bluuebunny/crossref_metadata_2025 huggingface dataset:
Auto-weighted Robust Federated Learning with Corrupted Data Sources
Authors: Li Shenghui , Ngai Edith , Ye Fanghua , Voigt Thiemo
Published: February 2022

Federated learning provides a communication-efficient and privacy-preserving training process by enabling learning statistical models with massive participants without accessing their local data. Standard federated learning techniques that naively minimize an average loss function are vulnerable to data corruptions from outliers, systematic mislabeling, or even adversaries. In this article, we address this challenge by proposing Auto-weighted Robust Federated Learning (
ARFL
), a novel approach that jointly learns the global model and the weights of local updates to provide robustness against corrupted data sources. We prove a learning bound on the expected loss with respect to the predictor and the weights of clients, which guides the definition of the objective for robust federated learning. We present an objective that minimizes the weighted sum of empirical risk of clients with a regularization term, where the weights can be allocated by comparing the empirical risk of each client with the average empirical risk of the best

\( p \)

clients. This method can downweight the clients with significantly higher losses, thereby lowering their contributions to the global model. We show that this approach achieves robustness when the data of corrupted clients is distributed differently from the benign ones. To optimize the objective function, we propose a communication-efficient algorithm based on the blockwise minimization paradigm. We conduct extensive experiments on multiple benchmark datasets, including CIFAR-10, FEMNIST, and Shakespeare, considering different neural network models. The results show that our solution is robust against different scenarios, including label shuffling, label flipping, and noisy features, and outperforms the state-of-the-art methods in most scenarios.
Few-Shot Object Detection: A Survey
Authors: Antonelli Simone , Avola Danilo , Cinque Luigi , Crisostomi Donato , Foresti Gian Luca , Galasso Fabio , Marini Marco Raoul , Mecca Alessio , Pannone Daniele
Published: February 2022

Deep learning approaches have recently raised the bar in many fields, from Natural Language Processing to Computer Vision, by leveraging large amounts of data. However, they could fail when the retrieved information is not enough to fit the vast number of parameters, frequently resulting in overfitting and therefore in poor generalizability. Few-Shot Learning aims at designing models that can effectively operate in a scarce data regime, yielding learning strategies that only need few supervised examples to be trained. These procedures are of both practical and theoretical importance, as they are crucial for many real-life scenarios in which data is either costly or even impossible to retrieve. Moreover, they bridge the distance between current data-hungry models and human-like generalization capability. Computer vision offers various tasks that can be few-shot inherent, such as person re-identification. This survey, which to the best of our knowledge is the first tackling this problem, is focused on Few-Shot Object Detection, which has received far less attention compared to Few-Shot Classification due to the intrinsic challenge level. In this regard, this review presents an extensive description of the approaches that have been tested in the current literature, discussing their pros and cons, and classifying them according to a rigorous taxonomy.
A Survey and Taxonomy of Latency Compensation Techniques for Network Computer Games
Authors: Liu Shengmei , Xu Xiaokun , Claypool Mark
Published: February 2022

Computer games, one of the most popular forms of entertainment in the world, are increasingly online multiplayer, connecting geographically dispersed players in the same virtual world over a network. Network latency between players and the server can decrease responsiveness and increase inconsistency across players, degrading player performance and quality of experience. Latency compensation techniques are software-based solutions that seek to ameliorate the negative effects of network latency by manipulating player input and/or game states in response to network delays. We search, find, and survey more than 80 papers on latency compensation, organizing their latency compensation techniques into a novel taxonomy. Our hierarchical taxonomy has 11 base technique types organized into four main groups. Illustrative examples of each technique are provided, as well as demonstrated use of the techniques in commercial games.
Deep Understanding Based Multi-Document Machine Reading Comprehension
Authors: Ren Feiliang , Liu Yongkang , Li Bochao , Wang Zhibo , Guo Yu , Liu Shilei , Wu Huimin , Wang Jiaqi , Liu Chunchao , Wang Bingchao
Published: February 2022

Most existing multi-document machine reading comprehension models mainly focus on understanding the interactions between the input question and documents, but ignore the following two kinds of understandings. First, to understand the semantic meaning of words in the input question and documents from the perspective of each other. Second, to understand the supporting cues for a correct answer from the perspective of intra-document and inter-documents. Ignoring these two kinds of important understandings would make the models overlook some important information that may be helpful for finding correct answers. To overcome this deficiency, we propose a deep understanding based model for multi-document machine reading comprehension. It has three cascaded deep understanding modules which are designed to understand the accurate semantic meaning of words, the interactions between the input question and documents, and the supporting cues for the correct answer. We evaluate our model on two large scale benchmark datasets, namely TriviaQA Web and DuReader. Extensive experiments show that our model achieves state-of-the-art results on both datasets.
A Contemporary Survey on Live Video Streaming from a Computation-Driven Perspective
Authors: Dao Nhu-Ngoc , Tran Anh-Tien , Tu Ngo Hoang , Thanh Tran Thien , Bao Vo Nguyen Quoc , Cho Sungrae
Published: February 2022

