bluuebunny/crossref_metadata_2025 huggingface dataset:
Indigenous Knowledge of Farmers in Breeding Practice and Selection Criteria of Dairy Cows at Chora and Gechi Districts of Ethiopia: An Implication for Genetic Improvements
Authors: Bulcha Gelaye Gebisa , Dewo Oda Gizaw , Desta Mengistu Asrat , Nwogwugwu Chiemela Peters
Published: February 2022

This study assessed the breeding practice and selection criteria of dairy cows in two districts. A total number of 288 structured questionnaires were utilized to gather information from households in the study areas. Logit model, indices, and descriptive statistics were employed for data analysis. Education, marital status, and family size of respondents from Chora district were confirmed as predictors for practicing the controlled mating system and significantly influenced at

p
<
0.05

. The odds of practicing the controlled mating system by educated and married farmers in Chora district were 10.01 and 4.82 times higher compared to uneducated and unmarried farmers, respectively, and also, for every additional increase in family size, they increased by the factor of 1.21. Educational and marital status of farmers in Gechi district also influenced the use of controlled mating. The odds of performing controlled mating based on the educational level and marital status of the farmers were higher among educated and married individuals. Based on indigenous knowledge, teat size, udder size, and pelvic width were the 1st three ranked traits used as major selection criteria of dairy cows in Gechi district, whereas body length was the 1st among others in Chora district. This finding indicated that the combination of indigenous knowledge with modern science is important to improve cow’s genetics. The study suggests that mating systems and selection criteria should be considered as baseline information for designing the genetic improvement programs.
Safety Assessment of Glucose-Lowering Drugs and Importance of Structured Education during Ramadan: A Systematic Review and Meta-Analysis
Authors: Shiju Rashmi , Akhil Ayesha , Thankachan Smitha , Tuomilehto Jaakko , Al Arouj Monira , Bennakhi Abdullah
Published: February 2022

Background. Ramadan is the sacred month of the Islamic Hijri (lunar) calendar, and during this entire month, healthy adult Muslims abstain from eating and drinking from dawn to sunset. Muslims with Type 2 Diabetes Mellitus (T2DM) who choose to fast during Ramadan encounter major risks such as hypoglycemia, hyperglycemia, diabetic ketoacidosis, dehydration, and thrombosis. Although patients with poor glycemic control and on multiple insulin injections are at high risk and exempt from fasting, many still insist on it. Thus, healthcare professionals play a pivotal role in managing diabetes-related complications in patients who fast during Ramadan. However, there is a lack of standard guidelines to be followed in association with structured education and administration of drugs and dosage. Therefore, we performed a systematic review and meta-analysis of the literature to determine the safety and efficacy of different classes of drugs and the importance of structured education during Ramadan. Methods. In this review, an extensive PubMed search was performed to obtain literature on T2DM patients who fast during the month of Ramadan until the year 2020. Preference was given to fully downloadable articles. The articles were extracted based on the eligibility criteria. The extracted data were analyzed using Review Manager software version 5.3. Results. A total of 32 articles were included for the review and 7 studies for meta-analysis. Majority of the studies demonstrated the importance of structured education either as a group session or as a one-on-one session with the healthcare professionals in preventing diabetes-related risks during Ramadan. As far as glucose-lowering drugs are concerned, DPP-4 inhibitor combined with metformin remains the drug of choice for T2DM patients who fast during Ramadan. The newer class of glucose-lowering agents appear to lower the risk of hypoglycemia in comparison with sulphonylureas, while among sulphonylureas gliclazide is relatively safe. The meta-analysis indicates that DPP-4 inhibitors would significantly reduce the risk of hypoglycemia as compared to sulphonylurea (odds ratio=0.38, 95% CI: 0.26 to 0.55,p<0.00001). Conclusion. The results of our systematic review show that structured education and counselling by healthcare professionals can be an effective tool in preventing complications associated with fasting during Ramadan in people with T2DM. Additionally, the safest class of oral glucose-lowering drugs preferred during Ramadan fasting in T2DM patients is DPP-4 inhibitors.
Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches
Authors: Teoh Yun Xin , Lai Khin Wee , Usman Juliana , Goh Siew Li , Mohafez Hamidreza , Hasikin Khairunnisa , Qian Pengjiang , Jiang Yizhang , Zhang Yuanpeng , Dhanalakshmi Samiappan
Published: February 2022

Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that can be captured by imaging modalities and translated into imaging features. Observing imaging features is a well-known objective assessment for knee OA disorder. However, the variety of imaging features is rarely discussed. This study reviews knee OA imaging features with respect to different imaging modalities for traditional OA diagnosis and updates recent image-based machine learning approaches for knee OA diagnosis and prognosis. Although most studies recognized X-ray as standard imaging option for knee OA diagnosis, the imaging features are limited to bony changes and less sensitive to short-term OA changes. Researchers have recommended the usage of MRI to study the hidden OA-related radiomic features in soft tissues and bony structures. Furthermore, ultrasound imaging features should be explored to make it more feasible for point-of-care diagnosis. Traditional knee OA diagnosis mainly relies on manual interpretation of medical images based on the Kellgren–Lawrence (KL) grading scheme, but this approach is consistently prone to human resource and time constraints and less effective for OA prevention. Recent studies revealed the capability of machine learning approaches in automating knee OA diagnosis and prognosis, through three major tasks: knee joint localization (detection and segmentation), classification of OA severity, and prediction of disease progression. AI-aided diagnostic models improved the quality of knee OA diagnosis significantly in terms of time taken, reproducibility, and accuracy. Prognostic ability was demonstrated by several prediction models in terms of estimating possible OA onset, OA deterioration, progressive pain, progressive structural change, progressive structural change with pain, and time to total knee replacement (TKR) incidence. Despite research gaps, machine learning techniques still manifest huge potential to work on demanding tasks such as early knee OA detection and estimation of future disease events, as well as fundamental tasks such as discovering the new imaging features and establishment of novel OA status measure. Continuous machine learning model enhancement may favour the discovery of new OA treatment in future.
Protein Supplement Perceptions, Use, and Associated Performance in Young Lebanese Resistance-Training Athletes
Authors: Saleh Khadije K. , Julien Sofi G.
Published: February 2022

The aims of this study were first to evaluate the nutritional knowledge, perception, and source of nutrition information among resistance-trained individuals consuming protein supplements (PS), to determine whether a correlation exists between nutrition-related knowledge and the use of PS, and finally to compare the impact of PS use among participants classified as nonprotein supplement users (NPSUs) and protein supplement users (PSUs). A cross-sectional study was conducted among a highly selected group of resistance-specialized trainees (RSTs). Among the 100 RST participants recruited, the Internet and coaches were the most common source of nutritional information. About one-third of participants believed that there were no health risks after consuming PS. Both NPSU and PSU exhibit performance improvement that was significantly lessened in PSU compared to NPSU. This study demonstrated that RST may have misconceptions regarding the benefits of PS usage to increase strength. Our data also suggest a shortage of knowledge about PS and confirm that PSUs lack proper professional guidance. These findings highlight the need for proper monitoring to ensure adequate perception, awareness, and safety in the Lebanese sports sector.
Assessment of Suspected Breast Lesions in Early-Stage Triple-Negative Breast Cancer during Follow-Up after Breast-Conserving Surgery Using Multiparametric MRI
Authors: Sad Lamiss Mohamed Abd El Aziz , Dabees Naglaa Lofty , Mohamed Dareen Abd El-Aziz , Tageldin Amr , Younis Samar Galal
Published: February 2022

Background. The local recurrence rate of triple-negative breast cancer (TNBC) can be as high as 12%.The standard treatment for early-stage TNBC is breast-conserving surgery (BCS), followed by postoperative radiotherapy with or without chemotherapy. However, detection of the local recurrence of the disease after radiotherapy is a major issue. Objective. The aim of this study was at investigating the role of dynamic and functional magnetic resonance imaging (MRI) during follow-up after BCS and radiotherapy with/without chemotherapy to differentiate between locoregional recurrence and postoperative fibrosis. Patients and Methods. This prospective study was conducted at the oncology, radiology, and pathology departments, Tanta University. It involved 50 patients with early-stage TNBC who were treated with BCS, followed by radiotherapy with/without chemotherapy. The suspected lesions were evaluated during the follow-up period by sonomammography. All patients were subjected to MRI, including conventional sequences, diffusion-weighted imaging (DWI), and dynamic postcontrast study. Results. Ten cases were confirmed as recurrent malignant lesions. After contrast administration, they all exhibited irregular T1 hypodense lesions of variable morphology with diffusion restriction and positive enhancement. Eight cases displayed a type III curve, while two showed a type II curve. Histopathological assessment was consistent with the MRI findings in all eight cases. The combination of the data produced by DWI-MRI and dynamic contrast-enhanced (DCE) MRI resulted in 100%sensitivity, 92.5% specificity, 90.9% positive predictive value, 100% negative predictive value, and 98% accuracy. Conclusion. Combination of DWI-MRI and DCE-MRI could have high diagnostic value for evaluating postoperative changes in patients with TNBC after BCS, followed by radiotherapy with/without chemotherapy. Trial Registrations. No trial to be registered.
Energy Economy and Energy Structure Optimization Countermeasures Based on Big Data Mining
Authors: Zhang Fangcheng , Lin Hong
Published: February 2022

The impact of energy on the economy must be examined not only from an energy structure standpoint but also from an economic structure standpoint, as there is a close relationship between energy structure and energy economy. To avoid the negative effects of energy consumption on the economy, it is also necessary to assess the constraints to the development of the energy economy and then optimize the energy economy and energy structure to achieve rapid economic growth. The research object in this paper is a data center powered by renewable energy, and the resource and energy consumption management model and algorithm are examined. Different adaptive scheduling algorithms are designed for different emphases, and an approximate application scheduling algorithm for renewable energy utilization based on DM is proposed. When building a data center, researching the resource management and energy consumption management strategies can help determine the best energy access scheme. It can provide the necessary reference for specific planning, such as software and hardware configuration, equipment parameter determination, and power access, resulting in lower construction and operation costs.
Ipsilateral Vestibular Schwannoma after Cochlear Implantation
Authors: Tüpker S. , Ay N. , Scholtz L. U. , Gehl H. B. , Mautner V. F. , Goon P. , Sudhoff H. , Todt I.
Published: February 2022

