bluuebunny/crossref_metadata_2025 huggingface dataset:
Tolerant Testers of Image Properties
Authors: Berman Piotr , Murzabulatov Meiram , Raskhodnikova Sofya
Published: May 2022

We initiate a systematic study of tolerant testers of image properties or, equivalently, algorithms that approximate the distance from a given image to the desired property. Image processing is a particularly compelling area of applications for sublinear-time algorithms and, specifically, property testing. However, for testing algorithms to reach their full potential in image processing, they have to be tolerant, which allows them to be resilient to noise.

We design efficient approximation algorithms for the following fundamental questions: What fraction of pixels have to be changed in an image so it becomes a half-plane? A representation of a convex object? A representation of a connected object? More precisely, our algorithms approximate the distance to three basic properties (being a half-plane, convexity, and connectedness) within a small additive error ε, after reading
poly
(1/ε) pixels, independent of the image size. We also design an efficient agnostic proper PAC learner of convex sets (continuous and discrete) in two dimensions under the uniform distribution.

Our algorithms require very simple access to the input: uniform random samples for the half-plane property and convexity, and samples from uniformly random blocks for connectedness. However, the analysis of the algorithms, especially for convexity, requires many geometric and combinatorial insights. For example, in the analysis of the algorithm for convexity, we define a set of reference polygons
P
ε
such that (1) every convex image has a nearby polygon in
P
ε
and (2) one can use dynamic programming to quickly compute the smallest empirical distance to a polygon in
P
ε
.
A Framework for Neural Network Architecture and Compile Co-optimization
Authors: Chen Weiwei , Wang Ying , Xu Ying , Gao Chengsi , Liu Cheng , Zhang Lei
Published: May 2022

The efficiency of deep neural network (DNN) solutions on real hardware devices are mainly decided by the DNN architecture and the compiler-level scheduling strategy on the hardware. When we try to fully exploit the underlying hardware and obtain the optimal tradeoff between DNN accuracy and runtime performance, we discovered that the two optimization goals of DNN architecture and scheduling policy are intimately related to each other. However, current hardware-aware Neural Architecture Search (NAS) methods primarily focus on the DNN architecture search process, ignoring the effects of various compiler-level scheduling strategies (e.g., graph-level optimization, loop transformations, parallelization, etc.) on network candidates being evaluated in the search process. As a result, they may overlook the true-optimal DNN implementations on hardware, which can only be discovered by trying-out different combinations of scheduling strategies and DNN architectures. This work proposes a NAS framework (CHaNAS) that searches for not only the network architecture but also the dedicated compiler-level scheduling policy, as the optimal co-design solution on the target hardware. We propose to use a block-based pre-scheduling methodology to reduce the co-design search space and enable the automatic generation of the optimal co-design, including the network architecture and the tensor programs that practice the scheduling policy. Further, we introduce a new search objective function based on the generalization gap to prevent the selection of architectures that are prone to overfitting. We evaluate CHaNAS on Imagenet on different hardware back-ends against the state-of-the-art hardware-aware search method based on the MobileNet-v3 search space. Experimental results show that the co-design solutions obtained by ChaNAS show up to 1.6×, 1.9×, and 1.7×, 24 performance boost on NVIDIA P100 GPU, Intel Xeon 8163 CPU, and Samsung Note 10 Mobile, respectively, over the baselines of the same-level accuracy.
Temperamental and Theoretical Contributions to Clinical Psychology
Authors: Kagan Jerome
Published: May 2022

This review considers two themes. The first section describes the influence of two temperamental biases detectable in infants that render children vulnerable to maladaptive behavior if the rearing environment invites such responses. Infants who display high levels of limb activity and crying in response to unexpected events are likely to be shy and fearful as children and are at risk for an anxiety disorder. Infants who display little limb movement and crying are susceptible to assuming risks and vulnerable to asocial behavior if the rearing environment invites these actions. The second section criticizes three common research practices: failure to examine patterns of measures for predictors and outcomes, an indifference to the power of the setting on the evidence recorded, and the distortions that semantic terms in questionnaires impose on replies.
Allostasis, Action, and Affect in Depression: Insights from the Theory of Constructed Emotion
Authors: Shaffer Clare , Westlin Christiana , Quigley Karen S. , Whitfield-Gabrieli Susan , Barrett Lisa Feldman
Published: May 2022

The theory of constructed emotion is a systems neuroscience approach to understanding the nature of emotion. It is also a general theoretical framework to guide hypothesis generation for how actions and experiences are constructed as the brain continually anticipates metabolic needs and attempts to meet those needs before they arise (termed allostasis). In this review, we introduce this framework and hypothesize that allostatic dysregulation is a trans-disorder vulnerability for mental and physical illness. We then review published findings consistent with the hypothesis that several symptoms in major depressive disorder (MDD), such as fatigue, distress, context insensitivity, reward insensitivity, and motor retardation, are associated with persistent problems in energy regulation. Our approach transforms the current understanding of MDD as resulting from enhanced emotional reactivity combined with reduced cognitive control and, in doing so, offers novel hypotheses regarding the development, progression, treatment, and prevention of MDD.
Enough Potential Repudiation: Economic and Legal Aspects of Sovereign Debt in the Pandemic Era
Authors: Gelpern Anna , Panizza Ugo
Published: May 2022

