bluuebunny/crossref_metadata_2025 huggingface dataset:
Linear, weakly nonlinear and fully nonlinear models for soft tissues: which ones provide the most reliable estimations of the stiffness?
Authors: Saccomandi G. , Vergori L. , Zanetti E. M.
Published: August 2022

Benign and malignant lesions in tissues or organs can be detected by elastographic investigations in which pathological regions are spotted from local alterations of the stiffness. As is known, the shear modulus provides a measure of the stiffness of an elastic material. Based on the classical theory of linear elasticity, an elastogram yields estimations of the
linear
shear modulus from measurements of the speed of small-amplitude transverse waves propagating in the medium tested. In this paper, we show that the estimation of the shear modulus can be improved significantly by employing the fourth-order weakly nonlinear theory of elasticity (FOE), and indicate how the stiffness can be assessed more precisely with the use of FOE. We discuss also why FOE provides more reliable results than the fully nonlinear theory of elasticity.

This article is part of the theme issue ‘The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity’.
An Ogden-like formulation incorporating phase-field fracture in elastomers: from brittle to pseudo-ductile failures
Authors: Ciambella Jacopo , Lancioni Giovanni , Stortini Nico
Published: August 2022

Over the past 50 years the Ogden model has been widely used in material modelling owing to its ability to match accurately the experimental data on elastomers at large strain, as well as its mathematical properties, such as polyconvexity. In this paper, these characteristics are exploited to formulate a finite-strain model that incorporates, through the phase-field approach recently proposed by Wu (Wu 2017
J. Mech. Phys. Solids
103
, 72–99) for small strains, a cohesive damage mechanism which leads to the progressive degradation of the material stiffness and to failure under tension. By properly tailoring the constitutive parameters, the model is capable of encompassing a wide range of effects, from brittle to pseudo-ductile failure modes. A plane stress problem is formulated to test the model against experiments on double-network elastomers, which display a pseudo-ductile damage behaviour at large strain, and on conventional rubber compounds with brittle failure. The results show that the proposed model is applicable to fracture coalescence and propagation in a wide range of materials.

This article is part of the theme issue ‘The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity’.
Ogden material calibration via magnetic resonance cartography, parameter sensitivity and variational system identification
Authors: Nikolov Denislav P. , Srivastava Siddhartha , Abeid Bachir A. , Scheven Ulrich M. , Arruda Ellen M. , Garikipati Krishna , Estrada Jonathan B.
Published: August 2022

Contemporary material characterization techniques that leverage deformation fields and the weak form of the equilibrium equations face challenges in the numerical solution procedure of the inverse characterization problem. As material models and descriptions differ, so too must the approaches for identifying parameters and their corresponding mechanisms. The widely used Ogden material model can be comprised of a chosen number of terms of the same mathematical form, which presents challenges of parsimonious representation, interpretability and stability. Robust techniques for system identification of any material model are important to assess and improve experimental design, in addition to their centrality to forward computations. Using fully three-dimensional displacement fields acquired in silicone elastomers with our recently developed magnetic resonance cartography (MR-

u

) technique on the order of greater than

20
 
000
 
points per sample

, we leverage partial differential equation-constrained optimization as the basis of variational system identification of our material parameters. We incorporate the statistical
F
-test to maintain parsimony of representation. Using a new, local deformation decomposition locally into mixtures of biaxial and uniaxial tensile states, we evaluate experiments based on an analytical sensitivity metric and discuss the implications for experimental design.

This article is part of the theme issue ‘The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity’.
Extremal states and coupling properties in electroelasticity
Authors: Menzel A. , Witt C.
Published: August 2022

Electroelastic materials possess properties most attractive for the design of smart devices and systems such as actuators and sensors. Typical polymers show changes in shape under the action of an electric field, and vice versa, together with fast actuation times, high strain levels and low elastic moduli. This paper deals with an Ogden model inspired framework for large deformation electroelasticity which, as a special case, can also be reduced to the modelling of transversely isotropic elasticity. Extremal (local) states are elaborated based on a coaxiality analysis, i.e. extremal states of energy are considered at fixed deformation and changing direction of electric field, respectively, fixed electric field and changing principal directions of deformation. This analysis results in extremal states when stresses and strain commutate, respectively, dielectric displacements and electric field are aligned. In order to further elaborate electromechanical coupling properties, the sensitivity of stresses with respect to electric field is analysed. This sensitivity is represented by a third-order tensor which, in general, depends on deformation and electric field. To illustrate this third-order tensor, a decomposition into deviators is adopted. Related norms of these deviators, together with the electromechanical coupling contribution to the augmented energy, are investigated for different states under homogeneous deformation and changing electric field direction. The analysis is considered to contribute to a better understanding of electromechanical coupling properties and extremal states in large deformation electroelasticity and by that, as a long-term goal, may contribute to the improved design of related smart devices and systems.

