bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Intelligence-Assisted Decision-Making Method for Legal Judgment Based on Deep Neural Network
Authors: Ma Wenqing
Published: October 2022

With the arrival of the third revolution of artificial intelligence, the applications of artificial intelligence in the fields of automatic driving, image recognition, smart home, machine translation, medical services, e-sports, and so on can be seen everywhere, and topics about artificial intelligence are constantly emerging. Since 2017, the discussion on artificial intelligence in the field of law has become more and more active. In this context, the application of artificial intelligence in the field of legal judgment and the hypothetical system based on this technology in court judgment has also become the object of discussion from time to time. In this paper, based on the artificial intelligence decision-making method of the deep neural network, aiming at the three subtasks of legal judgment prediction, namely, crime prediction, law recommendation, and sentence prediction, a multi-task judgment prediction model BERT12multi and a sentence interval prediction model BERT-Text CNN are proposed, which improve the prediction accuracy and adopt the knowledge distillation strategy to compress the model parameters and improve the reasoning speed of the judgment model. Experiments on the CAIL2018 data set show that the performance of the deep neural network model in crime prediction and law recommendation tasks can be significantly improved by adopting the pre training model adaptive training, grouping focus loss, and gradient confrontation training strategies. Using a step-by-step sentence prediction strategy can realize the weight sharing of pre training model and make use of the prediction results of charges and laws in sentence prediction. The recall training-prediction strategy can avoid error accumulation and improve the accuracy of sentence prediction. By integrating the artificial intelligence decision-making method, the case reasoning speed can be greatly improved, the highest compressible model volume can be about 11% of the original one, and the reasoning speed can be increased by about 8 times. At the same time, performance close to that of the deep neural model can be obtained, which is superior to other legal decision prediction models based on word embedding.
The Performance Evaluation Model of Hotel Green Human Resources Based on Internet of Things and Fuzzy Theory
Authors: Shen Linlin
Published: October 2022

The Internet of Things (IoT) is influencing national centers of excellence as well as businesses’ approaches to development and how they generate and exploit opportunities in day-to-day hotel activities. The IoT is revolutionary and will transform how human resources are created and managed, necessitating a fresh and adaptable strategy for human resource development. The promise of the IoT is that each device will have a unique means of identifying itself and will be addressable, allowing any object to be connected. This will present a new difficulty to how green human resource development in hotels is conducted. Besides, environmental protection has emerged as the most pressing problem in world politics. Green problems are widely acknowledged as a fundamental source of development. Due to increased customer awareness, the hotel service sector has advanced in terms of quality of services as green marketing has evolved into a crucial instrument for sustainable business approaches. Green marketing strategies are being implemented by businesses to improve company success. In order to improve the adaptive performance assessment capacity of hotel green human resources, this research proposes a performance evaluation model of hotel green human resources based on the Internet of Things and fuzzy theory. It develops a large data analysis model of hotel green human resource performance by statistically quantitatively assessing the constraint parameters of hotel green human resource performance assessment. It extracts the entropy characteristic amount of hotel green human resource performance big data to make the best choice and assessment of hotel green human resource performance by green hotel maximum economic benefit evaluation and fuzzy decision technique. Furthermore, it builds an expert system analysis model for evaluating the hotel green human resource performance. Adaptive optimization of hotel green human resource performance evaluation is carried out by the fuzzy theory adaptive learning algorithm, and the optimization strategy of the hotel green human supply performance evaluation model is realized by similarity characteristic parameter estimation and fuzzy multidimensional parameter constraint. The simulation results show that the performance evaluation of hotel green human resources with this method has high accuracy and good confidence level, which improves the performance evaluation efficiency of hotel green human resources.
Multisemantic Path Neural Network for Deepfake Detection
Authors: Wu Nan , Jin Xin , Jiang Qian , Wang Puming , Zhang Ya , Yao Shaowen , Zhou Wei
Published: October 2022

With the continuous development of deep learning techniques, it is now easy for anyone to swap faces in videos. Researchers find that the abuse of these techniques threatens cyberspace security; thus, face forgery detection is a popular research topic. However, current detection methods do not fully use the semantic features of deepfake videos. Most previous work has only divided the semantic features, the importance of which may be unequal, by experimental experience. To solve this problem, we propose a new framework, which is the multisemantic pathway network (MSPNN) for fake face detection. This method comprehensively captures forged information from the dimensions of microscopic, mesoscopic, and macroscopic features. These three kinds of semantic information are given learnable weights. The artifacts of deepfake images are more difficult to observe in a compressed video. Therefore, preprocessing is proposed to detect low-quality deepfake videos, including multiscale detail enhancement and channel information screening based on the compression principle. Center loss and cross-entropy loss are combined to further reduce intraclass spacing. Experimental results show that MSPNN is superior to contrast methods, especially low-quality deepfake video detection.
miR-18a-5p and ATM Expression in Esophageal Squamous Cell Carcinoma and Their Correlations with Clinicopathological Features
Authors: Qi Jinyou , Fan Wei
Published: October 2022