Objective. The vestibular schwannoma incidence rate is approximately 4.2 per 100,000/year. Thus far, about 700,000 cochlear implantations have been performed worldwide; therefore, the occurrence of vestibular schwannoma postcochlear implantations can be assumed to be infrequent. Recent developments allow safe observation and surveillance of the implanted-side internal auditory canal (IAC) and cochlea by magnetic resonance imaging (MRI), even after cochlear implantation. Patients. A 71-year-old woman with sudden hearing loss and a contralateral vestibular schwannoma without clinical and genetic signs of neurofibromatosis type II. Intervention(s). Ipsilateral cochlear implantation and contralateral vestibular schwannoma extirpation with regular tumor follow-up. Main Outcome Measure(s). Comparison of ipsilateral pre and postcochlear implantation 3T MRI T1 GAD. Results. We observed a tumor growing at the fundus of the internal auditory canal 1 year after cochlear implantation on the ipsilateral side. Although first detected after cochlear implantation beside a known vestibular schwannoma on the contralateral side, a scan slice thickness of 2 mm cannot fully exclude the preoperative persistence of a small tumor. Based on the clinical findings and after genetic exclusion of NFII, the patient was classified as a NFII mosaic type. Conclusion. Even after cochlear implantation, tumors in the IAC causing vertigo, facial palsy, and affecting the audiologic outcome can be detected by MRI. The MRI slice thickness used before cochlear implantation should be under 2 mm.
Automatic Building Extraction on Satellite Images Using Unet and ResNet50
Authors: Alsabhan Waleed , Alotaiby Turky
Published: February 2022

Recently, settlement planning and replanning process are becoming the main problem in rapidly growing cities. Unplanned urban settlements are quite common, especially in low-income countries. Building extraction on satellite images poses another problem. The main reason for the problem is that manual building extraction is very difficult and takes a lot of time. Artificial intelligence technology, which has increased significantly today, has the potential to provide building extraction on high-resolution satellite images. This study proposes the differentiation of buildings by image segmentation on high-resolution satellite images with U-net architecture. The open-source Massachusetts building dataset was used as the dataset. The Massachusetts building dataset includes residential buildings of the city of Boston. It was aimed to remove buildings in the high-density city of Boston. In the U-net architecture, image segmentation is performed with different encoders and the results are compared. In line with the work done, 82.2% IoU accuracy was achieved in building segmentation. A high result was obtained with an F1 score of 0.9. A successful image segmentation was achieved with 90% accuracy. This study demonstrated the potential of automatic building extraction with the help of artificial intelligence in high-density residential areas. It has been determined that building mapping can be achieved with high-resolution antenna images with high accuracy achieved.
[Retracted] Current Status of Malignant Tumors after Organ Transplantation
Authors: Shen Bairu , Cen Zhuofei , Tan Minghua , Song Changshan , Wu Xuhui , Wang Jiaqing , Huang Minqian
Published: February 2022

Objective. To analyze the diagnosis and treatment of patients with concomitant malignant tumors after organ transplantation by compiling data from organ transplantation patients. Methods. By searching CNKI and PubMed databases, we made a systematic analysis of the studies of postorgan transplantation complicating malignant tumors in the last decade. Results. There were 10 articles on malignant tumors after renal transplantation, 8 articles on liver transplantation, 2 articles on heart transplantation, and 1 article on lung transplantation. The incidence of malignant tumors complicating renal transplantation is 10.4% in Europe, with skin cancer and Kaposi’s sarcoma being common; the incidence in the United States is 3.4%, with PTLD having the highest incidence; the incidence of malignant tumors is relatively lowest in Asia, with gastrointestinal malignancies being the main ones. The mean time to complication of malignancy after renal transplantation is 3.83 years. The incidence of concurrent malignancies after liver transplantation is 8.8% in Europe, where skin cancer and Kaposi’s sarcoma are common; 5.6% in Asia, where gastrointestinal tract tumors are prevalent; and 4.5% in the United States, where gastrointestinal tract tumors, PTLD, and hematologic diseases are predominant. The mean time to complication of malignancy after liver transplantation is 4.79 years. The incidence of malignancy after heart transplantation is 6.8‐10.7%. The incidence of malignancy after lung transplantation is about 10.1%. Minimization of immunosuppression or modification of immunosuppression regimens may be a key component of cancer prevention. mTOR inhibitors and phenolate (MMF) reduce the incidence of de novo malignancies in patients after solid organ transplantation. Surgical treatment improves survival in patients with early malignancies. The use of external beam radiation therapy in the treatment of hepatocellular carcinoma is limited due to the risk of radiation liver disease. Conclusions. The risk of concomitant malignancy needs to be guarded for 5 years of immunosuppressive therapy after organ transplantation surgery. Adjusting the immunosuppressive treatment regimen is an effective way to reduce concurrent malignancies. Systemic chemotherapy or radiotherapy requires vigilance against the toxic effects of drug metabolism kinetics on the transplanted organ.
Material Innovation of Animation Modeling Design Based on Visual Symbol Theory
Authors: Cao Xuerui
Published: February 2022

