bluuebunny/crossref_metadata_2025_split huggingface dataset:
SMEs growth and profitability, productivity and debt relationships
Authors: Serrasqueiro Zélia , Pinto Beatriz , Sardo Filipe 
Published: November 2023

PurposeThis study aims to seek to analyse the relationships between profitability, productivity, external debt and growth in SMEs. The authors also analyse firm size and age as explicative variables of small and medium-sized enterprise (SME) growth.Design/methodology/approachIn this paper the data were collected for 3309 SMEs for the period 2010–2019. The authors estimate the model using the system generalised method of moments dynamic estimator.FindingsThe results show that after a certain level of profitability, this determinant positively impacts SME growth. Productivity influences positively the firm growth. There is a positive effect of external debt on SME growth, which can be explained by the insufficiency of internally generated funds. The authors obtained a negative signal between size and firm growth, contradicting Gibrat's Law (1931). Moreover, the results suggest that SMEs grow less after a certain age, suggesting that small firms grow less after reaching the minimum scale of efficiency.Practical implicationsFor SME owner-managers, this study enhances the importance of profitability and labour productivity for firm growth. For policymakers, the results suggest the need for favourable conditions for SMEs in accessing external finance.Originality/valueProfitability negatively impacts on SME growth. However, the authors found that above a certain level of profitability, probably, as firms accumulate retained earnings, profitability has a positive effect on SME growth. Moreover, this study shows that labour productivity and debt positively impact on SME growth, evidencing the importance of the availability of financial resources to sustain the growth of these firms.
How policy designs influence the innovation performance of China's emergency industry: an institutional grammar perspective
Authors: Yang Chao , Jia Wei 
Published: November 2023

PurposeThis study provides a configurational examination of how policy designs influence the innovation performance of the emergency industry in China.Design/methodology/approachThis study employs the Data Envelopment Analysis Malmquist index (DEA-Malmquist) to quantify the innovation performance of the emergency industry and then codes the innovation policies to calculate the syntactic components based on institutional grammar tools (IGTs). The configurations of syntactic components were determined by applying the fuzzy-set qualitative comparative analysis (fsQCA).FindingsThe results indicate that rules- and norms-oriented policy designs would improve the innovation performance of China's emergency industry. In the developed provinces, the “Deontic” and “aIm” combinations in the policy are useful for improving performance. In the developing provinces, the ambiguity of the “aIm” and “Context” conditions in the policy is leading to low performance. Additionally, a lack of strategy-oriented policy design would also result in poor performance.Originality/valueMost previous studies used substitute variables to understand policy impacts. This study contributes to identifying the impacts of the syntactic components of policy designs on the innovation performance of the emergency industry. The findings can assist policymakers in developing more effective policies to stimulate innovation development in the emergency industry.
The impact of inclusive leadership on employees' innovative behavior – an intermediary model with moderation
Authors: Zhang Guangning , Zhao Wenjia 
Published: November 2023

PurposeThis study aims to explore the influence mechanism of inclusive leadership on employees' innovative behavior, in order to provide useful inspiration for leaders and enterprises to develop.Design/methodology/approachThis study constructs a moderated mediation model based on the valid questionnaire data of 211 employees in service in enterprises and used SPSS23.0 and AMOS24.0 analysis software to analyze the data and test the theoretical hypotheses, and explore the influence mechanism of inclusive leadership on employees' innovative behavior.FindingsThe empirical findings show that inclusive leadership has a significant positive impact on employees' innovative behavior; organizational harmony plays a mediating role in the relationship between inclusive leadership and employees' innovative behavior; and innovation self-efficacy plays a positive moderating role between organizational harmony and employees' innovative behavior. Therefore, inclusive leadership can create a harmonious organizational climate and further improve employees' innovative behavior under the influence of employees' creative self-efficacy, which can promote innovative behavior and sustainable development of enterprises.Originality/valueThe authors put two variables, organizational harmony and employees' innovation self-efficacy, into the same model for correlation tests for the first time, and introduced into the mechanism of inclusive leadership's influence on employees' innovation behavior, which broadened people's understanding of organizational harmony and innovation self-efficacy and broadened the ideas for the subsequent research about the relationship between them.
Cutaneous vasculitis in autoinflammatory diseases
Authors: Chen Ko‐Ron 
Published: November 2023