This article is part of the theme issue ‘The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity’.
Mechanistic Deep Learning Framework on Cell Traits Derived from Single-Cell Mass Cytometry Data
Authors: Wang Bo , Zinkel Sandra S. , Gamazon Eric R.
Published: August 2022

Germline genetic variations can alter cellular differentiation, potentially impacting the response of immune cells to inflammatory challenges. Current variant- and gene-based methods in mouse and human models have established associations with disease phenotypes; however, the underlying mechanisms at the cellular level are less well-understood. Immunophenotyping by multi-parameter flow cytometry, and more recently mass cytometry, has allowed high-resolution identification and characterization of hematopoietic cells. The obtained characterization yields increased dimensionality; however, conventional analysis workflows have been inefficient, incomplete, or unreliable. In this work, we develop a comprehensive machine learning framework – MDL4Cyto – that is tailored to the analysis of mass cytometry data, incorporating statistical, unsupervised learning, and supervised learning models. The statistical modeling can be used to illuminate cell fate decision and cell-type dynamics. The unsupervised learning models along with complementary marker enrichment analyses highlight genetic perturbations that are significantly associated with alterations in cell populations in the hematopoietic system. Furthermore, our supervised learning models, including deep learning and tree-based algorithms, address the bottleneck to data pre-processing that characterizes conventional workflows and generate inferences (e.g., on marker/cell-type interactions) from raw experimental characterization. Notably, we reveal a close relationship among network design, prediction performance, and the underlying biological context. We show that the network architecture extracted from the differentiation cascade of the investigated biological system yields enhanced prediction performance. The presented methodology will enable new insights into hematopoietic differentiation at baseline and following perturbation.

Highlights

Analysis pipeline on mass cytometry data with high-performance implementation of statistical, unsupervised learning, and supervised learning models

Concordance of machine learning results with biological contexts

Biologically-informed neural network designs enhance prediction performance

Graphical Abstract
Bacterial communities associated with the surfaces of the fresh fruits sold around Dhaka Medical College and Hospital and their anti-microbial profiles
Authors: Kabir Rubaiya Binte , Zaman Rizwana , Tania Noor – E– Jannat , Asaduzzaman Md. , Haque Azmeri , Habib Farjana Binte , Tanni Nusrat Noor , Nesa Maherun , Chowdhury Akteruzzaman , Rahman Md. Faizur , Sarker Avizit , Halder Kakali , Sharmin Nazmun , Chowdhury Mahbuba , Nahar Sultana Shazeda , Rahman Md. Mizanur , Shahid Sazzad Bin , Shamsuzzaman SM
Published: August 2022

Background

Now-a-days, fresh fruits are popular sources of healthy diets with low energy density. Since they are consumed raw, it may act as a source of foodborne disease and a reservoir for antibiotic resistant organisms. This study aimed to determine microbial prevalence among the fruits sold outside Dhaka Medical College Hospital (DMCH) along with their antimicrobial profiles and to detect antimicrobial resistance genes among the resistant organisms.

Methods

Thirty-five different types of fruits were bought from around DMCH and analyzed for the presence of bacteria. Antibiotic sensitivity was done and ESBL, AmpC β-lactamase, and MBL positive strains were identified by standard methods followed by PCR to detect ESBL, AmpC β-lactamase, and MBL genes.

Findings

Twenty seven different organisms were isolated and identified which were-Klebsiella spp (33·33%), Citrobacter spp (29·64%), Enterobacter spp (22·22%), Escherichia coli (11·11%), and Staphylococcus aureus (3·70%). Among them 48·15% organisms were resistant to different antibiotics. Only one organism (Citrobacter spp) produced ESBL phenotypically (7·69%). Two (15·38%) were positive for AmpC β-lactamase and one of these (Enterobacter spp) possessed both SHV and CTX-M15A genes by PCR. Imipenem resistance was 84·62% of the antibiotic resistant organisms, and 10 (90·91%) were phenotypically MBL positive by CD test, DDS test, and MHT. By PCR, one Enterobacter spp had MBL encoding gene OXA-48.

Interpretation

Fresh fruits, contaminated with pathogens, might be a source of transmission of resistant organisms and attribute to public health issues.

Funding

The office of Directorate General of Health Service, Ministry of Health and Family Welfare, Bangladesh.

Importance

Fruits sold around Dhaka Medical College and Hospital (DMCH) are usually consumed by patients, patient’s attendant and Health care worker. This investigation emphasized not only on the extent of bacterial contamination but also attempted to measure the anti-microbial profile of these organisms isolated from the fruits commonly available and readily consumed in and around DMCH.
The palisade-specific gene IQD22 enhances photosynthetic capacity by phenocopying “sun leaf” architecture
Authors: Matthes Michaela C. , Pennacchi Joao P. , Napier Johnathan A. , Kurup Smita
Published: August 2022

