bluuebunny/crossref_metadata_2025 huggingface dataset:
Short-Term Creatine Supplementation and Repeated Sprint Ability—A Systematic Review and Meta-Analysis
Authors: Glaister Mark , Rhodes Lauren
Published: August 2022

The aim of this study was to conduct a systematic review and meta-analysis of the effects of short-term creatine supplementation on repeated sprint ability. Fourteen studies met the inclusion criteria of adopting double-blind randomized placebo-controlled designs in which participants (age: 18–60 years) completed a repeated sprint test (number of sprints: 4 < n ≤ 20; sprint duration: ≤10 s; recovery duration: ≤90 s) before and after supplementing with creatine or placebo for 3–7 days in a dose of ∼20 g/day. No exclusion restrictions were placed on the mode of exercise. Meta-analyses were completed using random-effects models, with effects on measures of peak power output, mean power output, and fatigue (performance decline) during each repeated sprint test presented as standardized mean difference (δ), and with effects on body mass and posttest blood lactate concentration presented as raw mean difference (D). Relative to placebo, creatine resulted in a significant increase in body mass (D = 0.79 kg; p < .00001) and mean power output (δ = 0.61; p = .002). However, there was no effect of creatine on measures of peak power (δ = 0.41; p = .10), fatigue (δ = 0.08; p = .61), or posttest blood lactate concentration (D = 0.22 L/min; p = .60). In conclusion, creatine supplementation may increase mean power output during repeated sprint tests, although the absence of corresponding effects on peak power and fatigue means that more research, with measurements of intramuscular creatine content, is necessary to confirm.
Font-Romeu (1964–1972): A Review of the Social Conditions Behind the Creation of an “International” Sports Center
Authors: Fleuriel Sébastien , Papin Bruno , Viaud Baptiste
Published: August 2022

In the mid-1960s, how did a small French mountain village become a high performance international Olympic training center? This article intends to answer this question by examining the social conditions behind the center’s creation. The sporting and political context of the Olympic Games in Tokyo (1964) and Mexico (1968) proved fertile ground for the rationalization of sports through stabilizing a medical and sporting administration and implementing a stronger scientific framework. From this perspective, the medicalization of athletic performance in the 1960s played a central role in the conversion of Font-Romeu, transformed from an acclimatization station in the early 1960s into a renowned international altitude training center just a few years later. The article will take a comprehensive look at the construction and management of such a center, and how it became a game changer in the international movement of sportspersons and sports-related personnel the world over.
Treponema denticola Induces Interleukin-36γ Expression in Human Oral Gingival Keratinocytes via the Parallel Activation of NF-κB and Mitogen-Activated Protein Kinase Pathways
Authors: Hinson Annie N. , Hawkes Colin G. , Blake Christopher S. , Fitzsimonds Zackary R. , Zhu Bin , Buck Gregory , Lamont Richard J. , Miller Daniel P.
Published: August 2022

The oral epithelial barrier acts as both a physical barrier to the abundant oral microbiome and a sentry for the immune system that, in health, constrains the accumulation of the polymicrobial plaque biofilm. The immune homeostasis during gingivitis that is largely protective becomes dysregulated, unproductive, and destructive to gingival tissue as periodontal disease progresses to periodontitis.
Specific and Sensitive Diagnosis of Babesia microti Active Infection Using Monoclonal Antibodies to the Immunodominant Antigen BmGPI12
Authors: Gagnon Jacqueline , Timalsina Sushma , Choi Jae-Yeon , Chand Meenal , Singh Pallavi , Lamba Pooja , Gaur Gauri , Pal Anasuya C. , Mootien Sara , Marcos Luis A. , Ben Mamoun Choukri , Ledizet Michel
Published: August 2022

The apicomplexan pathogen
Babesia microti
is responsible for most cases of human babesiosis worldwide. The disease, which presents as a malaria-like illness, is potentially fatal in immunocompromised or elderly patients, making the need for its accurate and early diagnosis an urgent public health concern.
B. microti
is transmitted primarily by
Ixodes
ticks but can also be transmitted via blood transfusion.
A Comparison of Online and In-Person Evolution Instruction That Includes Religious Cultural Competence
Authors: Bowen Chloe D. , Summersill Alexa R. , Jensen Jamie L. , Brownell Sara E. , Barnes M. Elizabeth
Published: August 2022

Evolution is one of the most important concepts in biology, but it is rejected by a substantial percentage of religious students due to a perceived conflict with their religious beliefs. The use of religious cultural competence in evolution education (ReCCEE) has been shown to effectively increase evolution acceptance among religious students during in-person instruction, but there is no research that we know of that indicates the effectiveness of these practices during online instruction.
Bcr4 Is a Chaperone for the Inner Rod Protein in the
Bordetella
Type III Secretion System
Authors: Goto Masataka , Abe Akio , Hanawa Tomoko , Suzuki Masato , Kuwae Asaomi
Published: August 2022

