bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vapor exposure to Δ9-tetrahydrocannabinol (THC) slows locomotion of the Maine Lobster (Homarus americanus)
Authors: Gutierrez Arnold , Creehan Kevin M. , Turner Mitchell L. , Tran Rachelle N , Kerr Tony M. , Nguyen Jacques D. , Taffe Michael A. 
Published: May 2021

AbstractRationaleDespite a long history of use in synaptic physiology, the lobster has been a neglected model for behavioral pharmacology. A restaurateur proposed that exposing lobster to cannabis smoke reduces anxiety and pain during the cooking process. It is unknown if lobster gill respiration in air would result in significant Δ9-tetrahydrocannabinol (THC) uptake and whether this would have any detectable behavioral effects.ObjectiveThe primary goal was to determine tissue THC levels in the lobster after exposure to THC vapor. Secondary goals were to determine if THC vapor altered locomotor behavior or nociception.MethodsTissue samples were collected (including muscle, brain and hemolymph) from Homarus americanus (N=3 per group) following 30 or 60 minutes of exposure to vapor generated by an e-cigarette device using THC (100 mg/mL in a propylene glycol vehicle). Separate experiments assessed locomotor behavior and hot water nociceptive responses following THC vapor exposure.ResultsTHC vapor produced duration-related THC levels in all tissues examined. Locomotor activity was decreased (distance, speed, time-mobile) by 30 min inhalation of THC. Lobsters exhibit a temperature-dependent withdrawal response to immersion of tail, antennae or claws in warm water; this is novel evidence of thermal nociception for this species. THC exposure for 60 minutes had only marginal effect on nociception under the conditions assessed.ConclusionsVapor exposure of lobsters, using an e-cigarette based model, produces dose-dependent THC levels in all tissues and reduces locomotor activity. Hot water nociception was temperature dependent, but only minimal anti-nociceptive effect of THC exposure was confirmed.
Cellular calcium levels influenced by NCA-2 impact circadian period determination in Neurospora
Authors: Wang Bin , Zhou Xiaoying , Gerber Scott A. , Loros Jennifer J. , Dunlap Jay C. 
Published: May 2021

AbstractIntracellular calcium signaling has been implicated in control of a variety of circadian processes in animals and plants but its role in microbial clocks has remained largely cryptic. To examine the role of intracellular Ca2+ in the Neurospora clock we screened knockouts of calcium transporter genes and identified a gene encoding a calcium exporter, nca-2, uniquely as having significant period effects. Loss of NCA-2 results in an increase in cytosolic calcium level, and this leads to hyper-phosphorylation of core clock components, FRQ and WC-1, and a short period as measured by both the core oscillator and overt clock. Genetic analyses showed that mutations in certain frq phospho-sites, and in Ca2+-calmodulin-dependent kinase (camk-2), are epistatic to nca-2 in controlling the pace of the oscillator. These data are consistent with a model in which elevated intracellular Ca+2 leads to increased activity of CAMK-2 leading to enhanced FRQ phosphorylation, accelerated closure of the circadian feedback loop, and a shortened circadian period length. At a mechanistic level some CAMKs undergo more auto-phosphorylations in Δnca-2, consistent with high calcium in the Δnca-2 mutant influencing the enzymatic activity of CAMKs. NCA-2 interacts with multiple proteins including CSP-6, a protein known to be required for circadian output. Most importantly, expression of nca-2 is circadian clock-controlled at both the transcriptional and translational levels, and this in combination with the period effects seen in strains lacking NCA-2, firmly places calcium signaling within the larger circadian system where it acts as both an input to and output from the core clock.ImportanceCircadian rhythms are based on cell-autonomous, auto-regulatory, feedback loops formed by interlocked positive and negative arms, and they regulate myriad molecular and cellular processes in most eukaryotes including fungi. Intracellular calcium signaling is also a process that impacts a broad range of biological events in most eukaryotes. Clues have suggested that calcium signaling can influence circadian oscillators through multiple pathways; however, mechanistic details have been lacking in microorganisms. Building on prior work describing calcium transporters in the fungus Neurospora, one such transporter, NCA-2, was identified as a regulator of circadian period length. Increased intracellular calcium levels caused by loss of NCA-2 results in over-activation of calcium-responsive protein kinases, in turn leading to a shortened circadian period length. Importantly, expression of NCA-2 is itself controlled by the molecular clock. In this way calcium signaling can be seen as providing both input to and output from the circadian system.
Single-dose SARS-CoV-2 vaccine in a prospective cohort of COVID-19 patients
Authors: van Gils Marit J. , van Willigen Hugo D. , Wynberg Elke , Han Alvin X. , van der Straten Karlijn , Verveen Anouk , Lebbink Romy , Dijkstra Maartje , Burger Judith A. , Oomen Melissa , Tejjani Khadija , Bouhuijs Joey H. , Appelman Brent , Lavell Ayesha H.A. , Poniman Meliawati , Caniels Tom G. , Bontjer Ilja , van Vught Lonneke A. , Vlaar Alexander P.J. , Sikkens Jonne J. , Bomers Marije K. , Sanders Rogier W. , Kootstra Neeltje A. , Russell Colin , Prins Maria , de Bree Godelieve J. , de Jong Menno D. ,   RECoVERED Study Group
Published: May 2021

