bluuebunny/crossref_metadata_2025_split huggingface dataset:
O papel da psicologia na promoção da saúde mental de agricultoras
Authors: Pisoni Godoy Luthiane , Da Rosa Ramos Bruna , Rafaela dos Santos Joice , Elisa Fank Rafaela 
Published: August 2024

Este estudo apresenta uma pesquisa acerca de aspectos da saúde psicológica de mulheres agricultoras e o papel que a psicologia exerce em suas vidas, destacando a complexidade de seus cotidianos, permeados de responsabilidades invisibilizadas. Mulheres rurais enfrentam sobrecarga de trabalho, desvalorização de suas atividades e falta de políticas específicas. A saúde mental nas comunidades rurais é pouco abordada, com dificuldades de acesso ao acompanhamento psicológico. Com os dados do projeto em andamento "Agricultoras em Ação", que utiliza grupos operativos para promover o empoderamento e discutir temas relevantes, esta pesquisa é qualitativa exploratória, baseada em entrevistas, realizadas com as mulheres participantes do projeto, selecionadas a partir de critérios específicos. A partir desse objeto, será presentada uma perspectiva teórica embasada em discussões de gênero, sexismo e excesso de carga de trabalho feminino, direcionando olhares para o meio rural. O estudo segue princípios éticos, garantindo anonimato e sigilo e os resultados são compostos por relatos das entrevistas e dos grupos, nos quais as participantes destacam questões de autoestima, ansiedade e a influência positiva do projeto em suas vidas, contribuindo para a melhoria da saúde psicológica, reduzindo o uso de medicação, lidando com crises e fortalecendo a autoconfiança. Aponta-se, ainda, para a importância de políticas públicas sensíveis à saúde mental dessas mulheres. De forma geral, o estudo contribui para a compreensão da saúde mental das mulheres agricultoras, evidenciando a importância da psicologia no contexto rural. Propõe a ampliação da atuação da psicologia nesses contextos, considerando as especificidades culturais e sociais.
Clonal propagated 'Ek Pothi Lehsun' as a potential antifungal agent against Candida sp.
Authors: Sharma Ankita , Shukla Shardulya , Patel Manoj Kumar , Chaurasia Om Prakash , Saxena Shweta 
Published: August 2024

'Ek Pothi Lehsun', also known as snow mountain garlic, is a type of garlic grown in the high mountainous region of Jammu and Kashmir state of India. The present study aimed to develop a protocol for propagating snow mountain garlic in-vitro using corm seed as an explant. The study also assessed the antifungal potential of in vitro-grown bulbils against different Candida species. Four different concentrations of NAA and 2,4-D were tested for their effectiveness in promoting root formation, and eighteen different combinations of BAP (µM), KN (µM) and TDZ (µM) were investigated for effective proliferation of shoots with varied lengths. Shoot with maximum length (5.03±1.40) was obtained in MS medium containing 1.0 µM TDZ after 24 days of inoculation, whereas MS basal media was found effective for rooting plantlets. Rooted micro shoots were acclimatized successfully in hardening treys with a percent survival of nearly 80%. Seven different concentrations of Sucrose, i.e. 5%, 7%, 10%, 15%, 17%, 20%, and 25% were investigated for effective bulbil formation. Bulbil with a maximum diameter of 0.86 cm was obtained in 20% sucrose-containing MS media in 5 days. Further, the antifungal potential of aqueous extract (TC-SMG) of in vitro grown bulbils was investigated against three Candida sp. A zone of inhibition of 22.30±0.33 mm, 17.3±0.33 mm and 19.3±0.33 mm was observed against C. albicans, C. tropicalis and C. glabrata respectively, by using 200 mg/mL extract after 24 hrs depicting the remarkable potential of TC-SMG as an antifungal agent. In vitro culture of snow mountain garlic has demonstrated promising antifungal properties against Candida species.
Intrapreneurial intention mediates between individual entrepreneurial orientation, entrepreneurial self-efficacy and intrapreneurial behaviour
Authors: Wijetunge Wijetunge Arachchige Deepani Sajeewa , Yusoff Siti Khalidah Binti Md , Azam Ferdous , Tham Jacquline 
Published: August 2024

