bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the cohomology of characters stacks for non-orientable surfaces
Authors: Scognamiglio Tommaso 
Published: December 2022

Abstract
We give a counterexample to a formula suggested by the work of Letellier and Rodriguez-Villegas [28] for the mixed Poincaré series of character stacks for non-orientable surfaces. The counterexample is obtained by an explicit description of these character stacks for (real) elliptic curves.
Mathematics subject classification: 14M35,14D23
Effects of different foods and cooking methods on the gut microbiota: an in vitro approach
Authors: Lerma-Aguilera Alberto M. , Pérez-Burillo Sergio , Navajas-Porras Beatriz , León E. Daniel , Ruíz Sonia , Pastoriza Silvia , Jiménez-Hernández Nuria , Cämmerer Bettina-Maria , Rufián-Henares José Ángel , Gosalbes María José , Francino M. Pilar 
Published: December 2022

Abstract
Background
Dietary interventions are likely tools for modulation of the gut microbiota but the large inter-individual variability in gut microbiota composition leads to different host responsiveness and the impact of a particular food cannot be assessed. In contrast, in vitro fermentation models allow characterization of the fecal microbiota when fermenting a large number of different foods. Furthermore, cooking methods also directly influence the effects of food on gut microbiota composition. The aim of this study was to investigate the gut microbiota growing on representative foods of the Mediterranean and Western diets as well as the influence of cooking methods using in vitro fermentations.
Results
We performed in vitro digestions and fermentations of 55 foods, raw or cooked using up to 5 cooking methods, for a total of 159 combinations, employing fecal material from three healthy adults as inoculum. The composition of the bacterial communities was determined by sequencing the 16S rRNA gene. Foods derived from plants or animals had significantly different impacts on the abundances of bacterial taxa. Animal and vegetable fats, fish and dairy products led to the greatest shifts in microbial composition. Specifically, an increase in the beneficial bacteria Faecalibacterium, Blautia and Roseburia was identified in animal and vegetable fats. However, butter, dairy products and fish also resulted in higher abundances of Lachnoclostridium, which has been associated to several diseases. With respect to cooking methods, only frying and roasting had strong and common effects across all food categories. In general, fried foods showed more differences than other cooking methods, and Ruminococcus was particularly responsive to the cooking method employed.
Conclusions
Despite substantial differences in baseline microbiota composition, some shared effects were detected across the three analyzed individuals, such as the substantial impact of high-fat foods on the abundance of health-relevant bacteria. Cooking methods effects on the gut microbiota resulted to be highly individualized and food-dependent, making them challenging to investigate and integrate into personalized diet. Further characterization of the responses of the fermentative microbiota to food-cooking method combinations will enable the refinement of dietary interventions aimed at gut microbiota modulation, paving the way towards personalized nutrition.
Analyzing Ball Bearing Capacitance using Single Steel Ball Bearings
Authors: Puchtler Steffen , Kuip Julius van der , Kirchner Eckhard 
Published: December 2022

Abstract
A precise modeling of the capacitance of rolling element bearings is of increasing significance over the last years, e.g. in the context of bearing damage estimation in electric drives. The complexity of a steel bearing as an electrical network makes reliable validation of calculation models under realistic operating conditions nearly impossible. A way to reduce complexity in yet realistic conditions is the use of hybrid bearings with a single steel rolling element. This helps to measure only one current path through the bearing at a time and thus, gives a much clearer picture of the contact capacitance of rolling elements in and out of the load zone. The usage of different materials comes with different thermal expansion coefficients and different elasticities, which cause a significant change in load distribution. For the first time, this work considers both of these effects in calculation and validates them with corresponding experiments using single steel ball bearings.
Customizable Document Control Solution for 3D Printing at the Point-of-Care
Authors: Lohss Maxwell , Hammersley Elliott , Ghodadra Anish 
Published: December 2022

