bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Method to Significantly Simplify the API Flow Tests for Gas-Lift Valves
Authors: Simoes Maciel Felipe , Waltrich Paulo 
Published: August 2022

Abstract
Accurate gas lift valve (GLV) performance is crucial for precise gas lift system design, but complex and time-consuming testing techniques are required to obtain valve performance correlations. Therefore, this paper presents a modeling approach that aims to reduce the testing effort and obtain the coefficients required for valve performance correlations. Specifically, the model replicates the flow capacity test (FCT) described in the API 11V2 (2001) and API 19G2 (2010) to determine the flow coefficient (Cv) and critical pressure ratio (Rcp) for gas lift valves (GLV). Technically, the FCT requires a modified GLV with an adjustable stem positioning system to obtain flow rate as a function of pressure drop and calculating Cv and Rcp for each stem travel. Among the drawbacks of the FCT are the valve modification itself and the large number of tests necessary. The proposed approach employs a 1D mechanistic model that considers equivalent diameters of the GLV orifice port and the check valve opening area to calculate the gas flow rate. The pressure drop across the restrictions is derived from Bernoulli's equation and used to calculate the flow rate, Cv and Rcp for several stem positions of the gas lift valve. Experimental data from a dynamic flow test (API 11V2) is used to calibrate the model. Simulation results of 12 different valves are compared to the Valve Performance Clearinghouse (VPC) database to validate the modeling approach. The VPC database was created based on GLV flow tests for valves from several manufacturers with different models and configurations. Results of flow capacity using the 1D mechanistic modeling show a consistent agreement with the VPC database. Overall, the error was always below 15% for both Cv and Rcp, which is a positive result considering that the current most accurate method shows errors of up to 25%. Even though the 1D modeling may be oversimplified given the consideration of 3D area changes as equivalent circular diameters, the method predicts Cv and Rcp with considerable accuracy. Moreover, the calibration using only one dynamic flow test result significantly reduces the time required to perform an FCT and eliminates the need to modify a GLV.
Tailoring Digital Approaches for Monitoring and Predictive Diagnosis for Sucker Rod Pumping Systems
Authors: Tran Ngoc Lam , Karami Hamidreza , Bello Opeyemi , Teodoriu Catalin 
Published: August 2022

Abstract
Sucker-rod pumps (SRP) are the most common form of artificial lift in depleted oil wells. Given vast datasets collected from years of operation, many operators are enacting digital technology to generate automated artificial lift systems. However, their online monitoring and optimization come with many challenges. Therefore, the individually engineered artificial lift is an imminent solution for long-term production, while maintaining cost efficiency. The key to make sucker-rod pumps operate effectively lies in downhole condition diagnostics. The emerging big-data analytics have provided relatively precise downhole condition forecasting based on available data, enabling better decision making. This study focuses on developing a testing digital SRP application, while leveraging analytical approaches to diagnose its operational anomalies.
This study presents an experimental and analytical workflow to monitor sucker-rod pumps and perform diagnostics using a designed Interactive Digital Sucker-Rod Pumping Unit (IDSRP). This unit consists of a vertical 50-ft long facility with a downhole rod pump at the bottom and proper instrumentation, capable of simulating a rod-pumped wellbore's operation. A linear actuator is used to provide the rod string's reciprocating movement and simulate different surface units and operating scenarios. The system utilizes the application of Pulse-width Modulation (PWM) technique and data-acquisition system (DAQ) to obtain analog results through signals detected by sensor. The surface dynamometer cards, and time-driven pressure and rate data are collected to train a cloud-based analytics software platform. The wave equation of Gibbs is used to draw the downhole pump card from the surface card. Some of the tested scenarios are normal pump operation with varying rates and varying levels of pumping off at the pump inlet.
The applied online prototype is designed to provide a step towards digitized automation systems. The setup is used to generate datasets for the rod-pump's operation at varying pump speeds, stroke lengths, and rod movement profiles. The collected data include the flowrate, bottomhole and surface pressures, and the dyno cards. The digitized transformation algorithms develop these physics-based inputs to generate predictive models, thus classifying operational conditions or failures of the pump. The model dynamically categorizes the pumps into key states of ideal condition and over-pumping with a regression fit accuracy of higher than 0.7 and overall classification accuracy of 92%.
The novelty of this setup consists not only of its mechatronic design but also allows thorough performance monitoring of the pump, thus easily validating models. The results have the potential of becoming a tool to optimize and shorten the downtime for repairing pump failures.
Wireless Sensor Technology to Monitor Rod Rotator Performance
Authors: Treiberg Terry , Furr Brandon 
Published: August 2022

