bluuebunny/crossref_metadata_2025_split huggingface dataset:
Studying the role of corporate social responsibility, green HRM and green innovation to improve green performance of SMEs
Authors: Azam Tamoor , Jamil Khalid 
Published: August 2024

Purpose
The purpose of this study is to find out the relationship between the corporate social responsibility (CSR) and green performance (GP) of Pakistani manufacturing SMEs. This study further explores the mediating roles of green human resource management (GHRM) and green innovation (GI) in the relationship between CSR and GP.

Design/methodology/approach
A survey method was used to collect data from manufacturing SMEs. Data were collected from 366 respondents working in higher positions and playing a decisive role in the organization. The collected data were analysed by applying structural equation modelling with the help of smart PLS.

Findings
The study shows that CSR (customers, society, employees) helps significantly improve a firm's GP. Furthermore, this study explores how GI (process, product) and GHRM (skills development, motivation and involvement) mediate the relationship between CSR and GP.

Research limitations/implications
This study is limited to manufacturing SMEs and a single developing country, Pakistan. However, this study will significantly contribute to the existing literature on GP and help manufacturing firms’ top management take steps to minimize carbon emissions and improve GP. Furthermore, this study will also provide valuable insights to government agencies in the Asian context to adjust their policies regarding the manufacturing sector to reduce pollution in the country.

Originality/value
As a pioneering study encompassing CSR, GHRM, GI and GP under one research paradigm in an emerging economy environment, the current research provides substantial additions to the literature on the impact of CSR on GP.
A high-efficiency positioning error compensation method for a large parallel mechanism based on pose correction similarity
Authors: Li Hongbin , Wang Zhihao , Sun Nina , Sun Lianwen 
Published: August 2024

Purpose
Considering the influence of deformation error, the target poses must be corrected when compensating for positioning error but the efficiency of existing positioning error compensation algorithms needs to be improved. Therefore, the purpose of this study is to propose a high-efficiency positioning error compensation method to reduce the calculation time.

Design/methodology/approach
The corrected target poses are calculated. An improved back propagation (BP) neural network is used to establish the mapping relationship between the original and corrected target poses. After the BP neural network is trained, the corrected target poses can be calculated with short notice on the basis of the pose correction similarity.

Findings
Under given conditions, the calculation time when the trained BP neural network is used to predict the corrected target poses is only 1.15 s. Compared with the existing algorithm, this method reduces the calculation time of the target poses from the order of minutes to the order of seconds.

Practical implications
The proposed algorithm is more efficient while maintaining the accuracy of the error compensation.

Originality/value
This method can be used to quickly position the error compensation of a large parallel mechanism.
ESG Disclosures in the Private Equity Industry
Authors: ABRAHAM JEFFERSON , OLBERT MARCEL , VASVARI FLORIN 
Published: August 2024

ABSTRACTThis paper offers the first systematic evidence on environmental, social, and governance (ESG) disclosures provided by a large global sample of private equity (PE) firms. Using historical websites from 2000 to 2022, we develop and validate a novel dictionary‐based measure of voluntary PE firm ESG disclosures. Descriptive statistics reveal an increasing time trend in these disclosures, with social topics becoming as important as environmental topics recently. Multivariate analyses show that the demand for ESG information from fund investors is a significant determinant of PE firms’ ESG disclosures. Leveraging data on PE firms’ portfolio companies, we document that more PE firm ESG disclosures are associated with better ESG outcomes at the portfolio company level, suggesting that voluntary ESG disclosures align with real actions for the average PE firm.
Simultaneous top–down and bottom–up control of cereal aphids by predation, companion planting and host‐plant diversity
Authors: Zeller Julian W. , Khudr Mouhammad Shadi , Fylypchuk Tetiana V. , Bahlei Oksana V. , Buzhdygan Oksana Y. 
Published: August 2024

