bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Laboratory Skills Application Based on Android as a Media of Flipped Learning Model for Nursing Student
Authors: Buhari Basok , Sari Rian Maylina
Published: August 2022

The development of the current era is closely related to the increase in digitalization. The impact of the development of digitalization has a positive effect on the field of education. Online learning using digitalization changes learning models that tend to be passive to active through the management of learning models in the classroom or laboratory based on digital media. The research design was development method which was adapted from the 4D model (Four D Model) which consists of four stages, namely: define, design, development, and dissemination. The data type of this research is quantitative data. Quantitative data is obtained from scores from experts and nursing student as user. The data type of this research is quantitative data. Quantitative data is obtained from scoring scores from experts and nursing student as user. This research was conducted at Nursing Study Program, Sekolah Tinggi Ilmu Kesehatan Harapan Ibu Jambi, Jambi Province, Indonesia. The results of media on experts learning applications get a percentage 96.25%. These percentage can be interpreted as application of dissemination media and is very decent to use. The results by design experts, overall learning application get a percentage 85.2%, with these percentage can be interpreted as application of dissemination media is very decent to use. The results of the attractiveness test show that nursing student respond very well to the use of Android as a learning media for flipped learning models. Nursing student consider the packaging of material in the form of material, procedural, learning videos and article, as well as the interactivity and ease of use of these media to make material about skills laboratory more interesting to study.
Nurses’ Experiences as Worker During the Covid-19 Pandemic
Authors: Wijaya Rafika Dora , Permatasari Henny , Fitriyani Poppy , Setiyadi Agus
Published: August 2022

Purpose: The Covid-19 pandemic had a significant impact on nurses. Nurses as workers faced various health hazards in the workplace (hospital). Nurses are also a group at risk of contracting the virus when providing nursing care to Covid-19 patients. This study is aimed to determine the meaning of nurses' experience as workers during the Covid-19 pandemic. Design: This research is qualitative research with a descriptive phenomenological approach. Methods: Data collection was done, using in-depth interviews with online interviews using the zoom application. The interview data were analyzed using the Colaizzi method. Results: The results of this study identified four main themes, namely feelings of insecurity, dangers faced by nurses, active nurses in preventing transmission, and meaning for nurses. Conclusion: This study reveals that nurses during the Covid-19 pandemic face various health hazards. The implications of this research are useful, as input to occupational health nursing science regarding the danger nurses face during the Covid-19 pandemic. Suggestions from this research are expected to optimize efforts to promote and protect the health and safety of nurses during the Covid-19 pandemic.
Self-Management Education to Control Blood Sugar Levels and Hba1c Value for Type 2 Diabetes Patients
Authors: Bakara Derison Marsinova , Kurniyati
Published: August 2022

Backgroud: Self-care education can be carried out patients with diabetes through the Diabetes Self-Management Education (DSME) method. The DSME method helps people to perform with type 2 diabetes self-management in managing and treating type 2 diabetes, such as controlling blood sugar levels and HbA1c values. Objective: The purpose of this research is to understand the effect of DSME for reducing blood sugar levels and decreasing HbA1c values ​​in type 2 diabetes patients. Methods: The design of this research is a Pre-Experimental with Pretest-Posttest Group Design with a Pretest-Posttest Group Design, approach which aims to see the use of the DSME method for reducing blood sugar levels and decreasing HbA1c values ​​in type 2 diabetes patients. This research was conducted from July to October 2021. The research location was at the Curup Regional General Hospital, Rejang Lebong Regency. Respondents in this study were 35 patients with type 2 diabetes. The instrument used was the DSME method consisting of 3 instruments, including the theoretical concept of diabetes, care and treatment of diabetes, and complications of diabetes. Results: The results of the study show a significant change in blood sugar levels before and after the DSME. Before being carried out, blood sugar levels were with a Mean±SD of 341.60±157.589; meanwhile, after the intervention, blood sugar levels became 107.97±9.984 with a p:0.001. On the other hand, the HbA1c Value before intervention was Mean±SD 8.4313±2.2610, and after the intervention, the HbA1c value became 6.4553±1.2426 with p=0.001. Conclusion: DSME can be used as an alternative intervention that decreases in blood sugar levels and HbA1c values ​​in patients with type 2 diabetes.
PEMBELAJARAN DARING UNTUK MENDUKUNG IMPLEMENTASI MERDEKA BELAJAR KAMPUS MERDEKA (MBKM)
Authors: Dewi Utari
Published: August 2022