Abstract
Mechanical rod rotators have been used as part of the beam lift artificial lift system since the concept was first patented in the 1930's. By rotating the rods, the frictional wear surface can be distributed around the circumference of the rod, versus on a single side of the rod. By distributing the wear surface, the rod life can be significantly extended. In the same way, the industry has used tubing rotators to derive this same benefit on the tubing, distributing the wear around the inner circumference of the tubing.
One of the biggest challenges associated with operating rotators is being able to confirm that proper rotation of the rods is taking place. The speed of rotation is very slow and is not easily observable without carefully watching the rods for several strokes, and often requires an observer to be very close to the rod string. Because of this challenge, the failure or malfunction of a rotator can go undetected for long periods of time, which often results in premature failure of the rod system, leading to excess cost and downtime.
This paper will explore some of the traditional methods that have been used to monitor rod rotators, including some of the advantages and disadvantages of these methods. It will also introduce a new wireless sensor that is capable of remotely reporting not only the proper operation of a rotator, but also the actual speed of rotation, which is very useful to understand the rotator's performance and to detect progressive failure. Field trial data was gathered as the algorithms were improved to eventually yield accurate monitoring capabilities. This data will be presented, along with several conclusions. This innovative sensor is adaptable to existing rotators and can be easily integrated into existing pump-off controllers, so it is agnostic with respect to the manufacturer of the equipment and will have broad application for rod pump wells in the industry.
Gut microbiota profiles in mental disorders and their association with behavior in children and adolescents.
Authors: Soltysova Marcela , Tomova Aleksandra , Ostatnikova Daniela 
Published: August 2022

Abstract
The aim of our work is to summarize the current state of knowledge on gut microbiota changes in children and adolescents with mental illnesses. To our knowledge, this is the first review comparing gut microbiota changes in various mental disorders in children and adolescents. To find the relevant articles, the PubMed, Web of Science and Google Scholar databases were searched. Articles in English presenting original data and comparing the composition of gut microbiota in child psychiatric patients with gut microbiota in healthy children and adolescents were selected. Finally, we identified 42 articles eligible for our purpose. The majority of patients with autism spectrum disorders (ASD) were investigated. A smaller number of studies evaluating the gut microbiota in children and adolescents with attention-deficit hyperactivity disorder (ADHD), Rett syndrome, anorexia nervosa, major depressive disorder and tic disorders were found. The main findings of this research are discussed in our review, focusing on the association between the gut microbiota and behavioural manifestations. To conclude, the gut microbiota in children and adolescents with mental disorders is evidently different from that in controls. Most pronounced changes are seen in children with autism spectrum disorders. These changes might be associated with often present gastrointestinal manifestations but, in general, also play a pathogenetic role in behavioural disorders. Based on research findings, we assume that there is a perspective of gut microbiota correction to improve clinical symptoms in psychiatry.
Differences in County-Level Cardiovascular Disease Mortality Rates due to Damage Caused by Hurricane Matthew and the Moderating Effects of Social Capital: A Natural Experiment
Authors: McCann Zachary H. , Szaflarski Magdalena 
Published: August 2022