Live video streaming services have experienced significant growth since the emergence of social networking paradigms in recent years. In this scenario, adaptive bitrate streaming communications transmitted on web protocols provide a convenient and cost-efficient facility to serve various multimedia platforms over the Internet. In these communication models, video content is delivered optimally, possibly transcoded, edited automatically, and cached temporarily by network elements along the path. To this end, the computational capabilities of various network elements are considered as major resources to be optimized for service quality improvements. This article provides a contemporary survey of cutting-edge live video streaming studies from a computation-driven perspective. First, an overview of the global standards, system architectures, and streaming protocols is presented. Next, hierarchical computation-driven models of live video streaming are anatomized, including cloud-, edge-, and peer-to-peer-based solutions. Cutting-edge studies are then reviewed to discover the advances they have made in improving system performance in multiple areas. Finally, open challenges are presented to direct future research in this field.
Simultaneously Regulating the Band Gap and Catalytic Activity of TiO2 via Embedded MoO2 Based on Interlaced CNT Carrier for Li-S Battery to Achieve Efficient Adsorption
Authors: Wang Tan , Zhang Sibo , Lang Xiaoshi , Li Lan , Yao Chuangang , Cai Kedi
Published: February 2022

To tackle the issues of lithium sulfur battery (Li-S), a strategy of simultaneous regulating the band gap and catalytic activity of TiO2 via embedded MoO2 based on interlaced carbon nanotubes carrier as substrate material to achieve efficient adsorption has been proposed. This substrate material is controlled to be nanosized with abundant catalytically active sites and widely-distributed pore through the cross-linked porous conductive skeleton, further promoting the electrolyte penetration and charge transfer. In addition, the introduction of MoO2 tailors the Ti electronic states, so the substrate material renders high adsorption energy of −1.47 eV for Li2S6 by theoretical calculation. Furthermore, the cathode exhibits high conversion efficiency from long-chain lithium polysulfide to Li2S (Qlow/Qhigh (the conversion capacity of Li2S) is 2.91 at 0.1C) and excellent sulfur utilization and fast sulfur reaction kinetics. The cathode also exhibits a low-capacity fade and excellent cycling performance.
General trends in skeletal muscle coverage in undergraduate human anatomy and anatomy and physiology courses
Authors: Reynolds Amberly , Goodwin Michael , O’Loughlin Valerie Dean
Published: February 2022

There is a widely variable breadth of coverage of skeletal muscle content across both undergraduate human anatomy and undergraduate anatomy and physiology (A&P) courses. In response to the need for a more global understanding of the content taught in undergraduate anatomy courses, we developed an online survey (administered through Qualtrics) where both human anatomy and A&P faculty could report skeletal muscle coverage in their courses. The survey also collected comparative demographic institutional data such as the type of institution (community college vs. 4 year), course format, and geographic location of the undergraduate institution. Skeletal muscles surveyed included those listed and described in a typical undergraduate human anatomy text (McKinley MP, O’Loughlin VD, Pennefather O. Human Anatomy (5th ed.), 2017, p. 960). The data indicated some interesting instructional trends regarding muscular system coverage. First, both the “identification” and “action” of specific muscles are taught at a higher frequency than the teaching of either “attachments or innervation.” Innervation of specific skeletal muscles is the least taught concept. In each body region, certain muscles were taught with higher frequency than others. This research shows there is a global trend in teaching identification of specific skeletal muscles within each body region and often this is accompanied by teaching actions of said muscles. These general instructional trends may increase our understanding of the anatomical and physiological education our undergraduate students are receiving and will lead to further critical conversations about content development and curriculum.
Ataxia telangiectasia mutated is required for efficient proximal airway epithelial cell regeneration following influenza A virus infection
Authors: Warren Rachel , Dylag Andrew M. , Behan Molly , Domm William , Yee Min , Mayer-Pröschel Margot , Martinez-Sobrido Luis , O’Reilly Michael A.
Published: February 2022

Children and young adults with mutant forms of ataxia telangiectasia mutated (ATM), a kinase involved in DNA damage signaling and mitochondrial homeostasis, suffer from recurrent respiratory infections, immune deficiencies, and obstructive airways disease associated with disorganized airway epithelium. We previously showed in mice how Atm was required to mount a protective immune memory response to influenza A virus [IAV; Hong Kong/X31 (HKx31), H3N2]. Here, Atm wildtype (WT) and knockout (Atm-null) mice were used to investigate how Atm is required to regenerate the injured airway epithelium following IAV infection. When compared with WT mice, naive Atm-null mice had increased airway resistance and reduced lung compliance that worsened during infection before returning to naïve levels by 56 days postinfection (dpi). Although Atm-null lungs appeared pathologically normal before infection by histology, they developed an abnormal proximal airway epithelium after infection that contained E-cadherin+, Sox2+, and Cyp2f2+ cells lacking secretoglobin family 1 A member 1 (Scgb1a1) protein expression. Patchy and low expression of Scgb1a1 were eventually observed by 56 dpi. Genetic lineage tracing in HKx31-infected mice revealed club cells require Atm to rapidly and efficiently restore Scgb1a1 expression in proximal airways. Since Scgb1a1 is an immunomodulatory protein that protects the lung against a multitude of respiratory challenges, failure to efficiently restore its expression may contribute to the respiratory diseases seen in individuals with ataxia telangiectasia.
Effects of −10° and −30° head-down tilt on cerebral blood velocity, dynamic cerebral autoregulation, and noninvasively estimated intracranial pressure
Authors: Kato Tomokazu , Kurazumi Takuya , Konishi Toru , Takko Chiharu , Ogawa Yojiro , Iwasaki Ken-ichi
Published: February 2022