The purpose of the study is to investigate the influence of Individual Entrepreneurial Orientation (IEO) and Entrepreneurial Self-efficacy (ESE) towards Intrapreneurial Behaviour (INB). Entrepreneurial Intention and Entrepreneurial Behaviour have been a growing interest of the scholars in research in entrepreneurship literature during the last three decades. Rigorous reviews on intentions and behaviors only appeared in limited number of studies to investigate the mediating effect of Intrapreneurial Intension. Further, this study examines the mediation effect on Intrapreneurial Intention (INI) between IEO, ESE, and INB. Thus, this study attempts to test an extended model to understand the individual behaviour of using TPB and IEO. The methodology is quantitative, followed by a survey method. The sample contained 120 small tea exporting companies in Sri Lanka, registered with the Sri Lanka Tea Board (SLTB). The data were collected from Owners and Managers of those companies. The results discovered that there is a significant positive impact of IEO, ESE, and INI on INB. Also, it was registered that Intrapreneurial Intention mediates the direct relationships and implies that IEO and ESE can enhance INB through Intrapreneurial intentions. In this scenario, INI plays an important role in influencing INB. Therefore, tea industry, the government, regulatory bodies and policymakers use these findings to enhance the INB among small tea exporters in Sri Lanka. This study provides useful insights to small tea exporters in Sri Lanka on how to enhance intrapreneurial behavior through psychological factors.
A need for emotionally intelligent leaders in educational institutions: A review of the effects of leadership style on burnout teachers
Authors: Dishari Samira , AlAfnan Mohammad Awad 
Published: August 2024

For the three pillars of education: teacher, student, and curriculum to function properly, leadership plays an intrinsic role. Academic leadership aims to provide the right working environment for proper teaching and learning to take place. Thus, leadership style has a paramount effect on teachers who consequently affect students and ensure proper instruction to all aspects of curriculum. This article review aims to unfold the dynamics of this relationship. In particular the researchers will attempt to explore the role of transformational leadership which also displays qualities of emotional intelligence on reducing the occurrence of the syndrome of burn out among teachers. Sample of empirical, experimental and case studies that examined the correlation between symptoms and causes of job burnout among teachers and the style of leadership practiced will be presented. Seven of which were examined to verify the impact of leadership in a school setting and three others to examine the same impact but in a university context. As a result, researchers assert that in traditional leadership where qualities of empathy, social awareness, and management of relationships are missing, job burnout cases among teachers increase. Finally, a recommendation to introduce emotional intelligence skills into academic leaders' training programs was made. The findings of this study shall serve leaders and policymakers in the teaching and learning sector in a way that would benefit them and assist their subordinates in avoiding burnout and achieve greater heights.
Exploring the Green Human Resource Management (GHRM) Practices of Public Higher Education Institutions (HEIs) Towards the Development of Green Social Responsibility Program Model
Authors: Garcia Arnaldo M. , Canoy Leonardo M. 
Published: August 2024

This study explores the practices of green human resource management (GHRM) and its relationships to environmental management systems (EMS) towards the development of green social responsibility program model. The study also looked at the impact and commitment to social responsibility programs and human resource management practices of selected HEIs in the provinces of MIMAROPA Region 4-B. The ability, motivation, and opportunity (A-M-O) theory was used to explain how the factors in this study related to one another and

