bluuebunny/crossref_metadata_2025_split huggingface dataset:
SARS-CoV-2 infects multiple species of North American deer mice and causes clinical disease in the California mouse
Authors: Lewis Juliette , Zhan Shijun , Vilander Allison C. , Fagre Anna C. , Kiaris Hippokratis , Schountz Tony 
Published: August 2022

ABSTRACTSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the virus that causes coronavirus disease-19 (COVID-19), emerged in late 2019 in Wuhan, China and its rapid global spread has resulted in millions of deaths. An important public health consideration is the potential for SARS-CoV-2 to establish endemicity in a secondary animal reservoir outside of Asia or acquire adaptations that result in new variants with the ability to evade the immune response and reinfect the human population. Previous work has shown that North American deer mice (Peromyscus maniculatus) are susceptible and can transmit SARS-CoV-2 to naïve conspecifics, indicating its potential to serve as a wildlife reservoir for SARS-CoV-2 in North America. In this study, we report experimental SARS-CoV-2 susceptibility of two additional subspecies of the North American deer mouse and two additional deer mouse species, with infectious virus and viral RNA present in oral swabs and lung tissue of infected deer mice and neutralizing antibodies present at 15 days post-challenge. Moreover, some of one species, the California mouse (P. californicus) developed clinical disease, including one that required humane euthanasia. California mice often develop spontaneous liver disease, which may serve as a comorbidity for SARS-CoV-2 severity. The results of this study suggest broad susceptibility of rodents in the genus Peromyscus and further emphasize the potential of SARS-CoV-2 to infect a wide array of North American rodents.ImportanceA significant concern is the spillback of SARS-CoV-2 into North American wildlife species. We have determined that several species of peromyscine rodents, the most abundant mammals in North America, are susceptible to SARS-CoV-2 and that infection is likely long enough that the virus may be able to establish persistence in local rodent populations. Strikingly, some California mice developed clinical disease that suggests this species may be useful for the study of human co-morbidities often associated with severe and fatal COVID-19 disease.
Automatic Retinoblastoma Screening and Surveillance Using Deep Learning
Authors: Zhang Ruiheng , Dong Li , Li Ruyue , Zhang Kai , Li Yitong , Zhao Hongshu , Shi Jitong , Ge Xin , Xu Xiaolin , Jiang Libin , Shi Xuhan , Zhang Chuan , Zhou Wenda , Xu Liangyuan , Wu Haotian , Li Heyan , Yu Chuyao , Li Jing , Ma Jianmin , Wei Wenbin 
Published: August 2022

ABSTRACTRetinoblastoma is the most common intraocular malignancy in childhood. With the advanced management strategy, the global salvage and overall survival have significantly improved, which proposes subsequent challenges regarding long-term surveillance and offspring screening. Here, we developed deep learning algorithm, called Deep Learning Assistant for Retinoblastoma (DLA-RB) training on A total of 36623 images from 713 patients. We validated it in the prospectively collected dataset, comprised of 1366 images form 139 eyes of 103 patients. In identifying active retinoblastoma tumors (treatment required) from all clinical-suspected patients, the area under the receiver operating characteristic curve (AUC) of DLA-RB reached 0.991 (95% CI 0.970-1.000). In identifying active retinoblastoma from stable retinoblastoma patients (treatment is not required), AUC of DLA-RB reached 0.962 (95% CI 0.915-1.000), respectively. Cost-utility analysis revealed that DLA-RB based diagnosis mode is more cost-effective in both retinoblastoma diagnosis and retinoblastoma activity surveillance. The DLA-RB achieved high accuracy and sensitivity in identifying active retinoblastoma from the normal and stable retinoblastoma fundus. It can be incorporated within telemedicine programs in the future.
Human resource management practices and innovation in Colombian firms
Authors: Costamagna Rodrigo , Idrovo-Carlier Sandra , Mendi Pedro , Rodriguez Alfredo 
Published: August 2022

