bluuebunny/crossref_metadata_2025 huggingface dataset:
Prioritizing disease-causing metabolic genes by integrating metabolomics with whole exome sequencing data
Authors: Bongaerts Michiel , Bonte Ramon , Demirdas Serwet , Huidekoper Hidde , Langendonk Janneke , Wilke Martina , de Valk Walter , Blom Henk J. , Reinders Marcel J.T. , Ruijter George J. G.
Published: May 2021

The integration of metabolomics data with sequencing data is a key step towards improving the diagnostic process for finding the disease-causing gene(s) in patients suspected of having an inborn error of metabolism (IEM). The measured metabolite levels could provide additional phenotypical evidence to elucidate the degree of pathogenicity for variants found in metabolic genes. We present a computational approach, called Reafect, that calculates for each reaction in a metabolic pathway a score indicating whether that reaction is being deficient or not. When calculating this score, Reafect takes multiple factors into account: the magnitude and sign of alterations in the metabolite levels, the reaction distances between metabolites and reactions in the pathway, and the biochemical directionality of the reactions. We applied Reafect to untargeted metabolomics data of 72 patient samples with a known IEM and found that in 80% of the cases the correct deficient enzyme was ranked within the top 5% of all considered enzyme deficiencies. Next, we integrated Reafect with CADD scores (a measure for variant deleteriousness) and ranked the potential disease-causing genes of 27 IEM patients. We observed that this integrated approach significantly improved the prioritization of the disease-causing genes when compared with the two approaches individually. For 15/27 IEM patients the correct disease-causing gene was ranked within the top 0.2% of the set of potential disease-causing genes. Together, our findings suggest that metabolomics data improves the identification of disease-causing genetic variants in patients suffering from IEM.
The impact of resource provisioning on the epidemiological responses of different parasites
Authors: Erazo Diana , Pedersen Amy B. , Fenton Andy
Published: May 2021

Events such as anthropogenic activities and periodic tree masting can alter resource provisioning in the environment, directly affecting animals, and potentially impacting the spread of infectious diseases in wildlife. The effect of these supplemental resources on infectious diseases can manifest through different pathways, affecting host susceptibility, transmission and host demography.

To date however, empirical research has tended to examine these different pathways in isolation, for example by quantifying the effects of provisioning on host behaviour in the wild or changes in immune responses in controlled laboratory studies. Further, while theory has investigated the interactions between these pathways, thus far this work has focussed on a narrow subset of pathogen types, typically directly-transmitted microparasites. Given the diverse ways that provisioning can affect host susceptibility, contact patterns or host demography, we may expect the epidemiological consequences of provisioning to depend on key aspects of parasite life-history, such as the duration of infection and transmission mode.

We developed a suite of generic epidemiological models to compare how resource provisioning alters responses for different parasites that vary in their biology (micro- and macro-parasite), transmission mode (direct, environmental, and vector transmitted) and duration of infection (acute, latent, and chronic). Next, we parameterised these different parasite types using data from the diverse parasite community of wild wood mice as a case study.

We show there are common epidemiological responses to host resource provisioning across all parasite types examined. In particular, the response to provisioning could be driven in opposite directions, depending on which host pathways (contact rate, susceptibility or host demography) are most altered by the addition of resources to the environment. Broadly, these responses were qualitatively consistent across all parasite types, emphasising the importance of identifying general trade-offs between provisioning-altered parameters.

Despite the qualitative consistency in responses to provisioning across parasite types, we found notable quantitative differences between parasites, suggesting specific epidemiological outcomes could strongly depend on parasite type, infection duration and permanency of recovery, and whether the parasite is directly, environmentally, or vector transmitted. These analyses therefore highlight the importance of knowing key specific aspects of host-parasite biology, such as host contact behaviours, parasite interactions with the host immune system, and how resource availability shapes host demographics, in order to understand and predict epidemiological responses to provisioning for any specific host-parasite system.
Serine catabolism generates NADPH to support hepatic lipogenesis
Authors: Zhang Zhaoyue , TeSlaa Tara , Xu Xincheng , Zeng Xianfeng , Yang Lifeng , Xing Gang , Tesz Gregory J , Clasquin Michelle F , Rabinowitz Joshua D
Published: May 2021