Abstract
Background
The rapid expansion and anticipated U.S Food and Drug Administration regulation of 3D printing at the point-of-care necessitates the creation of robust quality management systems. A critical component of any quality management system is a document control system for the organization, tracking, signature collection, and distribution of manufacturing documentation. While off-the-shelf solutions for document control exist, external programs are costly and come with network security concerns. Here, we present our internally developed, cost-effective solution for an electronic document control system for 3D printing at the point-of-care.
Methods
We created a hybrid document control system by linking two commercially available platforms, Microsoft SharePoint and Adobe Sign, using a customized document approval workflow.
Results
Our platform meets all Code of Federal Regulations Part 11 guidances.
Conclusions
Our hybrid solution for document control provides an affordable system for users to sort, manage, store, edit, and sign documents. The system can serve as a framework for other 3D printing programs to prepare for future U.S Food and Drug Administration regulation, improve the efficiency of 3D printing at the point-of-care, and enhance the quality of work produced by their respective program.
Hardware CPG Model That Generates Time Series Neural Signal Patterns for Controlling Human Walking and Running
Authors: Takeda Kenji , Goto Tatsumi , Ishihama Takumi , Ishibashi Motokuni , Yamazaki Kentaro , SHUXIN LYU , Aibara Megumi , Kaneko Minami , Uchikoba Fumio 
Published: December 2022

Abstract
A hardware CPG model for biped gait control using pulse-type hardware neural networks(P-HNNs) composed of analog electronic circuits to generate time-series neural signal patterns for controlling human walking and running is reported. Human walking and running are controlled by central pattern generators located in a spinal cord. Apart from this spinal system, gait and gait speed is known to be changed by a signal from a higher center input to a brainstem-spinal cord projection. However, the specific circuit configuration of the neural circuits for controlling gait locomotion is still unknown. In recent studies, walking and running have been estimated to be controlled with five simple time-series pulse patterns generated by the spinal cord and the duration of their pulses. We have previously used P-HNNs to generate time-series neural signal pulse patterns for controlling human walking and running. In the model, the order of the time series was determined manually by trigger input. In addition, the change in the pulse pattern period when switching from walking to running was not reproduced. In this paper, we propose a hardware CPG model for biped gait control, with a network configuration capable of automatically determining the order of the time series, and changing the pulse pattern period. Based on the circuit configuration of the proposed CPG model, circuit simulations and CPG circuits fabricated with surface mount components were measured. The measured results confirm the automatic output of the neural signal patterns for controlling walking and running in time-series order. We also confirmed the pulse pattern period becomes shorter when switching from walking to running.
Assessment of Low and Medium Anti-epileptic Medication Adherence among Epileptic Patients in Dessie Comprehensive Specialized Hospital, North-East Ethiopia: Cross Sectional Study
Authors: Fissha Yonas , Kibret Yohannes , Haile Yosef 
Published: December 2022

AbstractBackground Non-adherence to anti-seizure medication therapy is an important contributing factor to the higher mortality rate and treatment failure of epilepsy. Complete antiepileptic therapy is an essential intervention aimed at improving the quality of life of patients who suffer from a disease which is known for its stigmatization with many cultural misconceptions. So the aim of this study was to assess low and medium anti-epileptic medication adherence among epileptic patients in Dessie comprehensive specialized hospital, north-east Ethiopia. Method A cross sectional study design was conducted among the epileptic patient attending Dessie comprehensive specialized hospital from May 4 to August 4, 2022, on the total sample size of 253 selected epileptic patients by using convenient sampling technique. Data was collected by using structured interview-administered quastitionary; its quality was checked by pretest and continuous supervision. Data was entered into Epi-data 3.1 version and exported to SPSS version 23 for analysis. Multivariable multinomial logistic regression model was used to determine the relationship between the independent variable and the outcome variable. Relative risk ratio (RRR) with 95% confidence interval was used at p value less than 0.05 to declare statistical significance association. Result From 253 study participants, this study found a 20.2%, and 30.8% incidence of the low and medium anti-epileptic drug adherence respectively. The factors for low anti-epileptic drug adherence were seizure since last visit (RRR = 1.033, 95% CI, (1.005–1.219), comorbidity of patient (RRR = 36.389, 95% CI, (7.198-183.963), adverse effect experiences since last visit (RRR = 3.938, 95% CI, (1.065–14.565), and duration of drug (RRR = 56.745, 95% CI, (.903-3567.210). The factors for medium anti-epileptic drug adherence were seizure since last visit (RRR = (1.305, 95% CI, (1.101–1.920), occupation status of the patient (RRR 1.008, 95% CI, (1.01–1.156), rural residents (RRR = 1.031, 95% CI, (1.008–1.120), and age category 18–27 (RRR = .161, 95% CI, (.031-.835). Conclusion The prevalence of low and medium antiepileptic drug adherence was high in this study. Health care providers should provide health education and medication related counseling for all patients with epilepsy to improve adherence.
Adaptive behavior with selfish nodes based on fuzzy logic in delay tolerant network
Authors: Rashidjafari Fahimeh , Derakhshanfard Nahideh 
Published: December 2022

