bluuebunny/crossref_metadata_2025 huggingface dataset:
“Dimension Reduction: Feature Subset” Method for Selecting the Best Index Combination in Reputation Evaluation of Crowdsourcing Participants
Authors: Huang Yanrong , Zheng Zhan , Wei Bo
Published: October 2022

An effective reputation evaluation mechanism is an essential guarantee for the crowdsourcing mode's healthy, orderly, and rapid development. Aiming at the problems of unsound reputation evaluation mechanism, single reputation evaluation index, and poor discrimination ability of crowdsourcing platforms a “dimension reduction feature subset” method for selecting the best reputation evaluation index combination of crowdsourcing participants is proposed. This method first selects the best dimensionality reduction method by empirical method, then uses the classifier as the evaluation function of feature selection, and uses the sequential backward selection strategy (SBS) to select the feature subset and reputation evaluation algorithm with the best classification performance. The experimental results show that the reputation evaluation method of crowdsourcing participants based on ReliefF-SVM has the best performance in terms of accuracy, F1 measure, and stability and can select a comprehensive, objective, and effective evaluation index combination to distinguish the reputation status of crowdsourcing participants.
BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning
Authors: Chimeleze Collins , Jamil Norziana , Ismail Roslan , Lam Kwok-Yan , Teh Je Sen , Samual Joshua , Akachukwu Okeke Chidiebere
Published: October 2022

Malware detection refers to the process of detecting the presence of malware on a host system, or that of determining whether a specific program is malicious or benign. Machine learning-based solutions first gather information from applications and then use machine learning algorithms to develop a classifier that can distinguish between malicious and benign applications. Researchers and practitioners have long paid close attention to the issue. Most previous work has addressed the differences in feature importance or the computation of feature weights, which is unrelated to the classification model used, and therefore, the implementation of a selection approach with limited feature hiccups, and increases the execution time and memory usage. BFEDroid is a machine learning detection strategy that combines backward, forward, and exhaustive subset selection. This proposed malware detection technique can be updated by retraining new applications with true labels. It has higher accuracy (99%), lower memory consumption (1680), and a shorter execution time (1.264SI) than current malware detection methods that use feature selection.
Collaborative Governance of Rural Relative Poverty under Blockchain and Back Propagation Neural Network
Authors: Tian Xin-Jie , Ge Zhi-Jun
Published: October 2022

It aims at exploring the effect of coordinated relative poverty governance in rural areas based on blockchain and back propagation (BP) neural network, so that the living standard of rural areas can be significantly improved. In view of the shortcomings and defects existing in the rural relative poverty governance, artificial intelligence technologies such as blockchain and neural network are innovatively introduced to conduct intelligent storage and data visualization analysis on the rural relative poverty governance process. A visualized governance and mechanism innovation model of rural relative poverty data based on blockchain and BP neural network is constructed. Finally, its performance is analyzed through experiments. The results show that the accuracy of data visualization prediction of the proposed algorithm model reaches 94.31%. When the amount of data is 5.5 Mb, the calculation consumption of the proposed algorithm is 0.08 s, and the average leakage rate finally stabilizes below 10%. Therefore, the constructed poverty data visualization governance model can achieve good data transmission security performance while ensuring high classification accuracy. It can provide experimental basis and contribution for the intelligent development and mechanism innovation of rural relative poverty governance.
Lymph Node Metastases Detection Using Gd2O3@PCD as Novel Multifunctional Contrast Imaging Agent in Metabolic Magnetic Resonance Molecular Imaging
Authors: Rasouli Z. , Riyahi-Alam N. , Khoobi M. , Haghgoo S. , Gholibegloo E. , Ebrahimpour A. , H Ashouri , Hashemi H.
Published: October 2022

Axillary lymph node detection is crucial to staging and prognosis of the lymph node metastatic spread in breast cancer. Currently, lymphoscintigraphy and blue dye, as the conventional methods to localize sentinel lymph nodes (SLNs), are invasive and can only be performed during surgery. This study has had a novel hybrid gadolinium oxide nanoparticle coating with Cyclodextrin‐based polyester as a high‐relaxivity T1 magnetic resonance molecular imaging (MRMI) contrast agent (CA). Twelve female BALB/c mice were randomly divided into three groups of four mice; each group was injected with 4T1 cells to obtain metastasis lymph nodes and diagnosed by using the 3D T1W (VIBE) MRI (Siemens 3T, Prisma). The synthesized Gd2O3@PCD nanoparticles with a suitable particle size range of 20–40 nm have had much higher longitudinal relaxivity (r1) for Gd2O3@PCD and Gd‐DOTA (Dotarem) with the values of 3.98 mM−1·s−1 ± 0.003 and 2.71 mM−1·s−1 ± 0.005, respectively. Identical MR images in coronal views were subsequently obtained to create time‐intensity curves of the right axillary lymph nodes and to measure the contrast ratio (CR). The peak CR and qualitative assessment of axillary lymph nodes at five‐time points were evaluated. After subcutaneous injection, the contrast ratio of axillary lymph node and tumor in mice exhibited CR peak of Gd2O3@PCD and Dotarem with the values of 2.21 ± 0.06 and 0.40 ± 0.004 for lymph node and 2.54 ± 0.04 and 1.21 ± 0.007 for the tumor, respectively. Furthermore, the lumbar‐aortic lymph node is weakly visible in the original coronal image. In conclusion, the use of Gd2O3@PCD nanoparticles as novel MRMI CAs enables high resolution for the detection of lymph node metastasis in mice with the potential capability for breast cancer diagnostic imaging.
An Artificial Intelligence-Based Bio-Medical Stroke Prediction and Analytical System Using a Machine Learning Approach
Authors: Pitchai R. , Dappuri Bhasker , Pramila P. V. , Vidhyalakshmi M. , Shanthi S. , Alonazi Wadi B. , Almutairi Khalid M. A. , Sundaram R. S. , Beyene Ibsa
Published: October 2022