AbstractAphids are among the most economically significant pests in cereal crops worldwide. Despite high interest in the natural control of aphids by applying natural enemies, intercropping and companion planting, the concurrent effects of the combinations of these methods due to their synergistic or antagonistic interactions remain largely unknown for both aphids and their host crops. Here we identify the relative effectiveness of simultaneous bottom–up and top–down factors in controlling one of the most economically important species of cereal aphids, the bird cherry‐oat aphid Rhopalosiphum padi L. For this, we conducted microcosm experiments using a full‐factorial design of three aphid‐control treatments including predator presence (i.e., lacewing larvae of Chrysoperla carnea), host‐plant intercropping (i.e., barley alone vs barley in combination with wheat and rye) and companion planting with an aphid‐repellent plant (garlic), and estimated their direct, indirect and interactive effects on aphid density. Our results show strong simultaneous top–down control of the aphid population by predation and bottom–up control by both host‐plant biomass and companion planting with garlic. The use of garlic as a companion plant for cereal crops in our study neither altered crop biomass nor suppressed the efficiency of aphid predator. Our findings suggest that the simultaneous application of aphid predator and companion planting with garlic holds promise as a potential strategy for the natural control of cereal aphid populations on grain crops, without generating related agroecosystem disservices, such as loss in crop production and deterioration of the natural enemies of pests. However, given the controlled lab conditions and limited timeframe of our study, further research is needed to confirm its effectiveness in field conditions to ensure its broader applicability in sustainable agricultural practices.
Parenthood and gender inequality on labor market outcomes: Evidence from South Korea
Authors: Kim Eunha , Hong Baegeui 
Published: August 2024

AbstractThis study estimates the long‐term effect of parenthood on labor market outcomes and explores the variations within this effect by gender and education. We use the event study method to track changes in a range of labor market outcomes from 3 years before to 8 years after the first birth, with a sample of 556 married women and 528 married men from the Korea Labor and Income Panel Study (KLIPS). We find that women experience an immediate drop in wages following birth, whereas men experience continuous wage growth even before birth. The decline in women's wages arises largely from their withdrawal from the labor market, while the increase in men's wages could be explained by a positive selection bias among fathers. In addition, mothers' wage trajectories do not vary significantly by education level, whereas other labor market outcomes show discernible trends. These patterns are the opposite of those observed for men. The findings indicate that severe gender inequality in the Korean labor market lowers the wages of mothers, regardless of their education, while the wages of fathers are more likely to be affected by education. Based on the findings, we make policy suggestions for improving the work‐family balance for all genders.
Microbiome in sickle cell disease: Pathophysiology and therapeutic insights
Authors: Gupta Chhedi Lal , Jaganathasamy Nagaraj , Madkaikar Manisha 
Published: August 2024

SummarySickle cell disease (SCD) is a complex genetic blood disorder characterized by abnormal haemoglobin, resulting in sickle‐shaped red blood cells. While extensive research has concentrated on the genetic and physiological aspects of SCD, recent studies suggest a potential role of the human microbiome in SCD pathophysiology, adding new dimensions to its understanding. This review synthesizes current knowledge on the microbiome's involvement in SCD, focusing on alterations in the gut microbiome composition and diversity compared to healthy individuals, and their implications for disease pathogenesis. We explore how microbiome changes may contribute to vaso‐occlusive crises and other complications, along with the possible associations of specific microbial taxa or markers with disease crises and clinical outcomes. Additionally, we discuss the potential of microbiome‐targeted interventions, including probiotics, dietary modifications, and faecal microbiota transplantation, in managing SCD complications and improving patient outcomes. Understanding the intricate relationship between the microbiome and SCD could lead to innovative therapeutic strategies and personalized interventions for better managing the disease. This review underscores the importance of further microbiome research and its integration into holistic SCD care.
Effect of group play therapy as holistic geriatric interventional modality on feelings of loneliness among older people: A randomized control trial
Authors: Jamei Fateme , Saleh Moghadam Amir Reza , Mazlom Seyed Reza , Namazinia Mohammad , Asghari Nekah Seyed Mohsen , Mohajer Samira 
Published: August 2024

