bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteome allocation and the evolution of metabolic cross-feeding
Authors: Labourel Florian J. F. , Daubin Vincent , Menu Frédéric , Rajon Etienne
Published: December 2021

Metabolic cross-feeding (MCF) is a widespread type of ecological interaction where organisms share nutrients. In a common instance of MCF, an organism incompletely metabolises sugars and releases metabolites that are used by another as a carbon source to produce energy. Why would the former waste edible food, and why does this preferentially occur at specific locations in the sugar metabolic pathway (acetate and glycerol are preferentially exchanged) have challenged evolutionary theory for decades. Addressing these questions requires to model the cellular features involved; to this end, we built an explicit model of metabolic reactions, including their enzyme-driven catalysis and the cellular constraints acting on the proteome that may incur a cost to expressing all enzymes along a pathway. After showing that cells should in principle prioritise upstream reactions when metabolites are restrained inside the cell, we investigate how the diffusivity of these metabolites may trigger the emergence of MCF in a population. We find that the occurrence of MCF is rare and requires that an intermediate metabolite be extremely diffusive: indeed, up to high membrane permeability coefficients, the expected evolutionary outcome is not a diversification that resembles MCF but a single genotype that instead overexpresses downstream enzymes. Only at very high levels of membrane permeability and under distinctive sets of parameters should the population diversify and MCF evolve. These results help understand the origins of simple microbial communities, and may later be extended to investigate how evolution has progressively built up today’s extremely diverse communities.

Significance statement

Can two species thrive on a single energetic resource? While the competitive exclusion principle predicts that one in the pair should go extinct, it may occur that an organism releases partly metabolised molecules in the environment, securing an ecological niche for a second organism in a specialisation process called metabolic cross-feeding. Here we investigate how evolution may favor the waste of a useful resource using a model that considers how a cell packed with proteins may be less efficient, hence favoring a shortening of metabolic pathways in order to reduce cell packing. Our model indicates that such specialisation only occurs under restricted conditions. Incidentally, this makes the signatures of cross-feeding, such as which metabolites are preferentially involved, quite predictable.
Targeting macrophages with CAR-T cells delays solid tumor progression and enhances anti-tumor immunity
Authors: Sánchez-Paulete Alfonso R. , Mateus-Tique Jaime , Mollaoglu Gurkan , Nielsen Sebastian R. , Marks Adam , Lakshmi Ashwitha , Pia Luisanna , Baccarini Alessia , Merad Miriam , Brown Brian D.
Published: December 2021

Tumor-associated macrophages (TAMs) are one of the most abundant cell types in many solid tumors and typically exert protumor effects. This has led to an interest in macrophage-depleting agents for cancer therapy, but approaches developed to date have had limited success in clinical trials. Here, we report the development of a strategy for TAM depletion in mouse solid tumor models using chimeric antigen receptor (CAR) T cells targeting the macrophage marker F4/80 (F4.CAR-T). F4.CAR-T cells effectively killed macrophages in vitro and in vivo without toxicity. When injected into mice bearing orthotopic lung tumors, F4.CAR-T cells infiltrated tumor lesions and delayed tumor growth comparably to PD1 blockade, and significantly extended mouse survival. Anti-tumor effects were mediated by F4.CAR-T-produced IFN-γ, which promoted upregulation of MHC molecules on cancer cells and tumor-infiltrating myeloid cells. Notably, F4.CAR-T promoted expansion of endogenous CD8 T cells specific for tumor-associated antigens and led to immune editing of highly antigenic tumor cell clones. Antitumor impact was also observed in mouse models of ovarian and pancreatic cancer. These studies provide proof-of-principle evidence to support CAR-T targeting of TAMs as a means to enhance antitumor immunity.
Mutational robustness changes during long-term adaptation in laboratory budding yeast populations
Authors: Johnson Milo S. , Desai Michael M.
Published: December 2021

As an adapting population traverses the fitness landscape, its local neighborhood (i.e., the collection of fitness effects of single-step mutations) can change shape because of interactions with mutations acquired during evolution. These changes to the distribution of fitness effects can affect both the rate of adaptation and the accumulation of deleterious mutations. However, while numerous models of fitness landscapes have been proposed in the literature, empirical data on how this distribution changes during evolution remains limited. In this study, we directly measure how the fitness landscape neighborhood changes during laboratory adaptation. Using a barcode-based mutagenesis system, we measure the fitness effects of 91 specific gene disruption mutations in genetic backgrounds spanning 8,000-10,000 generations of evolution in two constant environments. We find that the mean of the distribution of fitness effects decreases in one environment, indicating a reduction in mutational robustness, but does not change in the other. We show that these distribution-level patterns result from biases in variable patterns of epistasis at the level of individual mutations, including fitness-correlated and idiosyncratic epistasis.
Phospho-proteomics reveals that RSK signaling is required for proliferation of natural killer cells stimulated with IL-2 or IL-15
Authors: MacMullan Melanie A. , Wang Pin , Graham Nicholas A.
Published: December 2021