The world requires a rise in crop production which needs to be increased significantly in order to satisfy demand by 20501. However traditional plant breeding approaches are anticipated to fall short in delivering the increases in yield required and therefore targeted manipulation of plant metabolism is increasingly being pursued with the aim to achieve this goal2. Improving photosynthetic efficiency is predicted to have a significant influence on enhancing crop productivity and several ambitious genetic engineering projects are currently under way to achieve higher photosynthetic rates in crops3,4. A naturally evolved adaptive trait which allows plants to increase photosynthetic efficiency specifically under high light is the differentiation of ‘sun’ leaves which are characterised by an increase in palisade cell layers and more elongated cells within this layer5. These morphological changes allow a more efficient distribution of light within the leaf and provide an increased cell surface to which chloroplasts can relocate thereby increasing the capacity for CO up-take6. Here we show that, surprisingly, this complex morphological trait can be phenocopied by the modulation of the expression of a single palisade specific gene, IQD22, in Arabidopsis. Furthermore, we could show that the architectural changes were reflected in an increase of photosynthetic rate of 30%. The simplicity with which we could enhance photosynthesis by phenocopying sun leave traits is in stark contrast to the complex and challenging metabolic engineering approaches currently being pursued.
Distinguish characters of luminal and glandular epithelium from mouse uterus using a novel enzyme-based separation method
Authors: Xu Qi-Xin , Zhang Wang-Qing , Lu Lei , Wang Ke-Zhi , Su Ren-Wei
Published: August 2022

The uterine luminal epithelium, glandular epithelium, and stromal cells are vital for the establishment of pregnancy. Previously studies have shown various methods to isolate mouse uterine epithelium and stromal cells, including Laser Capture Microdissection (LCM), enzyme digestion, and Immunomagnetic beads. Despite the importance of the endometrial epithelium as the site of implantation and nutritional support for the conceptus, there is no isolated method to separate the luminal epithelium and glandular epithelium. Here, we establish a novel enzyme-based way to separate two types of epithelium and keep their viability. In this article, we analyzed their purity by mRNA level, immunostaining, and transcriptome analysis. Our isolation method revealed several unstudied luminal and glandular epithelial markers in transcriptome analysis. We further demonstrated the viability of the isolated epithelium by 2D and 3D cultures. The results showed that we successfully separated the endometrial luminal epithelium and glandular epithelium. We also provided an experimental model for the following study of the physiological function of the different parts of the uterus and related diseases.
eIF3 mRNA selectivity profiling reveals eIF3k as a cancer-relevant regulator of ribosome content
Authors: Duan Haoran , Zhang Siqiong , Zarai Yoram , Öllinger Rupert , Wu Yanmeng , Sun Li , Hu Cheng , Tian Guiyou , Rad Roland , Cheng Yabin , Tuller Tamir , Wolf Dieter A.
Published: August 2022

eIF3, whose subunits are frequently overexpressed in cancer, regulates mRNA translation from initiation to termination, but mRNA-selective functions of individual subunits remain poorly defined. Using multi-omic profiling upon acute depletion of eIF3 subunits, we observed that while eIF3a, b, e, and f markedly differed in their impact on eIF3 holo-complex formation and translation, they were each required for cancer cell proliferation and tumor growth. Remarkably, eIF3k showed the opposite pattern with depletion promoting global translation, cell proliferation, tumor growth, and stress resistance through repressing the synthesis of ribosomal proteins, especially RPS15A. Whereas ectopic expression of RPS15A mimicked the anabolic effects of eIF3k depletion, disruption of eIF3 binding to the 5’-UTR ofRSP15AmRNA negated them. Supported by mathematical modeling, our data uncovers eIF3k-l as a mRNA-specific module which, through controllingRPS15Atranslation, serves as a rheostat of ribosome content to secure spare translational capacity that can be mobilized during stress.
Natural variation in PHY causes differential response to R/FR light following a latitudinal cline in Norway spruce
Authors: Ranade Sonali Sachin , García-Gil María Rosario
Published: August 2022

Detection of the genomic basis of local adaptation to environmental conditions is challenging in forest trees. Phytochromes (PHY) and cryptochromes (CRY) perceive the red (R)/far-red (FR) and blue light respectively and, play a fundamental role in regulating the light pathway in plants contributing to plant growth and development. Norway spruce shows an adaptive latitudinal cline for shade (low R:FR or FR-enriched light) tolerance and requirement of FR light for its growth, thus showing differential response to light quality. We analyzed the exome capture data that included a uniquely large data set of 1654 Norway spruce trees sampled from different latitudes across Sweden that differ in exposure to photoperiod and FR light received during the growing season. Statistically significant clinal variation was detected in allele and genotype frequencies of missense mutations in coding regions belonging to well-defined functional domains of PHYO (PAS-B), PHYP2 (PAS fold-2), CRY1 (CCT1) and CRY2 (CCT2) that strongly correlates with the latitudinal gradient in response to variable light quality in Norway spruce. Asn835Ser in PHYO displayed the steepest cline among all other polymorphisms. We propose that these variations represent signs of local adaptation to light quality in Norway spruce.
Screening of genes related to the interaction between Listeria monocytogenes and host cells
Authors: Fan Gao , Jun-xing Pu , Jin-wen Huang
Published: August 2022