This appears to be the first study to evaluate steady-state cerebral blood flow (CBF), dynamic cerebral autoregulation, and intracranial pressure (ICP) during −30° head-down tilt (HDT) compared with those during −10° HDT using noninvasive measurements. The results suggest that steady-state CBF and dynamic cerebral autoregulation are preserved despite the higher ICP during short-term −30° HDT compared with −10° HDT.
Is airway damage during physical exercise related to airway dehydration? Inputs from a computational model
Authors: Karamaoun Cyril , Haut Benoît , Blain Grégory , Bernard Alfred , Daussin Frédéric , Dekerle Jeanne , Bougault Valérie , Mauroy Benjamin
Published: February 2022

Using a computational model for heat and water transfers in the bronchi, we identified a threshold in ventilation during exercise above which airway dehydration is thought to occur. When this threshold was exceeded, epithelial damage was found. This threshold might therefore represent the ventilation upper limit during exercise in susceptible individuals. Our results might help to prevent maladaptation to chronic exercise such as exercise-induced bronchoconstriction or asthma.
The Diagnostic Value of Whole Blood lncRNA NR_120420 for Acute Ischemic Stroke
Authors: Tian Chunou , Li Zifu , Li Sisi , Zhang Lei , Dai Dongwei , Huang Qinghai , Zhou Yu , Hong Bo
Published: February 2022

Objective. Current clinical practice based on CT or multimodal images to diagnose ischemic stroke always led to substantial treatment delay. We perform this study to explore possible circulating lncRNA biomarker to help promptly diagnose the disease. Methods. We used microarray to identify the differentially expressed lncRNAs in the peripheral whole blood between AIS patients and controls and verified the results by quantitative polymerase chain reaction (qPCR). Multivariate logistic regressions were performed to determinate the lncRNAs independently associated with AIS occurrence. The ROC curve was used to detect the diagnostic accuracy of candidate lncRNAs in AIS and AIS subtypes, which was classified according to the Oxford Community Stroke Project (OCSP) criteria. Results. The microarray analysis screened out 5686 differentially expressed lncRNAs. Among the nine selected lncRNAs verified by qPCR, NR_120420 (OR 1.29, 95% CI 1.02-1.65,

P
=
0.037

) was found independently associated with AIS after balancing patient baseline characteristics. The receiver operating characteristic (ROC) analysis concerning NR_120420 in total anterior circulation infarction subgroup showed that the area under the curve was 0.86 (95% CI: 0.73-0.99,

P
=
0.003

), and at the optimal cutoff point of 1.93, the sensitivity and specificity reached 85.7% and 84.6%, respectively. Conclusion. Our study indicated that NR_120420 could predict the total anterior circulation infarction with high sensitivity and specificity and could be potentially used as a biomarker for total anterior circulation infarction in AIS patients.
A Deep Learning Method for Android Application Classification Using Semantic Features
Authors: Wang Zhiqiang , Li Gefei , Zhuo Zihan , Ren Xiaorui , Lin Yuheng , Gu Jieming
Published: February 2022

Android has become the most popular mobile intelligent operating system with its open platform, diverse applications, and excellent user experience. However, at the same time, more and more attackers take Android as the primary target. The application store, which is the main download source for users, still does not have a complete security authentication mechanism. Given the above problems, we designed an Android application classification model based on multiple semantic features. Firstly, we use analysis tools to automatically extract the application’s dynamic and static features into the text document and use variance and chi-square tests to optimize the features. Combined with natural language processing (NLP), we transform the feature file into a two-dimensional matrix and use the convolution neural network (CNN) to learn features efficiently. Also, to make the model satisfy more application scenarios, we design a dynamic adjustment method according to user requirements, the number of features, and other indicators. The experimental results demonstrate that the detection accuracy of malware is 99.3921%. We also measure this model’s performance in detecting a malware family and benign application, with the classification accuracy of 99.5614% and 99.9046%, respectively.
In Vitro Quantitative Evaluation of Postprocessing Filter for Metal Artifact Reduction in Cone Beam Computed Tomography Images of Titanium and Zirconium Dioxide Implants
Authors: Costa Andre Luiz Ferreira , Fardim Karolina A. C. , Mantoani Jennifer M. , Ricardo Ana Lucia Franco , Jardini Maria Aparecida N. , Orhan Kaan , de Castro Lopes Sérgio Lúcio Pereira
Published: February 2022

