bluuebunny/crossref_metadata_2025 huggingface dataset:
Ripened plant-based cheese analogs in Europe: nutritional and microbial profiles
Authors: Jaeger Isabela , Köhn Cecília R. , Evans Joshua D. , Frazzon Jeverson , Renault Pierre , Kothe Caroline Isabel
Published: April 2024

Plant-based cheese analogs have emerged as a novel global market trend driven by sustainability concerns for our planet. This study examines eleven soft ripened plant-based cheese analogs produced in Europe, primarily with bloomy rinds and cashew nuts as the main ingredient. First, we focused on exploring the macronutrients and salt content stated on the labels, as well a detailed fatty acid analysis of the samples. Compared to dairy cheeses, plant-based cheeses share similarities in lipid content, but their fatty acid profiles diverge significantly, with higher ratio of mono- and polyunsaturated fatty acids such as oleic and linoleic acids. We also investigated the microbiota of these analog products, employing a culture-dependent and -independent approaches. We identified a variety of microorganisms in the plant-based cheeses, withLactococcus lactisandLeuconostoc mesenteroidesbeing the dominant bacterial species, andGeotrichum candidumandPenicillium camembertithe dominant fungal species. Most of the species characterized are similar to those present in dairy cheeses, suggesting that they have been inoculated as culture starters to contribute to the sensorial acceptance of plant-based cheeses. However, we also identify several species that are possibly intrinsic to plant matrices or originate from the production environment, such asPediococcus pentosaceusandEnterococcusspp. This coexistence of typical dairy-associated organisms with plant associated species highlights the potential microbial dynamics inherent in the production of plant-based cheese. These findings will contribute to a better understanding of plant-based cheese alternatives, enable the development of sustainable products, and pave the way for future research exploring the use of plant-based substrates in the production of cheese analogues.
Machine learning driven image segmentation and shape clustering of algal microscopic images obtained from various water types
Authors: Nelli Filippo , Ge Zongyuan , Blackall Linda , Taheriashtiani Negar , Henry Rebekah , Brumley Douglas R. , Grace Michael , Jex Aaron , Burch Michael , Lin Tsair-Fuh , Bertelkamp Cheryl , Willis Anusuya , Gao Li , Schmidt Jonathan , Crosbie Nicholas D. , Zamyadi Arash
Published: April 2024

Algae and cyanobacteria are microorganisms found in almost all fresh and marine waters, where they can pose environmental and public health risks when they grow excessively and produce blooms. Accurate identification and quantification of these microorganisms are vital for ecological research, water quality monitoring, and public health safety. However, traditional methods of manually counting and morphologically identifying these microorganisms are time-consuming and prone to human error. Application of the machine learning-driven Fast Segment Anything Model (FastSAM), an image segmentation model, automates and potentially enhances the accuracy and efficiency of cell identification and enumeration from microscopic images. We assessed FastSAM for algal cell image segmentation, and three clustering evaluation metrics. Segmentation of microscopic images of algal and cyanobacterial cells in water and treated wastewater samples using the Convolutional Neural Network based FastSAM algorithm demonstrated benefits and challenges of this machine learning-driven image processing. Notably, the pre-trained algorithm segmented entire elements in all microscopic images used in this study. Depending on the shape, 50-100% similarity was observed between machine-based segmentation and manual validation of all segmented elements, with 100% of single cells being correctly segmented by FastSAM. The performance of clustering metrics varied between 57-94% with the Spectral Angle Mapper achieving the most accurate performance, 84-94%, compared to the manually chosen clustering benchmarks. Cyanobacterial and algal communities are biologically diverse and have ecological significance. The application of image clustering techniques in studying their cell shapes marks an important advancement in microbial ecology and environmental monitoring. As technology progresses, these methods will become increasingly utilised to decipher the complex roles that algae and cyanobacteria play in our ecosystems supporting mitigation and public health protection measures.
AutoGaitA – Automated Gait Analysis in Python
Authors: Hosseini M. , Klein I. , Kuzu T. D. , Semmler C. , Wunderle V. , Mardare V. , Galvao A. , Haustein M. , Büschges A. , Grefkes C. , Korotkova T. , Fink G. R. , Weiss P. H. , Gatto G. , Daun S.
Published: April 2024

