bluuebunny/crossref_metadata_2025 huggingface dataset:
College English Audio-Visual-Oral Teaching Mode from the Perspective of Artificial Intelligence
Authors: Ling Li
Published: September 2022

The “New Era Artificial Brain Power Improvement Plan” issued by the State Council and the “Computer Reasoning Development Activity Plan for Colleges and Universities” issued by the Ministry of Education clearly pointed out that it is necessary to attach importance to the combination of modern education and artificial intelligence. As a global language, English is becoming more and more important in global trade. Under the premise of educational plan changes in the new environment, English teaching is gradually reflected in the cultivation of college students’ English application ability. This research studies the current college English audio-visual-oral teaching mode from the perspective of artificial intelligence and analyzes the current situation of traditional English teaching by explaining the meaning of artificial intelligence, which mainly includes four stages: literature research, model construction, empirical research, and result analysis. In light of BP neural network, the showing assessment model of school English audio-visual-oral is laid out, and the change technique of showing method of school English audio-visual-oral under AI is advanced. Experiments show that this model achieves better teaching quality than the models constructed by traditional GA algorithm and BSA algorithm and is more suitable for promotion in college English teaching.
[Retracted] Evaluation of Teaching Quality on IP Environment Driven by Multiple Values Theory Based on Big Data
Authors: Gu Xiujuan
Published: September 2022

Despite the fact that big data technology has been applied in education, there are no studies and cases that combine big data with ideological and political (IP) teaching quality. At the same time, the existing methods of IP teaching quality evaluation lack the consideration of multiple values, and the system is not complete and systematic. The use of big data analysis technology can improve the rigor of teaching quality assessment and make the data analysis more scientific, so as to improve the management system of universities and enhance the education quality. Therefore, this paper fully considers the background conditions of large data at this stage, on the basis of studying the methods of evaluating the quality of IP teaching in colleges. The big data about teaching quality is obtained by distributed algorithm, and multiple value indicators are drawn into the quality evaluation system as a main driver to emphasize the multiple value theory. Hierarchical analysis (AHP) method and fuzzy comprehensive evaluation (FCE) method are selected as the data analysis methods to provide evaluation basis for the proposed model. This model can further test the evaluation index system of education and further verify the rationality of the distribution of the weight of indicators at all levels. The evaluation results based on the large educational data and research data of a university show that the IP teaching quality of the university is excellent. The comprehensive evaluation model overcomes the limitations of traditional evaluation methods and provides a more comprehensive analysis about the teaching quality of IP teaching in colleges. Meanwhile, the conclusions obtained by the proposed evaluation model can be used for both the overall comprehensive evaluation of teachers’ teaching quality and a single comprehensive evaluation of the single factor affecting teaching quality. Using the evaluation results obtained by the model, we can set up advanced models and encourage backward students to have evidence. With the single‐index evaluation, we can know what advantages the IP teaching or a certain teacher has and what aspects need to be strengthened. Therefore, we can put forward reasonable suggestions to progress instructing strategies and educating quality.
A System and Method for Intelligent Induced Maintenance of Space Application Facilities
Authors: Zhang Yanan , Zhang Lu , Fu Hongyong , Yu Dequan , Li Zhenxiang , Wang Ke
Published: September 2022

The product characteristics and maintenance characteristics of space complex repairable facilities were analyzed to aim at the maintenance requirements with a large number of on-orbit replaceable units, complex systems, and high operation accuracy. An intelligent induced maintenance system for space application facilities was developed, and unique evaluation criteria were established. The system, key technologies, and application effects are verified through typical application cases and comparative experiments. The results show that the implementation of the system can effectively reduce the workload of the astronauts in orbit and improve the work efficiency and provide new cooperation means for the astronauts to solve the urgent and unexpected tasks in orbit.
A Study on College Students’ Cognitive Intention and Path Choice of Entrepreneurship from the Perspective of Individual and Group Cooperation
Authors: Zhao Yingjie
Published: September 2022

In order to study the overall low entrepreneurial enthusiasm of college students, a method was proposed based on the cognitive intention and path choice of college students’ entrepreneurship from the perspective of individual and group cooperation. The method briefly introduces the achievement motivation theory, entrepreneurial intention theory, entrepreneurial cognition theory, classical game theory, computer simulation, and experimental methods. Then, the research hypothesis and model construction method are elaborated, and a questionnaire is designed to study the cognitive intention and path of entrepreneurship of college students. Finally, data analysis and hypothesis testing are described to provide a guarantee for college students’ entrepreneurship. The results show that the fundamental driving force for the great progress of entrepreneurship education in colleges and universities is to meet the needs of both the collective and the individual in the top-level design and to realize the mechanism through which entrepreneurship education can achieve common development.
[Retracted] An Intelligent Recommendation Model for Health Culture Based on Short Video Content Analysis in the Mobile Internet Environment
Authors: Ma Miao , Zhang Xijing
Published: September 2022