This article reviews recent economic and legal literature on sovereign debt in light of the COVID-19 shock. Most of the core theoretical contributions across the two disciplines hinge on immunity, and the sovereign borrower's consequent inability to commit to repay foreign creditors, as the distinguishing attribute of sovereignty. We highlight a persistent gap between sovereign debt theories grounded in immunity and empirical evidence that the governments of low- and middle-income countries borrow far more than theory would predict. On the other hand, the governments of advanced economies, generally viewed as outside the scope of this literature before the euro area debt crisis, have shown themselves to be far more commitment challenged than previously supposed. We conclude that the traditional split between a literature concerned with developing economy sovereigns that repudiate debt and one concerned with advanced economies that do not is no longer appropriate (if ever it was). We argue that shifting some attention away from immunity to a different attribute of sovereignty—authority—could help bridge the gap between the two literatures.
Ethical Guidance in Human Paleogenomics: New and Ongoing Perspectives
Authors: Fleskes Raquel E. , Bader Alyssa C. , Tsosie Krystal S. , Wagner Jennifer K. , Claw Katrina G. , Garrison Nanibaa’ A.
Published: May 2022

Over the past two decades, the study of ancient genomes from Ancestral humans, or human paleogenomic research, has expanded rapidly in both scale and scope. Ethical discourse has subsequently emerged to address issues of social responsibility and scientific robusticity in conducting research. Here, we highlight and contextualize the primary sources of professional ethical guidance aimed at paleogenomic researchers. We describe the tension among existing guidelines, while addressing core issues such as consent, destructive research methods, and data access and management. Currently, there is a dissonance between guidelines that focus on scientific outcomes and those that hold scientists accountable to stakeholder communities,such as descendants. Thus, we provide additional tools to navigate the complexities of ancient DNA research while centering engagement with stakeholder communities in the scientific process.
A Dosing-Spoon-Based Electrochemical Sensor for Fast Assessment of Andrographis paniculata Extracts
Authors: Sangsawang Rachanon , Thavarungku Panote , Kanatharana Proespichaya , Jeerapan Itthipon
Published: May 2022

Directly analyzing an herbal drug and its contamination is crucial to avoid severe problems due to uncertain dosages and unwanted contaminants. This article describes the first example of a dosing-spoon-based sensor for point-of-use detection of an herbal extract and its contamination.Andrographis paniculatais an herbal drug conventionally used for the therapy of many symptoms and infectious diseases, including COVID-19. The developed device consists of a sensitive electrochemical sensor, enabling the detection ofA. paniculataextract. The lab-on-a-spoon squarewave voltammetric system provides the detection result with favorable sensitivity and simplicity in a short time (less than 15 s). The calibration curve of the modeled herbal extract covers a range of 0.030–7.350 mg ml–1with a limit of detection of 20μg ml–1. The device and data analysis were applied for determining real samples ofA. paniculataextracts. The developed device is sensitive for the screening of processed products fromA. paniculata. Moreover, this single dosing-spoon-based sensor can also simultaneously screen the contamination of heavy metals (i.e., cadmium and lead). We envision that this lab-on-a-spoon demonstration would expand the scope of portable pharmaceutical and biochemical sensors, offering promising convenient screening tools for industrial and household applications.
Cellular mechanism underlying the facilitation of contractile response induced by IL-25 in mouse tracheal smooth muscle
Authors: Huang Ze-Xin , Qiu Zhuo-Er , Chen Lei , Hou Xiao-Chun , Zhu Yun-Xin , Zhou Wen-Liang , Zhang Yi-Lin
Published: May 2022

Asthma is a common heterogeneous respiratory disease characterized by airway inflammation and airway hyperresponsiveness (AHR) which is associated with abnormality in smooth muscle contractility. The epithelial cell-derived cytokine IL-25 is implicated in type 2 immune pathology including asthma, whereas the underlying mechanisms have not been fully elucidated. This study aims to investigate the effects of IL-25 on mouse tracheal smooth muscle contractility and elucidate the cellular mechanisms. Incubation with IL-25 augmented the contraction of mouse tracheal smooth muscles, which could be suppressed by the L-type voltage-dependent Ca2+ channel (L-VDCC) blocker nifedipine. Furthermore, IL-25 enhanced the cytosolic Ca2+ signals and triggered the upregulation of α1C L-VDCC (CaV1.2) in primary cultured mouse tracheal smooth muscle cells. Knocking down IL-17RA/IL-17RB receptors or inhibiting the transforming growth factor-β-activated kinase 1 (TAK1)-tumor progression locus 2 (TPL2)-MAPK kinase 1/2 (MEK1/2)-ERK1/2-activating protein-1 (AP-1) signaling pathways suppressed the IL-25-elicited upregulation of CaV1.2 and hyperreactivity in tracheal smooth muscles. Moreover, inhibition of TPL2, ERK1/2 or L-VDCC alleviated the AHR symptom induced by IL-25 in a murine model. This study revealed that IL-25 potentiated the contraction of tracheal smooth muscle and evoked AHR via activation of TPL2-ERK1/2-CaV1.2 signaling, providing novel targets for the treatment of asthma with a high-IL-25 phenotype.
Transient receptor potential cation channel 6 deficiency leads to increased body weight and metabolic dysfunction
Authors: Wang Zhen , do Carmo Jussara M. , da Silva Alexandre A. , Fu Yiling , Jaynes Lance T. , Sears Jaylan , Li Xuan , J. Mouton Alan , Omoto Ana Carolina M. , Xu Brittney P. , Hall John E.
Published: May 2022