AbstractAutoinflammatory diseases (AIDs) characterized by recurrent episodes of localized or systemic inflammation are disorders of the innate immune system. Skin lesions are commonly found in AIDs and cutaneous vasculitis can coexist with AIDs and even present as the most striking feature. This review aims to focus on the frequent cutaneous vasculitis association in three monogenic AIDs including familial Mediterranean fever (FMF), deficiency of adenosine deaminase type 2 (DADA2), and the recently identified adult‐onset VEXAS (vacuoles, E1 enzyme, X‐linked, autoinflammatory, somatic) syndrome. Cutaneous vasculitis in FMF is characterized by: (1) small‐vessel vasculitis similar to IgA vasculitis with palpable purpura but increased intussusception complication and less vascular IgA deposit, and (2) cutaneous arteritis–like vasculitis presenting as subcutaneous nodules most often with higher glomerular involvement. DADA2 has a wide spectrum of clinical presentations ranging from fatal systemic vasculitis with multiple strokes, especially in pediatric patients, to limited cutaneous disease in middle‐aged patients. DADA2 shares similar clinical and histopathological features with polyarteritis nodosa (PAN). As a result, DADA2 is commonly initially misdiagnosed as childhood PAN. Livedo racemosa reveals the most common cutaneous manifestation of cutaneous vasculitis in patients with DADA2. VEXAS syndrome is a life‐threatening disease. A diagnosis of VEXAS syndrome should be strongly considered or could be made in patients with skin lesions characterized by Sweet syndrome–like eruption, livedo racemosa, concomitant relapsing polychondritis, deep venous thrombosis, pulmonary involvement, and progressive hematologic abnormalities such as myelodysplastic syndrome with a unique finding of cytoplasmic vacuoles in myeloid and erythroid precursor cells from bone marrow aspirate smear. As skin involvement is common in AIDs and may present as the most frequent manifestation, especially in DADA2 (70% to 90%) and VEXAS syndrome (83% to 91%), dermatologists play a crucial role in contributing to the early diagnosis of these AIDs with early initiation of the appropriate therapy to avoid progressing fatal outcomes.
Towards a mechanistic understanding of animal–ecosystem interactions
Authors: Meyer G. Adam , Leroux Shawn J. 
Published: November 2023

AbstractResearch Highlight: Ferraro, K. M., Welker, L., Ward, E. B., Schmitz, O. J., & Bradford, M. A. (2023). Plant mycorrhizal associations mediate the zoogeochemical effects of calving subsidies by a forest ungulate. Journal of Animal Ecology, https://doi.org/10.1111/1365‐2656.14002. Animals play large roles in ecosystem elemental cycling but predicting effects in diverse contexts remains a substantial challenge. Fundamental to progress is (1) identifying mechanisms by which animals impact nutrient distribution and cycling, and (2) disentangling how environmental context mediates the operation of alternative mechanisms. In an elegant field experiment, Ferraro et al. (2023) provide the first detailed exploration of the impact of nutrient inputs from mammalian parturition on soil functioning and the stoichiometry of plant tissues. The authors find that nitrogen from experimental additions of ungulate parturition material (natal fluids) is rapidly incorporated into microsite soil organic pools and plant tissues. They also find that soil processes (soil microbial biomass, rates of carbon mineralization, nitrogen mineralization and nitrification) and the nitrogen content of plant tissues above‐ and belowground are increased by addition of parturition material. Notably, the authors identify that increases in some soil processes and plant tissue nitrogen are weaker in microsites dominated by ericoid mycorrhizal plants than those dominated by ectomycorrhizal plants. These findings demonstrate that parturition depositions, a ubiquitous but overlooked mechanism of mammalian impacts on ecosystems, impact ecosystem processes and plant tissue stoichiometry. Furthermore, plant–fungal associations are a predictive axis of context dependency mediating zoogeochemical effects at fine scales. Ferraro et al.'s (2023) novel approach simultaneously advances mechanistic understanding of animal–ecosystem interactions at fine scales and facilitates prediction of ungulate effects on nutrient availability at landscape extents.
Measuring restrictiveness of Medicare Advantage networks: A claims‐based approach
Authors: Feyman Yevgeniy , Pizer Steven D. , Shafer Paul R. , Frakt Austin B. , Garrido Melissa M. 
Published: November 2023