The heart and soul of the Chinese people and the greatest cultural soft power of contemporary China are excellent Chinese healthy cultural environments. Short video platforms and short videos have a chance to develop as the Internet revolution continues to intensify and mobile clients gain popularity. This essay examines the challenges involved in producing brief videos that promote a healthy cultural environment in the new context of internet plus, as well as the means of transmitting such videos and creative methods for doing so. Excellent communication content is created in this paper from two perspectives of visual presentation and in‐depth meaning, allowing users to fully understand the connotation of a healthy cultural environment. Through the theme of a healthy cultural environment, topic discussion and characteristic activities will be carried out to encourage users’ spontaneous sharing of the interactive behavior of communication and the fission communication of brief videos of a healthy environment. This paper develops a model for intelligent recommendation and short video content analysis based on this. In order to further encourage the creative dissemination and development of short videos about healthy cultural environments, the model is used to choose high‐quality videos and accurately recommend them to the appropriate users and to serve as an example of how a quick video can be used to communicate innovation and a healthy cultural environment.
[Retracted] Analysis of the Predictive Effect of Lactic Acid Combined with Cardiac Troponin T and 5‐Hydroxytryptophan on the Severity of Sepsis in ICU Patients and Its Correlation with Prognosis
Authors: Jiang Meini , Wu Weidong , Wang Xiuzhe , Zhao Caixia
Published: September 2022

In order to explore the effective markers of presepsis in the prediction of clinical disease and disease severity, the predictive effect of lactic acid (Lac) combined with cardiac troponin T (cTnT) and 5‐hydroxytryptophan (5‐HT) on the severity of sepsis in intensive care unit (ICU) patients and its correlation with prognosis is investigated. A total of 85 sepsis patients admitted to the ICU of our hospital from January 2020 to June 2021 are selected to establish the ICU sepsis group, and 72 health examination patients who received physical examination in our hospital during the same period are included in the healthy control group. The experimental results demonstrate that combined detection mode of serum Lac, cTnT, and 5‐HT indicators has a high predictive value for the condition of patients with ICU sepsis and those indicators are closely correlated with the prognosis of patients. It suggests that the follow‐up clinical monitoring of serum Lac, cTnT, and 5‐HT indicators for patients with ICU sepsis can evaluate their condition and improve and optimize the clinical diagnosis and treatment plan effectively.
Graphical Exploration of Generalized Picture Fuzzy Hypersoft Information with Application in Human Resource Management Multiattribute Decision-Making
Authors: Rahman Atiqe Ur , Saeed Muhammad , Bonyah Ebenezer , Arshad Muhammad
Published: September 2022

In this study, the graphical exploration of a novel hybrid, that is, possibility of picture fuzzy hypersoft graph (

popfhs

-graph) is accomplished. The

popfhs

-graph is more flexible and reliable in the sense that it has the ability to tackle the limitations of picture fuzzy soft graph regarding the entitlement of multiargument approximate mapping and possibility degree-based setting. Its approximate mapping considers the Cartesian product of subclasses of parameters as domain and then maps it to the power set of universal set. The possibility degree-based setting ensures the assessment of uncertain attitude of approximate elements up to the level of acceptance. First, some of elementary notions and set theoretic operations of

popfhs

-graph are investigated with the support of numerical examples and pictorial representations. Second, some of its variants, types of products, and composition are also discussed. Lastly, based on aggregation of the

popfhs

-graph, an algorithm is proposed for multiattribute decision-making problem and validated by resolving daily-life recruitment problem for the best selection of candidate.
On a Study of a Family of Higher-Order Recurrence Relations
Authors: Folly-Gbetoula Mensah , Mkhwanazi Kgatliso , Nyirenda Darlison
Published: September 2022

In this work, group theory is applied to obtain generators of the Lie algebra for a class of rational difference equations of order

k
+
l

where

k

and

l

are positive integers. This is followed by deriving invariants and solutions via some linear recurrences and with the introduction of some number-theoretic arithmetical functions. Furthermore, sufficient conditions for the existence of solutions for periods two and four are provided in special cases. The results in this paper generalize certain known results.
Ablation of Basic Leucine Zipper Transcription Factor ATF-Like Potentiates Estradiol to Induce Atopic Dermatitis
Authors: Zhang Peng , Liu Luhao , Lai Xingqiang , Chen Rongxin , Guo Yuhe , JunjieMa  , Chen Wenhao , Chen Zheng
Published: September 2022