Character modeling is an important link in animation design, and it is one of the keys to determining whether an animation is successful or not, as well as determining the value of animation and related industries. This paper examines the role of material innovation in the development of animation art, as well as the impact of various materials on animation production technology and design style, using the visual symbol theory as a guide. GA (genetic algorithm) is used in the comic design process to improve the fidelity and efficiency of the artwork. GA performs data training of multiple components; selection and crossover operations are carried out continuously according to the fitness threshold; and the particle swarm optimization strategy is added. This algorithm increases the rate of design reuse and efficiency, as well as the ability to determine the best component combination scheme.
OX40-Fc Fusion Protein Alleviates PD-1-Fc-Aggravated Rheumatoid Arthritis by Inhibiting Inflammatory Response
Authors: Huang Yanyan , Lin Shudian , Zhan Feng , Xiao Lu , Zhan Yuwei , Wang Ru
Published: February 2022

Background. Researches have confirmed that the abnormal signals of OX40 and PD-1 lead to the changes of T cell biological behavior, thus participating the immunopathological process of RA. However, the pathogenesis of RA immunopathological process has not been clarified yet. Methods. 30 DBA/1 mice were randomly divided into 5 groups (6 mice per group): control group, collagen-induced arthritis (CIA) group, PD-1-Fc/CIA group, OX40-Fc/CIA group, and PD-1-Fc + OX40-Fc/CIA group. The pathological changes in mice joints were observed by H&E staining. The proportion of CD4+ T, CD8+ T, CD28+, and CD19+ cells in peripheral blood mononuclear cells (PBMCs) was detected by flow cytometry. Serum inflammatory factors (CRP, IL-2, IL-4, IL-1β, INF-γ) and bone metabolism-related genes (CTX-I, TRACP-5b, BALP) were detected by ELISA assay. Western blotting was applied to measure the NF-κB signaling pathway-related protein (p-IKKβ, p-IκBα, p50) expression in synovial tissue of mice joint. Results. Compared with the control group, CIA mice showed significant increases in arthritis score and pathological score. In the CIA group, a marked decrease was identified in the proportion of CD8+ T, CD19+, and CD68+ cells. Additionally, the CIA group was associated with upregulation of secretion of inflammatory factors in serum and expression of bone metabolism-related genes and NF-κB pathway-related proteins. Compared with the CIA group, the same indexes above showed a further aggravation in the PD-1-Fc group while all indexes improved in the OX40-Fc group. Besides, OX40-Fc fusion protein slowed down significantly the further deterioration of CIA mouse pathological process caused by PD-1-Fc fusion protein. Conclusion. OX40-Fc fusion protein alleviates PD-1-Fc-aggravated RA by inhibiting inflammatory response. This research provides biological markers with clinical significance for diagnosis and prognosis of RA, as well as offers theoretical and experimental foundation to the new targets for immune intervention.
Polyacetylenes from Codonopsis lanceolata Root Induced Apoptosis of Human Lung Adenocarcinoma Cells and Improved Lung Dysbiosis
Authors: Wang Meng-Chuan , Wu Yu-Fang , Yu Wen-Ying , Yu Bing , Ying Hua-Zhong
Published: February 2022

Codonopsis lanceolata is a perennial smelly herbaceous plant and widely employed for the treatment of various lung cancer and inflammation. However, the anticancer substances in C. lanceolata and their underlying mechanisms had not been well clarified. In this study, six compounds were obtained from the water extracts of C. lanceolata polyacetylenes (CLP) and then identified as syringin, codonopilodiynoside A, lobetyol, isolariciresinol, lobetyolin, and atractylenolide III. Treatment with CLP remarkably suppressed the cell proliferation, colony formation, migration, and invasion of A549 cells. Synergistic effects of lobetyolin and lobetyol were equivalent to the antiproliferative activities of CLP, while other compounds did not have any inhibition on the viabilities of A549 cells. CLP also reduced the expression of Ras, PI3K, p‐AKT, Bcl‐2, cyclin D1, and CDK4 but increased the expression of Bax, GSK‐3β, clv‐caspase‐3, and clv‐caspase‐9, which could be reversed by the PI3K activator 740YP. Furthermore, CLP retarded the growths of tumor and lung pathogenic bacteria in mice. It demonstrated that lobetyolin and lobetyol were the main antitumor compounds in C. lanceolata. CLP induced cell apoptosis of lung cancer cells via inactivation of the Ras/PI3K/AKT pathway and ameliorated lung dysbiosis, suggesting the therapeutic potentials for treating human lung cancer.
A Cohort Study to Assess Cognitive Impairment and Its Effects on Older Patients in the Orthopedic Rehabilitation
Authors: Zhang Han , Pang Bo , Ma Zheng , Dong Huimei , He Hongyi , Jiang Lan
Published: February 2022