AbstractObjectiveTo develop and validate a measure of provider network restrictiveness in the Medicare Advantage (MA) population.Data SourcesPrescription drug event data and beneficiary information for Part D enrollees from the Center for Medicare and Medicaid Services, along with prescriber identifiers; geographic variables from the Area Health Resources Files.Study DesignA prediction model was used to predict the unique number of primary care providers that would have been seen by MA beneficiaries absent network restrictions. The model was trained and validated on Traditional Medicare (TM) beneficiaries. A pseudo‐Poisson and a random forest model were evaluated. An observed‐to‐expected (O/E) ratio was calculated as the number of unique providers seen by MA beneficiaries divided by the number expected based the TM prediction model. Multivariable linear models were used to assess the relationship between network restrictiveness and plan and market factors.Data Collection/Extraction MethodsPrescription drug event data were obtained for a 20% random sample of beneficiaries enrolled in prescription drug coverage from 2011 to 2017.Principal FindingsHealth Maintenance Organization plans were more restrictive (O/E = 55.5%; 95% CI 55.3%–55.7%) than Health Maintenance Organization‐Point of Service plans (67.2%; 95% CI 66.7%–67.8%) or Preferred Provider Organization plans (74.7%; 95% CI 74.3%–75.1%), and rural areas had more restrictive networks (31.6%; 95% CI 29.0%–34.2%) than metropolitan areas (61.5%; 95% CI 61.3%–61.7%). Multivariable results confirmed these findings, and also indicated that increased provider supply was associated with less restrictive networks.ConclusionsWe developed a means of estimating provider network restrictiveness in MA from claims data. Our results validate the approach, providing confidence for wider application (e.g., for other markets and specialties) and use for regulation.
Trout bioenergetics as a process‐based tool to estimate ecological risk in a regulated river
Authors: Rhoades Suzanne J. , Caldwell Timothy J. , McBain Scott , Henery Rene , Stauffer‐Olsen Natalie , McKinnon Tara , Rossi Gabriel J. , Chandra Sudeep 
Published: November 2023

AbstractBioenergetics models produce quantitative flow‐ecology relationships that summarize changes in habitat and food resources from altered flows. We used a drift‐foraging bioenergetics model to quantify the net rate of energetic intake (NREI) for trout above and below a water diversion. NREI is reduced by >95% below the water diversion in July–September, when up to 98% of unimpaired flows are diverted. We then used a risk‐based approach to estimate the maximum diversion rate, expressed as a percentage of unimpaired flow, that would produce NREI values that are not significantly lower than values under unimpaired flows throughout a 62‐year period. NREI decreased with increased precent‐of‐flow diversion rates in low‐flow months (July–September). Diversion rates of 16% in July and 9% in August and September would maintain NREI within the range of unimpaired flow conditions. In higher flow months, May–June, increasing diversions brought estimated instream flows closer to the peak NREI flow, leading to the assessment that increased diversions would increase NREI. Bioenergetic models can be used to develop protective flow rates at times of the year when fish growth and production would be high under unimpaired flows, which often coincides with when water is diverted. Our study is the first to develop protective percent‐of‐flow diversion rates for holistic flow management using a quantitative process‐based and fish‐centric ecological metric.
Spatial market integration during a pandemic: Evidence from food markets in Nigeria
Authors: Amare Mulubrhan , Abay Kibrom A. , Hatzenbuehler Patrick 
Published: November 2023