Background. Atopic dermatitis (AD) is an inflammatory and immune skin disorder. Basic leucine zipper transcription factor ATF-like (BATF) plays a key role in regulating the differentiation and functions of lymphocytes. However, the mechanism underlying the transcriptional regulation of BATF on AD is still not well understood. Methods. BATF knockout (BATF–/–) and C57BL/6(B6) mice were used for the development of spontaneous dermatitis. 17β-Estradiol was injected intraperitoneally to induce AD. The lesioned tail skin of the mice was stained with hematoxylin and eosin to analyze the pathological characteristics. Impaired skin barrier function was assessed by measuring the transepidermal water loss (TEWL). The skin epithelial barrier indicators and cytokine mRNA levels were quantified by real-time quantitative PCR. The total serum immunoglobulin E (IgE) levels were measured by enzyme-linked immunosorbent assay (ELISA). T lymphocytes were analyzed using flow cytometry. Results. Ablation of BATF led to the spontaneous development of AD only in female mice and not in male mice. BATF deletion led to elevated serum levels of IgE and increased infiltration of eosinophils, neutrophils, and lymphocytes and promoted cytokine production including IL-4, IL-22, IL-1β, IFN-γ, and TNF-α in the lesioned tail skin of the mice. The mRNA expression levels of filaggrin and loricrin significantly decreased, while S100A8 and S100A9 increased in female BATF–/– mice. BATF-deficient female mice were found to increase proliferation and IL-5 production by skin-infiltrating CD4+ T cells which implies Th2 activation. Moreover, AD was successfully induced only in the estradiol-treated BATF-deficient male mice and not in WT male mice. Estradiol enhanced the allergic and immunological responses to dermatitis primarily by triggering Th2-type immune responses via enhanced serum IgE and inflammatory cytokine levels in the male BATF–/– mice. Conclusion. The study concluded that BATF potentiates estradiol to induce mouse atopic dermatitis via potentiating inflammatory cytokine releases and Th2-type immune responses and may have important clinical implications for patients with AD.
Application of Neural Network with Autocorrelation in Long-Term Forecasting of Systemic Financial Risk
Authors: Zhang Junzhi , Chen Lei
Published: September 2022

Carrying out early warning of systemic financial risk is a prerequisite for timely adjustment of monetary policy and macroprudential policy to effectively prevent and resolve systemic financial risks. This paper constructs a systemic financial risk monitoring and early warning system for China’s banking industry based on isolated forest anomaly detection and neural network with autocorrelation mechanism and uses low-frequency data with high credibility to effectively identify the ten factors that have the greatest impact on systemic financial risk in China’s banking industry, improving the prospective and accuracy of risk early warning. The conclusions can help regulators to adjust their policies prospectively to curb the rise of systemic financial risks.
Analysis of Blasting Vibration Effect of Railway Tunnel and Determination of Reasonable Burial Depth
Authors: Wang Hailong , Zhao Yan , Shan Renliang , Tong Xiao , Liu Dong
Published: September 2022

Based on specific examples of underpass tunnel blasting, field measurements, and numerical simulation studies are carried out. According to the results of the blasting vibration data measured on-site, a regression model of the blasting vibration velocity is established. Based on the wavelet packet energy spectrum analysis method, the effect of frequency on the vibration response intensity is studied. In addition, the maximum charge per delay allowed for tunnel blasting is obtained by formula inversion. Relying on ANSYS/LS-DYNA to establish a three-dimensional numerical model, the accuracy of numerical simulation can be checked by the measured vibration data. The results show that the numerical simulation has high precision and can meet the subsequent analysis needs. Using numerical simulation, the variation law of the vibration response characteristics of ground blasting under different tunnel burial depths is studied. The analysis results show that with increasing tunnel burial depth, the ground blasting vibration velocity decays exponentially. According to the corresponding specification of blasting vibration, a reasonable value range of the buried depth of the underpass tunnel can be obtained. The research ideas and methods introduced can be used for reference for similar railway tunnel blasting control and railway tunnel route selection.
Dynamic Reliability-Aware Virtual Network Embedding for Airborne Tactical Networks
Authors: Miao Jingcheng , Lv Na , Chen Kefan , Gao Qi , Wang Xiang
Published: September 2022

Airborne tactical networks (ATNs) built on network virtualization (NV) can enable efficient information sharing for network-centric warfare by breaking the tight coupling between applications and network infrastructure and thus solving the network ossification problem. With dynamic changes during military missions, the application of virtualization is challenged by the changing demands on network resources when instantiating multiple virtual networks (VNs) on a shared substrate network (SN), known as virtual network embedding (VNE). However, existing dynamic VNE algorithms, mostly designed for wired networks, focus on the dynamic changes of single VN and do not consider the dynamic changes of different VNs. The proper processing of changes of different VNs is beneficial to improve the embedding profits of VNs. On these backgrounds, we investigate the dynamic wireless VNE that processes the dynamic changes of different VNs in the wireless environment of ATNs. A relationship matrix-based dynamic wireless VNE (DWVNE-RM) algorithm is proposed in order to maximize the acceptance ratio of VN requests. The dynamic changes of different VNs are classified into negative changes (requiring resource) and positive changes (releasing resource). Then, the relationship matrix between negative and positive changes is constructed to properly process the resource relationship among different changes in order to improve the acceptance ratio. In addition, the complex interference of ATNs is considered in the mapping or remapping of virtual nodes and links to improve the reliability. Through extensive simulation, DWVNE-RM is compared with multiple existing dynamic algorithms and outperforms over others.
Technology Opportunity Recognition Algorithm and Decision Assistance for Non-Drug Antidepressant Field in China
Authors: Cui Yanyin , Zhao Bingbing , Xia Fang
Published: September 2022