Natural killer (NK) cells are cytotoxic lymphocytes that play a critical role in the innate immune system. Although cytokine signaling is crucial for the development, expansion, and cytotoxicity of NK cells, the signaling pathways stimulated by cytokines are not well understood. Here, we sought to compare the early signaling dynamics induced by the cytokines interleukin (IL)-2 and IL-15 using liquid chromatography-mass spectrometry (LC-MS)-based phospho-proteomics. Following stimulation of the immortalized NK cell line NK-92 with IL-2 or IL-15 for 5, 10, 15, or 30 minutes, we identified 8,692 phospho-peptides from 3,023 proteins. Comparing the kinetic profiles of 3,619 fully quantified phospho-peptides, we found that IL-2 and IL-15 induced highly similar signaling in NK-92 cells. Among the IL-2/IL-15-regulated phospho-sites were both well-known signaling events like the JAK/STAT pathway and novel signaling events with potential functional significance including LCP1 Ser5, PAK2 Ser141, and STK17B Ser12. Using bioinformatic approaches, we sought to identify kinases regulated by IL-2/IL-15 stimulation and found that the p90 ribosomal S6 kinase (p90RSK) family was activated by both cytokines. Using pharmacological inhibitors, we then discovered that RSK signaling is required for IL-2 and IL-15-induced proliferation in NK-92 cells. Taken together, our analysis represents the first phospho-proteomic characterization of cytokine signaling in NK cells and increases our understanding of how cytokine signaling regulates NK cell function.
A deep learning approach to real-time HIV outbreak detection using genetic data
Authors: Kupperman Michael D. , Leitner Thomas , Ke Ruian
Published: December 2021

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands.

Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0≥ 3, and overall a specificity exceeding 85% and sensitivity better than 70%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

Author summary

The analysis of pathogen genomic data to analyze epidemics at scale is constrained by the computational cost associated with phylogenetic tree reconstruction. As a fast and efficient alternative, we employed convolutional neural networks to analyze evolutionary pairwise distance matrices as images to perform classifications of the current epidemiological situation of a growing public health sequence database. We used simulated data to train and test our model, and as validation we accurately mapped the start and end of two linked well-documented HIV-1 outbreaks in the backdrop of ongoing slower HIV spread. Thus, our new approach is efficient, accurate, scalable, and can analyze data in real time.
Nutrigenomic Regulation of Sensory Plasticity
Authors: Sung Hayeon , Vaziri Anoumid , Wilinski Daniel , Woerner Riley K.R. , Freddolino Peter L. , Dus Monica
Published: December 2021

Diet profoundly influences brain physiology, but how nutritional information is transmuted into neural activity and behavior changes remains elusive. Here we show that the metabolic enzyme O-GlcNAc Transferase (OGT) moonlights on the chromatin of the D. melanogaster gustatory neurons to instruct changes in chromatin accessibility and transcription that underlie sensory adaptations to a high sugar diet. OGT works synergistically with the Mitogen Activated Kinase/Extracellular signal Regulated Kinase (MAPK/ERK) rolled and its effector stripe (also known as EGR2 or Krox20) to integrate activity information. OGT also cooperates with the epigenetic silencer Polycomb Repressive Complex 2.1 (PRC2.1) to decrease chromatin accessibility and repress transcription in the high sugar diet. This integration of nutritional and activity information changes the taste neurons’ responses to sugar and flies’ ability to sense sweetness. Our findings reveal how nutrigenomic signaling generates cell-specific responses to global nutrient variations.
Environmental carcinogens disproportionally mutate genes implicated in neurodevelopmental disorders
Authors: Baker Brennan H. , Zhang Shaoyi , Simon Jeremy M. , McLarnan Sarah M. , Chung Wendy K. , Pearson Brandon L.
Published: December 2021

De novo mutations contribute to a large proportion of sporadic psychiatric and developmental disorders, yet the potential role of environmental carcinogens as drivers of causal de novo mutations in neurodevelopmental disorders is poorly studied. We demonstrate that several mutagens, including polycyclic aromatic hydrocarbons (PAHs), disproportionately mutate genes related to neurodevelopmental disorders including autism spectrum disorders (ASD), schizophrenia, and attention deficit hyperactivity disorder (ADHD). Other disease genes including amyotrophic lateral sclerosis (ALS), Alzheimer’s disease, congenital heart disease, orofacial clefts, and coronary artery disease were generally not mutated more than expected. Our findings support a new paradigm of neurodevelopmental disease etiology driven by a contribution of environmentally induced rather than random mutations.
MixEHR-Guided: A guided multi-modal topic modeling approach for large-scale automatic phenotyping using the electronic health record
Authors: Ahuja Yuri , Zou Yuesong , Verma Aman , Buckeridge David , Li Yue
Published: December 2021