AbstractThis paper uses comprehensive and long time series monthly food price data and a panel dyadic regression framework to evaluate the impact of the COVID‐19 pandemic and associated policy responses on spatial market integration across a diverse set of food items in Nigeria. The empirical results reveal several important insights. First, we show that a significant slowdown in the speed of adjustment and price transmission occurred during the pandemic. For some food items, the speed of adjustment and, by implication, spatial market integration weakened by two‐ to‐threefold after the outbreak of the pandemic. The effect was especially pronounced for perishable food items. Second, lockdown measures and the spread of the pandemic triggered additional dispersion in market prices across markets. For example, lockdown measures were associated with a 5%–10% reduction in the speed of readjustment toward long‐term equilibrium. Third, additional underlying attributes of markets, including lack of access to digital infrastructure and distance between markets, exacerbated impacts associated with the pandemic. For instance, access to Internet service reduced the slowdown in the speed of adjustment caused by the pandemic, but longer distances between market pairs induced greater slowdown in the speed of price transmission. Our findings offer important insights for revitalizing the efficiency of food markets affected by the pandemic. The heterogenous impacts of the pandemic across value chains and markets reinforce the need to properly target post‐pandemic recovery interventions and investments. Finally, we offer some insights to reduce the vulnerability of food and market systems to disruptions in future pandemics or similar phenomena that inhibit food marketing and trade.
Kinetic–pharmacodynamic model of warfarin for prothrombin time–international normalized ratio in Japanese patients
Authors: Hirai Toshinori , Aoyama Takahiko , Tsuji Yasuhiro , Itoh Toshimasa , Matsumoto Yoshiaki , Iwamoto Takuya 
Published: November 2023

AimsGenotype‐guided dosing algorithms can explain about half of the interindividual variability in prothrombin time–international normalized ratio (PT‐INR) under warfarin treatment. This study aimed to refine a published kinetic–pharmacodynamic model and guide warfarin dosage for an optimal PT‐INR based on renal function.MethodsUsing a retrospective cohort of adult patients (>20 years) who were administered warfarin and underwent PT‐INR measurements, we refined the kinetic–pharmacodynamic model with age and the genotypes of cytochrome P450 2C9 and vitamin K epoxide reductase complex subunit 1 using the PRIOR subroutine in the nonlinear‐mixed‐effect modelling programme. We searched the significant covariates for parameters, such as the dose rate for 50% inhibition of coagulation (EDR50), using a stepwise forward and backward method. Monte Carlo simulation determined a required daily dose of warfarin with a target range of PT‐INR (2.0–3.0 or 1.6–2.6) based on the significant covariates.ResultsA total of 350 patients with 2762 PT‐INR measurements were enrolled (estimated glomerular filtration rate [eGFR]: 47.5 [range: 2.6–199.0] mL/min/1.73 m2). The final kinetic–pharmacodynamic model showed that the EDR50 changed power functionally with body surface area, serum albumin level and eGFR. Monte Carlo simulation revealed that a lower daily dose of warfarin was required to attain the target PT‐INR range as eGFR decreased.ConclusionsModel‐informed precision dosing of warfarin is a valuable approach for estimating its dosage in patients with renal impairment.
On generating plausible values for multilevel modelling with large‐scale‐assessment data
Authors: Zheng Xiaying 
Published: November 2023

AbstractLarge‐scale assessments (LSAs) routinely employ latent regressions to generate plausible values (PVs) for unbiased estimation of the relationship between examinees' background variables and performance. To handle the clustering effect common in LSA data, multilevel modelling is a popular choice. However, most LSAs use single‐level conditioning methods, resulting in a mismatch between the imputation model and the multilevel analytic model. While some LSAs have implemented special techniques in single‐level latent regressions to support random‐intercept modelling, these techniques are not expected to support random‐slope models. To address this gap, this study proposed two new single‐level methods to support random‐slope estimation. The existing and proposed methods were compared to the theoretically unbiased multilevel latent regression method in terms of their ability to support multilevel models. The findings indicate that the two existing single‐level methods can support random‐intercept‐only models. The multilevel latent regression method provided mostly adequate estimates but was limited by computational burden and did not have the best performance across all conditions. One of our proposed single‐level methods presented an efficient alternative to multilevel latent regression and was able to recover acceptable estimates for all parameters. We provide recommendations for situations where each method can be applied, with some caveats.
Integrating microbiome science and evolutionary medicine into animal health and conservation
Authors: Bornbusch Sally L. , Power Michael L. , Schulkin Jay , Drea Christine M. , Maslanka Michael T. , Muletz‐Wolz Carly R. 
Published: November 2023

