bluuebunny/crossref_metadata_2025_split huggingface dataset:
CoAtGIN: Marrying Convolution and Attention for Graph-based Molecule Property Prediction
Authors: Zhang Xuan , Chen Cheng , Meng Zhaoxu , Yang Zhenghe , Jiang Haitao , Cui Xuefeng 
Published: August 2022

AbstractMolecule property prediction based on computational strategy plays a key role in the process of drug discovery and design, such as DFT. Yet, these traditional methods are time-consuming and labour-intensive, which can’t satisfy the need of biomedicine. Thanks to the development of deep learning, there are many variants of Graph Neural Networks (GNN) for molecule representation learning. However, whether the existed well-perform graph-based methods have a number of parameters, or the light models can’t achieve good grades on various tasks. In order to manage the trade-off between efficiency and performance, we propose a novel model architecture, CoAtGIN, using both Convolution and Attention. On the local level, k-hop convolution is designed to capture long-range neighbour information. On the global level, besides using the virtual node to pass identical messages, we utilize linear attention to aggregate global graph representation according to the importance of each node and edge. In the recent OGB Large-Scale Benchmark, CoAtGIN achieves the 0.0933 Mean Absolute Error (MAE) on the large-scale dataset PCQM4Mv2 with only 5.6 M model parameters. Moreover, using the linear attention block improves the performance, which helps to capture the global representation.
Dear-DIAXMBD: deep autoencoder for data-independent acquisition proteomics
Authors: He Qingzu , Zhong Chuan-Qi , Li Xiang , Guo Huan , Li Yiming , Gao Mingxuan , Yu Rongshan , Liu Xianming , Zhang Fangfei , Guo Tiannan , Guo Donghui , Ye Fangfu , Shuai Jianwei , Han Jiahuai 
Published: August 2022

AbstractData-independent acquisition (DIA) technology for protein identification from mass spectrometry and related algorithms is developing rapidly. The spectrum-centric analysis of DIA data without the use of spectra library from data-dependent acquisition (DDA) data represents a promising direction. In this paper, we proposed an untargeted analysis method, Dear-DIAXMBD, for direct analysis of DIA data. Dear-DIAXMBD first integrates the deep variational autoencoder and triplet loss to learn the representations of the extracted fragment ion chromatograms, then uses the k-means clustering algorithm to aggregate fragments with similar representations into the same classes, and finally establishes the inverted index tables to determine the precursors of fragment clusters between precursors and peptides, and between fragments and peptides. We show that Dear-DIAXMBD performs superiorly with the highly complicated DIA data of different species obtained by different instrument platforms. Dear-DIAXMBD is publicly available at https://github.com/jianweishuai/Dear-DIA-XMBD.
Medication Clusters at Hospital Discharge and Risk of Adverse Drug Events at 30-days Post-Discharge: A Population-based Cohort Study of Older Adults
Authors: Weir Daniala L. , Ma Xiaomeng , McCarthy Lisa , Tang Terence , Lapointe-Shaw Lauren , Wodchis Walter P. , Fernandes Olavo , McDonald Emily G. 
Published: August 2022