To investigate how host cells respond to the hijacking of host cells by Listeria monocytogenes (LM) and affect their gene expression in the process of infection by LM. In this study, three data lines in the GEO database were used for differential expression analysis. The results showed that 34 co-expressed genes (DEGs) were selected from the differential expression analysis of three data lines. Among them, 30 genes were co-up-regulated and 4 genes were co-down-regulated. In the blood test group, 131 genes were up-regulated and 28 genes were down-regulated. In the liver, 132 genes were up-regulated and 18 genes were down-regulated. In the spleen, 142 genes were up-regulated and 11 genes were down-regulated. Among the 30 upregulated IDEGs, GBP3, MB21D1, FPR2, SAMHD1, CXCL10, STAT2, IRF1, and STAT1 genes were involved in the defense response to the virus, type i interferon signaling pathway, and inflammatory response. Functional enrichment analysis revealed that 30 up-regulated genes were enriched in cytoplasmic spermatoproteasome complex, proteasome core complex, and cell membrane lateral signaling pathway, which were involved in the regulation of threonine-type endopeptidase activity and guanosine triphosphate (GTP) signaling process.
Performance efficient macromolecular mechanics via sub-nanometer shape based coarse graining
Authors: Bryer Alexander J. , Perilla Juan R.
Published: August 2022

Dimensionality reduction via coarse grain modeling has positioned itself as an indispensable tool for decades, particularly for biomolecular simulations where atomic systems encompass hundreds of millions of atoms. While distinct flavors of coarse grain modeling exist, those occupying the coarse end of the spectrum are typically knowledge based, relying on a priori information to parameterize models, thus hindering general predictive capability. Here, we present an algorithmic and transferable approach known as shape based coarse graining (SBCG) which employs unsupervised machine learning via competitive Hebbian adaptation to construct coarse molecules that perfectly represent atomistic topologies. We show how SBCG provides ample control over model granularity, and we provide a quantitative metric for selection thereof. Parameter optimization, inclusion of small molecule species, as well as simulation configuration are discussed in detail. Our method and its implementation is made available as part of the CGBuilder plugin, present in the widely-used visual molecular dynamics (VMD) and nanoscale molecular dynamics (NAMD) software suites. We demonstrate applications of our method with a variety of systems from the inositol hexaphosphate-bound, full-scale HIV-1 capsid to heteromultimeric cofilin-2-bound actin filaments. Overall, we show that SBCG provides a simple yet robust approach to coarse graining that requires minimal user input and lacks any ad hoc interactions between protein domains. Furthermore, because the Hamiltonian employed in SBCG is CHARMM compatible, SBCG takes full advantage of the latest GPU-accelerated NAMD3 yielding molecular sampling of over a microsecond per day for systems that span micrometers.
Human XIRP1 is a macrophage podosome protein utilized by Listeria for actin-based motility
Authors: Urbano Rodolfo , Park Eui-Soon , Tretina Kyle , Tunaru Alexandru , Gaudet Ryan G. , Hu Xiaoyun , Wang Da-Zhi , MacMicking John D.
Published: August 2022

Actin is integral to eukaryotic physiology as a biomechanical polymer and as a structural barrier for cell-autonomous defense against infection. Some microbial pathogens exploit the actin cytoskeleton, however, to evade cell-autonomous immunity. Subversion of actin to enter host cells and for actin-based motility are often employed by intracellular pathogens to spread from cell-to-cell. Using RNA-sequencing and computational data mining, we identify the host actin-binding protein XIRP1 as commonly induced during infection. XIRP1 is expressed by fibroblasts and macrophages in response to immune cytokines such as interferon-gamma (IFN-γ) and infection with bacteria such as Listeria, Shigella, and Salmonella. Confocal and super-resolution structured illumination microscopy (SIM) found XIRP1 localizes to fibroblast focal adhesions and macrophages podosomes. Within human macrophages, XIRP1 is recruited to cytosolic Listeria monocytogenes in an ActA-dependent manner as it replicates and uses actin-based motility for host cell escape. Chromosomal removal of XIRP1 in mice impaired this dissemination and rendered them more resistant to Listeria infection than C57BL/6NJ wildtype controls in vivo. We propose that professional cytosolic pathogens like Listeria can co-opt XIRP1 to escape the hostile intracellular environment of IFN-γ-activated macrophages as part of the host-pathogen arms race during cell-autonomous immunity.
Graph Neural Networks Ameliorate Potential Impacts of Imprecise Large-Scale Autonomous Immunofluorescence Labeling of Immune Cells on Whole Slide Images
Authors: Reddy Ramya , Reddy Ram , Sharma Cyril , Jackson Christopher , Palisoul Scott , Barney Rachael , Kolling Fred , Salas Lucas , Christensen Brock , Brooks Gabriel , Tsongalis Gregory , Vaickus Louis , Levy Joshua
Published: August 2022