The aim of this study is to propose a framework for non-pharmaceutical antidepressant technology opportunity identification in China, based on patent analysis and assisted decision making. Semantic mining technology was used to divide technology life cycle, classify technology, identify key technology associated opportunities, and identify core technology functions of 532 non-drug antidepressant patent data in China from 1995 to 2021. Combined with co-occurrence and multi-dimensional scale analysis, strategic coordinate maps and technology decision assistance maps were drawn. The development of non-drug antidepressant technology in China was divided into embryonic stage, formative stage, and development stage. Six technical categories, 30 high-frequency technical associated opportunities, and low-frequency and high-frequency core technical opportunities for non-drug antidepressants were summarized. Based on four technical fields and four functional clusters of strategic coordinate graphs, the technical opportunity decision auxiliary atlas was constructed. By comparison, this map is more intuitive than the technology-efficacy matrix, when presenting technology efficiency mapping. This study provides a set of systematic algorithms for opportunity identification and decision assistance based on patent data, in addition to reference for strategic decision making of non-drug antidepressant technology subjects in China.
Application of Deep Learning in College Physical Education Design under Flipped Classroom
Authors: Huang Jun , Yu Dian
Published: September 2022

With the development of information technology, teaching reform has also undergone major changes. The traditional college physical education teaching method cannot meet the needs of the majority of students, and the physical education teaching mode continues to be reformed. Microcourse is the most intuitive form of deep integration of information technology and physical education. From the perspective of the flipped classroom (FC), the physical education model has gradually changed from teacher centered to student centered. Deep learning (DL) emphasizes that learners have the ability to actively construct knowledge, effectively transfer knowledge, and solve real problems. This design applies DL and convolutional neural network to the teaching design of physical gymnastics in colleges and universities. The application of the DL teaching model based on FC in the microcourse teaching of gymnastics in colleges and universities is studied and evaluated. The results show that the current utilization of microcourse teaching resources is too low. Interest-oriented teaching microcourses cannot improve students’ interests. The proportion of students who are interested is relatively small, and more than 50% of students are not interested. Teachers generally believe that the current gymnastics microcourse needs further optimization and improvement. The poor quality of microvideos and the lack of supervision and reward mechanism in the course are the main reasons for the insufficient students’ interest. The complexity of the videos and the liveliness of the discussions are the main problems of low resource utilization. The student’s interest in learning is greatly improved after the application of the designed model, and the proportion increases to 82.4%. The effect on ordinary college students is the most obvious, and the effect of microvideo learning has been significantly promoted. Design mode has the most obvious improvement in improving learning efficiency and autonomous learning ability. The improvement of learning ability has increased from 18% to 72%, and the improvement of learning efficiency has increased from 39% to 82%. Meanwhile, students’ interest in learning is stimulated, and the utilization of resources is improved.
A Data-Driven Model for Automated Chinese Word Segmentation and POS Tagging
Authors: Xu Qing , Wang Zhiyou
Published: September 2022

Chinese natural language processing tasks often require the solution of Chinese word segmentation and POS tagging problems. Traditional Chinese word segmentation and POS tagging methods mainly use simple matching algorithms based on lexicons and rules. The simple matching or statistical analysis requires manual word segmentation followed by POS tagging, which leads to the inability to meet the practical requirements for label prediction accuracy. With the continuous development of deep learning technology, data-driven machine learning models provide new opportunities for automated Chinese word segmentation and POS tagging. Therefore, a data-driven automated Chinese word segmentation and POS tagging model is proposed in order to address the above problems. Firstly, the main idea and overall framework of the proposed automated model are outlined, and the tagging strategy and neural network language model used are described. Secondly, two main optimisations are made on the input side of the model: (1) the use of word2Vec for the representation of text features, thus representing the text as a distributed word vector; and (2) the use of an improved AlexNet for efficient encoding of long-range word, and the addition of an attention mechanism to the model. Finally, on the output side, an additional auxiliary loss function was designed to optimise the Chinese text based on its frequency. The experimental results show that the proposed model can significantly improve the accuracy and operational efficiency of Chinese word segmentation and POS tagging compared with other existing models, thus verifying its effectiveness and advancement.
Overexpression of SRD5A3 in Hepatocellular Carcinoma and Its Molecular Mechanism: A Study of Bioinformatics Exploration Analysis with Experimental Verification
Authors: Chen Erbao , Yi Jing , Ren Qingqi , Mi Yuanna , Gan Zhe , Liu Jikui
Published: September 2022