Stroke-related disabilities can have a major negative effect on the economic well-being of the person. When left untreated, a stroke can be fatal. According to the findings of this study, people who have had strokes generally have abnormal biosignals. Patients will be able to obtain prompt therapy in this manner if they are carefully monitored; their biosignals will be precisely assessed and real-time analysis will be performed. On the contrary, most stroke diagnosis and prediction systems rely on image analysis technologies such as CT or MRI, which are not only expensive but also hard to use. In this study, we develop a machine learning algorithm for the prediction of stroke in the brain, and this prediction is carried out from the real-time samples of electromyography (EMG) data. The study uses synthetic samples for training the support vector machine (SVM) classifier and then the testing is conducted in real-time samples. To improve the accuracy of prediction, the samples are generated using the data augmentation principle, which supports training with vast data. The simulation is conducted to test the efficacy of the model, and the results show that the proposed classifier achieves a higher rate of classification accuracy than the existing methods. Furthermore, it is seen that the rate of precision, recall, and f-measure is higher in the proposed SVM than in other methods.
A Generative Image Inpainting Model Based on Edge and Feature Self-Arrangement Constraints
Authors: Yao Fan , Chu Yanli
Published: October 2022

At present, the image inpainting method based on deep learning has achieved a better inpainting effect than traditional methods, but the inpainting results still have problems such as local structure disorder and blurred texture when the images involving a large defect area are processed. This paper proposes a second-order generative image inpainting model based on edge and feature self-arrangement constraints. The model consists of two parts: edge repair network and image repair network. Based on the self-encoder, the edge repair network generates the edges in the defect area according to the known information of the image and improves the edge repair effect by minimizing the adversarial loss and feature matching loss. The image inpainting network fills the defect area with the edge repair result as a priori condition. On the basis of U-Net, the feature self-arrangement module (FSM) is proposed to reconstruct the coding features of a specific scale, and the reconstructed feature skips to connect the decoding layer of the same scale, and it is fused with the upper layer underlying features for decoding. Meanwhile, guide loss, adversarial loss, and reconstruction loss are introduced to narrow the difference between the repaired image and the original image. The experimental results show that the inpainting results of the proposed model have stronger structural connectivity and clearer textures and the performance of PSNR, SSIM, and mean L1 loss in the Celeba, Facade, and Places2 is better than other inpainting methods, indicating that the algorithm can produce an inpainting effect with highly connected structure, reasonable semantics, and fine details.
Effect of Game Teaching Assisted by Deep Reinforcement Learning on Children’s Physical Health and Cognitive Ability
Authors: Guan Yingrong , Qiu Yaoyu , Xu Fang , Fang Jifu
Published: October 2022

In order to strengthen children’s physical health and cognitive ability, further promote the development of children’s teaching, and strengthen the promotion and application of game teaching in children’s teaching, this paper takes game teaching under learning guidance as the research basis. First, combined with relevant information on children’s teaching practice in China and foreign countries, teaching practice is carried out from the aspects of preparation, process, analysis and evaluation, reflection, and so on. Second, the questionnaire method, interview method, and observation method are used, and the application status of game teaching in children’s teaching is analyzed to make statistics and summary. Finally, by comparing the test results of the experimental class and the comparative class to understand the students’ knowledge after the completion of teaching, conclusions are drawn to understand the role of game teaching in students’ learning. The research finds that more than half of 56% of teachers believe that game teaching is very important in the teaching process, and 31% of teachers believe that game teaching is not important in the teaching process. It shows that although most teachers are aware of game teaching, a large proportion of teachers still has insufficient awareness of effective teaching. It is necessary to improve teachers’ attention and understanding of effective teaching. Through experimental research on the influence of game teaching on children’s physical health and cognitive ability in the classroom, the study found that 46% of the experimental group were not interested in learning before the experiment. After the experiment, it became more fun. After testing, 72% of the students said they were satisfied. 92% of the students said that playing games is a kind of enjoyment. It shows that game teaching can not only enhance children’s learning interests, but also enrich children’s emotions and cognition. Game teaching is of great help to young children’s healthy development and cognitive ability. In addition, through interviews with teachers, the current situation of game teaching is summarized and analyzed. The research results show that in the teaching process, students can participate in game teaching happily, autonomously, and actively. Regarding game teaching assistance in teaching, teachers can break through the traditional professional division of labour barriers, and students can become curriculum designers, implementers, evaluators, and managers. It is hoped that there will be more comprehensive and detailed research in the future to provide more valuable, scientific, and effective research conclusions for future research work and other related research.
The Effect of Bevacizumab and Propranolol on Nasal Polyposis
Authors: Olgun Yuksel , Aktas Safiye , Sutay Semih , Ecevit Mustafa Cenk
Published: October 2022