Animals change their location in space by means of walking, running, swimming, or flying, a series of rhythmic motor behaviours that together are defined as locomotion. Individual types of locomotion require a unique coordinated pattern of muscle contractions that can be inferred by the location of joints across the body. Implementations of recent advancements in machine learning (ML), such as DeepLabCut and Simi Shape, have automated the tracking of body posture, even in markerless subjects. Despite ML algorithms alleviating the tracking effort, making sense of the tracked points still requires substantial amounts of manual labour and lacks standardisation across research labs. To this end, we developedAutoGaitA(Automated Gait Analysis), an open-source Python toolbox designed to automate the analysis of locomotion by normalising the step cycle, extracting meaningful features from the tracked coordinates (e.g. angles, velocity, acceleration) and allowing intra- and inter-animal comparisons. Here, we employedAutoGaitAin a series of proof of principles experiments to show age-dependent changes in locomotion in flies, mice and humans, age-dependent changes in adaptation mechanisms in mice, and to compare the key features of walking across species.AutoGaitA’s adaptability to any kind of motor behaviour and any species of interest makes it a valuable tool for the motor community to standardise the analysis of rhythmic behaviours across genotypes, disease states and species.
AutoGDC: A Python Package for DNA Methylation and Transcription Meta-Analyses
Authors: Brown Chase Alan , Wren Jonathan D.
Published: April 2024

Abstract

0.1

Motivation

The Genomic Data Commons is a powerful resource which facilitates the exploration of molecular alterations across various diseases. However, utilizing this resource for meta-analysis requires many different tools to query, download, organize, and analyze the data. In order to facilitate a more rapid, simple means of analyzing DNA methylation and RNA sequencing datasets from the GDC we developedautogdc, a python package that integrates data curation and preprocessing with meta-analysis functionality into one simplified bioinformatic pipeline.

0.2

Availability and Implementation

Theautogdcpython package is available under the GPLv3 license at along with several examples of typical use-case scenarios in the form of a jupyter notebook. The data is all originally provided by the GDC, and is therefore available under the NIH Genomic Data Sharing (GDS) and NCI GDS policies.
Potential Opportunities of Modeling Bioavailability for Monoclonal Antibodies: An Overview of mAbs and the current challenges of mAb development
Authors: Kohli Aryan , Fayaz Omar , Jensen Alexandra Y. , Chung Christian , Korban Christopher
Published: April 2024

With a growing market size, and a large variety of applications, monoclonal antibody technology adoption and clinical usage is at an all-time high. This review article seeks to explore 10 monoclonal antibodies (mAbs) and their mechanism of action, specifically their pharmacodynamic (PD) and pharmacokinetic (PK) properties, and use a machine learning model with various parameters to assess whether the mAb has adequate bioavailability when delivered subcutaneously. This is an investigation of drug optimization and patient outcomes when transitioning from traditional IV administrations to subcutaneous injections. The machine learning model is an extension based on a paper by Han Lou and Michael Hageman,Machine Learning Attempts for Predicting Human Subcutaneous Bioavailability of Monoclonal Antibodies, where they took 10 mAbs and analyzed 45 different features. To further extend this paper, we took an additional 10 monoclonal antibodies that were delivered subcutaneously, and took into account their dosage concentration as an extension to traditional PK properties. By including additional mAbs and dosage, a more sophisticated model can be produced with high scalability to deep learning modalities.
Exploring Metabolic Anomalies in COVID-19 and Post-COVID-19: A Machine Learning Approach with Explainable Artificial Intelligence
Authors: Oropeza-Valdez Juan José , Padron-Manrique Cristian , Vázquez-Jiménez Aarón , Soberon Xavier , Resendis-Antonio Osbaldo
Published: April 2024

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms known as Long COVID or Post-COVID-19 syndrome. Emerging evidence suggests a crucial role of metabolic reprogramming in the infection’s long-term consequences. This study employs a novel approach utilizing machine learning (ML) and explainable artificial intelligence (XAI) to analyze metabolic alterations in COVID-19 and Post-COVID-19 patients. By integrating ML with SHAP (SHapley Additive exPlanations) values, we aimed to uncover metabolomic signatures and identify potential biomarkers for these conditions. Our analysis included a cohort of 142 COVID-19, 48 Post-COVID-19 samples and 38 CONTROL patients, with 111 identified metabolites. Traditional analysis methods like PCA and PLS-DA were compared with advanced ML techniques to discern metabolic changes. Notably, XGBoost models, enhanced by SHAP for explainability, outperformed traditional methods, demonstrating superior predictive performance and providing different insights into the metabolic basis of the disease’s progression and its aftermath, the analysis revealed several metabolomic subgroups within the COVID-19 and Post-COVID-19 conditions, suggesting heterogeneous metabolic responses to the infection and its long-term impacts. This study highlights the potential of integrating ML and XAI in metabolomics research.
ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention
Authors: Li Mingchen , Tan Pan , Ma Xinzhu , Zhong Bozitao , Yu Huiqun , Zhou Ziyi , Ouyang Wanli , Zhou Bingxin , Hong Liang , Tan Yang
Published: April 2024