Objective. To evaluate a postprocessing filter of a new imaging‐processing software for analysis of metal artifact reduction. Methods. Eight artificial edentulous mandibles (phantoms), where titanium and zirconium dioxide implants had been installed in four different regions (i.e., incisors, canine, premolars, and molars). CBCT volume was acquired, and then, four types of filters were applied to the images: BAR filter and Multi‐CDT NR filter (e‐Vol DX) and Sharpening Filters 1x and 2x (OnDemand). Artifact was assessed by measuring the standard deviation (SD) of the gray values of filtered and unfiltered images. The comparison between implant material, teeth, and filters was performed by using ANOVA, whereas multiple comparisons were performed by using Bonferroni’s test. The level of significance adopted was 5%. Results. The results showing higher SD values, which suggests a worse image, were obtained with titanium implants compared to zirconium dioxide ones. With regard to the four filters used, it can be seen that the lowest SD values were obtained with BAR and Multi‐CDT NR filters and the highest with Sharpening Filters 1x and 2x, with no statistical difference between them, except regarding the molar region in titanium implants. Conclusion. The highest SD values were seen in zirconium dioxide implants, mainly in the region of anterior teeth. The BAR filter was found to be the most effective as its SD value decreased significantly, indicating that the image quality was improved.
Repeated Yueju, But Not Fluoxetine, Induced Sustained Antidepressant Activity in a Mouse Model of Chronic Learned Helplessness: Involvement of CaMKII Signaling in the Hippocampus
Authors: Zou Zhilu , Huang Jiaru , Yang Qingqing , Zhang Yuxuan , Xu Bo , Wang Ping , Chen Gang
Published: February 2022

Objective. Depression is characterized with long disease length, whereas one major disadvantage of current mainstream treatment of depression is a high rate of relapse and recurrence. A sustained antidepressant activity is proposed to facilitate the prevention of relapse/recurrence. Here we compared the long-term antidepressant effect of Yueju, a traditional Chinese medicine formula, and a conventional antidepressant, fluoxetine, as well as revealing the underlying mechanism of long-term antidepressant effect of Yueju. Methods. Clinical long-term depression condition was modelled by using chronic learned helplessness (cLH) protocol in ICR strain mice. The short-term and long-term antidepressant effects of drugs were assessed with learned helplessness (LH), tail suspension test (TST), forced swim test (FST), and novelty-suppressed feeding (NSF) test. The expression of PKA, CaMKII signaling, and NR1, the NMDA receptor subunit, in hippocampus was determined. A CaMKII inhibitor (KN-62) was used to assess the role of CaMKII signaling in antidepressant effects of Yueju or fluoxetine. Results. In the mice exposed to chronic learned helplessness (cLH) procedure, administration of Yueju or fluoxetine for 3 weeks elicited comparable antidepressant effects, indicated by learned helplessness test, as well as TST and NSF. However, 5 days after termination of the 3-week-long drug administration, only mice previously treated with Yueju still showed the alleviation of depressive-like behaviors. At this time, the downregulation of PKA and p-CaMKII/CaMKII and upregulation of NMDA receptor subunit NR1 in the hippocampus were normalized in animals previously treated with Yueju. In contrast, none of the expressions of these proteins were changed in mice previously treated with fluoxetine. Interestingly, an administration of KN-62 blunted the antidepressant effect of Yueju. Conclusion. These findings showed the sustained antidepressant efficacy of chronic treatment with routine dose of Yueju and the CaMKII signaling activation may play a critical role in the sustained antidepressant response.
The Application of Molecular Techniques for Assessment of SOX2 and miR126 Expression as Prognostic Markers in Esophageal Carcinoma
Authors: Gharib Amal F. , Elsawy Wael H. , Alrehaili Amani A. , Amin Hanan S. , Alhuthali Hayaa M. , Bakhuraysah Maha M. , El Askary Ahmad
Published: February 2022

Objective. To study the problem in esophageal cancer, the function of SOX2 and miR-126 has not been completely explored. The objective of this study was to find out how SOX2 and miR-126 act in esophageal cancer and their relation to the clinical and prognostic features. Methods. The expression of SOX2 and miR-126 was properly assessed in the carcinoma of the esophagus, and the nearby healthy tissues surgically excised from 35 included patients. Results. SOX2 was elevated in esophageal cancer relative to normal tissues contrary to the miR-126 levels. This inverse relationship was linked to adverse clinical features. Background. SOX2 has been involved as an oncogene in various types of malignant tumors; microRNA-126 (miR-126) is extensively expressed in vascular endothelial cells, which control angiogenesis. Furthermore, many published reports reasonably concluded that based on the prime characteristic of malignant cells, miR-126 may act appropriately as a promotor or a suppressor for the malignant growth. Conclusion. In esophageal cancer, SOX2 works as an oncogene, whereas miR-126 acts as a tumor suppressor gene. SOX2 overexpression and miR-126 downregulation were shown to be linked to a poor prognosis.
Athlete Gait Feature Recognition Method Based on Multisource Sensing Information
Authors: Li Xu , Xue Chunlei , Gu Xiaobo
Published: February 2022

