bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tubing and Rod Failure Analysis in Rod Pumped Wells in an Indian Western Oil Field
Authors: Kumar Avinav , Upadhyay Rajeev , Kumar Sachiv 
Published: November 2022

Summary
Sucker rod pump (SRP) is the most popular form of artificial lift, used in one of the western assets of Oil and Natural Gas Corporation (ONGC). It has been used to produce both vertical and deviated wells. In one of the mature fields, frequent tubing and sucker rod failures have been witnessed in both vertical and deviated SRP wells with mean time between failures (MTBF) as low as 4–5 months, which resulted in frequent workover and associated workover cost and production loss. Rubbing between tubing and sucker rod in deviated wells and bending of rods and tubing in vertical and deviated wells below the rod and tubing neutral point in wells experiencing higher compressive load, as a result of loads caused by the frictional and viscous forces inside the tubing string, such as the mechanical pump friction, the friction between the rods and fluid, the fluid and tubing, the tubing and rods, and the friction due to the fluid flowing through valves, has resulted in wearing of downhole equipment and holes in tubings.
The paper analyzes the cause of failures and presents a comprehensive method to mitigate/minimize sucker rod and tubing failure. The study presented in this paper finds its application in a few candidate wells of ONGC, for the first time, where increased MTBF was achieved by the successful adoption of the said method. In addition, the present study has brought uniqueness by integrating the existing knowledge to bring out a rigorous workflow for maximizing the life of SRPs leading to considerable value addition to sucker rod operations of the candidate wells of ONGC. The suggested approach was useful in formulating a novel strategy to minimize the rod and tubing failure by application of a proposed workflow that includes (1) defining a computational method to estimate lateral loads acting along the rod string in deviated wells and to estimate tubing and sucker rod neutral point, (2) quantification of the number of guides to be placed below the neutral point and at points where the lateral load is high, and (3) estimation of the depth of the tubing anchor or length of the tail pipe to eliminate/minimize tubing buckling. The proposed method finds its validation in the field application, which is elaborately discussed in this paper.
Theoretical and Experimental Study of Fine Migration During Low-Salinity Water Flooding: Effect of Brine Composition on Interparticle Forces
Authors: Khezerloo-ye Aghdam Saeed , Kazemi Alireza , Ahmadi Mohammad 
Published: November 2022

Summary
The majority of sandstone reservoirs contain clay particles. When clay is exposed to low-salinity water, fine detachment and migration occur due to multi-ion exchange and electrical double layer (EDL) expansion. Fine migration due to low-salinity water enhances oil recovery while damaging injection and production wells.
This research investigates the effect of clay particles' weight percentage (wt%), ionic strength, total dissolved solids, and the injection rate of the low-salinity water on fine migration. The interparticle forces of kaolinite-kaolinite and kaolinite-quartz systems in various mediums were determined. Ten quartz sandpacks containing 2, 5, and 10 wt% of kaolinite were made to simulate clay-rich sandstone reservoirs. Afterward, different brines (10 and 50 mM solutions of NaCl, CaCl2, MgCl2, and Na2SO4 salts as well as seawater and its diluted samples) were injected into these sandpacks with different scenarios. It was observed that the interparticle forces for both systems in the presence of 10 mM solutions of NaCl, Na2SO4, and also 50 mM NaCl are repulsive.
Therefore, even by injecting the low flow rate of these samples (0.1 cm3/min), the total fine migration was observed leading to intense permeability reduction in high clay-rich sandstones. However, in the case of low clay-containing sandpacks, the magnitude of permeability starts to rise a while after getting imposed to fine migration. In the presence of brines containing 50 mM MgCl2 and CaCl2, seawater, and its five-times diluted sample, the interparticle forces were an attraction, and fine migration occurred under no condition. However, using other samples of low-salinity water, the interparticle forces in the kaolin-kaolin system were repulsive and attractive in the kaolin-quartz system. Therefore, the phenomenon of partial fine migration occurs while flooding. So, in low-clay sandpacks, fines migrated only in high rate injection. However, the fine migration was evident for sandpacks containing 10 wt% of clay particles even by low flow rate injection. In general, there is a trade-off between the intensity of fine migration and divalent cations concentration in flooding water. Eliminating these cations or using them at 10 mM concentration may result in total fine migration, which is beneficial for low clay-containing media but damages clay-rich ones strongly. A high concentration of these cations prevents fines from movement, eradicating low-salinity flooding advantages. However, using medium concentrations results in partial fine migration, and the intensity, in this case, depends on clay concentration and flooding rate.
Machining of Ebm Ti-6AL-4V Titanium Alloy Functional Femoral Cone
Authors: Festas António , Ramos A. , Davim J. P. 
Published: November 2022

