75) or medical therapy (n = 609), and 52 pairs of matched subjects were selected from both groups after propensity score matching. The 10-year and lifetime atherosclerotic CVD risk by using the China Prediction for ASCVD Risk equation at 5 years follow-up period in the bariatric surgery group improved significantly compared with the medical therapy group. In the fifth year of follow-up, the 10-year risk of coronary heart disease, fatal coronary heart disease, stroke, and fatal stroke by using the United Kingdom Prospective Diabetes Study risk engine were much lower in the bariatric surgery group than in the medical therapy group (10.37 ± 5.64% versus 27.25 ± 7.28%, P = .004; 6.3 ± 4.5% versus 22.3 ± 7.35%, P = .002; 4.97 ± 3.73% versus 15.05 ± 3.63%, P = .001; .59 ± .45% versus 1.52 ± .14%, P.001. respectively). The use of glucose-lowering medications, including insulin, was reduced from baseline in both groups, and patients in the bariatric surgery group required significantly fewer of these medications than those in the medical therapy group.Bariatric surgery in patients with T2D and low BMI conferred a lower calculated risk of CVD compared with medical therapy over 5 years of follow-up.

This paper presents a selective laser melting (SLM) 3-D printed Ku-band diplexer using dual-mode resonators with high thermal stability. The diplexer is designed using dual-mode dimpled ellipsoid resonators which enables the diplexer mechanically self-supported in fabrication. Hence, the design has higher compatibility with the SLM printing process and the design can be extended to multiplexers with more channels. The excellent thermal stability is benefited from both the 4J36 invar alloy material with a lower coefficient of thermal expansion (C.T.E) as well as the tailored SLM printing process. Electrical and thermal performances of the diplexer are measured, showing that the fabricated diplexer is with average insertion losses of 0.69dB/0.42dB, return losses of >14dB, and centre frequency shifts of 5.62MHz/3.75MHz (

In this paper, we address the challenges of detecting instances from emerging classes over a non-stationary data stream during classification. In particular, instances from an entirely unknown class may appear in a data stream over time. Existing classification techniques utilize unsupervised clustering to identify the emergence of such data instances. Unfortunately, they make strong assumptions which are typically invalid in practice; (i) Most instances associated with a class are closer to each other in feature space than instances associated with different classes, (ii) Covariates of data are normalized through an oracle to overcome the effect of a few data instances having large feature values, and (iii) Labels of instances from emerging classes are readily available soon after detection. To address the challenges that occur in practice when the above assumptions are weak, we propose a practical semi-supervised emerging class detection framework. Particularly, we aim to identify similar data instances within local regions in feature space by incorporating a mutual graph clustering mechanism. Our empirical evaluation of this framework on real-world datasets demonstrates its superiority of classification performance compared to existing methods while using significantly fewer labeled instances.

Light aromatic hydrocarbons are an important by-product of the coal chemical industry. The structure and properties of low molecular compounds (LMCs) embedded in coal are different from those of coal macromolecular skeleton structure, they have important effects on the coal pyrolysis. In this paper, the roles of LMCs on the formation of light aromatics during coal pyrolysis are investigated. The results show that LMCs have little effect on the thermal weight loss behavior of the three coals, but they can influence the carbon structure distribution of coals. The main source of light aromatics from coal pyrolysis is derived from thermal cracking of the coal macromolecular framework. And also the LMCs will be pyrolyzed to generate light aromatics. The total amount of BTEXN from extracts of Shengli coal (SL), Pingshuo coal (PS) and Hexi coal (HX) pyrolysis was 15%, 91%, and 12% of that of raw coal. The alkylbenzenes, naphthalene series, and PAHs can be cracked to form light aromatics. The long chain and cyclic aliphatic compounds can not only provide hydrogen for the free radical fragment of aromatics but also generate light aromatics. And the content of these compounds in the extracts of PS is higher than that of the other two coals. Due to the complexity of the combination between LMCs and coal structure, the extracts are easier to generate light aromatics than LMCs embedded in coal during pyrolysis. Because the composition and content of low molecules in coal with different metamorphic degrees are different, the effects of LMCs on the pyrolysis of low rank coal are more obvious compared with high rank coal.

Deep learning based device-free wireless sensing systems have achieved satisfactory performance in sensing human gesture, identity, location, etc.. However, subject to the limited computation and storage resources of wireless devices, complex deep learning algorithms could not run on these devices, which limits the practical implementation. In this paper, motivated by the emerging edge intelligence technique, we try to explore and exploit realizing lightweight device-free wireless sensing with network pruning and network quantization methods, which could reduce the complexity of a sensing system while keeping its sensing performance almost unchanged. Specifically, we propose a Taylor criterion ranking based network pruning strategy to remove the nonessential neurons so as to reduce the computational complexity and storage requirement, and design a network quantization strategy to quantize network parameters so as to further reduce the storage requirement. We design a mmWave-based device-free gesture recognition testbed to evaluate the proposed strategies. Extensive experimental results show that the developed strategies reduce the computational complexity and storage requirement to 27% and 14%, respectively, with the recognition accuracy reduced by only 2%.

Background This study was to perform an economic evaluation to understand clinical outcomes and health resource use between hip fracture patients receiving hospital-based postfracture fracture liaison service (FLS) care and those receiving usual care (UC) in Taiwan. Methods This cohort study included hospital-based data of 174 hip fracture patients who received FLS care (FLS group) from National Taiwan University Hospital, and 1697 propensity score-matched patients who received UC (UC group) of National Health Insurance claim-based data. Two groups had similar baseline characteristics but differed in hip fracture care after propensity score matching. Clinical outcomes included refracture-free survival (RFS), hip-refracture-free survival (HRFS), and overall survival (OS). Health resource use included inpatient, outpatient, and pharmacy costs within 2 years follow-up after the index of hip fracture. The economic evaluation of the FLS model was analyzed using the net monetary benefit regression framework based on the National Health Insurance perspective. Results The FLS group had longer RFS than the UC group, with an adjusted difference of 44.3 days (95% confidence interval: 7.2–81.4 days). Two groups did not differ in inpatient and outpatient costs during follow-up, but the FLS group had a higher expenditure than the UC group on osteoporosis-related medication. The probability of FLS being cost-effective was >80% and of increasing RFS, HRFS, and OS was 95%, 81%, and 80%, respectively, when the willingness-to-pay threshold was >USD 65/gross domestic product per day. Conclusion FLS care was cost-effective in reducing refracture occurrence days for patients initially diagnosed with hip fractures.

