bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating marginal external costs for road, rail and river transport in Colombia
Authors: Márquez Díaz Luis Gabriel 
Published: November 2022

This report presents the results of research regarding strategic freight transport network modelling in Colombia using external cost. The model uses sequential equilibrium between distribution and traffic assignment phases; it is national and inter-regional, involving strategic decision-making. The Colombian transport network consists of 27,469 km of roads, 11,257 km of navigable rivers, 2,192 km of railway lines and a set of centroid connectors for establishing a link with the zoning system (consisting of 70 internal areas and 8 external areas). Each link in a network involves internal costs: time, operation and external costs, congestion, accidents, air pollution and CO2 emissions. Vehicle ownership costs were excluded from internal cost analysis; costs such as noise, climate change and effects on the landscape were not studied in external costs. Marginal costs regarding the network were estimated by two methods. First, it was assumed that an additional unit of demand did not affect equilibrium in a transport network and then marginal cost was estimated as being the sum of marginal costs regarding links in the shortest path. The other approach assumed that an additional unit of demand changed network equilibrium; marginal costs were then estimated by calculating the difference between the two equilibrium scenarios. The methods were applied to 7 selected routes covering the most important Colombian freight transport corridors. An average 0.014 US$/ton/km rate was estimated for external costs regarding highway transport, 0.000105 US$/ton/km for water transport and 0.001625 US$/ton/km for railroad transport (preponderance of environmental costs exceeding 90%).
A comparative study of the combustion properties of normal biogas-air mixture and oxygen enriched biogas-air
Authors: Cacua Karen , Amell Andrés , Olmos Luis 
Published: November 2022

Research into renewable energy as energy alternatives and decreasing greenhouse gases from organic waste decomposition make biogas a promising alternative for fossil fuel substitution and an energy source from recovery of organic waste in urban, rural and agroindustrial areas.
This paper presents a sensitivity analysis of oxygen-enriched biogas combustion properties ranging from 22% to 35%. Results showed that properties such as deflagration speed, adiabatic flame temperature, dew temperature and CO2 and H2O percentage increased when oxygen percentage in air was increased. On the other hand, properties such as minimum ignition energy, stoichiometric air volume and dry fume volume decreased when the O2 percentage in air was higher than 21%.
Neural fuzzy digital filtering: multivariate identifier filters involving multiple inputs and multiple outputs (MIMO)
Authors: García Infante Juan Carlos , Medel Juárez José de J. , Sánchez García Juan Carlos 
Published: November 2022

Multivariate identifier filters (multiple inputs and multiple outputs - MIMO) are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948). This paper considers the MIMO digital filter model using neuro fuzzy digital filtering to find an adaptive parameter matrix which is integrated into the Kalman filter by the transition matrix. The filter uses the neural network as back-propagation into the fuzzy mechanism to do this, interpreting its variables and its respective levels and selecting the best values for automatically adjusting transition matrix values. The Matlab simulation describes the neural fuzzy digital filter giving an approximation of exponential convergence seen in functional error.
Denoising of Distributed Acoustic Sensing Seismic Data Using an Integrated Framework
Authors: Chen Yangkang , Savvaidis Alexandros , Fomel Sergey , Chen Yunfeng , Saad Omar M. , Wang Hang , Oboué Yapo Abolé Serge Innocent , Yang Liuqing , Chen Wei 
Published: November 2022

