bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling and Forecasting of COVID-19 New Cases in the Top 10 Infected African Countries Using Regression and Time Series Models
Authors: Argawu Alemayehu Siffir
Published: September 2020

Background

COVID-19 total cases have reached 1,083,071 (83.5%) in the top 10 infected African countries (South Africa, Egypt, Morocco, Ethiopia, Nigeria, Algeria, Ghana, Kenya, Cameroon, and Côte d’Ivoire) from Feb 14 to Sep 6, 2020. Then, this study aimed to model and forecast of COVID-19 new cases in these top 10 infected African countries.

Methods

In this study, the COVID 19 new cases data have been modeled and forecasted using curve estimation regression and time series models for these top 10 infected African countries from Feb 14 to Sep 6, 2020.

Results

From July to August, the prevalence of COVID-19 cumulative cases was declined in South Africa, Cote d□Ivoire, Egypt, Ghana, Cameron, Nigeria, and Algeria by 31%, 26%, 22%, 20%, 14%, 12%, and 4%, respectively. But, it was highly raised in Ethiopia and Morocco by 41%, and 38% in this period, respectively. In Kenya, it was raised only by 1%. In this study, the cubic regression models for the ln(COVID-19 new cases) data were relatively the best fit for Egypt, Ethiopia, Kenya, Morocco, Nigeria and South Africa. And, the quadratic regression models for the data were the best fit for Cameroon, Cote d□Ivoire and Ghana. The Algeria data was followed the logarithmic regression model. In the time series analysis, the Algeria, Egypt, and South Africa COVID-19 new cases data have fitted the ARIMA (0,1,0), ARIMA (0,1,0), and ARIMA (0,1,14) models, respectively. The Cameroon, Cote d’Ivoire, Ghana, and Nigeria data have fitted the simple exponential smoothing models. The Ethiopia, Kenya, and Morocco data have followed the Damped trend, Holt, and Brown exponential smoothing models, respectively. In the analysis, the trends of COVID-19 new cases will be declined for Algeria and Ethiopia, and the trends will be constantan for Cameroon, Cote d’Ivoire, Ghana and Nigeria. But, it will be raised slightly for Egypt and Kenya, and significantly for Morocco and South Africa from September 7 to October 6, 2020.

Conclusion

This study was conducted with the current measures; the forecasts and trends nobtained may differ from the number of cases that occur in the future. Thus, the study finding should be useful in preparedness planning against further spread of the COVID-19 epidemic in African countries. And, the researcher recommended that as many countries continue to relax restrictions on movement and mass gatherings, and more are opening their airspaces, and the countries’ other public and private sectors are reopening. So, strong appropriate public health and social measures must be instituted on the grounds again.
Machine learning approaches classify clinical malaria outcomes based on haematological parameters
Authors: Morang’a Collins M. , Amenga–Etego Lucas , Bah Saikou Y. , Appiah Vincent , Amuzu Dominic S. , Amoako Nicholas , Abugri James , Oduro Abraham R. , Cunnington Aubrey J. , Awandare Gordon A. , Otto Thomas D.
Published: September 2020

Background

Malaria is still a major global health burden, with more than 3.2 billion people in 91 countries remaining at risk of the disease. Accurately distinguishing malaria from other diseases, especially uncomplicated malaria (UM) from non-malarial infections (nMI) remains a challenge. Furthermore, the success of rapid diagnostic tests (RDT) is threatened byPfhrp2/3deletions and decreased sensitivity at low parasitemia. Analysis of haematological indices can be used to support identification of possible malaria cases for further diagnosis, especially in travelers returning from endemic areas. As a new application for precision medicine, we aimed to evaluate machine learning (ML) approaches that can accurately classify nMI, UM and severe malaria (SM) using haematological parameters.

Methods

We obtained haematological data from 2,207 participants collected in Ghana; nMI (n=978), UM (n=526), and SM (n=703). Six different machine learning approaches were tested, to select the best approach. An artificial neural network (ANN) with three hidden layers was used for multi-classification of UM, SM, and uMI. Binary classifiers were developed to further identify the parameters that can distinguish UM or SM from nMI. Local interpretable model-agonistic explanations (LIME) were used to explain the binary classifiers.

Results

The multi-classification model had greater than 85 % training and testing accuracy to distinguish clinical malaria from nMI. To distinguish UM from nMI, our approach identified platelet counts, red blood cell (RBC) counts, lymphocyte counts and percentages as the top classifiers of UM with 0.801 test accuracy (AUC = 0.866 and F1-score = 0.747). To distinguish SM from nMI, the classifier had a test accuracy of 0.960 (AUC= 0.983, and F1-score = 0.944) with mean platelet volume and mean cell volume being the unique classifiers of SM. Random forest was used to confirm the classifications and it showed that platelet and RBC counts were the major classifiers of UM, regardless of possible confounders such as patient age and sampling location.