Aiming at the problem of low accuracy of two-dimensional gait recognition at present, a gait feature recognition method based on multisource sensing information is proposed. The multisource sensing information is combined to collect the athlete’s gait characteristics, collect the single frame gait image sequence of the human lower limbs during the movement, and extract the human body’s three-dimensional feature data during human walking by using the body structure and multisource sensing information, so as to realize the separation of the athlete’s gait image background. Finally, it is confirmed by experiments that the recognition rate of athlete gait feature recognition method based on multisource sensing information is significantly improved.
A Transformation of Oral English Teaching Method in the Network Environment
Authors: Gong Yanwei
Published: February 2022

In order to effectually improve the application effect of the existing oral English teaching methods, this paper studies the conversion of effective oral English teaching methods under the network environment, aiming at the application problems, such as the flexibility of the current education platform. We build an effective oral English teaching platform which is comprised of oral English perception processing module, oral English pronunciation acquisition program module, oral English pronunciation preprocessing module, and oral English pronunciation error detection modeling module. We establish the information technology teaching objectives of the effective oral English teaching model on this basis. This research work is focused on the study of the output driven input-facilitated college oral English teaching model in oral English classroom. It is performed to realize the transformation of effective oral English teaching methods under the network environment. The experimental results show that the transformation effect of the effective teaching method of oral English, under the designed network environment, is better as compared to the existing work. The error detection rate in the proposed methodology reaches up to 98.6%, which is significantly higher than the results obtained by researchers in their existing work. The proposed method has obvious application advantages.
Farnesoid X Receptor Deficiency Induces Hepatic Lipid and Glucose Metabolism Disorder via Regulation of Pyruvate Dehydrogenase Kinase 4
Authors: Deng Wenyi , Fan Wenjing , Tang Tingting , Wan Hengquan , Zhao Simin , Tan Yao , Oware Kwabena Agyare , Tan Jieqiong , Li Jiequn , Qu Shunlin
Published: February 2022

Farnesoid X receptors (FXR) are bile acid receptors that play roles in lipid, glucose, and energy homeostasis. Synthetic FXR-specific agonists have been developed for treating nonalcoholic fatty liver disease (NAFLD) patients. However, the detailed mechanism remains unclear. To investigate the effects of FXR on NAFLD and the possible mechanism, FXR-null mice were fed either a normal or a high-fat diet. The FXR-null mice developed hepatomegaly, steatosis, accumulation of lipid droplets in liver cells, glucose metabolism disorder, and elevated serum lipid levels. Transcriptomic results showed increased expression of key lipid synthesis and glucose metabolism-related proteins. We focused on pyruvate dehydrogenase kinase 4 (PDK4), a key enzyme involved in the regulation of glucose and fatty acid (FA) metabolism and homeostasis. Subsequently, we confirmed an increase in PDK4 expression in FXR knockout cells. Moreover, inhibition of PDK4 expression alleviated lipid accumulation in hepatocytes caused by FXR deficiency in vivo and in vitro. Our results identify FXR as a nuclear transcription factor that regulates glucose and lipid metabolism balance through PDK4, providing further insights into the mechanism of FXR agonists in the treatment of metabolic diseases.
[Retracted] HHLA2 Used as a Potential Prognostic and Immunological Biomarker and Correlated with Tumor Microenvironment in Pan‐Cancer
Authors: Yang Zeng , Xu Diao , Ye Xiao , Lin Xuehua , Zhang Min , Su Yan , Xie Qun , Ni Wenjun
Published: February 2022

Background. The role of HERV–H LTR‐associating 2 (HHLA2) in cancer remains still unclear. This study analyzed the correlation between the prognosis and immune infiltrate function of HHLA2 in pan‐cancers. Methods. HHLA2 expression in pan‐cancers was analyzed using the databases of TCGA, GTEx, TIMER, GEPIA, UALCAN, and GSEA databases. Multiple bioinformatic methods were used to investigate the correlation of HHLA2 expression with survival, pathological stage, tumor mutation burden (TMB), microsatellite instability (MSI), tumor microenvironment (TME), immune cell infiltration, and immune checkpoint gene (ICG), and gene functional enrichment was performed by Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA). Results. HHLA2 was aberrantly expressed and was strongly correlated with positive or negative prognosis in multiple human cancers, which revealed that HHLA2 might play a vital role during cancer formation and development. Kaplan–Meier (KM) curves across cancers revealed that HHLA2 expression was correlated with overall survival (OS) in eight cancers, disease‐specific survival (DSS) in seven cancers, disease‐free interval (DFI) in four cancers, and progression‐free interval (PFI) in nine cancers. Furthermore, HHLA2 expression was positively correlated with TMB in 6 cancer types and negatively associated with TMB in 7 cancer types, respectively. The former included ESCA, HNSC, KIRP, PAAD, PRAD, and PCPG; the latter contained COAD, LGG, LUAD, LUSC, THYM, THCA, and UCEC. Additionally, we found HHLA2 expression was negatively related to MSI in ACC, COAD, PAAD, and UCEC. More importantly, HHLA2 expression was remarkably correlated with the degree of tumor‐infiltrating immune in many cancers, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells and strongly associated with immune checkpoint genes in 13 tumor types. Furthermore, KEGG pathway analyses indicated that HHLA2 could potentially impact cancer etiology or pathogenesis by functioning in amino sugar and nucleotide sugar metabolism, cytosolic DNA sensing pathway, and peroxisome pathways. Meanwhile, GSVA analysis results all indicate that HHLA2 was correlated with TSC/mTOR, RTK, RAS/MAPK, PI3K/AKT, EMT, DNA Damage Response, Cell Cycle, and Apoptosis pathways in various cancers. Conclusion. HHLA2 can function as a prognostic biomarker and correlate with tumor immunity in human pan‐cancer due to its important role in tumorigenesis and immune infiltration, which provides new insight into developing new targeted treatments in cancers.
Efficacy of Rubus coreanus Miq. and Astragalus membranaceus Bunge Extract for Postmenopausal Syndrome: A Randomised, Double-Blind, Placebo Comparative Clinical Trial
Authors: Park Jeong-Su , Sung Hyun Kyung , Kim Seul-Ki , Lee Hak Sung , Shin Seon Mi
Published: February 2022