The characteristics of tumor-infiltrating lymphocytes (TIL) are essential in cancer prognostication and treatment through the ability to indicate the tumor’s capacity to evade the immune system (e.g., as evidenced by nodal involvement). Machine learning technologies have demonstrated remarkable success for localizing TILs, though these methods require extensive curation of manual annotations or restaining procedures that can degrade tissue quality, resulting in imprecise annotation. In this study, we co-registered tissue slides stained for both hematoxylin and eosin (H&E) and immunofluorescence (IF) as means to rapidly perform large-scale annotation of nuclei. We integrated the following approaches to improve the prediction of TILs: 1) minimized tissue degradation on same-section tissue restaining, 2) developed a scoring algorithm to improve the selection of patches for machine learning modeling and 3) utilized a graph neural network deep learning approach to identify relevant contextual features for lymphocyte prediction. Our graph neural network approach accounts for surrounding contextual micro/macro-architecture tissue features to facilitate interpretation of registered IF. The graph neural network compares favorably (F1-score=0.9235, AUROC=0.9462) to two alternative modeling approaches. This study brings insight to the importance of contextual information leveraged from within and around neighboring cells in a nuclei classification workflow, as well as elucidate approaches which enable the rapid generation of large-scale annotations of lymphocytes for machine learning approaches for immune phenotyping. Such approaches can help further interrogate the spatial biology of colorectal cancer tumors and tumor metastasis.
Epidermal growth factor receptor signaling protects epithelia from morphogenetic instability and tissue damage in Drosophila
Authors: Yoshida Kentaro , Hayashi Shigeo
Published: August 2022

Dying cells in the epithelia communicate with neighboring cells to initiate coordinated cell removal to maintain epithelial integrity. Naturally occurring apoptotic cells are mostly extruded basally and engulfed by macrophages. Here, we investigated the role of Epidermal growth factor (EGF) receptor (EGFR) signaling in the maintenance of epithelial homeostasis. In Drosophila embryos, epithelial tissues undergoing groove formation preferentially enhanced extracellular signal-regulated kinases (ERK) signaling. In EGFR mutant embryos at stage 11, sporadic apical cell extrusion in the head initiates a cascade of apical extrusions of apoptotic and non-apoptotic cells that sweeps the entire ventral body wall. Here, we showed that clustered apoptosis, groove formation, and wounding sensitized EGFR mutant epithelia to initiate massive tissue disintegration. We further showed that tissue detachment from the vitelline membrane, which frequently occurs during morphogenetic processes, is a key trigger for the EGFR mutant phenotype. These findings indicate that, in addition to cell survival, EGFR plays a role in maintaining epithelial integrity, which is essential for protecting tissues from transient instability caused by morphogenetic movement and damage.
Validation of saline, PBS and a locally produced VTM at varying storage conditions to detect the SARS-CoV-2 virus by qRT-PCR
Authors: Ngetsa Caroline , Osoti Victor , Okanda Dorcas , Marura Faith , Shah Krupali , Karanja Henry , Mugo Daisy , Gitonga John , Mutunga Martin , Lewa Clement , Orindi Benedict , Bejon Philip , Ochola-Oyier Lynette Isabella
Published: August 2022

Coronavirus Disease-2019 tests require a Nasopharyngeal (NP) and/or Oropharyngeal (OP) specimen from the upper airway, from which virus RNA is extracted and detected through quantitative reverse transcription-Polymerase Chain Reaction (qRT-PCR). The viability of the virus is maintained after collection by storing the NP/OP swabs in Viral Transport Media (VTM).

We evaluated the performance of four transport media: locally manufactured (“REVITAL”) Viral Transport Media (RVTM), Standard Universal Transport Media (SUTM), PBS and 0.9% (w/v) NaCl (normal saline). We used laboratory cultured virus to evaluate: i) viral recovery and maintaining integrity at different time periods and temperatures; ii) stability in yielding detectable RNA consistently for all time points and conditions; and iii) their overall accuracy.

Four vials of SARS-CoV-2 cultured virus (2 high and 2 low concentration samples) and 1 negative control sample were prepared for each media type (SUTM, RVTM, PBS and normal saline) and stored at the following temperatures, -80°C, 4°C, room temperature (25°C) and 37°C for 7 days. Viral Ribonucleic acid (RNA) extractions and qRT-PCR were done on the following days after inoculation with the cultured virus, days 1, 2, 3, 4 and 7 to assess virus stability and viral recovery.

CT values fell over time at room temperature, but normal saline, PBS, RVTM and SUTM all showed comparable performance in maintaining virus integrity and stability allowing for the detection of SARS-CoV-2 viral RNA.

Overall, this study demonstrated that normal saline, PBS and the locally manufactured VTM can be used for COVID-19 sample collection and testing, thus expanding the range of SARS-CoV-2 viral collection media.
Insurance for climate change and environmental risk: a bibliometric review
Authors: Nobanee Haitham , Dilshad Mehroz Nida , Abu Lamdi Omar , Ballool Bashaier , Al Dhaheri Saeed , AlMheiri Noura , Alyammahi Abdalla , Alhemeiri Sultan Salah
Published: August 2022

Purpose

This study aims to examine the research output on climate change, environmental risks and insurance from 1986 to 2020, thereby revealing the development of the literature through collaborative networks. The relationship between insurance, climate change and environmental threats has gained research attention. This study describes the interaction between insurance, climate change and environmental risk.