Protein language models (PLMs) have shown remarkable capabilities in various protein function prediction tasks. However, while protein function is intricately tied to structure, most existing PLMs do not incorporate protein structure information. To address this issue, we introduce ProSST, a Transformer-based protein language model that seamlessly integrates both protein sequences and structures. ProSST incorporates a structure quantization module and a Transformer architecture with disentangled attention. The structure quantization module translates a 3D protein structure into a sequence of discrete tokens by first serializing the protein structure into residue-level local structures and then embeds them into dense vector space. These vectors are then quantized into discrete structure tokens by a pre-trained clustering model. These tokens serve as an effective protein structure representation. Furthermore, ProSST explicitly learns the relationship between protein residue token sequences and structure token sequences through the sequence-structure disentangled attention. We pre-train ProSST on millions of protein structures using a masked language model objective, enabling it to learn comprehensive contextual representations of proteins. To evaluate the proposed ProSST, we conduct extensive experiments on the zero-shot mutation effect prediction and several supervised downstream tasks, where ProSST achieves the state-of-the-art performance among all baselines. Our code and pretrained models are publicly available2.
Recurrent Interneuron Connectivity does not Support Synchrony in a Biophysical Dentate Gyrus Model
Authors: Müller-Komorowska Daniel , Fujishige Temma , Fukai Tomoki
Published: April 2024

Synchronous activity of neuronal networks is found in many brain areas and correlates with cognition and behavior. Gamma synchrony is particularly strong in the dentate gyrus, which is thought to process contextual information in the hippocampus. Several network mechanisms for synchrony generation have been proposed and studied computationally. One such mechanism relies solely on recurrent inhibitory interneuron connectivity, but it requires a large enough number of synapses. Here, we incorporate connectivity data of the dentate gyrus into a biophysical computational model to test its ability to generate synchronous activity. We find that recurrent interneuron connectivity is insufficient to induce a synchronous network state. This applies to an interneuron ring network and the broader dentate gyrus circuitry. In the asynchronous state, recurrent interneuron connectivity can have small synchronizing effects but can also desynchronize the network for specific types of synaptic input. Our results show that synchronizing mechanisms relying solely on interneurons are unlikely to be biologically plausible in the dentate gyrus.
Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium
Authors: Hecker Nikolai , Kempynck Niklas , Mauduit David , Abaffyová Darina , Vandepoel Roel , Dieltiens Sam , Sarropoulos Ioannis , Bravo González-Blas Carmen , Leysen Elke , Moors Rani , Hulselmans Gert , Lim Lynette , De Wit Joris , Christiaens Valerie , Poovathingal Suresh , Aerts Stein
Published: April 2024

Combinations of transcription factors govern the identity of cell types, which is reflected by enhancer codes in cis-regulatory genomic regions. Cell type-specific enhancer codes at nucleotide-level resolution have not yet been characterized for the mammalian neocortex. It is currently unknown whether these codes are conserved in other vertebrate brains, and whether they are informative to resolve homology relationships for species that lack a neocortex such as birds. To compare enhancer codes of cell types from the mammalian neocortex with those from the bird pallium, we generated single-cell multiome and spatially-resolved transcriptomics data of the chicken telencephalon. We then trained deep learning models to characterize cell type-specific enhancer codes for the human, mouse, and chicken telencephalon. We devised three metrics that exploit enhancer codes to compare cell types between species. Based on these metrics, non-neuronal and GABAergic cell types show a high degree of regulatory similarity across vertebrates. Proposed homologies between mammalian neocortical and avian pallial excitatory neurons are still debated. Our enhancer code based comparison shows that excitatory neurons of the mammalian neocortex and the avian pallium exhibit a higher degree of divergence than other cell types. In contrast to existing evolutionary models, the mammalian deep layer excitatory neurons are most similar to mesopallial neurons; and mammalian upper layer neurons to hyper- and nidopallial neurons based on their enhancer codes. In addition to characterizing the enhancer codes in the mammalian and avian telencephalon, and revealing unexpected correspondences between cell types of the mammalian neocortex and the chicken pallium, we present generally applicable deep learning approaches to characterize and compare cell types across species via the genomic regulatory code.
Assessment of the level of pollution based on soil andTilia × europaealeaves
Authors: Simon Edina , Bin Ismail Haziq , Sipos Bianka , Abriha-Molnár Vanda Éva , Abriha Dávid , Tőzsér Dávid , Sajtos Zsófi , Boluda Rafael , Roca-Pérez Luis
Published: April 2024