Objective. This study aims to evaluate the effects of bevacizumab and propranolol from the point of view of a possible antiangiogenic effect in a model of primary nasal polyp (NP) tissue culture. Methods. NP samples of 21 patients and normal healthy nasal mucosa samples of 7 patients were cultured. Samples were divided into four groups as follows (healthy nasal mucosa, NP without any treatment, NP treated with propranolol, NP treated with bevacizumab). Cultured tissues were formalin fixed and paraffin embedded. Tissue sections and immunohistochemical VEGF-A, angiopoietin-1 (Ang-1), and angiopoietin-2 (Ang-2) expressions were evaluated. ELISA was also performed for each one of them. Results. Both propranolol and bevacizumab significantly decreased the expressions of VEGF-A and Ang-1, and they significantly increased the expression of Ang-2 in comparison to the control NP group. In the healthy nasal mucosa group, no significant expression of VEGF-A was seen, a slight (+) Ang-1 expression, and a high (+++) Ang-2 expression were observed. Conclusion. Bevacizumab and propranolol exert an antiangiogenic effect on NP tissues, mainly by decreasing VEGF-A and Ang-1 expression, increasing Ang-2 expression.
Influence of Educational Informatization Based on Machine Learning on Teaching Mode
Authors: Ma Lei , Li Jian
Published: October 2022

In recent years, with the rapid progress of educational information techniques, the application of computer teaching methods in school education has also shown a constantly changing trend. How to change the traditional classroom structure, improve the teachers’ information literacy, build a new information-based teaching format, and promote the integration of information technique and pedagogy have become an important topic of the current educational research study. Machine learning is a key technology in artificial intelligence and is widely used in various fields. The core of educational informatization is to carry out personalized learning, and the main auxiliary technology of personalized learning is machine learning. So, this article studied the influence of machine learning-based educational informatization on the teaching mode. Through the investigation and research methods, this article found that the educational informatization teaching mode based on machine learning is helpful to improve students’ autonomous learning ability, comprehensive ability, and learning effect. In the information-based teaching mode, the learning effect reached a maximum of about 90, with an average increase of 12, which showed that the educational information-based teaching mode based on machine learning is feasible.
Evaluating the Diagnostic Potentials of Circulating Tumor DNA against Melanoma: A Systematic Review and Meta-Analysis
Authors: Zhang Jianchao , Qian Da , Xu Xiaochen , Xu Ming , Wang Ke , Lu Hui , Shen Guoliang
Published: October 2022

Background. The accurate detection of circulating tumor (ct) DNA is affected by multiple factors, and several controversies still persists regarding clinical applications. In order to assess the consistency of ctDNA gene mutation detection findings in matched melanoma tissue samples and peripheral blood, a meta-analysis was performed and provided evidence-based analysis for its clinical applications. Method. As of May 20, 2019, the database has been searched using the Embase, PubMed, and Cochrane Library search engines. The ctDNA investigations mentioned in this review may be used to directly or indirectly get the true positive (TP), true negative (TN), false positive (FP), and false negative (FN) values of melanoma patients. To be excluded from the study are duplicate publications, research that do not offer a full text, inadequate material or an inability to extract data, and animal trials. Results. Overall, the pooled specificity, sensitivity, NLR, PLR, and DOR were 0.94 (95% CI: 0.91-0.96), 0.73 (95% CI: 0.70-0.75), 0.32 (95% CI: 0.22-0.45), 8.21 (95% CI: 4.67-14.43), and 32.72 (95% CI: 14.81-72.30), respectively. Additionally, we calculated AUC by drawing the SROC curve, and the value of AUC is 0.9287, which indicates that the accuracy of ctDNA in diagnosing melanoma is 92.87% of the gold standard. Furthermore, we conducted a subgroup analysis for different countries, sample sources, and ctDNA detection methods. The pooled results showed that different countries, sample sources, and ctDNA detection methods showed significantly large differences in terms of sensitivity of ctDNA in diagnosing melanoma, while the specificity basically remained the same. Conclusion. We discovered that the diagnostic outcomes between matched tumor samples and ctDNA remained more reliable in melanoma patients. ctDNA has the advantages of low trauma, convenient dynamic monitoring, and simple operation. ctDNA is expected to become an auxiliary method for the diagnosis of melanoma gene mutations.
A Novel Coordinated Control System to Reactive Power Compensation of Photovoltaic Inverter Clusters
Authors: Pan Tingzhe
Published: October 2022