Abstract
Distributed acoustic sensing (DAS) is an emerging technology that offers great potential in the high-resolution multi-scale seismic investigation due to its dense spatial coverage and cost-effectiveness. However, DAS data notoriously suffer from the low signal-to-noise ratio (SNR) due to various types of strong noise, for example, high-frequency noise, high-amplitude erratic noise, vertical or horizontal noise. Here, we propose a novel denoising framework by cascading several individual denoising methods that are designed for suppressing specific types of noise. First, to suppress the high-frequency noise, we apply a bandpass filter, which is implemented by recursive infinite impulse response filtering in the time domain. Second, to suppress the erratic noise, we apply a structure-oriented median filter that arises from the reflection seismology field. Finally, to suppress the vertical or horizontal noise, we apply a carefully designed dip filter in the frequency–wavenumber domain. The overall effect of these cascaded denoising steps is that the DAS data can be dramatically improved in terms of SNR. We introduce in detail the implementations of each step in the proposed denoising framework and analyze their respective contribution toward the final improvement. We demonstrate the effectiveness of the proposed denoising framework through the open-access Frontier Observatory for Research in Geothermal Energy (FORGE) geothermal DAS dataset and provide the reproducible processing workflows for all the DAS subsets containing the catalog earthquake and microseismic events.
Opportunities for the Formation of National Self-Awareness of Schoolchildren Ьу Means of а Cultural and Developmental Environment in the System of Additional Education
Authors: Васильева А.И. , Тагариева И.Р. 
Published: November 2022

Рассматривается проблема формирования у школьников национального самосознания как важной составляющей социализации гражданина. Показана важность сохранения традиций национальной культуры, уважения к историческому быту и современному образу жизни представителей других национальностей и этнических групп в современных условиях. Представлены подходы к реализации авторской модели формирования национального самосознания у школьников 7–15 лет в системе дополнительного образования средствами культурно-развивающей среды, показаны основные результаты опытно-экспериментальной работы.
The problem of the formation of national self-consciousness among schoolchildren as an important component of the socialization of a citizen is considered. The importance of preserving the traditions of national culture, respect for the historical way of life and the modern way of life of representatives of other nationalities and ethnic groups in modern conditions is shown. Approaches to the implementation of the author’s model of the formation of national self-consciousness among schoolchildren aged 7–15 years in the system of additional education by means of a cultural and developing environment are presented, the main results of experimental work are shown.
Comparative Effectiveness of Virtual Reality (VR) vs 3D Printed Models of Congenital Heart Disease in Resident and Nurse Practitioner Educational Experience
Authors: Awori Jonathan , Friedman Seth D. , Howard Christopher , Kronmal Richard , Buddhe Sujatha 
Published: November 2022

Abstract
Background:
Medical trainees frequently note that cardiac anatomy is difficult to conceive within a two dimensional framework. The specific anatomic defects and the subsequent pathophysiology in flow dynamics may become more apparent when framed in three-dimensional models. Given the evidence of improved comprehension using such modeling, this study aimed to contribute further to that understanding by comparing Virtual Reality (VR) and 3D printed models (3DP) in medical education.
Objectives:
We sought to systematically compare the perceived subjective effectiveness of Virtual Reality (VR) and 3D printed models (3DP) in the educational experience of residents and nurse practitioners.
Methods:
Trainees and practitioners underwent individual 15-minute teaching sessions in which features of an anatomically normal heart as well as a congenitally diseased heart were demonstrated using both Virtual Reality (VR) and 3-D printed models (3DP). Participants then briefly explored each modality before filling out a short survey in which they identified which model (3DP or VR) they felt was more effective in enhancing their understanding of cardiac anatomy and associated pathophysiology. The survey included a binary summative assessment and a series of Likert scale questions addressing usefulness of each model type and degree of comfort with each modality.
Results:
27 pediatric residents and 3 nurse practitioners explored models of normal heart and tetralogy of Fallot pathology. Most participants had minimal prior exposure to VR (1.1 ± 0.4) or 3-D printed models (2.1 ± 1.5). Participants endorsed a greater degree of understanding with VR models (8.5±1) compared with 3D Printed models (6.3±1.8) or traditional models of instruction (5.5±1.5) p<0.001. Most participants felt comfortable with modern technology (7.6 ± 2.1). 87% of participants preferred VR over 3DP.
Conclusions:
Our study shows that, overall, VR was preferred over 3DP models by pediatric residents and nurse practitioners for understanding cardiac anatomy and pathophysiology.
Exploring the mechanism by which aqueous Gynura divaricata inhibits diabetic foot based on network pharmacology, molecular docking and experimental verification
Authors: Sun Yu , Gao Cailiang , Liu Huiting , Liu Xue , Yue Tun 
Published: November 2022

