bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving Teachers' Ability to Design Physical Education Learning Scenarios
Authors: Syaranamual Jusak , Syaranamual Mariana Ditboya 
Published: November 2024

This study aimed to: 1) Produce a draft lesson plan (RPP) in accordance with physical education learning. 2) Produce the design of physical education learning scenarios. The population in this study was elementary school Physical Education teachers in Ambon City, Central Maluku, and Tual City. The sample was determined by 1 Physical Education teacher from each district so that there were 4 teachers; 1 teacher from SD Negeri 65 Ambon, 1 teacher from SD Negeri 7 Masohi, 1 teacher from SD Negeri Sohoku, and 1 teacher from SD N Kolser Tual City. The area sampling technique was chosen based on the best representatives from each region. Data were collected using observation and documentation techniques. The assessment instrument for the preparation of Physical Education learning scenarios used the teacher professional education (PPG) assessment rubric. Data analysis used descriptive qualitative data analysis techniques. The results of preliminary data analysis show that the first, second, third, and fourth respondents all have very poor abilities. This can be seen from the results of the assessment score obtained amounting to 125 out of a total score of 280, or it can be said that the ability was 45%. Meanwhile, the fourth respondent hads an ability of 40%. Thus, based on the assessment scores of the elements of the learning model indicator, it was known that there is no teacher's ability to plan a learning model that can be used to teach the subject matter based on the demands of the 2013 curriculum. This can be seen from the acquisition of the average assessment score at the achievement of number 1. This is because the scenario does not include what learning model is suitable for teaching the selected subject matter.
Keywords: teacher ability, scenario design, physical education learning
Characteristics and Management of Neck and Trochanteric Femur Fractures at a Tertiary Hospital in Indonesia: A Retrospective, Single-Center Study
Authors: Pulungan Ndilalah , Thoriq Yusa Muhammad , Hartono Felix Giovanni , Adnan Muhammad Luthfi , Sasetyo Dadang Rona 
Published: November 2024

Background: Although hip fractures are common among the elderly population, there are still limited studies on neck-trochanteric fractures, one of the less common types of hip fractures. This study aims to describe the characteristics of patients and their management in patients with neck trochanteric fractures.
Methods: This retrospective cross-sectional study analyzed medical records of patients aged >18 years with trochanteric fractures from a tertiary hospital in Central Java, Indonesia, between January and December 2021. Fracture types were identified and classified using the Garden, Pauwels, and AO/OTA classifications. Demographic data, risk factors, fracture locations, and treatment types were also collected. Statistical analysis was performed using SPSS 21.0 to describe patient characteristics.
Results: The total sample was 77 patients, most were female (n = 55 (71.4%)) and aged > 60 years. More than a third of diagnosed fractures were neck of the femur fractures in 33 patients (42.9%). Among the most common classification types of fractures were Garden Type 3, Pauwels Type 3, and AO/OTA type A1.1. A total of 33 patients (42.9%) underwent open reduction of the fracture with internal fixation.
Conclusions: Our findings show that the prevalence of neck-trochanteric fractures mostly occurs in patients > 60 years of age and in females. Although open reduction with internal fixation is generally performed, there are several cases of fractures that are not classifiable due to limited imaging examinations. Further research on a wider population is needed to confirm the findings of this study.
Plastid genomics of wild grapevines (<i>Vitis vinifera</i> subsp. <i>sylvestris</i>) of Georgia the cradle of viticulture
Authors: Pipia Ia , Ujmajuridze Levan , Mamasakhlisashvili Londa , Hernández Álvaro , Tabidze Vazha 
Published: November 2024