The purpose of this study was to determine the effectiveness of bold learning tools for Model Development and Reality courses in the form of semester learning plans (RPS), media, and learning materials. This learning tool will be used by students who collaborate on student exchanges in order to support the implementation of Merdeka Belajar Kampus Merdeka (MBKM) in higher education. This development uses the ADDIE (Analyze, Design, Develop, Implement, and Evaluate) model. The results of the test using learning tools were declared very good by material experts (100%) and media experts (91.67%). Likewise with the results of trials conducted on students as user samples. Users say the results are very good (90%). Meanwhile, the effectiveness of this research product can be proven by the test scores achieved by the experimental class students. The results of the A test reached 86.4% of the experimental class students and 57.2% of the control class students. In conclusion, it can be stated that this product applies the principles used and is effectively used for bold learning. Considering that the resulting product is easily accessible and user friendly, it will be able to support the implementation of merdeka belajar kampus merdeka AbstrakTujuan penelitian ini adalah untuk mengetahui kelayakan dan keefektifan perangkat pembelajaran daring untuk mata kuliah Pengembangan Model dan Realia berupa rancangan pembelajaran semester (RPS), media, dan bahan pembelajaran. Perangkat pembelajaran ini akan digunakan secara daring oleh mahasiswa yang melakukan kerjasama pertukaran pelajar dalam rangka mendukung implementasi Merdeka Belajar Kampus Merdeka (MBKM) di Pendidikan tinggi. Pengembangan ini menggunakan model ADDIE (Analyze, Design, Develop, Implement, and Evaluate). Hasil uji kelayakan perangkat pembelajaran dinyatakan sangat baik oleh ahli materi (100%) dan ahli media (91,67%). Demikian juga dengan hasil uji coba yang dilakukan kepada mahasiswa sebagai sampel pengguna. Pengguna menyatakan hasilnya sangat baik (90%). Sedangkan keefektifan produk penelitian ini dapat dibuktikan dengan nilai hasil tes yang dicapai mahasiswa kelas experimen. Hasil tes nilai A dicapai 86,4% mahasiswa kelas eksperimen dan 57,2% mahasiswa kelas kontrol.  Sebagai kesimpulan dapat dikemukakan bahwa produk ini memenuhi kaidah-kaidah kelayakan dan efektif digunakan untuk pembelajaran daring. Mengingat produk yang dihasilkan ini mudah diakses dan user friendly maka akan dapat mendukung implementasi program merdeka belajar kampus merdeka.
ONLINE LEARNING FOR ISLAMIC EDUCATION IN THE INSAN MADANI INTEGRATED ISLAMIC JUNIOR SECONDARY SCHOOL 8 TANGERANG SELATAN DURING THE COVID-19 PANDEMIC: A CASE STUDY
Authors: Arifin Rusjdy Sjakyakirti , Wihda Nazela Salsabila
Published: August 2022

The objective of this research was to analyze the impact of implementing online learning from home during the Covid-19 pandemic, especially for Islamic Education subject matter. The research was conducted at SMP Islam Terpadu Insan Madani 8 Jurangmangu, Tangerang Selatan-Banten, one of the Islamic Junior Secondary Schools at Jurangmangu, Tangerang Selatan, Banten. The research was conducted in a qualitative approach with data collection techniques through interviews, observation, and documentation. The study indicated that the online-based learning during the Covid-19 pandemic was carried out quite well following the government circular letters No. 4/2020 and No.15 of 2020. Some obstacles faced are unstable internet signals and limited facilities. Some examples of the obstacles were (1) the use of one smartphone for online learning in a family, so they had to take turns with siblings at home, (2) teachers had difficulty in providing practical learning materials, and (3) some parents had difficulties in operating gadgets and explaining the Islamic Education materials to their children. Some solutions in overcoming these obstacles were (1) to make changes to the online learning platform so that easier for parents to facilitate their children to learn from home, and (2) to provide internet credit subsidies by providing tuition waivers by 33%.
Sisi Gelap dari Kepribadian Individu dan Perilaku Sabotase Pengetahuan: Peran Mekanisme Kontrak Psikologis Transaksional
Authors: Defaga Nadia , Muhammad Rasyid Abdillah  , Adolf Bastian
Published: August 2022

Penelitian ini bertujuan untuk menjelaskan secara ilmiah hubungan sisi gelap kepribadian individu terhadap perilaku sabotase pengetahuan. Lebih khusus, penelitian ini berupaya menjelaskan mekanisme kontrak psikologis transaksional. Dengan memanfaatkan sampel sebanya 288 orang tenaga kependidikan/dosen di perguruan tinggi di indonesia penelitian ini menemukan bahwa dua dari 3 sisi gelap kepribadian individu yaitu Machiavellianisme dan Psikopat berpengaruh positif terhadap Perilaku sabotase pengetahuan. Secara khusus penelitian ini menemukan bahwa Kontrak psikologis transaksional memediasi hubungan antara machiavellianisme dengan sabotase pengetahuan.
Pemanfaatan Film Animasi Dengue Hemorrhagic Fever Selama Masa Pandemi Covid-19
Authors: Katmawanti Septa , Al-Irsyad Muhammad , Paramita Farah , Saputra Fandi Achmad , Samah Dea Aflah , Mahardyka Gladys Cyntya , Sari Purnama Devita , Bachtiar Belisa Fitria Az Zahra
Published: August 2022