Lignocellulosic biomass photoreforming is a promising and alternative strategy for both sustainable H2 production and biomass valorization with infinite solar energy. However, harsh reaction conditions (high alkalinity or toxic organic solvents), with low biomass conversion and selectivity are often reported in literature. In this work, we report glucose photoreforming for coproduction of H2 and arabinose with improved selectivity under neutral condition using carbon quantum dots (CQDs) modified TiO2 composites. We show that the conventional CQDs fabricated by a facile one-step hydrothermal process could be endowed with novel color changing property, due to the particle aggregation under the regulation of incident light. The as-fabricated CQDs/TiO2 composites with certain colored CQDs could greatly improve glucose to arabinose conversion selectivity (~75%) together with efficient hydrogen evolution (up to 2.43 mmolh−1g−1) in water. The arabinose is produced via the direct C1-C2 α-scissions mechanism with reactive oxygen species of O2− and OH, as evidenced by 13C labeled glucose and the electron spin-resonance (ESR) studies, respectively. This work not only sheds new lights on CQDs assisted photobiorefinery for biomass valorization and H2 coproduction, but also opens the door for rationale design of different colored CQDs and their potential applications for solar energy utilization in the noble-metal-free system.

Aim: This study aimed to construct AS1411 and EpDT3-conjugated PEGylated silver nanotriangles (AENTs) and assess their ability to target breast cancer and cancer stem cells, as well as the antitumor and antimetastatic effects of AENT-mediated photothermal therapy. Materials & methods: AENTs were constructed and characterized. The targeting properties, as well as antitumor and antimetastatic activities, were evaluated in MDA-MB-231 breast cancer cells, cancer stem cells and breast cancer-bearing mice. Results: AENTs displayed excellent targeting property to breast cancer cells and cancer stem cells. AENT-mediated photothermal therapy greatly inhibited (>45%) the migration and invasion of breast cancer cells, as well as tumor growth and lung metastasis in the mice. Conclusion: AENT-mediated photothermal therapy might be an effective strategy for the treatment of breast cancer.

As the evaluation of image quality depends on the human visual system (HVS), many existing image quality assessment (IQA) methods focus on modeling the HVS to account for subjective perception. The visual attention of the HVS makes humans more sensitive to distortion on the attended regions than on regions which are not the focus of attention. Therefore, we propose an end-to-end multi-task deep convolution neural network with multi-scale and multi-hierarchy fusion (MMMNet), in which the IQA and saliency subtasks are jointly optimized to improve saliency-guided IQA performance. Particularly, the incorporation of saliency information is achieved by fusing saliency features with IQA features hierarchically to progressively improve the IQA features over network depth. A multi-scale feature extraction module (MSFE) is proposed to provide effective saliency features for the IQA network. Based on the saliency fusion, MMMNet introduces an auxiliary saliency task, achieving the multi-task learning to improve the generalization of the IQA task. Experimental results show that MMMNet achieves state-of-the-art performance and strong generalization ability on IQA databases.

PURPOSE To study the changes of hyoid position in infants with Robin sequence before and after mandibular distraction osteogenesis, and to explore the related factors. MATERIAL AND METHODS Twenty-six infants with Robin sequence underwent bilateral mandibular distraction osteogenesis from May 2016 to April 2020. Three-dimensional computed tomography data of patients before and after surgery were analyzed with Materialise Mimics 17.0. Changes in the three-dimensional position of the hyoid bone were studied. RESULTS The angle between the long axis of the tongue body and hard palate plane, and the angle between the long axis of the tongue body and mandibular plane were significantly decreased after surgery than before surgery. The hyoid bone-cranial base vertical distance, hyoid bone-mental point distance, and hyoid bone-epiglottis distance were significantly increased after surgery. The differences in the above-mentioned data were statistically significant (P

Background Although a vaccination campaign has been conducted since 2004, Japanese encephalitis (JE) is still a public health problem in Guizhou, one of the provinces with the highest incidence of JE in China. The aim of this study was to understand the spatiotemporal distribution of JE and its relationship with environmental factors in Guizhou Province in the post-vaccination era, 2004–2016. Methods We collected data on human JE cases in Guizhou Province from 2004 to 2016 from the national infectious disease reporting system. A Poisson regression model was used to analyze the relationship between JE occurrence and environmental factors amongst counties. Results Our results showed that the incidence and mortality of JE decreased after the initiation of vaccination. JE cases were mainly concentrated in preschool and school-age children and the number of cases in children over age 15 years was significantly decreased compared with the previous 10 years; the seasonality of JE before and after the use of vaccines was unchanged. JE incidence was positively associated with cultivated land and negatively associated with gross domestic product (GDP) per capita, vegetation coverage, and developed land. In areas with cultivated land coverage 55%, and urban area coverage > 25%, the JE risk was lower. The highest JE incidence was among mid-level GDP areas and in moderately urbanized areas. Conclusions This study assessed the relationship between incidence of JE and environmental factors in Guizhou Province. Our results highlight that the highest risk of JE transmission in the post-vaccination era is in mid-level developed areas.