to enhance employees’ abilities and efforts by fostering a collaborative work environment .
Alternately, to consider statistical treatment of data, through analysis of variations (ANOVA), and to determine the correlation between green HRM practices and the perceived level of environmental management systems’ performance of the Romblon State University (RSU), Palawan State University (PSU), and Mindoro State University (Min SU) as higher education institutions (HEIs) in MIMAROPA Region IV-B, Pearson’s product-moment correlation (Pearson’s r) was used to identify which among the green HRM practices that predicted the environmental management performance of these selected universities that significantly correlated the relationship between Green Human Resource Management and environmental Management Practices, with p value of less than 0.05, and it is interpreted that the correlation between the two variables is significant at 0.01 level (2-tailed). It means that GHRM affects the EMS through the full mediation of HEIs environmental knowledge, thus strengthening and validating the finding of a theoretical implication in terms of ability, motivation and opportunity (A-M-O)theory.
Analisis produksi telur peternakan ayam petelur di Kabupaten Kuningan Provinsi Jawa Barat
Authors: Atmadji Eko , Hafidhin Fahmi 
Published: August 2024

Purpose – This study analyze production of laying hen farms in Kuningan Regency using Cobb Douglas model and non-linear methods.
Methods – This study applies cluster method to select samples after determining the number of samples. The analysis method uses the Cobb Douglas production function. The Cobb Douglas model estimation employs a non-linear method, the Marquardt method. The production function model is that the amount of egg production is influenced by company capital and farm workers, whereas the estimation results are in the form of production elasticity numbers for capital and production elasticity numbers for workers. From the results of the estimated coefficients from the Cobb Douglas equation, this study obtains the category of returns to scale from laying hen farms in Kuningan Regency.
Findings – The findings of this study indicate that Non-Performing Loans (NPL) and Bank Operating Expenses to Operating Income (BOPO) have quite a large negative impact, but the Loan to Deposit Ratio (LDR) has a large beneficial impact on the Bank's Return on Assets (ROA) and Return on Equity (ROE).
Implication – The employment of capital is under capacity and the use of workers is over capacity. It means that breeders have to start utilizing their capital more, therefore egg production is more efficient.
Originality – This study employs Cobb Douglas production function model with non-linear estimation.

Abstrak
Tujuan – Penelitian ini menganalisis produksi di peternakan ayam petelur Kabupaten Kuningan dengan menggunakan model Cobb Douglas dan metode non linier.
Metode – Penelitian ini menggunakan metode kluster untuk memilih sampel setelah ditentukan jumlah sampelnya. Metode analisis menggunakan fungsi produksi Cobb Douglas. Estimasi model Cobb Douglas menggunakan metode non linier yaitu metode marquardt. Model fungsi produksinya adalah jumlah produksi telur dipengaruhi oleh kapital perusahaan dan pekerja peternakan dimana hasil estimasinya berupa angka elastisitas produksi atas kapital dan angka elastistisitas produksi atas pekerja. Dari hasil estimasi koefisien dari persamaan Cobb Douglas didapat jenis returns to scale dari peternakan ayam petelur di Kabupaten Kuningan.
Temuan – Berdasarkan hasil estimasi, penggunaan kapital masih berada di tahap 1 kurva produksi, sedangkan penggunaan pekerja berada di tahap 3. Secara total skala produksinya adalah increasing returns to scale.
Implikasi – Adanya penggunaan kapital yang di bawah kapasitas dan penggunaan pekerja di atas kapasitas, menyebabkan para peternak harus mulai lebih mendayagunakan kapitalnya agar produksi telur makin efisien.
Orisinalitas – Studi ini menggunakan model fungsi produksi Cobb Douglas dengan estimasi non linier.
Model empiris penggunaan e-money di Indonesia
Authors: Mustika Dhia Mega Ayu , Hakim Abdul 
Published: August 2024

Purpose – This paper analyzes the determinants of e-money usage in Indonesia. The determinants of e-money usage considered are inflation, interest rates from Bank Indonesia (BI-rate), and gross domestic product (GDP).
Methods – This paper estimates time series data from 2010 to 2022 in a conditional error correction model with the help of the Eviews 10 software package.
Findings – Data analysis found that all independent variables have an effect on e-money, both in the short term and in the long term.
Implication – The development of e-money, which has the potential to increase the amount of money in circulation and thus increase inflation, can be controlled by inflation, interest rates, and GDP.
Originality – The originality of this paper lies in the use of the conditional ECM model for modeling e-money in Indonesia.