Background. Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and more prevalent among males than females. However, the biological role of enzyme 5α-reductase (SRD5A3), which plays a critical role in the androgen receptor signaling pathway during HCC development, remains poorly understood. Methods. ONCOMINE, GEPIA, UALCAN, and Kaplan–Meier Plotter were used to analyze the expression and prognostic value of SRD5A3 in HCC. STRING and Metascape were applied to analyze potential target and molecular pathways underlying SRD5A3 in HCC. A real-time quantitative reverse transcription-polymerase chain reaction was used to validate the downstream target expression of SRD5A3. Results. The expression of SRD5A3 was significantly overexpressed in HCC tissues compared with normal tissues, while the expression of SRD5A1 and SRD5A2 were downregulated in multiple public datasets. It may be that the low methylation of the SRD5A3 promoter leads to its overexpression. The level of SRD5A3 tended to be higher expressed in clinical samples with advanced stage and positive node metastasis. Furthermore, the patients with higher SRD5A3 were remarkably associated with poorer overall survival and disease-free survival in the TCGA data. In addition, the increased mRNA expression of SRD5A3 could predict poorer overall survival in Kaplan–Meier Plotter database including different patient cohorts. Moreover, HCC patients with higher level of SRD5A3 had significantly shorter recurrence-free survival, progression-free survival, and disease-specific survival. Furthermore, enrichment analysis demonstrated that multiple processes, such as steroid hormone biosynthesis, lipid biosynthetic process, and androgen metabolic process, were affected by SRD5A1-3 alterations. In vitro experiments showed that the expression of SRD5A3 was increased in HCC tissues than that in adjacent tissues. SRD5A3 silencing promoted the expression of DOLK in two HCC cell lines. Conclusions. This study identified SRD5A3/DOLK as a novel axis to regulate HCC development.
From Hair to Colon: Hair Follicle-Derived MSCs Alleviate Pyroptosis in DSS-Induced Ulcerative Colitis by Releasing Exosomes in a Paracrine Manner
Authors: Chang Yuan , Zhang Yichi , Jiang Yanan , Zhao Lei , Lv Chengqian , Huang Qianqian , Guan Jingming , Jin Shizhu
Published: September 2022

Ulcerative colitis (UC) has attracted intense attention due to its high recurrence rate and the difficulty of treatment. Pyroptosis has been suggested to be crucial in the development of UC. Although mesenchymal stem cells (MSCs) are broadly used for UC therapy, they have rarely been studied in the context of UC pyroptosis. Hair follicle-derived MSCs (HFMSCs) are especially understudied with regard to UC and pyroptosis. In this study, we aimed to discover the effects and potential mechanisms of HFMSCs in UC. We administered HFMSCs to dextran sulfate sodium- (DSS-) treated mice and found that the HFMSCs significantly inhibited pyroptosis to alleviate DSS-induced UC. A transwell system and GW4869, an exosome inhibitor, were used to prove the paracrine mechanism of HFMSCs. HFMSC supernatant reduced pyroptosis-related protein expression and promoted cell viability, but these effects were attenuated by GW4869, suggesting a role for HFMSC-released exosomes (Exos) in pyroptosis. Next, Exos were extracted and administered in vitro and in vivo to explore their roles in pyroptosis and UC. In addition, the biodistribution of Exos in mice was tracked using an imaging system and immunofluorescence. The results suggested that Exos not only improved DSS-induced pyroptosis and UC but also were internalized into the injured colon. Furthermore, the therapeutic efficacy of Exos was dose dependent. Among the Exo treatments, administration of 400 μg of Exos per mouse twice a week exhibited the highest efficacy. The differentially expressed miRNAs (DEmiRNAs) between MSCs and MSC-released Exos suggested that Exos might inhibit pyroptosis through tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) signalling and interferon- (IFN-) gamma pathways. Our study reveals that HFMSCs can alleviate pyroptosis in UC by releasing DEmiRNA-containing Exos in a paracrine manner. This finding may lead to new treatments for UC.
Salmonella Exhibit Altered Cellular Localization in the Presence of HLA-B27 and Codistribute with Endo-Reticular Membrane
Authors: Kriston-Vizi Janos , Lenart Izabela , Iwawaki Takao , Gould Keith , Nesbeth Darren , Powis Simon J. , Antoniou Antony N.
Published: September 2022

Salmonella enteritica (S. enteritica) induce and require unfolded protein response (UPR) pathways for intracellular replication. Salmonella infections can lead to reactive arthritis (ReA), which can exhibit associations with Human Leucocyte Antigen (HLA)-B

∗

27 : 05. S. enteritica normally reside in a juxtanuclear position to the Golgi apparatus, representing the formation and residence within the Salmonella-containing vacuole (SCV). Changes in cellular localization of infecting Salmonella can alter their ability to replicate. We therefore used isogenic epithelial cell lines expressing physiological levels of HLA-B

∗

27 : 05 heavy chain (HC) and a control HLA-B allele, HLA-B

∗

35 : 01.HC to determine any changes in Salmonella localization within epithelial cells. Expression of HLA-B

∗

27 : 05 but not HLA-B

∗

35 : 01 was associated with a quantifiable change in S. enteritica cellular distribution away from the Golgi apparatus. Furthermore, the Salmonella requirements for UPR induction and the consequences of the concomitant endoplasmic reticulum (ER) membrane expansion were determined. Using confocal imaging, S. enteritica bacteria exhibited a significant and quantifiable codistribution with endo-reticular membrane as determined by ER tracker staining. Isogenic S. enterica Typhimurium mutant strains, which can infect but exhibit impaired intracellular growth, demonstrated that the activation of the UPR was dependent on an integral intracellular niche. Therefore, these data identify cellular changes accompanying Salmonella induction of the UPR and in the presence of HLA-B27.
Big Data Analytics in Supply Chain Management: A Qualitative Study
Authors: Aljabhan Basim , Abeyie Melese
Published: September 2022