Background. The cognitive role of older patients is regularly not investigated in orthopedic rehabilitation, after the elective as well as the nonelective operation. The objective of this research is to investigate the cognitive disorder and its influence over the duration of stay along with the functional consequences of the older patients who were admitted to orthopedic rehabilitation. Material and Methods. The inclusion criteria for this study were the patients with age above 50 years; who were admitted with the detection of orthopedic impairment and the surgery both elective and nonelective, investigated utilizing the MoCA (Montreal Cognitive Assessment) over admission, MBI (Modified Barthel Index), and FIM (Function Independent Measure) over admission and discharge status; and were discharged from the hospital. The demography, as well as the clinical data, comprising of the duration of stay, age and the detection was also reported. Result. Of the 109 admitted patients, 80 patients were included in the study where n = 47 (58.75%) patients were females and n = 33 (41.25%) were males. The age group range was 50 to 94 years with a mean age of 78.5 years (SD = 8.27). The diagnostic groups included for the study were fractured neck of femur (n = 34; 42.5%), orthopedic surgery (n = 22; 27.5%), and other orthopedic surgery (n = 24; 30%). The mean duration of rehabilitation stay was reported as 34 (4.39), where the MoCA was reported as 22.17 (2.44); functional independence measures were as follows: motor admission as 53.97 (7.55), motor discharge as 76.27 (5.35), cognitive admission as 30.71 (1.99), and cognitive discharge as 31.85 (1.94). Here, the diagnosis was done over the fractured neck of the femur (i.e., NOF being 34 (42.5%), elective surgeries 22 (27.5%), and other orthopedic as 24 (30%)). Conclusion. An excessive percentage of older-age patients in a rehabilitation unit with elective as well as nonelective diagnoses comprises the cognitive disorder. The cognitive screening was advised for all the older age patients in the rehabilitation units to report a specific rehabilitation plan to enhance the consequences along with the duration of stay. There is further study required to explore different cognitive strategies to enhance the rehabilitation consequences among older-age orthopedic patients.
An Optimized Framework for Breast Cancer Classification Using Machine Learning
Authors: Michael Epimack , Ma He , Li Hong , Qi Shouliang
Published: February 2022

Breast cancer, if diagnosed and treated early, has a better chance of surviving. Many studies have shown that a larger number of ultrasound images are generated every day, and the number of radiologists able to analyze this medical data is very limited. This often results in misclassification of breast lesions, resulting in a high false‐positive rate. In this article, we propose a computer‐aided diagnosis (CAD) system that can automatically generate an optimized algorithm. To train machine learning, we employ 13 features out of 185 available. Five machine learning classifiers were used to classify malignant versus benign tumors. The experimental results revealed Bayesian optimization with a tree‐structured Parzen estimator based on a machine learning classifier for 10‐fold cross‐validation. The LightGBM classifier performs better than the other four classifiers, achieving 99.86% accuracy, 100.0% precision, 99.60% recall, and 99.80% for the FI score.
Application of Deep Learning Technology in Glioma
Authors: Hu Guangdong , Qian Fengyuan , Sha Longgui , Wei Zilong
Published: February 2022

A common and most basic brain tumor is glioma that is exceptionally dangerous to health of various patients. A glioma segmentation, which is primarily magnetic resonance imaging (MRI) oriented, is considered as one of common tools developed for doctors. These doctors use this system to examine, analyse, and diagnose appearance of the glioma’s outward for both patients, i.e., indoor and outdoor. In the literature, a widely utilized approach for the segmentation of glioma is the deep learning-oriented method. To cope with this issue, a segmentation of glioma approach, i.e., primarily on the convolution neural networks, is developed in this manuscript. A DM-DA-enabled cascading approach for the segmentation of glioma, which is 2DResUnet-enabled model, is reported to resolve the problem of spatial data acquisition of insufficient 3D specifically in the 2D full CNN along with the core issue of memory consumption of 3D full CNN. For gliomas segmentation at various stages, we have utilized multiscale fusion approach, attention, segmentation, and DenseBlock. Moreover, for reducing three dimensionalities of the Unet model, a sampling of fixed region is used along with multisequence data of the glioma image. Finally, the CNN model has the ability of producing a better segmentation of tumor preferably with minimum possible memory. The proposed model has used BraTS18 and BraTS17 benchmark data sets for fivefold cross-validation (local) and online evaluation preferably official, respectively. Evaluation results have verified that edema’s Dice Score preferable average, enhancement, and core areas of the segmentation of the glioma with DM-DA-Unet perform exceptionally well on the validation set of BraTS17. Finally, average sensitivity was observed to be high as well, which is approximately closer to the best segmentation model and its effect on the validation set of BraTS1 and has segmented gliomas accurately.
Solving Capacitated Vehicle Routing Problem by an Improved Genetic Algorithm with Fuzzy C-Means Clustering
Authors: Zhu Ji
Published: February 2022

Aiming at solving the vehicle routing problem, an improved genetic algorithm based on fuzzy C-means clustering (FCM) is proposed to solve the vehicle routing problem with capacity constraints. On the basis of genetic algorithm, the FCM algorithm is used to decompose the large-scale vehicle routing optimization problem into small-scale subproblems, which can effectively improve the efficiency of the algorithm. At the same time, a generation method of the initial solution to CVRP problem is designed. The improved algorithm has good robustness and can also reduce the possibility of falling into local optimization in the search process. Finally, a simulation example is provided to verify the efficiency and superiority of the proposed algorithm.
[Retracted] Detection Method of Limb Movement in Competitive Sports Training Based on Deep Learning
Authors: Qin Chunlin , Huo Shenglu
Published: February 2022