Conclusions

The study provides proof of concept methods that classify UM and SM from nMI, showing that ML approach is a feasible tool for clinical decision support. In the future, ML approaches could be incorporated into clinical decision-support algorithms for the diagnosis of acute febrile illness, and monitoring response to acute SM treatment particularly in endemic settings.
The COVID-19 PHARMACOME: A method for the rational selection of drug repurposing candidates from multimodal knowledge harmonization
Authors: Schultz Bruce , Zaliani Andrea , Ebeling Christian , Reinshagen Jeanette , Bojkova Denisa , Lage-Rupprecht Vanessa , Karki Reagon , Lukassen Sören , Gadiya Yojana , Ravindra Neal G. , Das Sayoni , Baksi Shounak , Domingo-Fernández Daniel , Lentzen Manuel , Strivens Mark , Raschka Tamara , Cinatl Jindrich , DeLong Lauren Nicole , Gribbon Phil , Geisslinger Gerd , Ciesek Sandra , van Dijk David , Gardner Steve , Kodamullil Alpha Tom , Fröhlich Holger , Peitsch Manuel , Jacobs Marc , Hoeng Julia , Eils Roland , Claussen Carsten , Hofmann-Apitius Martin
Published: September 2020

The SARS-CoV-2 pandemic has challenged researchers at a global scale. The scientific community’s massive response has resulted in a flood of experiments, analyses, hypotheses, and publications, especially in the field of drug repurposing. However, many of the proposed therapeutic compounds obtained from SARS-CoV-2 specific assays are not in agreement and thus demonstrate the need for a singular source of COVID-19 related information from which a rational selection of drug repurposing candidates can be made. In this paper, we present the COVID-19 PHARMACOME, a comprehensive drug-target-mechanism graph generated from a compilation of 10 separate disease maps and sources of experimental data focused on SARS-CoV-2 / COVID-19 pathophysiology. By applying our systematic approach, we were able to predict the synergistic effect of specific drug pairs, such as Remdesivir and Thioguanosine or Nelfinavir and Raloxifene, on SARS-CoV-2 infection. Experimental validation of our results demonstrate that our graph can be used to not only explore the involved mechanistic pathways, but also to identify novel combinations of drug repurposing candidates.
NS-Forest: A machine learning method for the objective identification of minimum marker gene combinations for cell type determination from single cell RNA sequencing
Authors: Aevermann Brian , Zhang Yun , Novotny Mark , Bakken Trygve , Miller Jeremy , Hodge Rebecca , Lelieveldt Boudewijn , Lein Ed , Scheuermann Richard H.
Published: September 2020

Single cell genomics is rapidly advancing our knowledge of cell phenotypic types and states. Driven by single cell/nucleus RNA sequencing (scRNA-seq) data, comprehensive atlas projects covering a wide range of organisms and tissues are currently underway. As a result, it is critical that the cell transcriptional phenotypes discovered are defined and disseminated in a consistent and concise manner. Molecular biomarkers have historically played an important role in biological research, from defining immune cell-types by surface protein expression to defining diseases by molecular drivers. Here we describe a machine learning-based marker gene selection algorithm, NS-Forest version 2.0, which leverages the non-linear attributes of random forest feature selection and a binary expression scoring approach to discover the minimal marker gene expression combinations that precisely captures the cell type identity represented in the complete scRNA-seq transcriptional profiles. The marker genes selected provide a barcode of the necessary and sufficient characteristics for semantic cell type definition and serve as useful tools for downstream biological investigation. The use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and non-coding RNAs in neuronal cell type identity.
HIF1α-dependent induction of the mitochondrial chaperone TRAP1 regulates bioenergetic adaptations to hypoxia
Authors: Laquatra Claudio , Sanchez-Martin Carlos , Minervini Giovanni , Moroni Elisabetta , Schiavone Marco , Tosatto Silvio , Argenton Francesco , Colombo Giorgio , Bernardi Paolo , Masgras Ionica , Rasola Andrea
Published: September 2020

The mitochondrial paralog of the Hsp90 chaperone family TRAP1 is often induced in tumors, but the mechanisms controlling its expression, as well as its physiological functions remain poorly understood. Here, we find that TRAP1 is highly expressed in the early stages of Zebrafish development, and its ablation delays embryogenesis while increasing mitochondrial respiration of fish larvae. TRAP1 expression is enhanced by hypoxic conditions both in developing embryos and in cancer models of Zebrafish and mammals. The TRAP1 promoter contains evolutionary conserved hypoxic responsive elements, and HIF1α stabilization increases TRAP1 levels. TRAP1 inhibition by selective compounds or by genetic knock-out maintains a high level of respiration in Zebrafish embryos after exposure to hypoxia.