ABSTRACTBackground:Certain combinations of medications can be harmful and may lead to serious drug-drug interactions. Identifying potentially problematic medication clusters could help guide prescribing decisions in hospital.Objectives:To characterize medication prescribing patterns at hospital discharge and determine which medication clusters are associated with an increased risk of adverse drug events (ADEs) in the 30-days post hospital discharge.Methods:All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016-February 2017 were included. Identification of medication prescribing clusters at hospital discharge was conducted using latent class analysis. Cluster identification was based on medications dispensed 30-days post-hospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs post-discharge, while also evaluating other patient characteristics.Results:188,354 patients were included in the study cohort. Median age (IQR) was 77 (71-84) and patients had a median (IQR) of 9 (6-13) medications dispensed in the year prior to admission. The study population consisted of 6 separate clusters of dispensing patterns post discharge: Cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%) and surgical (24%). Overall, 12,680 (7%) patients had an ADE in the 30-days following discharge. After considering other patient characteristics, those in the respiratory cluster had the highest risk of ADEs (aOR: 1.12, 95% CI: 1.08-1.17) compared to all the other clusters, while those in the neurocognitive & complex care needs cluster had the lowest risk (aOR:0.82, 95% CI: 0.77-0.87).Conclusion:This study suggests that ADEs post hospital discharge are linked to identifiable clusters of medications, in addition to non-modifiable patient characteristics, such as age and certain comorbidities. This information may help clinicians and researchers better understand what patient populations and which types of interventions may benefit patients, to reduce their risk of experiencing an ADE.KEY POINTSThis study suggests that ADEs post hospital discharge are linked to identifiable clusters of medications, in addition to non-modifiable patient characteristics, such as age and certain comorbidities. This information may help clinicians and researchers better understand what patient populations and which types of interventions may benefit patients, to reduce their risk of experiencing an ADE.PLAIN LANGUAGE SUMMARYCertain combinations of medications prescribed to patients when they are being discharged from hospital can increase the risk of adverse events after hospital discharge.
Evaluation of Association between CSN2 Genetic Marker 7:32016718C>A with A1/A2 Milk in Pakistani Buffaloes
Authors: Mushtaq Mehwish , Saif Rashid , Raza Muhammad Hassan , Zafar Muhammad Osama , Ahmed Zubair , Ullah Sibghat , Ahmad Mateen , Karim Asma 
Published: August 2022

AbstractMilk is an essential part of the diet that plays an important role in human growth and development due to the presence of different components like calcium, fats and proteins. Among six major proteins of the milk, β-casein is one of them which is being investigated here due to the A1/A2 milk genetic variants and its associated gene of CSN2 in one of the valued species of Bubalus bubalis in Pakistan. Fifty buffalo samples were genotyped using the ARMS-PCR technique. CSN2 gene locus 32016718C>A is located on Chr.7 with CDS position c.350C>A on its 7th exon as per (GenBank transcript ID: XM_006071124.3). In β-casein, 117th amino acid position where histidine (CAT) is responsible for A1 and proline (CCT) for A2 milk phenotype. A2 milk is considered to be healthy for human health due to the absence of bioactive peptide β-casomorphin-7 (BCM7) in comparison with A1 milk. The current results showed that overall, 100% buffalo population is homozygous wild-type (CC) which means no mutant allele is detected in all studied samples therefore, Pakistani buffalo is exclusively producing A2 milk. Furthermore, this work may also be conducted on different buffalo breeds in Pakistan as well as other species of cattle, goat, sheep and camel to explore their genomic architecture for this valued trait.
The Botrytis cinerea Gene Expression Browser
Authors: Pérez-Lara Gabriel , Moyano Tomás C. , Vega Andrea , Larrondo Luis F. , Polanco Rubén , Álvarez José M. , Aguayo Daniel , Canessa Paulo 
Published: August 2022

AbstractTo analyze and visualize comprehensive gene expression patterns in the phytopathogenic fungus Botrytis cinerea, we developed BEB — a web-based B. cinerea gene expression browser. This tool and associated databases (DB) contain manually-curated RNA-Seq experiments conducted in B. cinerea. BEB allows easy gene expression analyses of genes of interest under different culture conditions by providing publication-ready heatmaps depicting transcripts levels. BEB is a computationally-inexpensive web-based application and gene expression DB that allows effortless visualization of the transcript levels of genes of interest without needing advanced computational skills. BEB also provides details of each experiment under analysis and user-defined gene expression clustering and visualization options. If needed, tables of gene expression values can be downloaded for further exploration, employing more sophisticated bioinformatics tools. The BEB implementation is based on open-source computational technologies that can be easily deployed for other organisms of interest with little additional effort. To demonstrate BEB’s usability and potential, we selected genes of interest in B. cinerea to determine their expression patterns across different conditions. We thus focused our analysis on secondary metabolite gene clusters, chromosome-wide gene expression, previously described virulence factors, and reference genes, leading to a comprehensive expression overview of these groups of genes in this relevant fungal phytopathogen.
Parallel streams of raphe VGLUT3-positive inputs target the dorsal and ventral hippocampus in each hemisphere
Authors: Fortin-Houde Justine , Henderson Fiona , Ducharme Guillaume , Amilhon Bénédicte 
Published: August 2022