Abstract
The advantages revealed by the application of 3D manufacturing processes such as Electron Beam Melting (EBM) are decisive in the manufacture of medical devices such as orthopedic implants, especially in custom-made devices. However, machining operations are indispensable on surfaces where surface roughness and dimensional accuracy have more demanding requirements.
This exploratory work aimed to manufacture by CNC turning of a functional cone of the modular component of the hip prosthesis obtained from titanium alloy Ti-6Al-4V obtained initially by EBM as well as a wrought rod. For this purpose, the differences in cutting forces and the surface roughness of the surface obtained in the turning tests were the object of analysis.
From the results obtained through turning tests, EBM test samples presented slightly higher roughness values and lower resulting cutting forces. The effect of the shell geometry of the EBM test samples did not decisively influence the results obtained, which means that it is possible to explore this potentiality in the design of components as it materializes as an economic advantage in the manufacture.
Students’ experiences of learning in virtual classrooms facilitated by Google Classroom
Authors: Hamad Wahid B. 
Published: November 2022

AbstractThe study evaluated students’ experience of learning with virtual classrooms facilitated by Google Classroom at the institute of social work, Dar es Salaam, Tanzania. The study employed the Activity Theory (AT) as a theoretical framework using the first triangle of the activity system, which includes three components - Subject-Tool-Object (S-T-O). In this study, an anonymous online survey was adopted for data collection and the quantitative method was used to analyze data. Additionally, the survey questionnaires were prepared and distributed using the KoBo Toolbox. The sample size considered a subgroup of the institute students, which includes the BTCLRPM, ODLRPM & BLRPM from the labor studies departments. At the end of the data collection period, 82 questionnaires were collected. Only 79 (96%) questionnaires yielded valid responses and were considered for analysis and 3 (4%) questionnaires were excluded as they are not yielded valid responses. The finding revealed that the student’s opinions specified that overall students were more interested in learning activities using the Google Classroom platform as a learning tool and they managed to achieve learning goals in the ICT module. Alternatively, the findings from ANOVA comparing the differences between the groups of students concerning the use of Google classroom as a learning tool revealed that the ODLRPM and BTCLRM students demonstrated higher online/blended learning experiences of using Google Classroom for the ICT module compared to BLRPM students. Finally, the study calls for institute policymakers to plan and initiate the policy for the usage of web 2.0 tools such as Google Classroom in the facilitation of online/blended teaching and learning at the institute.
Study Protocol: Short Against Long Antibiotic Therapy for Infected Orthopaedic Sites - SALATIO Trials
Authors: Uçkay Ilker , Wirth Stephan , Zörner Björn , Fucentese Sandro , Wieser Karl , Schweizer Andreas , Müller Daniel , Zingg Patrick , Farshad Mazda 
Published: November 2022