AbstractBackgroundThe urgent need for, but limited availability of, SARS-CoV-2 vaccines worldwide has led to widespread consideration of dose sparing strategies, particularly single vaccine dosing of individuals with prior SARS-CoV-2 infection.MethodsWe evaluated SARS-CoV-2 specific antibody responses following a single-dose of BNT162b2 (Pfizer-BioNTech) mRNA vaccine in 155 previously SARS-CoV-2-infected individuals participating in a population-based prospective cohort study of COVID-19 patients.Participants varied widely in age, comorbidities, COVID-19 severity and time since infection, ranging from 1 to 15 months. Serum antibody titers were determined at time of vaccination and one week after vaccination. Responses were compared to those in SARS-CoV-2-naive health care workers after two BNT162b2 mRNA vaccine doses.ResultsWithin one week of vaccination, IgG antibody levels to virus spike and RBD proteins increased 27 to 29-fold and neutralizing antibody titers increased 12-fold, exceeding titers of fully vaccinated SARS-CoV-2-naive controls (95% credible interval (CrI): 0.56 to 0.67 v. control 95% CrI: −0.16 to −0.02). Pre-vaccination neutralizing antibody titers had the largest positive mean effect size on titers following vaccination (95% CrI (0.16 to 0.45)). COVID-19 severity, the presence of comorbidities and the time interval between infection and vaccination had no discernible impact on vaccine response.ConclusionA single dose of BNT162b2 mRNA vaccine up to 15 months after SARS-CoV-2 infection provides neutralizing titers exceeding two vaccine doses in previously uninfected individuals. These findings support wide implementation of a single-dose mRNA vaccine strategy after prior SARS-CoV-2 infection.
VP-Detector: A 3D convolutional neural network for automated macromolecule localization and classification in cryo-electron tomograms
Authors: Hao Yu , Zhang Biao , Wan Xiaohua , Yan Rui , Liu Zhiyong , Li Jintao , Zhang Shihua , Cui Xuefeng , Zhang Fa 
Published: May 2021

AbstractMotivationCryo-electron tomography (Cryo-ET) with sub-tomogram averaging (STA) is indispensable when studying macromolecule structures and functions in their native environments. However, current tomographic reconstructions suffer the low signal-to-noise (SNR) ratio and the missing wedge artifacts. Hence, automatic and accurate macromolecule localization and classification become the bottleneck problem for structural determination by STA. Here, we propose a 3D multi-scale dense convolutional neural network (MSDNet) for voxel-wise annotations of tomograms. Weighted focal loss is adopted as a loss function to solve the class imbalance. The proposed network combines 3D hybrid dilated convolutions (HDC) and dense connectivity to ensure an accurate performance with relatively few trainable parameters. 3D HDC expands the receptive field without losing resolution or learning extra parameters. Dense connectivity facilitates the re-use of feature maps to generate fewer intermediate feature maps and trainable parameters. Then, we design a 3D MSDNet based approach for fully automatic macromolecule localization and classification, called VP-Detector (Voxel-wise Particle Detector). VP-Detector is efficient because classification performs on the pre-calculated coordinates instead of a sliding window.ResultsWe evaluated the VP-Detector on simulated tomograms. Compared to the state-of-the-art methods, our method achieved a competitive performance on localization with the highest F1-score. We also demonstrated that the weighted focal loss improves the classification of hard classes. We trained the network on a part of training sets to prove the availability of training on relatively small datasets. Moreover, the experiment shows that VP-Detector has a fast particle detection speed, which costs less than 14 minutes on a test tomogram.Contactzsh@amss.ac.cn, xfcui@email.sdu.edu.cn, zhangfa@ict.ac.cnSupplementary informationSupplementary data are available at Bioinformatics online.
Estimating anisotropy directly via neural timeseries
Authors: Fagerholm Erik D. , Foulkes W.M.C. , Gallero-Salas Yasir , Helmchen Fritjof , Moran Rosalyn J. , Friston Karl J. , Leech Robert 
Published: May 2021