Angka kasus Dengue Hemorrhagic Fever (DHF) di Malang Raya pada kondisi pandemi COVID-19 mengalami lonjakan. Hal ini disebabkan oleh adanya Program Pembatasan Social Berskala Besar (PSBB), sehingga usaha untuk menanggulangi penyebaran DHF pun tidak dapat berjalan maksimal. penelitian yang bertujuan untuk membuat film animasi yang mempermudah edukasi kepada masyarakat Malang Raya mengenai upaya pencegahan dan penanggulangan wabah DBD di masa pandemi dan masa yang akan datang. Metodologi penelitian yang dilakukan dengan metode penelitian dan pengembangan (Research and Development) yang dibagi menjadi dua bagian besar, yaitu desain produk dan produk berupa film animasi. Responden penelitian terdiri dari 16 responden dengan rentang usia 15-21 tahun. Hasil penelitian menunjukkan bahwa sebagian besar responden belum pernah menonton film animasi DHF. Tanggapan responden menunjukkan adanya potensi kenaikan penderita demam berdarah di masa pandemi COVID-19 yang disebabkan oleh kesadaran diri yang rendah seperti mengabaikan kualitas kesehatannya saat pembelajaran di rumah. Saran untuk film animasi DHF adalah dengan menambahkan informasi tentang cara menguras bak mandi dengan baik secara rutin, mengubur barang-barang bekas yang sudah tidak terpakai, menanam tanaman pengusir nyamuk, menggunakan obat nyamuk, dan membuat poster atau konten mengenai demam berdarah.
LUNG CANCER RELAPSE PREDICTION USING PARALLEL XGBOOST
Authors: Abdu-Aljabar Rana D. , A. Awad Osama
Published: August 2022

Lung cancer has been the most popular form of cancer for decades. Surgery will offer the non-small cell lung cancer (NSCLC) patients the best hope of a cure if the cancer is diagnosed in the early stage. However, many patients eventually die of their disease due to relapse after surgery. Because of no symptoms of lung cancer in its early stage, many researchers try to improve methods to predict lung cancer relapse early. This study proposed a method to predict lung cancer relapse more accurately. This method has three stages; feature selection, parallel extreme gradient boost (XGBoost) classifications with different hyperparameters, and selection stage. It used two datasets of a gene expression microarray for different lung cancer types with its clinical information. The accuracy of the proposed model is excellent compared to other machine learning.
Red blood cell sedimentation rate measurements in a high aspect ratio microchannel
Authors: Passos Andreas , Louka Marinos , Vryonidis Charalambos , Inglezakis Antonis , Loizou Constantinos , Nikiphorou Elena , Psarelis Savvas , Kaliviotis Efstathios
Published: August 2022

BACKGROUND: The erythrocyte sedimentation rate (ESR) test is commonly used in clinical practice for monitoring, screening and diagnosing pathological conditions and diseases related to the inflammatory response of the immune system. Several ESR techniques have been developed over the years improving the reliability, the precision and the duration of the measurement. OBJECTIVE: In the present study a new low cost micro-ESR technique is described providing the major advantage of reducing the measurement time and the blood sample volume by multiple times compared to the commercial methods. METHODS: Blood samples were obtained from healthy donors within the age group of 24–28 years and the haematocrit was adjusted to 30%, 40% and 50%. The ESR of the samples was measured utilizing a surface tension driven (STD) microfluidic chip and a monitoring device. RESULTS: The evaluation of the method showed a high correlation (0.94, p < 10–5) at all haematocrit levels with the commercial instrument indicating the feasibility of the technique. CONCLUSIONS: This micro-ESR technique provides the potential for a simple, low cost and fast tool for ESR measurement using low blood volume acquired by finger prick.
Neuropathological and Clinical Correlates of Lewy Body Disease Survival by Race and Ethnicity in the National Alzheimer’s Coordinating Center
Authors: Kurasz Andrea M. , De Wit Liselotte , Smith Glenn E. , Armstrong Melissa J.
Published: August 2022

Background: Survival and associated clinical and pathological characteristics in Lewy body disease (LBD)-related dementias are understudied. Available studies focus primarily on white non-Hispanic samples. Objective: We investigated demographic, clinical, and pathological correlates of survival by race and ethnicity in an autopsy-confirmed cohort of LBD cases. Methods: Using National Alzheimer’s Coordinating Center data, we selected participants who self-identified as Black, Hispanic, or white who had neuropathological assessments showing transitional or diffuse LBD pathology. We used Kruskal-Wallis and Pearson χ2 analyses to investigate group differences in demographic and presenting clinical and pathological characteristics. We used linear regressions to identify predictors of survival with sex, age at symptom onset, education, ethnoracial status, LBD pathology type, and Braak tangle stage included in the model. Results: Data from 1,441 white, 60 Black, and 54 Hispanic participants were available for analysis. Hispanics were more likely to have transitional LBD pathology and had a longer survival than white and Black participants. After controlling for demographic and pathological variables, length of survival did not differ between Hispanics and Black or white participants. Additional key findings demonstrated discrepancies between clinical diagnoses received at last visit and pathological findings, particularly among Black participants. Conclusion: LBD survival differences by race and ethnicity can be accounted for by LBD pathology type and co-occurring Alzheimer’s disease pathology. The discrepancies between clinical diagnoses and pathological findings raise the concern that dementia with Lewy bodies is underdiagnosed in NACC, especially for Black older adults.
Circulating Cell-Free Genomic DNA Is Associated with an Increased Risk of Dementia and with Change in Cognitive and Physical Function
Authors: Nidadavolu Lolita S. , Feger Danielle , Wu Yuqiong , Grodstein Francine , Gross Alden L. , Bennett David A. , Walston Jeremy D. , Oh Esther S. , Abadir Peter M.
Published: August 2022