Electronic Health Records (EHRs) contain rich clinical data collected at the point of the care, and their increasing adoption offers exciting opportunities for clinical informatics, disease risk prediction, and personalized treatment recommendation. However, effective use of EHR data for research and clinical decision support is often hampered by a lack of reliable disease labels. To compile gold-standard labels, researchers often rely on clinical experts to develop rule-based phenotyping algorithms from billing codes and other surrogate features. This process is tedious and error-prone due to recall and observer biases in how codes and measures are selected, and some phenotypes are incompletely captured by a handful of surrogate features. To address this challenge, we present a novel automatic phenotyping model called MixEHR-Guided (MixEHR-G), a multimodal hierarchical Bayesian topic model that efficiently models the EHR generative process by identifying latent phenotype structure in the data. Unlike existing topic modeling algorithms wherein the inferred topics are not identifiable, MixEHR-G uses prior information from informative surrogate features to align topics with known phenotypes. We applied MixEHR-G to an openly-available EHR dataset of 38,597 intensive care patients (MIMIC-III) in Boston, USA and to administrative claims data for a population-based cohort (PopHR) of 1.3 million people in Quebec, Canada. Qualitatively, we demonstrate that MixEHR-G learns interpretable phenotypes and yields meaningful insights about phenotype similarities, comorbidities, and epidemiological associations. Quantitatively, MixEHR-G outperforms existing unsupervised phenotyping methods on a phenotype label annotation task, and it can accurately estimate relative phenotype prevalence functions without gold-standard phenotype information. Altogether, MixEHR-G is an important step towards building an interpretable and automated phenotyping system using EHR data.
Hilltopping influences spatial dynamics in a patchy population of tiger moths
Authors: Pepi Adam , Grof-Tisza Patrick , Holyoak Marcel , Karban Richard
Published: December 2021

Dispersal is a key driver of spatial population dynamics. Dispersal behavior may be shaped by many factors, such as mate-finding, the spatial distribution of resources, or wind and currents, yet most models of spatial dynamics assume random dispersal. We examined the spatial dynamics of a day-flying moth species (Arctia virginalis) that forms mating aggregations on hilltops (‘hilltopping’) based on long-term adult and larval population censuses. Using time-series models, we compared spatial population dynamics resulting from empirically-founded hilltop-based connectivity indices, and modeled the interactive effects of temperature, precipitation, and density dependence. Model comparisons supported hilltop-based connectivity metrics over random connectivity, suggesting an effect of hilltopping behavior on dynamics. We also found strong interactive effects of temperature and precipitation on dynamics. Simulations based on fitted time series models showed lower patch occupancy and regional synchrony, and higher colonization and extinction rates when hilltopping was included, with potential implications for the probability of persistence of the patch network. Overall, our results show the potential for dispersal behavior to have important effects on spatial population dynamics and persistence, and we advocate inclusion of such non-random dispersal in metapopulation models.
Benefits of integrated screening and vaccination for infection control
Authors: Rabil Marie Jeanne , Tunc Sait , Bish Douglas R. , Bish Ebru K.
Published: December 2021

Importance

Screening and vaccination are essential in the fight against infectious diseases, but need to be integrated and customized based on community and disease characteristics.

Objective

To develop effective screening and vaccination strategies, customized for a college campus, to reduce COVID-19 infections, hospitalizations, deaths, and peak hospitalizations.

Design, Setting, and Participants

We construct a compartmental model of disease spread for vaccination and routine screening, and study the efficacy of four mitigation strategies (routine screening only, vaccination only, vaccination with partial routine screening, vaccination with full routine screening), and a no-intervention strategy. The study setting is a hypothetical college campus of 5,000 students and 455 faculty members, with 11 undetected, asymptotic SARS-CoV-2 infections at the start of an 80-day semester. For sensitivity analysis, we vary the screening frequency, daily vaccination rate, initial vaccination coverage, and screening and vaccination compliance; and consider three scenarios that represent low/medium/high transmission rates and test efficacy. Model parameters come from publicly available or published sources.

Results

With low initial vaccination coverage, even aggressive vaccination and screening result in a high number of infections: 1,024/2,040 (1,532/1,773) with routine daily (every other day) screening of the unvaccinated; 275/895 with daily screening extended to the newly vaccinated in base- and worst-case scenarios, with reproduction numbers 4.75 and 6.75, respectively, representative of COVID-19 Delta variant. With the emergence of the Omicron variant, the reproduction number may increase and/or effective vaccine coverage may decrease if a booster shot is needed to maximize vaccine efficacy.