Background/Aims When participants in individually randomized group treatment trials are treated by multiple clinicians or in multiple group treatment sessions throughout the trial, this induces partially nested clusters which can affect the power of a trial. We investigate this issue in the Whole Health Options and Pain Education trial, a three-arm pragmatic, individually randomized clinical trial. We evaluate whether partial clusters due to multiple visits delivered by different clinicians in the Whole Health Team arm and dynamic participant groups due to changing group leaders and/or participants across treatment sessions during treatment delivery in the Primary Care Group Education arm may impact the power of the trial. We also present a Bayesian approach to estimate the intraclass correlation coefficients. Methods We present statistical models for each treatment arm of Whole Health Options and Pain Education trial in which power is estimated under different intraclass correlation coefficients and mapping matrices between participants and clinicians or treatment sessions. Power calculations are based on pairwise comparisons. In practice, sample size calculations depend on estimates of the intraclass correlation coefficients at the treatment sessions and clinician levels. To accommodate such complexities, we present a Bayesian framework for the estimation of intraclass correlation coefficients under different participant-to-session and participant-to-clinician mapping scenarios. We simulated continuous outcome data based on various clinical scenarios in Whole Health Options and Pain Education trial using a range of intraclass correlation coefficients and mapping matrices and used Gibbs samplers with conjugate priors to obtain posteriors of the intraclass correlation coefficients under those different scenarios. Posterior means and medians and their biases are calculated for the intraclass correlation coefficients to evaluate the operating characteristics of the Bayesian intraclass correlation coefficient estimators. Results Power for Whole Health Team versus Primary Care Group Education is sensitive to the intraclass correlation coefficient in the Whole Health Team arm. In these two arms, an increased number of clinicians, more evenly distributed workload of clinicians, or more homogeneous treatment group sizes leads to increased power. Our simulation study for the intraclass correlation coefficient estimation indicates that the posterior mean intraclass correlation coefficient estimator has less bias when the true intraclass correlation coefficients are large (i.e. 0.10), but when the intraclass correlation coefficient is small (i.e. 0.01), the posterior median intraclass correlation coefficient estimator is less biased. Conclusion Knowledge of intraclass correlation coefficients and the structure of clustering are critical to the design of individually randomized group treatment trials with partially nested clusters. We demonstrate that the intraclass correlation coefficient of the Whole Health Team arm can affect power in the Whole Health Options and Pain Education trial. A Bayesian approach provides a flexible procedure for estimating the intraclass correlation coefficients under complex scenarios. More work is needed to educate the research community about the individually randomized group treatment design and encourage publication of intraclass correlation coefficients to help inform future trial designs.

Androgenetic complete hydatidiform moles (CHMs) are associated with an increased risk of gestational trophoblastic neoplasia. P57KIP2 expression in hydatidiform moles is thought to be a powerful marker for differentiating CHMs from partial hydatidiform moles (PHMs). However, since there are so few such families clinically, very few studies have addressed the importance of p57KIP2-positive in the diagnosis and prognosis of CHM. This study aimed to emphasize the significance of the accurate diagnosis of rare CHM and careful follow-up. The classification of the hydatidiform mole was based on morphologic examination and p57KIP2 expression was determined by p57KIP2 immunohistochemical staining. Copy number variation sequencing was used to determine the genetic make-up of the mole tissues. In addition, the short tandem repeat polymorphism analysis was used to establish the parental origin of the moles. Finally, whole-exome sequencing was performed to identify the causal genetic variants associated with this case. In one Chinese family, the proband had numerous miscarriages throughout her two marriages. Morphologic evaluation and molecular genotyping accurately sub-classified two molar specimens as uniparental disomy CHM of androgenetic origin. Furthermore, p57KIP2 expression was found in cytotrophoblasts and villous stromal cells. In the tissue, there were hyperplasia trophoblastic cells and heteromorphic nuclei. In this family, no deleterious variant genes associated with recurrent CHM were detected. It is important to evaluate the prognostic value of p57KIP2 expression in androgenetic recurrent CHM. This knowledge may help to minimize erroneous diagnosis of CHMs as PHMs, as well as making us aware of the need to manage potential gestational trophoblastic neoplasia.

Caching and transcoding at multi-access edge computing (MEC) server and wireless resource allocation in eNodeB interact with each other and together determine the quality of experience (QoE) of dynamic adaptive streaming over HTTP (DASH) clients. However, the relationship among the three factors has not been explored, which has led to limited improvement in clients’ QoE. Therefore, we propose a joint optimization framework of video segment caching and transcoding in MEC servers and resource allocation to improve the QoE of DASH clients. Based on the established framework, we develop an MEC caching management mechanism that consists of the MEC caching partition, video segment deletion, and MEC caching space transfer. Then, a joint optimization algorithm that combines the video segment caching and transcoding in the MEC server and resource allocation is proposed. In the algorithm, the clients’ channel state and the playback status and cooperation among MEC servers are employed to estimate the client's priority, video segment representation switch and continuous playback time. Considering the above four factors, we develop a utility function model of clients’ QoE. Then, we formulate a mixed-integer nonlinear programming mathematical model to maximize the total utility of DASH clients, where the video segment caching and transcoding strategy and resource allocation strategy are jointly optimized. To solve this problem, we propose a low-complexity heuristic algorithm that decomposes the original problem into multiple subproblems. The simulation results show that our proposed algorithms efficiently improve client's throughput, received video quality and hit ratio of video segments while decreasing the playback rebuffering time, video segment representation switch and system backhaul traffic.