Transient receptor potential cation channel 6 (TRPC6), a member of the TRPC family, is expressed in the hypothalamus and modulates cell Ca2+ influx. However, the role of TRPC6 in controlling metabolic and cardiovascular functions under normal conditions has not been previously determined. Thus the impacts of TRPC6 deletion on energy balance, metabolic, and cardiovascular regulation as well as the anorexic responses to leptin and melanocortin 3/4 receptor (MC3/4R) activation were investigated in this study. Extensive cardiometabolic phenotyping was conducted in male and female TRPC6 knockout (KO) and control mice from 6 to 24 wk of age to assess mechanisms by which TRPC6 influences regulation of energy balance and blood pressure (BP). We found that TRPC6 KO mice are heavier with greater adiposity, are hyperphagic, and have reduced energy expenditure, impaired glucose tolerance, hyperinsulinemia, and increased liver fat compared with controls. TRPC6 KO mice also have smaller brains, reduced proopiomelanocortin mRNA levels in the hypothalamus, and impaired anorexic response to leptin but not to MC3/4R activation. BP and heart rate, assessed by telemetry, were similar in TRPC6 KO and control mice, and BP responses to air-jet stress were attenuated in TRPC6 KO mice despite increased body weight and metabolic disorders that normally raise BP and increase BP responses to stress. Our results provide evidence for a novel and important role of TRPC6 in controlling energy balance, adiposity, and glucose homeostasis, which suggests that normal TRPC6 function may be necessary to link weight gain and hyperleptinemia with BP responses to acute stress.
Mining and Prediction of Large Sport Tournament Data Based on Bayesian Network Models for Online Data
Authors: Wang Junjian
Published: May 2022

In the modern society, competitive sports have an essential place in the world. Sports can reflect not only the comprehensive strength of a country to some extent but also the cohesion of a nation. Therefore, as China’s overall strength and international influence continue to rise, sports are being given more and more importance. At the same time, research and exploration on the prediction of match results have also become a hot topic. In the large sport tournaments, there are many factors that influence the outcome of a match. In actual matches, the outcome is not only determined by the strength of the participants, but also by a number of unexpected factors. The randomness brought about by these unexpected factors makes it difficult to predict the outcome of a sporting event. In recent years, many researchers have sought to enhance the understanding of complex objects with the help of prediction of sporting outcomes. One of the more traditional methods of prediction is the probabilistic statistical method. However, the traditional prediction methods have low accuracy and do not provide satisfactory stability in the prediction results. In fact, since most sporting matches are played against each other, the ability values of the players often play a key role in the match. They can determine the winner of a match, but unexpected factors such as player play, playing time, and injury situations can also have an impact on the strength of a playing team, so these factors should not be ignored. This study establishes a reasonable causal relationship between the offensive and defensive situations in the game and the players’ ability values and builds a complex Bayesian network model. A match prediction model is then built using the latent variables present during the match so that the various ability values of the match teams can be assessed.
Research on Data Fusion of Photoelectric Measuring Instrument Based on UKF Algorithm
Authors: Yikang Tang
Published: May 2022

The UKF algorithm-based data fusion technique was researched in this work in order to tackle the issues of conventional data fusion methods such as lengthy fusion processes, high recall rates of findings, and big errors. First, the photoelectric measuring principle is examined in this procedure. On the basis of UKF filtering operation on the data sample set, the fusion processing of photoelectric measurement instrument is completed through the steps of data pretreatment, vertical and horizontal fusion, and fusion quality optimization. The experimental results show that the fusion process time of this method is between 0.27 min and 0.40 min, the recall rate of the fusion result is always lower than 6%, and the fusion deviation is small, indicating that the design expectation is achieved.
An Algebraic Approach to Modular Inequalities Based on Interval-Valued Fuzzy Hypersoft Sets via Hypersoft Set-Inclusions
Authors: Rahman Atiqe Ur , Saeed Muhammad , Khan Khuram Ali , Nosheen Ammara , Mabela Rostin Matendo
Published: May 2022