Traditional methods have the problems of insufficient accuracy and slow speed in human posture detection. In order to solve the above problems, a limb movement detection method in competitive sports training based on deep learning is proposed. The force change parameters of sports limb movements in the process of sports are computed to achieve the detection of limb movements in competitive sports training, and the limb movement characteristics in competitive sports training are extracted using a deep learning algorithm. The experimental results show that the limb movement detection method based on deep learning in competitive sports training has significantly higher detection accuracy and faster speed.
The Social Public Issues Analysis Model Based on Deep Learning
Authors: Gu Yanqiong , Shi Jianyong
Published: February 2022

To improve the governance effect of public communities and protect community security, combined with the basic principles and network structure of CNN network in deep learning, a community security risk prediction model based on improved single-channel CNN network and decision tree is constructed. The experimental results show that expanding the single channel to the multichannel network greatly extends the receptive field of CNN network. Simultaneously, the accuracy of the prediction model is improved, which is as high as 87.7%. After inputting the output values of every single model into the comprehensive model, the prediction accuracy of the comprehensive model is improved by 4.8%. The feasibility and effectiveness of this method are further demonstrated.
Effect of the Imperfection of Open-End Yarn (Thin, Thick, and Nep Place) on Air Permeability of Plain Woven Fabric
Authors: Liyew Erkihun Zelalem
Published: February 2022

Wearing clothes is an intermediate channel by exchange of air released from human bodies and environments to bring breathing stability and to control body temperature. Air permeability is an expression describing the properties of a fabric that permit the passage of air through the fabric’s interstices. It has been found that there are many factors that can affect the air permeability of a fabric comfort. Several early studies of air permeability of different materials showed that different factors affect air permeability and breathability of fabrics, and some of them are imperfections of yarns (thick, thin, and nep place) which are introduced on the surface of the fabric that originated from the appearance of the yarn. In this experiment, the yarn and fabric samples are collected from five different spinning mills which have an identical warp yarn linear density of 20 Ne regardless of the weft linear density, and the fabric was constructed from those selected yarns by using the thread set of 28 ends per centimeter and 20 picks per centimeter. The experiment was conducted by measuring the imperfection of each code of yarn on USTER statistics and air permeability of the fabric with respect to the thin, thick, and nep place/km of the yarn and fabric cover. The impacts of each factor were analyzed, and the relationships of each parameter were stated on the graph. The results were discussed by using the design of the experiment by quadratic and linear models to the response of air permeability and fabric cover, respectively, and the results showed that there is a direct impact of thin, thick, and neps of the yarn on the ability of the fabric to permeate air.
[Retracted] On Qp‐Closed Sets in Topological Spaces
Authors: Zhou Huan , Hammad O. G. , Khalil Ahmed Mostafa
Published: February 2022

In the present paper, we will propose the novel notions (e.g., Qp‐closed set, Qp‐open set, Qp‐continuous mapping, Qp‐open mapping, and Qp‐closed mapping) in topological spaces. Then, we will discuss the basic properties of the above notions in detail. The category of all Qp‐closed (resp. Qp‐open) sets is strictly between the class of all preclosed (resp. preopen) sets and gp‐closed (resp. gp‐open) sets. Also, the category of all Qp‐continuity (resp. Qp‐open (Qp‐closed) mappings) is strictly among the class of all precontinuity (resp., preopen (preclosed) mappings) and gp‐continuity (resp. gp‐open (gp‐closed) mappings). Furthermore, we will present the notions of Qp‐closure of a set and Qp‐interior of a set and explain some of their fundamental basic properties. Several relations are equivalent between two different topological spaces. The novel two separation axioms (i.e., Qp‐ℝ0 and Qp‐ℝ1) based on the notion of Qp‐open set and Qp‐closure are investigated. The space of Qp‐ℝ0 (resp., Qp‐ℝ1) is strictly between the spaces of pre‐ℝ0 (resp., pre‐ℝ1) and gp‐ℝo (resp., gp‐ℝ1). Finally, some relations and properties of Qp‐ℝ0 and Qp‐ℝ1 spaces are explained.
Consent for Delivery Room Studies: What Can Be Learned from Perceptions of Parents
Authors: den Boer Maria C. , Houtlosser Mirjam , Witlox Ruben S. G. M. , van Zanten Henriëtte A. , de Vries Martine C. , te Pas Arjan B.
Published: February 2022