The type III secretion system (T3SS) is a needle-like complex that projects outward from bacterial cells.
Bordetella bronchiseptica
uses the T3SS to inject virulence proteins into host cells. Our previous study reported that a protein named Bcr4 is essential for the secretion of virulence proteins from
B. bronchiseptica
bacterial cells and delivery through the T3SS.
Loss of seryl-tRNA synthetase (SARS1) causes complex spastic paraplegia and cellular senescence
Authors: Verdura Edgard , Senger Bruno , Raspall-Chaure Miquel , Schlüter Agatha , Launay Nathalie , Ruiz Montserrat , Casasnovas Carlos , Rodriguez-Palmero Agustí , Macaya Alfons , Becker Hubert Dominique , Pujol Aurora
Published: August 2022

Background

Aminoacyl-tRNA synthetases (ARS) are key enzymes catalysing the first reactions in protein synthesis, with increasingly recognised pleiotropic roles in tumourgenesis, angiogenesis, immune response and lifespan. Germline mutations in several ARS genes have been associated with both recessive and dominant neurological diseases. Recently, patients affected with microcephaly, intellectual disability and ataxia harbouring biallelic variants in the seryl-tRNA synthetase encoded by seryl-tRNA synthetase 1 (SARS1) were reported.

Methods

We used exome sequencing to identify the causal variant in a patient affected by complex spastic paraplegia with ataxia, intellectual disability, developmental delay and seizures, but without microcephaly. Complementation and serylation assays using patient’s fibroblasts and anSaccharomyces cerevisiaemodel were performed to examine this variant’s pathogenicity.

Results

Ade novosplice site deletion inSARS1was identified in our patient, resulting in a 5-amino acid in-frame insertion near its active site. Complementation assays inS. cerevisiaeand serylation assays in both yeast strains and patient fibroblasts proved a loss-of-function, dominant negative effect. Fibroblasts showed an abnormal cell shape, arrested division and increased beta-galactosidase staining along with a senescence-associated secretory phenotype (raised interleukin-6, p21, p16 and p53 levels).

Conclusion

We refine the phenotypic spectrum and modes of inheritance of a newly described, ultrarare neurodevelopmental disorder, while unveiling the role of SARS1 as a regulator of cell growth, division and senescence.
How to become a successful scientist: the 2022 CSMB Arthur Wynne Gold Medal Lecture
Authors: Reithmeier Reinhart A.F.
Published: August 2022

There are many pathways to success. Mine followed a traditional one to an academic faculty position, but this pathway is not the one most life sciences PhD graduates will follow today. We have all had time during the COVID-19 pandemic to reflect on our personal pathway—where we are and where we are going. In this reflection, I outline five steps on my pathway to success:

Train with the best. Discover something. Mentor others. Go beyond. Promote science.

I will provide examples from my personal journey that I hope will resonate with the reader as they create their pathway to success.
Computational study on the interactions of functionalized C24NC (NC=C, –OH, –NH2, –COOH, and B) with chloroethylphenylbutanoic acid
Authors: Inah Bassey E. , Louis Hitler , Benjamin Innocent , Unimuke Tomsmith O. , Adeyinka Adedapo S.
Published: August 2022

Computational chemistry approach based on density functional theory (DFT) was utilized to investigate the interaction, adsorption behaviour, electronic and structural properties of nanostructured complexes formed by 4-(4-(bis(2-chloroethyl)amino)phenyl)butanoic acid (CPB) and all carbon fullerene nanocage, (C24NC), boron functionalized carbon nanocage (C24NC@B@CPB), carboxylate functionalized (C24NC@COOH@CPB), amino functionalized (C24NC@NH2@CPB), and hydroxy functionalized (C24NC@OH@CPB) nanostructured materials. To understand effectively the interaction of the drug and surface, topological analysis was conducted via the atoms in molecule (quantum theory of atoms in molecules) and noncovalent interaction approach. Electronic properties such as quantum chemical descriptors, natural bond orbital and nonlinear optics are equally considered and reported. All computations were achieved at the B3LYP-D3 and ωB97XD levels of theory with the 6-311++G(d, p) basis set. The results indicate that the adsorption energy of CPB on C24NC and its functionalized derivatives are in the range of −0.52 to 2.89 eV indicating that physisorption and chemisorption mechanism are prevalent mechanisms of adsorption. C23B@CPB, C24OH@CPB, and C24NH2@CPB were observed to possess the best characteristics to be considered as transport vehicles for CPB due to their strong adsorption nature (chemisorption) and solubility in solution.
Research on the coupling characteristics of energy power density of cutting vibration and cutting heat based on the particle swarm optimization algorithm
Authors: Li Songyuan , Li Shuncai , Li Yuqing , Vladimirovich Petrov Anton
Published: August 2022