Abstract
Background: Few studies address the appropriate duration of post-surgical antibiotic therapy for orthopedic infections; with or without infected residual implants. We perform two similar randomized-clinical trials (RCT) to reduce the antibiotic use and associated adverse events.
Methods: Two unblinded RCTs in adult patients (non-inferiority with a margin of 10%, a power of 80%) with the primary outcomes "remission" and "microbiologically-identical recurrences" after a combined surgical and antibiotic therapy. The main secondary outcome are antibiotic-related adverse events. The RCTs allocate the participants between 3 vs. 6 weeks of post-surgical systemic antibiotic therapy for implant-free infections; and between 6 vs. 12 weeks for residual implant-related infections. We need a total of 280 episodes (randomization schemes 1:1) with a minimal follow-up 12 months. We perform two interim analyses starting approximately after 1 and 2 years. The study approximatively lasts 3 years.
Discussion: Both parellel RCT will enable to prescribe less antibiotics for future orthopedic infections in adult patients.
Trial registration: ClinicalTrial.gov NCT05499481. Registered on 12 August 2022.
Protocol version: 2 (19 May 2022)
Consumption of ultra-processed foods and cardiometabolic risk factors in Brazilian adolescents: results from ERICA
Authors: Madalosso Mariana Migliavacca , Martins Nina Ferreira , Medeiros Brenda Massochin , Rocha Luana , Mendes Larissa , Schaan Beatriz , Cureau Felipe 
Published: November 2022

Abstract
Introduction: The consumption of ultra-processed foods (UPF), associated with overweight among adolescents, has increased in the last decades. However, few studies have investigated the association between UPF consumption and cardiovascular risk factors in adolescents from developing countries.
Objective: To evaluate the association between UPF consumption and cardiometabolic risk factors in Brazilian adolescents.
Methods: The sample consisted of Brazilian students aged 12–17 years from the Study of Cardiovascular Risk in Adolescents. Food consumption was assessed using a 24-hour food recall and the foods were classified according to their processing degree, based on the NOVA classification. Blood samples were collected after overnight fasting, and laboratorial analyses (triglycerides, total cholesterol, HDL-c, LDL-c, fasting glucose, insulin, and HbA1c) were performed. Overweight/obesity and blood pressure were included in cardiometabolic outcomes. Poisson regression analyses were used to evaluate associations.
Results: The analysis was composed of 36,952 adolescents. The average energy consumption from UPF was 30.7% (95%CI: 29.7–31.6) per day. Adolescents with high UPF consumption (top tertile, ≥38.7% per day) ingest more sodium, saturated and trans-fat, as well as few proteins, fibers, polyunsaturated fats, vitamins, and minerals. After adjusting for possible confounders, higher UPF consumption was directly associated with high LDL-c (PR=1.012; 95%CI: 1.005–1.029), and inversely associated with low HDL-c (PR=0.972; 95%CI: 0.952–0.993). We did not find associations between UPF consumption and other cardiometabolic risk factors evaluated in this study.
Conclusion: UPF consumption among Brazilian adolescents is high and can be associated with poor diet quality and changes in LDL-c.
Machine learning-based prediction for land degradation mapping using multi-source geospatial data in the Batanghari watershed, Sumatra, Indonesia
Authors: Yulianto Fajar , Raharjo Puguh Dwi , Pramono Irfan Budi , Setiawan Muhammad Anggri , Chulafak Galdita Aruba , Nugroho Gatot , Sakti Anjar Dimara , Nugroho Sapto , Budhiman Syarif 
Published: November 2022

Abstract
The study area is a tropical environment located in the Batanghari watershed, Sumatra, Indonesia. The existence of the environmental problems and damages in the study area can be identified based on land degradation. It can be interpreted as a complex process and is influenced by human activities, climate change, and natural events. This study proposes the latest Geospatial Artificial Intelligence (Geo-AI) model using multi-sources geospatial data that is specifically used to address challenges and phenomena related to the identification of land degradation in the study area. The novelty of this study is that it is the first time to integrate the 6 (six) main variables of multi-source geospatial data - Topographical, Biophysical, Bioclimatic, Geo-environmental, Global human modification, and Accessibility - in predicting potential land degradation in the tropical environment, such as Indonesia. Machine learning-based prediction Support Vector Machine (SVM), Minimum Distance (MD), Classification and Regression Trees (CART), Gradient Tree Boost (GTB), Naïve Bayes (NB), Random Forest (RF) algorithms were used to predict and to map land degradation in the study area. The overall accuracy of the results of comparison and evaluation of machine learning-based predictions on the RF, CART, GTB, SVM, NB, and MD in the study area are 86.2%, 85.8%, 81.2%, 52.8%, 36.3%, and 34.5%, respectively. Therefore, the study concluded that the RF, CART, and GTB algorithms are proposed to be applied to produce land degradation map in the study area.
Neural-network solutions to stochastic reaction networks
Authors: Tang Ying , Weng Jiayu , Zhang Pan 
Published: November 2022