Objectives. The most effective way to improve menopausal symptoms is to supplement deficient oestrogen; however, long-term administration of synthetic oestrogen increases the risk for breast and uterine cancers. Here, we report results from a clinical trial of Rubus coreanus Miq. and Astragalus membranaceus Bunge as agents for improving the menopause syndrome. Methods. This study was a single-centre, double-blinded, parallel-group, placebo-controlled study. The efficacy of an extract of R. coreanus Miq. and A. membranaceus Bunge was investigated. Participants were females with postmenopausal syndrome in the menopausal or menopausal transition period. The primary endpoint of validation was improvement in the Kupperman index (KI) score of women. The secondary end point was change in the Menopause Rating Scale (MRS) and lipid profile. The participants were randomly allocated at a 1 : 1 ratio into R. coreanus Miq. and A. membranaceus Bunge extract (RCAM) or placebo groups and were administered 2000 mg of the extract or placebo, respectively, daily for 12 weeks. Outcomes were measured at visits 2 (day 0) and 5 (week 12). Results. The RCAM group demonstrated decreased KI score and MRS compared with the placebo group after 12 weeks. In the safety evaluation, laboratory tests and vital signs demonstrated no clinically significant changes in subjects, and there was no difference in adverse reactions between the groups. The R. coreanus Miq. and A. membranaceus Bunge extract was effective in reducing postmenopausal symptoms in women. Moreover, the extract was found to be safe. Conclusions. For females with menopausal symptoms in the menopausal transitional and postmenopausal periods, ingestion of the R. coreanus Miq. and A. membranaceus Bunge extract for 12 weeks was effective, as demonstrated by a decrease in KI score and MRS relative to that in the placebo group, and significantly improved the menopausal symptoms.
Quantitative Proteomics Analysis Expands the Roles of Lysine β-Hydroxybutyrylation Pathway in Response to Environmental β-Hydroxybutyrate
Authors: Hou Wanting , Liu Guobin , Ren Xuelian , Liu Xianming , He Lei , Huang He
Published: February 2022

Lysine β-hydroxybutyrylation (Kbhb) is a newly identified protein posttranslational modification (PTM) derived from β-hydroxybutyrate (BHB), a product of ketone body metabolism in liver. BHB could serve as an energy source and play a role in the suppression of oxidative stress. The plasma concentration of BHB could increase up to 20 mM during starvation and in pathological conditions. Despite the progress, how the cells derived from extrahepatic tissues respond to elevated environmental BHB remains largely unknown. Given that BHB can significantly drive Kbhb, we characterized the BHB-induced lysine β-hydroxybutyrylome and acetylome by quantitative proteomics. A total of 840 unique Kbhb sites on 429 proteins were identified, with 42 sites on 39 proteins increased by more than 50% in response to BHB. The results showed that the upregulated Kbhb induced by BHB was involved in aminoacyl-tRNA biosynthesis, 2-oxocarboxylic acid metabolism, citrate cycle, glycolysis/gluconeogenesis, and pyruvate metabolism pathways. Moreover, some BHB-induced Kbhb substrates were significantly involved in diseases such as cancer. Taken together, we investigate the dynamics of lysine β-hydroxybutyrylome and acetylome induced by environmental BHB, which reveals the roles of Kbhb in regulating various biological processes and expands the biological functions of BHB.
Reinforcement Learning for Distributed Energy Efficiency Optimization in Underwater Acoustic Communication Networks
Authors: Yang Liejun , Wang Hui , Fan Yexian , Luo Fang , Feng Wei
Published: February 2022