Our data identify TRAP1 as a primary regulator of mitochondrial bioenergetics in highly proliferating cells following reductions in oxygen tension and HIF1α stabilization.
Prevalence of genetically similarFlavobacterium columnarephages across aquaculture environments reveals a strong potential for pathogen control
Authors: Runtuvuori-Salmela A , Kunttu HMT , Laanto E , Almeida GMF , Mäkelä K , Middelboe M , Sundberg L-R
Published: September 2020

Intensive aquaculture conditions expose fish to bacterial infections, leading to significant financial losses, extensive antibiotic use and risk of antibiotic resistance in target bacteria.Flavobacterium columnarecauses columnaris disease in aquaculture worldwide. To develop a bacteriophage-based control of columnaris disease, we isolated and characterized 126F. columnarestrains and 63 phages againstF. columnarefrom Finland and Sweden. Bacterial isolates were virulent on rainbow trout (Oncorhynchus mykiss) and fell into four previously described genetic groups A, C, E and G, with genetic groups C and E being the most virulent. Phage host range studied against a collection of 228 bacterial isolates demonstrated modular infection patterns based on host genetic group. Phages infected contemporary and previously isolated bacterial hosts, but bacteria isolated most recently were generally resistant to previously isolated phages. Despite large differences in geographical origin, isolation year or host range of the phages, whole genome sequencing of 56 phages showed high level of genetic similarity to previously isolatedF. columnarephages (Ficleduovirus, Myoviridae). Altogether, this phage collection demonstrates a potential to be used in phage therapy.

Significance Statement

Bacteriophages were discovered already over a century ago, and used widely in treatment of bacterial diseases before the era of antibiotics. Due to harmful effects of antibiotic leakage into environment, aquaculture is a potential target for phage therapy. However, the development of efficient phage therapy approach requires detailed characterization of bacterial pathogen virulence and phage host range. Here, we describe phage-bacterium interactions in the fish pathogenFlavobacterium columnare. We found that genetically similar phages are found from different fish farms, and their infectivity cluster according to genetic group of bacteria. In addition, phages were able to infect bacterial hosts from other farms, which is a preferable trait considering phage therapy approach. However, the most recently isolated phages had broader host range than the previously isolated phages, suggesting a response in the phage community to evolution of resistance in the bacteria. These results show that designing phage therapy for aquaculture (and other) systems needs consideration of both temporal and geographical aspects of the phage-bacterium interaction.
A phospho-regulated signal motif determines subcellular localization of α-TAT1 for dynamic microtubule acetylation
Authors: Roy Abhijit Deb , Gross Evan G. , Pillai Gayatri S. , Seetharaman Shailaja , Etienne-Manneville Sandrine , Inoue Takanari
Published: September 2020

Spatiotemporally dynamic microtubule acetylation underlies diverse physiological events ranging from cell migration to intracellular trafficking, autophagy and viral infections. Despite its ubiquity, the molecular mechanisms that regulate the sole microtubule acetylating agent, α-tubulin N-acetyltransferase 1 (α-TAT1) remain obscure. Here we report that dynamic intracellular localization of α-TAT1 unexpectedly determines the efficiency of microtubule acetylation. Specifically, we newly identified a conserved signal motif in the intrinsically disordered C-terminus of α-TAT1, consisting of three competing regulatory elements - nuclear export, nuclear import and cytosolic retention. Their balance is tuned via phosphorylation by serine-threonine kinases including CDK1 and CK2. While the un-phosphorylated form resides both in the cytosol and nucleus, the phosphorylated form binds to specific 14-3-3 adapters and accumulates in the cytosol for maximal substrate access. Cytosolic localization of α-TAT1 predominantly mediates microtubule acetylation, cell proliferation and DNA damage response. In contrast to other molecules with a similar phospho-regulated signal motif including transcription factors, α-TAT1 uniquely uses the nucleus as a hideout. As amino acid mutations to the motif have been reported in cancer patients, the present mechanism of subcellular α-TAT1 localization may help uncover a spatiotemporal code of microtubule acetylation in normal and aberrant cell functions.
Staphylococcus aureussecretes immunomodulatory RNA and DNA via membrane vesicles
Authors: Rodriguez Blanca V. , Kuehn Meta J.
Published: September 2020

Bacterial-derived RNA and DNA can function as ligands for intracellular receptor activation and induce downstream signaling to modulate the host response to bacterial infection. The mechanisms underlying the secretion of immunomodulatory RNA and DNA by pathogens such asStaphylococcus aureusand their delivery to intracellular host cell receptors are not well understood. Recently, extracellular membrane vesicle (MV) production has been proposed as a general secretion mechanism that could facilitate the delivery of functional bacterial nucleic acids into host cells.S. aureusproduce membrane-bound, spherical, nano-sized, MVs packaged with a select array of bioactive macromolecules and they have been shown to play important roles in bacterial virulence and in immune modulation through the transmission of biologic signals to host cells. Here we show thatS. aureussecretes RNA and DNA molecules that are mostly protected from degradation by their association with MVs. Importantly, we demonstrate that MVs can be delivered into cultured macrophage cells and subsequently stimulate a potent IFN-β response in recipient cells via activation of endosomal Toll-like receptors. These findings advance our understanding of the mechanisms by which bacterial nucleic acids traffic extracellularly to trigger the modulation of host immune responses.
Multimodal single-cell/nucleus RNA-sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer’s disease
Authors: Xu Jielin , Zhang Pengyue , Huang Yin , Bekris Lynn , Lathia Justin , Chiang Chien-Wei , Li Lang , Pieper Andrew A. , Leverenz James B. , Cummings Jeffrey , Cheng Feixiong
Published: September 2020