Anthropic activities related to urbanization release pollutants, including potentially toxic elements, into the atmosphere and these are eventually deposited in soils, water, infrastructures, vegetation. Urban soil and plant leaves are widely used as ecological indicators to assess the effect of urbanization. This study aimed to evaluate the impact of urbanization based on the elemental concentration of soil and leaves ofTilia × europaeafrom urban, suburban, and rural areas along an urbanization gradient in Debrecen, Hungary. Using the ICP-OES technique, we measured the concentration of Ba, Cd, Co, Cr, Cu, Ni, Pb, Sr, and Zn and based on the measured concentration, bioaccumulation factor (BAF) was calculated. The highest concentration of all elements was found in soil samples from urban areas, with an increasing tendency along the urbanization gradient. A significant difference was found along the urbanization gradient only for Cr based on the plant leaves.T. × europaeashowed bioaccumulation capacity for Cr and Sr. Our results suggest that urbanization has a remarkable effect on the elemental concentration of soil, which is a perfect ecological indicator. At the same time, we concluded that theT. × europaeawas not sensitive enough to indicate the effect of urbanization.
Beyond oscillations - A novel feature space for characterizing brain states
Authors: Balestrieri Elio , Chalas Nikos , Stier Christina , Fehring Jana , Ávila Cristina Gil , Dannlowski Udo , Ploner Markus , Gross Joachim
Published: April 2024

Our moment-to-moment conscious experience is paced by transitions between states, each one corresponding to a change in the electromagnetic brain activity. One consolidated analytical choice is to characterize these changes in the frequency domain, such that the transition from one state to the other corresponds to a difference in the strength of oscillatory power, often in pre-defined, theory-driven frequency bands of interest. Today, the huge leap in available computational power allows us to explore new ways to characterize electromagnetic brain activity and its changes.

Here we leveraged an innovative set of features on an MEG dataset with 29 human participants, to test how these features described some of those state transitions known to elicit prominent changes in the frequency spectrum, such as eyes-closed vs eyes-open resting-state or the occurrence of visual stimulation. We then compared the informativeness of multiple sets of features by submitting them to a multivariate classifier (SVM).

We found that the new features outperformed traditional ones in generalizing states classification across participants. Moreover, some of these new features yielded systematically better decoding accuracy than the power in canonical frequency bands that has been often considered a landmark in defining these state changes. Critically, we replicated these findings, after pre-registration, in an independent EEG dataset (N=210).

In conclusion, the present work highlights the importance of a full characterization of the state changes in the electromagnetic brain activity, which takes into account also other dimensions of the signal on top of its description in theory-driven frequency bands of interest.
Complementing Muscle Regeneration: Fibro-Adipogenic Progenitor and Macrophage-Mediated Repair of Elderly Human Skeletal Muscle
Authors: Brorson Jonas , Lin Lin , Wang Jakob , Billeskov Tine Borum , Just Jesper , Haskó János , Ravn Christen , Hansen Rehne L. , Bue Mats , Luo Yonglun , Jessen Niels , Farup Jean
Published: April 2024

The capacity to regenerate skeletal muscle function after injury requires a complex and well-coordinated cellular response. Here, we unravel the intricate dynamics of human skeletal muscle regeneration by combining spatial, temporal, and single cell transcriptomics. Using spatial RNA sequencing, we profiled the expression of human protein-coding genes in elderly human skeletal muscle biopsies before as well as 2-, 8-, and 30-days post injury. Single Cell-Spatial deconvolution analysis highlights monocytes/macrophages and fibro-adipogenic progenitors (FAPs) as pivotal players in human muscle regeneration. By utilizing flow cytometry and cell sorting we confirmed increased cellular content and activity during regeneration. Spatial correlation analysis unveils FAPs and monocytes/macrophages co-localization and intercellular communication, mediated by complement factor C3. Immunostaining confirms C3 expression in FAPs and FAP secretion of C3, suggesting a role in phagocytosis. Functional assays demonstrate C3’s impact on monocyte metabolism, survival and phagocytosis, unveiling its involvement in skeletal muscle regeneration. These insights elucidate FAP-macrophage interplay with perspectives for future therapeutic interventions.
Regional Diversity and Leaf Microbiome Interactions of the Fungal Maize PathogenExserohilum turcicumin Switzerland: A Metagenomic Analysis
Authors: Vidal-Villarejo Mireia , Dößelmann Bianca , Kogler Benedikt , Hammerschmidt Michael , Oppliger Barbara , Oppliger Hans , Schmid Karl
Published: April 2024