Abstract
Delay Tolerant Networks is a kind of Mobile Ad Hoc Networks which the nodes are mobile and therefore there is not any end to end path between the source and the destination node. Due to frequent disruption between the links, nodes use a store, carry and forward pattern to send messages in such networks. Message forward and carry is achieved due to the cooperation between relay nodes. Some of the nodes may avoid this cooperation to preserve their own sources (such as buffer and energy) and they are known as Selfish Nodes. In this paper a selfish node detection method based on a fuzzy logic is presented. In this method, the parameters of number of packet send and receive through node, centrality degree, and buffer capacity are considered as fuzzy inputs. The fuzzy outputs are active, semi-selfish, or selfish nodes and the nodes are treated based on it. The simulation results show that the proposed method improves the criteria of delivery rate and average delay compared with related works.
On the convergence of Kantorovich operators in Morrey spaces
Authors: Arsana Mu'afa Purwa , Gunadi Reinhart , Hakim Denny Ivanal , Sawano Yoshihiro 
Published: December 2022

Abstract
In this paper, we investigate Kantorovich operators on Morrey spaces. We first recall the main tool in the proof of the uniform boundedness of Kantorovich operators in Morrey spaces, namely a pointwise estimate of Kantorovich operators by the Hardy-Littlewood maximal operator. We also investigate the convergence of Kantorovich operators in Morrey spaces under weaker assumptions that is also true for the endpoint case. In addition, we obtain the rate of convergence of Kantorovich operators in Morrey spaces under the condition of Hölder continuity. Our result can be applicable to the function spaces in a recent result by Zeren, Ismailov and Karacam.
MSC (2020): 41A10, 41A25, 42B35, 47B38
Potential drug-drug interactions in COVID-19 comorbid patients: situation in outpatients department of different hospitals in Bangladesh
Authors: Tasfia Syeda Ripha , Sakib Hujaifa Ahmed , Khanam Tasmiah , Hoque Nazia , Rahman Mamunur , Khan Arif , Islam Sufia 
Published: December 2022