Mingran Qi,1 Bin Liu,2 Shuai Li,1 Zhaohui Ni,1,3– 5 Fan Li1,3– 6 1Department of Pathogenobiology, The Key Laboratory of Zoonosis, Chinese Ministry of Education, College of Basic Medicine, Jilin University, Changchun, Jilin, People’s Republic of China; 2Cardiovascular Disease Center, The First Hospital of Jilin University, Changchun, Jilin, People’s Republic of China; 3The Key Laboratory for Bionics Engineering, Ministry of Education, Jilin University, Changchun, Jilin, People’s Republic of China; 4Engineering Research Center for Medical Biomaterials of Jilin Province, Jilin University, Changchun, Jilin, People’s Republic of China; 5Key Laboratory for Health Biomedical Materials of Jilin Province, Jilin University, Changchun, Jilin, People’s Republic of China; 6State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, Xinjiang, People’s Republic of ChinaCorrespondence: Zhaohui Ni; Fan LiDepartment of Pathogenobiology, The Key Laboratory of Zoonosis, Chinese Ministry of Education, College of Basic Medicine, Jilin University, No. 126 Xinmin Street, Changchun, Jilin, 130021, People’s Republic of ChinaTel +86-431-85619107Email nich@jlu.edu.cn; lifan@jlu.edu.cnIntroduction: The current COVID-19 pandemic caused by a novel coronavirus SARS-CoV-2 is a quickly developing global health crisis, yet the mechanisms of pathogenesis in COVID-19 are not fully understood.Methods: The RNA sequencing data of SARS-CoV-2-infected cells was obtained from the Gene Expression Omnibus (GEO). The differentially expressed mRNAs (DEmRNAs), long non-coding RNAs (DElncRNAs), and microRNAs (DEmiRNAs) were identified by edgeR, and the SARS-CoV-2-associated competing endogenous RNA (ceRNA) network was constructed based on the prediction of bioinformatic databases. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted with the SARS-CoV-2-related DEmRNAs, and the protein–protein interaction network was also built basing on STRING database. The ROC analysis was performed for assessing the diagnostic efficiency of hub genes.Results: The results indicated that SARS-CoV-2-related DEmRNAs were associated with the interferon signaling pathway and other antiviral processes, such as IFNL3, IFNL1 and CH25H. Our analysis suggested that lncRNA NEAT1 might regulate the host immune response through two miRNAs, hsa-miR-374-5p and hsa-miR-155-5p, which control the expression of SOCS1, IL6, IL1B, CSF1R, CD274, TLR6, and TNF. Additionally, IFI6, HRASLS2, IGFBP4 and PTN may be potential targets based on an analysis comparing the transcriptional responses of SARS-CoV-2 infection with that of other respiratory viruses.Discussion: The unique ceRNA network identified potential non-coding RNAs and their possible targets as well as a new perspective to understand the molecular mechanisms of the host immune response to SARS-CoV-2. This study may also aid in the development of innovative diagnostic and therapeutic strategies.Keywords: COVID-19, ceRNA network, non-coding RNA, antiviral targets

The purpose of this study is to develop and validate the intelligent diagnosis of severe DR with lesion recognition based on color fundus photography. The Kaggle public dataset for DR grading is used in the project, including 53,576 fundus photos in the test set, 28,101 in the training set, and 7,025 in the validation set. We randomly select 4,192 images for lesion annotation. Inception V3 structure is adopted as the classification algorithm. Both 299 × 299 pixel images and 896 × 896 pixel images are used as the input size. ROC curve, AUC, sensitivity, specificity, and their harmonic mean are used to evaluate the performance of the models. The harmonic mean and AUC of the model of 896 × 896 input are higher than those of the 299 × 299 input model. The sensitivity, specificity, harmonic mean, and AUC of the method with 896 × 896 resolution images as input for severe DR are 0.925, 0.907, 0.916, and 0.968, respectively. The prediction error mainly occurs in moderate NPDR, and cases with more hard exudates and cotton wool spots are easily predicted as severe cases. Cases with preretinal hemorrhage and vitreous hemorrhage are easily identified as severe cases, and IRMA is the most difficult lesion to recognize. We have studied the intelligent diagnosis of severe DR based on color fundus photography. This artificial intelligence–based technology offers a possibility to increase the accessibility and efficiency of severe DR screening.

Novelty is the primary requirement and breeding target for plant breeding, which can make a significant contribution to the new cultivar. The key factor for successful breeding is the genetic variation in the progeny, which depends on the degree of genetic material mixing after meiosis. However, meiotic recombination is tightly astricting in plants, resulting in a limited number of crossovers (COs). Recently, several anti-CO factors have been identified that limiting the meiotic recombination in plants, and the knock-out mutants displayed a significant increase in recombination frequency. This provides a universal tool to manipulate the meiotic recombination in plants by applying anti-CO genes, which will facilitate the breeding procedure. Due to the rapid development of genome sequencing and gene editing technologies, the genomes of more and more plants have been sequenced. In the meanwhile, the efficient CRISPR-Cas9 system has also been established in plants. Thus, it’s time to break the shackles of meiotic recombination to create novel cultivars in the biological era of genomics. Here we summarize the functional studies of the main meiotic recombination suppressors in plants, with the discussion of the possibility to apply the anti-CO genes in plant breeding as an emerging tool, especially for ornamental plant breeding.

The ability of cubic phase (3C-) silicon carbide (SiC) to grow heteroepitaxially on silicon (Si) substrates (3C-SiC-on-Si) is an enabling feature for cost-effective wide bandgap devices and homogeneous integration with Si devices. In this article, the authors evaluated 3C-SiC-on-Si Schottky barrier contacts by fabricating and testing nonfreestanding lateral Schottky barrier diodes (LSBD). To gain a deep physical insight of the complex carrier transport phenomena that take place in this material, advanced technology computer aided design (TCAD) models were developed that allowed accurately matching of measurements with simulations. The models incorporate the device geometry, an accurate representation of the bulk material properties, and complex trapping/de-trapping and tunneling phenomena that appear to affect the device performance. The observed nonuniformities of the Schottky barrier height (SBH) were successfully modeled through the incorporation of interfacial traps. The combination of TCAD with fabrication and measurements enabled the identification of trap profiles and pin their influence on the electrical performance of 3C-SiC-on-Si LSBD. The effect of temperature was studied by engaging the identified trap profiles and calculating the occupation distribution of electrons in 3C-SiC at elevated temperature. The investigation constitutes an imperative knowledge step towards the development of devices that take advantage of 3C-SiC material properties.

Handwritten signature is one of the most important behavioral biometrics and plays an important role in the field of identity verification . It is regarded as a legal means to verify personal identity by administrative and financial institutions. Traditional manual signature verification requires large labor costs and the probability of verification error is relatively high. Nowadays, tablets are often used for signature capturing, which motivates us to explore the feasibility of using tablets for signature verification. In this paper, we propose an online handwriting s ignature v erification system based on s ound and v ibration (SVSV) generated during the signing process. We develop an application to collect signature-related vibration and sound data. We first extract the time domain features of the sound signal and use Fast Fourier Transform to extract the frequency domain features of the sound data. For vibration data, we use Discrete Cosine Transform for dimensionality reduction and feature extraction. Then we fuse the sound and vibration features. Finally, we design an efficient one-class classifier based on the Convolutional Neural Network to perform signature verification. Through extensive experiments with 12 volunteers, the results show that SVSV is a robust and efficient system with an AUC of 0.984 and an EER of 0.05 .