Carbohydrate can be converted into fat by de novo lipogenesis1,2. This process is known to occur in adipose and liver, and its activity is upregulated in fatty liver disease3. Chemically, de novo lipogenesis involves polymerization and reduction of acetyl-CoA, using NADPH as the electron donor1. While regulation of the responsible enzymes has been extensively studied, the feedstocks used to generate acetyl-CoA and NADPH remain unclear. Here we show that, while de novo lipogenesis in adipose is supported by glucose and its catabolism via the pentose phosphate pathway to make NADPH, liver makes fat without relying on glucose. Instead, liver derives acetyl-CoA from acetate and lactate, and NADPH from folate-mediated serine catabolism. Such NADPH generation involves the cytosolic serine pathway running in liver in the opposite direction observed in most tissues and tumors4,5, with NADPH made by the SHMT1-MTHFD1-ALDH1L1 reaction sequence. Thus, specifically in liver, folate metabolism is wired to support cytosolic NADPH production for lipogenesis. More generally, while the same enzymes are involved in fat synthesis in liver and adipose, different substrates are utilized, opening the door to tissue-specific pharmacological interventions.
3D-MASNet: 3D Mixed-scale Asymmetric Convolutional Segmentation Network for 6-month-old Infant Brain MR Images
Authors: Zeng Zilong , Zhao Tengda , Sun Lianglong , Zhang Yihe , Xia Mingrui , Liao Xuhong , Zhang Jiaying , Shen Dinggang , Wang Li , He Yong
Published: May 2021

Precise segmentation of infant brain MR images into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) are essential for studying neuroanatomical hallmarks of early brain development. However, for 6-month-old infants, the extremely low-intensity contrast caused by inherent myelination hinders accurate tissue segmentation. Existing convolutional neural networks (CNNs) based segmentation models for this task generally employ single-scale symmetric convolutions, which are inefficient for encoding the isointense tissue boundaries in baby brain images. Here, we propose a 3D mixed-scale asymmetric convolutional segmentation network (3D-MASNet) framework for brain MR images of 6-month-old infants. We replaced the traditional convolutional layer of an existing to-be-trained network with a 3D mixed-scale convolution block consisting of asymmetric kernels (MixACB) during the training phase and then equivalently converted it into the original network. Five canonical CNN segmentation models were evaluated using both T1- and T2-weighted images of 23 6-month-old infants from iSeg-2019 datasets, which contained manual labels as ground truth. MixACB significantly enhanced the average accuracy of all five models and obtained the most considerable improvement in the fully convolutional network model (CC-3D-FCN) and the highest performance in the Dense U-Net model. This approach further obtained Dice coefficient accuracies of 0.931, 0.912, and 0.961 in GM, WM, and CSF, respectively, ranking first among 30 teams on the validation dataset of the iSeg-2019 Grand Challenge. Thus, the proposed 3D-MASNet can improve the accuracy of existing CNNs-based segmentation models as a plug-and-play solution that offers a promising technique for future infant brain MRI studies.
Inhibition of immunoglobulin class-switching prevents pemphigus onset in desmoglein 3-specific B cell receptor knock-in mouse
Authors: Nomura Hisashi , Wada Naoko , Takahashi Hayato , Kase Yuko , Yamagami Jun , Egami Shohei , Iriki Hisato , Mukai Miho , Kamata Aki , Ito Hiromi , Fujii Hideki , Ishikura Tomoyuki , Koseki Haruhiko , Watanabe Takashi , Yamada Taketo , Ohara Osamu , Koyasu Shigeo , Amagai Masayuki
Published: May 2021

Although immunoglobulin class-switching is essential for humoral immunity, its role in B-cell immune tolerance remains unclear. Pemphigus vulgaris is an autoimmune blistering disease caused by IgG targeting desmoglein 3, an adhesion molecule of keratinocytes. In this study, we generated knock-in mice that express anti-Dsg3 AK23 autoantibodies. Knock-in B cells developed normallyin vivoand showed Ca2+influx upon IgM cross-linkingin vitro. The mice predominantly produced circulating AK23 IgM but little IgG antibodies. Although no IgG deposition or blister formation was observed in Dsg3-bearing tissues, Dsg3 immunization forced to induce pemphigus phenotype after class-switching to IgGin vivo. Transcriptomic analysis revealed thatFCGR2Band FcγRIIB-related genes were downregulated in B cells from peripheral blood of pemphigus patients. Indeed, in AK23 knock-in mice,Fcgr2bdeficiency or haploinsufficiency spontaneously led to class-switching, AK23 IgG production, and pemphigus phenotype development. Thus, inhibition of pathogenic class-switching is a crucial tolerogenic process to prevent pemphigus onset, where attenuated FcγRIIB signaling is one of the key predispositions to break this tolerogenic state.
A Spatiotemporal Map of Reading Aloud
Authors: Woolnough Oscar , Donos Cristian , Curtis Aidan , Rollo Patrick S. , Roccaforte Zachary J. , Dehaene Stanislas , Fischer-Baum Simon , Tandon Nitin
Published: May 2021