Abstract
BackgroundAs the climate continues to warm hurricanes will continue to increase in both severity and frequency. Hurricane damage is associated with cardiovascular events, but social capital may moderate this relationship. We examined the association between county-level hurricane damage and cardiovascular mortality rates after Hurricane Matthew, and the moderating effect of several aspects of social capital on this relationship in post-disaster contexts. Social capital refers to the social relationships and structures that provide individuals with material, financial, and emotional resources throughout their lives. Previous research has found an association between high levels of social capital and lower rates of cardiovascular disease (CVD) mortality. In post-disaster settings, social capital may protect against CVD mortality by improving access to life saving resources. We hypothesized that higher (vs. lower) hurricane damage would be associated with higher CVD mortality and measures of social capital would be associated with decreased CVD mortality in counties affected by Hurricane Matthew.MethodsCounty-level social data (n = 183) were compiled from federal surveys before and after Hurricane Matthew to construct, per prior literature, a social capital index based on four dimensions (sub-indices): family unity, informal civil society, institutional confidence, and collective efficacy. CVD mortality rate was constructed from epidemiological data. Changes in CVD mortality based on level of hurricane damage were assessed using regression adjustment. We used cluster robust Poisson population average models to determine the moderating effect of social capital on CVD mortality rates in both high and low damage counties.ResultsWe found that low levels of hurricane damage are associated with increased CVD mortality rates. Among the different social capital dimensions, institutional confidence was associated with reduced initial CVD mortality in high- damage counties (p ≤ .001), but its association with CVD mortality trends was null. The overall effects of social capital and its sub-indices were largely nonsignificant. ConclusionLow levels of hurricane damage are associated with increased CVD mortality for 18 months after Hurricane Matthew. The role of social capital remains unclear. Future research should focus on improving measurement of social capital and quality of hurricane damage and CVD mortality data.
MTX-PEG modified CG/DMMA polymeric micelles for targeted delivery of doxorubicin to induce synergistic autophagic death against triple negative breast cancer
Authors: Cao Zhiwen , Liu Rui , Li Yang , Luo Xinyi , Hua Zhenglai , Wang Xiangpeng , Xue Zeyu , Zhang Zhengjia , Lu Cheng , Lu Aiping , Liu Yuanyan 
Published: August 2022

Abstract
The chemotherapy of triple negative breast cancer (TNBC) based on doxorubicin (DOX) regimens suffer from great challenges on toxicity and autophagy raised off-target. In this study, a conjugate methotrexate-polyethylene glycol (shorten as MTX-PEG) modified CG/DMMA polymeric micelles were prepared to endue DOX tumor selectivity and synergistic autophagic flux interference to reduce systematic toxicity and to improve anti-tumor capacity. The micelles could effectively promote the accumulation of autophagosomes in tumor cells and interfere with the degradation process of autophagic flux, collectively inducing autophagic death of tumor cells. In vivo and in vitro experiments showed that the micelles could exert improved anti-tumor effect and specificity, as well as reduced accumulation and damage of chemotherapeutic drugs in normal organs. The potential mechanism of synergistic autophagic death exerted by the synthesized micelles in MDA-MB-231 cells have been performed by autophagic flux-related pathway.
Automatic Comprehensive Aspects Reports in Clinical Acute Stroke MRIs
Authors: Faria Andreia , Liu Chin-Fu , Li Alice , Kim Ganghyun , Miller Michael , Hillis Argye 
Published: August 2022

Abstract
The Alberta Stroke Program Early CT Score (ASPECTS) is a simple visual system to assess the extent and location of ischemic stroke core. The capability of ASPECTS for selecting patients’ treatment, however, is affected by the variability in human evaluation. In this study, we developed a fully automatic system to calculate ASPECTS comparable with consensus expert readings. Our system was trained in 400 clinical diffusion weighted images (DWIs) of patients with acute infarcts and evaluated with an external testing set of 100 cases. The models are interpretable, and the results are comprehensive, evidencing the features that lead to the classification. This system adds to our automated pipeline for acute stroke detection, segmentation, and quantification in MRIs (ADS), which outputs digital infarct masks and the proportion of diverse brain regions injured, in addition to the predicted ASPECTS, the prediction probability and the explanatory features. ADS is public, free, accessible to non-experts, has very few computational requirements, and run in real time in local CPUs with a single command line, fulfilling the conditions to perform large-scale, reproducible clinical and translational research
Non-Vitamin K Antagonist Anticoagulants versus Warfarin in newly diagnosed Atrial Fibrillation and CKD: the Korean National Health Insurance Data
Authors: Kee Youn Kyung , Jeon Hee Jung , Oh Jieun , Yoo Tae-Hyn , Kang Dongwoo , lee Jungkuk , Shin Dong Ho 
Published: August 2022