Cutting heat and cutting vibration are important basic research topics in the field of machining. Many factors affect cutting heat and cutting vibration, and cutting heat and cutting vibration also affect each other. This paper mainly studied the coupling characteristics between cutting vibration and cutting heat from the perspective of energy power density. A measurement system was built to collect the time-domain signals of cutting temperature and three-dimensional cutting vibration. Through Stefan–Boltzmann's law, the cutting thermal power density represented by the cutting temperature was obtained. Frequency domain analysis dealing with the self-power spectrum density was carried out on the three-dimensional vibration acceleration, and the operation of reducing the vibration dimension was carried out by principal component analysis. Based on the particle swarm optimization algorithm, two coupling models between cutting heat and cutting vibration were established. The research showed that the coupling correlation coefficient between cutting heat and cutting vibration was above 0.6. The coupling characteristics of cutting heat and cutting vibration were strong, and the impact of cutting vibration on cutting heat was more significant. The conclusions provide theoretical guidance for studying the coupling characteristics of cutting heat and cutting vibration from the energy perspective.
Improving the Quality of Service (QoS) and Resource Allocation in Vehicular Platoon Using Meta-Heuristic Optimization Algorithm
Authors: Priya R. , Sivakumar N.
Published: August 2022

The concept of vehicular platooning is emerging due to its self-driving capability, whereas a set of cars are arranged closely and that can drive safely even in high speed. Moreover the communication can also takes place between two platoons and hence the platoon leader can control the speed and direction. Traffic difficulties, like as collisions and delay at road junctions, need the use of platoon mechanisms. The most efficient vehicle traffic management in platoons is acknowledged in Intelligent Transportation System (ITS) for improving energy efficiency, road capacity, and road safety. Essentially, it is critical to analyse the connection characteristic of any two platoons in order to improve connectivity. As a result, under bi-directional platoon architecture, the possibility of connectivity between platoon members and Road Side Units (RSUs) is generated. Providing Quality of Service (QoS) to automotive network is difficult issue because elements such as asynchronous transmission or high mobility, crowded and fragmented channels, hardware defects, and various vehicular gadgets. As a result, it is extremely desired to utilize and distribute resources efficiently. Despite the existence of other bio-inspired meta-heuristic optimization methods, the Bacterial Foraging Algorithm has the benefit of simplicity and efficiency, and so may be used to a wide range of engineering applications. However, in the event of sophisticated analysis, the constraint is a lower convergence rate. To improve resource allocation, this study employs the Improved Bacterial Foraging Optimization based Channel Allocation (IBFOCA) technique. Set of channels allocated to platoon members are signified as bacteria’s position. By using latency, Signal-to-Interference Ratio (SINR) and Quality of Service (QoS), available channel is initially determined. This approach is used to find a channel that is acceptable for platoon members. Simulation results are used to examine the presentation of multi-channel distributions in platoons utilizing suggested optimization strategy. Signal-to-interference ratio is lowered by 29 decibel, throughput is raised by 69 kilobits per second, collision probability is reduced by 21.4 percent, and average batch size is 57 percent with a delay of 49 milliseconds.
DEFUSE: An Interface for Fast and Correct User Space File System Access
Authors: Lembke James , Roman Pierre-Louis , Eugster Patrick
Published: August 2022

Traditionally, the only option for developers was to implement file systems (FSs) via drivers within the operating system kernel. However, there exists a growing number of file systems (FSs), notably distributed FSs for the cloud, whose interfaces are implemented solely in user space to (i) isolate FS logic, (ii) take advantage of user space libraries, and/or (iii) for rapid FS prototyping. Common interfaces for implementing FSs in user space exist, but they do not guarantee POSIX compliance in all cases, or suffer from considerable performance penalties due to high amounts of wait context switchs between kernel and user space processes.

We propose DEFUSE: an interface for user space FSs that provides fast accesses while ensuring access correctness and requiring no modifications to applications. DEFUSE: achieves significant performance improvements over existing user space FS interfaces thanks to its novel design that drastically reduces the number of wait context switchs for FS accesses. Additionally, to ensure access correctness, DEFUSE: maintains POSIX compliance for FS accesses thanks to three novel concepts of
bypassed file descriptor (FD) lookup
,
FD stashing
, and
user space paging
. Our evaluation spanning a variety of workloads shows that by reducing the number of wait context switchs per workload from as many as 16,000 or 41,000 with filesystem in user space down to 9 on average, DEFUSE: increases performance 2× over existing interfaces for typical workloads and by as many as 10× in certain instances.
WebAssembly-based Delta Sync for Cloud Storage Services
Authors: Zheng Jianwei , Li Zhenhua , Qiu Yuanhui , Lin Hao , Xiao He , Li Yang , Liu Yunhao
Published: August 2022