The spread and adaptation of fungal plant pathogens in agroecosystems are facilitated by environmental homogeneity. Metagenomic sequencing of infected tissues allows to monitor eco-evolutionary dynamics and interactions betwen host, pathogen and the plant microbiome.Exserohilum turcicum, the causal agent of northern corn leaf blight (NCLB) in maize, is distributed in multiple clonal lineages throughout Europe. To characterize regional pathogen diversity, we conducted metagenomic DNA sequencing on 241 infected leaf samples from the highly susceptible Swiss maize landrace Rheintaler Ribelmais, collected over three years (2016-2018) from an average of 14 agricultural farms within the Swiss Rhine Valley. All major European clonal lineages ofE. turcicumwere identified. Lineages differ by their mating types which indicates potential for sexual recombination and rapid evolution of new pathogen strains, although we found no evidence of recent recombination. The associated eukaryotic and prokaryotic leaf microbiome exhibited variation in taxonomic diversity between years and locations and is likely influenced by local weather conditions. A network analysis revealed distinct clusters of eukaryotic and prokaryotic taxa that correlates with the frequency ofE. turcicumsequencing reads, suggesting causal interactions. Notably, the yeast genusMetschnikowiaexhibited a strongly negative correlation, supporting its known potential as biological control agent against fungal pathogens. Our findings show that metagenomic sequencing is a useful tool for analyzing the role of environmental factors and potential pathogen-microbiome interactions in shaping pathogen dynamics and evolution, suggesting their potential for effective pathogen management strategies.
Hippocampal place cell sequences during a visual discrimination task: recapitulation of paths near the chosen reward site and independence from perirhinal activity
Authors: Marchesi P. , Bos J. , Vinck M. , Pennartz C.M.A.
Published: April 2024

Compressed hippocampal place-cell sequences have been associated with memory storage, retrieval and planning, but it remains unclear how they align with activity in the parahippocampal cortex. In a visuospatial discrimination task, we found a wide repertoire of hippocampal place cell sequences, which recapitulated paths across the task environment. Place cell sequences generated at reward sites predominantly reiterated trajectories near the chosen maze side, whereas trajectories associated with the side chosen in the previous trial were underrepresented. We hypothesized that neurons in the perirhinal cortex, which during the task display broad firing fields correlated with the animal’s location, might reactivate in concert with hippocampal sequences. However, we found no evidence of significant perirhinal engagement during virtual trajectories, indicating that these hippocampal memory-related operations can occur independently of the perirhinal cortex.
Factors influencing the evolution of information ecosystems: an institutional theory perspective
Authors: Lin Tung-Cheng , Yeh Mei-Ling
Published: April 2024

Purpose

The ecosystem concept has attracted attention in information system research to explain business competition, innovation and many other emerging phenomena. Existing studies focus more on a single ecosystem type or a single ecosystem goal and pay little attention to the ecosystem’s evolution. The objective of the study is to investigate the factors that impact the evolution of the information ecosystem (IE) to gain a better understanding of strategic thinking.

Design/methodology/approach

The IE involves many actors, so the multi-case study approach is conducted with purposeful sampling to recruit all the significant ecosystem actors. The collected qualitative data are analyzed by coding data, exploring data relationships and structuring pattern steps; institutional theory is used as a theoretical framework.

Findings

The results demonstrate that industry practices, laws and regulations, new actors and the mimetic pressure of outsourcers drive the growth of the ecosystem. Strategy intention, cost pressure and normative pressure all contribute to the IE’s evolution.

Originality/value

The concept of ecosystems has attracted attention in information system research. The study investigates the factors contributing to the evolution of the IE from an institutional theory perspective. Our suggestion is that new players can find a niche in offering information technology (IT)/ information services (IS)-related solutions to survive in the ecosystem; however, they need to pay attention to the normative pressure.
Subjective norms towards entrepreneurship and Malaysian students’ entrepreneurial intentions: does gender matter?
Authors: Chin Jia Wei , Mustafa Michael J , Nungsari Melati
Published: April 2024

Purpose

Adopting an institutional view of entrepreneurship, this study aims to explore the potential mediating role of entrepreneurial self-efficacy (ESE) in the relationship between subjective norms and the entrepreneurial intentions of Malaysian students. Additionally, social role theory (SRT) was used to examine whether gender acts as a boundary condition in the proposed relationship.

Design/methodology/approach

Empirical evidence was based on responses from 220 final-year students registered from a final-year entrepreneurship module at a private university in Malaysia. The hypothesised relationships were tested using Model 7 of the PROCESS macro.

Findings

The findings indicated that subjective norms had a weak but positive effect on the entrepreneurial intentions of Malaysian students. Moreover, ESE was found to mediate the relationship between subjective norms and entrepreneurial intentions. However, contrary to theoretical expectations, gender did not act as a boundary condition in the proposed mediation relationship.

Originality/value

By incorporating SRT with institutional theory, this study sought to address a knowledge gap in the existing literature by investigating and empirically exploring the moderating influence of gender on the mediating effect of ESE in the relationship between subjective norms and entrepreneurial intentions.
How to promote workplace inclusion? Needs and meanings through the lens of HR managers
Authors: Zaccone Maria Cristina , Pedrini Matteo
Published: April 2024

Purpose

Although the topic of inclusion has become a hot and unavoidable issue for organizations, research on how this topic is being addressed in companies is still almost nonexistent. How do HR managers promote workplace inclusion? The objective of this study is to answer this research question.