Abstract
Background: COVID-19 was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. Unpredictable and peculiar characteristics of coronavirus left no single recommended treatment option apart from preventive actions. Bangladesh government adopts guidelines for the clinical management of mild, moderate, and severe cases of COVID-19 patients. Prescription error, the avoidable mistake, may cause havoc, especially for comorbid patients with diabetes and hypertension identified as a risky population group for COVID-19. Therefore, the present study was designed to evaluate the prescription errors, including the drug-drug interactions among the outdoor patients infected with the coronavirus. This study was carried out in outpatient departments of different hospitals in Bangladesh through a random sampling method between May 2021 and August 2021. Eighty prescriptions of COVID-19 patients were collected, among which 44 patients had comorbidity. Microsoft Excel 2016 program analyzed the prescription and online aiding tools such as Drug Interaction Checker (Drugs.com) to identify potential drug-drug interaction/s.
Results: Among those 80 prescriptions, 44 cases (55%) contained moderate drug-drug interaction; Moxifloxacin and Remdesivir, the highest observed combination, were detected in 10 prescriptions (12.5%). A total of 7 prescriptions (8.75%) contained significant drug-drug interactions. The dose was not mentioned in 37 cases (46.25%), while the patient’s history was not found in 21 cases (26%). Moreover, 6-10 drugs were found in 54 prescriptions (67.50%), while 11-15 drugs were prescribed in 19 prescriptions (23.75%).
Conclusions: The prescription error being an avoidable occurrence may be eradicated by awareness, helping tools with preventive measures.
An Efficient Synthetic Data Generation Algorithm to Improve Efficacy of Deep Learning Models of Medical Images
Authors: Maryada Sai Kiran , Booker William Lee , Danala Gopichandh , Jones Meredith , Mudduluru Sanjana , Pham Huong , Hougen Dean F. , Zheng Bin 
Published: December 2022

Abstract
Deep Convolutional Neural Networks (DCNNs) have emerged as powerful components of computer-aided systems to detect and classify diseases in medical images. In order to robustly achieve high performance, a large and diverse dataset with annotated images is required to train or fine-tune DCNNs. However, such datasets are often very difficult and/or expensive to obtain due to demands on clinicians’ time and inter-reader variability. To address these challenges and increase training dataset size, we propose an efficient multi-stage algorithm to generate synthetic medical image data by extracting annotated diseased regions and randomly projecting them onto disease-free images. To test the feasibility of this new algorithm, the publicly available Indian Diabetic Retinopathy Image Dataset (IDRiD) is used. This dataset is comprised of the annotated fundus images acquired from 81 patients with two categories of diseases. Among them, 54 and 27 images are used for training and testing images, respectively. Using the proposed algorithm, we generate synthetic data by inserting extracted diseased lesions onto another set of 60 disease-free images, which results in 7,902 and 6,786 images for the two categories of diseases, respectively. Three transfer-learning-based DCNN models (VGG16, ResNet50, and Inception-v3) are trained using original IDRiD images and synthetic dataset, respectively. When applied to the same test images, the model trained with the synthetic dataset outperformed the model trained using he original IDRiD dataset by 7.4% in disease classification. These results indicate that this simple algorithm can generate diverse and useful synthetic lesion data to improve performance of DCNN models.
The Antecedents of Acceptance of Clinical Decision Support Systems by Physicians and Pharmacists in Saudi Arabia
Authors: Albahly Mohammed Suliman , Seliaman Mohammed Elhassan 
Published: December 2022

Abstract
This research paper aims to identify the technological and non-technological factors influencing user acceptance of the CDSS in a group of healthcare facilities in Saudi Arabia. The research study uses the quantitative approach to evaluate the currently implemented CDSS as a part of Hospital Information System BESTCare 2.0 in the Saudi Ministry of National Guard Health Affairs. For data collection, a survey questionnaire is conducted at all Ministry of National Guard Health Affairs hospitals. Then, the collected survey data is analyzed using Structural Equation Modeling (SEM). This analysis includes measurement instrument reliability, discriminant validity, convergent validity, and hypothesis testing. Moreover, a CDSS usage data sample is extracted from the data warehouse to be analyzed as an additional data source. The results of the hypotheses testing show that usability, availability, and medical history accessibility are the critical factors influencing user acceptance of CDSS. This study provides prudence about healthcare facilities and their higher management to adopt CDSS.
Food allergen control at meat processing enterprise: scientific rationale and preliminary hazard analysis
Authors: Kryuchenko E. V. , Chernukha I. M. , Kuzlyakina Yu. A. , Zamula V. S. 
Published: December 2022