PurposeThis paper takes a closer look at the way firms combine human resources from different departments by analyzing firm-level data obtained from a series of innovation surveys conducted in Colombia by Departamento Administrativo Nacional de Estadística (DANE). In particular, the authors inquire into whether there are differences in innovation performance between firms that combine human resources from different departments and firms that choose not to do so.Design/methodology/approachThe authors apply a complementarity test between firms that combine human resources from different departments and firms that choose not to do so. As performance variables, the authors consider the propensity to innovate, the number of new innovative products that the firm introduces, the proportion of sales coming from products new to the firm and sales from new products as a percentage of current innovation expenditures.FindingsThe authors find that firms with an internal research and development (R&D) department have a better innovation performance, but the authors do not find evidence of the existence of complementarity between workers in R&D and workers in other departments, and the authors find some evidence that suggests substitutability in the case of product innovations.Practical implicationsThis paper provides managers with insights about how to deploy employees to improve firm innovation performance of employees.Originality/valueThis paper combines innovation literature with human resources management literature and applies a robust methodology to data not previously tested for the same purposes.
The mobilization of employees’ psychological resources: how servant leadership motivates pro-customer deviance
Authors: Hu Jiajing , Xiong Lin , Zhang Mengying , Chen Chen 
Published: August 2022

Purpose
Drawing on social learning theory and conservation of resources theory, this study aims to investigate how servant leadership (SL) is linked to employees’ pro-customer deviance (PCD) through the serial mediating effects of perceived organizational support for creativity (POS) and creative self-efficacy (CSE), work autonomy (WA) and CSE.

Design/methodology/approach
This study used an online questionnaire survey platform to accurately distribute the questionnaire to the target population. Data were collected from 439 frontline employees working in hotels. The data were analyzed with a structural equation modeling approach to identify the complex relationship.

Findings
Using an online survey, this study demonstrated the significant positive effect of SL on PCD and further revealed the two serial mediating paths (POS → CSE; WA → CSE) of the SL effect.

Practical implications
The findings of this research generate valuable implications for practitioners and managers. Managers need to be aware of the objectivity and universality of PCD in service delivery scenarios and fully understand how their leadership style influences the internal motivation and external performance of employees engaged in this behavior.

Originality/value
This study makes a prominent contribution to the hospitality literature by focusing on PCD. This study enriches the research on the antecedents of PCD, constructs a cross-level multipath mechanism model of PCD in the context of SL and reveals the rationalization process and nature of employees’ PCD.
PLS-SEM’s most wanted guidance
Authors: Becker Jan-Michael , Cheah Jun-Hwa , Gholamzade Rasoul , Ringle Christian M. , Sarstedt Marko 
Published: August 2022

Purpose
Partial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in hospitality management research. As PLS-SEM is relatively new compared to other multivariate analysis techniques, there are still numerous open questions and uncertainties in its application. This study aims to address this important issue by offering guidance regarding its use in contexts with which researchers struggle.

Design/methodology/approach
The authors examine the most prominent questions and answers posed in a well-known PLS-SEM discussion forum. The authors do so by using a text analysis technique to identify the most salient topics.

Findings
The data analysis identifies three salient PLS-SEM topics (i.e. bootstrapping and significance testing, higher-order constructs and moderation).

Research limitations/implications
The results allow us to address the PLS-SEM community’s main methodological issues. The authors discuss each area separately and provide explanations and guidelines.

Practical implications
The guidelines on the most important PLS-SEM topics provide decision-making and application aids. In this way, the authors make a decisive contribution to clarifying ambiguities when applying the PLS-SEM method in hospitality management research and other disciplines.