Background: Altered cell homeostasis, seen in cognitive decline and frailty, leads to cell death and turnover, releasing circulating cell-free DNA (ccf-DNA). Objective: The goal of this study is to determine if serum genomic cell-free DNA (ccf-gDNA) is associated with physical and cognitive decline in older adults. Methods: We used serum from 631 community-dwelling individuals from the Religious Orders Study or Rush Memory and Aging Project who were without cognitive impairment at baseline. ccf-gDNA fragments in serum were quantified using digital PCR. An array of cognitive and physical traits, risk of dementia, global cognition, and frailty at or nearest the time of blood draw were regressed on ccf-DNA, with adjustment for age, sex, race, and education. Results: Cross-sectionally, higher ccf-gDNA levels were associated with lower global cognition score and slower gait speed at the evaluation nearest to blood draw. Higher ccf-gDNA levels were associated with increased odds of incident dementia (OR 1.27, 95% CI 1.05, 1.54). Longitudinally, higher levels of ccf-gDNA were associated with steeper general cognitive decline and worsening frailty over eight years of follow up. Conclusion: This study demonstrates that ccf-gDNA fragments have utility for identifying persons at higher risk of developing dementia and worsening cognition and frailty.
Antimicrobial, Polarizing Light, and Paired Helical Filament Properties of Fragmented Tau Peptides of Selected Putative Gingipains
Authors: Kanagasingam Shalini , von Ruhland Christopher , Welbury Richard , Singhrao Sim K.
Published: August 2022

Background: Tau is an established substrate for gingipains secreted by Porphyromonas gingivalis. Hyperphosphorylation of tau and neurofibrillary tangle (NFT) formation is a defining lesion of Alzheimer’s disease (AD) where NFT distribution is related to Braak stage and disease severity. Objective: To assess gingipains’-fragmented tau peptides for their antimicrobial properties and for the likelihood of paired helical/straight filament (PHF/SF) formation with implications for the NFT lesion. Methods: Seven non-phosphorylated (A-G) and three phosphorylated (A-C) tau peptides, were tested for antimicrobial properties against P. gingivalis. Polarizing light properties were determined using Congo Red staining. Secondary and tertiary structures of peptides B-F were determined using transmission electron microscopy (TEM) and circular dichroism (CD) was undertaken for the soluble peptides A in phosphorylated and non-phosphorylated states. Results: Phosphorylated tau peptide A displayed a significant effect against planktonic P. gingivalis. The CD results demonstrated that both peptides A, in phosphorylated and non-phosphorylated states, in aqueous solution, adopted mainly β-type structures. Non-phosphorylated peptides B-F and phosphorylated peptides B-C were insoluble and fibrillar under the TEM. The secondary and tertiary structures of the non-phosphorylated peptide B demonstrated fewer helical twists, whereas peptide C displayed significantly more helical twists along the whole fiber(s) length following its phosphorylation. Conclusion: Phosphorylated peptide A reduced P. gingivalis viability. CD spectroscopy demonstrated the phosphorylated and the non-phosphorylated peptide A predominantly formed from β-sheet structures in aqueous solution with potential antimicrobial activity. Phosphorylation of tau peptides physically changed their tertiary structure into PHFs with potential for self-aggregation and binding to the NFT lesion.
Evaluating the Bidirectional Causal Association Between Daytime Napping and Alzheimer’s Disease Using Mendelian Randomization
Authors: Li Sijie , Liu Bian , Li Qing-hao , Zhang Yan , Zhang Haihua , Gao Shan , Wang Longcai , Wang Tao , Han Zhifa , Liu Guiyou , Wang Kun
Published: August 2022

Background: Until now, both cross-sectional and longitudinal studies have identified controversial findings about the association between daytime napping and Alzheimer’s disease (AD) or cognitive decline. Therefore, it remains unclear about the causal association between daytime napping and AD or cognitive decline. Objective: We aim to investigate the causal association between daytime napping and AD. Methods: Here, we conduct a bidirectional Mendelian randomization (MR) analysis to investigate the causal association between daytime napping and AD using large-scale GWAS datasets from daytime napping including 452,633 individuals of European ancestry and AD including 35,274 AD and 59,163 controls of European ancestry. A total of five MR methods are selected including inverse-variance weighted (IVW), weighted median, MR-Egger, MR-PRESSO, and contamination mixture method. Results: MR analysis highlights significant causal association of AD with daytime napping using IVW (beta = -0.006, 95% CI [–0.009, –0.002], p = 2.00E-03), but no significant causal association of daytime napping with AD using IVW (OR = 0.76, 95% CI 0.53-1.10, p = 1.40E-01). Conclusion: Our bidirectional MR analysis demonstrates the causal effect of AD on daytime napping. However, there is no causal effect of daytime napping on AD. Our current findings are consistent with recent evidence from other MR studies that highlight little evidence supporting a causal effect of sleep traits on AD and support the causal effect of AD on sleep traits.
The Association Between Osteoarthritis with Risk of Dementia and Cognitive Impairment: A Meta-Analysis and Systematic Review
Authors: Guo Rong , Ou Ya-Nan , Hu He-Ying , Ma Ya-Hui , Tan Lan , Yu Jin-Tai
Published: August 2022