Delta synchronization (sync) is crucial to the network-level efficiency of cloud storage services, especially when handling large files with small increments. Practical delta sync techniques are, however, only available for PC clients and mobile apps, but not web browsers—the most pervasive and OS-independent access method. To bridge this gap, prior work concentrates on either reversing the delta sync protocol or utilizing the native client, all striving around the tradeoffs among efficiency, applicability, and usability
and thus
forming an “impossible triangle.” Recently, we note the advent of WebAssembly
(WASM)
, a portable binary instruction format that is efficient in both encoding size and load time.
In principle,
the unique advantages of WASM
can
make web-based applications enjoy near-native runtime speed without significant cloud-side or client-side changes. Thus, we implement a straightforward WASM-based delta sync solution, WASMrsync, finding its quasi-asynchronous working manner and conventional In-situ Separate Memory Allocation greatly increase sync time and memory usage. To address them, we strategically devise sync-async code decoupling and streaming compilation, together with Informed In-place File Construction. The resulting solution, WASMrsync+, achieves comparable sync time as the state-of-the-art (most efficient) solution with nearly only half of memory usage,
letting
the “impossible triangle” reach a reconciliation.
Generative Datalog with Continuous Distributions
Authors: Grohe Martin , Kaminski Benjamin Lucien , Katoen Joost-pieter , Lindner Peter
Published: August 2022

Arguing for the need to combine declarative and probabilistic programming, Bárány et al. (TODS 2017) recently introduced a probabilistic extension of Datalog as a “purely declarative probabilistic programming language.” We revisit this language and propose a more principled approach towards defining its semantics based on stochastic kernels and Markov processes—standard notions from probability theory. This allows us to extend the semantics to continuous probability distributions, thereby settling an open problem posed by Bárány et al.

We show that our semantics is fairly robust, allowing both parallel execution and arbitrary chase orders when evaluating a program. We cast our semantics in the framework of infinite probabilistic databases (Grohe and Lindner, LMCS 2022) and show that the semantics remains meaningful even when the input of a probabilistic Datalog program is an arbitrary probabilistic database.
Effect of Toll-like receptor-2, -4, -5, -7, and NOD2 stimulation on potassium channel conductance in intestinal epithelial cells
Authors: Cosme Dina , Soares-da-Silva Patrício , Magro Fernando
Published: August 2022

This study highlights that PRRs stimulation directly influences K+-channel conductance in IECs. TLR-2, -4, -7 stimulation decreased K+ conductance, whereas TLR5 and NOD2 stimulation had the opposite effect, leading to an increase of it instead. This study reports for the first time that KCa3.1- and Kir6-channels play a role in K+ transport pathways triggered by TLR4 stimulation. These findings suggest that KCa3.1- and Kir6-channels modulation may be a potential target for new therapeutic agents in IBD.
Acute vaping in a golden Syrian hamster causes inflammatory response transcriptomic changes
Authors: Hinds Daniel M. , Nick Heidi J. , Vallin Tessa M. , Bloomquist Leslie A. , Christeson Sarah , Bratcher Preston E. , Cooper Emily H. , Brinton John T. , Bosco-Lauth Angela , White Carl W.
Published: August 2022

E-cigarette vaping is a major aspect of nicotine consumption, especially for children and young adults. Although it is branded as a safer alternative to cigarette smoking, murine and rat models of subacute and chronic e-cigarette vaping exposure have shown many proinflammatory changes in the respiratory tract. An acute vaping exposure paradigm has not been demonstrated in the golden Syrian hamster, and the hamster is a readily available small animal model that has the unique benefit of becoming infected with and transmitting respiratory viruses, including SARS-CoV-2, without genetic alteration of the animal or virus. Using a 2-day, whole body vaping exposure protocol in male golden Syrian hamsters, we evaluated serum cotinine, bronchoalveolar lavage cells, lung, and nasal histopathology, and gene expression in the nasopharynx and lung through reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Depending on the presence of nonnormality or outliers, statistical analysis was performed by ANOVA or Kruskal–Wallis tests. For tests that were statistically significant ( P < 0.05), post hoc Tukey–Kramer and Dunn’s tests, respectively, were performed to make pairwise comparisons between groups. In nasal tissue, RT-qPCR analysis revealed nicotine-dependent increases in gene expression associated with type 1 inflammation ( CCL-5 and CXCL-10), fibrosis [transforming growth factor-β ( TGF-β)], nicotine-independent increase oxidative stress response ( SOD-2), and a nicotine-independent decrease in vasculogenesis/angiogenesis (VEGF-A). In the lung, nicotine-dependent increases in the expression of genes involved in the renin-angiotensin pathway [angiotensin-converting enzyme ( ACE), ACE2], coagulation ( tissue factor, Serpine-1), extracellular matrix remodeling ( MMP-2, MMP-9), type 1 inflammation ( IL-1β, TNF-α, and CXCL-10), fibrosis ( TGF-β and Serpine-1), oxidative stress response ( SOD-2), neutrophil extracellular traps release ( ELANE), and vasculogenesis and angiogenesis ( VEGF-A) were identified. To our knowledge, this is the first demonstration that the Syrian hamster is a viable model of e-cigarette vaping. In addition, this is the first report that e-cigarette vaping with nicotine can increase tissue factor gene expression in the lung. Our results show that even an acute exposure to e-cigarette vaping causes significant upregulation of mRNAs in the respiratory tract from pathways involving the renin-angiotensin system, coagulation, extracellular matrix remodeling, type 1 inflammation, fibrosis, oxidative stress response, neutrophil extracellular trap release (NETosis), vasculogenesis, and angiogenesis.
Application of IoT-Based Drones in Precision Agriculture for Pest Control
Authors: Refaai Mohamad Reda. A. , Dattu Vinjamuri SNCH , Gireesh N. , Dixit Ekta , Sandeep CH. , Christopher David
Published: August 2022