Abstract
The stochastic reaction network is widely used to model stochastic processes in physics, chemistry and biology. However, the size of the state space increases exponentially with the number of species, making it challenging to investigate the time evolution of the chemical master equation for the reaction network. Here, we propose a machine-learning approach using the variational autoregressive network to solve the chemical master equation. The approach is based on the reinforcement learning framework and does not require any data simulated in prior by another method. Different from simulating single trajectories, the proposed approach tracks the time evolution of the joint probability distribution in the state space of species counts, and supports direct sampling of configurations and computing their normalized joint probabilities. We apply the approach to various systems in physics and biology, and demonstrate that it accurately generates the probability distribution over time in the genetic toggle switch, the early life self-replicator, the epidemic model and the intracellular signaling cascade. The variational autoregressive network exhibits a plasticity in representing the multimodal distribution by feedback regulations, cooperates with the conservation law, enables time-dependent reaction rates, and is efficient for high-dimensional reaction networks with allowing a flexible upper count limit. The results suggest a general approach to investigate stochastic reaction networks based on modern machine learning.
Exploring the relationship between cartilage-associated m6a gene and osteoarthritis development based on bioinformatics and machine learning
Authors: Song Shilei , Chen Yueping , Chen Feng 
Published: November 2022

Abstract
Purpose:This study aimed to analyze the expression of n6-methyladenosine (m6a)-related genes in osteoarthritis (OA), the relationship between m6a signature genes and clinical morbidity, and the correlation between m6a gene immune cells by using bioinformatics and random forest tree methods.
Methods:OA-related microarrays were obtained from the GEO database. The m6a-related genes were extracted, and their differential gene expression was analyzed using R software. Appropriate gene screening methods were selected to obtain m6a disease signature genes; m6a clinical prediction models were established; decision curve analysis (DCA) was applied to verify the model’s accuracy. Typing was performed according to m6a expression, and genetic differences between typing and differences in immune infiltration were analyzed. The correlation between the differential genes and immune cells was also analyzed. Finally, the m6a differential genes were analyzed using Metascape.
Results:Random forest tree screening was used to obtain the following m6a disease signature genes for cartilage in OA: METTL3, CBLL1, YTHDC1, YTHDC2, YTHDF1, and FMR1. A strong correlation was found between the expression of disease-characterizing genes and clinical disease incidence, which was higher when the total score was between 200 and 230. Based on the m6a gene expression in cartilage, the samples were divided into groups A and B, and METTL3, FMR1, and YTHDC2 had significant genetic differences in the two groups. Among the immune cells, activated CD4T, activated dendritic, natural killer T, and plasma cells were significantly different in the two groups. A significant correlation was found between the high expression of immune cells and the three m6a genes in group B. Metascape functional pathway analysis revealed that OA is mainly related to cell development, differentiation, morphological changes, chemotaxis, and inflammatory response, mainly involving the FRA pathway.
Conclusion: The expression of m6a disease-characterizing genes is significantly correlated with the clinical incidence of OA, and the abnormal expression of m6a-related genes in OA cartilage is an important factor that may cause cartilage damage mainly by affecting immune cells, thus releasing relevant pro-inflammatory factors causing damage to chondrocytes.
How cold is the junction of a millikelvin scanning tunnelling microscope?
Authors: Esat Taner , Yang Xiaosheng , Mustafayev Farhad , Soltner Helmut , Tautz Frank , Temirov Ruslan 
Published: November 2022