AimPrevious research has identified loneliness as a significant social stressor among the older adult population, and highlights the scarcity of empirical research on the efficacy of group play therapy as a method for addressing loneliness in this demographic. This study aimed to explore the impact of group play therapy on reducing feelings of loneliness among older individuals.MethodsA randomized clinical trial was carried out in 2018 on 60 older adult participants from two governmental health centers in Mashhad, Iran. The intervention group received adult‐centered play therapy for 12 sessions over 6 weeks, with each session lasting 60 min. The therapy protocol combined traditional and modern games, structured into three stages: warm‐up, working and closing. The University of California, Los Angeles (UCLA) scale was used to measure feelings of loneliness at baseline and after the intervention. Data analysis was carried out using SPSS version 21.ResultsThere was a significant decrease in feelings of loneliness in the intervention group compared with the control group (P < 0.001). Additionally, a significant difference in feelings of loneliness was observed within the intervention group between baseline and follow up (P < 0.001).ConclusionsGroup play therapy, involving a combination of traditional and modern games, can reduce feelings of loneliness among older adults. This method can promote healthy aging and improve mental health issues, such as loneliness, among older people. These findings can be utilized in healthcare centers and nursing homes for older adults. Geriatr Gerontol Int 2024; ••: ••–••.
Self‐normalization inference for linear trends in cointegrating regressions
Authors: Cho Cheol‐Keun 
Published: August 2024

In this article, statistical tests concerning the trend coefficient in cointegrating regressions are addressed for the case when the stochastic regressors have deterministic linear trends. The self‐normalization (SN) approach is adopted for developing inferential methods in the integrated and modified ordinary least squares (IMOLS) estimation framework. Two different self‐normalizers are used to construct the SN test statistics: a functional of the recursive IMOLS estimators and a functional of the IMOLS residuals. These two self‐normalizers produce two SN tests, denoted by and respectively. Neither test requires studentization with a heteroskedasticity and autocorrelation consistent (HAC) estimator. A trimming parameter must be chosen to implement the test, whereas the test does not require any tuning parameter. In the simulation, the test exhibits the smallest size distortion among the inferential methods examined in this article. However, this may come with some loss of power, particularly in small samples.
Rethinking rural: Public health advocates' views on ENDS cessation for young adults in rural areas
Authors: Thongpriwan Vipavee , Christraksa Wilawan , Eyadat Anwar , Gwon Seok Hyun 
Published: August 2024

AbstractElectronic nicotine delivery systems (ENDS, commonly referred to as e‐cigarettes), have become popular among young adults (YAs, 18–24 years) in the United States. YAs in rural areas increasingly consume more ENDS than those in urban areas. However, there is a knowledge gap regarding the perspectives of public health advocates (PHAs) on ENDS use and cessation among YAs in rural areas.The objectives of the study are to describe the perspectives of PHAs and identify strategies to strengthen the capacity for promoting the cessation of ENDS among YAs in rural communities.A qualitative study and interpretive description were used with semi‐structured interviews. The content analysis was used to analyze the data.Twenty‐two PHAs, including public health officers, nurses, and tobacco‐free educators, from Wisconsin, Minnesota, and North Dakota, were invited to the semi‐structured interviews.Four themes emerged: (a) Perceived ENDS use and cessation; (b) rural contexts and infrastructure influencing ENDS use; (c) essential public health responsibilities controlling ENDS use in rural areas; and (d) regulating ENDS use: Policies and law. PHAs stressed the importance of increased awareness of ENDS use in YAs, improved regulation, and tailored policies to tackle rural communities’ distinct challenges.The study emphasizes the urgency for specialized programs to aid YAs in quitting ENDS in rural areas. A comprehensive strategy is needed to effectively address ENDS use among YAs in rural areas, involving education, policy adjustments, and community‐based initiatives.
Facilitators and barriers in the implementation of a fall prevention program based on physical activity for elderly people living in the community: A qualitative study
Authors: Costa‐Menén Maria Àngels , Gimeno‐Pi Iraida , Martin‐Servet Gemma , García‐Martínez Ester , Porté‐Llotge Mercè , Blanco‐Blanco Joan 
Published: August 2024