Systematic identification of molecular networks in disease relevant immune cells of the nervous system is critical for elucidating the underlying pathophysiology of Alzheimer’s disease (AD). Two key immune cell types, disease-associated microglia (DAM) and disease-associated astrocytes (DAA), are biologically involved in AD pathobiology. Therefore, uncovering molecular determinants of DAM and DAA will enhance our understanding of AD biology, potentially identifying novel therapeutic targets for AD treatment. Here, we present an integrative, network-based methodology to uncover conserved molecular networks between DAM and DAA. Specifically, we leverage single-cell and single-nucleus RNA sequencing data from both AD transgenic mouse models and AD patient brains, drug-target networks, metabolite-enzyme associations, and the human protein-protein interactome, along with large-scale patient data validation from the MarketScan Medicare Supplemental Database. We find that common and unique molecular network regulators between DAM (i.e,PAK1, MAPK14, andSYK) and DAA (i.e.,NFKB1, FOS, andJUN) are significantly enriched by multiple neuro-inflammatory pathways and well-known genetic variants (i.e.,BIN1) from genome-wide association studies. Further network analysis reveal shared immune pathways between DAM and DAA, including Fc gamma R-mediated phagocytosis, Th17 cell differentiation, and chemokine signaling. Furthermore, integrative metabolite-enzyme network analyses imply that fatty acids (i.e., elaidic acid) and amino acids (i.e., glutamate, serine, and phenylalanine) may trigger molecular alterations between DAM and DAA. Finally, we prioritize repurposed drug candidates for potential treatment of AD by agents that specifically reverse dysregulated gene expression of DAM or DAA, including an antithrombotic anticoagulant triflusal, a beta2-adrenergic receptor agonist salbutamol, and the steroid medications (fluticasone and mometasone). Individuals taking fluticasone (an approved anti-inflammatory and inhaled corticosteroid) displayed a significantly decreased incidence of AD (hazard ratio (HR) = 0.858, 95% confidence interval [CI] 0.829-0.888,P< 0.0001) in retrospective case-control validation. Furthermore, propensity score matching cohort studies also confirmed an association of mometasone with reduced incidence of AD in comparison to fluticasone (HR =0.921, 95% CI 0.862-0.984,P< 0.0001).
Induction of GLUTAMINE DUMPER1reveals a link between amino acid export, abscisic acid, and immune responses
Authors: Yu Shi , Aghamirzaie Delasa , Harich Kim , Collakova Eva , Grene Ruth , Pilot Guillaume
Published: September 2020

Amino acid homeostasis in plants is finely tuned to match developmental needs and response to adverse environments. Over-expression of the single-transmembrane domain protein GLUTAMINE DUMPER1 (GDU1) leads to increased amino acid export, reduced growth and constitutive induction of immune responses. We used an inducible gene expression system to tease apart the primary and secondary effects caused byGDU1, and demonstrated that the primary effect is increasing amino acid export, followed by increased amino acid content and abscisic acid (ABA) response, and a subsequent activation of defense responses. TheGDU1-mediated hypersensitivity to ABA partially depended on the E3 ubiquitin ligase LOSS-OF-GDU1 2 (LOG2), a known GDU1 interactor. More importantly, the lysine catabolite pipecolic acid played a pivotal role in theGDU1-induced defense responses. This work unravels a novel relationship between amino acid transport, ABA and defense responses, potentially mediated by the GDU1-LOG2 complex, critical for understanding how plants respond to amino acid imbalance.

ONE SENTENCE SUMMARY

Genetically induced disturbance of amino acid homeostasis sequentially triggers responses to abiotic stresses and plant defenses to pathogens in Arabidopsis through undefined sensing mechanisms
Dynamic Analysis of Alternative Polyadenylation from Single-Cell RNA-Seq (scDaPars) Reveals Cell Subpopulations Invisible to Gene Expression Analysis
Authors: Gao Yipeng , Li Lei , Amos Christopher I. , Li Wei
Published: September 2020

Alternative polyadenylation (APA) is a major mechanism of post-transcriptional regulation in various cellular processes including cell proliferation and differentiation, but the APA heterogeneity among single cells remains largely unknown. Single-cell RNA sequencing (scRNA-seq) has been extensively used to define cell subpopulations at the transcription level. Yet, most scRNA-seq data have not been analyzed in an “APA-aware” manner. Here, we introduce scDaPars, a bioinformatics algorithm to accurately quantify APA events at both single-cell and single-gene resolution using standard scRNA-seq data. Validations in both real and simulated data indicate that scDaPars can robustly recover missing APA events caused by the low amounts of mRNA sequenced in single cells. When applied to cancer and human endoderm differentiation data, scDaPars not only revealed cell-type-specific APA regulation but also identified cell subpopulations that are otherwise invisible to conventional gene expression analysis. Thus, scDaPars will enable us to understand cellular heterogeneity at the post-transcriptional APA level.
Ancestry Inference Using Reference Labeled Clusters of Haplotypes
Authors: Wang Yong , Song Shiya , Schraiber Joshua G. , Sedghifar Alisa , Byrnes Jake K. , Turissini David A. , Hong Eurie L. , Ball Catherine A. , Noto Keith
Published: September 2020