The species Vitis vinifera (common grape) is dividing into two sub-species: Vitis vinifera subsp. vinifera (cultivated grapevines) and Vitis vinifera subsp. sylvestris (wild grapevines). Vitis vinifera subsp. vinifera is widely utilised for table fruits and serves as the primary source for the production of grape-related beverages, including wine and vinegar. Wild grapevines (Vitis vinifera subsp. sylvestris) are of great interest as they are considered the progenitors of cultivated varieties and are key to understanding the grapevine domestication process in general. To unlock the molecular mechanisms of grapevine domestication, genome-based studies are widely carried out. In this study, the complete chloroplast genome of two Georgian wild grapevine samples is subject to Illumina sequencing and in silico genome assembly, followed by gene annotation. According to the results, each analysed chloroplast genome is 160.928 bp in length, comprises a total of 128 genes (83 protein coding, 37 tRNA, 8 rRNA) and belongs to the genetically unique ‘Rkatsiteli’ haplotype (AAA). A comparative genomic study reveals the presence of certain InDels and SNPs in the chloroplast genomes.
Changes in total soluble solids concentration, fruit acidity, and yeast assimilable nitrogen in response to altered leaf area to fruit weight ratio in Pinot noir
Authors: Assefa Mewael Kiros , Creasy Glen L. , Hofmann Rainer W. , Parker Amber K. 
Published: November 2024

The increasing consumer demand for lower alcohol wine and the need to mitigate against a warming climate presents new challenges for winegrowers and the desire to produce grapes with lower total soluble solids (sugar) or earlier harvesting, while preserving other wine compounds and attributes, particularly for varieties intended for red wine production. We investigated how reducing vine leaf area through shoot trimming and leaf removal, applied at different severities and timings to modify the leaf area to fruit weight (LA) ratio, affects fruit composition for producing lower alcohol quality Pinot noir wine. Shoot trimming treatments (half canopy, H in 2015/16 and 2016/17, and quarter canopy, Q in 2016/17 by alternately removing leaves after trimming shoots to half) were applied shortly before veraison (V-, E-L 34), during veraison (V, E-L 35) and post-veraison (V+, E-L 36) in three different vineyard locations (Marlborough, Canterbury and Central Otago, New Zealand). Untrimmed vines served as the control. Lateral shoots were removed during treatment application, and regrowth was removed to maintain a consistent leaf area. Results showed that reducing the LA:FW ratio delayed the accumulation and concentration of total soluble solids (reduction of 1.0 to 2.7 °Brix) at harvest in all trimmed vines over both seasons. Berry weight, malic acid concentration, titratable acidity, and pH at harvest were unaffected by trimming. At target TSS levels of 18 °Brix (10 % ethanol, v/v) in the Marlborough vineyard and 20 °Brix (11 % v/v) in the Central Otago vineyard, V+ vines showed malic acid and titratable acidity levels comparable to the control. At the Canterbury vineyard, these parameters remained similar across all treatments at 16 °Brix (8.9 % v/v). Yeast-assimilable nitrogen concentration increased (188 to 411 mg/L) in early trimmed vines. At Central Otago, roots showed lower carbohydrate reserves across all trimming treatments, likely due to the high yield at the site, while at Canterbury, trimming did not result in significant differences in carbohydrate reserves, likely due to the low yield at the site. At the Marlborough vineyard, vines trimmed early and more severely had less starch in their roots, while HV+ vines maintained similar levels of starch to controls. In conclusion, halving the canopy post-veraison (HV+, LA 0.70 m²/kg as observed in Marlborough) could be considered a viable viticultural option to lower sugar accumulation, thereby reducing potential alcohol content, without affecting titratable acidity and pH. This practice offers significant potential for adapting to a warming climate and producing lower alcohol Pinot noir wines in a sustainable manner.
Production Decline Analysis in Fortin de Piedra Field. Application of Time-Rate Relations Using Public Data
Authors: Vezzosi Ivan , Piñeiro Patricio , Testa Ezequiel 
Published: November 2024