With the development of new energy, a cost-effective reactive power compensation scheme is essential to the voltage stability of the power system for small-capacity distributed generation. This paper proposes a coordinated control scheme of inverter cluster which is based on the reactive power support capability of the photovoltaic inverter. Moreover, by using power angle vectors, a reactive power distribution algorithm is proposed to solve the poor power quality of the point of common coupling connecting source and load in the distributed generation station. Simulations verify the performance of the algorithm is better than the conventional static capacity distribute algorithm and dynamic residual margin distribute algorithm. Finally, the effectiveness of the reactive power compensation scheme and distribution strategy for improving power quality and regulation ability proposed in this paper is verified by operation experiments in the actual power station.
The Overexpression of miR-377 Aggravates Sepsis-Induced Myocardial Hypertrophy by Binding to Rcan2 and Mediating CaN Activity
Authors: Wang Shiji , Wang Guang , Dong Lihua , Liu Xingang , Pan Weiyun , Han Jinfeng , Lu Ying
Published: October 2022

Sepsis remains a complicated and incompletely understood syndrome, and myocardial dysfunction is one of the main complications contributing to poor clinical outcomes. Accumulating evidence has revealed the critical involvement of the deregulated expression of specific microRNAs (miRNAs) in cardiac pathologies caused by sepsis. Intriguingly, miR-377 has been correlated with cardiomyocyte apoptosis, whereas its effect on myocardial hypertrophy remains to be illustrated. Thus, the current study sets out to explore the impact and underlying mechanism of miR-377 on myocardial hypertrophy induced by sepsis. The expression pattern of miR-377 was detected in myocardial tissues of septic mice induced by cecal ligation-perforation (CLP). We found that miR-377 was highly expressed in myocardial tissues of CLP-induced septic mice with cardiomyocyte hypertrophy. Besides, miR-377 inhibition could relieve cardiomyocyte hypertrophy and reduce inflammation in septic mice. Further, mechanistic studies found that miR-377 could target Rcan2 and then regulate calcineurin (CaN) activity via Ca2+/CaN signaling pathway. Collectively, our findings illuminate that miR-377 enhances myocardial hypertrophy caused by sepsis, by targeting Rcan2 and further regulating the Ca2+/CaN signaling pathway. This work highlights downregulation of miR-377 as a novel target for the management of sepsis-induced myocardial hypertrophy.
Construction of Computer English Corpus Assisted by Internet of Things Information Perception and Interaction Technology
Authors: Tian Miao
Published: October 2022

Aiming at the situation that multiple sensing devices in the sensing layer sense the same sensing quantity, multiple redundant measurement data will be generated. In this paper, an improved Kalman filtering algorithm is used. The algorithm combines with numerical test theory to remove abnormal error data before filtering, thereby reducing the error of filtering result and improving its reliability. The parallel multiprotocol processing mechanism of the gateway is designed, and the IoT gateway has a hierarchical modular processing design for different protocol signals of the heterogeneous perception layer. The web interaction function with good platform versatility is designed to provide a visual interaction interface for the application layer, which is convenient for the application layer terminal to monitor and manage the perception layer equipment. This paper realizes the retrieval and query function of keywords, wrong sentences, and English character errors. This corpus enriches the less existing Madagascar corpus and establishes a separate English character error query database. This paper describes the overall process of corpus from preliminary preparation to establishment and the related use instructions of corpus, makes a statistical analysis of the current corpus data, and puts forward some suggestions for building a computer English corpus according to the analysis results.
Evaluation of Physical Education Teaching Effect Based on Big Data
Authors: Shu Xinyun , Wang Qian , Tang Hui , Ge Yinfeng
Published: October 2022

In order to provide a new vision and a broad idea for the evaluation of physical education in colleges and universities, a physical education teaching effect evaluation system based on big data is proposed. This study uses the method of a questionnaire survey to understand the problems encountered in the current sports evaluation of a college in China and to determine the evaluation index and its weight coefficient of college sports. The foundation of big data applications is mainly used for the establishment of college sports evaluation. The results showed that 50 percent of physical education teachers and 44.2 percent of students thought physical education examination was unnecessary, while only 16.67 percent of physical education teachers and 24.2 percent of students thought it was necessary. However, 90 percent of physical education teachers and 90.4 percent of students think school physical education evaluation is very important. At the same time, 63.33% of P.E. teachers think that the evaluation of the college P.E. curriculum is not enough and there is no responsibility. At present, there are many problems in the evaluation of physical education courses in colleges and universities, such as the curriculum, model, and scale being simple and unclear, the process is not scientific, there being no good model, and the guarantee mechanism is not good. It is concluded that the current evaluation of physical education in colleges and universities in this province has many problems, such as single subject and model, simple and fuzzy index, unscientific method, lack of individuality in the standard, imperfect guarantee mechanism, and imperfect feedback mechanism.
Outcomes of Human Papilloma Virus Vaccination in a Private Women Health Clinic in Lebanon
Authors: Seoud Muhieddine , Jaafar Iman , Ghanem Rayan , Soubhieh Christiane , Adra Abdallah , Nassar Anwar , Khalil Ali
Published: October 2022