Objective. To investigate miR-18a-5p and ataxia telangiectasia muted (ATM) expression in esophageal squamous cell carcinoma (ESCC) and their correlations with clinicopathological features. Methods. The subjects of this study were 62 ESCC patients (research group, RG) and 57 healthy controls (control group, CG) presented to our hospital between July 2019 and April 2020. Peripheral blood (PB) miR-18a-5p and ATM levels in these participants were quantified via qRT-PCR, and the correlations of the two genes with ESCC patients’ clinicopathological characteristics were investigated. In addition, a two-year follow-up was performed on ESCC patients to understand their survival, so as to further determine the prognostic utility of miR-18a-5p and ATM in ESCC. Factors influencing patient outcomes were identified by COX analysis. Results. PB miR-18a-5p expression was higher in RG compared with CG, while ATM was lower, suggesting an inverse connection between the two genes in ESCC (

P
<
0.001

). miR-18a-5p and ATM levels were determined to be strongly linked to TNM stage, differentiation degree, and lymph node metastasis in ESCC patients (

P
<
0.001

and

P
=
0.007

). The patients who succumbed to the disease exhibited higher miR-18a-5p and lower ATM than the survival (

P
<
0.05

). ROC analysis suggested favorable evaluation effects of miR-18a-5p and ATM on the occurrence and prognostic death of ESCC (

P
<
0.001

). Further, these two genes were identified by the COX analysis to be factors independently affecting the prognosis of ESCC. Conclusion. miR-18a-5p is highly expressed in ESCC, and ATM is underexpressed, both of which are closely linked to the pathological process of ESCC and have a good evaluation effect on the occurrence and prognosis of ESCC, which may become a breakthrough in future diagnosis and treatment of ESCC.
The Application of Personalized Recommendation System in the Cross-Regional Promotion of Provincial Intangible Cultural Heritage
Authors: Wang Qin
Published: October 2022

With the accelerated trend of globalization and modernization, many provincial intangible cultural heritages (PICH) are in danger of being lost. In the context of Internet technology, the use of digital multimedia for personalized recommendation is an effective way to promote the transmission of intangible cultural heritage. However, traditional recommendation systems tend to treat different members as homogeneous objects, ignoring the relationship between members’ professional backgrounds and the inherent properties of items, and cannot truly solve the problem of conflicting preferences in the integration process. In view of this, this paper proposes a group recommendation system based on nonnegative matrix decomposition. First, the group rating information is decomposed into a user matrix and item matrix by nonnegative matrix decomposition. Then, the item affiliation matrix and member expertise matrix are calculated by using the affiliation and expertise weights for the two matrices, respectively, and the contribution degree of each member to different item ratings is obtained from them. Finally, the group preference model is constructed by weighted fusion of members’ preferences based on their contribution degrees, and different recommendation lists are generated for different user preferences. The experimental results prove that this system has high recommendation accuracy in cross-regional promotion of PICH.
An Improved Runway Operation Capacity Model for V-Open Multirunway Airports in China
Authors: Shen Zhiyuan , Xu Xinyu , He Yong , Yan YongGang , Zhou Lin , Hu Yingying
Published: October 2022

Diverging runways are receiving considerable attention as replacements for parallel runways when constructing three or more runways in China. This has been prompted by the limitations associated with a single-direction airspace and associated regulations when using parallel runways. However, the operating efficiency of diverging runways is still greatly constrained by the separation standard for departing aircraft in CCAR-93TM-R5 and Decree of CAAC NO.123. To address these problems, an improved runway operation capacity model for a V-open multirunway airport is proposed to reduce the separation standard based on the equivalent lateral separation operation (ELSO) standard. A collision risk module is first proposed to assess the feasibility and safety of the proposed policy. Also, a novel runway capacity model for V-open multiple runways is then built to improve the operating efficiency for diverging runway. A series of comparative experiments based on actual flight data from Chengdu Tianfu International Airport demonstrated that reducing the divergence angle from 15° to 10° improved the runway operation capacity by about 8% based on the proposed improved policy. These research results could play a major role in facilitating appropriate amendments to the associated CAAC operation regulations.
The Adsorption Potential of Cr from Water by ZnO Nanoparticles Synthesized by Azolla pinnata
Authors: Wenjie Ou , Ahmed Waqas , Xiuxian Fu , Lu Wang , Jiannan Li , Jie Yang , Asghar Rana Muhammad Ammar , Mahmood Mohsin , Alatalo Juha M. , Imtiaz Muhammad , Li Weidong , Mehmood Sajid
Published: October 2022