This work explores the leading supply chain processes impacted by big data analytic techniques. Although these concepts are being extensively applied to supply chain management, the number of works that examine and classify the main processes in the current literature is still scarce. This article, therefore, provides a classification of the current literature on the use of big data analytics and provides insight from professionals in the field in relation to this topic. A well-established set of practical guidelines was used to design and carry out a systematic literature mapping. A total of 50 primary studies were analysed and classified, chosen from a sample of 5, 437 studies after careful filtering to answer six research questions. In addition, a survey was prepared and applied by professionals working in the area. In total, 25 professionals answered a questionnaire with eleven questions, ten of which seek to explore the importance of big data analytics for the areas of the supply chain addressed in this work, and one intends to list the three areas where BDA can be more shocking. More than 60% of the studies are directly linked to the area of chain management; most studies performed empirical studies but rarely classified or detailed methodological procedures; almost 50% bring models to optimize some process or forecasts for better decision-making; more than 50% of professionals working in the area believe that the processes where big data analytics can effectively contribute are related to inventory and stockout management. This study serves as a basis for further research and future work, as it reviews the literature, pointing out the main areas that are being addressed and making a relationship with understanding these areas in practice.
[Retracted] The Disparity in the Management of Polycystic Ovary Syndrome between Obstetrician‐Gynecologists in Different‐Level Hospitals under the Hierarchical Medical System
Authors: Wang Yue , Chen Jie , Dong Han , Ma Ruilin , Zou Ying , Wang Wei , Zheng Qingmei , Feng Ying , Tan Zhangyun , Zeng Xiaoqin , Zhao Yinqing , Deng Yan , Wang Yanfang , Gu Bei , Sun Aijun
Published: September 2022

Background. PCOS is a prevalent endocrine and metabolic disorder in women characterized by abnormal blood glucose, dyslipidemia, and abnormal mental health. To improve patient care, the goal of our study is to find out if there are differences in how PCOS patients are treated at different hospital levels within the hierarchical medical system. Methods. Obstetricians and gynecologists from primary, secondary, and tertiary hospitals were the participants in the survey. The responses provided and collected were analyzed using various statistical techniques like the chi‐square test, Fisher exact test, and logistic regression with multiple variables. Results. The investigation examined 2298 survey replies (13.1% primary hospitals, 52.4% secondary hospitals, and 34.5% tertiary hospitals). As hospital grade increases, more participants inquire about a patient’s history of unfavorable pregnancies concerning hormone evaluation; the better the hospital’s grade, the greater the number of participants who would undergo AMH and androgen‐related tests. The higher the hospital level, the more participants would pick the oral glucose tolerance test (OGTT) to determine insulin resistance, the BMI Asian criteria for defining obesity, and blood lipids. Participants in primary (odds ratio (OR) = 0.383, 95% confidence interval (CI) 0.282‐0.520) and secondary (OR = 0.607, 95% confidence interval (CI) 0.481‐0.765) hospitals were significantly less likely to select OGTT than those in tertiary hospitals. Comparatively, fewer primary hospitals chose to do lipid profiling than tertiary hospitals (OR 0.689, 95% CI 0.523‐0.909). With the increase in hospital level, participants were more knowledgeable about the multiple efficacies and dose alternatives of metformin and selected letrozole and assisted reproduction more frequently. Conclusion. Our study uncovered differences in the endocrine evaluation, metabolic screening, and management of PCOS patients across obstetrics and gynecology at various hospital levels. Simultaneously, it underlines the need to improve the hierarchical medical system and close the knowledge gap across hospitals.
Research on 24-Hour Dense Crowd Counting and Object Detection System Based on Multimodal Image Optimization Feature Fusion
Authors: Ren Guoyin , Lu Xiaoqi , Li Yuhao
Published: September 2022

Motivation. In the environment of day and night video surveillance, in order to improve the accuracy of machine vision dense crowd counting and target detection, this paper designs a day and night dual-purpose crowd counting and crowd detection network based on multimode image fusion. Methods. Two sub-models, RGBD-Net and RGBT-Net, are designed in this paper. The depth image features and thermal imaging features are effectively fused with the features of visible light images, so that the model has stronger anti-interference characteristics and robustness to the light noise interference caused by the sudden fall of light at night. The above models use density map regression-guided detection method to complete population counting and detection. Results. The model completed daytime training and testing on MICC dataset. Through verification, the average absolute error of the model was 1.025, the mean square error was 1.521, and the recall rate of target detection was 97.11%. Night vision training and testing were completed on the RGBT-CC dataset. After verification, the average absolute error of the network was 18.16, the mean square error was 32.14, and the recall rate of target detection was 97.65%. By verifying the effectiveness of the multimode medium-term fusion network, it is found to exceed the current most advanced bimodal fusion method. Conclusion. The experimental results show that the proposed multimodal fusion network can solve the counting and detection problem in the video surveillance environment during day and night. The ablation experiment further proves the effectiveness of the parameters of the two models.
A Preclinical and Phase Ib Study of Palbociclib plus Nab-Paclitaxel in Patients with Metastatic Adenocarcinoma of the Pancreas
Authors: Hidalgo Manuel , Garcia-Carbonero Rocio , Lim Kian-Huat , Messersmith Wells A. , Garrido-Laguna Ignacio , Borazanci Erkut , Lowy Andrew M. , Medina Rodriguez Laura , Laheru Daniel , Salvador-Barbero Beatriz , Malumbres Marcos , Shields David J. , Grossman Joseph E. , Huang Xin , Tammaro Meggan , Martini Jean-François , Yu Yanke , Kern Kenneth , Macarulla Teresa
Published: September 2022

Purpose:

To assess the preclinical efficacy, clinical safety and efficacy, and MTD of palbociclib plus nab-paclitaxel in patients with advanced pancreatic ductal adenocarcinoma (PDAC).

