bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spinal motor neuron development and metabolism are transcriptionally regulated by Nuclear Factor IA
Authors: Gauberg Julia , Moreno Kevin B. , Jayaraman Karthik , Abumeri Sara , Jenkins Sarah , Salazar Alisa M. , Meharena Hiruy S , Glasgow Stacey M 
Published: June 2024

SUMMARYNeural circuits governing all motor behaviors in vertebrates rely on the proper development of motor neurons and their precise targeting of limb muscles. Transcription factors are essential for motor neuron development, regulating their specification, migration, and axonal targeting. While transcriptional regulation of the early stages of motor neuron specification is well-established, much less is known about the role of transcription factors in the later stages of maturation and terminal arborization. Defining the molecular mechanisms of these later stages is critical for elucidating how motor circuits are constructed. Here, we demonstrate that the transcription factor Nuclear Factor-IA (NFIA) is required for motor neuron positioning, axonal branching, and neuromuscular junction formation. Moreover, we find that NFIA is required for proper mitochondrial function and ATP production, providing a new and important link between transcription factors and metabolism during motor neuron development. Together, these findings underscore the critical role of NFIA in instructing the assembly of spinal circuits for movement.
Validation of electron-microscopy maps using solution small-angle X-ray scattering
Authors: Lytje Kristian , Pedersen Jan Skov 
Published: June 2024

The determination of the atomic resolution structure of biomacromolecules is essential for understanding details of their function. Traditionally, such a structure determination has been performed with crystallographic or nuclear resonance methods, but during the last decade, cryogenic transmission electron microscopy (cryo-TEM) has become an equally important tool. As the blotting and flash-freezing of the samples can induce conformational changes, external validation tools are required to ensure that the vitrified samples are representative of the solution. Although many validation tools have already been developed, most of them rely on fully resolved atomic models, which prevents early screening of the cryo-TEM maps. Here, a novel and automated method for performing such a validation utilizing small-angle X-ray scattering measurements, publicly available through the new software package AUSAXS, is introduced and implemented. The method has been tested on both simulated and experimental data, where it was shown to work remarkably well as a validation tool. The method provides a dummy atomic model derived from the EM map which best represents the solution structure.
Discovering students' continuous intentions to use ChatGPT in higher education: a tale of two theories
Authors: Tan Christine Nya-Ling , Tee Mcxin , Koay Kian Yeik 
Published: June 2024

PurposeThis study investigates the factors affecting university students’ intentions to continuously use ChatGPT by integrating the UTAUT3 (Unified Theory of Acceptance and Use of Technology) and ISS (Information Systems Success) theories.Design/methodology/approachBy using self-reported questionnaires, 388 usable data from university students in Malaysia were analysed using partial least squares structural equation modelling.FindingsThe results indicate that hedonic motivation, habit, and facilitating conditions significantly impact students’ continuous intentions to utilise ChatGPT. Furthermore, system quality, information quality, service quality, and conversational quality significantly influence students’ ChatGPT satisfaction. Crucially, satisfaction is a critical factor in continuous intention to utilise ChatGPT.Originality/valueThis research integrates UTAUT3 and ISS theories to understand factors influencing university students’ satisfaction with continuous intentions to use ChatGPT, filling the gap in previous studies that have focused on these theories separately.
Presenting a model for enhancing the performance of sustainable supply chain management using a data-driven approach
Authors: Bagherpasandi Masoud , Salehi Mahdi , Hajiha Zohreh , Hejazi Rezvan 
Published: June 2024