Interval-valued fuzzy hypersoft set is an emerging field of study which is projected to address the limitations of interval-valued fuzzy soft set for the entitlement of multiargument approximate function. This kind of function maps the subparametric tuples to power set of universe. It emphasizes on the partitioning of attributes into their respective subattribute values in the form of disjoint sets. These features make it a completely new mathematical tool for solving problems dealing with uncertainties. In this study, after characterization of essential properties, operations, and set-inclusions (

L

-inclusion and

J

-inclusion) of interval-valued fuzzy hypersoft set, some of its modular inequalities are discussed via set-inclusions. It is proved that all set-inclusion-based properties and inequalities are preserved when ordinary approximate function of interval-valued fuzzy soft set is replaced with multiargument approximate function of interval-valued fuzzy hypersoft set.
A Novel Literary Translation Text Classification Method Based on Distributed Incremental Sequence Data Mining Algorithm
Authors: Sun Ji
Published: May 2022

With the rapid development of electronic information technology and Internet technology, people's ability to generate and collect data is also increasing. With the rapid development of international exchanges, the number of literary translation texts has also increased dramatically. The information contained in the huge data of literary translation texts is huge, but these data are disorganized at this stage. Therefore, the classification of literary translation texts has become the key to efficient management of translated text information. Literary translation text classification is the process of classifying a given text as one or several of several predetermined text categories according to the content of the text. As one of the key steps in processing huge amounts of text data, text classification is generally regarded as the orderly organization of text sets, that is, grouping similar and related texts together. In this way, the problem of information clutter can be solved to a greater extent, and the efficiency of users' discovery, filtering, and analysis of text information resources can be effectively improved. At present, the basis of text classification is mainly based on the characteristics of words in the article, to analyze the correlation between words and categories. This approach ignores information such as word order and collocations in literary translation texts. To solve this problem, this paper introduces the distributed incremental sequence data mining algorithm into the classification of literary translation texts. This method can fully mine the features of syntactic order and other features based on considering the words and phrasing characteristics of articles in different application fields. The text classification effect is strengthened by discovering more effective information. The experimental results show that the method can improve the classification performance of literary translation texts.
Analysis of Various Types of Glomerulonephritis with Crescents at a Single Center
Authors: Nakakita Tomo , Akiyama Kenichi , Karasawa Kazunori , Miyabe Yoei , Moriyama Takahito , Uchida Keiko , Nitta Kosaku
Published: May 2022

Background. The importance of crescent formation in glomerulonephritis has increased. However, detailed analysis of crescentic glomerulonephritis in Asia is scarce. In addition, advances in serological diagnostic techniques (antineutrophil cytoplasmic and antiglomerular basement membrane autoantibodies) and early diagnosis have reduced the number of cases meeting the strict definition of crescentic glomerulonephritis (>50% of glomeruli are crescentic). Therefore, we analyzed the clinicopathological features and renal prognosis of glomerulonephritis cases that exhibited at least one crescentic lesion. Methods. We retrospectively evaluated 265 adult patients diagnosed with glomerulonephritis with at least one crescent formation based on the results of renal biopsy. We divided the patients into two groups based on the four types of glomerulonephritis, namely, the immune-complex (type II: IgA nephropathy, IgA vasculitis with nephritis, and lupus nephritis) and pauci-immune (type III: microscopic polyangiitis) groups. Factors affecting renal prognosis (end-stage renal failure requiring renal replacement therapy) were examined in a multivariate analysis using the Cox proportional hazards model. Kaplan–Meier curves and log-rank test were used to analyze and compare time from entry to renal death. Results. Renal prognosis differed significantly between the immune-complex and pauci-immune groups. Among the four types of glomerulonephritis, IgA nephropathy was the most prevalent. Multivariate analysis showed that renal function at renal biopsy and the ratio of global sclerosis independently predicted renal prognosis, but the type of glomerulonephritis was not a factor. Conclusions. Renal dysfunction at renal biopsy and the ratio of global sclerosis predicted renal prognosis, because it reflects the degree of irreversible renal damage. We also suspect that the formation of at least one crescentic lesion led to the development of these predictive factors, regardless of the type of glomerular disease and degree of crescent formation.
Understanding the Slow Motion of the Wangjiashan Landslide in the Baihetan Reservoir Area (China) from Space‐Borne Radar Observations
Authors: Wu Mingtang , Yi Xiaoyu , Dun Jiawei , Yang Jianyuan , Cai Wei , Zhang Guoqiang
Published: May 2022