Experimental Design:

Preclinical activity was tested in patient-derived xenograft (PDX) models of PDAC. In the open-label, phase I clinical study, the dose-escalation cohort received oral palbociclib initially at 75 mg/day (range, 50‒125 mg/day; modified 3+3 design; 3/1 schedule); intravenous nab-paclitaxel was administered weekly for 3 weeks/28-day cycle at 100‒125 mg/m2. The modified dose–regimen cohorts received palbociclib 75 mg/day (3/1 schedule or continuously) plus nab-paclitaxel (biweekly 125 or 100 mg/m2, respectively). The prespecified efficacy threshold was 12-month survival probability of ≥65% at the MTD.

Results:

Palbociclib plus nab-paclitaxel was more effective than gemcitabine plus nab-paclitaxel in three of four PDX models tested; the combination was not inferior to paclitaxel plus gemcitabine. In the clinical trial, 76 patients (80% received prior treatment for advanced disease) were enrolled. Four dose-limiting toxicities were observed [mucositis (n = 1), neutropenia (n = 2), febrile neutropenia (n = 1)]. The MTD was palbociclib 100 mg for 21 of every 28 days and nab-paclitaxel 125 mg/m2 weekly for 3 weeks in a 28-day cycle. Among all patients, the most common all-causality any-grade adverse events were neutropenia (76.3%), asthenia/fatigue (52.6%), nausea (42.1%), and anemia (40.8%). At the MTD (n = 27), the 12-month survival probability was 50% (95% confidence interval, 29.9–67.2).

Conclusions:

This study showed the tolerability and antitumor activity of palbociclib plus nab-paclitaxel treatment in patients with PDAC; however, the prespecified efficacy threshold was not met.

Trial Registration:

Pfizer Inc (NCT02501902)

Significance:

In this article, the combination of palbociclib, a CDK4/6 inhibitor, and nab-paclitaxel in advanced pancreatic cancer evaluates an important drug combination using translational science. In addition, the work presented combines preclinical and clinical data along with pharmacokinetic and pharmacodynamic assessments to find alternative treatments for this patient population.
Dietary Fat Composition Affects Hepatic Angiogenesis and Lymphangiogenesis in Hepatitis C Virus Core Gene Transgenic Mice
Authors: Diao Pan , Wang Yaping , Jia Fangping , Wang Xiaojing , Hu Xiao , Kimura Takefumi , Sato Yoshiko , Moriya Kyoji , Koike Kazuhiko , Nakayama Jun , Tanaka Naoki
Published: September 2022

Introduction: Previous research has demonstrated that an isocaloric diet rich in trans-fatty acid (TFA), saturated fatty acid (SFA), and cholesterol (Chol) promoted steatosis-derived hepatic tumorigenesis in hepatitis C virus core gene transgenic (HCVcpTg) mice in different manners. Growth factor signaling and ensuing angiogenesis/lymphangiogenesis are key factors in hepatic tumorigenesis that have become recent therapeutic targets for hepatocellular carcinoma. However, the influence of dietary fat composition on these factors remains unclear. This study investigated whether the type of dietary fat would have a specific impact on hepatic angiogenesis/lymphangiogenesis in HCVcpTg mice. Methods: Male HCVcpTg mice were treated with a control diet, an isocaloric diet containing 1.5% cholesterol (Chol diet), or a diet replacing soybean oil with hydrogenated coconut oil (SFA diet) for a period of 15 months or with shortening (TFA diet) for 5 months. The degree of angiogenesis/lymphangiogenesis and the expression of growth factors, including fibroblast growth factor (FGF), vascular endothelial growth factor (VEGF), and platelet-derived growth factor (PDGF), were evaluated in non-tumorous liver tissues using quantitative mRNA measurement, immunoblot analysis, and immunohistochemistry. Results: Long-term feeding of SFA and TFA diets to HCVcpTg mice increased the expressions of vascular endothelial cell indicators, such as CD31 and TEK receptor tyrosine kinase, in addition to lymphatic vessel endothelial hyaluronan receptor 1, indicating that angiogenesis/lymphangiogenesis were upregulated only by these fatty acid-enriched diets. This promoting effect correlated with elevated VEGF-C and FGF receptor 2 and 3 levels in the liver. c-Jun N-terminal kinase (JNK) and hypoxia-inducible factor (HIF) 1α, both key regulators of VEGF-C expression, were enhanced in the SFA- and TFA-rich diet groups as well. The Chol diet significantly increased the expressions of such growth factors as FGF2 and PDGF subunit B, without any detectable impact on angiogenesis/lymphangiogenesis. Conclusion: This study revealed that diets rich in SFA and TFA, but not Chol, might stimulate hepatic angiogenesis/lymphangiogenesis mainly through the JNK-HIF1α-VEGF-C axis. Our observations indicate the importance of dietary fat species for preventing hepatic tumorigenesis.
A Rare Dichorionic Triamniotic Triplet Pregnancy with Spontaneous Twin Anemia-Polycythemia Sequence between Two Dichorionic Fetuses
Authors: Jørgensen Ditte S. , Nørgaard Lone N. , Ekelund Charlotte K. , Jensen Lisa Neerup , Sundberg Karin
Published: September 2022