Reading words aloud is a fundamental aspect of literacy. The rapid rate at which multiple distributed neural substrates are engaged in this process can only be probed via techniques with high spatiotemporal resolution. We probed this with direct intracranial recordings covering most of the left hemisphere in 46 humans as they read aloud regular, exception and pseudo-words. We used this to create a spatiotemporal map of word processing and to derive how broadband gamma activity varies with multiple word attributes critical to reading speed: lexicality, word frequency and orthographic neighborhood. We found that lexicality is encoded earliest in mid-fusiform (mFus) cortex and precentral sulcus, and is represented reliably enough to allow single-trial lexicality decoding. Word frequency is first represented in mFus and later in the inferior frontal gyrus (IFG) and inferior parietal sulcus (IPS), while orthographic neighborhood sensitivity resides solely in IPS. We thus isolate the neural correlates of the distributed reading network involving mFus, IFG, IPS, precentral sulcus and motor cortex and provide direct evidence for dual-route models of reading, with parallel processes via the lexical route from mFus to IFG, and the sub-lexical route from IPS and precentral sulcus to anterior IFG.
Alpha Oscillatory Activity Causally Linked to Working Memory Retention: Insights from Online Phase-corrected Closed-loop Transcranial Alternating Current Stimulation (tACS)
Authors: Chen Xueli , Ma Ru , Zhang Wei , Wu Qianying , Yimiti Ajiguli , Xia Xinzhao , Cui Jiangtian , Zeng Ginger Qinghong , Bu Junjie , Chen Qi , Yu Nancy Xiaonan , Wang Shouyan , Deng Zhi-De , Sack Alexander T. , Laughlin Myles Mc , Zhang Xiaochu
Published: May 2021

Although previous studies have reported correlations between alpha oscillations and the “retention” sub-process of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain. Conventional tACS is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention sub-process). Here, we developed an online phase-corrected closed-loop transcranial alternating current stimulation (tACS) system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits both up- and down-regulation of brain oscillations at the target stimulation frequency within a short stimulation period, and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to 39 participants during the retention sub-processes of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. Moreover, the in-phase tACS-induced changes in WM performance were positively correlated with alpha oscillatory activity. These findings strongly support a causal link between alpha oscillations and WM retention, and illustrate the broad application prospects of phase-corrected tACS.
Karyon: a computational framework for the diagnosis of hybrids, aneuploids, and other non-standard architectures in genome assemblies
Authors: Naranjo-Ortiz Miguel A. , Molina Manu , Mixão Verónica , Gabaldón Toni
Published: May 2021

Recent technological developments have made genome sequencing and assembly accessible to many groups. However, the presence in sequenced organisms of certain genomic features such as high heterozygosity, polyploidy, aneuploidy, or heterokaryosis can challenge current standard assembly procedures and result in highly fragmented assemblies. Hence, we hypothesized that genome databases must contain a non-negligible fraction of low-quality assemblies that result from such type of intrinsic genomic factors. Here we present Karyon, a Python-based toolkit that uses raw sequencing data and de novo genome assembly to assess several parameters and generate informative plots to assist in the identification of non-chanonical genomic traits. Karyon includes automated de novo genome assembly and variant calling pipelines. We tested Karyon by diagnosing 35 highly fragmented publicly available assemblies from 19 different Mucorales (Fungi) species. Our results show that 6 (17%) of the assemblies presented signs of unusual genomic configurations, suggesting that these are common, at least within the Fungi.
Identification of a new Infectious Pancreatic Necrosis Virus (IPNV) isolate in Atlantic salmon (Salmo salar L.) that causes mortality in resistant fish
Authors: Hillestad Borghild , Johannessen Stein , Melingen Geir Olav , Moghadam Hooman K.
Published: May 2021

Infectious pancreatic necrosis (IPN) is an important viral disease of salmonids that can affect fish during various life cycles. In Atlantic salmon, selecting for genetically resistant animals against IPN has been one of the most highly praised success stories in the history of fish breeding. The findings that resistance against this disease has a significant genetic component, which is mainly controlled by variations in a single gene, has helped to reduce the IPN outbreaks over the past decade to a great extent. In this paper, we present the identification of a new isolate of the IPN virus, from a field outbreak, that had caused mortality, even in the genetically resistant animals. We recovered and assembled the full-length genome of this virus, following deep-sequencing of an infected tissue. The comparative sequence analysis revealed that for the critical amino acid motifs, previously found to be associated with the degree of virulence, the newly identified isolate is similar to the virus’s avirulent form. However, we detected a set of deduced amino acid residues, particularly in the hypervariable region of the polyprotein, that collectively are unique to this strain compared to all other reference sequences assessed in this study. We suggest that these mutations have likely equipped the virus with the capacity to escape the host defence mechanism more efficiently, even in the genetically deemed IPN resistant animals.
Cryo-ET reveals two major tubulin-based cytoskeleton structures inToxoplasma gondii
Authors: Sun Stella Y. , Segev-Zarko Li-av , Chen Muyuan , Pintilie Grigore D. , Schmid Michael F. , Ludtke Steven J. , Boothroyd John C. , Chiu Wah
Published: May 2021

