bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of production and injection wells location in an oil field with faulted oil-rich reservoir zones in southern Iran using GA, PSO, and HGAPSO algorithms
Authors: Nikravesh Hamed , Azin Reza , Ranjbar Ali 
Published: November 2023

Abstract
The problem is to optimize the location of wells and injection sites in such a way as to maximize oil production and also protect oil reservoirs from possible damages. In this study, oil well location optimization and economic evaluation in the water injection process have been done. In this regard, three particle swarm optimization algorithms (PSO), Genetic Optimization Algorithm (GA) and Hybrid Optimization Algorithm (HGAPSO) and Net Present Value (NPV) calculation have been performed. In this simulation, 100 repetitions and 50 particles were used. The results of the simulations show that the PSO algorithm has a better performance than the GA and HGAPSO algorithms and can be used as a strong and effective method to optimize the location of wells and the number of production and water injection wells in the oil injection process. We want to optimize the production well, the PSO algorithm has been 124.12% more profitable than the production in the well location optimization mode in the conventional way. The GA algorithm has been 124.12% more profitable than the production in the conventional well drilling mode The HGAPSO algorithm has 123.45% more profit than the production in the case of optimizing the location of the well by the conventional method. In the case of optimizing the location of 2 injection wells, the simulation results of each of the PSO, GA and HGAPSO algorithms are respectively 118.6%. and 118.58% and 118.51% shows more profit than the production in the case of optimizing the well location in the conventional way. In the studied reservoir, PSO algorithm in the case where the location of 4 production wells is optimized, the production has increased by 18.7% compared to the production in the case of optimizing the location of wells in the conventional way. When the location of two injection wells is optimized with the PSO algorithm, production has increased by 18.8% compared to the time of drilling an injection well using the conventional method.
Factors affecting decisions of an HMO Drug Exemptions Committee on individual patient requests for coverage of non-formulary drugs
Authors: Topol Yael , Weiss Lior , Lomnicky Yossi , Yifrach-Damari Inbal , Markovits Noa , Loebstein Ronen , Gueta Itai 
Published: November 2023

Abstract

Background
In Israel, coverage of health needs is delivered by four health maintenance organizations (HMOs), which are budgeted by the government according to the recommendations of the National Drug Formulary (NDF) Committee. For medications not listed in the NDF, individuals may request to cover the costs by the HMO Exemptions Committee (DEC). The objectives of the current study, a first of its kind, are to document the DEC decision process, to identify its components as formalized in the USA (Eddy criteria) and to determine the decisions' clinical outcome.
Methods
This retrospective cohort study included all members (≥ age 18) of the Maccabi Healthcare Service (MHS) who submitted a request to the DEC between June 2017 and December 2018. Collected data include patient demographics, clinical information and components of the decision process. Decision success was defined by clinical outcome over a one-year follow-up.
Results
A total of 335 requests were included. Strong evidence and rare disease were positively associated with approvals, while the availability of alternative treatments and costs were negatively associated. In the majority of decisions (75%), clinical outcome was correctly anticipated by the DEC (i.e., a successful decision). Only estimated costs were found to be associated with decision success.
Conclusions
Factors that reduce the potential costs of a requested drug are significantly associated with higher odds for drug approval, but only when the evidence supports potential benefit. Given that no objective measurement could predict decision outcomes, and yet > 70% were found to be correct, it appears that the mixture of committee members may in itself be a determining factor.
Piezo2 contributes to traumatic brain injury by activating the RhoA/ROCK1 pathways
Authors: Xiao Yinggang , Zhang Yang , Yuan Wenjuan , Wang Cunjin , Ge Yali , Huang Tianfeng , Gao Ju 
Published: November 2023