The analysis of landslide evolution using archived optical remote‐sensing images is common, but it is often limited by the acquisition frequency, cloud cover, and resolution. With the development of space‐borne radar observation technology, small baseline subset interferometric synthetic aperture radar (SAR) technology provides a new technical approach for detecting landslide deformation before disasters. The Sentinel‐1A SAR datasets (20170219–20210330) were used to study the time‐series deformation characteristics of the Wangjiashan landslide in the Baihetan Reservoir area before its impoundment. The time‐series results show that the Wangjiashan landslide was in an initial deformation state in the prior four years, and the deformation first occurred in the middle part and then expanded to the landslide toe and crown retrogressive movement characteristics. Combined with an analysis of field deformation signs, these findings suggest that the upper landslide mass formed a local sliding surface, which caused serious deformation of the road. An analysis of historical rainfall data revealed that the Wangjiashan landslide is sensitive to rainfall, and the deformation is not only significantly correlated with cumulative rainfall but also influenced by concentrated heavy rainfall. The research in this study provides a basis for the monitoring, early warning, and risk management of the Wangjiashan landslide during the impoundment period. This work also provides a useful reference for investigations using space‐borne SAR Earth observations in geological disaster prevention and control.
Design of College English Online Teaching Platform Based on Dual-Server PEKS Framework
Authors: Wang Hua
Published: May 2022

To improve the English learning efficiency of college students and improve the performance of network teaching, the research on the college English network teaching platform is carried out under the dual-server PEKS framework. After systematic testing and debugging, deployment and implementation, course migration, personnel training, and other links, the system has successfully completed deployment and implementation, which strongly support the research on the college English network teaching platform. The proposed dual-server PEKS search framework makes the teaching platform more secure by designing a linear homomorphic smooth projection HASH function and solves the security loopholes of traditional PEKS. Relevant research groups have conducted questionnaire surveys and information feedback on some teachers and students and generally have a good evaluation of the online teaching platform, indicating that the system has better realized the predetermined functions and effectively supported the research on the college English online teaching platform.
A Progressive Combined Variable Selection Method for Near-Infrared Spectral Analysis Based on Three-Step Hybrid Strategy
Authors: Sun Hongmin , Kong Fanze , Xiu Cheng , Shen Weizheng , Wang Yan
Published: May 2022

A specific variable selection method was proposed based on a three-step hybrid strategy for near-infrared spectral analysis. By analyzing functions of each step and characteristics of various variable selection methods, synergy interval partial least squares, iterative variable subset optimization, and bootstrapping soft shrinkage were chosen for three steps. To test the effect of the three-step hybrid method, it was applied to corn and soil spectral data and compared to other common methods. Results for oil content in corn data showed that the three-step hybrid variable selection method selected 1% variables of full spectrum, calibration determination coefficient, and prediction determination coefficient reached 0.998 and 0.993 where the explained variance was increased by 27.30%. It could effectively extract variables related to the tested substance and provide a new variable selection method for near-infrared spectral analysis.
The Core Mechanism of Yiqi Yangjing Decoction Inhibiting Nonsmall-Cell Lung Cancer
Authors: Yi Kaiyan , Zhou Yaning , Zhang Ming , Guo Yijun
Published: May 2022

Background. Yiqi Yangjing prescription (YQYJ) is a traditional Chinese medicine prescription used for treating lung cancer. It has a significant effect on enhancing efficacy, reducing toxic symptoms, and improving patients’ physical well-being. The effective inhibitory effect on nonsmall-cell lung cancer (NSCLC) has been demonstrated in vitro and in vivo. However, the mechanism of action and the material basis still remain unclear. Methods. In this study, we explored this mechanism using network pharmacology, after which we explored the pharmacodynamics and the action mechanism of YQYJ using cell viability evaluation, plate clone formation assay, flow cytometry, real-time quantitative PCR, and Western blot. Results. The enrichment results showed that there were 50 active components and 68 core targets related to YQYJ inhibiting NSCLC, including quercetin, luteolin, gamatin, kaempferol, heat shock protein HSP 90-alpha (HSP90AA1), cyclin-dependent kinase 2 (CDK2), epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 3 (STAT3), and others. Among them, quercetin and kaempferol revealed the best binding effect with core targets. Most importantly, YQYJ promoted A549 cells from the quiescent phase into the proliferative phase to enhance the sensitivity of A549 cells to YQYJ and inhibited the proliferation of A549 cells significantly (

P
<
0.05

). The A549 cells were blocked in both S and G2/M phases while the apoptosis ratio was increased. The proliferation score of A549 cells treated with YQYJ was significantly reduced compared to A549 cells in the proliferative phase (

P
<
0.05

). This regulatory effect was related to the expression regulation of HSP90AA1, CDK2, STAT3, and phosphor-STAT3 (p-STAT3) by YQYJ, kaempferol, and quercetin. Conclusion. Our results suggested that the inhibition of NSCLC via YQYJ had multicomponent and multitarget characteristics. Its core mechanism is related to the regulation of the cell cycle, proliferation, and apoptosis of NSCLC. This study provides a direction and scientific basis for exploring the future mechanism of YQYJ for the treatment of NSCLC.
Construction of Medical Academic English Translation Model Driven by Bilingual Corpus-Based Data
Authors: Liu Jinping , Liu Hong
Published: May 2022