Background: The relationship between osteoarthritis (OA) and risk of dementia and cognitive impairment (CIM) has long been debated; however, uncertainties still persist. Objective: The aim of our present meta-analysis and systematic review was to roundly illuminate the association between OA and the risk of dementia and CIM. Methods: We identified relevant studies by searching PubMed, Embase, and Web of Science up to October 2021. The relative risk (RR) or odds ratio (OR) with 95% confidence interval (CI) were aggregated using random-effects methods. Credibility of each meta-analysis was assessed. Meta-regression and subgroup analyses were conducted. Publication bias was explored using funnel plot. Results: Of 21,925 identified literatures, 8 were eligible for inclusion in the systematic review and 19 observational studies involving 724,351 individuals were included in the meta-analysis. The risk of developing dementia and CIM among OA patients was demonstrated in 11 prospective studies (RR = 1.42, 95% CI = 1.07–1.86, I2 = 98.9%, p < 0.001), 2 retrospective cohort studies (RR = 1.35, 95% CI = 1.19–1.52, I2 = 61.0%, p = 0.109), 3 retrospective case-control studies (OR = 1.21, 95% CI = 0.96–1.53, I2 = 95.2%, p < 0.001), and 4 cross-sectional studies (OR = 1.51, 95% CI = 1.09–2.09, I2 = 75.8%, p = 0.006). Meta-regression analyses did not find any valid moderators. Heterogeneity in subgroup analyses for population age, OA location, year of publication, outcome type, adjusted for BMI, depression, and comorbidity decreased to zero. No significant evidence of publication bias was found. Conclusion: OA associated with an increased risk of dementia and CIM. Effective interventions in OA patients may decrease new incidence of dementia or CIM.
Design of an algorithm for recommending elective courses based on collaborative filtering
Authors: Yu Jian , Xiong Zenggang , Bao Qi , Ning Xiao
Published: August 2022

At present, college students generally choose courses according to their own interests or understanding of the course, which has a certain subjectivity and blindness. In many cases, students know little about the courses before class, and only rely on the course name to guess the course content, so as to decide whether to take this course. However, the existing studies are mainly aiming at online learning resources which are heterogeneous, these methods cannot be effectively applied to the recommendation of university courses. This paper explores improve collaborative filtering for university application environments, provides a knowledge recommendation algorithm for university elective courses. First, we created individual models of the course and the students based on background information. Next, we use context-based recommendation and “Parent Class Filling” method to reduce the impact of Cold Start and Sparsity problem on the initial stage of the system. Then, recommendations are generated based on the course evaluation model and similarity matrix. We select several commonly used algorithms to achieve the recommendation, and the experimental results proved that the proposed algorithm is accurate and effective.
A convolutional neural network model of multi-scale feature fusion: MFF-Net
Authors: Yi Yunyun , Wang Jinbao , Ding Xingtao , Li Chenlong
Published: August 2022

MFF-Net (a multi-scale feature fusion convolutional neural network) was designed to improve the recognition rate of handwritten digits. The low-level, middle-level and high-level features of the image were first extracted through the convolution operation, and then the low-level and intermediate features were further extracted through different convolutional layers, later directly fused with the high-level features of the image with a certain weight, and then processed by the full connection layer. By adding a batch normalization layer before the activation layer, and a dropout layer between the full connection layers, the accuracy and generalization capacity of the network are improved. At the same time, a dynamic learning rate algorithm was designed, with which, the trained network accuracy was significantly improved as shown in the experiments on the MNIST data set. The accurate rate could reach 99.66% through only 30 epochs training. The comparison indicated that the accuracy of the network model is significantly higher than that of others.
Application analysis of highway traffic accident risk model based on geographically weighted negative binomial regression
Authors: Gu Xun , Dai Shuai
Published: August 2022

The traditional generalized linear model (GLM) can not effectively analyze discrete road traffic accidents when analyzing road traffic accidents with spatial dependence and heterogeneity. Therefore, a risk analysis method of highway traffic accidents based on geographically weighted negative binomial regression model (GWNBR) is proposed. Using geographical weighted regression (GWR) model and negative binomial regression (NB) model, this paper makes a comparative analysis of highway traffic accidents in Xi’an, including local spatial geographical weighted Poisson regression (GWPR) model and two geographical weighted negative binomial regression (GWNBRg and GWNBR) models. The corresponding model bandwidth is determined, and the performance of the model is compared based on the data of traffic environment, road characteristics, crowd characteristics and road alignment. The experimental results show that compared with the single NB model, the proposed model can effectively reduce the interference of the spatial nonstationarity of the data, and can effectively extract the risk factors affecting the accident. The coefficients of GWNBRg model and GWNBR model are positive, which are better than GLM in the mean and likelihood of the residuals. The spatial autocorrelation of the residuals is significantly reduced, and the significance level is 5%, which reduces the spatial heterogeneity of the data. The over dispersion parameter value of GWNBRg model shows a downward trend from southwest to northeast in space, which can effectively reflect the spatial relationship between traffic flow and accident rate, indicating that GWNBR model has a good effect in traffic accident risk analysis of super discrete highway. Therefore, the application of geographical weighted negative binomial regression to highway traffic accident risk prediction has a good application effect, and can effectively reduce the probability of accidents as safety prevention and early warning.
Cooperative control method of robot formation movement path based on machine vision
Authors: Zhang Yang
Published: August 2022