Introduction: This report presents a rare case of spontaneous twin anemia-polycythemia sequence (TAPS) between two dichorionic fetuses in a spontaneous, homozygotic, dichorionic, triamniotic, triplet pregnancy treated with multiple intrauterine blood transfusions (IUTs) and partial exchange transfusions (PETs). Case Presentation: The pregnancy was diagnosed with stage IV TAPS at gestational week 25+1. The patient was treated with laser surgery combined with multiple IUTs and PETs. The triplets were delivered at a planned caesarean section at gestational week 28+1 with postnatal hemoglobin values of 18.21, 26.43, and 11.92 g/dL in triplet 1, 2, and 3, respectively. At 4 years of age, triplet 1 is considered healthy, triplet 2 is diagnosed with mild mental retardation, and triplet 3 with profound mental retardation and dystonic cerebral palsy. Discussion: This is an extremely rare case of TAPS between dichorionic fetuses in a triplet pregnancy, and routine surveillance with measurement of middle cerebral artery peak systolic velocity in dichorionic pregnancies may contribute to the detection of similar cases in the future. Furthermore, this case contributes with rare long-term follow-up data of children treated for high-stage TAPS with multiple IUTs and PETs.
Toward Network Intelligence
Authors: Pentland Alex
Published: September 2022

This article proposes a conceptual framework to guide research in neural computation by relating it to mathematical progress in other fields and to examples illustrative of biological networks. The goal is to provide insight into how biological networks, and possibly large artificial networks such as foundation models, transition from analog computation to an analog approximation of symbolic computation. From the mathematical perspective, I focus on the development of consistent symbolic representations and optimal policies for action selection within network settings. From the biological perspective, I give examples of human and animal social network behavior that may be described using these mathematical models.
Capacity Limitations of Visual Search in Deep Convolutional Neural Networks
Authors: Põder Endel
Published: September 2022

Deep convolutional neural networks (CNN) follow roughly the architecture of biological visual systems and have shown a performance comparable to human observers in object classification tasks. In this study, three deep neural networks pretrained for image classification were tested in visual search for simple features and for feature configurations. The results reveal a qualitative difference from human performance. It appears that there is no clear difference between searches for simple features that pop out in experiments with humans and for feature configurations that exhibit strict capacity limitations in human vision. Both types of stimuli reveal comparable capacity limitations in the neural networks tested here.
Rwandan Perceptions of Jews, Judaism, and Israel
Authors: Beloff Jonathan R.
Published: September 2022

Religious studies of Rwanda typically focus on Christi26662531anity’s involvement before, during, and after the 1994 Genocide against the Tutsi, also referred to as the Rwandan Genocide. Rwanda’s postgenocide reconstruction has witnessed new and changing political and social commitments by previously established religious organisations such as the Roman Catholic, Protestant, and Adventist Churches. The Rwandan government has taken a more progressive stance on divisions of power and religious institutions, and the promotion of religious freedoms that has benefitted the domestic Muslim population. This essay examines how Judaism, a previously unknown religion in the region, is impacting Rwandan identity formation. Jewish identity is increasingly being tied to the nation’s own reconstructed identity, with a strong focus on historical persecution, rebuilding after genocide, and development. This essay suggests that Rwandan identity and religious studies should include the ever-growing ties with Jews and Israel to better understand its political and social reconstruction since 1994.
‘Wash and Pray’
Authors: Muyambo Tenson , Sande Nomatter , Tendere Jane
Published: September 2022

‘Continue to wash your hands, continue to wear your mask, continue to sanitize, continue to maintain social distance, and lastly continue to pray’. These were the closing remarks of a pastor who was preaching online to his congregants in the context of the second and third waves of COVID-19 variants. This article focuses on the church’s utilisation (or lack) of both religion and science under the ‘wash’ and ‘pray’ theology. The article raises this fundamental question: to what extent is the church embracing scientific knowledge in its efforts to deal with COVID-19? Data was collected through an online questionnaire survey, review of available literature, listening to clerics on YouTube, follow-up WhatsApp interviews, as well as overt and covert observations. The article argues that religion and science differ on a number of issues but in the context of COVID-19 and as indicated by this study, they must learn from each other and pool resources to combat COVID-19. COVID-19 calls for undivided attention, and when religion and science unify humanity vastly benefit. The article adds to the continuous debate on the relationship between science (wash) and religion (pray), arguing for the significance of religious ideas that make science effective in addressing the pandemic and vice versa.