Unmanned aerial vehicles (UAVs), commonly known as drones, have been progressively prevalent due to their capability to operate quickly and their vast range of applications in a variety of real-world circumstances. The utilization of UAVs in precision farming has lately gained a lot of attention from the scientific community. This study addresses with the assistance of drones in the precision agricultural area. This paper makes significant contributions by analyzing communication protocols and applying them to the challenge of commanding a fleet of drones to protect crops from parasite infestations. In this research, the effectiveness of nine powerful deep neural network models is measured for the detection of plant diseases using diverse methodologies. These deep neural networks are adapted to the immediate situation using transfer learning and deep extraction of features approaches. The presented study takes into account the used pretrained deep learning model for extracting features and fine-tuning. The deep feature extraction characteristics are subsequently categorized using support vector machines (SVMs) and extreme learning machines (ELMs). For measuring performance, the precision, sensitivities, specific, and F1-score are all evaluated. Deep feature extraction and SVM/ELM classification generated better outcomes than transfer learning, according to the analysis result. Furthermore, the analysis of the various methodologies tries to assess their effectiveness and costs. The different approaches, for example, confront difficulties such as investigating the region in the shortest possible time feasible, while eliminating the same region being searched by more drones, detecting parasites, and stopping their spread by applying the appropriate number of pesticides. Simulation models are a significant aid to researchers in conducting to evaluate these technologies and creating specific tactics and coordinating procedures capable of effectively supporting farms and achieving the aim. The main objective of this paper is to compare the search techniques of two distinct methods of parasitic to identify performance.
Application of Big Data Technology in Environmental Pollution Control in Energy Ecological Economic Zone
Authors: Jin Xinxue , Jin Xinxin
Published: August 2022

In order to solve the problem of environmental pollution control in the energy ecological economic zone, this paper proposes a technology to realize environmental pollution control by using big data. The main content of this technology is based on the characteristics and application of big data technology; through the collection of online monitoring data of ecological environment pollution, the construction of the online monitoring data quality model of ecological environment pollution, and finally through the experiments in the simulation environment, the feasibility of big data technology is obtained. The experimental results show that the average quality factor data of the quality control model in the environmental scientific data supervision is 2.16, the average quality factor data of the Internet of things in the marine pollution monitoring is 5.88, and the average quality factor data of the model in the ecological environment pollution online monitoring based on the big data technology is 8.64. Big data technology has good applicability. It is proven that the research of big data technology can meet the needs of environmental pollution control in the energy ecological economic zone.
A Self-Adaptive Recommendation Method for Online Ideological and Political Teaching Resources Based on Deep Reinforcement Learning
Authors: Jin Ying
Published: August 2022

The online ideological as well as the political teaching resource management system structure is established in the view of information management in colleges and universities. Furthermore, the online ideological as well as the political teaching information level is improved by combining the optimized design of resource recommendation model. In this paper, an online ideological as well as political teaching resource adaptive recommendation system and algorithm, which is designed on deep reinforcement learning, is suggested. The cost relationship model between online ideological as well as the political teaching resources and learning profitability is constructed. Similarly, the multidimensional constraint index parameter analysis method is adopted, and the adaptive matching model of online ideological as well as the political teaching resources is established. According to online ideological as well as the political teaching norms, combined with the analysis of high-quality educational resources of audience groups, the dynamic evaluation of online ideological as well as the political teaching resources and the adaptive matching model of interest preferences are established. Finally, the deep reinforcement learning method is adopted. By analyzing the characteristics of the resource structure model of online ideological as well as the political teaching resources, through benefit evaluation, resource supply and demand balance management analysis and balanced game control, the online ideological as well as the political teaching resources management system can be improved and self-adaptive recommended. The simulation outcomes indicate that this approach has noble adaptability and high correctness in recommending online ideological as well as the political teaching resources.
A New Collaborative Filtering Algorithm Integrating Time and Multisimilarity
Authors: Liu Qin
Published: August 2022

Aiming at the problem of low recommendation accuracy of existing recommendation algorithms, an algorithm integrating time factors and multisimilarity is proposed to improve the impact of long-term data, user attention, and project popularity on the recommendation algorithm and the similarity of user attributes is introduced to improve the problem of cold start to a certain extent. Considering that the longer the time, the less likely it is to be selected again, time is introduced into the algorithm as a weight factor. When the behavior occurs, i.e., interest in the project, so as to judge the similarity between users, not just the score value, we normalize the popularity to avoid misjudgment of high scoring and popular items. Because new users do not have past score records, the problem of cold start can be solved by calculating the similarity of user attributes. Through the comparative experiment on Movielens100K dataset and Epinions dataset, the results show that the algorithm can improve the accuracy of recommendation and give users a better recommendation effect.
Multiobjective Optimization of Vehicle Handling and Stability Based on ADAMS
Authors: Zhang Genge , Wei Yi , Ju Chengwei , He Shuilong
Published: August 2022