From a public health point of view, the control of food allergens in enterprises is one of the main methods of food safety management required by national and international standards. The implementation results of measures for allergen control and identification of noncompliance are presented using the developed checklist, which includes 41 questions. The survey was conducted at meat processing plant in the Moscow region, which is certified for compliance with the requirements of ISO 22000:2018 “Food safety management systems — Requirements for any organization in the food chain” and FSSC22000 certification scheme. Compliance with the criteria included in the checklist was assessed by the method of interviewing employees at the enterprise and direct onsite observation. The highest level of noncompliance according to 7 groups of criteria established in the checklist was identified in the following sections; “Cleaning”, “Transport and storage” and “Hazard awareness”. Factors complicating the implementation of allergen control activities include available methods to assess cleaning effectiveness when removing specific allergens, experience in separating allergen-containing and allergen-free products and raw materials during transport and storage, and staff training in allergen control. At the same time, the PCR method was used to study 15 samples of meat products manufactured at the selected enterprise for the presence of legumes (soybeans), gluten, mustard, and peanuts. In six samples, undeclared allergens were detected in quantities hazardous to the health of the consumer. The results obtained indicated the need to develop and implement measures aimed at minimizing the risk of allergen transfer to the meat products during their production. Based on the results of the research, a procedure for allergen control has been developed, including additional measures for the control of food allergens.
Genome-wide analysis in the search for candidate genes associated with meat productivity traits in meat-and-dairy goats
Authors: Selionova M. I. , Aibazov A.-M. M. , Sermyagin A. A. , Belous A. A. , Zinovieva N. A. 
Published: December 2022

The development of the tourism cluster in the North Caucasus causes the expansion of product range with high consumer characteristics, in particular, a sustainable offer of dairy and meat products labeled as environmentally friendly. In the range of such products with high dietary properties, a special role may be played by goat meat obtained from Karachay goats, which are the most common meat-and-dairy goats in the region. The aim of the work was to search for candidate genes associated with live weight and meat productivity of Karachay goats. GWAS analysis using Goat 50K BeadChip high-density DNA microarray determined a genome-wide level of significance for six SNPs located on chromosomes 5, 6, 10 and 16 associated with the live weight of young animals (4 and 8 months old). Three of the six SNPs within the ± 200 kb region were localized to HMGA2, CRADD, and MAX genes. These genes were selected to study the meat productivity traits of young goats with different genotypes. It was found that in the locus linked with HMGA2 gene, young goats with GG genotype were characterized by the best indicators of meat productivity. Compared to AA genotype animals, they had superiority in pre-slaughter weight, slaughter carcass weight, slaughter yield, boneless meat weight and loin eye area by 8.9%, 13.6%, 4.3% (P<0.05), 10.5% (P<0.05) respectively. Young goat meat of this genotype was characterized by the high protein content of 22.56% and low fat content of 9.12%. For the CRADD gene, animals with GG genotype had a higher pre-slaughter weight, slaughter weight, slaughter carcass yield, boneless meat weight and loin eye area. Animals with AG genotype were characterized by the lowest indicators. According to the above characteristics, the difference between the compared genotypes was 15.8%, 25.7% (P<0.01), 8.4% (P <0.05), 18.3%, and 15.7% (P 0.01) respectively. There were no significant differences in the chemical composition of muscle tissue between animals of different genotypes. HMGA2 and CRADD genes are promising for further research of Karachay goats breeding to increase meat productivity and meat quality.
The water finance gap and the multiple interpretations of ‘bankability’
Authors: McCoy Wilder , Schwartz Klaas 
Published: December 2022

Abstract
In discussing progress on achieving SDG target 6.1 (universal access to water services by 2023), a large ‘financing gap’ is frequently referred to. It is often repeated in development circles that the key to bridging the ‘financing gap’ in the water sector is through the creation of ‘bankable’ water projects. However, there remains a wide gap between technical professionals in the water sector and market-oriented financiers in understanding how ‘bankability’ is practically operationalized. This paper presents a framework of bankability, which highlights the complexity of making projects in the water services sector bankable. This complexity means that making projects bankable requires innovative water project structuring to align interests of investors, water entrepreneurs, and society to leverage more capital into the water sector.