Background: Obtaining ethically valid consent to participate in delivery room (DR) studies from parents facing an imminent premature birth can be challenging. This study aims to provide insight into parental experiences with and perceptions of consent for DR studies. Methods: Semistructured interviews were conducted with parents of very and extreme preterm infants. Interviews were audio-recorded, transcribed, and analyzed using the qualitative data analysis software Atlas. ti V.8.4. Results: Twenty-five parents were interviewed. Despite being in an emotional and stressful situation, most parents considered being approached for DR studies as valuable. According to parents, this was mostly due to appropriate timing and communication, compassion, and investigators not being obtrusive. Interviewed parents generally decided to accept or decline study participation based on perceived risk. Parents differed widely in how risk of specific study interventions was perceived, but agreed on the fact that parental consent is needed for DR studies that involve risk. There was no consensus among parents on deferred consent for DR studies running at our NICU. However, parents considered deferred consent appropriate for observational studies. Furthermore, it became clear that parental misunderstanding of various aspects of DR studies, including aims, the concept of randomization, and risk associated with specific interventions, was common. Conclusions: Insight into parental perceptions of consent for DR studies allowed us to determine areas where the validity of parental consent can be improved. Further research on parental perspectives for consent for DR studies will allow us to establish consent procedures that are considered both valid and valuable.
Correlations between Hand Dexterity and Bimanual Coordination on the Activities of Daily Living in Older Adults with Mild Cognitive Impairment
Authors: Rattanawan Prathomchai
Published: February 2022

Background/Aims: Many motor impairments are present in older adults with cognitive decline. One of them is the impairment of hand dexterity and bimanual coordination that result in poor functional ability in the activities of daily living (ADL). This study investigated the effects of hand dexterity and bimanual coordination declination on the sub-domains of ADL in older adults with mild cognitive impairment (MCI). Methods: Thirty-one senior individuals with MCI were recruited in this study. The Purdue Pegboard Test was used to measure hand dexterity, and bimanual coordination was assessed by the continuous circle-drawing task. Their ADL were assessed with the General Activity Daily Living questionnaire. Results: The correlations analysis showed an association between the dominant hand and bimanual dexterity with the domestic domain of ADL and all conditions of hand dexterity with the complex domain of ADL. Moreover, the multiple regression analysis showed that the predictor of the greatest effect for domestic and complex domains was dominant hand dexterity. Discussion/Conclusion: These results revealed that dominant hand dexterity strongly affected domestic and complex ADL in older adults with MCI. There were age-related changes regarding lateral asymmetrical motor reduction, especially in cognitive tasks. However, complex tasks involving cognitive function may need dominant, nondominant and bimanual hand dexterity.
Preliminary Comparison of Endoscopic Brush and Net Catheters as the Sampling Tool to Analyze the Intestinal Mucus in the Rectum with Ulcerative Colitis Patients
Authors: Nakamura Masanao , Maeda Keiko , Yamamoto Kenta , Yamamura Takeshi , Sawada Tsunaki , Ishikawa Eri , Kakushima Naomi , Furukawa Kazuhiro , Iida Tadashi , Mizutani Yasuyuki , Ishikawa Takuya , Ohno Eizaburo , Honda Takashi , Ishigami Masatoshi , Kawashima Hiroki
Published: February 2022

Background: The pathophysiology of ulcerative colitis (UC) remains unclear, but early lesions on the colorectal mucosal surface may play an important role in its etiology. Intestinal mucus samples, including inner and outer layers, are collected by net or brush catheters, but the quality of the samples obtained by each method has not been fully investigated. Objective: The purpose of this study was to compare the microbiome and protein content of intestinal mucus collected by net and brush catheters during colonoscopy. Methods: Intestinal mucus samples from the lower rectum of 4 patients with UC were collected using a net catheter, a brush catheter, and intestinal fluid suction. Microbiome and protein content were analyzed using 16S rRNA gene sequencing and mass spectrometry. Results: The patients demonstrated significant differences in microbiome alpha diversity (p < 0.05), but this difference was not observed between the sampling methods. Net catheter samples demonstrated higher total protein concentrations than brush catheter samples. The brush catheter group had more Lachnospira, a butyrate-producing bacterium, when compared to the net group. The brush catheter group also had more oral bacteria of Staphylococcus and Dialister in those with active phase when compared to the net group. Conclusions: Brush catheters are more likely to collect the intestinal mucus inner layer, whereas net catheters are more likely to collect larger samples that include the outer mucus layer, as well as the intestinal fluid. Two sampling methods with different types of collection of the mucosa may lead to different results among patients with mucosal vulnerabilities.
Safety and Efficacy of Self-Expandable Metallic Stent Placement Using Low Radial Force Stent for Malignant Dysphagia after Radiotherapy
Authors: Ishioka Mitsuaki , Yoshio Toshiyuki , Sasaki Takashi , Tamashiro Atsuko , Yoshizawa Natsuko , Suzuki Keigo , Tokura Junki , Namikawa Ken , Tokai Yoshitaka , Yoshimizu Shoichi , Horiuchi Yusuke , Ishiyama Akiyoshi , Hirasawa Toshiaki , Chin Keisho , Ogura Mariko , Sasahira Naoki , Fujisaki Junko
Published: February 2022