In the obligate intracellular parasite,Toxoplasma gondii, the subpellicular microtubules (SPMTs) help maintain shape, while the apical conoid (also tubulin-based) is implicated in invasion. Here, we use cryo-electron tomography to determine the molecular structures of the SPMTs and the conoid-fibrils (CFs) in vitrified and detergent-lysed parasites. Subvolume densities from detergent-extracted parasites yielded averaged density maps at subnanometer resolutions, and these were related back to their architecturein situ. An intraluminal spiral (IS) lines the interior of the 13-protofilament SPMTs, revealing a preferred orientation of these microtubules relative to the parasite’s long axis. Each CF is composed of 9 tubulin protofilaments, that produce a comma-shaped cross-section, plus additional associated components. Conoid protrusion, a crucial step in invasion, is associated with an altered pitch of each CF. The use of basic building blocks of protofilaments and different accessory proteins in one organism, illustrates the versatility of these critical structures.
Automatic instance segmentation of mitochondria in electron microscopy data
Authors: Nightingale Luke , de Folter Joost , Spiers Helen , Strange Amy , Collinson Lucy M , Jones Martin L
Published: May 2021

We present a new method for rapid, automated, large-scale 3D mitochondria instance segmentation, developed in response to the ISBI 2021 MitoEM Challenge. In brief, we trained separate machine learning algorithms to predict (1) mitochondria areas and (2) mitochondria boundaries in image volumes acquired from both rat and human cortex with multi-beam scanning electron microscopy. The predictions from these algorithms were combined in a multi-step post-processing procedure, that resulted in high semantic and instance segmentation performance. All code is provided via a public repository.
The gut bacterial natural product colibactin triggers induction of latent viruses in diverse bacteria
Authors: Silpe Justin E. , Wong Joel W. H. , Owen Siân V. , Baym Michael , Balskus Emily P.
Published: May 2021

Colibactin is a chemically unstable small molecule genotoxin produced by multiple different bacteria, including members of the human gut microbiome.1,2 While the biological activity of colibactin has been extensively investigated in mammalian systems,3 little is known about its effects on other microorganisms. Here, we discover that colibactin targets bacteria carrying prophages, inducing lytic development via the bacterial SOS response. DNA, added exogenously, protects bacteria from colibactin, as does expressing a colibactin resistance protein (ClbS) in non-colibactin-producing cells. The prophage-inducing effects we observe apply broadly across taxonomically diverse phage-bacteria systems. Finally, we identify bacteria that possess colibactin resistance genes but lack colibactin biosynthetic genes. Many of these bacteria are infected with predicted prophages, and we show that the expression of their ClbS homologs provides immunity from colibactin-triggered induction. Our study reveals a mechanism by which colibactin production could impact microbiomes and highlights an underappreciated role for microbial natural products in influencing population-level events such as phage outbreaks.
Generative neural networks separate common and specific transcriptional responses
Authors: Lee Alexandra J. , Mould Dallas L. , Crawford Jake , Hu Dongbo , Powers Rani K. , Doing Georgia , Costello James C. , Hogan Deborah A. , Greene Casey S.
Published: May 2021

Genome-wide transcriptome profiling identifies genes that are prone to differential expression across contexts (“common DEGs”), as well as genes with changes specific to the experimental manipulation. Distinguishing common DEGs from those that are specifically changed in a context of interest allows more efficient prediction of which genes are specific to a given biological process under scrutiny. Currently, commonly differentially expressed genes or pathways can only be identified through the laborious manual curation of highly controlled experiments, an inordinately time-consuming and impractical endeavor. Here we pioneer an approach for identifying common patterns using generative neural networks. This approach produces a background set of transcriptomic experiments from which a null distribution of gene and pathway changes can be generated. By comparing the set of differentially expressed genes found in a target experiment against the generated background set, common results can be easily separated from specific ones. This “Specific cOntext Pattern Highlighting In Expression data” (SOPHIE) approach is broadly applicable to new platforms or any species with a large collection of gene expression data. We apply SOPHIE to diverse datasets including those from human, human cancer, and the bacterial pathogen Pseudomonas aeruginosa. SOPHIE identifies common DEGs in concordance with previously described, manually and systematically determined common DEGs. Further, molecular validation indicates that SOPHIE detects highly specific, but low magnitude, biologically relevant, transcriptional changes. SOPHIE’s measure of specificity can complement log fold change values generated from traditional differential expression analyses. For example, by filtering the set of differentially expressed genes, one can identify those genes that are specifically relevant to the experimental condition of interest. Consequently, these results can inform future research directions.
Preservation of HIV-1 Gag helical bundle symmetry by bevirimat is central to maturation inhibition
Authors: Pak Alexander J. , Purdy Michael D. , Yeager Mark , Voth Gregory A.
Published: May 2021