Abstract
Background
To predict and validate the potential mechanism by which Gynura divaricata (GD) functions in the treatment of diabetic foot (DF).
Methods
The main chemical constituents of GD were identified by reviewing the literature, the traditional Chinese medicine database platform (TCMIP) and the BATMAN-TCM platform. DF disease targets were identified with the GeneCards database, and the compound-target network was constructed by using the intersection of drugs and disease. The STRING platform was used to construct the protein–protein interaction (PPI) network, and Cytoscape 3.7.2 software was used to visualize the results. Moreover, the Metascape database was used for Gene Ontology (GO) enrichment analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking of the active ingredients of GD and core protein targets of DF was performed using AutoDock software. Finally, the predicted results were preliminarily verified with experiments.
Results
A total of 140 potential targets of GD were identified and associated with DF. According to the PPI network analysis, GD accelerated DF wound healing, and the mechanism may be related to proteins such as AKT1, TP53, IL6, CASP3, TNF, and VEGFA. GO and KEGG enrichment analyses indicated that GD may play a role in the treatment of diabetic foot by affecting various signaling pathways. Molecular docking results showed that the proteins AKT1, TP53, IL6, CASP3, TNF, and VEGFA were closely associated with the components of GD. The animal experiments showed that GD reduced the levels of IL-6 and TNF-α and increased the mRNA and protein expression of VEGFA in rats with DF.
Conclusions
GD regulates multiple targets and multiple pathways to promote wound healing in DF.
New Mixed Integer Fractional Programming Problem and Some Multi-objective Models for Sparse Optimization
Authors: Pirouz Behzad , Gaudioso Manlio 
Published: November 2022

Abstract
We propose a novel Mixed-Integer Nonlinear Programming (MINLP) model for sparse optimization based on the polyhedral k-norm. We put special emphasis on the application of sparse optimization in Feature Selection for Support Vector Machine (SVM) classification. We address the continuous relaxation of the problem, which comes out in the form of a fractional programming problem (FPP). In particular, we consider a possible way for tackling FPP by reformulating it via a DC (Difference of Convex) decomposition. We also overview the SVM models and the related Feature Selection in terms of multi-objective optimization. The results of some numerical experiments on benchmark classification datasets are reported.
Acute Atrial Fibrillation During Onset of Stroke Indicates Higher Probability of Post-Stroke Death Outcomes
Authors: Li Yongxia , Gao Qin , Jiang Jiamei , Fu Yimu , Xu Qing , Deng Jiangshan , Feng Qiming 
Published: November 2022

Abstract
Patients with atrial fibrillation (AF) have a higher risk of ischemic stroke. However, it is still unknown whether acute atrial fibrillation (AAF) in the emergency department can affect the outcomes of acute ischemic stroke (AIS) patients. In this study, the risk and prognosis of AIS patients with AFF were assessed with a total of 706 identified patients, who were grouped based on their AF history. Logistic regression showed that age ≥ 73 (OR: 2.00; 95% CI: 1.18–3.37; p = 0.010), baseline NIHSS score (OR: 1.18; 95% CI: 1.15–1.22; p < 0.001), and AAF onset (OR: 1.87; 95% CI: 1.09–3.19; p = 0.022), were independent risk factors of severity of early neurological deficits in AIS. Baseline NIH Stroke Scale/Score (NIHSS) (OR: 1.11; 95% CI: 1.08 to 1.13; p < 0.001) and AAF onset (OR: 1.74; 95% CI: 1.01 to 2.98; p = 0.044) were independent predictors of the mortality. AAF in the emergency department was not only an independent risk factor for the severity of early AIS neurological deficits, but also an indicator of high probability of post-stroke death in 30 days.
Correlation and Path Coefficient Analyses in Hot Pepper (Capsicum annum L.)
Authors: Amde Bantayehu 
Published: November 2022