AbstractThe hippocampus (HP) receives neurochemically diverse inputs from the raphe nuclei, including glutamatergic fibers characterized by the expression of the vesicular glutamate transporter VGLUT3. These raphe-HP VGLUT3 (VGLUT3HP) projections have been suggested to play a critical role in HP functions, yet a complete anatomical overview of raphe VGLUT3 projections to the forebrain, and in particular the HP, is lacking. Using anterograde viral tracing, we describe largely non-overlapping VGLUT3-positive projections from the dorsal raphe (DR) and median raphe (MnR) to the forebrain, with the HP receiving inputs from the MnR. A limited subset of forebrain regions such as the amygdaloid complex, claustrum and hypothalamus receive projections from both the DR and MnR that remain largely segregated. This highly complementary anatomical pattern suggests contrasting roles for DR and MnR VGLUT3 neurons. To further analyse the topography of VGLUT3 raphe projections to the HP, we used retrograde tracing and found that VGLUT3HP neurons distribute over several raphe sub-regions (including the MnR, paramedian raphe and B9 nucleus) and lack co-expression of serotonergic markers. Strikingly, two-color retrograde tracing unraveled two parallel streams of VGLUT3-positive projections targeting the dorsal and ventral poles of the HP. These results demonstrate highly organized and segregated VGLUT3-positive projections to the HP, suggesting independent modulation of HP functions such as spatial memory and emotion-related behavior.
Perceived barriers and entrepreneurial exit intentions: moderating role of regular versus sustainable entrepreneurship
Authors: Shahid Subhan 
Published: August 2022

PurposeThis study aims to untangle how perceived barriers provoke entrepreneurial exit intentions during an entrepreneurial engagement. Drawing on the social cognitive theory (SCT), the study also theorizes the mediating role of self-efficacy and moderating effects of the nature of entrepreneurship activity (regular versus sustainable entrepreneurship) on the barriers–exit relationship.Design/methodology/approachThe survey data were collected from 302 entrepreneurs in the UK in two waves using a time-lagged method and analyzed through the structural equation modeling techniqueFindingsThe results indicate that perceived barriers positively related to entrepreneurial exit intentions, whereas self-efficacy served as an effective intervening mechanism to untangle the barriers–exit relationship. In addition, consistent support was found for the moderating role of the nature of entrepreneurship activity for the hypothesized relationships.Practical implicationsThe investigation unfolds that perceived barriers lead entrepreneurs to stimulate exit intentions. Therefore, it is recommended that all the stakeholders, including government, industries and academia, must collaborate and provide a favorable institutional environment where sustainable entrepreneurship can thrive and nourish.Originality/valueUnlike studies that exhibited perceived barriers as an inhibitor to entrepreneurial intentions, the study theorizes the relevance of perceived barriers during entrepreneurial engagement and demonstrates how it determines entrepreneurial exit intentions. The study also comprehends the exiting knowledge by underpinning the SCT construct self-efficacy as an intervening factor in explaining the barriers–exit relationship.
From Industry 4.0 to Construction 4.0: barriers to the digital transformation of engineering and construction sectors
Authors: Wang Kaiyang , Guo Fangyu , Zhang Cheng , Schaefer Dirk 
Published: August 2022