We present ARCHes, a fast and accurate haplotype-based approach for inferring an individual’s ancestry composition. Our approach works by modeling haplotype diversity from a large, admixed cohort of hundreds of thousands, then annotating those models with population information from reference panels of known ancestry. The running time of ARCHes does not depend on the size of a reference panel because training and testing are separate processes, and the inferred population-annotated haplotype models can be written to disk and reused to label large test sets in parallel (in our experiments, it averages less than one minute to assign ancestry from 32 populations to 1,001 sections of a genotype using 10 CPU). We test ARCHes on public data from the 1,000 Genomes Project and HGDP as well as simulated examples of known admixture. Our results demonstrate that ARCHes outperforms RFMix at correctly assigning both global and local ancestry at finer population scales regardless of the amount of population admixture.

Author Summary

Human DNA is inherited from ancestors that come from different populations across the globe and across time. Being able to identify which of those populations make up an individual’s DNA, how much they contribute, and on which chromosomes, is currently an important open research problem with many applications in the study of human diversity and history. As DNA sequencing and genotyping technology has developed, we have greater and greater amounts of data, which allows for the development of new sophisticated machine learning methods to approach this problem, and presents a need to process large amounts of data efficiently. These methods learn from examples of DNA data from known populations, and must be robust to differences in size and diversity among those reference populations. We present a new approach to this problem called ARCHes (Ancestry inference usingReference labeledClusters ofHaplotypes), that models the global diversity of small segments of human DNA sequence (“haplotypes”), and the extent to which these haplotypes are associated with each of a set of population reference panels. It then computes the most likely population assignments and the points along the genome where the populations change. Our experiments show that ARCHes has superior accuracy compared to a state-of-the-art method in identifying source populations and their locations on the genome, regardless of the number of different populations present in the genome, how closely related those populations are. ARCHes is also able to model populations despite having a small amount of population reference DNA data.
Structural and optical characterization of Er-doped CaMoO4down-converting phosphors
Authors: Kaur Puneet , Kumar Rajesh , Davessar Shreya , Khanna Atul
Published: September 2020

xEr2O3–(1−x)CaMoO4(x= 1, 3, 5, 7 and 10 mol%) nanoparticles were synthesized by solid-state sintering at 800°C. X-ray diffraction studies confirmed the tetragonal crystal structure of CaMoO4, while the doped samples show the co-existence of cubic Er2O3and tetragonal CaMoO4and rule out the replacement of Ca2+by Er3+in the structure. The crystal unit-cell dimensions, phase concentration and atomic position coordinates were determined by Rietveld refinement. The short-range structure of CaMoO4consists of tetrahedral MoO4and snub disphenoid deltahedral CaO8units, while the unit cell of Er2O3consists of two types of ErO6octahedral units. All MoO4units contain Mo—O bonds of equal lengths, whereas two types of slightly different Ca—O bond lengths exist in CaO8. Raman spectra of the doped samples show only Mo—O vibrational modes and the Raman peaks of Er2O3are masked by Mo—O bond vibrations. CaMoO4shows bluish-green emission at 500 nm, while Er-doped samples show strong green emission under UV excitation. UV irradiation (380 nm) induces down-conversion green emission at 531 nm and 552 nm and good color purity in 1 mol% Er2O3–CaMoO4sample which makes it a potential candidate for applications in optical devices.
Challenges for work–life balance during COVID-19 induced nationwide lockdown: exploring gender difference in emotional exhaustion in the Indian setting
Authors: Bhumika Bhumika
Published: September 2020

Purpose

This paper aims to attempt to explore the nature of relationship between work–life balance and emotional exhaustion experienced by the employed individuals while working from home during the pandemic COVID-19 induced nationwide lockdown in the Indian setting.

Design/methodology/approach

Data were collected from 180 working professionals in North India who were working from home during the lockdown. PROCESS macro developed for SPSS was used to test the hypotheses.

Findings

Findings depicted that in comparison to men, women felt more emotional exhaustion due to personal life interference in work during work from home period. Surprisingly, the relationship between work interference with personal life, and emotional exhaustion did not differ by gender. It was found that the participative leadership could contribute to reduction of work interference with personal life, and through such an influence, emotional exhaustion experienced by an employee could be reduced to some extent.

Originality/value

Many previous studies have explored the nature of the relationship between work–life balance and emotional exhaustion, but rarely any study could cover any Pandemic affected working scenario. This study attempted to investigate such a relationship when employees were obligated to mandatorily work from home during the countrywide lockdown.
“Gendering” contamination: physical, social and moral taint in the context of COVID-19
Authors: Simpson Ruth , Morgan Rachel
Published: September 2020

Purpose

The purpose of this paper is to explore the “gendering” of contamination in the context of COVID-19 where “gendering” is taken to include other, cross-cutting areas of disadvantage.

Design/methodology/approach

This paper draws on secondary sources to explore gender and COVID-19.

Findings

The authors show that contamination is rooted in structural disadvantage, reproducing classed, gendered and racial difference in terms of how it is encountered and experienced.