Abstract
Traumatic brain injury (TBI) can lead to short-term and long-term physical and cognitive impairments, which have significant impacts on patients, families, and society. Currently, treatment outcomes for this disease are often unsatisfactory, due at least in part to the fact that the molecular mechanisms underlying the development of TBI are largely unknown. Here, we observed significant upregulation of Piezo2, a key mechanosensitive ion channel protein, in the injured brain tissue of a mouse model of TBI induced by controlled cortical impact. Pharmacological inhibition and genetic knockdown of Piezo2 after TBI attenuated neuronal death, brain edema, brain tissue necrosis, and deficits in neural function and cognitive function. Mechanistically, the increase in Piezo2 expression contributed to TBI-induced neuronal death and subsequent production of TNF-α and IL-1β, likely through activation of the RhoA/ROCK1 pathways in the central nervous system. Our findings suggest that Piezo2 is a key player in and a potential therapeutic target for TBI.
Optimizing the detection of emerging infections using mobility-based spatial sampling
Authors: Zhang Die , Ge Yong , Wang Jianghao , Liu Haiyan , Zhang Wen-Bin , Wu Xilin , Heuvelink Gerard , Wu Chaoyang , Yang Juan , Ruktanonchai Nick , Qader Sarchil , Ruktanonchai Corrine , Cleary Eimear , Yao Yongcheng , Liu Jian , Nnanatu Chibuzor , Wesolowski Amy , Cummings Derek , Tatem Andrew , Lai Shengjie 
Published: November 2023

Abstract

Background
Timely and precise detection of emerging infections is crucial for effective outbreak management and disease control. Human mobility significantly influences infection risks and transmission dynamics, and spatial sampling is a valuable tool for pinpointing potential infections in specific areas. This study explored spatial sampling methods, informed by various mobility patterns, to optimize the allocation of testing resources for detecting emerging infections.
Methods
Mobility patterns, derived from clustering point-of-interest data and travel data, were integrated into four spatial sampling approaches to detect emerging infections at the community level. To evaluate the effectiveness of the proposed mobility-based spatial sampling, we conducted analyses using actual and simulated outbreaks under different scenarios of transmissibility, intervention timing, and population density in cities.
Results
By leveraging inter-community movement data and initial case locations, the proposed case flow intensity (CFI) and case transmission intensity (CTI)-informed sampling approaches could considerably reduce the number of tests required for both actual and simulated outbreaks. Nonetheless, the prompt use of CFI and CTI within communities is imperative for effective detection, particularly for highly contagious infections in densely populated areas.
Conclusions
The mobility-based spatial sampling approach can substantially improve the efficiency of community-level testing for detecting emerging infections. It achieves this by reducing the number of individuals screened while maintaining a high accuracy rate of infection identification. It represents a cost-effective solution to optimize the deployment of testing resources, when necessary, to contain emerging infectious diseases in diverse settings.
Identifying Novel Necroptosis-Related Long Non-Coding RNAs: Prognostic and Immunotherapeutic Implications for Head and Neck Squamous Cell Carcinoma
Authors: Yin Ji , Chen Yuxiang , Bi Junjie , He Lu , Hu Wenjian , Qin Fengfeng 
Published: November 2023

Abstract
Background Necroptosis could be a trigger and amplifier of anti-tumor immunity in cancer therapy. LncRNAsare vital in controlling immune system gene expression. We designed to establish a NRlncRNA signature for evaluation and prognosis prediction in HNSCC, ultimately providing a new perspective for clinical application.
Materials and methods We acquired RNA-seq and clinical data for HNSCC and 67 NRGs. Subsequently, diverse analytical methods were utilized to discern predictive NRlncRNAs, calculate the risk score, and construct a meticulous risk evaluation model. Furthermore, the predictive capability of the risk model was confirmed through survival analysis, ROC curves, PCA, DCA, C-index, and nomograms. We endeavored to discern disparities among distinct cohorts concerning clinical characteristics, the infiltration of immune cells, the sensitivity to pharmaceutical agents, as well as molecules associated with immune response.
Results A risk signature for 12 NRlncRNAs was developed, and the signature had high sensitivity and specificity in predicting survival rates. The established model exhibited a strong association with both survival outcomes and clinical features. Notably, the low-risk group demonstrated a substantially elevated survival probability and displayed a significant positive correlation with diverse immune cell infiltrations. Lastly, we selected different clinical drug regimens based on the different risk groups.
Conclusion A prognostic model of NRlncRNAs has been developed for HNSCC that enables the estimation of the TME and the response to cancer immunotherapy. The model also has the potential to predict the prognosis, which may pave the way for novel clinical applications.
An innovative intergenerational intervention to promote co-physical activity in grandparents and their grandchildren: the ‘Ages get Active’ intervention – Development, insights and future directions
Authors: Iliano Evelien , Cardon Greet , Latomme Julie 
Published: November 2023