Conclusion

Integrated vaccination and routine screening can allow for a safe opening of a college when initial vaccination coverage is sufficiently high. The interventions need to be customized considering the initial vaccination coverage, estimated compliance, screening and vaccination capacity, disease transmission and adverse outcome rates, and the number of infections/peak hospitalizations the college is willing to tolerate.
The chemical Langevin equation for biochemical systems in dynamic environments
Authors: Ham Lucy , Coomer Megan A. , Stumpf Michael P. H.
Published: December 2021

Modelling and simulation of complex biochemical reaction networks form cornerstones of modern biophysics. Many of the approaches developed so far capture temporal fluctuations due to the inherent stochasticity of the biophysical processes, referred to as intrinsic noise. Stochastic fluctuations, however, predominantly stem from the interplay of the network with many other — and mostly unknown — fluctuating processes, as well as with various random signals arising from the extracellular world; these sources contribute extrinsic noise. Here we provide a computational simulation method to probe the stochastic dynamics of biochemical systems subject to both intrinsic and extrinsic noise. We develop an extrinsic chemical Langevin equation—a physically motivated extension of the chemical Langevin equation— to model intrinsically noisy reaction networks embedded in a stochastically fluctuating environment. The extrinsic CLE is a continuous approximation to the Chemical Master Equation (CME) with time-varying propensities. In our approach, noise is incorporated at the level of the CME, and can account for the full dynamics of the exogenous noise process, irrespective of timescales and their mismatches. We show that our method accurately captures the first two moments of the stationary probability density when compared with exact stochastic simulation methods, while reducing the computational runtime by several orders of magnitude. Our approach provides a method that is practical, computationally efficient and physically accurate to study systems that are simultaneously subject to a variety of noise sources.
Characteristics, origin, and potential for cancer diagnostics of ultrashort plasma cell-free DNA
Authors: Hudecova Irena , Smith Christopher G. , Hänsel-Hertsch Robert , Chilamakuri Chandra S. , Morris James A. , Vijayaraghavan Aadhitthya , Heider Katrin , Chandrananda Dineika , Cooper Wendy N. , Gale Davina , Garcia-Corbacho Javier , Pacey Simon , Baird Richard D. , Rosenfeld Nitzan , Mouliere Florent
Published: December 2021

Current evidence suggests that plasma cell-free DNA (cfDNA) is fragmented around a mode of 166 bp. Data supporting this view has been mainly acquired through the analysis of double-stranded cfDNA. The characteristics and diagnostic potential of single-stranded and damaged double-stranded cfDNA in healthy individuals and cancer patients remain unclear. Here, through a combination of high-affinity magnetic bead–based DNA extraction and single-stranded DNA sequencing library preparation (MB-ssDNA), we report the discovery of a large proportion of cfDNA fragments centered at ∼50 bp. We show that these “ultrashort” cfDNA fragments have a greater relative abundance in plasma of healthy individuals (median = 19.1% of all sequenced cfDNA fragments, n = 28) than in plasma of patients with cancer (median = 14.2%, n = 21, P < 0.0001). The ultrashort cfDNA fragments map to accessible chromatin regions of blood cells, particularly in promoter regions with the potential to adopt G-quadruplex (G4) DNA secondary structures. G4-positive promoter chromatin accessibility is significantly enriched in ultrashort plasma cfDNA fragments from healthy individuals relative to patients with cancers (P < 0.0001), in whom G4-cfDNA enrichment is inversely associated with copy number aberration-inferred tumor fractions. Our findings redraw the landscape of cfDNA fragmentation by identifying and characterizing a novel population of ultrashort plasma cfDNA fragments. Sequencing of MB-ssDNA libraries could facilitate the characterization of gene regulatory regions and DNA secondary structures via liquid biopsy. Our data underline the diagnostic potential of ultrashort cfDNA through classification for cancer patients.
Crystal structures of 3/4-pyridyl-based thiosemicarbazones and related Cu and Ni coordination compounds
Authors: Lobana Tarlok Singh , Kaushal Mani , Bhatia Robin , Bala Ritu , Butcher Ray J. , Jasinksi Jerry P.
Published: December 2021