Practical implications

This “thought piece” suggests a greater awareness of how pandemics and other public health emergencies impact of structural disadvantages.

Originality/value

This “thought piece” applies notions of taint to a contemporary pandemic that has had far-reaching consequences for issues of equality.
Teaching leadership the “Day After”, with care
Authors: Panayiotou Alexia
Published: September 2020

Purpose

This paper aims to share the author’s thoughts and reflections on teaching leadership in “pandemic times”. The author has been teaching leadership for nearly 20 years, both to undergraduate and graduate students, always stressing the importance of humility and compassion, traits that were often doubted and questioned vis-à-vis more traditional, masculine, perceptions of leadership. Yet, local and international leadership during the pandemic brought to surface the need and effectiveness of such characteristics, or what the author calls “the need for a feminist ethics of care” in leadership.

Design/methodology/approach

This paper is a thought piece stemming from the author’s experiences and reflections.

Findings

The paper discusses the fact that the most successful handling of the pandemic was largely carried out by female leaders, while also asking “why did so many male leaders do badly?”

Research limitations/implications

With this thought piece, the author hopes to not only engage the readers in a discussion about effective leadership but also on how to teach leadership in today’s schools of management.

Originality/value

The paper hopes to serve as a springboard for opening the discussion around traditional masculinist modes of leadership that have proven to be detrimental in managing the COVID-19 pandemic while also proposing that feminist leadership embedded in an ethics of care is what the world needs today.
An Empirical Study on the Nonlinear Dynam Relationship between Spot and Futures Pri
Authors: Kim In Joon , Seo Young Gyun
Published: September 2020

This paper examines empirically the dynamic relationship between spot and futures prices in stock index futures market using data for the KOSPI200 during 1996 to 2001, and employing nonlinear-equilibrium-correction approach that essentially is based on the extension of Markovian regime shifts to nonstationary framework. A linear-VECM was rejected strongly when tested against a Markov-switching (MS) VECM that allowed for two regimes in the mean of equilibrium correction model, as well as in the variance-covariance matrix. The empirical model ultimately proposed therefore, is consistent with the spirit of Cost of Carry model, as well as with the increasingly growing empirical literature stressing the existence of important nonlinearities in both spot and futures prices movements.
Optimal Hedging Strategy with Natural Ga Futures and Options
Authors: Kwon Sang Jang , Kwak Soo Jong
Published: September 2020

In this paper, we theoretically examine the optimal hedge strategy for a natural gas company. The use of natural gas derivatives to minimize consumers' per unit cost of natural gas consumed, or to minimize the upside risk associated with extreme bills would be the strategy being considered by local distribution companies (LDCs) and regulators. The objective is, therefore, to stabilize the summer and the winter months' natural gas prices as well as to improve the level of customers' welfare. In general, during the summer injection period, April through October, utility companies purchase a certain amount of natural gas and keep in storage facilities and, hence, during the winter withdrawal months, November through March, utility companies supply natural gas at a predetermined minimal fuel cost rate to residential and commercial customers. Therefore, to manage these conflicts of interests efficiently should natural gas companies be supported by accurate forecast of the natural gas price for the winter months. Otherwise, natural gas companies will trade natural gas derivatives in order to reduce costs charged to customers. The results show that customers benefit from the use of natural gas derivatives. If the natural gas market is deregulated, the typical risk-return trade off shows that natural gas derivatives would provide the most efficient tools for utility companies to minimize the natural gas price volatilities.
A Market Microstructure Analysis of the KOSPI200 Stock Index Options Market: Investor‘s Strategic Behavior
Authors: Eom Gyeong Sig , Han Sang Beom
Published: September 2020

This paper analyzes trader‘s strategic behavior in the KOSPI200 index options market. Using intraday data for various at-the-money options, we obtain the following results : (1) The frequency of trades is a better market statistic than trade size for option price volatility. This may result from the hedging behavior of large traders. This also suggests that the informed traders utilize their informational advantage gradually. (2) The effect of the duration of previous intervals on the expected duration of current intervals is persistent. (3) In the modified ACD model, the standardized distribution of duration is not exponential; rather, it is Weibull with r < 1. (4) There is no specific diurnal pattern of the duration of the duration of the options market. (5) we find a clear maturity effect.
Pricing of the Korean Treasury Bond Futures Using the Term Structure of Interest Rates
Authors: Park Jin U , Choi Youngsoo
Published: September 2020

This paper shows the limitation of the cost-of-carry model which is used for pricing the theoretical value of the KTB futures, and proposes an alternative pricing model based on the term structure of interest rates. Under the assumption of 1-factor term structure, this paper treats the theoretical price of KTB futures price as a risk-neutral expectation of payoff function at maturity and derives the approximated formula for pricing the KTB futures. As compared with our price of KTB futures using the term structure of interest rates, the conventional KOFEX price based on the cost-of-carry model tends to be overvalued as the time to maturity increases. This result is due to the difference between the futures and forward prices which is caused by treating the futures contract as the forward contract in the conventional KOFEX pricing model. In particular, this discrepancy becomes more significant when the price of underlying asset and the interest rates are negatively correlated and the time to maturity is longer. The bond futures contract is a typical example of financial instrument whose price has a negative correlation with interest rates
Pricing KTB Futures: An Application of Black-Karasinski Model
Authors: Kang Jang Gu , Lee Jeong Jin
Published: September 2020