Contagious diseases are prevalent even in the current era of advanced technology. A uniformed initiative is required to build a reliable interactive information exchange service targeting vaccination data management and other medical services. The conventional data exchange mechanism is centralized, creating many vulnerable issues such as a single point failure, data leakage, access control, etc. This article introduces a Blockchain-based medical data-sharing framework (called GlobeChain) to overcome the technical challenges to handle the outbreak records. The challenges that might arise due to the proposed Blockchain-based framework are also presented as a future direction that grabs the proposal's effectiveness.

Obstructive sleep apnea (OSA) leads to important vascular abnormalities, including the endothelial dysfunction and the production of endothelial cell adhesion molecules. The adhesion molecules play an important role in the process of endothelial dysfunction in the pathogenesis of atherosclerosis. We assess the relationship between the levels of adhesion molecules and the presence of coronary artery disease (CAD) in Chinese adults with moderate to severe OSA.The cross-sectional study included a total of 189 Chinese adults: 90 patients with moderate to severe OSA (apnea-hypopnea index≥15 events/h) alone, 40 patients with moderate to severe OSA and CAD, and 59 controls without OSA or with mild OSA and without CAD. We used high-throughput Multiplex Immunobead Assay technology to simultaneously test plasma levels of vascular cell adhesion molecule 1 (VCAM-1) and intercellular adhesion molecule 1 (ICAM-1). The associations between the levels of circulating adhesion molecules and CAD in moderate to severe OSA patients were evaluated by multivariate logistic regression analysis.The circulating VCAM-1 levels were significantly elevated in patients suffering from moderate to severe OSA combined CAD compared with patients having moderate to severe OSA alone [853.28 (564.26) vs. 416.61 (301.69) ng/mL, P 0.001]. Furthermore, circulating VCAM-1 levels were independently associated with CAD (odds ration = 2.113, 95%CI 1.400-2.766, P 0.001) and showed higher discriminatory accuracy in assessing the presence of CAD (AUC: 0.899, 95%CI 0.849-0.950, P 0.001) in moderate to severe OSA patients. However, no significant association was found between circulating ICAM-1 levels and CAD in moderate to severe OSA patients.The circulating VCAM-1 levels were significantly correlated with the presence of CAD in Chinese adults with moderate to severe OSA. The circulating VCAM-1 may function as a novel biomarker for monitoring the development and progression of CAD in patients with moderate to severe OSA.

The safety of the elderly has attracted much attention nowadays. Among various daily activities, fall is one of the most dangerous events for the elderly, especially those who live alone. Most existing works on fall detection are based on wearable devices, which are inconvenient in using. Several solutions only use coarse-grained Wi-Fi signal information that contains many biases, and lack considerations on environmental changes. These situations motivate us to design a fine-grained and robust fall detection approach. In this article, we propose a fall detection system, called FallViewer, based on analyzing the channel state information (CSI) of Wi-Fi signals. To get fine-grained information, we propose phase and amplitude calibration methods for deviation correction. Then, an adjustment approach for antenna power is designed to eliminate the multipath interference. Furthermore, we apply a double sliding window to get a flexible threshold, which improves the robustness of FallViewer to various environments. Finally, FallViewer extracts features of the processed Wi-Fi signal and sends the features to a LibSVM for classification. Through experiments in different environments, FallViewer can detect fall events with an average accuracy of 95.8%, which indicates that FallViewer can work reliably and effectively.

Hemolymphangioma is an extremely rare type of lymphatic and vascular malformation, histologically comprised of both cystic dilated veins and lymphatic vessels. They have been reported to occur in the skin, extremities, pancreas, spleen, mediastinum, as well as in the gastrointestinal tract. A 61-year-old male patient presented with a 2-week history of left lower abdominal and back pain. He had no relevant personal or family past medical history. He denied fever, trauma or weight change, but had noted early satiety with eating. On physical examination, a 10 cm soft, mobile, well-defined, minimally tender mass was palpated in the lower left abdomen. Computed tomography confirmed a large intraperitoneal cystic mass, and resection was advised. The mass was completely excised laparoscopically from the transverse mesocolon. Histopathology verified the diagnosis of hemolymphangioma. The patient recovered uneventfully, and no recurrence was identified at 3 months follow-up. Hemolymphangioma is more common in women and occurs in the fourth to fifth decades of life. The intent of this case report and literature review was to highlight the key aspects of presentation, organ involvement, imaging, histopathological characteristics, and treatment of hemolymphangioma involving the gastrointestinal tract.

Drowsy driving is one of the biggest threats to driving safety, which has drawn much public attention in recent years. Thus, a simple but robust system that can remind drivers of drowsiness levels with off-the-shelf devices (e.g., smartphones) is very necessary. With this motivation, we explore the feasibility of using acoustic sensors on smartphones to detect drowsy driving. Through analyzing real driving data to study characteristics of drowsy driving, we find some unique patterns of Doppler shift caused by three typical drowsy behaviours (i.e., nodding, yawning and operating steering wheel), among which operating steering wheels is also related to drowsiness levels. Then, a real-time D rowsy D riving D etection system named D $^3$ 3 -Guard is proposed based on the acoustic sensing abilities of smartphones. We adopt several effective feature extraction methods, and carefully design a high-accuracy detector based on LSTM networks for the early detection of drowsy driving. Besides, measures to distinguish drowsiness levels are also introduced in the system by analyzing the data of operating steering wheel. Through extensive experiments with five drivers in real driving environments, D $^3$ 3 -Guard detects drowsy driving actions with an average accuracy of 93.31%, as well as classifies drowsiness levels with an average accuracy of 86%.