Aqueous solutions containing toxic elements (TEs) (such as hexavalent chromium (Cr (VI)) can be toxic to humans even at trace levels. Thus, removing TEs from the aqueous environment is essential for the protection of biodiversity, hydrosphere ecosystems, and humans. For plant fabrication of zinc oxide nanoparticles (PF‐ZnONPs), Azolla pinnata plants were used, and X‐ray diffraction (XRD), energy dispersive spectroscopy (EDS), SEM, and FTIR techniques were used for the identification of PF‐ZnONPs and ZnONPs, which were used to remove Cr (VI) from aqueous solution. A number of adsorption parameters were studied, including pH, dose, concentration of metal ions, and contact time. The removal efficiency of PF‐ZnONPs for Cr (VI) has been found to be 96% at a time (60 min), 69.02% at pH 4, and 70.43% at a dose (10 mg·L−1). It was found that the pseudo‐second‐order model best described the adsorption of Cr (VI) onto PF‐ZnONPs, indicating a fast initial adsorption via diffusion. The experimental data were also highly consistent with the Langmuir isotherm model calculations.
Evaluating the Quality of Engineering Translator Training Based on the DEA Model
Authors: Han Yujuan
Published: October 2022

This paper adopts the DEA model to conduct in-depth research and analysis on the evaluation of the quality training of engineering English translation talents. The BIM application performance of nine engineering projects is empirically analyzed, including slack value analysis, correlation validity analysis, and BIM application performance path optimization. The nine cases have an unreasonable allocation of resources invested in BIM application in the early stage so that the performance path optimization is carried out to find out the key paths for the reallocation of resources. Further analysis of BIM application performance improvement strategies, including strengthening the training of BIM application professionals. The fuzzy two-stage DEA model with adjustable fuzzy opportunity constraint constructed for the situation where both intermediate and final processes have non-desired outputs. First, the additive efficiency decomposition model in the exact number environment is extended to the non-desired output situation. Second, the generalized fuzzy measure and opportunity constraint planning are applied to further extend the model to a non-expected output fuzzy DEA model, and a two-stage DEA model with adjustable fuzzy opportunity constraints is constructed. There are still some differences between the two. Strengthening practice is the general trend of current curriculum reform in our country. Finally, the proposed model is applied to the evaluation problem of quality training of engineering English translators. The adjustable fuzzy opportunity-constrained DEA model proposed in this paper can effectively evaluate the efficiency of real production and operation activities. The research results of this paper not only enrich the existing DEA model theoretical system but also have broad application prospects and values in practical problems. We provide a reasonable guarantee in terms of system and funding and pay attention to the follow-up communication with employers to strengthen the implementation of the influence of social forces on the quality evaluation of English teaching in higher education. To a certain extent, this study enriches the theoretical research on the quality evaluation of English translation talents’ quality training and can play a role in strengthening and improving the quality evaluation of translation talents’ quality training at the present stage.
A Voice Cloning Method Based on the Improved HiFi-GAN Model
Authors: Qiu Zeyu , Tang Jun , Zhang Yaxin , Li Jiaxin , Bai Xishan
Published: October 2022

With the aim of adapting a source Text to Speech (TTS) model to synthesize a personal voice by using a few speech samples from the target speaker, voice cloning provides a specific TTS service. Although the Tacotron 2-based multi-speaker TTS system can implement voice cloning by introducing a d-vector into the speaker encoder, the speaker characteristics described by the d-vector cannot allow for the voice information of the entire utterance. This affects the similarity of voice cloning. As a vocoder, WaveNet sacrifices speech generation speed. To balance the relationship between model parameters, inference speed, and voice quality, a voice cloning method based on improved HiFi-GAN has been proposed in this paper. (1) To improve the feature representation ability of the speaker encoder, the x-vector is used as the embedding vector that can characterize the target speaker. (2) To improve the performance of the HiFi-GAN vocoder, the input Mel spectrum is processed by a competitive multiscale convolution strategy. (3) The one-dimensional depth-wise separable convolution is used to replace all standard one-dimensional convolutions, significantly reducing the model parameters and increasing the inference speed. The improved HiFi-GAN model remarkably reduces the number of vocoder model parameters by about 68.58% and boosts the model’s inference speed. The inference speed on the GPU and CPU has increased by 11.84% and 30.99%, respectively. Voice quality has also been marginally improved as MOS increased by 0.13 and PESQ increased by 0.11. The improved HiFi-GAN model exhibits outstanding performance and remarkable compatibility in the voice cloning task. Combined with the x-vector embedding, the proposed model achieves the highest score of all the models and test sets.
Analysis on the Development of Automation and Intelligence in China’s Manufacturing Industry—Taking R & D Collaboration among Automobile Enterprises
Authors: Ye Jun , Liu Guoxin
Published: October 2022