Traditionally, people values KTB futures contracts using the model based on the cost-of-carry argument. However, the underlying commodity for the KTB futures is non-tradable, and so the cost of carry argument cannot be applied to the KTB futures. This paper regards KTB futures contracts as interest-rate derivatives, and prices them using the Black-Karasinski (B-K) term structure model. This paper documents that (1) the market prices of KTB futures are more close to B-K model price than the price by the cost-of-carry argument, though the KTB futures are generally underpriced in the market even under the B-K model; (2) The extent of underpricing is a decreasing function of the remaining maturity of the futures, and becomes smaller recently; (3) The cost of carry argument relatively overprices the KTB futures, and the degree of overpricing is a decreasing function of interest rates and the remaining maturity of the futures; (4) The daily resettlement in the futures contracts affects the futures price very little; (5) The trading strategies based on the theoretical pricing models produce very high trading profit.
Hedging Strategies with the KTB Futures
Authors: Lee Jae Ha , Hui Han Deog
Published: September 2020

This study explores hedging strategies that use the KTB futures to hedge the price risk of the KTB spot portfolio. The study establishes the price sensitivity, risk-minimization, bivariate GARCH (1,1) models as hedging models, and analyzes their hedging performances. The sample period covers from September 29, 1999 to September 18, 2001. Time-matched prices at 11:00 (11:30) of the KTB futures and spot were used in the analysis. The most important findings may be summarized as follows. First, while the average hedge ration of the price sensitivity model is close to one, both the risk-minimization and GARCH model exhibit hedge ratios that are substantially lower than one. Hedge ratios tend to be greater for daily data than for weekly data. Second, for the daily in-sample data, hedging effectiveness is the highest for the GARCH model with time-varying hedge ratios, but the risk-minimization model with constant hedge ratios is not far behind the GARCH model in its hedging performance. In the case of out-of-sample hedging effectiveness, the GARCH model is the best for the KTB spot portfolio, and the risk-minimization model is the best for the corporate bond portfolio. Third, for daily data, the in-sample hedge shows a better performance than the out-of-sample hedge, except for the risk-minimization hedge against the corporate bond portfolio. Fourth, for the weekly in-sample hedges, the price sensitivity model is the worst and the risk-minimization model is the best in hedging the KTB spot portfolio. While the GARCH model is the best against the KTB +corporate bond portfolio, the risk-minimization model is generally as good as the GARCH model. The risk-minimization model performs the best for the weekly out-of-sample data, and the out-of-sample hedges are better than the in-sample hedges. Fifth, while the hedging performance of the risk-minimization model with daily moving window seems somewhat superior to the traditional risk-minimization model when the trading volume increased one year after the inception of the KTB futures, on the average the traditional model is better than the moving-window model. For weekly data, the traditional model exhibits a better performance. Overall, in the Korean bond markets, investors are encouraged to use the simple risk-minimization model to hedge the price risk of the KTB spot and corporate bond portfolios.
Uplift behaviour of axial granular pile anchor encased with geogrid in cohesionless soil
Authors: Sharma Abhishek , Sharma Ravi Kumar
Published: September 2020

Purpose

The purpose of this paper is to provide a cost-effective foundation technique for the design of foundations of transmission towers, heavily loaded structures, etc.

Design/methodology/approach

Experimental model tests are conducted in a model test tank to find out the effect of length and diameter of geogrid encased granular pile anchors, the relative density of sand and the angle of inclination of the pile from the vertical on uplift behavior of granular pile anchors.

Findings

The uplift capacity of the geogrid encased granular pile anchor increased with increasing length and diameter of granular pile anchor. Further, increasing the relative density of surrounding soil increased uplift capacity of geogrid encased granular pile anchor system. Moreover, increasing the angle of inclination of loading also increased uplift capacity of whole system. Thus, the proposed system can be effectively used in field for further applications.

Originality/value

The paper is helpful for the engineers looking for cost-effective foundation techniques for heavily loaded structures.
Reducing nonpriority queues at theme parks
Authors: Sakamoto Noriaki
Published: September 2020

Purpose

This study examined the waiting times to board an attraction at a theme park (Tokyo DisneySea in Japan) using a simulation based on measured values. Park visitors often complain that waiting times are too long; guests (Disney's term for park visitors) must stand in long, slow-moving queues outdoors in all weather, enduring heat, cold, rain and wind. This can undermine their health and reduce customer satisfaction. To date, no research has offered a scientific approach to solve the problem in the context of theme park queues.

Design/methodology/approach

The attraction examined two queues: a short waiting queue for guests with priority entry tickets and a long waiting queue for guests without priority entry tickets. The total number of guests with priority entry tickets remained a constant value, as in the current system; however, the author designed the number as a monotonically increasing function to reduce the waiting times for nonpriority entry. It was impractical to analyze queues or try to explain proposed wait time reduction methods using theories and mathematical models alone. Therefore, the author used a simulation study based on real data to demonstrate the proposed method of this study.