Tumor metastasis remains a major challenge for patients with breast cancer. Aberrant epigenetic factor lysine‐specific demethylase 6B (KDM6B) has been associated with tumor progression. Here, we show that KDM6B is significantly down‐regulated in human breast cancer tissues, and its low expression is associated with poor prognosis of patients with breast cancer. Furthermore, overexpression of KDM6B remarkably inhibited cell proliferation, invasion, migration and epithelial–mesenchymal transition markers of breast cancer cells in vitro and tumor growth and lung metastasis in vivo. Notably, the expression of KDM6B in breast cancer tissues was negatively correlated with that of β‐catenin, and overexpression of KDM6B decreased the expression of β‐catenin and its accumulation in the nucleus of breast cancer cells. Overall, our findings provide novel insights into suppression of metastasis of breast cancer cells by KDM6B via β‐catenin and suggest involvement of the KDM6B‐Wnt/β‐catenin axis in breast cancer progression., We investigated the effect of histone demethylase lysine‐specific demethylase 6B (KDM6B) on metastasis of breast cancer. KDM6B could inhibit the growth and metastasis of breast cancer by suppressing β‐catenin expression and its nuclear accumulation. These results suggest a significant role for the KDM6B‐Wnt/β‐catenin axis in breast cancer progression.

To comparatively analyze differences in macular choroidal thickness and volume in primary chronic angle-closure glaucoma (PACG) eyes.Thirty-one PACG patients were sequentially selected for this case-control study. Thirty-one eyes with PACG were included in group A, 31 fellow eyes were included in group B, and group C included 67 normal eyes. Enhanced-depth imaging optical coherence tomography (EDI-OCT) was used to measure choroidal thickness and volume.The choroidal thicknesses and volumes of the central subfield macula (CSM), nasal inner macula (NIM), temporal inner macula (TIM), inferior inner macula (IIM), temporal outer macula (TOM), inferior outer macula (IOM), and mean macula (MM) in group A were all higher than those in group C (P 0.05). The choroidal thicknesses and volumes of the NIM, superior inner macula (SIM), IIM, nasal outer macula (NOM), and MM in group B were all higher than those in group C (P 0.05). No statistically significant differences were found between groups A and B (P 0.05). The choroidal thicknesses of different macular regions in group A were not correlated with the mean defect (MD).Increased macular choroidal thickness may be a common anatomical characteristic of PACD eyes. Macular choroidal thickness is not a good marker for assessing PACG severity.

Artificial Intelligence (AI) has expanded in a diverse context, it infiltrates our social lives and is a critical part of algorithmic decision-making. Adopting AI technology, especially AI-enabled design, by end users who are non-AI experts is still limited. The incomprehensible, untransparent decision-making and difficulty of using AI become obstacles which prevent these end users to adopt AI technology. How to design the user experience (UX) based on AI technologies is an interesting topic to explore.This paper investigates how non-AI-expert end users can be engaged in the design process of an AI-enabled application by using a framework called Smart Service Blueprint Scape (SSBS), which aims to establish a bridge between UX and AI systems by mapping and translating AI decisions based on UX. A Dutch mobility service called ‘stUmobiel ’ was taken as a design case study. The goal is to design a reservation platform with stUmobiel end users. Co-creating with case users and assuring them to understand the decision-making and service provisional process of the AI-enabled design is crucial to promote users’ adoption. Furthermore, the concern of AI ethics also arises in the design process and should be discussed in a broader sense.

The purpose of this meta-analysis is to comprehensively investigate the effect of iodine excess on children's intellectual development in areas with high iodine levels in their drinking water. We systematically searched the electronic databases and identified 17 publications (16 in Chinese and 1 in English) on the effect of iodine excess on children's intelligence published between January 31, 1985, and January 31, 2020. This meta-analysis included 14,794 children from 28 studies. The results showed that compared with the control group, the intelligence level of children in the high iodine group reduced significantly by 1.64 points (WMD=-1.64; 95% CI (-3.225, -0.049), Z=2.02, P 900μg/L, the intelligence level of the high iodine groups decreased by varying degrees, although not statistically significant (all P>0.05). The water iodine concentration of the control group was divided into two groups ( 0.05). Conversely, we observed that among the studies which used the China Binet intelligence test and the binaphthalene intelligence test of Tanzhida in Japan to evaluate children's intelligence level, the intelligence level of children in the high iodine groups was significantly lower (3.65 points and 8.0 points, respectively) compared with the control groups (P 0.05), the association was statistically significant in the southern part of China (WMD=-1.86, 95% CI (-3.57, -0.09), P

Background:. There were few studies on real-world data about autologous hematopoietic stem cell transplantation (auto-HSCT) or allogeneic HSCT (allo-HSCT) in peripheral T-cell lymphoma (PTCL). This study aimed to investigate the clinical outcomes of patients who received auto-HSCT or allo-HSCT in China. Methods:. From July 2007 to June 2017, a total of 128 patients who received auto-HSCT (n = 72) or allo-HSCT (n = 56) at eight medical centers across China were included in this study. We retrospectively collected their demographic and clinical data and compared the clinical outcomes between groups. Results:. Patients receiving allo-HSCT were more likely to be diagnosed with stage III or IV disease (95% vs. 82%, P = 0.027), bone marrow involvement (42% vs. 15%, P = 0.001), chemotherapy-resistant disease (41% vs. 8%, P = 0.001), and progression disease (32% vs. 4%, P

The environmental regulation and foreign direct investment (FDI) inflow have an important impact on the progress of green technology. This study analyzes the impacts of environmental regulation and FDI on green technology innovation (GTI) based on the panel data of 13 Chinese manufacturing sectors. The results of static panel regression show that the environmental regulation has a positive impact on GTI, while the FDI has a negative impact. The results of the panel threshold model reveal that the effect of environmental regulation on GTI presents a nonlinear shape. The negative effect of FDI on GTI is strengthened when the environmental regulation exceeds its threshold. Increasing FDI inflow can inhibit the effect of environmental regulation. Meanwhile, a strict environmental regulation can enhance the inhibiting effect of FDI on GTI. The FDI inflow into high-tech manufacturing sectors has a less negative impact on GTI than the FDI inflow into low-tech sectors in the case of the enhancement of environmental regulation. This study provides some implications for the formulation of environmental regulation and the FDI inflow into China to improve the GTI.