With the development of intelligence for automated automobile industries in China, the traditional R&D mode of enterprise has evolved from integrated internal innovation within a single enterprise to collaborative innovation among enterprises, which makes enterprises break the limit of the organizational boundaries to seek for the right partners and cooperation. However, the R&D environment among business partners and the mismatch between R&D and management have greatly affected the development of intelligence for automated industrial. Based on synergetic, from the perspective of collaborative R&D among automobile companies, this paper takes the collaborative R&D between Renault-Nissan Alliance and Dongfeng Motor Group as the research object, conducting quantitative analysis using regression models and structural equation models with 423 valid questionnaires collected in three months (from October 2017 to May 2018), and attempting to reveal the situational context in the distributed innovation network as well as how the dynamic collaborative behaviors among R&D enterprises act on “collaborative R&D performance.” The results show that first, the four “collaborative contexts”–strategic context, cultural context, institutional context, and network context–have a significant positive correlation with the level of collaborative R&D; second, the three “collaborative behaviors”—knowledge sharing, information sharing, and specific asset investment—have a significant positive correlation with the level of knowledge growth; and third, the level of collaborative R&D and knowledge growth have a significant positive correlation with R&D performance. Thus, it is revealed that not only are there situational contexts among the R&D and innovation activities of the core enterprises but also dynamic collaborative behavior. This creates a new perspective for the research on the development of intelligence for automated automobile industries in China among automobile companies.
A Case of Granulomatosis with Polyangiitis (GPA) Where a Multicystic Nasal Septal Abscess Aided in the Diagnosis
Authors: Sasawaki Mayuko , Omura Kazuhiro , Ebihara Teru , Otori Nobuyoshi
Published: October 2022

A 69-year-old male patient presented to the hospital with a chief complaint of nasal obstruction. Physical examination revealed swelling of the anterior nasal septum and nasal dorsum and tender indurated oedema of the dorsum of both hands. Blood tests showed an elevated inflammatory response, and contrast-enhanced computed tomography (CT) showed a polycystic abscess in the nasal septum. Emergency surgery and histopathology were performed on the day of the initial visit for incisional drainage. Intraoperative findings showed white necrosis between the nasal septal cartilage and nasal septal mucosa, as well as white necrosis and pus accumulation in the periosteum and soft tissue of the piriform aperture and the nasal bone. The patient underwent endoscopic dissection and drained as much as possible, and the abscess and surrounding normal nasal septal mucosa were sampled for diagnostic purposes. The patient was diagnosed with vasculitis based on the clinical findings, pathological examination results, and blood test results. After the diagnosis was confirmed, steroid and cyclophosphamide pulse administration was initiated, and the swelling of the anterior nasal septum and nasal dorsum and the bilateral dorsal indentation oedema improved markedly. The patient is now doing well and will continue to be carefully monitored in the outpatient clinic.
Ferroptosis, a Rising Force against Renal Fibrosis
Authors: Liu Yi , Wang Jingyu
Published: October 2022

Ferroptosis is a type of programmed cell death characterized by iron overload, oxidative stress, imbalance in lipid repair, and mitochondria-specific pathological manifestations. Growing number of molecular mechanisms and signaling pathways have been found to be involved in ferroptosis progression, including iron metabolism, amino acid metabolism, lipid metabolism, and energy metabolism. It is worth noting that ferroptosis is involved in the progression of fibrotic diseases such as liver cirrhosis, cardiomyopathy, and idiopathic pulmonary fibrosis, and inhibition of ferroptosis has acquired beneficial outcomes in rodent models, while studies on ferroptosis and renal fibrosis remains limited. Recent studies have revealed that targeting ferroptosis can effectively mitigate chronic kidney injury and renal fibrosis. Moreover, myofibroblasts suffer from ferroptosis during fiber and extracellular matrix deposition in the fibrotic cascade reaction and pharmacological modulation of ferroptosis shows great therapeutic effect on renal fibrosis. Here, we summarize the latest molecular mechanisms of ferroptosis from high-quality studies and review its therapeutic potential in renal fibrosis.
The Transformation and Leachability of Fly Ash/Cement Waste Forms Subjected to the Simultaneous Effect of Heat and Chemistry
Authors: Zheng Zhao , Wen Hua , Li Yuxiang , Qin Min , Wang Yao
Published: October 2022

The utilization of cement waste forms with high content of fly ash is a potential method in large-volume immobilization of low- and intermedium-level radioactive waste at near-surface. However, the migration behavior of radionuclides in fly ash/cement waste forms under geological environment is still unclear. This study researched the transformation of products, pore structure as well as the leachability of Ca2+, Na+, and simulated radioactive nuclides (Sr2+ and Cs+) in fly ash/cement waste forms under simultaneous effect through X-ray diffractometer (XRD), mercury intrusion porosimetry (MIP), and inductively coupled plasma optical emission spectroscopy (ICP-OES). Furthermore, the relationship between the decalcification and the leaching of Sr2+ and Cs+ was established by the fitting curves of apparent diffusion coefficient. The results indicated that the products of fly ash/cement waste forms were kept stable under simultaneous effect and the pore structure has excellent resistance to temperature. The increasing salt concentrations of leachant and temperature promoted the leaching of radionuclides while the protection layer formed at 60–80°C inhibited this phenomenon. The relationship of apparent diffusion coefficient between Sr2+ and Ca2+ was quadratic nonlinear, while the relationship between Cs+ and Ca2+ showed a linear relationship. Compared to cement waste forms, fly ash/cement waste forms were more stable. In addition, the long-term retention ability of fly ash/cement waste forms to Cs+ was more outstanding than Sr2+.
A Blockchain-Enabled Trusted Protocol Based on Whole-Process User Behavior in 6G Network
Authors: Tu Zhe , Zhou Huachun , Li Kun , Song Haoxiang , Yang Yuzheng
Published: October 2022