Design/methodology/approach

This study is a bibliometric analysis of the literature and assessed the current state of science. A total of 97 academic papers from top-level journals listed in the Scopus database are shortlisted.

Findings

The understanding of climate change, environmental risks and insurance is shaped and enhanced through the collaborative network maps of researchers. Their reach expands across different networks, core themes and streams, as these topics develop.

Research limitations/implications

Data for this study were generated from English-written journal articles listed in the Scopus database only; subsequently, this study was representative of high-quality papers published in the areas of climate change, environmental risks and insurance.

Practical implications

The results of this study can be useful to academic researchers to aid their understanding of climate change, environmental risks and insurance research development, to identify the current context and to develop a future research agenda.

Social implications

The findings of this study can improve the understanding of industry practitioners about climate change and global warming challenges, and how insurance can be used as a tool to address such challenges.

Originality/value

This study is a novel attempt. To the best of the authors’ knowledge, this is one of the first studies to better understand climate change, environmental risks and insurance as a research topic by examining its evolution in an academic context through visualization, coupling and bibliometric analysis. This bibliometric study is unique in reviewing climate change literature and providing a future research agenda. Using bibliometric data, this study addressed the technical aspects and the value it adds to actual practice. Bibliometric indicators quantitatively and qualitatively evaluate emerging disciplinary progress in this topic.
Bolstering green supply chain integration via big data analytics capability: the moderating role of data-driven decision culture
Authors: Liu Yang , Fang Wei , Feng Taiwen , Gao Na
Published: August 2022

Purpose

Based on organizational information processing theory, this research explores how big data analytics capability (BDAC) contributes to green supply chain integration (GSCI) and the contingency role that data-driven decision culture plays.

Design/methodology/approach

Using the two-wave survey data collected from 317 Chinese manufacturing firms, the authors validate the hypotheses.

Findings

The results show that big data managerial capability has positive impacts on three dimensions of GSCI, while big data technical capability has positive impacts on green internal and customer integration. Moreover, green internal integration mediates the impacts of big data technical capability and managerial capability on green supplier and customer integration. Finally, data-driven decision culture alleviates the positive impacts of big data technical and managerial capability on green internal integration.

Practical implications

The findings suggest that firms can leverage big data technical and managerial capability to enhance information processing capability for achieving a higher degree of GSCI. Further, the critical role of data-driven decision culture in affecting the link between BDAC and GSCI should not be overlooked.

Originality/value

This research contributes to literature on green supply chain management by revealing the role of BDAC in improving GSCI.
Belief perseverance in students’ perceptions of accounting in a distance-learning environment: evidence from a GCC university
Authors: Elsayed Nader
Published: August 2022

Purpose

By drawing on Belief Perseverance Theory (BPT), this study investigates the pre- and post-perceptions of the First Accounting Course (FAC) differentiating between accounting and non-accounting students in a virtual learning setting at a Gulf Cooperation Council (GCC) university, and explains why students' perceptions have formed.

Design/methodology/approach

Adopting a case study approach, this study employs quantitative (anonymous questionnaires) and qualitative (semi-structured interviews) methods.

Findings

Responses from 142 financial accounting students indicate that non-accounting majors generally changed the students' perceptions significantly at the end of the semester, whereas students' accounting counterparts had relatively stable perceptions. This study also finds that a large number of non-accounting students perceived the benefits of taking the FAC and generally have less negative perceptions of the accounting profession, which supports the notion that non-accounting students evaluated discrediting information to reassess non-accounting students pre-established perceptions.

Practical implications

This study has several implications as follows: for the accounting education literature on how FAC assists students in changing students' perceptions through the lens of BPT, for professional accounting bodies to find ways to promote accounting careers for students and for educators to increase students’ desire for accounting study and profession.

Originality/value

The findings from this study are expected to contribute to GCC society by providing clarifications towards increasing students’ desire for accounting studies and professions.
Cloud-based accounting information systems usage and its impact on Jordanian SMEs’ performance: the post-COVID-19 perspective
Authors: Al-Okaily Manaf , Alkhwaldi Abeer F. , Abdulmuhsin Amir A. , Alqudah Hamza , Al-Okaily Aws
Published: August 2022

Purpose

The purpose of this study is to examine the factors influencing the usage of cloud-based accounting information systems (AIS) in the crisis era (i.e. the COVID-19 pandemic) by expanding the unified theory of acceptance and use of technology (UTAUT) with new related critical factors.

Design/methodology/approach

A quantitative research approach based on a cross-sectional online questionnaire was used for collecting empirical data from 438 potential and current users of cloud-based AIS. Structural equation modeling based on analysis of a moment structures 25.0 was applied in the data analysis.

Findings

The outcome of the structural path revealed that performance expectancy, social motivation, COVID-19 risk (COV-19 PR) and trust (TR) were significantly influencing users’ behavioral intention (BI) toward using cloud-based AIS and explained 71% of its variance. While, contrary to what is expected, the impact of effort expectancy and perceived security risk (SEC) on BI was insignificant. In addition, BI was revealed to influence the actual usage behaviors and explained 74% of its variance. The outcome factors: communication quality (CQ) and decision quality (DQ) were significantly influenced by the usage of cloud-based AIS.