In order to improve the steering characteristics, roll characteristics, and lateral characteristics of heavy commercial vehicles, a multiobjective handling stability comprehensive score optimization model (MHSCS optimization model) was proposed in this study. In this study, the main factors affecting the steering characteristics, roll characteristics, and lateral characteristics are determined by combining the road test method and ADAMS software simulation analysis method. Based on the above road tests and ADAMS software simulation analysis, the MHSCS optimization model was proposed with “understeering degree,” “vehicle roll angle”, and “rearward amplification (RWA)” as evaluation indexes, and the response surface method combined with genetic algorithm was used to carry out multiobjective optimization of heavy commercial vehicle. ADAMS simulation results show that the comprehensive improvement degree of steering characteristics, roll characteristics, and lateral characteristics of a heavy commercial vehicle after optimization is 15.26%. Finally, the field road test results show that the scoring error between the comprehensive scoring optimization model and the real vehicle test was controlled at 0.4%, which proves the accuracy of the optimization model established in this study and effectively improves the handling stability of heavy commercial vehicles.
Key Information Extraction Algorithm of Different Types of Digital Archives for Cultural Operation and Management
Authors: Ma Xiulun
Published: August 2022

In order to improve the effect of key information extraction from digital archives, a key information extraction algorithm for different types of digital archives is designed. Preprocess digital archive information, taking part of speech and marks as key information. Self-organizing feature mapping network is used to extract the key information features of digital archives, and the semantic similarity calculation results are obtained by combining the feature extraction results. Combine with mutual information collection, take that word with the highest mutual information value as the collection cent, traverse all keywords, and take the central word as the key information of digital archives to complete the extraction of key information. Experiments show that the recall rate of the algorithm ranges from 96% to 99%, the extraction accuracy of key information of digital archives is between 96 and 98%, and the average extraction time of key information of digital archives is 0.63 s. The practical application effect is good.
Classification of Artistic Styles of Chinese Art Paintings Based on the CNN Model
Authors: Chen Bingquan
Published: August 2022

People’s appreciation needs of Chinese paintings have gradually increased. The research on automatic classification and recognition of Chinese painting artistic style and its authors have great practical value. This study presents a Chinese painting classification algorithm with higher classification accuracy and better robustness. Using a convolutional neural network (CNN) to extract the features of Chinese painting, the image features of Chinese painting are extracted by fine-tuning the pretrained VGG-F model. The mutual information theory is introduced into embedded machine learning, so that the embedded principle is affected by feature selection and feature importance. An embedded classification algorithm based on mutual information is proposed, and Chinese painting is classified.
Network Intelligent Education System Based on the Deep Learning Algorithm
Authors: Li Zhiwei
Published: August 2022

In order to promote the deep integration of education and artificial intelligence and promote the landing of artificial intelligence in the field of education, a method based on deep learning is proposed. Deep learning is a very advanced pattern recognition algorithm, and it can mine potentially valuable knowledge from massive data and provide support for people’s scientific decision-making. Experimental data show that the classification accuracy of deep learning algorithm reaches 99.5%. Even in the case of large data volume and large data categories, the accuracy is still up to 96.3%, which is far higher than the support vector machine algorithm, Bayesian theory algorithm, and K-means algorithm, which can mine and learn knowledge for users more accurately. Conclusion. The network intelligent education system based on deep learning strengthens the automation, intelligence, and interest of learning, so as to ensure the initiative of users in learning.
Light Weight Deep Learning Algorithm for Voice Call Quality of Services (Qos) in Cellular Communication
Authors: Ramalingam Mritha , Sultanuddin S. J. , Nithya N. , Michael Raj T. F. , Rajesh Kumar T. , Suji Prasad S. J. , Al-Ammar Essam A. , Siddique M. H. , Udayakumar Sridhar
Published: August 2022

In this paper, a deep learning algorithm was proposed to ensure the voice call quality of the cellular communication networks. This proposed model was consecutively monitoring the voice data packets and ensuring the proper message between the transmitter and receiver. The phone sends its unique identification code to the station. The telephone and station maintain a constant radio connection and exchange packets from time to time. The phone can communicate with the station via analog protocol (NMT-450) or digital (DAMPS, GSM). Cellular networks may have base stations of different standards, which allow you to improve network performance and improve its coverage. Cellular networks are different operators connected to each other, as well as a fixed telephone network that allows subscribers of one operator to another to make calls from mobile phones to landlines and from landlines to mobiles. The simulation is conducted in Matlab against different performance metrics, that is, related to the quality of service metric. The results of the simulation show that the proposed method has a higher QoS rate than the existing method over an average of 97.35%.
Spontaneous Retroperitoneal Bleeding as a Complication of Unusual Renal Paraganglioma
Authors: Sangey Tawfeeq I. , Abdul Rusheke Hamim , Sangey Ansaar I. , Chaya Nimishkumar , Ngaiza Advera
Published: August 2022