Objectives. The study aims to report on the feasibility and associated adverse events of HPV-Vaccination (HPVV) in a private clinic setting in Lebanon and, when available, the results of subsequent cervical cancer screening. Methods. Opportunistic HPV vaccination is offered at the Women’s Health Center of the AUBMC. We retrospectively reviewed the patients’ demographic data, the incidence of adverse events, and their cytological screening. Results. A cohort of healthy women (n = 1013) aged 26.2 years (12–54 years) were opportunistically vaccinated with one of two HPV vaccines; 845 (83.4%) received the quadrivalent vaccine (Q4V), and 151 (14.1%) received the bivalent vaccine (B2V). The majority (75.8%) received three doses while 16% received two doses. Out of these women, 26.3% (267) became sexually active postvaccination (NS2), whereas 17% (174) were sexually active prior to vaccination (SA) and the rest 57% (572) reported no sexual activity (NS1). Among the SA group, 26% (46/147) presented with abnormal cytology at time of vaccination. As for the NS2 women, 5% (14/267) had subsequently abnormal screening within 37 (12–103) months following vaccination. Conclusions. In this observational study, we report the successful introduction of HPVV with negligible adverse events. The incidence of abnormal cervical cytology was low among our patients.
Investigation on Mechanical Behaviour of LM6 Aluminum Alloy Hybrid Composites Processed Using Stir Casting Process
Authors: Suresh Pungaiah S. , Sahu Kuldip Kumar , Yuvaraja R. , Jayahari Prabhu G. , Raja Sudharsan R. , Thamizhvalavan P. , Ramaswamy Kiran
Published: October 2022

The stir casting process produces boron nitride (B4N) and fly ash-based LM6 metal matrix composites. This hybrid composite was fabricated by varying fly ash from 3% to 15% with an increase of 3%. While the other reinforcement B4N concentration was kept constant as 3%. The morphology of the metal matrix composite is analysed using a light optical microscope. The microstructure analysis shows the uniform distribution of hybrid reinforcement throughout the matrix, and only a few clusters are found in the matrix alloyed with 15% B2N. Both pure and reinforced matrices are evaluated for the mechanical properties’ evaluation. The result shows an increment in hardness from 70.4 VHN to 96.2 VHN. Similarly, the tensile strength of the composite material is improved from 151 MPa to 192 MPa. The reason for improving strength and hardness is the uniform distribution of hybrid reinforcement in the LM6 matrix.
Movement Evaluation Algorithm-Based Form Tracking Technology and Optimal Control of Limbs for Dancers
Authors: Chen Jia , Chen Luxi
Published: October 2022

This study designs an optimal control model of dance personnel from tracking technology and limb control based on an action evaluation algorithm by constructing a human action evaluation algorithm model and conducting an in-depth study of dance personnel from tracking technology and limb control. This study proposes an OpenPose method based on pose flow optimization to address the false detection of vital human points and misconnection between critical issues in traditional OpenPose-based human pose estimation. The human pose estimation results of OpenPose are optimized by using the human pose flow information in the image sequence. This makes up for the shortcomings of traditional OpenPose that ignores the interframe image information. In this study, we analyze the experimental data of action evaluation, define a set of formulas to evaluate the action after summarizing the distribution pattern of DTW difference sample points from 8 angles, and design an action evaluation system to demonstrate the rationality of this action evaluation method. Since the bases and factors in the evaluation formula are constantly recalculated as the action changes, which increases the complexity of the evaluation method, the following work is to improve the parameters of the activity evaluation formula, so that the evaluation method has better efficiency and adaptability. To enhance the effect of action recognition, this study uses the Kinect sensor to obtain the 3D coordinates of 20 skeletal joints of the human body. It uses the relative distance and angle sequence of the joints as the feature parameters according to the characteristics of human posture. In static pose recognition, the feature vector’s sample set is trained, and the KNN algorithm is used as a classifier to recognize the pose.
A YOLOv3-Based Industrial Instrument Classification and Reading Recognition Method
Authors: Zhang Haifei , Chen Qianqian , Lei Liting
Published: October 2022

Aiming at the demand of industrial instrument reading, this study proposes a method of industrial instrument classification and reading recognition based on YOLOv3. Given that industrial meters can be divided into pointer meters and digital meters according to the dial type, this method conducts a reading study for each of the two types of meters. Firstly, the YOLOv3 model is trained to recognize and detect the meter types and classify the meters according to the values of the obtained classes. The pointer meter uses a Hough circle to detect the dial, extracts the scale and the pointer, calculates the angle between the 0 scale line and the pointer, and obtains the reading of the pointer meter. The digital meter extracts the digits by finding the contours of the dial and the digit area and then uses a support vector machine (SVM) to identify the extracted digits and output the readings of the digital meter. Through the test, the mean average precision (mAP) of the recognition model in this study is 93.73%. The absolute error of pointer meter reading is less than 0.1 in general, and the maximum relative error is 0.35%. The accuracy of the digital meter reading is 99.7%. The proposed method can accurately read the value of the instrument and meet the needs of industrial production.
Assessment of Intravenous Antibiotics to Peroral Antibiotics Conversion Practice and Its Associated Factor at University of Gondar Comprehensive Specialized Hospital: Prospective Observational Study
Authors: Tarekegn Getachew Yitayew , Dagnew Samuel Berihun , Wondm Samuel Agegnew , Kebede Bekalu , Ayele Emneteab Mesfin
Published: October 2022