Abstrak
Tujuan – Paper in menganalisis faktor-faktor penentu penggunaan E-money di Indonesia. Variabel-variabel penentu penggunaan e-money yang dipertimbangkan adalah Inflasi, tingkat bunga dari Bank Indonesia (BI-rate), dan produk domestik bruto (PDB).
Metode – Paper ini menggunakan data time series dari tahun 2010 hingga 2022. Paper ini menggunakan model conditional error correction model dengan bantuan program Eviews 10.
Temuan –Analisis data menemukan bahwa semua variabel independen berpengaruh terhadap e-money, baik dalam jangka pendek maupun dalam jangka panjang.
Implikasi – Perkembangan e-money, yang berpotensi menambah jumlah uang beredar dan dengan demikian bisa meningkatkan inflasi, bisa dikontrol dengan inflasi, tingkat bunga, serta PDB.
Orisinalitas – Orisinalitas dari paper ini terletak pada penggunaan model conditional ECM atas pemodelan e-money di Indonesia.
First Utilization of Fast Method of Casing Cut & Pull Motorized System in Middle East Region: First Combination of 8-1/4" Hydraulic Internal Casing Cutter with Standard Spear and Low Specs 4-3/4" Mud Motor as the Drive System Which Successfully Cut 5,653 Ft of 9-5/8" Casing in 20 Minutes
Authors: Al-Saadi D. M. , Gholoum S. M. , Al-Ajmi A. S. , Al-Ajmi M. B. , Pratama K. , Chib A. , Sadek T. 
Published: August 2024

Abstract
Traditional method of casing cutting takes long time as it requires two trips and there are risks associated due to long section of 9-5/8" casing that need to be retrieved. Furthermore, cutting casing in compression is not ideal in our case. Using cut and pull motorized system has an advantage in which surface verification for successful cut downhole can be observed on rig floor however one of the main challenges is to utilize a low specification mud motor 4-3/4" with flow rate range 150 - 250 gallon per minute (GPM) that can deliver approximately 4.45 K ft-lbs torque at 860 psi pressure differential across the tool. The one trip system consists of standard spear with spear stop sub, a spacer to accommodate the cutting depth, 8-1/4" hydraulic casing cutter with carbide inserts and 4-3/4" mud motor. The spear in the string helps to keep the casing in tension meanwhile the mud motor will deliver torque for the casing cutter knives to complete the job.
The single trip cut and pull system was performed successfully to cut long sections of 9-5/8" in 20 minutes only and managed to pull the 9-5/8" casing out of hole to surface without additional trips required. Monitoring string hook load and standpipe pressure are critical throughout the operation. All tools were functioned as expected although the cutting time take much longer compared to the bigger mud motor with higher specification in order to deliver maximum torque for the casing cutter. Knives came out of the hole in normal conditions with carbides worn-out observed at the knife tip. This successful cutting operation enables the operator in Kuwait to perform open-hole sidetrack below the 13-5/8" casing shoe, eliminating the cost to re-drill the well and reduces operational rig time. The integrated BHA design is proved to be applicable for onshore application despite the limitation of the rig.
Fast Track Drilling Campaign in a Large Field by Unlocking the Value of Digital & Rig Automation Technologies
Authors: AlHosni F. , AlRomaihi A. , Arias M. , Khader M. , Metwally O. , Handoko L. , Salah M. , Imad M. , Yasari A. 
Published: August 2024