The access of massive users and devices in the 6G networks increases the risk of network attacks. Designing a trusted protocol to control user behavior can effectively improve the security capability of the network. However, most of the existing trusted protocols focus on unilateral user behavior and lack effective control over the whole process of user behavior. In this paper, we design a blockchain-enabled trusted protocol based on the whole-process user behavior. At first, we describe the Whole-Process User Behavior (WPUB) after the user accesses the network, and model the whole-process trusted control process. The proposed model establishes a trusted chain between user identity, access action, and communication traffic, and realizes the control of WPUB. Then, based on the proposed model, we design a whole-process trusted protocol with smart agents and smart contracts in combination with blockchain. Finally, we evaluate the designed protocol in the HyperLedger Fabric-based prototype system. Evaluations show that the proposed protocol can control the WPUB and reduce the risk of the network being attacked.
Development of a Thin Vibrotactile Actuator Based on the Electrostatic Force Mechanism for Large Haptic Touch Interfaces
Authors: Kim Jae-Ik , Jo Gwanghyun , Koo Jeong-Hoi , Kim Dong-Jun , Kim Young-Min , Yang Tae-Heon
Published: October 2022

Vibrotactile feedback in touch screen displays (TSDs) contributes to improved usability and enhanced engagement. It is prevalent in small consumer electronic devices, such as smart phones. While vibrotactile feedback is a desirable feature for large TSDs, it is limited in such devices due to a lack of proper actuators. In this study, we propose a thin vibrotactile actuator based on an electrostatic force mechanism suitable for mounting on the back of large TSDs. The primary goals of this study are to design and test a thin or slim electrostatic resonant actuator (ERA) and investigate its feasibility for large TSD applications. A prototype ERA was constructed by employing a “leaf” spring design to reduce the thickness and to support a mass that is grounded electrically. Upon applying a high-voltage input to the prototype, the electrostatic attraction force coupled with the spring’s restoring force makes the mass to oscillate, and the maximum vibration occurs at its resonant frequency. The ERA module testing shows that the prototype produced the maximum output acceleration of 2.5 g at its resonance frequency (99 Hz), which is significantly larger than the threshold value which humans can perceive. After validating that the thin ERA can produce sufficient vibrotactile sensations, a haptic touch display module consisting of a 17-inch touch panel supported by four ERAs was constructed. To experimentally evaluate the performance of this prototype, three distant input frequencies were used, and the acceleration response of the panel was measured at multiple points. The results show that the acceleration magnitude varies, exhibiting distinct patterns throughout the panel surface, when different input frequency values were applied. The results further show that the maximum acceleration magnitude is greater than that of the human-perceivable threshold values for the input frequencies considered in this study. Overall, the results show that the proposed ERA is feasible to use in large TSDs to convey vibration tactile sensations to users while keeping the thickness of the haptic interface module thin.
Social Work Management Intelligent System Based on Improved Genetic Algorithm
Authors: Guo Xiaojian , Ma Ye
Published: October 2022

With the continuous development of society, social work is gradually professionalized, and relevant service fields are also growing. However, the limited resources of social work activities and the different needs of service projects are also more prominent. The intelligent management concept can assist social work services, thus providing fresh vitality for the field. How to effectively apply this vitality to the actual work process and form a unique intelligent management mode of social work service has always been the core issue of the sustainable development of social work specialization. Intelligent social work management is a new development trend. Based on this background, in this paper, a class of the intelligent social work management system is designed. The core technology of this system is an improved genetic algorithm. The system design is generally divided into four modules, and each module has different functions, including user-level acquisition module, intermediate acquisition module, load balancing module, and platform-level data storage and analysis module. Through the design and test, after the design simulation experiment test, it can be known that the system can effectively complete the design objectives, solve practical application problems, reasonably complete the work tasks, and meet the needs of users. In addition, the application of the system can improve the efficiency and management of social work services. Finally, this paper makes an in-depth analysis of the problems existing in the field of actual social work management and proposes corresponding solutions on this basis. In this study, an improved genetic algorithm is combined with social work management, and an effective intelligent management system is designed to realize work assistance.
[Retracted] Long Noncoding RNA DSCAM‐AS1 Facilitates Proliferation and Migration of Hemangioma Endothelial Cells by Targeting miR‐411‐5p/TPD52 Axis
Authors: Wang Yulong , Zhai Shuiting , Xing Jianwu , Zhang Jinchi , He Yingkun , Wang Guoquan , Li Tianxiao
Published: October 2022