In this investigation, the crystal structures of the thio-ligands 3-formylpyridine 4-phenylthiosemicarbazone (C13H12N4S,1) and 4-benzoylpyridine 4-ethylthiosemicarbazone (C15H16N4S,2), and of two new coordination compounds, chlorido(3-formylpyridine 4-phenylthiosemicarbazone-κS)bis(triphenylphosphane-κP)copper(I) acetonitrile monosolvate, [CuCl(C13H12N4S)(C18H15P)2]·CH3CN,3, and bis(3-formylpyridine 4-ethylthiosemicarbazonato-κ2N1,S)nickel(II), [Ni(C9H11N4S)2],4, are reported. In complex3, the thio-ligand coordinates in a neutral form to the Cu atom through its S-donor atom, and in complex4, the anionic thio-ligand chelates to the Ni atom through N- and S-donor atoms. The geometry of complex3is distorted tetrahedral [bond angles 99.70 (5)–123.23 (5)°], with the P—Cu—P bond angle being the largest, while that of complex4is square planar, withtrans-S—Ni—S and N—Ni—N bond angles of 180°.
The landowner role in beginning farmer/rancher land access: predictors of landowners' views of extrafamilial farm transfer to a BFR
Authors: Valliant Julia C.D. , Dickinson Stephanie , Zhang Yijia , Golzarri-Arroyo Lilian , Farmer James R.
Published: December 2021

Purpose

Beginning farmers and ranchers (BFRs) are more likely to access land through an unrelated landowner than through family. Thus, farm and ranch owners who might transfer their land or businesses out of family are potential sources of land access for BFRs and are the most frequent participants in incentive programs to facilitate land transfer to BFRs. To assist in identifying landowners who might transfer out of family, the paper aims to explore similarities and differences between landowners according to their expectations for intra-familial versus extra-familial farm transfer.

Design/methodology/approach

Pairwise and regression analysis of USA Midwestern and Plains landowners' responses to an online survey (n = 322).

Findings

Landowners who might transfer out of family were likely to need the proceeds from a land sale to finance their retirement. Landowners' financial needs interacted with their widespread interest in transferring to a BFR such that 97% of owners who expected extra-familial transfer wanted to transfer to a BFR. There were also statistical patterns around the size of owners' landholdings in relation to their transfer plans.

Research limitations/implications

This exploratory inquiry suggests patterns for future research to examine, especially around landowners' juxtaposition of their retirement income and their interest in transferring to a BFR and how to align these priorities and values.

Originality/value

By exploring the characteristics of landowners who are the most likely to provide land access to BFRs, the authors begin to examine how to target these owners in program outreach. Patterns for further exploration point to landowners' financial needs in relation to their interest in helping a BFR to get started in agriculture.
Exploring the design risk factors for modular integrated construction projects
Authors: Wuni Ibrahim Yahaya , Shen Geoffrey Qiping , Antwi-Afari Maxwell Fordjour
Published: December 2021

Purpose

Modular integrated construction (MiC) is considered as a process innovation to improve the performance of construction projects. However, effective delivery of MiC projects requires management of risks and uncertainties throughout its delivery chain. Although the design stage of MiC projects is usually managed with limited knowledge based on highly uncertain data and associated with epistemic uncertainties, MiC design risks have not received adequate research attention relative to other stages. The purpose of this paper is to conduct a knowledge-based evaluation and ranking of the design risk factors (DRFs) for MiC projects.

Design/methodology/approach

The paper reviewed the relevant literature to identify potential DRFs and validated their relevance through pilot expert review. The paper then used questionnaires to gather data from international MiC experts from 18 countries and statistically analyzed the data set.

Findings

Analysis results showed that the five most significant DRFs for MiC projects include unsuitability of design for the MiC method; late involvement of suppliers, fabricators and contractors; inaccurate information, defective design and change order; design information gap between the designer and fabricator; and lack of bespoke MiC design codes and guidelines. A correlation analysis showed that majority of the DRFs have statistically significant positive relationships and could inform practitioners on the dynamic links between the DRFs.

Practical implications

The paper provides useful insight and knowledge to MiC practitioners and researchers on the risk factors that could compromise the success of MiC project designs and may inform design risk management. The dynamic linkages among the DRFs instruct the need to adopt a system-thinking philosophy in MiC project design.

Originality/value

This paper presents the first study that specifically evaluates and prioritizes the risk events at the design stage of MiC projects. It sets forth recommendations for addressing the identified DRFs for MiC projects.
Is it possible to improve the international business action towards the sustainable development goals?
Authors: Celone Andrea , Cammarano Antonello , Caputo Mauro , Michelino Francesca
Published: December 2021

Purpose

The purpose of this paper is to investigate possible improvements in the pursuit of the sustainable development goals (SDGs) by multinational enterprises (MNEs) through an analysis of the literature.

Design/methodology/approach

A critical framework based on Gleicher’s formula for change is provided after conducting a systematic literature review.

Findings

The best way to pursue the SDGs is through an integrated approach that recognises the importance of MNEs in terms of possibilities and power of action. Working towards the SDGs appears to be largely limited by three aspects of the problem: its complexity and wickedness, the genuine interest in reaching some SDGs, at the expense of profit and low foresight.