Abstract
This paper describes the implementation of the Drilling Automation System, which has been initiated to control and enhance the drilling performance. The automation system fully controls the drilling parameters and surface rig equipment to improve the drilling Rate of Penetration (ROP) and mitigate drilling challenges. The results were measured systematically and compared to the manual rig operation benchmark.
The Drilling Automation System was integrated into the rig control system during the rig manufacturing process, then deployed and configured upon spud drilling operation. The system controls the Top Drive System (TDS), drawworks, mud pumps, and auto-driller by augmented intelligence. The system -when enabled- intelligently controls drilling parameters and surface equipment by creating a model of how the formation reacts to each drilling parameter along with segmenting the input of the engineering team to optimize drilling ROP, automated downlinking, and surveying for trajectory control, and optimize pre and post connection times. Additionally, it mitigates stick and slip, shocks and vibrations, and high erratic torque, which elongates the durability of drilling tools.
On the field level, a comprehensive drilling performance data analysis has been conducted to get an accurate comparison between manually operated rig performance and rigs with an integrated automation system. Close monitoring of the improvements in drilling performance, avoidance of hidden Non-Productive Time (NPT), overcoming drilling challenges, more downhole tools durability, and smooth directional drilling performance. The automated rig outcomes proved the success and capability of achieving higher Key Performance Indicators (KPIs) and benchmarks than manually operated rigs by an additional 33%, with a possible window for future enhancements. The Automation System is beneficial for automating surface equipment; however, the great output comes from the automation of the driller's decisions with full procedural adherence.
Automating the drilling process with a synergy between surface and downhole tools is the future. The system's immediate response to downhole conditions minimizes drilling issues without human interaction. The result seen in this experiment shows a promising future for implementing this technology with flexibility for further upgrades.
Digital Pore Pressure Prediction for Well Drilling Using Machine Learning in a Deep Shale Gas Field
Authors: Yue W. H. , Liu P. , Wen R. , Gou Q. Y. , Li Q. S. , Xu E. S. , Ling W. T , Huang Y. J. , Ren X. X. , Yu T. , Ninsom C. , Doan D. 
Published: August 2024

Abstract
Abnormal pressure and wellbore instability are the main challenges during drilling in shale gas reservoirs. Traditionally, the pre-drill predictions of pore pressure and wellbore stability are executed manually by geomechanics engineers. The procedures are usually complicated and take time, the results also highly depend on the executor's expertise. All these make pore pressure and wellbore stability prediction far from ideal and automatic. In this study, we utilized machine learning methods to perform prediction in a simpler manner. The digital models were trained with existing well data, geology data and drilling data, and were correlated with spacing coordinates, that contains geological structure information. The models on formation materials properties are trained and learnt with patterns recognition; the pore pressure, earth stresses and wellbore stability are trained with physics-based hybrid algorithm. The trained models are then used to predict pore pressure and mud weight window at any point in subsurface or along any planned well trajectory, to identify drilling risks and recommend solutions.
This approach was applied and validated in a deep shale gas field in Sichuan basin, China. In this field, the main shale gas reservoirs are overpressured and severe drilling complexities were encountered in drilling. Horizonal development wells are planned to drill to enhance production. This requires pre-drill pore pressure and wellbore stability prediction. Due to multiple abnormal pressure mechanisms and subsurface complexity, manual methodology is usually time-consuming, and the results are not consistent with different executors. With the developed new machine learning method, the digital models were trained with eleven geology surfaces and well data from eight existing wells. The trained model was used to predict pore pressure and mud weight window, including formation collapse pressure, mud loss pressure and breakdown pressure. The machine learning prediction of planned horizontal well Y14H and well Y15H were then compared against manual results calculated by geomechanics experts. The digital results matched well with manual results. The actual drilling results of well Y15H also confirmed the accuracy of the machine learning method. In well Y15H drilling, there were no drilling complexities and hole enlargements as using mud weight optimized with machine learning prediction. After well completed, the results showed that the pore pressure difference was only 0.5% between downhole measurement, 53.1MPa, and machine learning prediction, 52.8MPa. The minimum horizontal stress difference was about 5% between machine learning prediction, 72.88MPa, and downhole measurement, 76.76MPa. This field study confirmed the accuracy, effectiveness, and efficiency of machine learning method.