Practical implications

The current research would be valuable for small- and medium-sized enterprises officials and policymakers to illustrate the relatively low rates of cloud-based AIS and formulate strategies to boost the acceptance and use of cloud-based AIS by Jordanian users, where cloud-based services are still deemed as an innovation.

Originality/value

To the best of the authors’ knowledge, the current study is the first academic paper that extends the UTAUT by integrating additional factors: TR, SEC and COV-19 PR. In addition to two outcome variables: CQ and DQ, to study the cloud-based AIS in the Jordanian setting beyond the COVID-19 pandemic. The current research contributes to the academic knowledge on information technology information system adoption by considering cloud accounting acceptance and use and integration into the work practices of users through the BIs and actual use of cloud-based AIS in Jordan.
Evaluation of Sovereign Sukuk as a government financing instrument with stakeholder theory: a moving forward policy from Indonesia’s experience
Authors: Surachman Eko Nur , Hermawan Ricky Pramoedya , Handayani Dian , Astuti Erin
Published: August 2022

Purpose

This study aims to examine the performance of government projects financed by the issuance of Indonesia Sovereign Sukuk (SBSN Project) from stakeholder theory perspective and propose policy recommendations to improve its effectiveness as a government financing instrument.

Design/methodology/approach

The authors applied a qualitative interpretive approach in this study by conducting content analysis using stakeholder theory. Big data from official webinars about Indonesia Sovereign Sukuk issuance on the internet were used and coded by qualitative data analysis software.

Findings

The results reveal the stakeholders’ concerns regarding the project implementation. The cluster analysis confirms that technical ministries are the instrumental stakeholders who have the authority and tools to achieve SBSN Project success. The authors propose inclusive policy recommendations for each stakeholder, such as establishing an SBSN Project Master Plan, presuming disincentive to use project extension facility and setting up a comprehensive approach to assist working units in technical ministries in project preparation, development and service delivery. From the perspective of sustainability, the Government of Indonesia should focus more on education to the local community as end-users, value creation to integrate SBSN Projects with other financing schemes and regulation to ensure the effectiveness of a reward–punishment mechanism.

Practical implications

The findings of this study may be useful to the Government of Indonesia, especially the Ministry of Finance, in determining and establishing moving forward policies that are relevant and contribute significantly to the sustainability of the Sovereign Sukuk programme.

Originality/value

This study is one of a few studies exploring Islamic public financing instruments, with its originality lying in the examination of the SBSN Project performance from an academic approach, specifically stakeholder theory. This study uses big data available from the public domain to formulate proposed actions to achieve a sustainable SBSN Project programme.
Perceptions about the common malpractice of Zakat paying in Bangladesh during Covid-19 pandemic: evidence from the supply side
Authors: Islam Md. Karimul , Mitu Shayyada Tunnesha , Munshi Riaz , Khanam Rabeya
Published: August 2022

Purpose

A nationwide common malpractice in Zakat distribution has been prevailing in Bangladesh for the past few decades. The paper is a groundbreaking effort to investigate the perceptions of the Zakat payers about the common malpractices and to highlight whether any change in the conventional distribution of Zakat has occurred during the Covid-19 pandemic. The study also aims to extract the common perception of the Zakat payers regarding the validity of the changed practices during the pandemic.

Design/methodology/approach

The study adopts the qualitative research approach allowing an in-depth interview technique based on an unstructured questionnaire schedule to obtain information from the Zakat payers, complemented by the key informant interview with the Islamic Scholars. The study obtained data from Zakat payers administering a purposive sampling technique based on two specified criteria. After coding the information on three main themes, content analysis is used to examine the results.

Findings

The results reveal that although the Zakat payers dislike the common practices because of some antithetical issues, they still practice the same customs. Moreover, they apportion most of the value of Zakat in purchasing low-quality festive-motive clothes for the recipients. They are ignorant about Islamic law and the validity of such practices. According to scholars, these activities are not a pure system of Zakat provision and unable to alleviate poverty. Amid the Covid-19 pandemic, this practice shifted heavily to buying food items for the poor due to the financial hurdles they confronted during the pandemic. Although no solid argument is deduced from the participants about the exactitude of such distributional change, scholars regard the transformation as beneficial to the afflicted and the impoverished who have been hit by the pandemic, as well as not conflicting with the Zakat legislation.

Practical implications

The study is a novel contribution to addressing the malpractice in Zakat distribution through receiving practical information from the Zakat payers, which will help produce more in-depth research in Islamic finance. Furthermore, this research will help the government and people raise awareness about the authentic practices of Zakat distribution according to the codes of Shari’ah.