Because the formation path information is not extracted in the process of robot formation motion path cooperative control, the image processing time is long and the effect of avoiding obstacles to reach the target position is poor. Therefore, a robot formation motion path cooperative control method based on machine vision is proposed. Through the design of embedded chip control module, image acquisition module and communication module, the application process of machine vision technology is designed, and the target features in the motion path of robot formation are extracted, including other robot targets and obstacle targets in the formation. Then, the formation path information is extracted based on image preprocessing. On this basis, using the formation form of virtual structure-driver following method, the obstacle avoidance control of robot formation motion path is completed by potential field method. The experimental results show that after using this method, the images of its CCD camera when performing various processing are less than 200 ms. The moving environment image shows that this method has high processing performance for robot formation, and under the control of this method, the formation can change the formation and intelligent robot to avoid obstacles and reach the target position.
Visual retrieval of digital media image features based on active noise control
Authors: Zhang Ying , Luo Xiaobo
Published: August 2022

In order to improve the recall and precision of image retrieval, a visual retrieval method of digital media image features based on active noise is proposed. In this paper, Canny algorithm is used to detect the edge of the image to get the feature information of the edge of the image. The RGB color space model is used to decompose the color information of the image, and the color characteristic information of the image is obtained. Extracting image features to retain the useful information contained in the image as much as possible; In order to facilitate the visual retrieval of image features, reduce the retrieval complexity and further fuse image features, FPCA and ReliefF algorithms are used to reduce the dimensionality of image features, and the active noise control method is used to sharpen the image. After processing the results, a digital media image feature visual retrieval platform is established to realize the visual retrieval of digital media image features. Experimental results show that the proposed method has a high accuracy of over 80% and a high recall rate of 95.2%.
Weak illumination image enhancement algorithm based on cyclic generation countermeasure network
Authors: Zhang Yu
Published: August 2022

To solve the problem of missing or distorted detail texture when manually adjusting image parameters, a weak illumination image enhancement algorithm based on cyclic generation game network is proposed. The image features are normalized by Gaussian distribution. Combined with homomorphic filtering theory and defogging operation, the image is generated and denoised according to the network brightness to enhance the weak illumination image. The experimental results show that after using this method to process the image, the image entropy increases by 6.8%, the contrast increases by 27.5%, and the noise content decreases by 24.1%. It has better contrast. It can not only meet the enhancement effect of weak light, but also ensure the details of the image, so that the image has richer details and good visual appearance.
Calibration and Distraction Mining Network for Aortic True Lumen segmentation
Authors: Fan Xin , Tian Shengwei , Yu Long , Han Min , Liu Lu , Cheng Junlong , Wu Weidong , Kang Xiaojing , Zhang Dezhi
Published: August 2022

Automatic segmentation of aortic true lumen based on deep learning can save the time for diagnosis of aortic dissection. However, fuzzy boundary, small true lumen region, and high similarity usually leads to inaccurate prediction. To make better use of the details supplemented by the encoder to restore boundaries, we decompose the recovery of detail features in the decoder into two sub-processes: calibration and distraction mining. And we propose a novel calibration and distraction mining (CDM) module. It utilizes deep features to calibrate shallow features so that features are concentrated in the main region. Then, it leverages the distraction mining procedure to extract false-negative features as a supplement to calibrated features and recover details of the segmentation object. We construct CDM-Net and verify its performance on the Aorta-CT dataset (private dataset), it achieves the Dice similarity coefficient of 96.94% and the Jaccard index coefficient of 94.08%, which is the best compared with 10 latest methods. Similarly, we explore its robustness on three more public datasets, including ISIC 2018 dataset (skin lesion segmentation), the 2018 data science bowl dataset (nucleus segmentation), LUNA dataset (lung segmentation). Experimental results prove that our method produces competitive results on all three data sets. Through quantitative and qualitative research, the proposed CDM-Net has good performance and can process aortic slices with complex semantic features, additional experiments show that it has good robustness, and it has the potential to be applied and expanded conveniently.
Proprioceptive neuromuscular facilitation in chronic low back and neck pain and disability: A systematic review and meta-analysis
Authors: Suresh Vaishnavi , Karthikbabu Suruliraj , Prem Venkatesan
Published: August 2022

BACKGROUND: Proprioceptive neuromuscular facilitation (PNF) is one of the neurophysiological techniques aimed at reducing pain and disability. This systematic review objective addresses the current evidence on PNF techniques’ effectiveness in chronic low back and neck pain. METHODS: Literature search in PubMed, Scopus, Cochrane, Wiley and Ovid databases were searched until 2021. The content of the titles and the abstracts were analysed to gather information about the effects of PNF in chronic back and neck pain with outcomes of pain and disability. The quality of the studies was analysed by the Joanna Briggs Institute (JBI) critical appraisal score. Meta-analysis was performed on Visual Analogue Scale (VAS), Numerical Rating Scale (NRS) for chronic low back pain and Oswestry Disability Index (ODI), Roland Morris Disability Questionnaire (RMDQ) for disability. RESULTS: Nine studies addressed the different PNF based interventions on chronic low back pain, with a total of 416 participants. The intervention period ranged 3–6 weeks, and two studies conducted 12-weeks follow-up. Many studies measured pain using a VAS and NRS, whereas the disability through ODI and RMDQ. The JBI score ranged from 6/13 to 11/13. None of the PNF studies treated chronic neck pain. CONCLUSION: PNF might be beneficial for reducing low back pain and related disability. The long term effects of PNF on chronic low back pain, and also to determine its benefits on chronic neck pain are warranted in future studies.
Semantic models and services for conservation and restoration of cultural heritage: A comprehensive survey
Authors: Moraitou Efthymia , Christodoulou Yannis , Caridakis George
Published: August 2022