ABSTRACTMicrobiome science has provided groundbreaking insights into human and animal health. Similarly, evolutionary medicine – the incorporation of eco‐evolutionary concepts into primarily human medical theory and practice – is increasingly recognised for its novel perspectives on modern diseases. Studies of host–microbe relationships have been expanded beyond humans to include a wide range of animal taxa, adding new facets to our understanding of animal ecology, evolution, behaviour, and health. In this review, we propose that a broader application of evolutionary medicine, combined with microbiome science, can provide valuable and innovative perspectives on animal care and conservation. First, we draw on classic ecological principles, such as alternative stable states, to propose an eco‐evolutionary framework for understanding variation in animal microbiomes and their role in animal health and wellbeing. With a focus on mammalian gut microbiomes, we apply this framework to populations of animals under human care, with particular relevance to the many animal species that suffer diseases linked to gut microbial dysfunction (e.g. gut distress and infection, autoimmune disorders, obesity). We discuss diet and microbial landscapes (i.e. the microbes in the animal's external environment), as two factors that are (i) proposed to represent evolutionary mismatches for captive animals, (ii) linked to gut microbiome structure and function, and (iii) potentially best understood from an evolutionary medicine perspective. Keeping within our evolutionary framework, we highlight the potential benefits – and pitfalls – of modern microbial therapies, such as pre‐ and probiotics, faecal microbiota transplants, and microbial rewilding. We discuss the limited, yet growing, empirical evidence for the use of microbial therapies to modulate animal gut microbiomes beneficially. Interspersed throughout, we propose 12 actionable steps, grounded in evolutionary medicine, that can be applied to practical animal care and management. We encourage that these actionable steps be paired with integration of eco‐evolutionary perspectives into our definitions of appropriate animal care standards. The evolutionary perspectives proposed herein may be best appreciated when applied to the broad diversity of species under human care, rather than when solely focused on humans. We urge animal care professionals, veterinarians, nutritionists, scientists, and others to collaborate on these efforts, allowing for simultaneous care of animal patients and the generation of valuable empirical data.
Discovery and development of COVID‐19 vaccine from laboratory to clinic
Authors: Saravanan Venkatesan , Chagaleti Bharath Kumar , Narayanan Pavithra Lakshmi , Anandan Vijay Babu , Manoharan Haritha , Anjana G.V. , Peraman Ramalingam , Namasivayam S. Karthik Raja , Kavisri M. , Arockiaraj Jesu , Muthu Kumaradoss Kathiravan , Moovendhan Meivelu 
Published: November 2023

AbstractThe world has recently experienced one of the biggest and most severe public health disasters with severe acute respiratory syndrome coronavirus (SARS‐CoV‐2). SARS‐CoV‐2 is responsible for the coronavirus disease of 2019 (COVID‐19) which is one of the most widespread and powerful infections affecting human lungs. Current figures show that the epidemic had reached 216 nations, where it had killed about 6,438,926 individuals and infected 590,405,710. WHO proclaimed the outbreak of the Ebola virus disease (EVD), in 2014 that killed hundreds of people in West Africa. The development of vaccines for SARS‐CoV‐2 becomes more difficult due to the viral mutation in its non‐structural proteins (NSPs) especially NSP2 and NSP3, S protein, and RNA‐dependent RNA polymerase (RdRp). Continuous monitoring of SARS‐CoV‐2, dynamics of the genomic sequence, and spike protein mutations are very important for the successful development of vaccines with good efficacy. Hence, the vaccine development for SARS‐CoV‐2 faces specific challenges starting from viral mutation. The requirement of long‐term immunity development, safety, efficacy, stability, vaccine allocation, distribution, and finally, its cost is discussed in detail. Currently, 169 vaccines are in the clinical development stage, while 198 vaccines are in the preclinical development stage. The majority of these vaccines belong to the Ps—Protein subunit type which has 54, and the minor BacAg‐SPV (Bacterial antigen‐spore expression vector) type, at least 1 vaccination. The use of computational methods and models for vaccine development has revolutionized the traditional methods of vaccine development. Further, this updated review highlights the upcoming vaccine development strategies in response to the current pandemic and post‐pandemic era, in the field of vaccine development.