Research limitations/implications

A fundamental limitation of the study concerns, as in most of the literature on the matter, the impossibility of providing an optimal solution to the problem of meeting the SDGs, given their nature. However, formulating the best definition of the problem and its characteristics can contribute to making its management better.

Social implications

This study has social implications due to the extreme importance that many SDGs have with regard to democracy and social equity, beyond their environmental and economic aspects.

Originality/value

The claimed contribution is the value brought by the synthesis of several points of view, through the interdisciplinary analysis of the research question. The novelty consists in organising the literature according to the formula for change.
Determinants of the exit value in European venture capital-backed technology startups
Authors: Montanaro Benedetta , Cavallo Angelo , Giudici Giancarlo , Ghezzi Antonio
Published: December 2021

Purpose

This study aims to analyze the impact of different exit alternatives, investor presence and founders’ human capital on the exit value of European venture capital (VC)-backed high technology startups.

Design/methodology/approach

The empirical analysis is based on a sample of 107 European firms that obtained an exit through Merger&Acquisition (M&A) or an initial public offering (IPO) between 2010 and 2017, backed by VC investors.

Findings

This study provides empirical evidence on how different exit alternatives, investor heterogeneity and founders’ human capital may affect the exit value of European VC-backed startups. Exiting through an IPO and retaining a larger equity stake are positively correlated with the exit value. The presence of business angels and non-governmental VC firms is associated with larger valuations. Founders’ previous education was positively correlated with the exit value.

Originality/value

Exit strategies in technology startups are essential to capitalize investors’ efforts and reinvest cash into new ventures, supporting the development of entrepreneurial ecosystems and countries’ competitiveness. The results of this study provide interesting hints for policymakers and contribute to an in-depth understanding of the drivers of exit valuation for startups.
Canard-induced mixed mode oscillations as a mechanism for the Bonhoeffer-van der Pol circuit under parametric perturbation
Authors: Yu Yue , Zhang Cong , Chen Zhenyu , Zhang Zhengdi
Published: December 2021

Purpose

This paper aims to investigate the singular Hopf bifurcation and mixed mode oscillations (MMOs) in the perturbed Bonhoeffer-van der Pol (BVP) circuit. There is a singular periodic orbit constructed by the switching between the stable focus and large amplitude relaxation cycles. Using a generalized fast/slow analysis, the authors show the generation mechanism of two distinct kinds of MMOs.

Design/methodology/approach

The parametric modulation can be used to generate complicated dynamics. The BVP circuit is constructed as an example for second-order differential equation with periodic perturbation. Then the authors draw the bifurcation parameter diagram in terms of a containing two attractive regions, i.e. the stable relaxation cycle and the stable focus. The transition mechanism and characteristic features are investigated intensively by one-fast/two-slow analysis combined with bifurcation theory.

Findings

Periodic perturbation can suppress nonlinear circuit dynamic to a singular periodic orbit. The combination of these small oscillations with the large amplitude oscillations that occur due to canard cycles yields such MMOs. The results connect the theory of the singular Hopf bifurcation enabling easier calculations of where the oscillations occur.

Originality/value

By treating the perturbation as the second slow variable, the authors obtain that the MMOs are due to the canards in a supercritical case or in a subcritical case. This study can reveal the transition mechanism for multi-time scale characteristics in perturbed circuit. The information gained from such results can be extended to periodically perturbed circuits.
Analyzing the impact of financial policies on construction projects performance using system dynamics
Authors: Dabirian Shahin , Ahmadi Mostafa , Abbaspour Soroush
Published: December 2021

Purpose

The research aims to analyze the effects of financial policies on a cash flow system to meet project performance goals and improve profitability. The policies are divided into four groups; owner related, bank-related, labor-related and supplier-related policies. This research presents a developed model for planning, forecasting and managing the cash flow in construction projects using system dynamics (SD).

Design/methodology/approach

A System Dynamics (SD model is developed to evaluate the effect of different financial policies on construction project performance. By identifying the feedback loops in the cash flow system, a dynamic model is developed to forecast, plan and manage different policies, including prepayment, overbilling, loans, incentive payment, delay in payment and equipment lease.

Findings

A case study (a construction activity as part of a pharmaceutical factory development project) is used to analyze the cash flow and financing policies. The findings demonstrate the effects of different policies such as incentive payments on project cash flow estimation, which proved to reduce the project duration, improve the profit and increase the financing during the project execution.

Originality/value

The presented model would be a major attempt to estimate precisely the cash flow and the effect of employing different financial policies on project performance. Applying this model, project managers and decision-makers have the opportunity to model different financial policies concerning a variety of limiting variables applicable to each situation. Ultimately, with this, one can make more reasoned decisions and, in effect, optimize the utility of the project.
Productivity assessment of the real estate industry in China: a DEA-Malmquist index
Authors: Liu Xiao-xiao , Liu Hui-hui , Yang Guo-liang , Pan Jiao-feng
Published: December 2021

Purpose

The high-quality development of the real estate industry is crucial to the transformation of China's economy. However, few studies apply the productivity to explore the development path of the real estate industry in China. To fill this gap, this study mainly investigates the total factor productivity (TFP) of the real estate industry of 30 sample provinces in mainland China from 2007 to 2016.