Abstract
The scope of this paper is to determine flow regimes, forecast production and estimate the ultimate recovery for Fortin de Piedra field, applying time-rate relations and diagnostic plots developed for unconventional reservoirs, to type decline curves of horizontal wells derived from production data analysis.
Oil and gas well production data were compiled and a data base was created. Oil and gas production rates, monthly and yearly production and cumulative production, and Gas-Oil Ratio per well were calculated. Wells were clasified based on produced fluid. Oil and gas production rate curves for dry gas, wet gas and condensate gas type wells, were fitted using Hyperbolic, Stretched Exponential, Power Law Exponential, Duong and Logistic Growth models. Decline curves were analysed. Flow regimes were identified using diagnostic parameters: Decline Rate, b and β parameters, log (q vs t), log (q/Q vs t). Production was forecasted and ultimate recoveries for dry gas, wet gas and condensate gas type wells and total reserves of the field were estimated.
Fortin de Piedra wells produce condensate gas on the eastern side of the field and wet gas on the western side. Two wells produce dry gas.
In average, after one year of production, gas production rate declines 39% in condensate gas wells, 31% in wet gas wells, and 46% in dry gas wells. Oil production rate declines 31% in condensate gas wells and 21 % in wet gas wells.
Condensate gas, wet gas and dry gas type wells exhibit transient bilinear, followed by transient linear and then pseudo-steady state, boundary dominated flow.
EUR is predicted between 266 and 408 million cubic meters of gas, and between 23,900 and 37,100 cubic meters of oil for condensate gas wells; 295 and 408 million cubic meters of gas for wet gas wells; and between 159 and 263 million cubic meters of gas for dry gas wells. EUR of the entire field is predicted between 79,000 and 140,000 cubic meters of gas, and 4,500,000 and 7,000,000 cubic meters of oil.
In this work, production is forecasted and oil and gas reserves are estimated for Fortin de Piedra field type wells and for the entire field, by applying traditional (Arps) and advanced (developed for unconventional reservoirs) empirical models to match production decline curves derived from production data. The application of each model was assessed. Flow regimes were identified. Also by identifying and classifying the fluids produced in each well, the Vaca Muerta Formation fluid distribution map is readjusted.
Integral Workflow for Optimizing Unconventional Field Development Strategies
Authors: Zorzi E. , Ricci B. , Romano L. , Monaco A. , Herrero F. 
Published: November 2024

AbstractThe development of unconventional reservoirs like La Calera in the Vaca Muerta formation presents unique challenges due to the complex behavior of gas-oil ratio (GOR), varying PVT properties, gas and condensate dispatch restrictions, parent-child degradation, frac-hits impacts, performance of different stacking/completion, rigs availability and simultaneous operations among others. In this paper, we introduce a set of custom-built tools designed to optimize the field's development strategy: Virtual Flow Metering (VFM), Auomated History Matching and an Integrated Production Model (IPM) coupled with an optimized and a Parent-Child Module. VFM enables daily production tracking, well-by-well allocation, and loss identification, allowing for real-time decision-making to meet gas and condensate demands. A workflow for automatic parameter estimation allows for scalable well-by-well tuning, capturing the uncertainties inherent in these reservoirs. By integrating these tools with a coupled reservoir model and optimizer, we generate reliable short- and long-term production forecasts, optimizing both development schedules and commercial commitments.The decision to implement these tools in Python provided unmatched flexibility, enabling custom adjustments for the Vaca Muerta formation's specific characteristics. This in-house solution avoids the limitations of commercial software and allows for continuous updates and scaling as new data becomes available. We also minimize dependency on commercial licenses, making it possible to run the model across multiple workstations simultaneously. In the near future, we aim to migrate IPM to the cloud for enhanced computational scalability, enabling the parallel execution of complex scenarios. Additionally, a stochastic module is under development to capture uncertainties from type-well parameters and put-on-production schedules. An algorithm is also being designed to propose drilling and completion scenarios based on rig availability, production commitments, and fracture-driven interactions, minimizing the parent-child effect and optimizing economic performance.These tools and workflows have proven effective in optimizing La Calera's development strategy, contributing to the overall value maximization of the asset by aligning technical and commercial objectives.
Injection Allocation in Secondary Petroleum Recovery
Authors: Rotondo J. 
Published: November 2024