Abstract
Background
Despite the benefits of non-vitamin K antagonist oral anticoagulants (NOACs), whether NOAC therapy has a better risk-benefit profile than warfarin therapy in patients with non-valvular atrial fibrillation (AF) and chronic kidney disease (CKD), including end-stage renal disease (ESRD), remains uncertain. We investigated the efficacy and safety of NOACs compared to warfarin in these patients using a nationwide database.
Methods
We evaluated patients with incident non-valvular AF and CKD in the Korea National Health Insurance Database from 2013 to 2018. The primary and secondary efficacy outcomes were ischemic stroke and all-cause mortality, respectively. The primary safety outcomes included intracranial hemorrhage, gastrointestinal bleeding, and extracranial or unclassified major bleeding.
Results
Among the 1,885 patients, 970 (51.5%) initiated warfarin therapy, whereas 915 (48.5%) initiated NOAC therapy. Although NOAC users had a lower proportion of patients with ESRD than warfarin users (6.6% vs. 32.5%, p < 0.001), NOAC users had a higher Charlson comorbidity index, CHA2DS2-VASC score, and modified HAS-BLED score compared with warfarin users. During a mean follow-up period of 23.8 months, there were 293 and 214 cases of ischemic stroke and all-cause death, respectively. There was no difference in ischemic stroke between the two groups. However, Kaplan-Meier survival analysis showed that all-cause mortality was significantly lower in NOAC users than in warfarin users. In multivariate Cox regression analyses, the hazard ratio for all-cause mortality compared to warfarin therapy was 0.41 (95% CI, 0.30–0.56; p < 0.001) in NOAC therapy. Additionally, NOAC therapy significantly reduced intracranial hemorrhage and gastrointestinal bleeding in multivariate Cox regression analyses.
Conclusions
This study showed that NOAC therapy had a better risk-benefit profile than warfarin therapy in patients with AF and CKD. To clarify the benefits of NOACs in patients with AF and CKD, further well-designed clinical trials are needed.
Carbon neutrality does not equal climate neutrality in saltmarsh restoration
Authors: Nightingale Joseph , McMahon Lucy , Steinke Michael , McGenity Terry J. , Gehrels W. , Dumbrell Alex , Schäfer Hendrik , Redeker Kelly 
Published: August 2022

Abstract
Saltmarsh restoration efforts often highlight high carbon burial rates as a climate mitigation opportunity. We created a 200-year managed-realignment model incorporating carbon burial, albedo change, and emissions of climate-active compounds across three successive realignment stages: mudflat, realigned saltmarsh, and mature saltmarsh. Total climatic outcomes from all forcing agents differ substantially from those derived solely from carbon burial across latitude and over time. Latitude explains a significant proportion of variation in emissions for methane, methyl bromide, and methyl chloride in mature saltmarshes and carbon burial in mature and realigned saltmarshes. The climate mitigation effects of managed realignments were significantly reduced at subtropical latitudes, and aerosol and albedo impacts had greater influence on total radiative forcing relative to carbon burial. Future land-use mitigation strategies should therefore use spatiotemporally explicit accounting of climate-impacting processes and not rely solely on carbon budgets to underpin climate mitigation strategies.
Improving Remote Material Classification Ability with Thermal Imagery
Authors: Großmann Willi , Horn Helena , Niggemann Oliver 
Published: August 2022

Abstract
Material recognition using optical sensors is a key enabler technology in the field of automation. Nowadays, in the age of deeplearning, the challenge shifted from (manual) feature engineering to collecting big data. State of the art recognition approachesare based on deep neural networks employing huge databases.
But still, it is difficult to transfer these latest recognition results into the wild – various lighting conditions, a changing imagequality, or different and new material classes are challenging complications. Evaluating a larger electromagnetic spectrum isone way to master these challenges.
In this study, the infrared (IR) emissivity as a material specific property is investigated regarding its suitability for increasing thematerial classification reliability. Predictions of a deep learning model are combined with engineered features from IR data.This approach increases the overall accuracy and helps to differentiate between materials that visually appear similar. Thesolution is verified using real data from the field of automatized disinfection processes.
Hydrogen peroxide-induced oxidative stress impairs the calcification ability of human dental pulp cells
Authors: Shirawachi Satomi , Takeda Katsuhiro , Naruse Tomoya , Takahasi Yohei , Nakanishi Jun , Shindo Satoru , Shiba Hideki 
Published: August 2022

