bluuebunny/crossref_metadata_2025_split huggingface dataset:
Radiographic Outcomes of Robot-Assisted Versus Conventional Total Knee Arthroplasty
Authors: Riantho Albert , Butarbutar John Christian Parsaoran , Fidiasrianto Kevin , Elson Elson , Irvan Irvan , Haryono Handy , Prasetio Jeremy Nathan 
Published: May 2023

Background:
Total knee arthroplasty (TKA) has long been considered the definitive treatment for knee osteoarthritis. Although tremendous improvements have been made in surgical techniques for conventional TKA, a substantial dissatisfaction rate among patients has persisted because of moderate-to-severe pain and stiffness following TKA. Robot-assisted TKA was developed as an alternative to conventional TKA with the goal of improving operative precision and producing better clinical outcomes with minimal postoperative complications. The aim of this study was to compare the radiographic outcomes, duration of surgery, and complication rate between robot-assisted TKA and conventional TKA.

Methods:
We conducted relevant literature searches of Medline, Scopus, ClinicalTrials.gov, and the Cochrane Library databases with use of specific keywords. The outcomes for continuous variables were pooled into mean differences, whereas the outcomes for dichotomous variables were pooled into odds ratios with 95% confidence intervals with use of random-effects models.

Results:
A total of 12 randomized clinical trials were included. Our pooled analysis revealed that robot-assisted TKA was associated with fewer outliers in the hip-knee-ankle (HKA) angle (p < 0.0001), femoral component (coronal) angle (p = 0.0006), femoral component (sagittal) angle (p = 0.009), tibial component (coronal) angle (p = 0.05), and tibial component (sagittal) angle (p = 0.01) when compared with conventional TKA. The postoperative HKA angle was also significantly more neutral in the robot-assisted TKA group (mean difference, −0.77°; p < 0.0001). However, the complication rate did not differ significantly between the 2 groups.

Conclusions:
Robot-assisted TKA may produce more accurate placement of the prosthetic component and better joint alignment accuracy than conventional TKA as shown by fewer outliers in several joint angles.

Level of Evidence:
Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
Prediction of Surface Wellhead Deformation Via Calculation of Tubular Growth Due to Thermal Effects
Authors: Proano Manuel Alejandro , Meneses Alba Rolanda , Tates Victor Andres , Aponte Jesus , Magalhaes Tasso , Duque Gerardo Javier 
Published: May 2023

Abstract
After implementing a water injection project with high temperature (up to 235°F @ surface) sourced water in existing wells, 63% of the conventional Wellhead associated with waterflooding installed showed growth/inclination at the surface. A detailed analysis of twenty-seven wells in the Orient Basin of Ecuador was performed, where onsite measurements and engineering calculations of the loads and elongations of the production casing and tubing strings were caused by thermal effects.
A specialized tubular modeling software was used to simulate the water producer wells and injector well thermal profiles, casing elongation, and buckling. The produced water has temperatures superior to 200°F and is transferred directly to the injector wells without any allowed time to cool down. The analysis focused mainly on the 9-5/8″ production casing since it is not cemented to the surface and has almost 6,000ft of free pipe able to elongate due to high-temperature injected water. As the other casing strings were cemented to the surface, it was assumed that they were adequately anchored, and no elongation would occur.
All the wells were inspected before entering service, and no wellhead deformation was observed. Once operations started, the surface temperatures reached up to 235°F on the water producers and injectors. After six months, the production operators noticed the first signs of wellhead movement, with consequent inclination. A survey was carried out in 27 wells, where the wellhead deformations were measured by taking the projection in 3 planes (X, Y, and Z). Out of 27 wells surveyed, two water producers presented an inclination above 2° and one injector well above 1.5°, which was deemed excessive. It was possible to establish a good correlation between the specialized tubular modeling software results and the deformations measured at the surface, enabling the development of guidelines to define if high-temperature wellheads with expansion capabilities would be required.
It also evaluated the possibility of using insulated packer fluids to minimize heat transfer and production casing elongation. The simulation estimated an average elongation reduction of 28% and 41% when water-based and oil-based packer fluids are used, respectively.
This work created a workflow to identify wells with a high risk of suffering wellhead deformation caused by high surface temperature. Combining the simulation results with the field measurements made it possible to determine when deformation at the surface was expected and high-temperature wellheads with expansion capabilities were needed. It also evaluated the effectiveness of insulated packer fluids in reducing the casing elongation and avoiding the installation of such wellheads.
The Impacts of Gas Adsorption on the Productivity of Marcellus Shale Horizontal Well
Authors: Bulule Valcia , Sattari Arya , Aminian Kashy , El Sgher Mohamed , Samuel Ameri 
Published: May 2023