The assembly and maturation of human immunodeficiency virus type-1 (HIV-1) requires proteolytic cleavage of the Gag polyprotein. The rate-limiting step resides at the junction between the capsid protein CA and spacer peptide 1, which assembles as a six-helix bundle (6HB). bevirimat (BVM), the first-in-class maturation inhibitor drug, targets the 6HB and impedes proteolytic cleavage, yet the molecular mechanisms of its activity, and relatedly, the escape mechanisms of mutant viruses, remain unclear. Here, we employed extensive molecular dynamics (MD) simulations and free energy calculations to quantitatively investigate molecular structure-activity relationships, comparing wild-type and mutant viruses in the presence and absence of BVM and inositol hexakisphosphate (IP6), an assembly cofactor. Our analysis shows that the efficacy of BVM is directly correlated with preservation of six-fold symmetry in the 6HB, which exists as an ensemble of structural states. We identified two primary escape mechanisms, and both lead to loss of symmetry, thereby facilitating helix uncoiling to aid access of protease. Our findings also highlight specific interactions that can be targeted for improved inhibitor activity and support the use of MD simulations for future inhibitor design.
The view from the front line: shifting beneficiary accountability and interrelatedness in the time of a global pandemic
Authors: Yates David , Difrancesco Rita Maria
Published: May 2021

Purpose

We discuss the beneficiary accountability implications that arose due to the COVID-19 pandemic (and resultant social distancing restrictions) for a branch of a religious non-governmental organisation (NGO) based in mainland Spain, whose main beneficiaries are homeless individuals.

Design/methodology/approach

We utilise a singular case method to observe accountability implications in the case organisation. We also utilise two sources of primary data: eight semi-structured interviews with volunteers of the NGO branch, supported by auto-ethnographic data recorded in forty-six diary entries throughout the period of research.

Findings

As the main mechanism for the discharge of beneficiary accountability for the case organisation is through action, this was affected greatly by the COVID-19 pandemic and social distancing measures. Beneficiary accountability (discharged through action) changed rapidly, resulting in neglect of previous beneficiaries, carrying profound implications for charitable actors, beneficiaries and the organisation.

Research limitations/implications

Our case focuses on that of a small organisation, and therefore the generalisability of findings will be somewhat limited and context specific. The number of interviews (eight) is also relatively small.

Practical implications

Insights can be drawn for the management of volunteers, alignment of personally held accountabilities of internal actors with those of organisations and emotional aspects of accountability for NGO managers and organisers.

Originality/value

NGO accountability theorisation is enhanced via the use of Levinas' Judaic writings concerning the importance of the ritual practice of ethics for the individual involved in charitable action. The intertwined nature of personal accountability of volunteers and beneficiary accountability for the organisation is emphasised.
Learning accounting through visual representations
Authors: Sithole Seedwell , Datt Ragini , de Lange Paul , Tharapos Meredith
Published: May 2021

Purpose

The purpose of this study is to investigate the effectiveness of diagrammatic visualisation techniques versus sentential learning contexts in an accounting subject using the theoretical lens of cognitive load theory (CLT).

Design/methodology/approach

The present study used four groups of students; two groups completed a task using diagrammatic visualisation learning materials, with one of the groups undertaking their leaning activities collaboratively and another on an individual basis, whereas two comparison groups were given a sentential learning context without diagrams, with one group undertaking their leaning activities collaboratively and the other individually. In addition to performance grades, cognitive load self-report scores were also elicited from participants.

Findings

The findings of this study indicate support for diagrammatic visualisation techniques for students working collaboratively. Compared with sentential learners, the authors find significantly improved test performance for students who work collaboratively in a diagrammatic visualisation environment. Students in the visualisation environments obtained higher grades than those in the sentential group. In terms of mental effort, students in the visualisation conditions reported the lowest cognitive load.

Practical implications

The authors conclude that diagrammatic visualisation learning techniques enhance student performance outcomes, particularly for those who work collaboratively. CLT assists in the understanding of the mental processes involved in learning. Instructional designers need to consider CLT when developing diagrammatic visualisation material to enable students to obtain the best possible learning outcomes.

Originality/value

This study addresses a gap in the literature by examining the use of diagrammatic visualisation materials as an alternative to text when learning accounting. The study explores the effect of visualisation material on students’ cognitive load by analysing their mental effort. The study contributes useful findings on visualisation as a conduit to enhancing the understanding of accounting using CLT principles.
New results for the realization of interfered direct-form digital filters with single two's complement nonlinearity
Authors: Kumar Mani Kant , Jha Nishant
Published: May 2021

Purpose

This paper deals with the problem of input/output-to-state stability (IOSS) of direct-form digital filters, which simultaneously contain external disturbances and two's complement nonlinearity. The nonlinearity under consideration is confined to the sector [–1, 1], which contains saturation, zeroing, two's complement and triangular.

Design/methodology/approach

The proposed condition is based on IOSS approach, which is capable of providing a framework for checking and analysing the stability of nonlinear system based on input as well as output information.