AbstractAn isotropic dynamical system is one that looks the same in every direction, i.e., if we imagine - standing somewhere within an isotropic system, we would not be able to differentiate between different lines of sight. Conversely, anisotropy is a measure of the extent to which a system deviates from perfect isotropy, with larger values indicating greater discrepancies between the structure of the system along its axes. Here, we derive the form of a generalised scalable (mechanically similar) discretized field theoretic Lagrangian that allows for levels of anisotropy to be directly estimated via timeseries of arbitrary dimensionality. We generate synthetic data for both isotropic and anisotropic systems and, by using Bayesian model inversion and reduction, show that we can discriminate between the two datasets – thereby demonstrating proof of principle. We then apply this methodology to murine calcium imaging data collected in rest and task states, showing that anisotropy can be estimated directly from different brain states and cortical regions in an empirical in vivo biological setting. We hope that this theoretical foundation, together with the methodology and publicly available MATLAB code, will provide an accessible way for researchers to obtain new insight into the structural organization of neural systems in terms of how scalable neural regions grow – both ontogenetically during the development of an individual organism, as well as phylogenetically across species.
Classification models for likelihood prediction of diabetes at early stage using feature selection
Authors: Oladimeji Oladosu Oyebisi , Oladimeji Abimbola , Oladimeji Olayanju 
Published: May 2021

PurposeDiabetes is one of the life-threatening chronic diseases, which is already affecting 422m people globally based on (World Health Organization) WHO report as at 2018. This costs individuals, government and groups a whole lot; right from its diagnosis stage to the treatment stage. The reason for this cost, among others, is that it is a long-term treatment disease. This disease is likely to continue to affect more people because of its long asymptotic phase, which makes its early detection not feasible.Design/methodology/approachIn this study, the authors have presented machine learning models with feature selection, which can detect diabetes disease at its early stage. Also, the models presented are not costly and available to everyone, including those in the remote areas.FindingsThe study result shows that feature selection helps in getting better model, as it prevents overfitting and removes redundant data. Hence, the study result when compared with previous research shows the better result has been achieved, after it was evaluated based on metrics such as F-measure, Precision-Recall curve and Receiver Operating Characteristic Area Under Curve. This discovery has the potential to impact on clinical practice, when health workers aim at diagnosing diabetes disease at its early stage.Originality/valueThis study has not been published anywhere else.
Panasonic life solutions: anchoring its future growth strategy
Authors: Mehrotra Sonia , Salunkhe Uday 
Published: May 2021

Learning outcomes
The learning outcomes of this paper is as follows: to explain the importance of rationalizing business operations to achieve efficiencies. To explain the importance of constantly re-inventing the product portfolio and the business for the survival and growth of the business. To discuss the use of product-market expansion strategies as used by businesses for growth and sustainability. To evaluate the internal challenges faced by a company as they adopt business strategies for business growth. To discuss a firm’s strategy to exploit significant opportunities in an evolving business environment.

Case overview/synopsis
Panasonic Life Solutions India Limited (PLSIND) an electrical products company with operations in India – an emerging market has set a Vision 2022 to achieve INR 69.21bn revenue target by the year 2022. PLSIND is marketed through the distributor business to consumer sales channel. To achieve the new growth targets, it was imperative for them to expand the product portfolio and explore marketing through the new business to business (B2B) and business to government (B2G) sales channels. Dinesh Aggarwal the Joint Managing Director of PLSIND was tasked with this responsibility. Both propositions depicted attractive business potential but at the same time came with additional risks of a longer sales/revenue cycle. PLSIND to a certain extent had ventured into new business projects with the launch of home automation, solar solutions for industries and smart street lighting business projects. In 2019, they also made a modest beginning by achieving revenues of INR 3.4bnn (constituting 10% of their aggregate revenues of INR 34bn) from B2B/B2G sales channels. Aggarwal believed that this was a good beginning. However, to achieve 2022 growth targets, they had to aggressively move forward with the new business strategy. Aggarwal had to work with the management team to gain acceptance and then to manage these additional risks for growth that came with this new business strategy. How could he win the confidence of the management team? How could he best reorganize the business teams and processes internally to enhance the required operational efficiencies for business growth?

Complexity academic level
This case is designed for business students at the MBA or executive MBA level courses.

Supplementary materials
Teaching notes are available for educators only.

Subject code
CSS 11: Strategy.
Gender in vocational education and training: an integrative review
Authors: Ray Sarah , Zarestky Jill 
Published: May 2021

Purpose
Vocational education and training (VET) programmes are key contributors to skill and talent development for nations worldwide, as aligned with the UN’s sustainable development goals (SDGs). The purpose of this paper is to explore gender inclusion in VET programmes from an economic feminist (EF) theoretical perspective.