Over the last decade, the Cultural Heritage (CH) domain has gradually adopted Semantic Web (SW) technologies for organizing information and for tackling interoperability issues. Several semantic models have been proposed which accommodate essential aspects of information management: retrieval, integration, reuse and sharing. In this context, the CH subdomain of Conservation and Restoration (CnR) exhibits an increasing interest in SW technologies, in an attempt to effectively handle the highly heterogeneous and often secluded CnR information. This paper investigates semantic models relevant to the CnR knowledge domain. The scope, development methodology and coverage of CnR aspects are described and discussed. Furthermore, the evaluation, deployment and current exploitation of each model are examined, with focus on the types and variety of services provided to support the CnR professional. Through this study, the following research questions are investigated: To what extent the various aspects of CnR are covered by existing CnR models? To what extent existing CnR models incorporate models of the broader CH domain and of relevant disciplines (e.g., Chemistry)? In what ways and to what extent services built upon the reviewed models facilitate CnR professionals in their various tasks? Finally, based on the findings, fields of interest that merit further investigation are suggested.
Fracture toughness of 3D printed denture teeth
Authors: Alqahtani Nasser M. , Chaturvedi Saurabh , Tomar Shobhit Singh , Kumari Lalima , Gill Shruti , Nayan Kamal , Shariff Mansoor , Bhagat Tushar V. , Addas Mohammed Khalid , Chaturvedi Mudita
Published: August 2022

BACKGROUND: Advances in digital dentistry lead to use of three-dimensional (3D) printed resin denture teeth. Fracture toughness of these teeth must be assessed. OBJECTIVE: This study aimed to compare the chipping and indirect tensile fracture resistance of denture teeth fabricated by 3D printing technique with traditionally fabricated resin denture teeth. METHOD: Four groups (Gr) were made (n= 50/group): Gr-1 3D printed denture teeth (denture teeth; Formlabs Inc., Somerville, MA, USA), Gr-2 SR-Orthosit-PE (Ivoclar Vivadent AG), Gr-3 Portrait IPN (Dentsply Sirona), Gr-4 Pala Premium 8 (Heraeus Kulzer GmbH). Stereolithography 3D printing was used to create the methacrylate-based photopolymerized resin teeth models and remaining group teeth were collected commercially. A 1 mm/min chipping and indirect tensile fracture speed tests were carried out till fracture occurred. The data so obtained were statistically analysed using one-way analysis of variance with Tukey’s honestly significant difference multiple comparisons test (p< 0.05). At the end of the test, the fractured areas of the specimens were evaluated by the chief researcher to assess the fracture pattern of the teeth. RESULTS: The indirect tensile fracture values of the 3D printed teeth were more than that of Pala Premium-8 and SR-Orthosit-PE but it was lower than that of Portrait IPN teeth. In chipping test, buccal chipping of the loaded cusp was seen in 3D printed resin without distortion and in indirect tensile test in 3D printed resin teeth, line of fracture emerges near the loading point propagates from the inner incline of both cusps and extends cervically, unlike in other groups where first deformation occurs then fracture. CONCLUSION: Prosthetic teeth fabricated by the 3D printing technique using printable resin material provide adequate fracture resistance as denture teeth.
Pandemic lessons: New strategies and technologies of teaching
Authors: Grinshkun V. V. , Zaslavskaya O. Yu.
Published: August 2022

The article describes the results of the analysis of the experience gained while organizing the educational process during the two-year pandemic of COVID-19. In particular, the problem situations that arose onthe transition to emergency distance learning are considered. The main attention is paid to summarizing the existing approaches to teaching students and schoolchildren, the actions necessary to mitigate the consequences of such a transition, as well as highlighting the strategic directions for training teachers, allowing them to be prepared for similar situations.

The effective use of information and communication technologies has played an important role in overcoming the learning difficulties caused by the pandemic. At the same time, not only students needed timely support, but also teachers did not always have enough professionalism to quickly switch to online learning. Not all educational organizations turned out to be prepared for an almost instantaneous transition to new forms of their activities.