With the rapid development of information collection technology and natural language processing technology, the construction of English-Chinese bilingual parallel corpus has developed rapidly. The scale of corpus and related technology have a large research space; and how to obtain effective data and knowledge from massive resources, in order to better serve the basic and applied research, is becoming a trend. Based on the research of parallel bilingual corpora at home and abroad, this article extracts the text features of medical English and constructs English-Chinese bilingual corpora with different levels aligned. Based on the statistical analysis of the distribution characteristics of phrase structures and the acquisition of characteristic knowledge, an English-Chinese bilingual translation model is constructed based on the bilingual corpus, and then the phrase structure knowledge in English and Chinese sentences is extracted from the data-driven English-Chinese bilingual corpus through the model. The results show that the accuracy of the test set is 91.63% and the F value is 90.05% under the condition of keeping the recall rate stable. The accuracy of the text structure features has been significantly improved, and the expected effect has been achieved through the test.
Chinese Herbal Medicine for Cervicogenic Dizziness: A Systematic Review and Meta-Analysis
Authors: Oh Hyunjoo , Shin Seungwon , Lee Euiju , Chung Won-Seok
Published: May 2022

Background. Chinese herbal medicines (CHMs) have been widely used in the treatment of cervicogenic dizziness (CGD) based on their empirical effectiveness and safety. Herein, we reviewed and evaluated the clinical evidence of the efficacy and safety of CHMs for CGD. Methods. Among the relevant studies published in 11 electronic databases up to December 2021, only randomised controlled trials were included. Methodological quality was assessed using the revised Cochrane risk-of-bias tool for randomised trials, and the strength of evidence for the main outcomes was evaluated using the grading of recommendations assessment, development, and evaluation system. Results. All 35 included randomised controlled trials with 3,862 participants were conducted with six types of modified CHM and four types of active controls. More than half of the included studies were of low quality because of the high risk of bias due to deviations from intended interventions. CHM plus active control was more effective in the treatment of CGD than active control alone. CHM plus anti-vertigo drugs, CHM plus manual therapy, CHM plus acupuncture therapy, and CHM plus manual and acupuncture therapy were all effective in treating CGD, with CHM plus manual and acupuncture therapy showing the most reliable effect. All CHMs were effective for specific patterns of CGD when administered with active controls, with Dingxuan Tang and Yiqi Congming Tang demonstrating the most reliable effects. No serious adverse events were reported in any of the included studies. Conclusion. The current evidence suggests that CHM may enhance the treatment of CGD when combined with other treatments without serious adverse events. Further high-quality evidence is needed to draw definitive conclusions.
Attentional Biases toward Face-Related Stimuli among Athletes after State Thwarting Need for Relatedness
Authors: Xu Na , Zhang Xuchang , Liu Xiuli , Sun Mingyu , Rui Li , Wang Yingchun
Published: May 2022

The present study aimed to examine attentional biases’ components and processes toward the interpersonal evaluation information among athletes after state thwarting need for relatedness. 51 athletes completed a visual dot-probe task while their eye-movements were tracking. Results indicated athletes showed different attentional bias pattern. Acceptance information is early orientation (directional bias); early acceleration detection; sustained to late attention maintenance (difficulty in disengaging). Rejection information is early orientation (directional bias); early accelerated detection; continuous attention to maintenance (attention avoidance); late attention to maintenance (difficulty in disengaging). That is to say, they had motivation to seek acceptance toward the accepted interpersonal evaluation information and to avoid rejection information toward the rejected one. Therefore, it is suggested that the coaches provide more interpersonal communicating opportunities, so as to help them to restore their demands toward interpersonal communication, and provide the customized attentional bias trainings to improve their coping response after state thwarted need for relatedness.
Mathematical Modeling of Carreau Fluid Flow and Heat Transfer Characteristics in the Renal Tubule
Authors: Rooman Muhammad , Shah Zahir , Bonyah Ebenezer , Jan Muhammad Asif , Deebani Wejdan
Published: May 2022

This study looks into the steady heat transfer issue of a flow of an incompressible Carreau fluid. Carreau fluid exhibits the shear thinning and thickening characteristics at low, moderate, and high shear rates. At the tubule wall, the fluid absorption is used as a function of pressure gradient and wall permeability through the tubule wall. Supposing the tubule radius considerably small in comparison to its length, the governing equations are considerably simplified. Significant quantities of interest are computed analytically by using perturbation, and the influence of emergent parameters is discussed through graphical results. The comparisons of results with existing data are set up to be good agreement.
Quantifying the Bullwhip Effect in a Reverse Supply Chain: The Impact of Different Forecasting Methods
Authors: Yuan Xigang , Zhang Xiaoqing , Wang Min , Zhang Dalin
Published: May 2022

The reason for this study is that the bullwhip effect can pose very serious consequences for enterprises, such as increased production costs, additional manufacturing costs, excessive inventory levels, excess storage costs, large capital overstocking, and excessive transportation costs. Thus, the problem for this study is that quantifying the bullwhip effect in a reverse supply chain and comparing the impact of different forecasting methods on it. The objective of this paper is the bullwhip effect (BE) in a reverse supply chain (RSC). In particular, this study proposes a quantitative expression of the BE in a RSC, that is,