Background. Improper utilization of antibiotics harms the patient, the public, and the economy. The overuse of injections is one of the key factors in the irrational use of medicines. However, little is known about intravenous (IV) to peroral (PO) conversion practice in the Ethiopian healthcare setting, specifically in the Northwest part of Ethiopia. Objective. To assess antibiotics IV to PO conversion practice and its associated factors at the internal medicine ward of the University of Gondar Comprehensive and Specialized Hospital (UOGCSH). Method. A prospective observational study was conducted on 324 study participants who were admitted to the University of Gondar Specialized Hospital from October 3 to November 14, 2021. A systematic random sampling technique was employed to select the study participants. Stata version 14.2 was used for the analysis. Descriptive statistics result was presented using mean and standard deviation. Logistic regression analysis was done to determine the association between independent variables and dependent variables. The association between independent variables and dependent variables was tested at 95% CI andPvalue≤ 0.05 was considered statistical significance. Result. A total of 324 study participants were included in the study, and the mean age of the patients was 41.4 ± 18.6. Of the 324 study participants, 63.3% were male. The most frequently prescribed antibiotics used for empiric treatment were ceftriaxone (45.4%), followed by metronidazole (33.2%), and cloxacillin (11.4%). A total of 34.5.57% of patients who took antibiotics were converted to PO antibiotics. The most frequently converted type of conversion practice was sequential (23.1%), followed by the switch type of conversion (7.4%). Tachypnea, unavailability of medication, higher temperature, hospital stay greater than 10.78-days, and the presence of comorbidity were predictors of IV medications not being converted to PO medications. Conclusion. Intravenous to peroral conversion practice was infrequent. The most frequently applied conversion practice was sequential type conversion practice, followed by switch type of conversion practice. IV to PO conversion practice was significantly associated with tachypnea, unavailability of medication, higher temperature, hospital stay greater than 10.78-days, and comorbidity. Awareness of IV to PO conversion practice and short-term training for healthcare teams is vital for better antibiotic conversion practice.
Symmetrical Peripheral Gangrene: Report of Three Cases
Authors: Acosta Héctor , Forcada Pau , Bonjorn Marta , Mustafa Amer , Pilares Paul , Colomina Jordi
Published: October 2022

Symmetrical peripheral gangrene (SPG) is a rare clinical syndrome characterized by an acute onset of ischemic damage in two or more extremities without obstruction or vasculitis of supplying vessels. Body parts commonly affected include toes, hands, scrotum, and earlobes, increasing the risk of limb amputation and impairing the quality of life. The vascular injury mechanism is disseminated intravascular coagulation. SPG may manifest unpredictably in conditions associated with septic shock, low output states, vasospastic conditions, myeloproliferative disorders, or hyperviscosity syndrome. A review on the topic is presented based on a 3-case series of SPG that required amputation of fingers and toes after the administration of vasopressors in a septic shock context.
Effect of Extraction and Preservation Methods on the Microbiological and Physicochemical Quality of Pentadesma butyracea Butter Produced in a Traditional Area in Benin
Authors: Badoussi Marius Eric , Madode Yann E. , Tchekessi Célestin K. C. , Honfozo Laurenda , Chabi Ifagbémi Bienvenue , Chabi Sika Kamirou , Adjatin Arlette , Hounhouigan Joseph D. , Azokpota Paulin
Published: October 2022

P.butyracea butter, produced by different traditional methods, is often stored for further use in different types of packaging which may affect its quality. The present work aims to evaluate the effect of the production method and the type of packaging used on the physicochemical and microbiological quality of butter during storage. The extraction of Pentadesma butter was first carried out through production monitoring in three repetitions by three different butter producers according to the two most used traditional production methods. Then, butter from production was stored for three months in four types of packaging (aluminium bowls, calabashes, baskets, and black polyethylene bags) in the production environment. The microbiological and physicochemical quality of the stored butter was assessed at 0, 30, 60, and 90 days using normative reference methods. The production method and the type of packaging used had a significant effect on the variation of free fatty acid content (1.54 ± 0.07%–2.6 ± 0.2%), peroxide value (0.96 ± 0.09°meq·O2/Kg–3.9 ± 0.7°meq·O2/Kg), and colour of the butter during storage. In contrast, only the type of packaging material influenced the microbiological characteristics of the butter during storage. After three months of storage, the yeast and mould load was out of the standard range in all packages, i.e., 2.53 ± 0.4 log°CFU/g, 2.9 ± 0.2 log°CFU/g, 4.67 ± 0.2 log°CFU/g, and 1.4 ± 0.2 log°CFU/g for aluminium bowls, calabashes, baskets, and black polyethylene bags, respectively. The aerobic mesophilic germ load was within the standard in black polyethylene bags (3.22 ± 0.08 log°CFU/g), in contrast to the other packages (4.23 ± 0.08 log°CFU/g–6.45 ± 0.13 log°CFU/g). This shows that black polyethylene bags are the best packaging to guarantee the quality of butter. It is important to continue this investigation by storing butter for a longer period of time with more appropriate packaging.
Verification and Validation of Two Hydrodynamic Methods for Simulations
of High Energy Density Physics Problems
Authors: Chiravalle Vincent P. , Atzeni Stefano
Published: October 2022