Findings

The simulation results indicated that the proposed method significantly decreased guests' waiting times in the nonpriority entry queue, without changing the number of guests in both priority and nonpriority entry queues.

Research limitations/implications

Simple queues can be analyzed using theoretical calculations, but complicated queue systems require simulation methods. Therefore, this paper cannot provide a theoretical basis for the method.

Practical implications

The proposed method offers benefits to managers of any event or location seeking to manage queue times and not just theme parks (e.g. exhibitions, concerts, etc.). Advance tickets are equivalent to priority entry tickets, so applying the proposed method can shorten waiting times on the day of the event.

Originality/value

This study has important practical implications for queues management, and the proposed approach is a unique system that reduces waiting times, thus increasing customer satisfaction. The proposed method can be applied to similar types of priority entry systems.
Does open access to academic research help small, science-based companies?
Authors: ElSabry ElHassan , Sumikura Koichi
Published: September 2020

Purpose

This study investigates the extent to which a company's usage of open access (OA) literature for R&D activities depends on its size. The authors’ assumption is that smaller pharmaceutical companies have less access to (usually expensive) journal subscriptions.

Design/methodology/approach

A fixed-effect Poisson model was used to study a panel dataset of USPTO pharmaceutical company patents. The dependent variable is the count of citations to OA resources in a given company patent.

Findings

Results support current anecdotal evidence that many SMEs suffer from high journal prices.

Originality/value

This result justifies the assumption made by policymakers about the potentially positive impact OA mandates have on national innovation activity. It was also shown that collaborating with universities can be a potential coping mechanism for companies that struggle to gain access to the journals they need. In addition to the novelty of its findings, this study introduces a new way to study the impact of OA in nonacademic contexts.
An instructional note to obtain an efficient portfolio with a short sale restriction
Authors: Thompson Thomas H.
Published: September 2020

Purpose

The purpose of this paper is to provide a SAS program for an efficient portfolio given a short sale restriction.

Design/methodology/approach

We provide a 50-stock portfolio given 50 weekly stock returns. We contrast results with a 50-stock portfolio without a restriction.

Findings

We portfolio weights and utility scores for a range of returns from zero to 2.06%.

Practical implications

This program can be used for any sized portfolio.

Originality/value

This is the first SAS program for a 50-stock portfolio given return information.
Influence of social capital offline and online on early-stage entrepreneurs
Authors: Silva Tatiane Andreza de Souza , Corrêa Victor Silva , Vale Gláucia Maria Vasconcellos , Giglio Ernesto Michelangelo
Published: September 2020

Purpose

The purpose of this article is to investigate if and how social capital offline – stemming from face-to-face interactions – and social capital online – stemming from social digital media – can influence early-stage entrepreneurs, i.e. ventures with up to 42 months of existence.

Design/methodology/approach

The authors used herein a qualitative research approach. The method used was the case study. The authors investigated three early-stage entrepreneurs in order to achieve the objective of the paper. These entrepreneurs are both the unit of analysis and the unit of observation.

Findings

The outcomes of this research indicate (1) the combined importance of social capital offline and online; (2) the different performance of the two different types of social capital (they seem to operate in relatively distinct ways) and (3) the existence of recursiveness between resources stemming from the two social spheres (offline and online).

Research limitations/implications

As research limitations, the authors point out the following: (1) the use of semistructured interviews as the only data collection instrument; (2) the limitation of the outcomes to entrepreneurs only (3) the absence of information on the performance of the business ventures; the focus of the paper was only on establishing causality between social capital offline and online and entrepreneurial performance.

Originality/value

This paper provides important research contributions. Initially, the paper presents a range of offline and online variables, which can be used in further research. At the same time, the paper emphasizes the combined impact of social capital offline and online, expanding the literature related to entrepreneurship. Moreover, this study proposes the creation of an integrative model. Finally, the authors point out the need for new theoretical and empirical studies on the subject, which still presents a gap in the literature.
The real body of therapeutic communities in society of lockdown
Authors: Bruschetta Simone
Published: September 2020

Purpose

It is argued that COVID-19 epidemic has critically affected, from many points of view, the hyper-modern economic system, dominant in the globalized capitalist societies. This paper aims to describe the point of view of therapeutic communities, basing my reflections on the Italian experience.

Design/methodology/approach

The author would like to share a critical thought on three issues that this pandemic crisis has made manifest in Italian society: the return of the removed bodies, the feeling of excess represented by therapeutic communities and the emergence of the need for a common thought.

Findings

Body become again an object of studies and with it also the group, as grouping of the bodies. Also the community become a now old-object of studies, as grouping of bodies and groups in a human environment. The objectives of this study are presented as the substance of the democratic vision of society, which therapeutic communities have a responsibility to promote scientifically and ethically.

Originality/value

Therapeutic community is presented as transformative and evolutionary for individuals and groups that compose it, as equally conflictual and destructive, both internally and externally. The author thinks this is the substance of the democratic vision of society, which therapeutic communities have a responsibility to promote scientifically and ethically.