Introduction: We aimed to investigate the safety and efficacy of self-expandable metallic stent (SEMS) placement in patients with prior radiotherapy (RT) using the Niti-S stent, which is characterized by low radial force, in comparison to patients without prior RT. Methods: A consecutive series of 83 patients who were treated by SEMS placement using Niti-S stent for severe malignant esophageal obstruction or fistula were enrolled. The adverse event rates and efficacy were retrospectively compared between patients with/without prior RT before SEMS placement (RT group [n = 32] versus non-RT group [n = 51]). Results: The incidence rate of major adverse events in the RT group was 6.3% and was not significantly different from that in the non-RT group (5.9%, p = 0.95). Among the RT group, 84.4% were able to resume oral intake within a median of 2 days. Among the patients with fistula, 78.6% could resume oral intake and survive for 73 days after SEMS placement. Cox proportional hazard regression analysis identified significant factors affecting overall survival to be prior RT (hazard ratio [HR]: 1.96), low performance status (HR: 3.87), and subsequent anticancer treatment after SEMS placement (HR: 0.41). However, compared to the non-RT group, the RT group had received longer duration of anticancer treatment before SEMS placement and a lower rate of subsequent anticancer treatment after SEMS placement. Conclusions: With the Niti-S stent, the incidence of major adverse events was sufficiently low even for patients after RT. SEMS with low radial force would be an effective palliative treatment option for patients, regardless of prior RT.
Oral Corticosteroids Impair Mucin Production and Alter the Posttransplantation Microbiota in the Gut
Authors: Okafuji Hirofumi , Iida Noriho , Kitamura Kazuya , Seishima Jun , Wang Ziyu , Yutani Masahiro , Yoshio Takatoshi , Yamashita Taro , Sakai Yoshio , Honda Masao , Yamashita Tatsuya , Fujinaga Yukako , Shinkura Reiko , Hamaguchi Yasuhito , Mizukoshi Eishiro , Kaneko Shuichi
Published: February 2022

Introduction: Gut microbiota alterations cause inflammation in patients with ulcerative colitis (UC). Fecal microbiota transplantation (FMT) enables manipulating the microbiota’s composition, but the mechanisms underlying colonization of the posttransplantation microbiota are poorly understood. Methods: In this open-label, nonrandomized study, the FMT efficacy and changes in the gut microbiota were evaluated in 8 UC patients with mild-to-moderately active endoscopic colonic lesions. Compositional changes in the fecal and mucosal microbiotas between donors and recipients were examined via 16S rRNA-based sequencing. To investigate the effects of oral corticosteroids on microbiota colonization, FMT was performed in germ-free prednisolone (PSL)-administered mice to examine the factors determining colonization. Results: Four UC patients achieved clinical remission (CR) after FMT, and 3 also achieved endoscopic remission. The fecal microbiotas of the CR patients changed similar to those of the donors after FMT. The mucin-coding gene, MUC2, was less expressed in the colons of the PSL-dependent patients than in the PSL-free patients. In the mice, PSL treatment decreased the fecal mucin production and altered the posttransplantation fecal microbiota composition. Adding either exogenous mucin or the mucin secretagogue, rebamipide, partially alleviated the PSL-induced dysbiosis of the gut microbiota. Administering rebamipide with FMT from healthy donors relieved inflammation in mice with Enterococcus faecium-induced colitis. Conclusion: Colonic mucin controlled the gut microbiota composition, and oral corticosteroid treatment modified the gut microbiota partly by reducing the colonic mucin.
ПРОФЕСІЙНА КОМУНІКАЦІЯ ПЕДІАТРА З ДИТИНОЮ ТА ЇЇ БАТЬКАМИ: МЕТОДИЧНА РОЗРОБКА ПРАКТИЧНОГО ЗАНЯТТЯ ДЛЯ ВИКЛАДАЧА
Authors: Стефанишин К. Л.
Published: February 2022

Стаття стосується проблеми навчально-методичного забезпечення дисципліни за вибором «Професійна медична комунікація українською мовою лікаря з пацієнтом» для студентів третього року навчання спеціальності 222 «Медицина». Вивчення дисципліни ґрунтується на отриманих знаннях із української мови як іноземної та передбачає забезпечення комунікативних потреб студентів у навчально-професійній і навчально-науковій сферах, закладає основи фахової мови медика з перспективою їх подальшого використання у професійній діяльності, продовжує формувати комунікативні навички майбутніх спеціалістів.
Представлено методичну розробку практичного заняття «Професійна комунікація педіатра з дитиною та її батьками» для викладачів медичних закладів вищої освіти. Хід заняття структуровано згідно з вимогами до практичних занять у медичному ЗВО та адаптовано до комунікативних потреб іноземних студентів. Структура заняття містить п’ять етапів: актуалізацію опорних знань, роботу з текстом, засвоєння нового матеріалу, виконання тренувальних вправ, поточний контроль. Змістове наповнення відповідає програмі навчальної дисципліни: cкарги дитини (її батьків) із захворюваннями різних систем та органів; дитячі захворювання; об’єктивне обстеження; попередній діагноз.
Розроблена система вправ ознайомлює студентів із лексикою на позначення дитячих інфекційних захворювань; вчить реалізовувати комунікативні наміри в ситуаціях, пов’язаних з основними пунктами збору сімейного анамнезу (розпитування батьків), розвиває вміння збору анамнезу життя дитини раннього і старшого віку, практикує комунікативні навички спілкування педіатра з дитиною (батьками дитини), в якої є скарги на захворювання однієї із систем організму. Звернуто увагу на граматичні аспекти комунікативного мінімуму, необхідного для усного і письмового професійно орієнтованого спілкування українською мовою.