B

E

R

=

V
a
r

q

t

/

V
a
r

r

t

, and analyzes the impact of different forecasting methods (e.g., the moving average technique (MA), the exponential smoothing technique (ES), and the minimum mean square error forecasting technique (MMSE)) on the bullwhip effect. We evaluate the conditions under which the collector should select different forecasting methods based on the BE. We use simulation date and get some conclusions that, in some cases when using the MMSE method, the BE does not exist in a RSC. This finding is significantly different from the results on the BE in a forward supply chain. Moreover, the MMSE method can reduce the lead-time demand forecast error to the greatest possible extent, which allows the BE to reach the lowest level.
Gas Seepage Model and Experiment Based on Bedding Effect of Fractured Coal Body
Authors: Tian Kunyun , Wei Erjian
Published: May 2022

Gas drainage is of great significance for the efficient and safe mining in coal mine, in which the coal seam layer bedding has a great influence on it. For obtaining gas permeability characteristics of coal body with the parallel and vertical bedding in fractured coal under the action of stress loading and unloading, experimental research was carried out employing a three-stress-axis simulation device. Experimental results showed that in the stress loading process, the permeability decreased with increasing effective stress; the decrement was initially rapid albeit it slowed later. With the increase of effective stress, the coal sample underwent three stages, namely, crack compaction, elastic deformation, and plastic deformation. In the stress unloading process, the permeability of coal samples increased with decreasing of effective stress, and the increasing trend of permeability was consistent. The degree of fracture compaction of the parallel bedding coal samples after compression was much higher than that of vertical bedding. In the stress-relieved coal seam, gas drainage boreholes should be arranged vertically to the bedding fissure to maximise the gas drainage effect. A group of parallel and vertical bedding gas drainage holes were arranged in the test mine to investigate the drainage effect. Field engineering application also showed that the drilling direction should be perpendicular to the bedding direction as far as possible, so as to improve the gas drainage effect. The research results can provide a reference for the gas drainage borehole layout, thus maximising the gas extraction efficiency and ensuring the sustainability of mine safety production.
Feasibility Study on the Integration of Innovation and Entrepreneurship Education and Occupational Therapy Training Mode for College Students Based on Big Data
Authors: Yang Yan , Xie Juan
Published: May 2022

With the development of information technology, the status of the traditional teaching method combining chalk and blackboard is declining. People need a novel teaching method to reform traditional education, so the hybrid teaching mode combining the advantages of both is produced and has become a major research hotspot in the field of education technology at present. Further accelerating the reform of innovation and entrepreneurship teaching in higher education institutions and improving students’ innovation and entrepreneurial ability based on big data technology are the fundamental measures to do a good job in managing college students’ entrepreneurship and employment. Therefore, the reform of dual-innovation education in colleges and universities has become a research hotspot in recent years. How to combine the two aforementioned research hotspots in order to improve college students’ dual-innovation ability is a key issue that needs to be solved urgently. College students’ innovation and entrepreneurship practice is in full swing in colleges and universities, but the success rate of college students’ entrepreneurship is not high. In order to promote the development of college students’ entrepreneurial practice, colleges and universities can give them the necessary help. Integrating the content of “dual innovation” education with big data technology into the ideological and political education of college students can not only improve the ideological and political quality and moral and psychological quality of college students but also convey the relevant legal policies of innovation and entrepreneurship to college students. Today’s society has entered the Internet era, the resource of information technology, and the rapid development of the Internet which provides good technical support and rich content choices for the innovation of ideological and political education of college students in the context of “dual innovation,” but it also poses new challenges for the ideological and political education of college students. By studying the exercise data of groups at all levels in the campus, we analyze and compare the overall exercise situation of each type of group and explore and study the overall exercise situation of various classes, grades, schools, etc., to understand the physical activity. We can build a group of ideological and political education teachers with innovative and entrepreneurial literacy based on big data analysis. Only in this way can the ideological and political education of college students really give some help to the practice of innovation and entrepreneurship of college students and stimulate the potential of innovation and entrepreneurship of college students from a deeper level.
Optimal Design and Aerodynamic Performance Prediction of a Horizontal Axis Small-Scale Wind Turbine
Authors: Yin Rui , Xie Jian-Bin , Yao Ji
Published: May 2022