PurposeThis paper aims to determine the key factors and provide an effective model to enhance the performance of sustainable supply chain management (SSCM).Design/methodology/approachData were collected using a semi-structured interview technique, a snowball sampling method and qualitative study method. For this purpose, ten supply chain and food production managers and experts were interviewed semi-structured. The data were analyzed using open, central and selective coding methods with grounded theory approach. In the proposed model, 13 principal codes have been specified, including organizational productivity, sustainable supply chain (SSC), industry supply chain, macro policies, organizational performance, social factors, economic factors, organizational factors, political factors, technology, manufactured products, customer and supply chain failures.FindingsThe model and concepts obtained from the participants clearly show that several reasons and motivations are involved in increasing the performance of SSCM. Moreover, the designed model indicates that the motives and reasons for turning to this system are satisfactory when implemented.Originality/valueThe distinctive and knowledge-enhancing feature of this paper compared to previous studies is the focus on the selected background, intervening and causal factors with the influence of strategies designed to achieve a new and local model for the SSC model and assess its impact on organizational performance and productivity. The proposed components of this paper have not been investigated so far.
Adopting Industry 4.0 through absorptive capacity and innovation ambidexterity with the moderation of learning capability
Authors: Hashem Gharib 
Published: June 2024

PurposeBased on a quantitative investigation, this paper endeavors to examine Industry 4.0 (I4.0) adoption process by studying the impacts of absorptive capacity (AC) and innovative ambidexterity (exploration, exploitation), while also considering the moderating influence of learning capability (LC).Design/methodology/approachData has been gathered through administering questionnaire to 468 managers representing 175 manufacturing firms. Subsequently, PLS-SEM technique has been employed to verify the research hypotheses.FindingsStudy findings reveal that AC is significantly associated with I4.0 adoption and innovation ambidexterity. However, innovation ambidexterity demonstrates partial (only exploration) significant association with the adoption of I4.0. Similarly, the findings indicate that LC acts as a partial moderator between innovation ambidexterity (exploration) and I4.0 adoption.Research limitations/implicationsThe study presents significant insights into I4.0 adoption process. The findings may support managers of manufacturing firms to understand and assess the influence of integrating contextual factors facilitating successful adoption of I4.0. The study emphasizes necessity of managers’ awareness regarding the importance of firm’s AC to transform smoothly to I4.0 technologies. In addition to, encouraging the innovation ambidexterity along with LC to enhance the adoption of I4.0.Originality/valueWhile researchers demonstrate increasing interest in applying I4.0, concrete evidence to support the I4.0 adoption process is, still, insufficient due to ongoing challenges in digital transformation. Consequently, further research is needed, particularly in exploring how a firm’s ability to realize knowledge and foster innovation contributes to implementing I4.0. This paper seeks to tackle this lack of research by examining the connection between AC, innovation ambidexterity, and LC and the adoption of I4.0 in an emerging economy.
A warehousing dilemma: where do I store the material?
Authors: Desai Sumanth Pramod , Pare Sushil , Hanji Sanjay , Munshi M.M. 
Published: June 2024

Learning outcomes
After completion of the case study, the students will be able to appraise the importance of different methods of location planning in warehouse selection, analyze the load distance values for warehouse location and choose the optimum location based on the load distance analysis.

Case overview/synopsis
DB Builders, a prominent Indian construction company, faced a crucial decision in selecting an ideal storage warehouse for a project involving 100 flats spread across five locations. Mr Vijay Kumar, an experienced material handling expert, was entrusted with this task as part of transitioning the company’s material allocation system toward centralization. Using practical travel distances, Kumar meticulously scouted four potential warehouse locations. The selection process hinged on three primary factors: load, distance to apartment sites, safety and cost of the premises, each carrying specific weightage. The project planning department provided scores for safety and cost, helping evaluate the options. This unique challenge arises due to varying material requirements across the apartment locations, demanding an efficient warehouse planning. The selection of the optimal storage warehouse holds paramount importance in facilitating the smooth execution of these larger projects. Kumar’s expertise and strategic decision-making are pivotal in ensuring a seamless transition toward centralized material handling, which is essential for the company’s future success.

Complexity academic level
This teaching activity is aimed at introductory/basic courses in Bachelors and Masters of Business administration.

Supplementary materials
Teaching notes are available for educators only.

Subject code
CSS 9: Operations and Logistics.
Career agency and person-environment fit: female globally mobile employees in Japan
Authors: Qin Jiayin , Sekiguchi Tomoki 
Published: June 2024

Purpose
This study aims to understand how female globally mobile employees (GMEs), a group that is gaining a stronger presence in global work, exert their career agency within the context of structural constraints.