To solve the problems of poor quality of service and low energy efficiency of nodes in underwater multinode communication networks, a distributed power allocation algorithm based on reinforcement learning is proposed. The transmitter with reinforcement learning capability can select the power level autonomously to achieve the goal of getting higher user experience quality with lower power consumption. Firstly, we propose a distributed power optimization model based on the Markov decision process. Secondly, we further give a reward function suitable for multiobjective optimization. Finally, we present a distributed power allocation algorithm based on Q-learning and use it as an adaptive mechanism to enable each transmitter in the network to adjust the transmit power according to its own environment. The simulation results show that the proposed algorithm not only increases the total channel capacity of the system but also improves the energy efficiency of each transmitter.
Synthesis, Carbonic Anhydrase II/IX/XII Inhibition, DFT, and Molecular Docking Studies of Hydrazide‐Sulfonamide Hybrids of 4‐Methylsalicyl‐ and Acyl‐Substituted Hydrazide
Authors: Khushal Adil , Mumtaz Amara , Shadoul Wamda Ahmed , Zaidi Syeda Huda Mehdi , Rafique Hummera , Munir Abida , Maalik Aneela , Shah Syed Jawad Ali , Baig Ayesha , Khawaja Wajiha , al-Rashida Mariya , Hashmi Muhammad Ali , Iqbal Jamshed
Published: February 2022

Carbonic anhydrases (CAs and EC 4.2.1.1) are the Zn2+ containing enzymes which catalyze the reversible hydration of CO2 to carbonate and proton. If they are not functioning properly, it would lead towards many diseases including tumor. Synthesis of hydrazide‐sulfonamide hybrids (19-36) was carried out by the reaction of aryl (10-11) and acyl (12-13) hydrazides with substituted sulfonyl chloride (14-18). Final product formation was confirmed by FT‐IR, NMR, and EI‐MS. Density functional theory (DFT) calculations were performed on all the synthesized compounds to get the ground‐state geometries and compute NMR properties. NMR computations were in excellent agreement with the experimental NMR data. All the synthesized hydrazide‐sulfonamide hybrids were in vitro evaluated against CA II, CA IX, and CA XII isozymes for their carbonic anhydrase inhibition activities. Among the entire series, only compounds 22, 32, and 36 were highly selective inhibitors of hCA IX and did not inhibit hCA XII. To investigate the binding affinity of these compounds, molecular docking studies of compounds 32 and 36 were carried out against both hCA IX and hCA XII. By using BioSolveIT’s SeeSAR software, further studies to provide visual clues to binding affinity indicate that the structural elements that are responsible for this were also studied. The binding of these compounds with hCA IX was highly favorable (as expected) and in agreement with the experimental data.
Intelligent Community Management System Based on Big Data Technology
Authors: Liu Yang
Published: February 2022

Community safety has become an important part of social public safety. The construction of a safe community focuses on the accumulation of community safety capabilities. This paper discusses the application of big data technology in community safety construction and the improvement of community safety promotion capabilities. We analyzed the sources and collection methods of community data, classified multisource heterogeneous community data, and constructed seven types of community data. We designed the conceptual structure and storage structure of the community database. On the basis of the construction of the community database, the architecture design of the big data platform for community security was launched. From the perspective of different user types, the functional requirements of the big data platform were analyzed. Combined with demand analysis, the overall architecture design of the community big data platform was carried out. On the basis of the overall architecture, the application architecture and technical architecture were designed in more detail, and the key technologies of the community big data platform were analyzed. Finally, it analyzes how to use the community big data platform to predict public security risks by constructing a CART regression tree model.
Main Applications and Recent Research Progresses of Additive Manufacturing in Dentistry
Authors: Huang Gan , Wu Libo , Hu Jie , Zhou Xiongming , He Fei , Wan Li , Pan Shu-Ting
Published: February 2022

In recent ten years, with the fast development of digital and engineering manufacturing technology, additive manufacturing has already been more and more widely used in the field of dentistry, from the first personalized surgical guides to the latest personalized restoration crowns and root implants. In particular, the bioprinting of teeth and tissue is of great potential to realize organ regeneration and finally improve the life quality. In this review paper, we firstly presented the workflow of additive manufacturing technology. Then, we summarized the main applications and recent research progresses of additive manufacturing in dentistry. Lastly, we sketched out some challenges and future directions of additive manufacturing technology in dentistry.
Black Truffle Extract Exerts Antidiabetic Effects through Inhibition of Inflammation and Lipid Metabolism Regulation
Authors: Wu Ziyuan , Jayachandran Muthukumaran , Cheang Wai San , Xu Baojun
Published: February 2022