AbstractBackgroundPhysical activity is recognized as beneficial for older individuals in preventing falls. Achieving high adherence to exercise programs among the elderly poses challenges for administrations and healthcare systems. This study explored the facilitators and barriers perceived by both the participants and nurse trainers involved in an exercise program aimed at preventing falls in primary healthcare.MethodsSixteen semi‐structured interviews with elderly people who had participated in the Otago Exercise Program and a focus group of nurse trainers of this program were conducted between October 2018 and September 2019 in primary health care centers in Lleida, Spain. Interviews were transcribed and analyzed using inductive thematic analysis with Atlas.ti 8 software.ResultsAnalysis revealed five overarching categories and 17 subcategories. Key facilitators included personal motivation, the perceived benefits of exercise, and the supportive role of nurse trainers. Primary barriers encompassed factors such as the excessive duration of the program, not considering personal preferences for individual or group participation, and differences in physical condition among group participants.ConclusionsTo increase participation and adherence to exercise programs, it is necessary to consider the important role of the nursing professionals that recommend program enrolment and the participants’ personal motivations. The program with group sessions is a model that is easy to integrate into Primary Healthcare centers, which must always take into account the preferences and physical conditions of the participants.
A modern concept of Lagrangian hydrodynamics
Authors: Margolin L. G. , Canfield J. M. 
Published: August 2024

AbstractWe offer a modern interpretation of Lagrangian hydrodynamics as employed in Lagrangian simulations of compressible fluid flow. Our main result is to show that artificial viscosity, traditionally viewed as a numerical artifice to control unphysical oscillations in flows with shocks, actually represents a physical process and is necessary to derive accurate simulations in any compressible flow. We begin by reviewing the origins of two numerical devices, artificial viscosity and finite‐volume methods. We proceed to construct a mathematical (PDE) model that incorporates those numerics and in which a new length scale, the observer, arises representing the discretization. Associated with that length scale, there are new inviscid fluxes that are the artificial viscosity as first formulated by Richtmyer and an artificial heat flux postulated by Noh but typically not included in Lagrangian codes. We discuss the connection of our results to bivelocity hydrodynamics. We conclude with some speculation as to the direction of future developments in multidimensional Lagrangian codes as computers get faster and have larger memories.
Improved Machined Accuracy Under a Constant Feed Speed Vector at the End-Milling Point Considering Machining Force and Machining Area in Tool Approach
Authors: Suzuki Takamaru , Hirogaki Toshiki , Aoyama Eiichi 
Published: August 2024

Abstract
A five-axis machining center is known for its synchronous control capability, allowing complicated three-dimensional surfaces, such as propellers and hypoid gears, to be quickly created. We aimed to maintain the feed speed vector at the end-milling point by controlling two linear axes and a rotary axis with a five-axis machining center to improve the machined surface quality. In previous research, we suggested a method to reduce the shape error of machined workpieces (referred to as the shape error herein) considering the approach path of the tool determined via calculation. However, a high machining force at the start of the workpiece cutting was observed. In this research, a theoretical method to estimate the machining force is developed by using an instantaneous cutting force model, which considers the synchronized motion of two linear axes and a rotary axis of the 5MC. Subsequently, the most suitable approach path of the tool is determined considering the prediction of machining force and the machining area in the approach path. Therefore, both a high machining force at the start of the workpiece cutting and shape error reduction can be realized by using the proposed approach path of the tool.
Agile Surface Inspection Framework for Aerospace Components Using Unsupervised Machine Learning
Authors: Nandagopal Arun , Kulkarni Abhishek , Acton Colin , Manohar Krithika , Chen Xu 
Published: August 2024