Design/methodology/approach

The Malmquist index is applied to estimate the productivity (i.e. TFP) of the real estate industry, based on the data envelopment analysis (DEA). Then, the truncated tobit regression analysis explores the external influencing factors on the TFP of the real estate industry.

Findings

Through empirical analysis, it is found that the high-quality development of the real estate industry depends on the technological innovation by the real estate enterprises and the targeted policies by the provincial government. Moreover, the development of the real estate industry has a positive correlation with the growth of China's economy but a negative correlation with the development of other industries.

Practical implications

TFP mainly reveals the development status of the provincial real estate industry and identifies the driving force for exploring the high-quality development mode of the real estate sector. Furthermore, the fluctuation rule of TFP can be applied to predict the development trend of the real estate industry in the future.

Originality/value

As an application, this study measures the TFP of the Chinese real estate industry in different provinces and periods. The results have meaningful policy implications for policymakers regulating the real estate industry.
Human resource management studies in hospitality and tourism domain: a bibliometric analysis
Authors: Pelit Elbeyi , Katircioglu Esra
Published: December 2021

Purpose

Bibliometric analysis allows examining a large volume of bibliometric data within an objective perspective. The purpose of this study is to conduct a bibliometric analysis to reveal the current status of human resource management (HRM) studies while exploring research trends and future directions.

Design/methodology/approach

Web of Science was chosen to identify studies in the field. In total, 1,404 articles were selected for bibliometric analysis. The VOSviewer program was used to analyze and visualize obtained data.

Findings

The findings revealed that the most frequently used keywords were job satisfaction, hospitality, tourism, HRM and work engagement. Karatepe and Baum were the most cited authors and Inoue (2011), Felps (2009), Shaw (2011), Gursoy (2008) and Cooper (2006) were the most cited documents in HRM studies in the hospitality and tourism domain.

Research limitations/implications

The study provides some theoretical and practical implications. The study findings can give researchers and practitioners insights into the current position of HRM studies and trend topics. Besides, it can be used as a practical guide for determining potential gaps in the literature.

Originality/value

This study contributes to the literature by bringing HRM studies in the hospitality and tourism fields together and revealing the current position of the inquiry by determining the most cited authors, articles, journals, organizations and collaborations among authors.
Entrepreneurial performance of new-generation rural migrant entrepreneurs in China
Authors: Ma Hongyu , Zhang Yongmei Carol , Butler Allan , Guo Pengyu , Bozward David
Published: December 2021

Purpose

China has a new rural revitalization strategy to stimulate rural transformation through modernizing rural areas and resolving their social contradictions. While social capital is recognized as an important element to rural revitalization and entrepreneurship, research into the role of psychological capital is less developed. Therefore, this paper assesses the impact of both social and psychological capital on entrepreneurial performance of Chinese new-generation rural migrant entrepreneurs (NGRMEs) who have returned to their homes to develop businesses as part of the rural revitalization revolution.

Design/methodology/approach

Based on a survey, data were collected from 525 NGRMEs in Shaanxi province. This paper uses factor analysis to determine variables for a multiple linear regression model to investigate the impacts of dimensions of both social capital and psychological capital on NGRMEs’ entrepreneurial performance.

Findings

Through the factor analysis, social capital of these entrepreneurs consists of five dimensions (reputation, participation, networks, trust and support), psychological capital has three dimensions (innovation and risk-taking, self-efficacy and entrepreneurial happiness) and entrepreneurial performance contains four dimensions (financial, customer, learning and growth, and internal business process). Furthermore, the multiple linear regression model empirically verifies that both social capital and psychological capital significantly influence and positively correlate with NGRMEs' entrepreneurial performance.

Originality/value

This study shows the importance of how a mixture of interrelated social and psychological dimensions influence entrepreneurial performance that may contribute to the success of the Chinese rural revitalization strategy. This has serious implications when attempting to improve the lives of over 100 million rural Chinese citizens.
Impact of hydropower consumption, foreign direct investment and manufacturing performance on CO2emissions in the ASEAN-4 countries
Authors: Danmaraya Ismail Aliyu , Danlami Abubakar Hamid
Published: December 2021

Purpose

The continuous increase in the discharges of carbon emissions (CO2) in the global atmosphere and the likely negative consequences of this practice on the atmosphere draw the attention of researchers and policymakers to argue on the causes and perpetrators of CO2emissions. This paper aims to examine the impacts of hydropower consumption, FDI and manufacturing performance on CO2emissions in the Association of southeast Asian nations (ASEAN)-4 countries.