PurposeThe purpose of this study is to systematically identify, assess, and categorize the barriers to digital transformation (DT) in the engineering and construction sectors, and thus to better understand the impact and how these sectors might be overcome.Design/methodology/approachThis study adopted a sequential mixed qualitative and quantitative data collection and analysis approach. DT barriers were first identified from relevant literature and verified by an expert panel. Then, a questionnaire survey assessing the impacts of the identified DT barriers was distributed to construction professionals in China, and 192 valid responses were retrieved. Further, the data obtained were analyzed using ranking analysis, exploratory factor analysis (EFA), and partial least squares-structural equation modeling (PLS-SEM).FindingsBased on the ranking analysis, the top three barriers are “lack of industry-specific standards and laws,” “lack of clear vision, strategy and direction for DT,” and “lack of support from top management for DT.” EFA enabled the grouping of the 26 barriers into 3 categories: (1) lack of laws and regulations (LLR), (2) lack of support and leadership (LSL), and (3) lack of resources and professionals (LRP). The PLS-SEM analysis revealed that LLR, LSL, and LRP were found to have significant negative impacts on DT.Originality/valueThese findings contribute to the body of knowledge on DT in the construction industry and help construction firms and government bodies improve the understanding of these barriers to DT and put forward relevant policies and incentives, thus seizing the DT benefits as a way to enhance construction project management.
Managing global HRM integration in international expansion: the case of Geely cross-border acquisition
Authors: Xie Zaiyang , Wei Mei , Ding Xinyi , Thomson Stanley Bruce 
Published: August 2022

Learning outcomes
This case was designed for use at the undergraduate and MBA level in human resource management and international business. Upon completion of the case study discussion and assignments, students will be able to: (1) understand human resource management in multinational corporations and the importance of cross-cultural management and human resource integration in acquisitions; (2) understand the challenges and solutions faced by multinational corporations in the process of expansion; (3) analysis of what characteristics should be considered in CEO selection for managing a newly acquired company; and (4) analyze how to better promote global human resource management from the dimensions of localized HRM system reform and human resource structure reconstruction.

Case overview/synopsis
After a long period of negotiation, exploration, suspension and restart, Geely Group finally acquired 49.9% of the shares of DRB’s Proton Holding and 51% of the shares of the luxury car brand, Lotus Group. On the afternoon of May 24, Geely Holding Group held an acquisition signing ceremony with the Malaysia DRB-HICOM Berhad (hereinafter referred to as DRB). Geely’s commercial territory now extended into Southeast Asia, and its product spectrum increased to luxury sports cars.However, the completion of the acquisition did not mean peace of mind. On the contrary, Geely still faced a series of challenges because of differences in cultural background. The national cultures of the two countries (China and Malaysia) were very different, and so were the values of the two enterprises. Facing the challenges of promoting global human resource integration, Geely needs to make a fundamental decision on the HRM mode in the new-acquired company. Should Geely transplant its own management practice into the Proton, or adopt localized HRM philosophy? Which kind of global HRM practice would be more effective for supporting the new-acquired company developments in the future? In the post-acquisition management, how to better realize the global human resources integration become a key problem faced by Geely.

Complexity academic level
This case was designed for use at the undergraduate and MBA level in human resource management and international business.

Supplementary materials
Teaching notes are available for educators only.

Subject code
CSS 6: Human Resource Management.
“Literacy to me is about power”: reading book-length fiction and non-fiction texts in a disciplinary literacy teacher education course
Authors: Neville Mary , Marlatt Rick 
Published: August 2022

PurposeThis paper aims to examine the reading of a book-length fiction or non-fiction text in one disciplinary literacy (DL) teacher education course. This paper considers how the assignment may help pre- and in-service teachers understand literacy as multifaceted and connected within and beyond their content areas (Moje, 2015). The research explores how reading a book-length text may help support DL, equity-oriented curricula that consider literacy as empowerment and connected to lived and communal experiences (Gonzálezet al., 2005; Muhammad, 2020).Design/methodology/approachThis work is grounded in a qualitative, humanizing methodology and thematic analysis approach (Braun and Clarke, 2006; Paris and Winn, 2014). This approach examines student work in one DL course, considering how teachers within and beyond English language arts (ELA) respond to the task of reading a book-length text.FindingsFirst, the assignment offered space for participants to redefine literacy as empowerment and enjoyment. Second, the assignment helped participants connect literacy within and beyond their content areas and to see literacy as active and interdisciplinary. Third, the assignment includes clear limitations for a DL approach, particularly when participants focus mainly on connections to their content area. This sometimes obfuscated participants’ enjoyment of reading.Originality/valueThe study offers a new perspective on a task that is often seen as specifically “ELA”: reading a book-length text. This project offers space for ELA educators to consider literacy from a DL, equity-oriented framework focused on enjoyment in literature within and beyond ELA classrooms.
The impact of perceived value on engagement: the role of teacher behavior
Authors: Al Issa Hussein-Elhakim , Saad Shahrin , Dittavichai Rungrudee 
Published: August 2022