Abstract
Background:Intergenerational physical activity programming is a promising approach to increase (co-)physical activity in children and older adults. Unfortunately, most of these programs do not take into account the needs and preferences of the target group and mostly focus on children and older adults who are not family-related. Furthermore, the development process of an intergenerational physical activity program often remains underexamined. This study aims to comprehensively describe the systematic development of an evidence-based, co-created intergenerational physical activity intervention, the ‘Ages get Active’ intervention, which jointly engages grandparents and their grandchildren in physical activity.
Methods: The three stages and seven steps of the theoretical framework, the Behaviour Change Wheel, were described. This theoretical framework was combined with a participatory co-creation approach to develop an intergenerational physical activity program for grandparents and grandchildren. Six grandchildren (1 boy and 5 girls, M age 6.83; Std 1.17) and four grandparents (3 women and 1 man, M age 63.5; Std 3.11) participated in the co-creation sessions. A meeting with organizational stakeholders was organized to gain additional input.
Results: Four intervention components emerged from the development phase: 1) an educational component; 2) organized group-based intergenerational movement sessions; 3) home-based (intergenerational) activities and 4) the promotion of community-based events. The intervention will start with an educational component where grandparents and parents will receive information about the intervention. During six weeks, six movement sessions will take place where grandparents and grandchildren will work on different aspects (coordination, strength,…) together. Grandparents and grandchildren will use a booklet with physical activities they can do together or individually at home and will also receive a list of events they can do together in the community.
Conclusions: The ‘Ages get Active’ intervention was developed using the Behaviour Change Wheel in combination with co-creation. The comprehensive and transparent description of the steps of the Behaviour Change Wheel and how these steps were integrated into the co-creation sessions, findings and insights into the process development can help future researchers and health professionals in developing interventions for older adults (grandparents) and children (grandchildren).
Effect of the observer’s gender bias monitoring acute pain using a validated behavior scale in castrated piglets
Authors: Trindade Pedro Henrique Esteves , Lopez-Soriano Magdiel , Merenda Victoria Rocha , Tomacheuski Rubia Mitalli , Pairis-Garcia Monique Danielle 
Published: November 2023

Abstract
We aimed to investigate the observer’s gender bias on acute pain assessment using the Unesp-Botucatu Pig Composite Acute Pain Scale (UPAPS) in piglets before and after castration. Twenty-nine piglets were filmed at 1h pre-castration, 0h and 3h post-castration. Two observers self-identified as women and two as men, and all four observers assessed all films using the UPAPS. Intraclass correlation coefficient (ICC), Lin's concordance correlation coefficient (CCC), and Bland-Altman were used to estimate the agreement, and modeling was conducted to compare genders. The ICC of the UPAPS total sum was ‘very good’ (0.84) when considering both genders and ‘good’ when considering each gender separately. Furthermore, women had a higher level of agreement (0.74) than men (0.65). The agreement of the UPAPS total sum assessed by women and men demonstrated minimal bias (-0.04), no proportion bias, and 55% of the assessments were identical. The UPAPS total sum was statistically equivalent between genders (P = 0.66). In conclusion, we found no evidence supporting gender bias in applying UPAPS in piglets before and after castration. Our findings permit the assessment of piglets' acute pain regardless of the observers’ gender, which might benefit the swine industry and researchers monitoring pain in piglets.
An Estimated Two-Country DSGE Model to Analyse Monetary Policy with Heterogeneous Agents : Euro Area and the US Economy
Authors: signe Franck Xavier , POUTINEAU Jean-Christophe , Gankou Jean Marie 
Published: November 2023