Spontaneous retroperitoneal bleeding is a rare occurrence that might have catastrophic implications. We present a 58-year-old male with a 4-day history of progressively worsening left-sided flank pain due to retroperitoneal hemorrhage from a nonfunctional renal paraganglioma. Abdominal contrast CT scan was helpful in locating the tumor, estimating tumor size and extent of bleeding, visualizing the interaction between the tumor and the surroundings, and ruling out any potential metastasis; however, it lacked specificity in identifying the origin of the mass, needing histologic investigation for a conclusive diagnosis. MRI was not available at our center. We report a rare case of spontaneous retroperitoneal bleeding as a complication of an unusual nonfunctional renal paraganglioma, which was initially misdiagnosed as renal cell carcinoma but later confirmed by postoperative histopathology.
English Teaching Ability Evaluation Algorithm Based on Random Matrix Model and Fuzzy K-Means Clustering
Authors: Shen Yueying , Wu Jingfang
Published: August 2022

This paper proposes a nonelliptic extended English teaching ability evaluation algorithm based on an adaptive random matrix model. The algorithm models a nonelliptical expansion target as multiple elliptical sub-objectives, and the expansion state of each sub-target is described by an inverse Wishart distribution. The new method is combined to improve the robustness problem caused by the initialization after the algorithm expansion. This research uses the smart teacher education platform to conduct research and analysis on the evaluation of teaching practice ability of intern normal students. From the perspective of data evaluation, we explore the influence of normal students’ curriculum training on the teaching practice ability of normal students. By analyzing the correlation between normal students’ course grades and practice grades, this paper explores the influence of normal students’ prepractice training on normal students’ teaching practice ability. This paper explores the influence of the training of normal students’ course learning on the teaching practice ability of normal students. The results show that the learning level of normal students’ professional courses has a significant impact on the development of normal students’ practice performance and teaching practice ability; the impact of normal students’ pedagogical course level on normal students’ practice performance and teaching practice ability is relatively low.
Application of MRI in the Prevention of Sports Injuries in Physical Education Teaching
Authors: Zhao Jing
Published: August 2022

In order to explore the situation of ankle sports injury in physical education, the author proposed the application method of MRI in sports injury prevention in physical education. In a retrospective analysis of 28 patients with clinically diagnosed ankle injuries, taking ankle arthroscopy/incision as the standard, the sensitivity and diagnostic value of MRI examination for ankle sports injury were analyzed statistically. The result shows that 6 cases of ankle fracture were correctly diagnosed by MRI, and the diagnostic sensitivity for bone marrow contusion and edema was 100%. Among the 19 cases of clinically diagnosed ankle ligament injury, 16 cases were diagnosed by MRI, and the overall sensitivity was 84%. Of the 8 cases of calcaneofibular ligament injury, 6 cases were correctly diagnosed by MRI, with a sensitivity of 75%. Conclusion. 3.0 T MRI examination has high sensitivity for ligament, tendon, and cartilage injury, which can well show ankle joint injury and provide an objective basis for early clinical treatment and rehabilitation.
Using Real-Time fMRI Neurofeedback to Modulate M1-Cerebellum Connectivity
Authors: Madkhali Yahia , Al-Wasity Salim , Aldehmi Norah , Pollick Frank
Published: August 2022

Objective. The potential of neurofeedback to alter the M1-cerebellum connectivity was explored using motor imagery-based rt-fMRI. These regions were chosen due to their importance in motor performance and motor rehabilitation. Methods. Four right-handed individuals were recruited to examine the potential to change the M1-cerebellum neurofeedback link. The University of Glasgow Cognitive Neuroimaging Centre used a 3T MRI scanner from January 2019 to January 2020 to conduct this prospective study. Everyone participated in each fMRI session, which included six NF training runs. Participants were instructed to imagine complicated hand motions during the NF training to raise a thermometer bar’s height. To contrast the correlation coefficients between the initial and last NF runs, a t-test was performed post hoc. Results. The neurofeedback connection between M1 and the cerebellum was strengthened in each participant. Motor imagery strategy was a significant task in training M1-cerebellum connectivity as participants used it successfully to enhance the activation level between these regions during M1-cerebellum modulation using real-time fMRI. The t-test and linear regression, on the other hand, showed this increase to be insignificant. Conclusion. A novel technique to manipulate M1-cerebellum connectivity was discovered using real-time fMRI NF. This study showed that each participant’s neurofeedback connectivity between M1 and cerebellum was enhanced. This increase, on the other hand, was insignificant statistically. The results showed that the connectivity between both areas increased positively. Through the integration of fMRI and neurofeedback, M1-cerebellum connectivity can be positively affected.
Nutritional and Therapeutic Potential of Soursop
Authors: Afzaal Muhammad , Saeed Farhan , Asghar Aasma , Shah Yasir Abbas , Ikram Ali , Ateeq Huda , Hussain Muzzamal , Ofoedu Chigozie E. , Chacha James S.
Published: August 2022