Background. Diagnosed as a kind of vascular neoplasm of infancy, hemangioma (HA) occurs mainly due to the aberrant proliferation of endothelial cells. Existing evidence has manifested the close relationship of long noncoding RNAs (lncRNAs) with the pathogenesis of HA. Although lncRNA DSCAM antisense RNA 1 (DSCAM‐AS1) has been revealed to be implicated in the progression of human diseases, the underlying mechanism DSCAM‐AS1 exerts in HA formation is unclear. Aims. To figure out how DSCAM‐AS1 may regulate the progression of human hemangioma endothelial cells (HemECs). Methods. DSCAM‐AS1 expression was verified through RT‐qPCR detection. Functional assays including EdU assay, colony formation assay, flow cytometry analysis, TUNEL assay, and transwell assay were applied to evaluate cell proliferation, apoptosis, and migration upon DSCAM‐AS1 knockdown. Moreover, RNA pull‐down assay, luciferase reporter assay, RIP assay, and other mechanism experiments were utilized for evaluating the correlation of DSCAM‐AS1 and RNAs in HemECs. Results. DSCAM‐AS1 knockdown inhibited proliferative capability and migratory capability of HemECs whereas expedited apoptosis. Molecular mechanism results testified DSCAM‐AS1 could function as a ceRNA to bind miR‐411‐5p in HemECs. Besides, it was confirmed that tumor protein D52 (TPD52) served as a downstream target of miR‐411‐5p in HemECs. More importantly, related rescue assays uncovered that elevated expression of TPD52 or inhibited expression of miR‐411‐5p reversed the repressive progression of HemECs mediated by DSCAM‐AS1 depletion. Conclusion. DSCAM‐AS1 expedited HA progression via miR‐411‐5p/TPD52 pathway, which provided a novel therapeutic option for HA treatment.
The Therapeutic Potential of Targeted Nanoparticulate Systems to Treat Rheumatoid Arthritis
Authors: Liang Wenqing , Yu Yijun , Liu Zunyong , Ming Wenyi , Lin Hongming , Long Hengguo , Zhao Jiayi
Published: October 2022

Rheumatoid arthritis (RA) is a widespread autoimmune inflammatory disease. It implicates damage to bones, cartilage, and joints with uncertain pathogenesis. It is coupled with an elevated risk of cardiovascular complications and human disability. The conventional dosage forms for RA treatment pose numerous problems including poor efficacy, large dosages, frequent administration, limited responsiveness, greater expenses, and severe side effects. The nanoparticulate systems are emerging as a new thought for the diagnosis and treatment of RA. Anti‐inflammatory drug‐loaded nanoparticulate systems aid in the active and passive targeting of the inflamed region. Improved bioavailability and targetability are achieved by using these systems. In this review, the pathophysiology of RA and its conventional treatment has been discussed. The role of various nanoparticulate systems for passive and active targeting of RA has been reviewed. The authors have summarized the current practices in the typical and novel nanosystems to improve the quality of life in RA patients.
Higher Education Course Evaluation Based on Deep Learning Model
Authors: Zheng Xiaoxia
Published: October 2022

Higher education has completed a revolutionary transition stage from traditional elite education to mass quality education, and the improvement of higher education quality has increasingly become the focus of social attention. Courses are the most basic unit of university teaching, and the quality of courses directly affects the quality of personnel training. The expansion of higher education has resulted in insufficient teaching resources and a decline in the quality of courses. Improving quality is the eternal theme of higher education reform. How to formulate scientific curriculum quality standards and objectively evaluate curriculum quality is the most concerned issue of the society. Therefore, in-depth analysis of the factors that affect the quality of the curriculum and the establishment of the curriculum quality evaluation system and method has certain practical significance for improving the quality of the curriculum. This work combines the evaluation of higher education courses with deep learning models and proposes a network MSACNN for quality evaluation of higher education courses. This work proposes to use an attention-based multiscale network to explicitly learn the relationship between the qualities of various higher education courses. By using parallel networks with different convolution kernels, it combines different scale features at the same spatial location to better learn the relationship between the quality features of higher education courses. This work conducts sufficient experiments on the higher education curriculum quality dataset, and the experimental results demonstrate that the multiscale network based on the attention mechanism exhibits superior performance. MSACNN surpasses other machine learning methods in both precision and recall metrics.
Optimization of Meat and Poultry Farm Inventory Stock Using Data Analytics for Green Supply Chain Network
Authors: Kler Rajnish , Gangurde Roshan , Elmirzaev Samariddin , Hossain Md Shamim , Vo Nhut V. T. , Nguyen Tien V. T. , Kumar P. Naveen
Published: October 2022