BACKGROUND: The significant morbidity and mortality resulted from the infection of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) call for urgent development of effective and safe vaccines. We report the immunogenicity and safety of an inactivated SARS-CoV-2 vaccine, KCONVAC, in healthy adults. METHODS: Phase 1 and phase 2 randomized, double-blind, and placebo-controlled trials of KCONVAC were conducted in healthy Chinese adults aged 18 to 59 years. The participants in the phase 1 trial were randomized to receive two doses, one each on Days 0 and 14, of either KCONVAC (5 or 10 µg/dose) or placebo. The participants in the phase 2 trial were randomized to receive either KCONVAC (at 5 or 10 µg/dose) or placebo on Days 0 and 14 (0/14 regimen) or Days 0 and 28 (0/28 regimen). In the phase 1 trial, the primary safety endpoint was the proportion of participants experiencing adverse reactions/events within 28 days following the administration of each dose. In the phase 2 trial, the primary immunogenicity endpoints were neutralization antibody seroconversion and titer and anti-receptor-binding domain immunoglobulin G seroconversion at 28 days after the second dose. RESULTS: In the phase 1 trial, 60 participants were enrolled and received at least one dose of 5-µg vaccine (n = 24), 10-µg vaccine (n = 24), or placebo (n = 12). In the phase 2 trial, 500 participants were enrolled and received at least one dose of 5-µg vaccine (n = 100 for 0/14 or 0/28 regimens), 10-µg vaccine (n = 100 for each regimen), or placebo (n = 50 for each regimen). In the phase 1 trial, 13 (54%), 11 (46%), and seven (7/12) participants reported at least one adverse event (AE) after receiving 5-, 10-µg vaccine, or placebo, respectively. In the phase 2 trial, 16 (16%), 19 (19%), and nine (18%) 0/14-regimen participants reported at least one AE after receiving 5-, 10-µg vaccine, or placebo, respectively. Similar AE incidences were observed in the three 0/28-regimen treatment groups. No AEs with an intensity of grade 3+ were reported, expect for one vaccine-unrelated serious AE (foot fracture) reported in the phase 1 trial. KCONVAC induced significant antibody responses; 0/28 regimen showed a higher immune responses than that did 0/14 regimen after receiving two vaccine doses. CONCLUSIONS: Both doses of KCONVAC are well tolerated and able to induce robust immune responses in healthy adults. These results support testing 5-µg vaccine in the 0/28 regimen in an upcoming phase 3 efficacy trial. TRIAL REGISTRATION: http://www.chictr.org.cn/index.aspx (No. ChiCTR2000038804, http://www.chictr.org.cn/showproj.aspx?proj=62350; No. ChiCTR2000039462, http://www.chictr.org.cn/showproj.aspx?proj=63353).

This paper proposes a novel displacement–strain transfer (DST) matrix method to estimate the local bending deformation of bridge deck using the measured strain. The DST matrix of the bi-dimensional plate with various boundary conditions is derived theoretically, and the local bending deformation of the plate can be further estimated. A plate with four simply supported edges, two simply supported edges, and one clamped edge under various load cases is simulated. The DST matrix is calculated, and the local bending deformation is finally estimated. The proposed method is also verified by the experimental test of a simply supported plate. Both the numerical and experimental results indicate that the proposed method can effectively estimate the local bending deformation of a bi-dimensional plate. Finally, a steel–concrete composite girder bridge is simulated, and the local bending deformation of the bridge deck is also effectively estimated based on the proposed method.

Background Intradural disc herniation (IDH) is a rare type of disc degeneration that infrequently affects the upper lumbar spine. Pre- and intraoperative diagnosis and surgical management of IDH are challenging. The present case study provides insight into these aspects of upper lumbar IDH and discusses possible mechanisms. Case description A 63-year-old female with a history of chronic lower back and leg pain presented with an acute lumbar sprain that had occurred 1 month prior. The pain progressed and spread to the front of the left thigh, which affected her ability to lift her leg when ascending/descending stairs. Sagittal gadolinium-enhanced magnetic resonance imaging (MRI) revealed a disc protruding into the ventral dural sac showing a hawk-beak sign, and the posterior edge of the disc annulus and local posterior longitudinal ligament was broken. Total L2 laminectomy was performed, and the dorsal side of the dural sac was exposed and incised to enable exploration of the ventral side of the dura. We found two free fragments protruding into the inner wall of the dura through the left ventral dura mater defect. After carefully and completely removing the mass, we repaired the defect and performed internal fixation. Postoperative pathologic analysis confirmed that the mass was nucleus pulposus tissue from the degenerated disc. The patient's pain significantly improved after surgery, and she was able to walk normally at the 1-month follow-up. Conclusion Upper lumbar IDH is an extremely rare type of disc degeneration. An enhanced MRI scan can provide diagnostic evidence, but the final diagnosis requires surgical exploration of the path of herniation and pathologic examination of the mass lesion.

Purpose. To evaluate the differences in macular choroidal thickness and volume between patients with primary open-angle glaucoma (POAG) and healthy controls to assess the correlation between macular choroidal thickness and visual field mean defect (MD). Methods. Case-control study. A total of 101 patients (101 eyes) with POAG who were hospitalized in our hospital and 102 healthy subjects (102 eyes) matched by age, sex, and axial length were consecutively selected as the POAG group and the control group, respectively. The macular choroidal thickness and volume in nine regions were measured in all subjects by enhanced-depth imaging optical coherence tomography (EDI-OCT). Results. The mean thicknesses of the choroid in the macular area in the POAG group and healthy group were 207.97 ± 62.83 µm and 208.24 ± 47.97 µm, and the mean volumes were 0.63 ± 0.19 µm3 and 0.64 ± 0.14 µm3. There were no significant differences in macular choroidal thickness, volumes of various macular regions, or mean choroidal thickness or volume between the POAG and healthy groups (all p > 0.05 ). The macular choroidal thickness of various macular regions was not correlated with visual field MD in the POAG group (all p > 0.05 ). Conclusion. The macular choroidal thicknesses and volumes in POAG patients were not significantly different from those in healthy individuals. The macular choroidal thickness was not correlated with MD in POAG patients. Therefore, macular choroidal thickness is not an appropriate parameter to evaluate damage caused by POAG, and the role of the macular choroid thickness in POAG needs to be further investigated.