Abstract
This study proposes an enhancement to the injection allocation method in Golfo San Jorge aimed at increasing the accuracy of injected flow rate measurements during secondary oil recovery, with the objective of reducing the number of flowmeter interventions in the field.
Two new correction factors are introduced in the calculation of injection allocation, which consider the stabilization of the injector well after an intervention with wireline or workover equipment, as well as the measurement obtained from the flowmeter associated with the well or an external flowmeter. The analysis involved comparing data from 112 injection wells across various databases, particularly using data from Wireline and Flowmetry, supported by a telemetry system that provides telemetered field data.
The incorporation of these new correction factors has significantly improved injection allocation and reduced the need for interventions on flowmeters by 68% within a group of 112 injection wells. This improvement stems from mitigating errors associated with previously unconsidered variables, such as pressure and flow stabilization in injection wells post-wireline intervention.
The innovation of this project lies in demonstrating that by challenging and improving current calculations and procedures, it is possible to optimize a process and reduce costs by efficiently utilizing existing resources. In this study, field telemetry flow data was used, and new correction factors were proposed to obtain actual flow rates that account for the real behavior of the injection well post-wireline intervention.
AI-Driven Digital Facility Assistant for Enhanced Operational Efficiency and Safety
Authors: Andiarena J. C. , Medina E. G. Bogado 
Published: November 2024

Abstract
This work describes the development and implementation of a digital assistant for the remote management of industrial facilities, focused on improving precision and operational decision making. The digital assistant, developed in three phases, integrates both manual and real-time data to diagnose and recommend corrective actions. In the first phase, the system assesses component health using a database of operational, safety, and environmental parameters. The second stage integrates historical and real-time data, and the third automates corrective actions. Preliminary results demonstrate significant improvements in operational efficiency and safety, emphasizing the assistant's potential as a critical tool in the sector's digital transformation. This document details the system architecture, evaluation methodology and observed benefits, providing a roadmap for the future implementation of this type of technologies in the industry.
New Approaches to Researching AI Crime: Institutionalization of Digital Criminology
Authors: Spyropoulos F. 
Published: November 2024

Objective: the article deals with modern scientific approaches to the “digital society”, identifies new criminological perspectives, such as that of digital criminology in an ever-changing hybrid world, in the scientific study of the potential use of AI by criminals, including what is referred to here as AI crime.Methods: this article is an essay commonly used in humanities and social sciences, as the author aims to present provocative arguments to encourage readers to rethink AI issues in relation to criminality in the “hybrid world” based on a non-systematic literature review. The arguments should be supported by relevant references to “digital criminology” and its non-binary way of thinking in favour of a techno-social approach.Results: the era of divided perspectives is coming to an end, and it’s time for synergies, especially at the interdisciplinary level. The «mirror of artificial intelligence» can help identify flaws and solutions, ensuring the future of AI and human society is decided by the people. In a digital society, technology is integrated into people’s lives, including crime, victimization, and justice. Digital technologies blur the boundaries between online and offline realities, creating a human-technological hybrid world where crimes occur in virtual networks. AI has potential for social good and Sustainable Development Goals, but concerns about human rights violations need to be addressed. Multidisciplinary approaches are needed to ensure safe use, address education inequalities, enhance justice, and identify online behavior as deviant or criminal. In the context of emerging technoethics, the idea that this unofficial norm, derived from a popular belief, will be the ‘touchstone’ for characterising online mediated behaviour as deviant/ crimninal, is missing - or rather in the process of being formed.Scientific novelty: the author aims to provide some insightful thoughts on formulating the right questions and interesting reflections from a technoethical perspective on the phenomenon of the use of information and communication technologies for criminal purposes under the catalytic influence of AI, recognising the social challenges arising from technological disruption (e.g. prediction and prevention through the transformation of policing, increased surveillance and criminal justice practises) in “digital society”.Practical significance: some of the initial ideas of this theoretical material can be used in the elaboration of proposals for amendements and additions to the current crime legislation, as well as in pedagogical activity, especially in the implementation of educational courses or modules on crime in the context of the digital transformation of society.
Coexistence of the blaZ Gene and Selected Virulence Determinants in Multidrug-Resistant Staphylococcus aureus: Insights from Three Nigerian Tertiary Hospitals
Authors: Kilani Adetunji Misbau , Alabi Emmanuel Dayo , Adeleke Oluwafemi Ezekiel 
Published: November 2024