Abstract
To assess the correlation and find out the direct and indirect effect of yield attributing traits on yield, twenty six accessions and four varieties were grown during the off-season period from November 2016 to May 2017 under irrigation at Dire dawa, Ethiopia. The experiment was conducted using RCBD design with three replications. Plant height, primary branch per plot, days to fifty percent flowering, stem width, number of fruit per plant, fruit length, days to maturity and number of fruit per plant were positive and highly significantly correlated with dry fruit yield per plot at both genotypic and phenotypic correlation. Plant height (0.1081), number of fruit per plant (0.2610), fruit length (0.4293), stem width (0.4059), pedicel length (0.0122), days to maturity (0.0401) and internode length (0.0227) exerted positive direct effect on dry fruit yield per plot at phenotypic level. Genotypic path analysis showed that days to fifty percent flowering (0.0956), stem width (0.5867), fruit length (0.3671), plant height (0.0754), number of fruit per plant (0.2673) and internode length (0.0079)had positive direct effect. The direct effect of these characters on dry fruit yield per plot indicates that improvement on these traits may increase yield.
Relationship between Intraoperative Blood Pressure Variability and postoperative Acute Kidney Injury following Non-cardiac Surgery
Authors: yu xinran , han qingbo , yang Jingtao , zu liting , cai lisong , wu shouling , guo pingxuan 
Published: November 2022

Abstract
BACKGROUND
We aimed to determine the effect of intraoperative blood pressure variability on postoperative acute kidney injury (PO-AKI) following non-cardiac surgery.
METHODS
We studied 2,224 patients who underwent non-cardiac surgery under general anesthesia from the Kailuan study cohort. Blood pressure variability was assessed using the coefficient of variation (CV) of the mean arterial pressure (MAP), pulse pressure (PP), systolic pressure (SBP), and diastolic pressure (DBP). The outcome was PO-AKI, defined using the Kidney Disease Improving Global Outcomes criteria. Multivariate logistic regression was used to analyze the effect of short-term intraoperative blood pressure variability on PO-AKI, and the effect of such variability on the change in serum creatinine concentration during surgery was analyzed using a generalized linear model.
RESULTS
PO-AKI occurred in 88 of 1,503 participants. After adjustment for potential confounding factors, the risk of high postoperative serum creatinine and PO-AKI increased with increasing blood pressure variability; generalized linear models showed that increases of single units in MAP_CV, PP_CV, and SBP_CV were associated with increases in serum creatinine of 0.23 µmol/L, 0.17 µmol/L, and 0.30 µmol/L, respectively. Multivariate logistic regression showed that with MAP_CV and SBP_CV quartiles as independent variables, the odds ratios (95% confidence intervals) for PO-AKI in the highest quartiles were 2.00 (1.03–3.92) and 2.24 (1.08–4.60), respectively, versus the lowest quartiles.
CONCLUSIONS
During non-cardiac surgery, high blood pressure variability is positively associated with increases in the risks of high serum creatinine and PO-AKI, with SBP variability having the strongest relationship.
Clinical characteristics analysis and predictive diagnostic model building of community-acquired pneumonia in adults requiring hospitalisation in Fujian Provincial Hospital
Authors: Wu Fan , Yue Wenxiang , Wu Jian , Zhao Yunan , Yu Xueying , Zhang Chi , Hu Xinlan , Xu Nengluan , Lin Ming , Xiao Yan , Ren Lili , Chen Yusheng , Li Hongru 
Published: November 2022