Abstract
This paper seeks to quantitatively assess the key role in open economy of heterogeneity in the conduct of monetary policy in Europe and the US, we take into account the fact that these two economies trade with each other and with the rest of the world, as well as the role of the exchange rate in trade. Using Bayesian estimation techniques, we estimate two models that take these specific features into account, a model with representative agents (RANK model), a model with heterogeneous agents (TANK model). Analysis of the Bayes ratio and the empirical characteristics of the two models shows that the TANK model plays a key role in the conduct of monetary policy in Europe and the United States and in the mitigation of cycles and fluctuations. The American economy is more sensitive to heterogeneity than the European one, because the differences in parameters between the models are greater in the USA than in Europe.
JEL Classification: E21 , E31 , E40 , E50 , E52 , E61
Digital literacy and online learning satisfaction among junior high school students in the context of COVID-19: The mediating role of online learning engagement and the moderating role of parents' educational expectations
Authors: Liu Xue-zhi , Wu Jian-xiao , Guo Ling-jing , Li Bing-bing , Ye Bao-juan 
Published: November 2023

Abstract
During the COVID-19 lockdown period, educational institutions in many countries adopted online teaching methods to varying degrees to cope with the impact of the epidemic on education, and online learning satisfaction was an important indicator to measure the effect of online learning. This study aimed to explore the mechanism among digital literacy, online learning satisfaction, online learning engagement, and parents' educational expectations. The Digital Literacy Scale, Online Learning Engagement Scale, Perceived Parental Expectation (PPE) Scale, and Satisfaction with the Online Learning Scale were adopted to measure 916 Chinese junior school students. The results were: (1) The digital literacy of junior high school students had a positive correlation with their online learning satisfaction. (2) Online learning engagement mediated the relationship between digital literacy and online learning satisfaction. (3) The positive effect of digital literacy on online learning engagement was different among middle school students who perceived different levels of parental educational expectations; that is, parental educational expectations moderated the first half of the mediating effect. The relationship between digital literacy and online learning satisfaction was a moderated mediated model. More measures should be taken to improve the digital literacy of middle school students and promote the quality of online learning.
Numerical simulation and in vitro experimental study of the hemodynamic performance of vena cava filters with helical forms
Authors: Huang Yuxiang , Li Qi , Liu Ming , Zhao Ming , Chen Ying 
Published: November 2023

Abstract
Inferior vena cava filter (IVCF) implantation is a common method of thrombus capture. By implanting a filter in the inferior vena cava (IVC), microemboli can be effectively blocked from entering the pulmonary circulation, thereby avoiding acute pulmonary embolism (PE). Inspired by the helical flow effect in the human arterial system, we propose a helical retrievable IVCF, which, due to the presence of a helical structure inducing a helical flow pattern of blood in the region near the IVCF, can effectively avoid the deposition of microemboli in the vicinity of the IVCF while promoting the cleavage of the captured thrombus clot. It also reduces the risk of IVCF dislodging and slipping in the vessel because its shape expands in the radial direction, allowing its distal end to fit closely to the IVC wall, and because its contact structure with the inner IVC wall is curved, increasing the contact area and reducing the risk of the vessel wall being punctured by the IVCF support structure. We used Ansys Fluent software to conduct unidirectional fluid-structure coupling simulation of four different forms of IVCF, combined with microthrombus capture experiments in vitro, to explore the impact of these four forms of IVCF on blood flow patterns and to evaluate the risk of IVCF perforation and IVCF dislocation. It can be seen from the numerical simulation results that the helical structure does have the function of inducing blood flow to undergo helical flow dynamics, and the increase in wall shear stress (WSS) brought about by this function can improve the situation of thrombosis accumulation to a certain extent. Meanwhile, the placement of IVCF will change the flow state of blood flow and lead to the deformation of blood vessels. In in vitro experiments, we found that the density of the helical support rod is a key factor affecting the thrombus trapping efficiency, and in addition, the contact area between the IVCF and the vessel wall has a major influence on the risk of IVCF displacement.
DocXClassifier: Towards a Robust and Interpretable Deep Neural Network for Document Image Classification
Authors: Saifullah Saifullah , Agne Stefan , Dengel Andreas , Ahmed Sheraz 
Published: November 2023