The traditional meat and poultry farms use a fixed quantity of supply, which creates an imbalance between demand and supply. Due to this imbalance, a huge amount is spent on balancing the requirements. There is an inequality among demand and supply since typical meat and poultry farms use a fixed amount of supply. A lot of money is spent trying to balance the requirements because of this mismatch. In addition, when connecting and building the meat and poultry farm system, the procedure ignores the impact on the environment. The owner’s primary goals are to retain massive profits and raise reliability. The classical method neglects the effect on the environment while linking and designing the meat and poultry farm system. The main aim of the owner is to increase the quality and maintain the maximum profit. This paper deals with the meat and poultry farms in two folds. In the first step, the IoT based system is implemented for the traceability and demand‐supply monitoring. The second steps include optimization of the supply network to reduce the carbon emission from the transportation. Both steps take data analytics as an input to process the final result for the farm to run and optimize. Effective inventory optimization algorithms have been shown to be able to evaluate a significant portion of previous sales data and anticipate inventory future demand by taking seasonality and lead times into account. Revenue, productivity, and customer satisfaction are just a few of the business variables that these strategies may affect. Finally, the comparison is done with the traditional farm and supply chain on the points of demand‐supply balance, cost, carbon emission, and wastage. It is found that the farms using data analytics to optimize the overall system perform better and with 37% more efficient than the traditional systems.
Transcriptome Sequencing Analysis of lncRNA and mRNA Expression Profiles in Bone Nonunion
Authors: Zhou Jian , Wan Rongjun , Tian Qunyan , Wu Ziyi , Lin Zhengjun , Wang Wanchun , Tao Cheng , Liu Tang
Published: October 2022

Background. Bone nonunion is a serious complication of fracture. This study explored the differentially expressed lncRNAs (DELs) and mRNAs (DEGs) and identified potential lncRNA-mRNA interactions in bone nonunion. Methods. We extracted total RNA from three bone nonunion and three bone union patient tissue samples. RNA sequencing was performed to detect DELs and DEGs between bone nonunion and union tissue samples. The lncRNAs and genes with absolute log2-fold change

log
2
FC

>
1

and adjusted

p

value < 0.05 were further chosen for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. lncRNA and targeted mRNA interaction networks were constructed. Results. We observed 179 DELs and 415 DEGs between the bone nonunion and union tissue samples. GO analysis indicated that DELs and DEGs were mainly enriched in the chondroitin sulfate proteoglycan biosynthetic process. DELs and DEGs were enriched in “ECM-receptor interaction” and “Staphylococcus aureus infection” KEGG pathways. Several potential lncRNA-mRNA interactions were also predicted. Conclusions. This study identified bone nonunion-associated lncRNAs and mRNAs using deep sequencing that may be useful as potential biomarkers for bone nonunion.
Effect of Spectacle Lenses with Highly Aspherical Lenslets on Binocular Vision and Accommodation in Myopic Children with and without Intermittent Exotropia
Authors: Fengchao Zhou , Xue Li , Yingying Huang , Yuhao Li , Jiali Zhang , Hao Chen , Jinhua Bao
Published: October 2022

Purpose. To evaluate the influence of spectacle lenses with highly aspherical lenslets (HAL) on binocular vision and accommodation in myopic children with intermittent exotropia (IXT) and compare the changes after wearing HAL in binocular vision and accommodation in myopic children with or without IXT. Method. Forty myopic subjects aged 8–12 years were recruited: 20 with IXT and 20 visually normal children. Stereoacuity, phoria, accommodative facility, fusional vergence, vergence facility, near point of convergence, amplitude of accommodation, and accommodative response (AR) were measured by wearing HAL or single vision spectacle lenses (SVL) in a random order after adapting for 20 minutes. Accommodative microfluctuation (AMF) was defined as the standard deviation of AR. Changes in binocular vision and accommodation after wearing HAL were compared between the two groups. Results. No significant differences were found in binocular vision after wearing HAL versus SVL in either group (all

P
>
0.05

). A greater AMF was found after wearing HAL than after wearing SVL in both groups (0.04 D, 95% confidence interval (CI), 0.03 to 0.05 D,

P
<
0.001

for the IXT group; 0.05 D, 95% CI, 0.03 to 0.07 D,

P
<
0.001

for the visually normal group); however, the other accommodation parameters did not change significantly (all

P
>
0.05

). There were no differences in the changes after wearing HAL in any parameter between the two groups (all

P
>
0.05

). Conclusion. HAL did not significantly change the binocular vision and accommodation for myopic children with or without IXT except for AMF in the short term.
Effects of Solar Photovoltaic Penetration on the Behavior of Grid-Connected Loads
Authors: Okedu Kenneth E. , Al Abri Ahmed
Published: October 2022