A 3D verification and validation suite of test problems is presented and
used to evaluate hydrodynamic methods within a radiation hydrodynamics code,
xRAGE. These test problems exercise different levels of complexity, building
towards ICF problems which in addition to hydrodynamics also include three
temperature plasma physics, thermal conduction, and radiation diffusion.
Among the problems in the test suite are the Kidder ball problem, the Verney
shell problem, and a 5-material compression problem, which exercise
different purely hydrodynamic methods implemented within xRAGE. There is
excellent agreement between 2D and 3D XRAGE simulation results and between
the xRAGE results and the benchmark solutions. Two 3D ICF test problems are
also presented, based on an OMEGA direct drive capsule experiment and on a
NIF indirect drive capsule experiment. It is demonstrated that the newer
unsplit hydrodynamic method in xRAGE produces more vorticity relative to the
older default method. For the indirect drive capsule, the 3D simulations are
in reasonable agreement with the experimental values of ion temperature and
neutron production.
Chaotic Honeybees Optimization Algorithms Approach for Traveling Salesperson Problem
Authors: Palominos Pedro , Ortega Carla , Alfaro Miguel , Fuertes Guillermo , Vargas Manuel , Camargo Mauricio , Parada Victor , Gatica Gustavo
Published: October 2022

Due to the difficulty in solving combinatorial optimization problems, it is necessary to improve the performance of the algorithms by improving techniques to deal with complex optimizations. This research addresses the metaheuristics of marriage in honey‐bees optimization (MBO) based on the behavior of bees. The current study proposes a technique for solving combinatorial optimization problems within proper computation times. The purpose of this study focuses on the travelling salesperson problem and the application of chaotic methods in important sections of the MBO metaheuristic. Three experiments were conducted to measure the efficiency and quality of the solutions: (1) MBO with chaos to generate initial solutions (MBO2); (2) MBO with chaos in the workers (MBO3); and (3) MBO with chaos to generate initial solutions and the workers (MBO4). The application of chaotic functions in MBO was significantly better at solving the travelling salesperson problem.
lncRNA DLEU2 Accelerates Oral Cancer Progression via miR-30a-5p/RAP1B Axis to Regulate p38 MAPK Signaling Pathway
Authors: Zhang Wenbo , Wang Yanchun , Xu Pu , Du Yongxiu , Guan Weiwei
Published: October 2022

Background. Oral cancer (OC) is common cancer in the world. Long noncoding RNAs (lncRNAs) have been shown to be involved in cancer regulation, including oral cancer (OC). The aim of this study was to investigate the role of lncRNA deleted in lymphocytic leukemia 2 (DLEU2) in oral cancer. Method. The Gene Expression Omnibus database was used to analyze differentially expressed lncRNA/microRNA (miRNA, miR)/mRNA. The expression levels of DLEU2, miR-30a-5p, and RAP1B in OC cells were detected by RT-qPCR. Dual-luciferase was used to analyze the binding of lncRNA/miRNA/mRNA. Cell Counting Kit-8 was used to measure cell proliferation. Transwell assay was used to inspect cell migration and invasion abilities. Western blot was used to detect MAPK pathway-related protein levels. Result. Our research shows that, in contrast to miR-30a-5p, DLEU2 or RAP1B was upregulated in OC cells, and high expression of DLEU2 or RAP1B was associated with poorer overall survival. Inhibiting the expression of DLEU2 slowed the proliferation and reduced the ability of migration and invasion of Tca8113 and CAL-27 cells. miR-30a-5p was predicted to interact with DLEU2 or RAP1B by bioinformatics, and dual-luciferase analysis confirmed this interaction. Notably, si-DLEU2 suppressed RAP1B expression and protein level, and after overexpression of RAP1B in OC cells, reversal of suppressed DLEU2 expression was observed. Furthermore, the inhibitory effect of si-DLEU2 on MAPK signaling was reversed by overexpression of RAP1B. Therefore, si-DLEU2 regulates MAPK signaling through the miR-30a-5p/RAP1B axis and inhibits OC development. Conclusion. DLEU2 contributed to proliferation, migration and invasion via miR-30a-5p/RAP1B axis to regulate MAPK signaling pathway in OC cells.
Financial Data Mining Model Based on K-Truss Community Query Model and Artificial Intelligence
Authors: Han Zhuhua , Li Feng , Wang Gong
Published: October 2022

With the continuous development of Internet technology and related industries, emerging technologies such as big data and cloud computing have gradually integrated into and influenced social life. Emerging technologies have, to a large extent, revolutionized people’s way of production and life and provided a lot of convenience for people’s life. With the popularity of these technologies, information and data have also begun to explode. When we usually use an image storage system to process this information, we all know that an image contains countless pixels, and these pixels are interconnected to form the entire image. In real life, communities are like these pixels. On the Internet, communities are composed of interconnected parts. Nowadays, in various fields such as image modeling, we still have some problems, such as the problem of recognition rate, and we also found many problems when studying the community structure, which attracts more and more researchers, but the research on community query problems started late and the development is still relatively slow, so designing an excellent community query algorithm is a problem we urgently need to solve. With this goal, and based on previous research results, we have conducted in-depth discussions on community query algorithms, and hope that our research results can be applied to real life.
Functionalization of Carbon Electrodes with Nanotitania by Atomic Layer Deposition
Authors: De Souza Graciano B. , Hotza Dachamir , Janßen Rolf , Furlan Kaline P. , Rambo Carlos R.
Published: October 2022