Design/methodology/approach

The results are based on evidence that emerged during in-depth interviews conducted with 16 human resources professionals from the world of large-scale retail trade, as well as from the analysis of documents and reports produced by the companies in which the interviewed professionals work.

Findings

The findings reveal that the promotion of corporate inclusion is not only aimed at satisfying the need for belongingness and uniqueness. It is also aimed at satisfying two other types of human needs, namely, the human need to share and the human need to be impactful. In addition, the results reveal that HR professionals promote workplace inclusion through six initiatives that can be traced to two main ways in which inclusion is conceived.

Originality/value

Even though there is an extensive number of studies aimed at defining and measuring the construct of workplace inclusion, progress has not been made in understanding how HR professionals promote inclusion. This study covers this literature gap by bringing to light the existence of two main meanings associated by HR professionals to workplace inclusion: extensive inclusiveness and narrow inclusiveness.
A landscape of practice approach to enhance employability: insights from domestic and international postgraduates
Authors: Soltani Behnam , Donald William E.
Published: April 2024

Purpose

Drawing on a theoretical framework of sustainable career ecosystem theory, our paper aims to consider how domestic and international postgraduates can enhance their employability through participation in a landscape of practice.

Design/methodology/approach

The study employed an exploratory, longitudinal case study design to capture students' lived experiences on an 18-month Master of Professional Practice course at a higher education institution in New Zealand. The data collection procedure involved field note observations (months 1–4), a focus group (month 13) and narrative frames (months 16–18). The sample was domestic students from New Zealand (n = 2) and international students from Asia (n = 5).

Findings

One’s participation in multiple communities of practice represents their landscape of practice and a commitment to lifewide learning. Through participation in various communities of practice, domestic and international students can enhance their employability in three ways: (1) boundary encounters to develop social capital, (2) transcending contexts to enhance cultural capital, and (3) acknowledging the development of psychological capital and career agency.

Originality/value

Our work offers one of the earliest empirical validations of sustainable career ecosystem theory. Expressly, communities of practice represent various contexts whereby employability capital is developed over time. Additionally, the postgraduate students themselves are portrayed as interconnected and interdependent actors, presenting a novel framing of such dependencies at the micro-level of the ecosystem. The practical implications come from informing universities of the value of a landscape of practice to enhance the employability of domestic and international students in preparation for sustainable careers and to promote the sustainability of the career ecosystem.
Social reputation, loan contracting and governance mechanisms
Authors: Kuzey Cemil , Hamrouni Amal , Uyar Ali , Karaman Abdullah S.
Published: April 2024

Purpose

This study aims to investigate whether social reputation via corporate social responsibility (CSR) awarding facilitates access to debt and decreases the cost of debt and whether governance mechanisms moderate this relationship.

Design/methodology/approach

The sample covers the period between 2002 and 2021, during which CSR award data were available in the Thomson Reuters Eikon/Refinitiv database. The empirical models are based on country, industry and year fixed-effects regression.

Findings

While the main findings produced an insignificant result for access to debt, they indicated strong evidence for the positive relationship between CSR awarding and the cost of debt. Moreover, the moderating effect highlights that while the sustainability committee helps CSR-awarded companies access debt more easily, independent directors help firms decrease the cost of debt via CSR awarding. Furthermore, the results differ between the US and the non-US samples, earlier and recent periods, high- and low-leverage firms and large and small firms.

Originality/value

For the first time, to the best of the authors’ knowledge, the authors assess whether social reputation via CSR awarding facilitates access to debt and decreases the cost of debt in an international and cross-industry sample. Little is known about the effect of social reputation on loan contracting, although social reputation conveys broader information that goes beyond the firm’s internal (performance) and external (reporting) CSR practices. The authors also draw attention to the differing roles of distinct governance mechanisms in leveraging social reputation for loan contracting.
Exploring smallholder farmers’ perceptions of climate change and its adaptation options in the Dire Dawa administration zone, Eastern Ethiopia
Authors: Asefa Bogale Girma
Published: April 2024

Purpose

This study aims to explore the smallholder farmers’ perceptions of climate change and its adaptation options (changing crop variety; improved crop and livestock; soil and water conservation [SWC]; and irrigation practices) and drought indices in the Dire Dawa Administration Zone, Eastern Ethiopia.

Design/methodology/approach

A cross-sectional household survey was used. A structured interview schedule for respondent households for key informants and focus group discussions were used. This study used both descriptive statistics and an econometric model. The model was used to compute the determinants of climate adaptation options in the study area. Drought characterization was carried out by DrinC software.