Originality/value

This study is a pioneering investigation since a scarcity of scholarly works attempted to identify the impact of Covid-19 on the practice of Zakat distribution and the associated perception regarding its Islamic jurisprudence. To the best of the authors’ knowledge, the investigation of common malpractices of Zakat is still unearthed by no former rigorous studies in the context of Bangladesh. The present study bridges this gap and paves a pragmatic research dimension in the Islamic finance.
Early backers' social and geographic influences on the success of crowdfunding
Authors: Ma Zecong
Published: August 2022

Purpose

While crowdfunding provides a novel method for entrepreneurs and startups to raise funding from consumers, a high percentage of crowdfunding projects fail to achieve their funding goals. This study aims to investigate the impact of early backers on crowdfunding success (i.e. reaching funding goals) by considering their social and geographic peer influences.

Design/methodology/approach

The author constructed a social network and a geographic network of crowdfunding backers based on a data set from Kickstarter.com and used closeness centrality to quantify the network positions of early backers.

Findings

For project categories with low completion uncertainty, early backers who were socially closer to their peers led to a higher chance of success. However, such an impact declines for projects with higher uncertainty. On the other hand, for project categories with high completion uncertainty, early backers who were geographically closer to their peers led to a higher chance of success. Still, such an impact declines for projects with lower uncertainty.

Originality/value

This paper contributes to the literature by investigating the peer influence between socially and geographically related consumers on a crowdfunding platform. The findings provide managerial implications for crowdfunding project creators to target the right crowd.
Clinical outcomes of PD Check‐In, a model for supported self‐managed maintenance of speech in Parkinson's disease: A Phase 1 study
Authors: Finnimore Ann , Theodoros Deborah , Rumbach Anna F.
Published: August 2022

Background

For many people with Parkinson's disease (PWPD), the long‐term maintenance of speech following intensive treatment remains elusive. PD Check‐In, a model for supported self‐managed maintenance of speech following LSVT LOUD®, was developed and evaluated.

Aims

To evaluate the impact of PD Check‐In on vocal intensity and level of satisfaction of PWPD and their communication partners (CPs) over 24 months following LSVT LOUD.

Methods & Procedures

A repeated‐measures study design examined the impact of PD Check‐In on the speech of 16 PWPD. Participants received LSVT LOUD followed by PD Check‐In at 6 and 12 weeks, and 6, 12 and 24 months after treatment. Outcome measures included acoustic measures of vocal intensity (sound pressure level–SPL) during sustained phonation, functional phrases, reading, and monologue, and satisfaction questionnaires for PWPD and their CPs.

Outcomes & Results

A significant treatment effect for time (p < 0.01) was identified for all SPL variables. Planned comparisons showed significant improvements for each variable pre‐ to post‐LSVT LOUD. There was a significant maintenance effect for SPL maximum sustained phonation only, post‐LSVT LOUD to 24 months. SPL remained significantly above baseline for functional phrases and maximum sustained phonation at 24 months. Participants’ satisfaction with PD Check‐In was high, at 93.75% for PWPD and 79.99% for CPs, at 24 months post‐treatment. Long intervals between appointments led PWPD to feel less motivated about speech practice but more confident in self‐management.

Conclusions & Implications

For PWPD and CPs, maintenance of speech following LSVT LOUD encompasses more than acoustic outcomes.

WHAT THIS PAPER ADDS

What is already known on this subject?

Maintenance of speech following LSVT LOUD has been shown to be variable in individual and group models. For PWPD and their CPs, a model for speech maintenance supports their expectation of sustained treatment effect over time and meets their changing needs for speech and language therapy services. Supported self‐management is a model under investigation for long‐term maintenance of speech.

What this paper adds to existing knowledge?

This study presents the impact of five individual PD Check‐In interventions on the maintenance of vocal intensity (SPL) of 16 PWPD over 24 months following LSVT LOUD. PWPD and CPs reported a high level of satisfaction with PD Check‐In independent of acoustic outcomes.

What are the potential or actual clinical implications of this work?

Participant satisfaction with PD Check‐In is derived from multiple factors and not limited to acoustic outcomes post‐LSVT LOUD. Further investigation of the efficacy of PD Check‐In to support the perceived maintenance of speech of PWPD and CPs is warranted.
Improved maize adoption and impacts on farm household welfare: Evidence from rural Ethiopia
Authors: Geffersa Abebayehu Girma , Agbola Frank W. , Mahmood Amir
Published: August 2022

The use of improved crop varieties can increase agricultural productivity and enhance the welfare of farmers. This study examined whether the adoption of improved maize varieties (IMV) is associated with the increased welfare of farmers in rural Ethiopia. A panel data set with 1886 observations collected in three waves from 2009/10 to 2014/15 were used for the analysis. The adoption decision was modelled using a double‐hurdle model, and the welfare effect of IMV adoption was estimated using a fixed‐effects instrumental variable approach. Our findings reveal that IMV affects the welfare of farmers. Specifically, we found that IMV adoption increases households' income, asset ownership and maize consumption while also reducing income poverty. The poverty estimates indicate that a 10% increase in the area allocated to IMV was associated with a 4.79% reduction in the probability of being below the $1.90 poverty line. However, the poverty‐reducing effect of IMV adoption was heterogeneous across households, with the most pronounced effect experienced by households with extensive landholdings. Our findings suggest that facilitating access to IMV and land under cultivation can effectively improve farmers' welfare and reduce poverty in rural Ethiopia.