The improved aerodynamic design of a horizontal axis small-scale wind turbine blade is crucial to increasing the efficiency and annual energy production of the turbine. One of the vital stages in aerodynamic design is the selection of the airfoil. Using the existing airfoils for a blade design which results in higher turbine characteristics is tedious. Consequently, this paper provides an optimal design strategy for a horizontal axis small-scale wind turbine blade through the multiobjective optimization of the airfoil using the Nondominated Sorting Genetic Algorithm II (NSGA-II). The latter outperforms the other commonly used genetic algorithms (GAs), as well as the Computational Fluid Dynamics (CFD) investigation of the different airfoil types and the wind turbine rotors on the steady or unsteady state aerodynamic performance. An NACA4412 airfoil with higher aerodynamic efficiency is considered as a baseline for the optimization in order to increase the lift coefficient and lift to drag ratio while avoiding excessive variations in the maximum relative thickness and area. The optimized airfoil (NACA4412-OPT) is used as the cross-sectional profile in the design procedure for a novel 1.15 m diameter three-bladed wind turbine rotor at a wind speed of 11.5 m/s, tip speed ratio of 4.65, and pitch angle of 0.2° by the Wilson design method. The two-dimensional analysis demonstrates that the optimized airfoil outperforms the other airfoils yielding the highest lift coefficient and lift to drag ratio, as well as a larger pitch range. The three-dimensional analysis shows that the time-averaged power coefficient value (0.33) of the new wind turbine is almost 26% higher and more stable than that of the original wind turbine while avoiding a high increase of the axial thrust.
Magnetic Anomaly Data Detection of Local Marine Geomagnetic Field Model considering Robust Trend Surface Scientific Calculation Algorithm
Authors: Su Wei
Published: May 2022

As a momentous part of marine data detection, modeling the marine geomagnetic field and detecting its magnetic data have momentous theoretical and practical value for obtaining its geomagnetic field parameters and characteristic distribution and then carrying out marine environment research. The detection of magnetic anomaly data of local marine geomagnetic field model has become a momentous prerequisite for obtaining key parameter info of local ocean and subsequent development and utilization. On account of this, this paper first analyzes the detection of local marine geomagnetic anomaly data, then studies the theoretical basis of local marine geomagnetic field model, as well as the measurement and modeling of local marine geomagnetic field data, and finally gives the analysis of the detection results of local marine geomagnetic anomaly data considering the robust trend surface.
Work‐Related Musculoskeletal Disorders and Their Associated Risk Factors among Pakistani Dental Practitioners: A Cross‐Sectional Study
Authors: Younis Usman , Shakoor Asma , Chaudhary Farooq Ahmad , Din Shahab Ud , Sajjad Sadia , Younis Maryiam , Javed Muhammad Qasim , Alam Mohammad Khursheed
Published: May 2022

Background. Work‐related musculoskeletal disorders (WMSDs) have a negative impact on quality of life, and dentists are at risk of WMSDs due to the nature of work being static, repetitious, and for a long duration. The study was aimed at measuring the prevalence and distribution of work‐related musculoskeletal disorders and determining the risk factors associated with affliction among Pakistani dentists. Methods. An online cross‐sectional survey was conducted using a validated questionnaire consisting of four sections. The first section had questions related to sociodemographic information, the second section had questions that assessed the intensity and frequency of musculoskeletal pain (MSP), third section questions were concerned with the effect of MSP on the respondents’ daily life, while the last section contained questions on whether they perceived their work in the dental clinic as a cause of their pain. Chi‐square and one‐way ANOVA tests were used for the analysis of the data in SPSS‐23. Results. A total of 600 completely filled questionnaires were received with a response rate of 76.4%, and about 87% of the dental practitioners had some sort of MSD. The intensity and frequency of WMSDs were statistically significant (p < 0.05) in association with all the sociodemographic characteristics. The lower back area was the most reported site of WMSD pain (51.3%) followed by the neck/upper back (21.3%) and shoulder (17.6%). The site of pain was statistically significant (p < 0.05) in association with all the sociodemographic characteristics except gender (p = 0.11). A majority of participants (95.4%) had sought medical treatment and taken sick leaves (70%) due to WMSDs pain during their life. Participants attributed a number of working years and working posture as the two main reasons behind WMSDs. Conclusion. Considering the high prevalence of WMSDs among dentists, preventive strategies that minimize the occurrence of WMSDs should be adopted by dental professionals. The impact of WMSDs can be reduced by maintaining good posture, taking breaks and rest in between work, doing regular exercise, and improving the work environment.
Analysis on the Sharing Method of English Mobile Education Resources Based on Wireless Broadband Connection
Authors: Chen Li , Wang Linlin
Published: May 2022

The sharing of English educational resources has always been a research hotspot in the English industry. The traditional English educational resource sharing system has low resource sharing efficiency and no real-time contribution capability. Therefore, this paper proposes a method to analyze the characteristics of online educational resources. By comparing the main features of the IEEE802 wireless standard series, the IEEE802.16 protocol stack model is constructed by using the IEEE802.16 protocol, the business layer design and CS layer of the English education resource system are realized through the MAC layer and the CPS layer, and the mobile English education resource sharing system is analyzed. Live voting service: in order to improve the sharing speed of mobile English education resources, an NRTPS uplink bandwidth allocation mechanism is proposed, and the design of a mobile English education resource sharing system based on wireless broadband connection is realized. The experimental results show that the resource sharing efficiency of the system is high, and it plays an important role in the development of English education.