Abstract
We employ a scanning tunnelling microscope (STM) cooled to millikelvin temperatures by an adiabatic demagnetization refrigerator (ADR) to perform scanning tunnelling spectroscopy (STS) on an atomically clean surface of Al(100) in a superconducting state using normal-metal and superconducting STM tips. Varying the ADR temperatures between 30 mK and 1.2 K, we show that the temperature of the STM junction T is decoupled from the temperature of the surrounding environment Tenv. Simulating the STS data with the P(E) theory, we determine that Tenv ≈ 1.5 K, while the fitting of the superconducting gap spectrum yields the lowest T=77 mK.
An Integrated Multicenter Amplicon Sequencing Data Reveals New Evidence of the Interaction Between the Gut Microbiota and Irritable Bowel Syndrome
Authors: Chen Han , Ou Rong , Tang Nana , Su Wei , Yang Ruoyun , Yu Xin , Zhang Guoxin , Jiao Jianhua , Zhou Xiaoying 
Published: November 2022

Abstract
Background
Gut dysbacteriosis has been reported as one of the etiologies for irritable bowel syndrome (IBS). However, the association between gut microbiota and IBS is still inconclusive. The study aims to provide new evidence of the interaction between the gut Microbiota and IBS.
Method
A paired-sample study was designed by retrieving original multicenter 16s-rRNA data of IBS patients and healthy controls from the GMrepo database. The propensity score matching (PSM) algorithm was applied to reduce confounding bias. The differential analysis of microbiota composition was performed at different taxonomic levels. The co-occurrence network was established. Subgroup analysis was performed to identify specific microbial compositions in different IBS subtypes.
Results
A total of 1522 amplicon samples were initially enrolled. After PSM, 708 samples (354 IBS and 354 healthy individuals) were eligible for further analysis. A total of 1,160 genera were identified. We identified significantly changed taxa in IBS groups (IBS-enriched: the families Enterobacteriaceae, Moraxellaceae, and Sphingobacteriaceae; the genera Streptococcus, Bacillus, Enterocloster, Sphingobacterium, Holdemania, and Acinetobacter. IBS-depleted: the phyla Firmicutes, Euryarchaeota, Cyanobacteria, Acidobacteria, and Lentisphaerae; the families Bifidobacteriaceae, Ruminococcaceae, Methanobacteriaceae, and the other 25 families; the genera Faecalibacterium, Bifidobacterium, and other 68 genera). In subgroup analysis, we profiled microbial compositions in IBS with predominant diarrhea and constipation. We further identified the genera Bilophila and Enterocloster that may be involved in linking IBS with psychiatric disorders. The co-occurrence network identified three hub genera and six hub species (including Faecalibacterium prausnitzii) that may be important in IBS pathophysiology. Strong positive interactions were identified among the Bifidobacterium longum, Bifidobacterium breve, and Bifidobacterium adolescentis in the Bifidobacterium community.
Conclusion
This study provides updated evidence in identifying specific microbes that may involve in IBS pathogenesis. Future modalities may be further validated by targeting these microorganisms.
Analytical Hierarchy Process and Economic Analysis for Optimal Renewable Sites in Bangladesh
Authors: Amin Ifte Khairul , Islam Md. Nahid , Jaman Azam , Hasan Md. Kabir , Parvez Shahadat Hussain , Shajid Md. Salim Shahed 
Published: November 2022

Abstract
Bangladesh has a huge potential for utilizing renewable energy with the
availability of sources for solar, wind, hydro, and biogas. This paper
provides a comprehensive analysis of the potential for renewable energy
sources and predicts optimal sites for renewable plant implementation
in Bangladesh. A country-wise mapping approach is followed by validation
of prediction using Multi-Criteria Decision Analysis (MCDA)
known as Analytical Hierarchy Process (AHP) which will aid in the
planning and execution of Bangladesh’s upcoming expansion of renewable
farms and will also be a useful tool for policymakers. Moreover,
an economic analysis for 50 MW solar and wind power plant has been
presented to estimate the Levelized Cost of Electricity (LCoE) of the
system and society. This work predicts the enormous potential for the
expansion of renewable energy by assessing the appropriate future sites,
economic viability, and cost estimation from Bangladesh’s perspective.