PurposeThis paper investigates the impact of perceived value on academic engagement (AE) of students in an online learning environment. The mediating effect of teacher behavior (TB) on the relationships is also explored.Design/methodology/approachData were collected from 542 students studying at different specializations in Malaysia and Thailand academic institutions. This study employed a quantitative methodology and utilized the SmartPLS for data analyses.FindingsThe results suggest that students' perceived value is a strong predictor of AE, while TB positively and significantly mediated only social value–engagement association and spiritual value–engagement association.Practical implicationsThese findings suggest focusing on TB as a dynamic variable in pursuing students' AE. Still, the cross-cultural and gender differences uncovered added important factors to consider when designing online learning programs across different student groups.Originality/valueBy building on reasoned action theory (TRA) and integrating TRA with social motivational theory, this study provides novel theoretical insights that reveal mechanisms whereby students' perceived value promotes AE through TB in online learning.
A forecasting analytics model for assessing forecast error in e-fulfilment performance
Authors: Ho G.T.S. , Choy S.K. , Tong P.H. , Tang V. 
Published: August 2022

PurposeDemand forecast methodologies have been studied extensively to improve operations in e-commerce. However, every forecast inevitably contains errors, and this may result in a disproportionate impact on operations, particularly in the dynamic nature of fulfilling orders in e-commerce. This paper aims to quantify the impact that forecast error in order demand has on order picking, the most costly and complex operations in e-order fulfilment, in order to enhance the application of the demand forecast in an e-fulfilment centre.Design/methodology/approachThe paper presents a Gaussian regression based mathematical method that translates the error of forecast accuracy in order demand to the performance fluctuations in e-order fulfilment. In addition, the impact under distinct order picking methodologies, namely order batching and wave picking. As described.FindingsA structured model is developed to evaluate the impact of demand forecast error in order picking performance. The findings in terms of global results and local distribution have important implications for organizational decision-making in both long-term strategic planning and short-term daily workforce planning.Originality/valueEarlier research examined demand forecasting methodologies in warehouse operations. And order picking and examining the impact of error in demand forecasting on order picking operations has been identified as a research gap. This paper contributes to closing this research gap by presenting a mathematical model that quantifies impact of demand forecast error into fluctuations in order picking performance.
Exploring sentiment divergence on migrant workers through the lens of Sina Weibo
Authors: Li Qilan , Zuo Zhiya , Zhang Yang , Wang Xi 
Published: August 2022

PurposeSince the opening of China (aka, reform and opening-up), a great number of rural residents have migrated to large cities in the past 40 years. Such a one-way population inflow to urban areas introduces nontrivial social conflicts between urban natives and migrant workers. This study aims to investigate the most discussed topics about migrant workers on Sina Weibo along with the corresponding sentiment divergence.Design/methodology/approachAn exploratory-descriptive-explanatory research methodology is employed. The study explores the main topics on migrant workers discussed in social media via manual annotation. Subsequently, guided LDA, a semi-supervised topic modeling approach, is applied to describe the overall topical landscape. Finally, the authors verify their theoretical predictions with respect to the sentiment divergence pattern for each topic, using regression analysis.FindingsThe study identifies three most discussed topics on migrant workers, namely wage default, employment support and urban/rural development. The regression analysis reveals different diffusion patterns contingent on the nature of each topic. In particular, this study finds a positive association between urban/rural development and the sentiment divergence, while wage default exhibits an opposite relationship with sentiment divergence.Originality/valueThe authors combine unique characteristics of social media with well-established theories of social identity and framing, which are applied more to off-line contexts, to study a unique phenomenon of migrant workers in China. From a practical perspective, the results provide implications for the governance of urbanization-related social conflicts.