Abstract

Background and Purpose
Infections caused by β-lactamase-producing strains of Staphylococcus aureus have become increasingly difficult to treat due to the expression of multiple virulence factors. This has heightened concerns about managing S. aureus-related infections. This study was conducted to characterize the blaZ gene and selected virulence determinants in β-lactam resistant S. aureus from human sources in three Nigerian tertiary hospitals.
Materials and Methods
Three hundred and sixty samples were collected for the study. S. aureus was isolated and characterized following standard microbiological protocols and nuc gene amplification. Antibiotic susceptibility and minimum inhibitory concentration tests were performed using the disk diffusion method and E-tests, respectively. Biofilm formation and β-lactamase production were assessed using Congo red agar and nitrocefin kits, while the blaZ gene was examined using conventional PCR. Capsular polysaccharide genotyping, accessory gene regulator (agr) detection, Panton-valentine leucocidin (PVL), and PVL proteins were performed using PCR and Western blotting.
Results
S. aureus was recovered from 145 samples, 50 (34.5%) of these isolates exhibited multidrug resistance, with MICs ranging from 0.125 to 1.00 µg/mL, and showed significant resistance to aminoglycosides, fluoroquinolones, and β-lactams. Of these, 31 strains produced β-lactamases, 30 of which carried the blaZ gene in combination with cap8 (80%) or cap5 (20%). Biofilm formation and PVL gene were observed in 85% of the 20 randomly selected blaZ-positive multidrug-resistant (MDR) strains. The agr2 allele was predominant, found in 70% of the selected MDR strains. No significant difference in the occurrence of the blaZ gene was found among the three clinical sources (p ≤ α0.05).
Conclusion
The co-occurrence of the blaZ gene with PVL, capsular polysaccharide genes, and agr alleles is associated with biofilm formation, indicating a high risk of β-lactam-resistant S. aureus infections. Our findings highlight the need for continuous molecular surveillance to enhance infection management, treatment options, and patient outcomes in the study locality. A limitation of this study is the random selection of MDR isolates, which may affect the comprehensiveness of the analyses.
Process Optimization and Mechanical Properties Analysis of Inconel 718/Stainless Steel 316L Multi-material via Direct Energy Deposition
Authors: Chen Yu-Xiang , Qiu Jun-Ru , Chang Wei-Ling , Hwang Yi-Kai , Hwang Sheng-Jye 
Published: November 2024

Abstract

Additive manufacturing (AM), also known as 3D printing, is a recent innovation in manufacturing, employing additive techniques rather than traditional subtractive methods. This study focuses on Directed Energy Deposition (DED), utilizing a blend of nickel-based superalloy IN 718 and stainless steel SS316 powders in varying ratios (25%+75%, 50%, and 75%+25%). The objective is to assess the impact of process parameters on quality and optimize them. Mechanical properties of the different powder mixtures are compared. In the study, Taguchi-grey relational analysis is employed for parameter optimization, with four key factors identified: laser power, overlap ratio, powder feed rate, and scanning speed, affecting cladding efficiency, deposition rate, and porosity. Verification experiments confirm optimization repeatability, and further fine-tuning is achieved through one-factor-at-a-time experiments. Optimized parameters yield varied tensile properties among different powder mixtures; for example, a 25% SS316L and 75% IN718 blend demonstrates the highest ultimate tensile strength (499.37 MPa), while a 50% SS316L and 50% IN718 blend exhibits the best elongation (13.53%). This study offers an effective approach for using DED technology to create mixed SS316 and IN718 powders, enabling tailored mechanical performance based on mixing ratios.