Findings

A linear matrix inequality (LMI)-based new sufficient criterion for the IOSS of the suggested system is obtained. The obtained criterion is capable of detecting the output-to-state stability (OSS) and asymptotic stability of direct-form digital filters with zero external disturbances. In addition, state-norm estimator for the filter under consideration is constructed by adopting an exponential-decay IOSS criterion. Several examples are provided to illustrate the usefulness of the proposed criteria.

Originality/value

The result of the paper is introduced for the first time, and it is suitable for stability analysis of interfered direct-form digital filter with two's complement overflow using IOSS approach.
Formation and management of public debt sustainability on the example of the Republic of Kazakhstan and the Russian Federation
Authors: Mukhtarkhan Asset
Published: May 2021

Purpose

The purpose of this paper is to study debt sustainability of countries with a resource-based economy on the example of the Republic of Kazakhstan and the Russian Federation.

Design/methodology/approach

Macroeconomic indicators and data on external and internal public debt of the Republic of Kazakhstan and the Russian Federation for the period from 2007 to 2019 were analyzed using quantitative, qualitative, comparative, descriptive and graphical methods. Based on the collected data, the indicators were calculated, analyzed and compared, taking into account the threshold values, using The Debt Sustainability Framework for Low-Income Countries of the International Monetary Fund and the World Bank.

Findings

The results of the study showed that the indicators of the public debt of both the Republic of Kazakhstan and the Russian Federation, during the period covered by the study, were in the zone of reduced risk and were stable. In addition, the study revealed a slight shift in the structure of the public debt of the Republic of Kazakhstan toward a decrease in the share of domestic borrowing (from 67% to 55%), whereas in the structure of the Russian public debt, the share of domestic borrowing increased significantly (from 52% to 74%).

Originality/value

The results of this study can be applied by scientists to analyze the sustainability of public debt in various countries and regions, as well as by officials to determine the fiscal and budgetary policies of the Republic of Kazakhstan and the Russian Federation, as well as other states.
Prioritizing Green HRM practices from policymaker’s perspective
Authors: Mehrajunnisa Mehrajunnisa , Jabeen Fauzia , Faisal Mohd Nishat , Mehmood Khalid
Published: May 2021

Purpose

This study aims to identify and prioritize Green human resource management (GHRM) practices from the policymaker’s perspective in the United Arab Emirates (UAE)-based manufacturing and service sectors to facilitate sustainable environmental performance.

Design/methodology/approach

Drawing upon the ability–motivation–opportunity (AMO) and corporate environmentalism theory, this study uses the analytic hierarchy process (AHP), a multi-criteria decision-making model, to rank the most influential enablers of GHRM practices. Data were collected from 24 C-suite executives of UAE-based manufacturing and service units.

Findings

Top management orientation for Green, Green organizational culture and Green corporate strategic planning were the most critical enablers that promote GHRM practices in the UAE’s manufacturing and service firms. Past research has mostly overlooked the strategic variables and focused only on organizational level antecedents based on HR bundles of practices.

Research limitations/implications

Data were collected only from UAE firms, hence limiting its generalizability. The study shall help organizations operating in emerging countries adopt the best GHRM practices toward Green goal agendas.

Originality/value

This research provides an AHP framework that can be used to conceptualize and prioritize GHRM practices, which aids in a firm’s Green decision-making and transition toward sustainable Green growth. This study furthers understanding of GHRM practices play out at the various levels-of-analysis within organizations to present a comprehensive paucity of integrative and multi-level studies over recent years. The study may be relevant for other organizations in other national contexts with similar governance homogeneity.
A novel series-parallel hybrid robot for climbing transmission tower
Authors: Yao Yanzhang , Wang Wei , Qiao Yue , He Zhihang , Liu Fusheng , Li Xuelong , Liu Xinxin , Zou Dehua , Zhang Tong
Published: May 2021

Purpose

The purpose of this paper is to describe the design and development of a novel series-parallel robot, which aims to climb on the transmission tower.

Design methodology approach

This study introduces a hybrid robot, which consists of adsorption and two 3-degree of freedom (DOF) translation parallel legs connected by a body linkage. The DOF of the legs ensures that the robot can move on the climbing plane, also contribute to a compact design of the robot. An electromagnet is used to adsorb onto the transmission tower, simplifying the overall structure. Based on the robot design, this paper further defines its climbing gait and adopt the 6th B-spline curves for climbing trajectory planning under different working environments.

Findings

The developed prototype that implements the design of the robot, which was used in simulation and experiments, showing that the robot is capable of climbing in the test environments with the planned climbing gait.