Abstract
The shale formations, in addition to the gas present in the pores of the rock, contain gas in the adsorbed state in the organic matter within the rock. As the pressure depletes in the reservoir the adsorbed gas is released and augments the gas production. In addition, gas desorption can potentially lead to permeability enhancement due to shale matrix shrinkage. At the same time, the pressure depletion increases the effective stress causing shale permeability and hydraulic fracture conductivity impairments. The purpose of this study was to investigate the impact of the gas desorption on the productivity of Marcellus shale horizontal well with multiple hydraulic fracture stages. The impacts of hydraulic fracture properties including half-length, conductivity, and stage spacing on gas desorption were also investigated.
To investigate the impact of the gas desorption on gas production from Marcellus shale, a reservoir model for a horizontal well completed with multiple hydraulic fracture stages was used. The model has been developed based on the available information from several existing Marcellus shale horizontal wells in West Virginia. The laboratory and published data relative to adsorbed gas and the geomechanical factors were analyzed and geomechanical multipliers were generated and incorporated in the model. The geomechanical multipliers account for the impairments in hydraulic fracture conductivity and the reduction in the formation (matrix and fissure) permeability as well as the shale shrinkage caused by the reservoir depletion. The model was then utilized to investigate the impact of different parameters including Langmuir pressure and volume, fracture half-lengths, fracture spacings, and fracture conductivity on gas desorption and gas production. The inclusion of geomechanical multipliers provided more realistic production predictions and better understanding of the desorbed gas impact. The gas desorption was found to have a significant impact on the productivity during later stages of the production. This is contributed to pressure depletion required for desorption to become significant. The contribution of the desorbed gas to production increases as the fracture half-length increases and the fracture spacing decreases. Therefore, it can be concluded that desorption of gas depends on the stimulated reservoir volume.
Systematic Evaluation of Alternative Acid System for High-Temperature Carbonate Formation
Authors: Gajipara Riten Prafulbhai , Hill A. D. , Zhu Ding , AlNajjar Najim , Chkolny Nikita , Weissenberger Markus 
Published: May 2023

Abstract
Alternative acid systems for carbonate acidizing have been developed to overcome some weaknesses of conventionally used hydrochloric acid. Such systems are of particular interest for the reservoirs with high temperature because of high reactivity and corrosiveness of HCl at temperatures above 200°F. The main advantages of the evaluated alternative acid include better wormhole efficiency at lower injection rates and less corrosiveness to protect tubulars and surface equipment. In a high-temperature environment, the performance of alternative acids needs to be evaluated for the feasibility of being an effective stimulation fluid. Even though there are plenty of core flood data in the literature for carbonate rocks, there are fewer studies/publications that provide acid performance at high temperatures. In this paper, we present an experimental study of an alternative acid over a wide range of temperatures up to 300°F. The goal is to confirm the applicability and identify the optimal conditions for field operations. We conducted core flood tests using the alternative acid to generate wormhole efficiency curves with different interstitial velocities. The optimal condition was determined from the experimental results for each temperature tested. The temperature for testing ranged from 125°F to 300°F. The tested acid system created a preferred wormhole structure with a dominant wormhole for all test conditions. This indicates that the alternative acid system can be used as a matrix acidizing fluid for carbonate reservoirs over a broad range of temperatures up to 300°F. As observed by HCl core flood tests, wormhole efficiency for the alternative acid also decreases with increasing temperature when compared with its performance at low temperature, but it showed reasonable results of wormholing, while HCl experiments was not practical at 300°F. The challenge of stimulating high-temperature formations can be addressed when the acid system and injection condition are designed correctly. The data presented in this paper add new information for high-temperature acid core flood testing, and provide useful information for matrix acidizing design using alternative acid systems.
Ensemble Machine Learning for Data-Driven Predictive Analytics of Drilling Rate of Penetration (ROP) Modeling: A Case Study in a Southern Iraqi Oil Field
Authors: Al-Sahlanee Dhuha T. , Allawi Raed H. , Al-Mudhafar Watheq J. , Yao Changqing 
Published: May 2023