Originality/value
There has as yet been no systematic analysis of this kind in the field of PLS-SEM; the authors, therefore, present the first research results. The findings and recommendations provide guidance for PLS-SEM applications in hospitality research and practice.
Does digital technology adoption affect COVID-19 health outcomes? A quantitative analysis on the global level
Authors: Yazdi Faezeh , Rasoulyan Farzin , Mirnezami Seyed Reza 
Published: August 2022

Purpose
Adopting digital technology could facilitate the public health response to the COVID-19 pandemic. Some analysts argue that countries that adopted digital technology in their health sector have managed to control the virus better (Whitelaw et al., 2020). For instance, countries with more comprehensive contact tracing have significantly lower fatality rates (Yalaman et al., 2021). Moreover, World Health Organization (WHO) believes this technology is a crucial enabler for countries to meet the current challenge (WHO. Regional Office for the Western Pacific & University of Melbourne, 2021). In this regard, this study aims to quantitatively find the relationship between the technological advancement of countries and COVID-19 health outcomes, using seven technological indices that measure technological advancement.

Design/methodology/approach
The authors used the multiple linear regression method to answer the research questions. The first analysis focuses on a cross section of all countries worldwide, and the second focuses on European countries for which weekly death statistics exist after the pandemic.

Findings
The findings support those countries with more technological abilities managed to control the virus’s mortality better, as evidenced by the negative link between the mortality rate of COVID-19 and the technological factors at the national level. Results also reveal that technology adoption decreases the death risk due to COVID-19 in countries with more elderly people. The authors may argue that technological advancement positively correlates with the number of deaths and diagnosed cases because the authors can better collect data or because the virus spreads due to higher economic and business activities. However, such technological advancement significantly decreases the death risk (lower mortality rate in the first analysis and lower mortality rate for elderly people in the second analysis).

Research limitations/implications
Three important conclusions could be made from the results: a lower mortality rate is generally expected for countries adopting advanced technology; technological advancement significantly decreases the death risk for elderly people; and a higher technology adoption level does not necessarily result in fewer diagnosed cases of/death due to COVID-19.

Originality/value
Although some studies have focused on e-health applications in the public health response to the COVID-19 pandemic, no studies, to the best of the authors’ knowledge, have tried to quantify its efficacy, most especially on the global level.
Revenue sharing bids of a loss-averse supplier for a new product development contract: a multi-method investigation
Authors: Ribbink Dina , Pun Hubert , Yan Tingting 
Published: August 2022

PurposeWhen developing a new product, a buying firm solicits revenue sharing bids from two competing suppliers. Bidding behaviors of suppliers do not always align with predictions from rational agent models due to task uncertainty and bounded rationality, which could result in non-optimal supplier offers and ultimately hurt buying firm interests. This paper aims to discuss the aforementioned issues.Design/methodology/approachThe authors built an analytical model that considers the impact of supplier technological risk, buyer–supplier coordination cost and supplier loss aversion on the optimal bid of the supplier. Next, using limited information processing capacity as a theoretic lens, the authors explore antecedents to the size of a focal supplier's bidding error, the absolute difference between the actual bid and the optimal bid. The authors used quantitative lab experimental data to test the hypotheses.Findings(1) Bounded rational bidders often fail to differentiate between relevant and irrelevant competitive information when placing bids, (2) loss aversion of a bidder significantly affects not only levels of bids, particularly for bidders with competitive disadvantages, but also sizes of the bidding error and (3) competitive information that has clearer performance implications are more influential in reducing sizes of bidding errors.Originality/valueThe results provide a comprehensive view of the bidding behaviors of a bounded rational supplier in an innovation outsourcing context with competition. With the results, managers now have a better understanding of behavioral influencers behind non-optimal supplier bids in an innovation outsourcing context.
Surface quality prediction and lapping process optimisation on the fixed-abrasive lapping plate of sapphire wafers
Authors: Wang Yanfu , Wang Xin , Liu Lifei 
Published: August 2022

Purpose
Lapping is a vital flattening process to improve the quality of processed semiconductor wafers such as single-crystal sapphire wafers. This study aims to optimise the lapping process of the fixed-abrasive lapping plate of sapphire wafers with good overall performance [i.e. high material removal rate (MRR), small surface roughness (Ra) of the wafers after lapping and small lapping plate wear ratio (η)].