Originality value

The hybrid robot is able to climb under varying degrees of inclinations and cross the obstacles, and the magnetic attraction can ensure stable climbing.
Corporate cash holdings and firm life cycle: evidence from China
Authors: Rehman Ajid Ur , Ahmad Tanveer , Hussain Shahzad , Hassan Shoaib
Published: May 2021

Purpose

The purpose of this paper is to investigate how corporate cash holdings changes across firm life cycle and how firms undergo heterogeneous dynamic cash adjustment as they advance from one stage to the next stage.

Design/methodology/approach

This study uses an extensive data set of 2,994 Chinese A-listed firms. The authors use generalized method of moments (GMM) and Fisher Panel unit root testing to investigate the targeting behavior of Chinese firms.

Findings

The uni-variate investigation reveals that firms in the growth stage exhibits the highest cash levels and firms in the decline stage report the lowest cash levels. As growth firms have high investment needs, they may require raising external capital to meet investment needs. To avoid the costly external financing, firms in growth stage tend to hold more cash. The GMM estimation reveals that along all the phases of firm life cycle there are evidences of trade-off behavior of corporate cash holdings. The authors report that adjustment rate increases as firms enters into the growth stage.

Practical implications

The findings provide both theoretical and practical insight to align cash policies with the available strategic choices along firm life cycle in an emerging market characterized by market imperfections.

Originality/value

The study is unique from the context that it is applying robust methodology to one of rarely investigated area in corporate cash policy. The peculiar Chinese study setting characterized by higher information asymmetry, high cost of external financing and heterogeneous access to financing sources provide theoretical and empirical underpinnings to investigate and gain insight about how corporate cash policy can be aligned with strategic choices available across different stages of life cycle.
Unmasking conflict in vertical coopetition
Authors: Rajala Anni , Tidström Annika
Published: May 2021

Purpose

The purpose of this study is to increase understanding about vertical coopetition from the perspective of interrelated conflict episodes on multiple levels.

Design/methodology/approach

The empirical part is based on a qualitative single case study of a coopetitive buyer-supplier relationship in the manufacturing sector.

Findings

Conflicts in vertical coopetition evolve from being merely functional and task-related to becoming dysfunctional and relationship-related, as the level of competition increases. The nature of conflict episodes influences the development of vertical coopetition, and therefore, the interrelatedness of conflict episodes is important to acknowledge.

Practical implications

Although a conflict is considered functional within a company, it may still be dysfunctional as far as the coopetitive relationship with the buyer or seller is concerned. Competition may trigger conflicts related to protecting own technology and knowledge, which may lead to termination of the cooperation, therefore coopetition should be managed in a way that balance sharing and protecting important knowledge to get advantages of coopetition.

Originality/value

The findings enhance prior research on vertical coopetition by offering new perspectives on causes of conflicts, their management, outcomes and types. The value of taking a multilevel approach lies in the ability to show how conflicts occur and influence other conflicts through the interrelatedness of conflict elements on different levels.
A transaction cost approach for public procurement
Authors: Rokkan Aksel I. , Haugland Sven A.
Published: May 2021

Purpose

This paper aims to develop a theoretical framework based on transaction cost economics that identifies key factors shaping public agencies’ governance of supplier relationships and related performance implications.

Design/methodology/approach

The paper presents an extended transaction cost framework for research on public procurement (PP) with a corresponding set of propositions. Transaction cost theory and specific features of and challenges to the PP function identified in extant literature constitute the main elements of the framework.

Findings

This conceptual paper makes three sets of proposals. First, public agencies tend to rely on market governance of supplier relationships and when PP deploys non-market governance, such governance tends to be of a unilateral (vs bilateral) kind. Second, increases in purchasing competence and autonomy of PP and particularly if implemented in tandem, will reduce PP’s overreliance on market governance and increase PP’s use of non-market governance. Third, PP should perform better for less complex transactions – and when contracting complexity relates to safeguarding of specific assets rather than when complexity relates to environmental and behavioral uncertainty. Increases in competence and autonomy should increase PP’s performance, particularly for complex transactions.

Practical implications

Public agencies may be in a better position to align governance solutions with transaction complexities by developing their procurement competence, decentralizing procurement decisions and increasing the flexibility of national and international procurement regulations. Private companies selling to public agencies need to be aware of and able to adapt to PP practices such as extensive use of market governance and unilateral governance as the primary form of non-market governance.

Social implications

The paper discusses how public agencies can improve procurement performance through better alignment of governance of supplier relationships with transaction attributes and thereby increase the quality of public services.

Originality/value

The paper relies on a well-established theoretical perspective, enabling identification (and, potentially, correction) of governance misalignment in the public sector.
Psychological contract breach and teachers' organizational commitment: mediating roles of job embeddedness and leader-member exchange
Authors: Amoah Veronica Serwaa , Annor Francis , Asumeng Maxwell
Published: May 2021

Purpose

The study examined the relationship between psychological contract breach and organizational commitment and whether leader-member exchange and job embeddedness mediate this relationship.