Abstract
The present study was conducted to investigate the effect of hydrogen peroxide (H2O2) as an inducer of oxidative stress on the calcification ability of human dental pulp cells (hDPCs) and the involvement of inositol 1, 4, 5-trisphosphate (IP3). hDPCs were exposed to H2O2. Cell viability and reactive oxygen species (ROS) production were then evaluated. To investigate the effect of H2O2 on the calcification ability of hDPCs, real-time PCR for alkaline phosphatase (ALP) mRNA expression, ALP staining, and Alizarin red staining were performed. Data were compared with those of hDPCs pretreated with 2-aminoethyldiphenylborate (2-APB), which is an IP3 receptor inhibitor. H2O2 at concentrations above 250 µM significantly reduced cell viability. More ROS production occurred in 100 µM H2O2-treated hDPCs than in control cells. H2O2-treated hDPCs showed significant reductions in ALP mRNA expression, ALP activity, and mineralized nodule deposition compared with negative control cells. 2-APB significantly inhibited these reductions. To the best of our knowledge, this is the first study documenting the involvement of IP3 signaling in the calcification ability of human dental pulp cells impaired by H2O2. The results of the present study add molecular insight into internal root resorption and may provide a clue to the development of new therapeutic agents in endodontic therapy.
Transformative effects of COVID-19 pandemic in Health Professions Education: Experience of utilizing e-Learning from Medical Universities in Tanzania
Authors: Mugusi Sabina , Mbwambo Orgeness Jasper , Mmbaga Blandina Theophil , William Erick , Mloka Doreen , Amon Yohana , Ibrahim Glory , Kisenge Rodrick , Balandya Emmanuel , Peter Thandiwe Yvonne , Sirili Nathanael , Macfarlen Sarah , Mteta Kien , Kwesigabo Gideon 
Published: August 2022

Abstract
Introduction: The emergence of coronavirus disease 2019 (COVID-19) pandemic has caused a shift in education training both in high, middle and low-income countries with an increased need of adapting the e-Learning system to encounter the lockdown situation and social distancing. This article provides an overview of the effects of COVID-19 pandemic on e-Learning and mitigations done among three medical universities in Tanzania that implements the Transforming Health Professional Education in Tanzania (THET) project. Methods: The study was conducted at Muhimbili University of Health and Allied Sciences (MUHAS), Kilimanjaro Christian Medical University College (KCMUCo), and the Catholic University of Health and Allied Sciences (CUHAS). Information on e-Learning use before and after the university closure and social distancing observation period, and the measures taken to enhance e-Learning was retrieved from Information Communication and Technology Departments (ICT) in each respective university. The e-Learning usability and the number of courses that adopted e-Learning was tracked and compared within the universities before, during and after the pandemic. The challenges encountered were noted as well as lessons learned from the process. Results: The institution's efforts and desire to continue with training led to accelerated utilization of e-Learning and digital platforms in medical education in Tanzania. In each institution, the effort led to more courses adopting e-Learning and online training. Scaling up of e-Learning was done in parallel with increased training to faculty members as well as students accessing the online system in both universities. Challenges such as poor internet connection, knowledge of both students and academic staff on proper utilization of e-Learning as well as access to devices outside the university environment even for those who used e-Learning prior to the closure were noted. Conclusion: The implementation and use of e-Learning is possible in medical universities in Tanzania. It is high time for all medical universities to increase investment on e-Learning as one of the elements of the adopted competency-based curriculum and emergency preparedness for training institutions during pandemics which may necessitate closure of institutions. The efficacy of e-Learning on the quality of medical education to produce desired outcomes and exploring barriers for e-Learning implementation calls for further research.