Abstract
Modeling the drill bit Rate of Penetration (ROP) is crucial for optimizing drilling operations as maximum ROP causes fast drilling, reflecting efficient rig performance and productivity. In this paper, four Ensemble machine learning (ML) algorithms were adopted to reconstruct ROP predictive models: Random Forest (RF), Gradient Boosting (GB), Extreme Gradient Boost (XGB), and Adaptive Boosting (AdaBoost). The research was implemented on well data for the entire stratigraphy column in a giant Southern Iraqi oil field. The drilling operations in the oil field pass through 19 formations (including 4 oil-bearing reservoirs) from Dibdibba to Zubair in a total depth of approximately 3200 m. From the stratigraphic column, various lithology types exist, such as carbonate and clastic with distinct thicknesses that range from (40-440) m. The ROP predictive models were built given 14 operating parameters: Total Vertical Depth (TVD), Weight on Bit (WOB), Rotation per Minute (RPM), Torque, Total RPM, flow rate, Standpipe Pressure (SPP), effective density, bit size, D exponent, Gamma Ray (GR), density, neutron, and caliper, and the discrete lithology distribution. For ROP modeling and validation, a dataset that combines information from three development wells was collected, randomly subsampled, and then subdivided into 85% for training and 15% for validation and testing. The root means square prediction error (RMSE) and coefficient of correlation (R-sq) were used as statistical mismatch quantification tools between the measured and predicted ROP given the test subset. Except for Adaboost, all the other three ML approaches have given acceptable accurate ROP predictions with good matching between the ROP to the measured and predicted for the testing subset in addition to the prediction for each well across the entire depth. This integrated modeling workflow with cross-validation of combining three wells together has resulted in more accurate prediction than using one well as a reference for prediction. In the ROP optimization, determining the optimal set of the 14 operational parameters leads to the fastest penetration rate and most economic drilling. The presented workflow is not only predicting the proper penetration rate but also optimizing the drilling parameters and reducing the drilling cost of future wells. Additionally, the resulting ROP ML-predictive models can be implemented for the prediction of the drilling rate of penetration in other areas of this oil field and also other nearby fields of the similar stratigraphic columns.
Towards Improved Risk Assessment and Accident Investigation
Authors: Duhon Howard , Ariamuthu Venkidasalapathy Joshiba , Kalantri Pranav 
Published: May 2023