Recently, the authority for electricity regulations in Oman introduced a new regulation for grid-connected photovoltaic (PV) systems. One of the main concerns is how the penetration of the grid-connected PV systems would affect the Mazoon Electricity Company’s (MZEC) load behavior, especially at peak times. This paper presents the behavior of grid-connected loads considering the MZEC, which is one of the power distribution companies in Oman. The Al Bashir primary substation load distribution network was used as a case study. The MZEC peak load pattern was considered with respect to solar PV connection regulations in Oman. Furthermore, the various timings for electricity billing and the expected incentives were also used in evaluating the economical benefits of integrating the solar PV systems into the power grid. Data were collected for two years for the feeder and distribution transformers in the power grid. The export and import average power generation within the period of the study were also investigated. The behavior of the grid loads was investigated before and after installing the PV systems. The variables of the average power, load import, and export for different periods were used to evaluate the system performance. The obtained results reflect that with proper synchronization of the solar PV systems in the power grid, the maximum load of the primary substation decreased from 80% to 40%, considerably saving cost. Consequently, more consumers could be fed with the excess solar power, with less distribution transformers in the power grid.
Improved Matrix Multiplication by Changing Loop Order
Authors: Almurayh Abdullah
Published: October 2022

Matrix multiplication has been implemented in various programming languages, and improved performance has been reported in many articles under various settings. Matrix multiplication is of paramount interest to machine learning, a lightweight matrix-based key management protocol for IoT networks, animation, and so on. There has always been a need and an interest for improved performance in terms of algorithm implementation. In this work, the authors compared the run times of matrix multiplication in popular languages such as C++, Java, and Python. This analysis showed that Python’s implementation was poor while Java was relatively slower compared to the C++ implementation. All the aforementioned languages use a row-major scheme, and hence, there are many cache misses encountered when implemented through simple looping. In contrast, the authors show that by changing the loop order, more performance gains are possible. Moreover, we evaluated the performance of matrix multiplication by comparing the execution time under various loop settings. The authors observed tremendous performance gains due to better spatial locality. In addition, the authors also implemented a parallel version of the same algorithm using OpenMP with eight logical cores and achieved a speed-up of seven times compared to the serial implementation.
Targeting the DLL/Notch Signaling Pathway in Cancer: Challenges and Advances in Clinical Development
Authors: You Weon-Kyoo , Schuetz Thomas J. , Lee Sang Hoon
Published: October 2022

The DLL/Notch signaling pathway plays an important role in cancer as a key driver in maintaining cancer stemness and inducing tumor angiogenesis. Many different types of DLL/Notch inhibitors have been developed and explored in clinical trials for cancer treatment, including small-molecule compounds to inhibit gamma-secretase and antibodies targeting Notch ligands or receptors. Despite promising efficacy of these inhibitors in preclinical studies, the overall clinical outcomes have been insufficient to advance to the next stage of clinical development primarily due to safety concerns or modest efficacy. To overcome the narrow therapeutic window of DLL/Notch inhibitors, diverse strategies for improving the balance between the safety and efficacy are currently being explored. Here, we review the clinical perspective and potential of DLL/Notch inhibitors as anticancer agents based on recent results from multiple clinical studies. An antibody specifically targeting Notch ligands or receptors may offer a better approach to reduce concerns about toxicity derived from broad-spectrum DLL/Notch blockers. In addition, combination therapy with an angiogenesis inhibitor targeting VEGF could be a better option for increasing anticancer efficacy. Taken together, the results of clinical trials suggest a bispecific antibody blocking the DLL/Notch and VEGF/VEGFR signaling pathways as a promising approach for effective anticancer treatment.
Acceptance of Illness, Satisfaction with Life, and Emotional Control in the Early Stage of Autosomal Dominant Polycystic Kidney Disease
Authors: Jankowska Magdalena , Walerzak Anna , Harciarek Michał , Rutkowski Bolesław , Dębska-Ślizień Alicja
Published: October 2022

Introduction: Psychological disorders are strong predictors of life expectancy and have an impact on quality of life. Autosomal dominant polycystic kidney disease (ADPKD) is frequently diagnosed before the onset of subjective symptoms. Similar to other disorders of genetic origin, ADPKD may be a source of remarkable psychological discomfort. One way of coping with emotional distress is its suppression, and this could be measured. Our study aimed to provide data on the acceptance of illness, the emotional suppression of anger, and both anxiety and depression as well as satisfaction with life in young patient population of early-stage ADPKD in comparison to healthy demographically matched individuals. Methods: Fifty patients in the asymptomatic stage of ADPKD with an eGFR >60 mL/min (4p MDRD) and 50 healthy demographically matched individuals were included in this study. Participants filled out a set of psychological questionnaires: Acceptance of Illness Scale (AIS), Courtauld Emotional Control Scale (CECS), and Satisfaction with Life Scale (SWLS). Results: Asymptomatic patients with ADPKD had 80% scores indicative of disease acceptance in AIS. As compared to healthy individuals, they presented with significantly stronger suppression of both anxiety and depression but not anger. The ADPKD group had significantly lower satisfaction with life in comparison to the healthy group. Conclusion: Asymptomatic ADPKD patients had a high level of disease acceptance. Anger suppression in this group was comparable to healthy individuals, but anxiety and depression were controlled more intensively. Despite the asymptomatic course of the disease, ADPKD patients revealed lower satisfaction with life in comparison to healthy persons.