Abstract
Quality Control is an important step in manufacturing machined parts, especially complex, customized parts for safety critical systems such as airplane engines. Visual Inspection by humans is one of the modalities used for this purpose, but it is limited in many ways. Inspectors need months of training, need to maintain tremendous focus for a long duration, and are required to keep up with the growing pace of manufacturing. It is thus imperative to automate this process. This article proposes a flexible automated path planning framework which can be adapted to any robot, which implements a mesh segmentation algorithm and attempts to generalize the custom solution. The paper describes elements of the solution, and evaluates its efficacy pertaining to geometries of parts with characteristics similar to components found in aerospace. Furthermore, this article explores a potential improvement to the automated inspection process.
Virtual Sensing by Dense Encoder for Process Signals in Resistance Spot Welding
Authors: Kershaw Joseph , Wang Peng , Ghassemi-Armaki Hassan , Carlson Blair E. 
Published: August 2024

Abstract
Resistance Spot Welding (RSW) is one of the largest automated manufacturing processes in industry, consequently making it also one of the most researched. While this ubiquity has led to advancements in the consistency of this process, RSW is innately uncertain due to the high degree of interplaying mechanics that occur during the process. Additionally, to ensure the quality of a completed weld empirically, expensive analysis tools are required to inspect the result. One solution to removing this monetary and temporal cost is in-line process monitoring. During the weld, various signals can be measured and evaluated to predict the weld quality in real-time. The most common signal to measure is the Dynamic Resistance (DR) due to its ease of sensor implementation and richness of information. Other common signals are the electrode force and displacement. These give a more inclusive look into the overall process, especially the mechanical aspects, but these are typically limited to lab settings due to the increased cost of deploying them at scale. One solution to realize the insight of these other process signals on the factory floor is to utilize Machine Learning techniques to create virtual sensors that convert extant sensing data to other domains. This would allow for more robust and interpretable signal processing without incurring additional costs or downtime.
Prediction of Blind via Hole Quality Based on Stacking Ensemble Learning for Laser Drilling Condition of Printed Circuit Boards
Authors: Soma Nowatari , Masao Nakagawa , Toshiki Hirogaki , Eiichi Aoyama 
Published: August 2024

Abstract
In laser drilling, the appropriate laser parameters must be specified to obtain the desired machined hole. Therefore, the effects of process variables on the machined-hole parameters must be investigated and a method for constructing the optimum irradiation condition search must be devised. In this study, we establish a method to predict machined-hole parameters based on artificial intelligence (AI) using the process variables after investigating the parameter distribution of machined holes created via laser drilling. Using this method, the shape of the resulting machined hole can be determined prior to machining. Furthermore, applying the results of this study allows one to determine the irradiation conditions, which consequently enables the identification of process variables that satisfy the required hole parameters and machining quality.
First, the effects of the pulse width and pulse spacing of multiple pulses on machined-hole parameters were investigated. The parameter distribution of the machined-hole diameter was evaluated using the response-surface method by varying the pulse width of a CO2 laser. The result shows that the parameter distribution of the machined-hole diameter varied significantly under different pulse widths. Next, we propose an AI-based method for predicting machined-hole parameters using process variables on a small dataset. The proposed method reduces the prediction error of machined-hole parameters by feeding back the prediction results to the hole-opening process based on laser irradiation via stacking, which is one of the ensemble methods of AI models in the prediction model. By introducing this method, we confirmed that the prediction error was smaller compared with the case when AI was designed to perform prediction using process variables. Furthermore, the stacking was validated using a model comprising ideal data, which is not suitable for actual operation as the measured machined-hole parameters are used as input data during the validation.