Abstract
Risk assessments are an important part of HAZOPs, root cause analysis studies, and other process safety evaluations. But process risk assessments, as typically performed, suffer from several identifiable and fixable flaws. These include: The assumption that accidents have a root cause, such as a component failure or human error,Ambiguous risk matrices that yield questionable and non-repeatable results,Flawed concepts of how people in the ‘line of fire’ make decisions.
Failure to identify/acknowledge common failure modes when they exist at a hierarchical level above the component level.
This paper addresses all these flaws and suggests solutions. The solutions are based on several schools of thought, including: Nancy Leveson's System Theoretic Accident Model and Processes (STAMP)Gary Klein's work on Naturalistic Decision Making (NDM)James Reasons’ work on human error,Level of Protection Analysis (LOPA) and Safety Integrity Level (SIL)Complexity science and Hierarchy Theory
Three cases studies are used to illustrate the implications of these flaws in practice and the power of improved approaches. Evaluation of a root cause analysis (conducted by others) of a fatal accident involving loss of containment of sour water.Comparison of the use of a typical color-coded risk matrix vs. LOPA-based risk matrix for process risk assessment.A risk assessment study used to determine which valves on a sour gas platform should be locked open or locked closed.
Operational Theory and Qualification of a Unique Autonomous Inflow Control Device for First Use in a Heavy Oil Layered Reservoir
Authors: Yao Xiutian , Xu Lei , Wang Chao , Simonds Floyd , Ding Bing , Zhao Liang 
Published: May 2023

Abstract
As Operators face challenges due to increased water production worldwide the application of Passive and Autonomous Inflow Control Devices has proven effective at both delaying water production onset (passive functionality) and reducing water production at the surface (autonomous functionality). Passive technology has been deployed very effectively in hundreds of wells while autonomous devices are showing great promise to reduce costs, environmental risk, and potentially a significant reduction in topside infrastructure.
Passive devices only delay the onset of unwanted fluid breakthrough. Once breakthrough occurs, these tools do not restrict production. This led to the development of AICD technology which provides passive functionality initially but restricts water production at breakthrough. This functionality is greatly enhanced when compartments are created downhole to enable a "network" of devices to function independently at breakthrough, allowing other compartments to produce oil relatively unrestricted. The design proposed in this paper uses no moving parts, significantly restricts water production in a wide range of crude viscosities, is easily configured for a variety of downhole conditions, and delivers passive ICD performance with AICD benefits using a simple, reliable, and unique design.
The tool functions to restrict water production progressively as either oil viscosity or water cut increase without ever completely or nearly completely closing to production, which makes it an excellent solution for marginal production wells, younger reservoirs, and wells with lower overall production rates compared to other technologies.
The paper will discuss the theory of the device's functionality to differentiate between fluids present. Laboratory test results will be shown to demonstrate flow performance as well as API 19ICD[1] testing for erosion, plugging resistance, and mud flow initiation testing. The completion modeling process will be discussed in detail for an upcoming completion in Sinopec's Shengli Field.
Managing the terror of publication bias: A comprehensive p-curve analysis of the Terror Management Theory literature
Authors: Chen Lihan , Benjamin Rachele , Guo Yingchi , Lai Addison , Heine Steven J. 
Published: May 2023

Abstract
We assessed the evidential value of the large literature (k=826 studies) investigating the mortality salience (MS) hypothesis from terror management theory. We employed a multitool assessment approach and reviewed past efforts to replicate experiments testing the MS hypothesis, and conducted a p-curve, a z-curve, and a random effects meta-analysis including bias corrections of the selection model, PET-PEESE, and WAAP-WLS on the studies. Overall, the different meta-analytic tools pointed to conflicting conclusions, reflecting differences in the methodology and philosophy of these tools. Our synthesis of these findings suggests there are true effects underlying some studies of the MS hypothesis, although the effects are highly heterogeneous, and the majority of studies are underpowered. We recommend future replications to assume a smaller effect size (r = .10 ~ .15) and to follow expert guidance in the experimental protocol. Given the conflicting findings that emerged, we suggest that future attempts to evaluate other literatures would benefit from a multitool assessment approach.
Transposons are important contributors to gene expression variability under selection in rice populations
Authors: Castanera Raul , Morales-Díaz Noemia , Gupta Sonal , Purugganan Michael , Casacuberta Josep 
Published: May 2023