Abstract
Background
We compared the clinical characteristics of infections caused by different pathogens and established a viral/bacterial infection prediction model to guide early clinical identification of pathogens among inpatients with community-acquired pneumonia (CAP).
Methods
Data were analysed to establish a prediction model for the early treatment of bacterial or viral infections. Basic data, clinical symptoms, laboratory examinations, and imaging of patients were collected and compared, and the virus/bacteria prediction equation was established.
Results
The proportion of patients with muscle soreness and headaches was significantly higher in the viral infection group than in the bacterial infection group. Procalcitonin (PCT) levels, erythrocyte sedimentation rate (ESR), and neutrophil alkaline phosphatase (NAP) scores were significantly higher in the bacterial infection group than in the viral infection group. The creatine kinase level was significantly higher in the viral infection group than in the bacterial infection group (P < 0.05). More patients in the atypical pathogen infection group (up to 52.0%) had real lung degeneration, and the difference was statistically significant compared with other groups (P < 0.005). Patchy shadows were more common in the viral infection group than in other groups (up to 92.5%). There were significant differences in the PCT levels and the presence of fever or muscle soreness between the groups. A binary logistic regression equation was obtained, which could predict the probability of viral infection (sensitivity 57.5%, specificity 67.7%, area under the ROC curve 0.651).
Conclusions
Adult CAP patients with viral infection are more likely to have headaches and muscle soreness than those with bacterial infection. An elevated PCT level, NAP score, and ESR indicated a high possibility of bacterial infection. Accordingly, a viral and bacterial infection prediction model was established.
ICT4D: development or destabilization? A cross-country study on the polarizing effect of political disinformation through social media
Authors: Vasist Pramukh Nanjundaswamy , Krishnan Satish 
Published: November 2022

Abstract
Information and communication technologies hold immense potential to enhance our lives and societal well-being. However, digital spaces have also emerged as a fertile ground for propaganda operations and fake news campaigns, which pose a threat to societal harmony. Despite the fact that this dark side is acknowledged in the literature, little is known about the diverse influence of disinformation operations by a variety of actors. In addition, internet censorship and social media monitoring efforts have largely been accused of stifling personal liberties. The current study builds on these gaps and challenges the status quo by drawing on complexity theory and utilizing fsQCA for a cross-country investigation of the influence of a variety of disinformation campaigns and hate speech in polarizing societies. In doing so, it offers a balanced perspective on internet censorship and social media monitoring as necessary evils to combat the disinformation menace and sheds light on the definitive role of foreign disinformation and hate speech. Implications for theory and practice are discussed.
Patient-derived zebrafish xenografts of uveal melanoma reveal ferroptosis as a drug target
Authors: Groenewoud Arwin , Yin Jie , Gelmi Maria-Chiara , Alsafadi Samar , Nemati Fariba , Decaudin Didier , Roman-Roman Sergio , Kalirai Helen , Coupland Sarah , Jochemsen Aart , Jager Martine , Engel Felix , Snaar-Jagalska Ewa 
Published: November 2022

Abstract
Uveal melanoma (UM) has a high risk to progress to metastatic disease with a median survival of 3.9 months after metastases detection, as metastatic UM responds poorly to conventional and targeted chemotherapy and is largely refractory to immunotherapy. Here, we present a patient-derived zebrafish UM xenograft model mimicking metastatic UM. Cells isolated from Xmm66 spheroids derived from metastatic UM patient material were injected into 2 days-old zebrafish larvae resulting in micro-metastases in the liver and caudal hematopoietic tissue. Metastasis formation could be reduced by navitoclax and more efficient by the combinations navitoclax/everolimus and flavopiridol/quisinostat. We obtained spheroid cultures from 14 metastatic and 10 primary UM tissues, which were used for xenografts with a success rate of 100%. Importantly, the ferroptosis-related genes GPX4 and SLC7A11 are negatively correlated with the survival of UM patients (TCGA: n = 80; Leiden University Medical Centre cohort: n = 64), ferroptosis susceptibility is correlated with loss of BAP1, one of the key prognosticators for metastatic UM, and ferroptosis induction greatly reduced metastasis formation in the UM xenograft model. Collectively, we have established a patient-derived animal model for metastatic UM and identified ferroptosis induction as a possible therapeutic strategy for the treatment of UM patients.