Design/methodology/approach
Using theoretical perspectives of career-agency theory and person-environment fit as frames of reference, this study collected 113 blog posts written by 19 female GMEs and conducted semi-structured interviews with 11 female GMEs who are currently living and working in Japan.

Findings
This study found that the informants exercised career agency as a response to challenges related to foreignness and gender. Through career-related agentic behaviors, the informants strove to increase their fit with their environments while interacting with different aspects of structural constraints. This study also found that people in different stages of global mobility exhibited different mindsets toward their foreignness, consequently influencing their career agency.

Originality/value
This study highlights the dynamic interaction between structural constraints and the agency of female GMEs, advancing the understanding of career agency in women’s global work. In addition, it recognizes the presence of expatriate residents as a distinct subgroup within the GME population, shedding light on the evolving ambiguous boundaries between self-initiated expatriates and other talent categories.
A novel ChatGPT-based multimodel framework for tourism review mining: a case study on China’s five sacred mountains
Authors: Cheng Xinquan , Chen Yuanhong , Wang Pingfan , Zhou YanXi , Wei Xiaojing , Luo Wenjiang , Duan Qingxin 
Published: June 2024

Purpose
This study aims to introduce an innovative framework for mining tourism reviews that not only excels in sentiment analysis accuracy but also prioritizes user-friendly design for enhanced usability.

Design/methodology/approach
Online reviews of China’s Five Sacred Mountains were analyzed using an integrated methodology. Sentiment analysis was performed using ChatGPT, bidirectional encoder representations from transformers (BERT) and convolutional neural networks, with ChatGPT demonstrating superior performance. Latent Dirichlet allocation extracted key attributes. Models including importance–performance analysis (IPA), asymmetric impact-performance analysis (AIPA) and importance–performance competitor analysis (IPCA) then synthesized findings.

Findings
The results demonstrate that ChatGPT outperforms both machine learning and lexicon-based models in sentiment recognition, exhibiting performance comparable to that of the BERT model. In the case study, integrating sentiment analysis outcomes with IPA reveals deficiencies in both topics and attributes. Moreover, the synergistic combination of IPA, AIPA and IPCA furnishes actionable recommendations for resource management and enables nuanced monitoring of sustainability attributes.

Practical implications
Leveraging this framework in conjunction with the ChatGPT platform for application development can bring practical convenience to the tourism industry. It supports sentiment analysis, topic categorization and opinion mining. Equipped with monitoring capabilities, it provides valuable insights for sustainable improvement, aiding managers in formulating effective marketing strategies.

Originality/value
This research develops a novel multimodel framework integrating various ML/DL techniques and business models in a synergistic way. It provides an innovative and highly accurate yet simple approach to tourism review mining and enhances accessibility of advanced artificial intelligence for sustainable tourism monitoring, addressing limitations of prior methods.
Dynamic grey relational analysis-based optimization of electrochemical machining processes
Authors: Das Partha Protim , Chakraborty Shankar 
Published: June 2024

Purpose
Grey relational analysis (GRA) has already proved itself as an efficient tool for multi-objective optimization of many of the machining processes. In GRA, the distinguishing coefficient (ξ) plays an important role in identifying the optimal parametric combinations of the machining processes and almost all the past researchers have considered its value as 0.5. In this paper, based on past experimental data, the application of GRA is extended to dynamic GRA (DGRA) to optimize two electrochemical machining (ECM) processes.

Design/methodology/approach
Instead of a static distinguishing coefficient, this paper considers dynamic distinguishing coefficient for each of the responses for both the ECM processes under consideration. Based on these coefficients, the application of DGRA leads to determination of the dynamic grey relational grade (DGRG) and grey relational standard deviation (GRSD), helping in initial ranking of the alternative experimental trials. Considering the ranks obtained by DGRG and GRSD, a composite rank in terms of rank product score is obtained, aiding in final rankings of the experimental trials for both the ECM processes.