Carbon fibers are materials with a very high surface area and are interesting for applications such as filters, fire-resistant heat insulation, photocatalysis, and capacitor electrodes. Moreover, thermal burnout can easily remove these fibers, making them ideal templates for high-precision coatings or keeping them within the coated structure, generating nanostructured composites. In this work, two different substrates, carbon felt and bacterial nanocellulose were coated by TiO2 with atomic layer deposition (ALD). After deposition, the templates were pyrolyzed or further removed by burnout in the air. The microstructure evolution of the 3D interlocked-fibers structures was characterized by scanning electron microscopy and nitrogen adsorption surface area after each step. Stable anatase was present as a single TiO2 phase even after heat treatment at 800°C. Moreover, electrochemical impedance spectroscopy and constant current charge-discharge were employed to investigate the electrochemical properties of the samples. Our results show that all samples display a uniform layer after ALD and that the surface area decreases with an increasing number of ALD cycles. After burnout, the 3D structures presented a straw-like appearance to the shells. Nonetheless, both samples presented a power density comparable to a porous NiO/C, with the pyrolyzed bacterial nanocellulose sample displaying a higher pseudocapacitance performance than the carbon-felt samples.
Fundus-Vascular Responses to Color Deviation Caused by Non-Oxidative Blue Filtering
Authors: Cai Jianqi , Hao Wentao , Zeng Shanshan , Li Junkai , Guo Ya , Tan Kai , Kang Yongyin , Huang Yitao , Zhang Yue , Santos Thebano , Qian Cheng , Luo Aiqin
Published: October 2022

Aims. Short-wavelength blue light damaged retina by the oxidative stress in the retinal pigment epithelial (RPE) cells. Filtering blue light from screen could reduce blue hazard, whereas it inevitably altered color-gamut coverage and color-deviation level. Although abnormal fundus-vascular density (FVD) sometimes indicated fundus disease, few researchers noticed its responses to the variation of color-gamut coverage and color-deviation level. Methods. In this study, we performed cellular experiments and analyzed the RPE cell viabilities (CVs) in spectrums with different blue (455-475 nm) ratios to describe the corresponding oxidative-stress levels. Further, we investigated the effects of color-gamut and deviation on FVD variations during the screen-watching task using human factor experiments with 30 participants (university students, including 17 males and 13 females, 21 to 30 years old). Results. RPE CVs were similar in different spectrums, implying that non-oxidative blue filtering hardly contributed to CV improvement. Color-deviation level seems to induce more significant effects on the visual function compared to color-gamut coverage, and MTF and FVD presents similar variation trends during the visual task. Conclusion. Oxidative-free blue filtering contributed little to decrease retinal oxidative stress yet caused color-deviation increase, which caused significant FVD reduction.
PRC2-Mediated Epigenetic Suppression of Type I IFN-STAT2 Signaling Impairs Antitumor Immunity in Luminal Breast Cancer
Authors: Hong Juyeong , Lee Ji Hoon , Zhang Zhao , Wu Yanming , Yang Mei , Liao Yiji , de la Rosa Richard , Scheirer Jessica , Pechacek Douglas , Zhang Nu , Xu Zhenming , Curiel Tyler , Tan Xi , Huang Tim H.-M. , Xu Kexin
Published: October 2022

The immunosuppressive tumor microenvironment in some cancer types, such as luminal breast cancer, supports tumor growth and limits therapeutic efficacy. Identifying approaches to induce an immunostimulatory environment could help improve cancer treatment. Here, we demonstrate that inhibition of cancer-intrinsic EZH2 promotes antitumor immunity in estrogen receptor α–positive (ERα+) breast cancer. EZH2 is a component of the polycomb-repressive complex 2 (PRC2) complex, which catalyzes trimethylation of histone H3 at lysine 27 (H3K27me3). A 53-gene PRC2 activity signature was closely associated with the immune responses of ERα+ breast cancer cells. The stimulatory effects of EZH2 inhibition on immune surveillance required specific activation of type I IFN signaling. Integrative analysis of PRC2-repressed genes and genome-wide H3K27me3 landscape revealed that type I IFN ligands are epigenetically silenced by H3K27me3. Notably, the transcription factor STAT2, but not STAT1, mediated the immunostimulatory functions of type I IFN signaling. Following EZH2 inhibition, STAT2 was recruited to the promoters of IFN-stimulated genes even in the absence of the cytokines, suggesting the formation of an autocrine IFN-STAT2 axis. In patients with luminal breast cancer, high levels of EZH2 and low levels of STAT2 were associated with the worst antitumor immune responses. Collectively, this work paves the way for the development of an effective therapeutic strategy that may reverse immunosuppression in cancer.

Significance:

Inhibition of EZH2 activates a type I IFN-STAT2 signaling axis and provides a therapeutic strategy to stimulate antitumor immunity and therapy responsiveness in immunologically cold luminal breast cancer.