Findings

The results revealed households adapted to selected adaptation options. The model results confirmed that education level, farm size, tropical livestock units (TLUs) and access to agricultural extension services have positive and significant impacts on changing crop variety by 0.0014%, 0.045%, 0.032% and 0.035%, respectively. The likelihood of farmers’ decisions to use adaptation strategies (family size, TLU, agricultural extension service and distance from the market) has positive and significant impacts on SWC. The reconnaissance drought index (RDI6) of ONDJFM and AMJJAS showed extreme and severe drought index values of −2.88 and −1.96, respectively.

Originality/value

This study used a locally adopted climate change adaptation intervention for smallholder farmers, revealing the importance of drought characterization indices both seasonally and annually.
Critical factors for capacity building of NGOs working in the intellectual disability sector in India: a TISM-MICMAC approach
Authors: Rajan Rishabh , Jain Mukesh , Dhir Sanjay
Published: April 2024

Purpose

This study aims to identify the critical factors contributing to India-based non-governmental organizations (NGOs) capacity building and value creation for beneficiaries.

Design/methodology/approach

A total interpretive structural modeling technique has been used to develop a hierarchical model of critical factors and understand their direct and indirect interrelationships. The driving force and dependence force of these factors were determined by using cross-impact matrix multiplication applied to classification analysis.

Findings

This study identifies 12 critical factors influencing NGO capacity building in India’s intellectual disability sector across four dimensions. Internal organizational capabilities include infrastructure, staff qualifications, fundraising, vocational activities and technical resources. Second, coordination and stakeholder engagement highlight government and agency collaboration, dedicated board members and stakeholder involvement. Third, adaptability and responsiveness emphasize adjusting to external trends and seizing opportunities. Finally, impact and value creation emphasis on improving value for persons with disabilities (PWDs).

Practical implications

The findings of this study have practical implications for Indian NGOs working for PWDs. The study provides NGOs with a structural model for improving organizational capacity by identifying and categorizing critical factors into the strategic model.

Originality/value

There is a scarcity of literature on capacity building for disability-focused NGOs in India. This study seeks to identify critical factors and develop a hierarchical model of those factors to assist policymakers in India in building the capacity of NGOs.
American put options with regime-switching volatility
Authors: Jang Bong-Gyu , Koo Hyeng Keun
Published: April 2024

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.
Nexus between good governance and financial sustainability: evidence from microfinance sector of India
Authors: Maeenuddin Maeenuddin , Hamid Shaari Abdul , Nassir Annuar Md , Fahlevi Mochammad , Aljuaid Mohammed , Jermsittiparsert Kittisak
Published: April 2024

Purpose

Microfinance emerged as an essential catalyst for socio-economic development and financial inclusion to reduce poverty. Microfinance institutions cannot meet their primary objective of poverty reduction if they are not sustainable financially. With the theoretical support of profit incentive theory, this paper aims to investigate the impact of organizational structure (OS), growth outreach (average loan per borrower [ALPB] and number of active borrowers), women empowerment (percentage of women borrowers [PWB]), liquidity, leverage and cost efficiency (cost per borrower) on the financial sustainability of microfinance providers (MFPs) in India and explore the possible moderating effect of the national governance indicators (NGIs).

Design/methodology/approach

A financial sustainability index has been developed by using principal components analysis, including both conventional measures (return of assets and return on equity) and efficiency measures (operational self-sufficiency and financial self-sufficiency). Due to the existence of endogeneity and heteroskedasticity, this study uses two-step system generalized method of moments estimates to examine the relationships for a period of 2006 to 2018.

Findings

The finding reveals that there is a strong significant relationship between financial sustainability and its influential factors. Organizatioanl Structure, loan size, women borrowers, Gross Domestic Products and inflation enhance the financial sustainability of India’s microfinance sector. However, a number of borrowers, liquidity, leverage and operating costs negatively affect the financial sustainability of MFPs of India. The estimates demonstrate that NGIs significantly moderate the association between financial sustainability and its influential factors. The NGIs negatively affect the positive impact of Organizatioanl Structure on financial sustainability. National governance increases the positive effect of loan size (ALPB) and reduces the negative effect of a number of borrowers and leverage on the financial sustainability of MFPs of India. However, NGIs negatively affect the positive relationship between Percentage of Women Borrowers and Financial sustainability of Microfinance Providers of India.