Findings
In the first example, the maximum material removal rate (MRR) would be obtained at an optimal combination of ECM parameters as electrolyte concentration = 2 mol/l, voltage = 16V and current = 4A, while another parametric intermix as electrolyte concentration = 2 mol/l, voltage = 14V and current = 2A would result in minimum radial overcut and delamination. For the second example, an optimal combination of ECM parameters as electrode temperature = 30°C, voltage = 12V, duty cycle = 90% and electrolyte concentration = 15 g/l would simultaneously maximize MRR and minimize surface roughness and conicity.

Originality/value
In this paper, two ECM operations are optimized using a newly developed but yet to be popular multi-objective optimization tool in the form of the DGRA technique. For both the examples, the derived rankings of the ECM experiments exactly match with those obtained by the past researchers. Thus, DGRA can be effectively adopted to solve parametric optimization problems in any of the machining processes.
Application of new rock physics method to estimate petrophysical properties
Authors: Shadlow James 
Published: June 2024

AbstractA new method for estimating petrophysical properties from elastic well log or seismic data is evaluated on data from the Carnarvon Basin, Northwest Australia. The study has utilized well and seismic inversion data covering part of the Triassic‐aged fluvio‐deltaic Mungaroo Formation on the Exmouth Plateau. The method applied is based on several recently published papers to use acoustic impedance, velocity ratio Vp/Vs and estimated constants to calculate clay volume (VCL), effective porosity and water saturation (SW). The case study showed exceptional results on well data. A strong match is observed between petrophysically derived VCL, effective porosity and SW and the estimates derived from elastic logs. When applied to seismic inversion volumes, pay in the wells is predicted from seismic, and porosity of the sands can be estimated with confidence. Petrophysical properties for nearby direct hydrocarbon indicator–supported prospects could also be evaluated, although an imprint of the direct hydrocarbon indicator was observed on the VCL prediction, and overall predictions are less than expected based on regional well results. Using these results, a minor modification is proposed to the equations used, and a workflow is derived to enable easy application to other projects. The modified approach was validated on the well data from the original publication. The results also indicate that the approach can be used to help identify erroneous synthetic Vs estimates in limited data settings.
Modeling the linkage between climate change, CH4 emissions, and land use with Iran's livestock production: A food security perspective
Authors: Mahdavian Seyed Mohammadreza , Askari Fatemeh , Kioumarsi Hamed , Naseri Harsini Reza , Dehghanzadeh Hushang , Saboori Behnaz 
Published: June 2024

AbstractThe livestock production sector plays a crucial role in food security and income generation and has an undeniable relationship with the environment. Like other agricultural sectors, it faces the significant challenge of climate change. However, the attention given to this issue has not been satisfactory given its importance. Thus, the primary aim of the current research is to assess the impact of temperature change, precipitation, CH4 emissions, gross fixed capital, and land use on the livestock production index as an indicator of food security in Iran. The modeling uses data from 1990 to 2020, employing the NARDL approach and Granger causality. The results show that a 1% increase in temperature can lead to an 8.06% decrease in livestock production (food security), while a 1% decline in temperature results in a 3.85% surge in livestock production. Precipitation has a direct relationship with food security; a 1% rise and drop in rainfall lead to an increase and reduction in livestock production by 0.8% and 1.02%, respectively. A 1% increase in gross fixed capital boosts food security by 0.47%, while a 1% decrease leads to a 2.32% reduction. A statistically insignificant relationship is seen between the positive CH4 shock and food security in the long run. However, the negative shock of this variable positively influences food security by 7.5%. Negative changes in land use will reduce livestock production. The Granger causality test proves a two‐way causal relationship between CH4 emissions and livestock production. A unidirectional causality is discovered from production to temperature and from land use to livestock production. To mitigate the impact of global warming on livestock production, strategic investments in infrastructure, livestock micro insurance, and informing producers about the consequences of climate change and solutions for addressing this phenomenon can be considered effective policies.
Productive and physiological characteristics of tomato plants produced on different rootstocks
Authors: de Jesus Tello Jean Paulo , de Almeida Guimarães Marcelo , dos Santos Viana Caris , Garcia Manuel Filipe Nascimento , Gomes João Germano , Mesquita Rosilene Oliveira , Zanuncio José Cola 
Published: June 2024