Smoke detection based on video monitoring is of great importance for early fire warning. However, most of the smoke detection methods based on neural network only consider the normal weather. The harsh weather such as the fog environment is ignored. In this paper, we propose a smoke detection in normal and fog weather, which combines attention mechanism and feature-level and decision-level fusion module. First, a new fog smoke dataset with diverse positive and hard negative samples dataset is established through online collection and offline shooting. Then, an attention mechanism module combining spatial attention and channel attention is proposed to solve the problem of small smoke detection. Next, a lightweight feature-level and decision-level fusion module is proposed, which can not only improve the discrimination of smoke, fog and other similar objects, but also ensure the real-time performance of the model. Finally, a large number of comparative experiments on the existing dataset and our self-created dataset, show that our method can obtain higher detection accuracy rate, precision rate, recall rate, and F1 score from the perspective of overall, each category, small smoke and hard negative samples detection than the existing methods.

Introduction: The thulium laser resection of bladder tumors (TmLRBT) was increasingly used in the treatment of non-muscle-invasive bladder cancer (NMIBC) recently, and here we report the relevant outcomes of our institution to evaluate its efficacy and safety. Methods: We retrospectively collected the data of NMIBC patients who underwent either TmLRBT or transurethral resection of bladder tumor (TURBT). The baseline characteristics and perioperative outcomes were compared in these 2 groups. Results: The TmLRBT had a higher rate of detrusor identification than TURBT (97.4 vs. 87.6%, p = 0.001). After screening, 134 patients who underwent TmLRBT and 152 patients who received TURBT were enrolled in the analysis, and their baseline characteristics were similar. During the TURBT, 24 (15.8%) obturator nerve reflexes and 9 (5.9%) bladder perforations occurred, while none happened during the TmLRBT. After surgery, TmLRBT patients had fewer postoperative gross hematuria (38.1 vs. 96.7%, p < 0.001) and postoperative irrigation (27.6 vs. 92.7%, p < 0.001), and its irrigation duration was significantly shorter (2.3 vs. 3.3 day, p < 0.001). During the follow-up, no significant difference in the recurrence rate was detected (p = 0.315). Conclusions: TmLRBT is a safer technique than conventional TURBT in the treatment of NMIBC, and it could offer better specimens for pathologic assessment while the cancer control was not compromised.

Nowadays, people’s requirements for comfort are getting higher and higher, and traditional steady-state thermal comfort environment sometimes cannot meet people’s requirements. Dynamic thermal comfort is considered to meet people's requirements for comfort better than traditional thermal comfort, and it is also conducive to the health of occupants and building energy conservation. Therefore, this article reviews the literature on dynamic thermal comfort. First, this article briefly describes the transition from a steady-state thermal environment to a dynamic thermal environment. Next, this article reviews the research related to dynamic thermal comfort, such as the frequency of airflow fluctuations, simulation of natural wind, thermal prediction models, the use of intelligent detection equipment, and personal environmental control. This article summarizes the related research and development of dynamic thermal comfort from the aspects of dynamic airflow parameters, indoor thermal environment regulation, thermal experience, etc. This article aims to illustrate the necessity of the development of dynamic thermal comfort and its current results. The results show that under the trend of the artificial intelligence era, dynamic thermal comfort still has broad development potential. This article It can provide some research ideas for subsequent thermal comfort research. Practical application: This paper summarizes the research and development of dynamic thermal comfort from dynamic airflow, indoor thermal environment control, thermal experience, etc., and makes appropriate extensions and prospects accordingly. At the same time, the necessity of combining thermal comfort with AI trends is emphasized. This paper can provide references and ideas for thermal research on thermal comfort.

Previous research shows that online reviews may have different effects for search goods and experience goods. However, as a typical type of experience goods, software can be further divided into different categories based on product characteristics. Little research has been conducted regarding the different effects of online reviews for different types of software. Furthermore, to offer free samples is another common practice of software firms to alleviate consumer uncertainty prior to purchase. To fill the corresponding research gap, this research focuses on the interaction effects between online reviews and free samples for different types of software. Through our empirical analysis, we find that user ratings significantly increase consumers’ sample downloads. Furthermore, consumers download more samples for some categories than for others. Finally, user and editor ratings might have differential effects for different types of software.

Software-Defined Networking has become an integral technology for large scale networks that require dynamic flow management. It separates the control function from data plane devices and centralizes it in a domain controller. However, only a limited number of switches can be managed by a single and centralized controller which introduces challenges such as scalability, reliability, and availability. Distributed controller architecture resolves these issues but also introduces new challenges of uneven load and traffic management across domains. As real-world networks have redundant links, hence a significant challenge is to distribute traffic flows on multiple paths, within a domain, and across multiple independent domains. The selection of ingress and egress switches becomes even more problematic if the intermediate domain is non-cooperative. In this work, we propose a Dynamically Optimized and Load-balanced Path for Inter-domain (DOLPHIN) communication system, a customized solution for different SDN controllers. It provides control beyond the virtual switch elements in intra and inter-domain communication and extends the range of programmability to wireless devices, such as the Internet of Things or vehicular networks. Extensive simulation results show that the traffic load is distributed evenly on multiple links connecting different domains. We model data center communication and 5G vehicular network communication to show that, by load balancing the flow completion times of the different types of network traffic can be significantly improved.

Background: To evaluate differences in the proportion of uterine fibroid (UF) treatments that are uterine-sparing between Black women and White women and identify factors that could explain dispari...

Objective To minimize the adverse events of uterine compression suture in controlling postpartum hemorrhage (PPH) and to search for a prophylactic approach to potential PPH. Methods A retrospective analysis was performed in 39 women with removable retropubic uterine compression suture (RRUCS) to stop PPH due to uterine atony during cesarean section (CS). The procedure was to suspend and compress the uterus to the retropubic abdominal wall using an absorbable suture. Results The technique was sufficient to stanch bleeding immediately in 36 patients (92.31%, 36/39). No morbidity or abnormalities occurred in women who underwent RRUCS. Subsequent pregnancies occurred in 10 cases, but the others lacked the desire for future pregnancy. Conclusion RRUCS is a simple, safe, and effective technique in controlling atonic PPH; it is also used as a prophylactic application in patients with potential PPH after CS.