Design/methodology/approach
The influence of process parameters such as lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed on MRR, Ra and η of lapping-processed sapphire wafers was studied, and the results were combined with experimental data to establish a regression model. The multi-evaluation index optimisation problem was transformed into a single-index optimisation problem via an entropy method and the grey relational analysis (GRA) to comprehensively evaluate the performance of each parameter.

Findings
The results revealed that lapping time, abrasive size, abrasive concentration, lapping pressure and lapping speed had different influence degrees on MRR, Ra and η. Among these parameters, lapping time, lapping speed and abrasive size had the most significant effects on MRR, Ra and η, and the established regression equations predicted the response values of MRR, Ra and η to be 99.56%, 99.51% and 93.88% and the relative errors between the predicted and actual measured values were <12%, respectively. With increased lapping time, MRR, Ra and η gradually decreased. With increased abrasive size, MRR increased nearly linearly, whereas Ra and η initially decreased but subsequently increased. With an increase in abrasive concentration, MRR, Ra and η initially increased but subsequently decreased. With increased lapping pressure, MRR and η increased nearly linearly and continuously, whereas Ra decreased nearly linearly and continuously. With increased lapping speed, Ra initially decreased sharply but subsequently increased gradually, whereas η initially increased sharply but subsequently decreased gradually; however, the change in MRR was not significant. Comparing the optimised results obtained via the analysis of influence law, the parameters optimised via the entropy method and GRA were used to obtain sapphire wafers lapping with an MRR of 4.26 µm/min, Ra of 0.141 µm and η of 25.08, and the lapping effect was significantly improved.

Originality/value
Therefore, GRA can provide new ideas for ultra-precision processing and process optimisation of semiconductor materials such as sapphire wafers.
Photocatalytic degradation of dye (Reactive Red 198) and pharmaceutical (tetracycline) using MIL-53(Fe) and MIL-100(Fe): catalyst synthesis and pollutant degradation
Authors: Ahmadi Shahin , Mahmoodi Bahaaddin , Kazemini Mohammad , Mahmoodi Niyaz Mohammad 
Published: August 2022

Purpose
Environmental issues and lack of drinking water have forced researchers to find some alternatives to wastewater treatment. Because dyes are used in a variety of industrial applications such as textile and pharmaceutical, wastewater of these factories leads to several environmental problems. Using catalysis under ultraviolet-irradiation (photocatalysis) is one of the cases that is used in wastewater treatment. The purpose of this work is the photocatalytic degradation of dye (Reactive Red 198) and pharmaceutical (tetracycline) using MIL-53(Fe) and MIL-100(Fe).

Design/methodology/approach
In this work, Reactive Red 198 (RR198), an anionic dye and tetracycline as a pharmaceutical are tested with two catalysts, MIL-53(Fe) and MIL-100(Fe). Catalyst synthesis method and characterization were discussed by X-ray diffraction, scanning electron microscopy and Fourier Transform Infrared analyses, and their results are described in detail.

Findings
Dye concentration varies among 15, 20, 30 and 40 mg/L for MIL-100(Fe) for which the removal percent is 97%, 94%, 89% and 58% and for MIL-53(Fe), dye concentration increases from 20 to 40, 60 and 80 mg/L, the removal percent of which is 98%, 88%, 75% and 50%. Pharmaceutical degradation by MIL-53(Fe) and MIL-100(Fe) was 75% and 80%, respectively.