Design/methodology/approach
This integrative literature review identified and analysed relevant empirical studies to create a more comprehensive representation of supports for global gender equity and economic growth through VET.

Findings
A gap exists between EF theory, human resource development and VET practices. Consequently, instructor preparation and practice do not adequately contribute to equitable workplaces beyond VET programmes. VET programmes continually struggle to create inclusive environments that support women and challenge masculinized fields and workplace norms.

Research limitations/implications
This paper limits empirical studies addressing gender in VET. Future empirical work should investigate the value to students, instructors and communities when masculine industry norms are reconstructed and redesigned for gender inclusivity.

Practical implications
VET advisors and instructors are influential in contextualizing vocational fields for students and influencing students’ career trajectories. Women need more accessible training and employment in traditional masculine industries.

Originality/value
This comprehensive review of gender in VET can aid in inclusivity efforts of programmes and employers and support nations’ efforts to achieve the UN’s SDGs.
Determinants of adaptation to climate variability among farming households in Tyhume Valley communities, Eastern Cape province, South Africa
Authors: Mtintsilana Olona , Akinyemi Babatope Ebenezer , Zhou Leocadia 
Published: May 2021

Purpose
This paper aims to determine factors affecting adaptation to climate variability on crop production among farming households in Tyhume Valley.

Design/methodology/approach
This study conducted an empirical analysis of the impact of adaptation on crop yield of farming households and estimated the factors affecting adaptation to climate variability on farming households. The analysis used primary data from 205 farming households practicing crop production in Tyhume Valley communities.

Findings
Based on binary logit results, factors affecting rural farming households’ adaptation to climate variability are gender, age, heatwave, employment status, strong high wind occasional experience and cell phone. The adaptation measures adopted by the farming households in the study area include irrigation (94.8%), crop rotation (66%), changing crop variety (7.4%) and other methods of adaptation were found to be (1.3%). The other methods of adaptation used included the use of ash to kill (intuku) mole and using dirty water from washing dishes and clothes when irrigating to kill parasites on crops.

Originality/value
This research paper will be an addition to the body of knowledge on adaptation strategies to climate variability in South Africa, especially at the rural farming household level. This study may assist the rural communities in decision-making when dealing with the challenges of climate variability on their crop production, thereby increasing their crop production. The information gathered in this study might assist policymakers in revising the existing policies. This study will also help rural farming households to practice appropriate adaptation strategies.
The impact of new affective components on museum visitor retention: the context of major city event using SEM and CTree
Authors: Gorgadze Aleksei , Sinitsyna Anastasia , Trabskaya Julia , Bala To'neill 
Published: May 2021

PurposeThe main purpose of this study is to examine the relationship between ranges of affective components that have an impact on the revisit intention of museum visitors, in the context of a major city event. The study reveals the most significant factors that affect decision-making by applying the findings to a structural equation modelling (SEM) and conditional inference tree (CTree).Design/methodology/approachThe paper utilises face-to-face survey research at the “Long Night of Museums” event in Saint Petersburg, 298 questionnaires were completed on the night of the event. The empirical part of the research is based on the SEM and interpreted by using the CTree. The SEM model measures the direct and indirect influence of the cognitive and affective components; the CTree enables the testing of both component and the joint effect they both produce.FindingsThis study shows a strong indirect correlation between the cognitive component of the major city event and the revisit intention of museum visitors. When focussing on affective components, both the SEM and the CTree demonstrated that attractiveness and atmosphere are revealed to be the most impactful elements regarding visitor retention and repeat custom. The research allows for a deeper understanding of visitor behaviours, intentions and their decision-making processes.Practical implicationsThe results of the study allow museum managers to understand how to create repeat custom amongst visitors, by appreciating the importance of participation in major city events and the role that attraction and atmosphere play when creating intention for repeat visit. The research has uncovered which dimensions are the most important to visitors, and as a result, these particular dimensions should be thoroughly developed by museums in future in order to attract and repeat visits. This study has demonstrated the practical implications for museums participating in city events. When considering policy makers, this particular research provides an opportunity to develop recommendations for future city events, as well as using the CTree to assess and predict the effectiveness of visitor behaviour.Originality/valueThis is an original study which aims to integrate the impact of the perceived value of the cognitive component and a new range of affective elements regarding museum retention in the context of a major city event. The study includes newly developed dimensions of perceived value, as well as a unique focus on affective dimensions such as – atmosphere and attraction. Another point of originality is provided by using a CTree, which captures an in depth understanding of the intention formation process. This study provides an opportunity to advance our understanding of visitor decision-making processes.