Soursop (Annona muricata) has been one of the most studied fruits in recent years, owing to its potential medicinal benefits, as evidenced by many studies. Soursop is a tropical and subtropical fruit having great versatility and is quite sensitive to drastic temperature fluctuations. Since soursop contains various phytochemicals, it can be used medicinally to treat a wide range of conditions, including diabetes (by inhibiting the enzymes α-glucosidase and α-amylase), tumor, cancer, oxidative stress, blood pressure, the induction of apoptosis in tumor cells as well as hemorrhagic disease and cholesterol lowering. Due to its significant nutritional profile and therapeutic potential, it can be utilized in the development of nutraceuticals and medicines. Its pulp, seed, and leaf extract are used as functional ingredients in different foods as value-added foods. This review article is intended to characterize fruit development patterns and examines potential maturity indicators in soursop. In addition, it also elaborates on the potential nutritional and active phytochemicals present in this magnificent gift of nature and their possible uses in the food and pharmaceutical industries.
The Relationship between Physical Activity and Academic Achievement in Multimodal Environment Using Computational Analysis
Authors: Li Lingshu , Zhang Li
Published: August 2022

Health has always been recognized as the imperative parameter to excel in any field whether professional or personal. People with sound health having regular habit of physical activities show more potential in their professional and personal lives than the people who do not participate in the physical activities. Many state-of-the-art studies exist in the literature where researchers have proved the significance of physical activities as supportive treatment for the existing ailments and in improving the overall health of human beings. Our research aims at accessing the correlation between physical activities carried out by the students and its impact on the success rate of academic achievements. The study is using computational techniques to investigate the relevance of physical activities on the academic achievements of middle school children. The study employs data mining techniques for processing the data. The computational methods are used in a multimodal environment where the surrounding parameters of the environment are considered before performing computational techniques on the subjects (participants in terms of sample for the study). In this cross-sectional study, we have considered the data on various physical activities such as aerobic fitness, running, playing, and participation in extracurricular activities. After collection of data in a real multimodal environment from middle school students, the data preprocessing is performed to handle the missing values. Then, the computational techniques are applied in a step-by-step approach using regression and the bootstrap methods to examine the data and predict the outcome. The correlation is assessed between academic achievements and physical activities. The outcome predicts that physical activities promote the success rate of academic achievements including extra-curricular activities.
Hypoxia-Induced Nestin Regulates Viability and Metabolism of Lung Cancer by Targeting Transcriptional Factor Nrf2, STAT3, and SOX2
Authors: Liu Yongshi , Zhang Xinglin , Jiang Tao , Du Ning
Published: August 2022

Objective. To investigate hypoxia-induced Nestin regulates lung cancer viability and metabolism by targeting transcription factors Nrf2, STAT3, and SOX2. Methods. Eighty-four cases of nonsmall cell lung cancer (nonsmall cell lung cancer, NSCLC), which had been treated from June 2020 to February 2021, were randomly selected from our clinicopathology database. Immunohistochemical staining of collected tissue cells was performed to assess the expression patterns of Nestin, STAT3, Nrf2, and SOX2. Data were quantified and statistically analyzed using one-way and two-way ANOVA tests with

P
<
0.05

. Results. Clinicopathological findings showed significant differences in lymph node metastasis, tissue differentiation, and histology on induction of Nestin expression; Nestin expression correlated with STAT3, Nrf2, and SOX2 expression.Nestin/STAT3/SOX2/Nrf2 are involved in angiogenesis and lung cancer development. Conclusion. Hypoxia-induced Nestin promotes the progression of nonsmall lung cancer cells by targeting the downstream transcription factors STAT3, Nrf2, and SOX2.
Analysis on the Path of Digital Villages Affecting Rural Residents’ Consumption Upgrade: Based on the Investigation and Research of 164 Administrative Villages in the Pilot Area of Digital Villages in Zhejiang Province
Authors: Zhang Liying , Ma Xingchao
Published: August 2022

The weak consumption of rural residents has become an important factor restricting the healthy development of the Chinese economy. With the continuous development of digital construction in rural areas, its role in the upgrading of rural residents’ consumption is becoming more and more important. Based on the mechanism of 164 administrative villages in the pilot area of Zhejiang Province, and using staggered cluster analysis, MLR analysis, mediation effect model, etc., this paper discusses the impact and transmission mechanism of digital villages on rural residents’ consumption upgrade. The results show that farmers’ wage income, property income, and total income all play a significant positive mediating role in the process of promoting consumption upgrading in digital villages; information literacy is a latent variable in the process of promoting consumption upgrading in digital villages. It also played a significant positive mediating role. The research provides the micromechanism of the digital village affecting the consumption upgrade of rural residents and puts forward to promote the process of infrastructure construction, improve the construction of e-commerce system, pay attention to the differences among residents and other suggestions.