Originality/value
Photocatalytic degradation of RR198 and tetracycline using MIL-53(Fe) and MIL-100(Fe) was not studied in detail.
Novel compound heterozygous mutations in the PLEC gene in a neonate with epidermolysis bullosa simplex with pyloric atresia
Authors: Kaneyasu Hidenobu , Takahashi Kazumasa , Ohta Naoki , Okada Seigo , Kimura Sasagu , Yasuno Shuichiro , Murata Susumu , Katsura Shunsaku , Yamada Naoyuki , Shiraishi Koji , Tsuda Junko , Miyai Shunsuke , Kurahashi Hiroki , Hasegawa Shunji , Shimomura Yutaka 
Published: August 2022

AbstractEpidermolysis bullosa (EB) is a heterogeneous group of inherited disorders characterized by the blistering of the skin and mucous membranes. Although the molecular basis of EB has been significantly elucidated, the precise phenotypes of the lethal types of EB have not been completely characterized. Herein, we report a severe case of EB with pyloric atresia (PA). The patient was a Japanese boy who not only had skin lesions but also various complications such as PA, dysphagia, hypotonia, infectious keratitis with corneal ulcer, obstructive uropathy and protein‐losing enteropathy. Genetic analysis led to the identification of two novel compound heterozygous mutations in the last exon of the plectin (PLEC) gene. Based on this finding, EB simplex with PA was diagnosed. Immunostaining with anti‐plectin antibodies revealed truncated plectin proteins lacking the C‐terminus in the patient's skin. We also conducted a prenatal diagnosis in subsequent pregnancy. Our report further highlights the crucial role of plectin in many organs and provides valuable information regarding the phenotypes resulting from mutations in the PLEC gene.
Dissecting cellulitis of the scalp with typical clinical features: A retrospective cross‐sectional study in a Department of Dermatology, Beijing, China
Authors: Jiang Tiande , Liu Cuie 
Published: August 2022

AbstractDissecting cellulitis of the scalp (DCS) is a rare skin disease and understudied. The aim of the study was to collect the demographic, clinical features and laboratory tests of patients with DCS in a dermatology outpatient clinic. A cross‐sectional study was conducted in a department of dermatology in Beijing. Patients whose diagnoses have included DCS were selected from July 2021 to December 2021. DCS patients were stratified according to whether they were follicular occlusion triad (FOT) or not. There were 169 patients with DCS included. All 169 patients were male, and the median patient age was 32 years. The most common comorbidities in this study were seborrheic dermatitis (10.65%). Over 1/3 of patients had elevated white blood cell (WBC) and neutrophil counts, and 12 of 18 patients had dyslipidemia. CD8+ T cell counts increased in 15 of 26 patients while CD4+ T/CD8+ T ratios were all normal. DCS mainly affects men in their thirties. More research about DCS is needed to clarify the clinical significance of laboratory tests.
NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations
Authors: Khalighifar Ali , Gotthold Benjamin S. , Adams Erin , Barnett Jenny , Beard Laura O. , Britzke Eric R. , Burger Paul A. , Chase Kimberly , Cordes Zackary , Cryan Paul M. , Ferrall Emily , Fill Christopher T. , Gibson Scott E. , Haulton G. Scott , Irvine Kathryn M. , Katz Lara S. , Kendall William L. , Long Christen A. , Mac Aodha Oisin , McBurney Tessa , McCarthy Sara , McKown Matthew W. , O'Keefe Joy , Patterson Lucy D. , Pitcher Kristopher A. , Rustand Matthew , Segers Jordi L. , Seppanen Kyle , Siemers Jeremy L. , Stratton Christian , Straw Bethany R. , Weller Theodore J. , Reichert Brian E. 
Published: August 2022

Abstract

Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community‐driven conservation solutions.

Here, we present NABat ML, an automated machine‐learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet‐based computing resources (‘cloud environment’), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future ‘unseen’ data. We evaluated model performance using a comprehensive, independent, holdout dataset.

NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted‐average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud‐environment computing instance, the entire model training process took <16 h.

Synthesis and applications. Our convolutional neural network (CNN)‐based model, NABat ML, classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species‐level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open‐source and reproducible, enabling future implementations as software on end‐user devices and cloud‐based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big‐data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad‐scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species.