Abstract
Transposable elements are an important source of genome variability. Here, we analyze their contribution to gene expression variability in rice by performing a TE insertion polymorphism (TIP)-eQTL mapping using expression data from 208 varieties from the O. sativa ssp. indica and O. sativa ssp. japonica subspecies. Our data shows that TE insertions are associated with changes of expression of many genes known to be targets of rice domestication and breeding. An important fraction of these insertions were already present in the rice wild ancestors, and have been differentially selected in indica and japonica rice populations. Taken together, our results show that small changes of expression in signal transduction genes induced by TE insertions accompany the domestication and adaptation of rice populations.
Application of Multi-Objective Optimization and Graph Theory Algorithms to Achieve Efficient and Adaptable Partitioning of District Metered Areas in Water Distribution Networks
Authors: Shekofteh Mohammad Reza , Yousefi-Khoshqalb Ehsan , Piratla Kalyan 
Published: May 2023

Abstract
The management of network infrastructure in the context of water sector sustainability poses a significant challenge due to the increasing demand for fresh water, rapid infrastructure deterioration, and rising global water shortages. This paper presents a practical method to address these challenges by partitioning water distribution networks (WDNs) into district metered areas (DMAs) during critical hydraulic conditions to ensure adequate water supply, appropriate pressure and flow rates, and improved customer satisfaction. The proposed method employs efficient graph theoretic algorithms and a multi-objective optimization approach to reduce computational effort and determine the optimal dynamic layout of DMAs based on flow meters and gate valves, while minimizing variable installation costs and regulating water loss monitoring and management. The method ensures that only the number of flowmeters and gate valves may require modification, rather than the DMA layout, as hydraulic criteria may frequently change for a network due to various reasons. The effectiveness of the proposed method is demonstrated through successful implementation on six complex WDNs consisting of hundreds of pipes and nodes.
Diverse Amdoparvoviruses Infecting Farmed Asian Badgers (Meles meles)
Authors: Wu Yanhong , Zhao Yongqiang , Zhang Xiuting , Wei Tao , Peng Qianwen , Wang Jianke , Liu Zongyue , Zhu Yanzhu , Shao Xiqun 
Published: May 2023

Abstract
Amdoparvoviruses infect various carnivores, including mustelids, canids and felids et al. Aleutian mink disease virus (AMDV), Carnivore amdoparvovirus 1, infects mink and other Mustelidae and causes subclinical diseases or fatal chronic immune stimulation and immune complex diseases. Here, we identified a nearly complete genome (4265nt) of a novel amdoparvovirus from farmed Asian badgers (Meles meles) and tentatively named Meles meles amdoparvovirus (MMAV). Furthermore, we constructed phylogenetic trees based on the NS1 and VP2 proteins, respectively, as well as the amdoparvoviral VP2 nucleotide hypervariable region. MMAV NS1 protein shared 62.6%-88.8% sequence identities with other known amdoparvoviruses and phylogenetically clustered into a unique clade, while VP2 protein shared 76.7%-97.2% identities and clustered into two clades, of which one was more closely related to raccoon dog and arctic fox amdoparvovirus (RFAV), and the other clade is independent of other known amdoparvoviruses. According to the NS1 genetic distance-based criteria, MMAV is classified as a novel species of Amdoparvovirus. the positive rate for amdoparvovirus by PCR was 32.8% (47/143) in 143 clinical samples collected from 134 individual badgers. MMAV DNA was detected in feces, blood, spleen, liver, lung, and adipose tissue from Asian badgers. Eight isolates were sequenced from eight samples, with five obtaining approximate complete genomes. Six serum samples were PCR,CIEP and IAT-positive, with four having high serum antibody titers (＞512) against AMDV-G. Twenty-six of the 41 amdoparvovirus-positive badgers exhibited diseased symptoms, and some necropsy revealed organic lesions. Therefore, these lines of evidence suggested that we discovered novel and diverse amdoparvoviruses, MMAVs, that naturally infect Asian badgers of mustelid and may be cause Aleutian disease in badgers similar to that seen in mink. Furthermore, our findings supported that mustelid species are susceptible to diverse amdoparvoviruses and the molecular characteristics of amdoparvorviruses divergence between hosts species.