Abstract
Model interpretability and robustness are becoming increasingly critical today for the safe and practical deployment of deep learning (DL) models in industrial settings. As DL-backed automated document processing systems become increasingly common in business workflows, there is a pressing need today to enhance interpretability and robustness for the task of document image classification, an integral component of such systems. Surprisingly, while much research has been devoted to improving the performance of deep models for this task, little attention has been given to their interpretability and robustness. In this paper, we aim to improve upon both aspects and introduce DocXClassifier, an inherently interpretable deep document classifier that not only achieves significant performance improvements over existing approaches in image-based document classification, but also holds the capability to simultaneously generate feature importance maps while making its predictions. Our approach attains state-of-the-art performance in image-based classification on two popular document datasets, RVL-CDIP and Tobacco3482, with top-1 classification accuracies of 94.17% and 95.57%, respectively. Additionally, it sets a new record for the highest image-based classification accuracy on Tobacco3482 without transfer learning from RVL-CDIP, at 90.14%. In addition, our proposed training strategy demonstrates superior robustness compared to existing approaches, significantly outperforming them on 19 out of 21 different types of novel data distortions, while achieving comparable results on the remaining two. By combining robustness with interpretability, DocXClassifier presents a promising step towards the practical deployment of DL models for document classification tasks.
Overfertilization alters the ecological interactions and floral morphology in peri-urban environment
Authors: Vera Gabriel A. Brito , Calderón Ximena , Pérez Fernanda 
Published: November 2023

Abstract
Nitrogen is a crucial element that affects plant metabolic processes and indirectly influences the structure and dynamics of ecological interactions in terrestrial ecosystems. Since the invention of the Haber-Bosch process, human activity has significantly influenced the amount of nitrogen released into the environment. But, how might these processes of overfertilization impact flora and fauna within urban ecosystems? In our experiment, we employed elevated nitrogen concentrations to simulate terrestrial eutrophication in Nicotiana tabacum. We assessed the floral morphology through geometric morphometrics and quantified the nectar volume and the concentration of solutes. Subsequently, we investigated the impact of these modifications on herbivory and pollination interactions in a peri-urban setting. Overfertilization resulted in notable modifications to the floral shape of the lobes, along with a significant increase in herbivory rates due to chewing insects and daily pollination rates. However, we observed that herbivory intensity in fertilized plants and reduction in leaf size at the end of the experiments were not directly correlated with the overall pollination rate per plant. Furthermore, our findings indicate that the daily pollination rates were influenced by overfertilization. However, this increase was not attributed to the energetic content of nectar (including volume, concentration, and energy), but probably to other factors, such as the presence of nitrogen compounds in the nectar. Nitrogen is a crucial element not only for plants in natural terrestrial ecosystems but also plays a fundamental role in the modification and shaping of reproductive and vegetative structures. Moreover, it affects the functionality of ecological interactions of pollination and herbivory in anthropogenic environments such as peri-urban areas under potential terrestrial eutrophication scenarios.