Design/methodology/approach

The study uses the data on variables, such as hydro-power consumption, FDI, manufacturing value added and CO2emissions spanning the period 1980–2015. Autoregressive Distributive Lag Bound test approach was used to assess the relationships among the variables.

Findings

The long run estimation of elasticities for all the countries indicates that the coefficient of hydro power consumption was found to be significantly related to CO2emissions only in Malaysia. Additionally, the coefficients manufacturing performance were found to be significant in influence the amount of CO2emission in all the ASEAN-4 countries. Furthermore, the coefficients of FDI inflows were found to be significant in explaining CO2emissions in Malaysia and the Philippines, respectively. In the short run, the estimated results show that all the variables were found to be significant in explaining CO2emissions in the countries under study.

Research limitations/implications

Singapore is excluded from the ASEAN-4 due to insufficient data on hydro energy consumption.

Practical implications

The study recommends that as Hydro power energy is a clean source of renewable electricity. Its consumption indicates a negative relationship with CO2emissions. The countries should emphasize more on the use of hydro source of energy than the other sources which increase the rate of CO2emissions in the atmosphere.

Originality/value

As most of the relevant previous studies did not consider the simultaneous impact of hydro energy consumption, FDI and manufacturing value added on CO2emissions in the ASEAN-4, this study is an important contribution to the existing relevant literature.
A novel approach for detection and classification of re-entrant crack using modified CNNetwork
Authors: Mahenge Shadrack Fred , Alsanabani Ala
Published: December 2021

Purpose

In the purpose of the section, the cracks that are in the construction domain may be common and usually fixed with the human inspection which is at the visible range, but for the cracks which may exist at the distant place for the human eye in the same building but can be captured with the camera. If the crack size is quite big can be visible but few cracks will be present due to the flaws in the construction of walls which needs authentic information and confirmation about it for the successful completion of the wall cracks, as these cracks in the wall will result in the structure collapse.

Design/methodology/approach

In the modern era of digital image processing, it has captured the importance in all the domain of engineering and all the fields irrespective of the division of the engineering, hence, in this research study an attempt is made to deal with the wall cracks which are found or searched during the building inspection process, in the present context in association with the unique U-net architecture is used with convolutional neural network method.

Findings

In the construction domain, the cracks may be common and usually fixed with the human inspection which is at the visible range, but for the cracks which may exist at the distant place for the human eye in the same building but can be captured with the camera. If the crack size is quite big can be visible but few cracks will be present due to the flaws in the construction of walls which needs authentic information and confirmation about it for the successful completion of the wall cracks, as these cracks in the wall will result in the structure collapse. Hence, for the modeling of the proposed system, it is considered with the image database from the Mendeley portal for the analysis. With the experimental analysis, it is noted and observed that the proposed system was able to detect the wall cracks, search the flat surface by the result of no cracks found and it is successful in dealing with the two phases of operation, namely, classification and segmentation with the deep learning technique. In contrast to other conventional methodologies, the proposed methodology produces excellent performance results.

Originality/value

The originality of the paper is to find the portion of the cracks on the walls using deep learning architecture.
A time series projection model of online seasonal demand for American wine and potential disruption in the supply channels due to COVID-19
Authors: Huq Faizul , Jones Vernon , Hensler Douglas Alfred
Published: December 2021

Purpose

This study statistically examines the shifting distribution channels in the American wine industry based on the growth trajectory of sales, seasonality and disruption due to consumers switching to online platforms. The purpose of this paper is to design a model that will have general applicability beyond the wine industry.

Design/methodology/approach

The research uses regression-based additive decomposition of time series data to predict the trajectory of the market share for the digital distribution channel. The study develops a statistical prediction model using time series data between 2007 and 2020, inclusive, sourced from US Annual Wine Reports and Bureau of Alcohol, Tobacco and Firearms databases.

Findings

The results show an increasing trajectory of wine sales through the online distribution channel with predictable seasonality. The disruptive effects of consumer switching behavior point to a steady increase in sales due both to increasing demand and accelerating switching. Nevertheless, the model shows that bricks and mortar purchases will remain strong and continue to account for the bulk of wine sales. COVID-19 has caused a step function increase in online sales but this should moderate after the crisis subsides and can be tested further.

Originality/value

This study is original in developing a model for an industry where bricks and mortar sales are growing and are expected to remain strong while there is still identifiable switching to online sales. The wine industry presents a classic case of accelerating switching behavior where there is still a strong franchise for in-store purchases. The model should have general applicability to distribution channels beyond the wine industry where steady growth, marked seasonality and disruptive consumer switching are in evidence.