Originality/value

To the best of the authors’ knowledge, this study is the first of its kind that incorporates all of the six dimensions of the National Governance Indicators (NGIs) and uses as a moderator. Secondly, a financial sustainability index has been developed for measuring the financial sustainability of Microfinance Providers (MFPs).
Satisfaction with human resource practices, job dedication and job performance: the role of incentive gamification
Authors: Kefas Hyelda Ibrahim , Cemal Nat Muesser , Iyiola Kolawole
Published: April 2024

Purpose

While the potential of human resource practices (HRPs) for promoting performance is widely recognized, even though crucial, employees’ assessment of HRPs remains under-researched, especially in emerging economies. Hence, the purpose of this research is to examine the influence of employee satisfaction with HRPs on job performance through the mediating role of job dedication (JD) and the moderating role of incentive gamification.

Design/methodology/approach

The current research adopts a quantitative method. Specifically, using a questionnaire survey, 418 valid responses collected (through purposive sampling) via cross-sectional method from the employees of Nigerian Information and Communication Technology (ICT) firms were used to test the research hypotheses empirically.

Findings

The results revealed that satisfaction with HRPs has a positive influence on job performance. Satisfaction with human resource practices has a positive influence on job dedication. Job dedication has a positive influence on job performance. The link between employees’ satisfaction with human resource practices and job performance is mediated by job dedication. The link between satisfaction with human resource practices and job dedication is moderated by incentive gamification, that is, the positive link is stronger when incentive gamification is high. The link between satisfaction with human resource practices and job performance is moderated by incentive gamification, that is, the positive link is stronger when incentive gamification is high.

Originality/value

The current study highlights the importance of employees’ assessments of human resource practices, which may be used to promote employee dedication, which in turn results in improved performance. The findings are helpful to open the black box of the impact of satisfaction with HRPs on job performance. The results also offer important new valuable guidance for practitioners and will aid the management of human resource practice design, audits, and communication.
Thermo-mechanical aging of carbon-black reinforced styrene-butadiene rubber under cyclic-loading
Authors: Dinari Amina , Benameur Tarek , Khoshnaw Fuad
Published: April 2024

Purpose

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

Design/methodology/approach

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

Findings

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

Originality/value

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.
Factors influencing adherence to iron drop supplementation in infants aged 6 to 24 months: a systematic review of observational studies
Authors: Hasanzadeh Maryam , Kalantari Fereshteh , Emamat Hadi , Ghalandari Hamid , Tangestani Hadith
Published: April 2024

Purpose

Iron deficiency anemia (IDA) is the most common nutritional anemia in the world and a pervasive health problem, especially in developing countries. Children under two years of age are more prone to be affected by IDA. The best strategy to prevent and treat IDA is to use iron supplements. This study aims to examine the factors associated with noncompliance (such as non-utilization or inconsistent usage) of iron drop supplementation among infants between 6 and 24 months old.

Design/methodology/approach

Online databases (PubMed, Scopus and SID) were searched to retrieve relevant articles published from inception up to July 2023. Among the 2,177 articles detected, after removing duplicate and irrelevant titles, 21 cross-sectional studies that met the authors’ inclusion criteria were included. Screening for articles and data extraction were conducted separately by two researchers.

Findings

The findings suggest that some factors related to mothers, such as education, knowledge, attitude and performance; some factors associated with child such as child’s gastrointestinal and dental complications; taste and smell of iron drops; and birth order and gender are the main determinants of adherence to iron supplementation.

Originality/value

It can be proposed that the most significant factors affecting the feeding of iron drops to children under the age of two include: the level of mother’s awareness, socio-economic status of the household and the occurrence of digestive complications following the supplementation. Given these observations, adopting proper policies toward improving the nutritional awareness of mothers and producing iron supplements with minimal side effects seems crucial.
How perceived socially responsible HRM and job insecurity influence employee voice behavior: does psychological availability matter?
Authors: Vu Thinh-Van
Published: April 2024

Purpose

This study aims to examine the multifaceted connection between perceived socially responsible human resource management (PSR-HRM), job insecurity (JI), psychological availability (PA) and employee voice behavior (VB). Furthermore, it delves into the mediating roles of PA, and JI in the linkage between PSR-HRM and VB and the moderating role of PA in the connection between JI and VB.

Design/methodology/approach

The empirical data for this study were collected from a sample of 385 full-time employees in Vietnam. To analyze the data and explore the relationships among the constructs, partial least squares structural equation modeling (PLS-SEM) was used.

Findings

The study reveals positive relationships between PSR-HRM, PA and VB. Furthermore, it demonstrates that PA serves as a partial mediator in the nexus between PSR-HRM and VB, while JI similarly partially mediates this association. In addition, the research identifies a positive moderating effect of PA on the linkage between JI and VB.

Originality/value

Grounded in social exchange theory and social cognitive theory, this study uncovers significant relationships, providing nuanced insights into the intricate interplay among PSR-HRM, JI, PA and VB. It represents one of the initial investigations into the moderating influence of PA on the connection between JI and VB.