AbstractGrafting facilitates the management of phytodiseases, especially of soils, but the growth and development of the grafted plant depend on the compatibility with rootstocks. The objective was to evaluate the graft union and survival, the growth characteristics, fruit biometrics, yield and physiological characteristics of the tomato plant ‘Santa Clara’ on five rootstocks. The study was conducted at the Pici Campus of the Federal University of Ceará in Fortaleza, Ceará state, Brazil. The seven treatments were tomato ‘Santa Clara’ ungrafted and self‐grafted, or grafted onto cherry tomato ‘Vermelho’, hybrid tomato ‘Guardiao’, eggplant ‘Comprida Roxa’, jiló ‘Comprido Grande Rio’ (Solanum gilo) and cocona (Solanum sessiliflorum). Cleft grafting was used. The growth characteristics evaluated were stem diameter (SD), plant height (PH), and number of commercial (NCF) and total (NTF) fruits. The biometric characteristics of the fruits (diameter‐FD, length‐FL and average mass‐AMF) and productive (commercial‐CFM and total‐TFM fruit mass) and yield of commercial (YCF) and total (YTF) fruits were estimated per hectare. Physiological evaluations were performed to obtain the internal concentration of CO2 (Ci), transpiration rate (E), stomatal conductance (Gs), liquid photosynthesis (A), ratio between internal CO2 and the environment (Ci/Ca) and carboxylation efficiency (A/Ci). The graft union and survival of S. lycopersicum plants was 100% at 10 days after grafting. The number of commercial and total fruits were higher in non‐grafted tomato plants. The FD of the plants was higher with rootstocks of the ‘Vermelho’ cherry tomato and ‘Guardião’ hybrid, the CFM and TFM with ungrafted, the AMF and TFM with ‘Vermelho’ cherry tomato and the YCF and YTF with ungrafted and grafting on the ‘Vermelho’ cherry tomato. The tomato plant ‘Santa Clara’ completed its development in rootstocks and, therefore, they are compatible with this plant. The production of tomato fruits was higher with grafting on the ‘Vermelho’ cherry tomato with diameter and productivity similar to those of the ungrafted plants, indicating that this tomato cultivar can be used as rootstock.
The pharmacokinetic differences between 10‐ and 15‐μg daily vitamin D doses
Authors: You Tao , Muhamad Nadda , Jenner Joseph , Huang Zhonghui 
Published: June 2024

AimsThe reference nutrient intake for vitamin D in people aged ≥4 years is 10 μg/day (400 IU/day) in the UK, but the recommended daily allowance is 15 μg/day (600 IU/day) for people aged 1–70 years in the USA. Here, we aim to compare the 25‐hydroxyvitamin D (25(OH)D) serum concentration profiles between the 2 doses.MethodsWith world‐wide trial data of adults aged ≥18 years, 45–93 kg, we constructed a minimal physiologically based pharmacokinetics model of serum concentrations of vitamin D and 25(OH)D using nonlinear mixed effects modelling. We used this model to forecast the mean, 2.5th and 97.5th percentiles for serum 25(OH)D concentrations in British adults aged ≥16 years.ResultsOur final model used bodyweight to adjust volume of each compartment and maximum clearance of 25(OH)D. No other covariate was identified. The model accurately predicted independent data from trials of a broad range of dosing regimens. We simulated British adults and showed that circulating 25(OH)D concentrations in 95% of people taking 10 μg/day for a year is predicted to reach 50 nmol/L in 32 weeks, while 97.5% of those on 15 μg/day were predicted to attain this threshold within 28 weeks.ConclusionBoth doses are efficacious in >95% of the British population. The daily dose of 15 μg can help 97.5% of the British adults achieve 50 nmol/L serum 25(OH)D and reach the 25 nmol/L threshold in 4 weeks.