Based on the results of the analysis, it was possible to formulate the strategic and technological directions of possible significant research that contribute to the preparation of future and current teachers for work in a changing environment.
Some aspects of the development of information-cybernetic thinking in pedagogical university students when studying the basics of cybernetics
Authors: Mayer R. V.
Published: August 2022

The rapid development of various information-cybernetic systems and their introduction into all spheres of human life and activity necessitate a deeper study of the foundations of informatics and cybernetics in schools and pedagogical universities. Conducting an analysis of the features of the formation of information-cybernetic thinking of students of pedagogical universities and the development of training tasks that contribute to a deeper mastery of the basic provisions of cybernetics are key aspects for the teacher. At the same time, the method of analyzing educational and scientific-methodical literature, methods of programming and computer modeling, as well as mathematical methods are used. The main types of educational tasks that contribute to the development of informationcybernetic thinking of students are selected: 1) explanation of the principles of cybernetics and their justification on the example of specific technical systems; 2) explanation of the general principles of functioning of various types of information-cybernetic systems; 3) explanation of the operation of specific automatic control systems (ACS) and their individual components; 4) the invention of “new” control systems with desired properties; 5) creation of technical control systems and experimental study of their work; 6) creation of computer models of control systems and transmission links. Solutions of educational problems involving computer modeling of automatic control systems and various transmission links in the Pascal ABC environment are discussed. The proposed elements of the methodology can be used in any university when teaching students the basics of cybernetics.
MANIPULATIVE STRATEGY AND TACTICS OF INVESTIGATORS IN THE PRE-TRIAL INVESTIGATION DISCOURSE
Authors: Pavlichenko L. V. , Nikiforova Ye. Yu. , Havryliuk O. O.
Published: August 2022

The article deals with the manipulative strategy and tactics of an investigator in the pre-trial investigationdiscourse that can have psychological effect on suspects and result in both positive and false confessions.The study offers the general outline and characteristic features of the pre-trial investigation discourse, focuseson the analysis of the applied strategy and tactics and their combinations. Communicative strategies and tacticsof the participants of the interrogation are identified by applying of the following methods: situational-strategicand contextual-interpretive analysis; elements of discourse analysis for analyzing of the strategic and tacticalinteraction of participants in the discourse of interrogation with the account of pragmatic, social and personalfactors of communication. The choice of the applied manipulative strategy and tactics by investigators dependson the background information about suspects and accused supplied at a pre-interrogation stage of a case.The authors offer the classification for the most typical strategies and tactics of the participants with a specialconcern to manipulative ones and demonstrate that the choice depends on the relations between participantsof an interaction, a procedural status of an interrogated person that can change, as well as the personal featuresof a suspect and an accused. The paper highlights that the strategies and tactics of a suspect and an accused dependprimarily on the manipulative strategies and tactics used by an interrogator as a representative of an institution,and emphasizes that they are directed mainly upon defense due to limitations and restrictions of interrogation.Relevant examples and sources are also provided.
Canavalia ensiformis (L.) DC (Fabaceae)
Authors: López Raquel Elisa da Silva
Published: August 2022

A Canavalia ensiformis é uma leguminosa com ampla distribuição tropical. É bastante utilizada em agricultura como cobertura verde para enriquecer o solo de nutrientes. Devido ao seu elevado valor nutricional suas sementes são empregadas na alimentação do gado e suas folhas na alimentação humana. Ela é bastante resistente às variações das condições ambientais, insetos e microorganismos. Seus principais componentes biologicamente ativos são proteínas, peptídeos, enzimas ou derivados de aminoácidos e dentre os quais é importante chamar a atenção para concanavalina A, urease, canatoxina, jaburetox, serino-proteases e L-canavanina / L-canalina. Estes compostos apresentam importantes funções bioquímicas e suas atividades biológicas têm sido objeto de intensas investigações. Além disso, estes principais componentes purificados de sementes de C. ensiformis exercem importantes efeitos farmacológicos, auxiliando assim na compreensão da fisiologia dos organismos, como também no tratamento de diversas patologias.Canavalia ensiformis (L.) DC (Fabaceae)Canavalia ensiformis is a widely distributed tropical legume. It is extensively used in agriculture as a green cover for the nutritional enrichment of soils. Due to the high nutritional values the seeds are used to feed cattle and the leaves are food for humans. It is quite resistant to changes in environmental conditions, insects and microorganisms. The major compounds of C. ensiformis are biologically active proteins, peptides, enzymes or amino acid derivatives. Among these compounds it is important to mention concanavalin A, ureases, canatoxin, jaburetox, serine proteases, glycosidases and L-canavanina/L-canalina. These compounds play important biochemical roles in the plant and, their activities have been the subject of intense investigations. In addition, these major compounds extracted from seeds of C. ensiformis have important pharmacological effects, thereby aiding in the understanding of physiology of organisms and in the treatment of various pathologies.
ANALISIS PENGARUH LDR DAN CAR TERHADAP RETURN SAHAM DENGAN PROFITABILITAS SEBAGAI VARIABEL MODERASI
Authors: Wulandari Retno
Published: August 2022

Riset  ini mempunyai sebuah tujuan yakni untuk pengujian serta analisis adanya loan to deposit ratio serta capital adequacy ratio (car) pada return saham keuangan perbankan tahun 2017-2019 dengan profitabilitas sebagai variabel moderasi. teknik pengambilan sampel yakni purposive judgement sampling serta diperolehnya 21 perusahaan sebagai sampel penelitian. Teknik analis data yang diterapkan ialah analisis berganda, uji asumsi klasik serta uji jalur. Hasil analisis menjelaskan LDR secara parsial tidak memengaruhi return saham, CAR memengaruhi return saham, dan ROA memengaruhi return saham. Terkait hasil atas pengujian jalur didapatkan ROA memperlemah hubungan FDR terhadap return saham serta hasil yang terakhir yakni ROA memperkuat hubungan antara CAR pada return saham.