Black truffle, a culinary and medical fungus, is highly valued worldwide for its nutritional and therapeutic importance. To enhance the existing knowledge about the beneficial properties, this study investigates the antioxidant, antihyperlipidemic, and anti-inflammatory effects of black truffle extract in in vitro biochemical assays and animal study. Briefly, black truffle extract was administered orally to treat streptozotocin- (STZ-) induced diabetic Wistar rats for 45 days. At the end of the experimental duration, rats were sacrificed to perform biochemical and gene expression analyses related to lipid regulatory and inflammatory pathways. Our results indicated that total cholesterol, triglycerides, free fatty acids, phospholipids, and low-density lipoprotein in different tissues and circulation were significantly increased in diabetic rats. Furthermore, the β-hydroxy β-methylglutaryl-CoA enzyme was also significantly increased; lipoprotein lipase and lecithin–cholesterol acyltransferase enzymes were significantly decreased in diabetic rats. However, the above conditions were reversed upon black truffle extract feeding. Furthermore, black truffle extract was also found to downregulate the expression of proinflammatory cytokines (tumor necrosis factor-α and interleukin-6) and lipid regulatory genes (serum regulatory element-binding protein-1 and fatty acid synthase). The truffle extract-treated effects were comparable to glibenclamide and medication commonly used to treat diabetes mellitus. Overall, our results suggested that black truffle possesses strong antihyperlipidemic and anti-inflammatory effects on diabetic rats. These findings will enhance the current knowledge about the therapeutic importance of black truffles. They might be exploited as a possible food supplement or even as a natural source of pharmaceutical agents for diabetes prevention and treatment.
Oxycodone Alleviates Endometrial Injury via the TLR4/NF-κB Pathway
Authors: Zhu Aibing , Yang Jianping
Published: February 2022

Endometrial injury is a common female disease. This study was designed to illustrate the effects of oxycodone on mifepristone-induced human endometrial stromal cells (hEndoSCs) injury and delineate the underlying molecular mechanism. hEndoSCs were stimulated with mifepristone to generate the endometrial injury in vitro model. hEndoSCs viability, cytotoxicity, and apoptosis were measured by methyl thiazolyl tetrazolium (MTT) assay, lactate dehydrogenase assay (LDH), and flow cytometry (FCM) analysis, respectively. Meanwhile, quantitative reverse transcription polymerase chain reaction (RT-qPCR) and Western blot assay were conducted to evaluate gene and protein expressions. The secretions of inflammatory cytokines (TNF-α, IL-1β, and IL-6) were measured using enzyme-linked immunosorbent assay (ELISA). The data revealed that mifepristone exposure memorably inhibited hEndoSCs viability and promoted cell apoptosis and inflammatory cytokines secretion, and oxycodone had no cytotoxicity on hEndoSCs. Oxycodone increased hEndoSCs growth, blocked cell apoptosis, enhanced Bcl-2 expression, reduced Bax levels, and decreased the secretion of inflammatory cytokines in mifepristone-induced hEndoSCs, exhibiting the protective effects in endometrial injury. In addition, the TLR4/NF-κB pathway-related protein levels (TLR4 and p-p65) in mifepristone-treated hEndoSCs were enhanced, while these enhancements were inhibited by oxycodone treatment. In conclusion, oxycodone exhibited the protective role in mifepristone-triggered endometrial injury via inhibiting the TLR4/NF-κB signal pathway.
Evaluation and Analysis of the Impact of Airport Delays
Authors: Zhou Fen , Jiang Guosong , Lu Zhengwu , Wang Qingdong
Published: February 2022

To characterize the real dynamic process of delay propagation between airports and to understand the mechanism of delay propagation from a global perspective, this paper establishes a network of delay propagation relationships between airports based on causal analysis and conducts an example analysis. First, the flight operating status data processing is used to obtain the arrival delay time series of each airport. Then, the delay propagation relationship between airports is analyzed in pairs through the causal analysis method to obtain the delay propagation relationship network between all airports. Finally, the complex network theory and related indicators are used. The network is analyzed, and these analysis results can provide theoretical support for the formulation of delay propagation mitigation measures.
[Retracted] Enhanced Watershed Segmentation Algorithm‐Based Modified ResNet50 Model for Brain Tumor Detection
Authors: Sharma Arpit Kumar , Nandal Amita , Dhaka Arvind , Koundal Deepika , Bogatinoska Dijana Capeska , Alyami Hashem
Published: February 2022

This work delivers a novel technique to detect brain tumor with the help of enhanced watershed modeling integrated with a modified ResNet50 architecture. It also involves stochastic approaches to help in developing enhanced watershed modeling. Cancer diseases, primarily the brain tumor, have been exponentially raised which has alarmed researchers from academia and industry. Nowadays, researchers need to attain a more effective, accurate, and trustworthy brain tumor tissue detection and classification approach. Different from traditional machine learning methods that are just targeting to enhance classification efficiency, this work highlights the process to extract several deep features to diagnose brain tumor effectively. This paper explains the modeling of a novel technique by integrating the modified ResNet50 with the Enhanced Watershed Segmentation (EWS) algorithm for brain tumor classification and deep feature extraction. The proposed model uses the ResNet50 model with a modified layer architecture including five convolutional layers and three fully connected layers. The proposed method can retain the optimal computational efficiency with high‐dimensional deep features. This work obtains a comprised feature set by retrieving the diverse deep features from the ResNet50 deep learning model and feeds them as input to the classifier. The good performing capability of the proposed model is achieved by using hybrid features of ResNet50. The brain tumor tissue images were extracted by the suggested hybrid deep feature‐based modified ResNet50 model and the EWS‐based modified ResNet50 model with a high classification accuracy of 92% and 90%, respectively.