Design/methodology/approach

The study adopted a quantitative approach and is based on a sample of 298 teachers in basic schools in Accra, Ghana. Participants completed surveys with standardized measures on psychological contract breach, job embeddedness, leader-member exchange and organizational commitment. Hypothesized relationships were tested using structural equation modeling in AMOS 21.0.

Findings

Psychological contract breach had a direct negative relationship with affective and normative commitment but had no significant direct relationship with continuance commitment. Psychological contract breach was indirectly related to affective and normative commitment through both job embeddedness and leader-member exchange, and indirectly related to continuance commitment through only job embeddedness.

Practical implications

Findings from the study suggest that employers' failure to fulfill their obligations to employees has significant potential cost to the organization, and underscore the need for managers, particularly in educational institutions, to institute measures to eliminate or minimize the occurrence of psychological contract breach.

Originality/value

The study contributes to research examining antecedents of organizational commitment as well as the mechanisms linking psychological contract breach to organizational commitment in the educational context.
Distributed model for customer churn prediction using convolutional neural network
Authors: Tariq Muhammad Usman , Babar Muhammad , Poulin Marc , Khattak Akmal Saeed
Published: May 2021

Purpose

The purpose of the proposed model is to assist the e-business to predict the churned users using machine learning. This paper aims to monitor the customer behavior and to perform decision-making accordingly.

Design/methodology/approach

The proposed model uses the 2-D convolutional neural network (CNN; a technique of deep learning). The proposed model is a layered architecture that comprises two different phases that are data load and preprocessing layer and 2-D CNN layer. In addition, the Apache Spark parallel and distributed framework is used to process the data in a parallel environment. Training data is captured from Kaggle by using Telco Customer Churn.

Findings

The proposed model is accurate and has an accuracy score of 0.963 out of 1. In addition, the training and validation loss is extremely less, which is 0.004. The confusion matric results show the true-positive values are 95% and the true-negative values are 94%. However, the false-negative is only 5% and the false-positive is only 6%, which is effective.

Originality/value

This paper highlights an inclusive description of preprocessing required for the CNN model. The data set is addressed more carefully for the successful customer churn prediction.
Municipal waste management and electrical energy generation from solid waste: a mathematical programming approach
Authors: Valizadeh Jaber , Mozafari Peyman , Hafezalkotob Ashkan
Published: May 2021

Purpose

Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. The purpose of this study is to design a new model for municipal waste collection vehicle routing problems with time windows and energy generating from waste. To this purpose, a bi-objective model is presented with the objectives of increasing the income of waste recycles and energy generation from waste and reducing emissions from environmental pollutants.

Design/methodology/approach

A bi-objective model is presented with the objectives of increasing income of recycles trade and energy generation and reducing emissions from environmental pollutants. Concerning the complexity of the model and its inability to solve large-scale problems, non-dominated sorting genetic algorithms and multi-objective particle swarm optimization algorithms are applied.

Findings

In this research, an integrated approach to urban waste collection modeling that coordinates the various activities of waste management in the city of Kermanshah and energy generation from waste are provided. Besides, this study calculates the criteria that show the environmental effects of municipal waste. The proposed model helps to collect municipal wastes in the shortest possible time in addition to reducing the total cost, revenues from the sale of recycled materials and energy production.

Originality/value

The proposed model boosts the current understanding of the waste management and energy generation of waste. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.
Predictors of recycling behavior: the role of self-conscious emotions
Authors: Haj-Salem Narjes , Al-Hawari MohD Ahmad
Published: May 2021

Purpose

The purpose of this study is to develop a model that integrates self-conscious emotions (i.e. anticipated guilt and anticipated pride) alongside the theory of planned behavior’s key explanatory factors to challenge the idea that recycling behavior is driven mainly by cognitive factors. The model is empirically validated in the United Arab Emirates (UAE), a region where research are lacking despite generating one of the highest per capita solid waste and holding one of the lowest recycling rates.

Design/methodology/approach

The data was collected from the general public in the UAE using a two-wave survey (n = 287). The first wave of data collection measured the constructs except for the actual recycling behavior. The second wave assessed the respondent’s self-reported recycling behavior for the previous fortnight.

Findings

Anticipated guilt, subjective norms, perceived effort and recycling knowledge are the main drivers of the intention to recycle. The latter impacts the actual recycling behavior positively. Attitude toward recycling and anticipated pride failed to predict the intention to recycle. Awareness of consequences triggers only anticipated pride, while the degree of concern is a significant predictor of both anticipated pride and guilt.

Practical implications

One key implication of this research is that governments in the Middle East have not only to focus on cognitive factors but also emotions to promote recycling behavior.

Originality/value

This study adds to the pro-environmental literature by showing that the decision to recycle is not only based on cognitive factors but also anticipated guilt. It is also one of the first that explore recycling behavior in the UAE.