bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated segmentation of soft X-ray tomography: native cellular structure with sub-micron resolution at high throughput for whole-cell quantitative imaging in yeast
Authors: Chen Jianhua , Mirvis Mary , Ekman Axel , Vanslembrouck Bieke , Le Gros Mark , Larabell Carolyn , Marshall Wallace F. 
Published: November 2024

AbstractSoft X-ray tomography (SXT) is an invaluable tool for quantitatively analyzing cellular structures at sub-optical isotropic resolution. However, it has traditionally depended on manual segmentation, limiting its scalability for large datasets. Here, we leverage a deep learning-based auto-segmentation pipeline to segment and label cellular structures in hundreds of cells across threeSaccharomyces cerevisiaestrains. This task-based pipeline employs manual iterative refinement to improve segmentation accuracy for key structures, including the cell body, nucleus, vacuole, and lipid droplets, enabling high-throughput and precise phenotypic analysis. Using this approach, we quantitatively compared the 3D whole-cell morphometric characteristics of wild-type, VPH1-GFP, andvac14strains, uncovering detailed strain-specific cell and organelle size and shape variations. We show the utility of SXT data for precise 3D curvature analysis of entire organelles and cells and detection of fine morphological features using surface meshes. Our approach facilitates comparative analyses with high spatial precision and statistical throughput, uncovering subtle morphological features at the single cell and population level. This workflow significantly enhances our ability to characterize cell anatomy and supports scalable studies on the mesoscale, with applications in investigating cellular architecture, organelle biology, and genetic research across diverse biological contexts.Significance StatementSoft X-ray tomography offers many powerful features for whole-cell multi-organelle imaging, but, like other high resolution volumetric imaging modalities, is typically limited by low throughput due to laborious segmentation.Auto-segmentation for soft X-ray tomography overcomes this limitation, enabling statistical 3D morphometric analysis of multiple organelles in whole cells across cell populations.The combination of high 3D resolution of SXT data with statistically useful throughput represents an avenue for more thorough characterizations of cellsin totoand opens new mesoscale biological questions and statistical whole-cell modeling of organelle and cell morphology, interactions, and responses to perturbations.
All-atom simulations elucidate the molecular mechanism underlying RNA-membrane interactions
Authors: Di Marco Salvatore , Aupič Jana , Bussi Giovanni , Magistrato Alessandra 
Published: November 2024

AbstractRNA-membrane interactions are starting to emerge as an important organizing force in both natural and synthetic biological systems. Notably, RNA molecules were recently discovered to be present on the extracellular surface of living cells, where they mediate intercellular signalling. Furthermore, RNA-membrane interactions influence the efficacy of lipid-based RNA delivery systems. However, the molecular terms driving RNA localisation at the membrane remain poorly understood. In this work, we investigate how RNA-phospholipid membrane interactions occur, by means of all-atom simulations. We find that among the four RNA nucleobases guanine exhibits the strongest interaction with the membrane due to extensive hydrogen bond formation. Additionally, we show that intra-RNA base pairing present in organised RNA structures significantly hinders RNA binding to the membrane. Elucidating the molecular details of RNA-membrane association will importantly contribute to improving the design of RNA-based drugs as well as lipid-based RNA delivery systems and to parsing out RNA transport and localisation mechanisms.
Learning Binding Affinities via Fine-tuning of Protein and Ligand Language Models
Authors: Gorantla Rohan , Gema Aryo Pradipta , Yang Ian Xi , Serrano-Morrás Álvaro , Suutari Benjamin , Jiménez Jordi Juárez , Mey Antonia S. J. S. 
Published: November 2024

AbstractAccuratein-silicoprediction of protein-ligand binding affinity is essential for efficient hit identification in large molecular libraries. Commonly used structure-based methods such as giga-docking often fail to rank compounds effectively, and free energy-based approaches, while accurate, are too computationally intensive for large-scale screening. Existing deep learning models struggle to generalize to new targets or drugs, and current evaluation methods do not reflect real-world performance accurately. We introduceBALM, a deep learning framework that predictsbindingaffinity using pretrained protein and ligandlanguagemodels. BALM learns experimental binding affinities by optimizing cosine similarity in a shared embedding space. We also propose improved evaluation strategies with diverse data splits and metrics to better assess model performance. Using the BindingDB dataset, BALM shows strong generalization to unseen drugs, scaffolds, and targets. It excels in few-shot scenarios for targets such asUSP7andMpro, outperforming traditional machine learning and docking methods, including AutoDock Vina. Adoption of the target-based evaluation methods proposed will allow for more stringent evaluation of machine learning-based scoring tools. Frameworks such as BALM show good performance, are computationally efficient, and are highly adaptable within this evaluation setting, making them practical tools for early-stage drug discovery screening.
South–South mobility: Chilean students’ educational journeys in China
Authors: Morales Valdés José Manuel 
Published: November 2024

PurposeThe study investigates the motivations, learning experiences and impacts of Chilean student mobility in China, focusing on postgraduate students. It analyzes how this education has influenced their professional trajectories and Sino-Chilean relations.Design/methodology/approachThe methodology employs a qualitative approach, based on 13 semi-structured interviews, with an analysis covering aspects such as the reasons for studying in China, the acquisition of Mandarin Chinese, the academic experience and professional projections.FindingsThe research concludes that these students, trained in China, significantly contribute to strengthening bilateral ties in various fields, highlighting cultural diplomacy as a key factor in expanding collaboration between the two countries.Originality/valueAdditionally, it underscores the need to consider student mobility as an essential component of relations between Chile and China, in particular, and among different Global South countries in general, transcending the limitations of financing criteria and the Eurocentric orientation that predominates in the internationalization policies of Chilean higher education.
Toward the successful adoption of Lean Six Sigma in manufacturing organizations: proposing a causal model
Authors: Limon-Romero Jorge , García-Alcaraz Jorge Luis , Gastelum-Acosta Carlos , Antony Jiju , Baez-Lopez Yolanda , Tortorella Guilherme 
Published: November 2024

PurposeThis paper aims to provide new and valuable insights for organizations that have decided to implement Lean Six Sigma (LSS) as a strategy for continuous improvement in search of business excellence. This objective is achieved through statistically modeling the causal relationships between the critical success factors (CSFs) of LSS for a successful deployment of this strategy.Design/methodology/approachA statistically validated questionnaire was used to collect information from LSS practitioners in manufacturing industries located on Mexico’s northern border. Some hypotheses for relationships between LSS CSFs are developed theoretically first and empirically tested later using the structural equation modeling technique.FindingsProposed relationships between LSS CSFs have been demonstrated to be statistically significant, making clear that this implementation should always begin with a strong and decided participation and commitment of top management. Later, other CSFs must be activated and put into operation in a specified order to increase the probability of a successful implementation reflected in well-executed continuous improvement projects and achieving the expected benefits.Originality/valueThis paper proposes a structural model which has been statistically validated with information directly collected from skilled practitioners who have developed continuous improvement projects using the LSS methodology. Further, some relationships between LSS CSFs that, to the best of the author’s knowledge, had not been demonstrated empirically are now explored and verified in our work.
A low-cost self-powered triboelectric nanogenerator sensor for detecting loosening bolt under impact loading
Authors: Xi Yinhu , Deng Jinhui , Li Baokun , Li Yanbiao , Deng Haishun 
Published: November 2024

Purpose
The purpose of this study is to detect the bolt loosening under conditions of impact loading with a low-cost self-powered triboelectric nanogenerator sensor.

Design/methodology/approach
In this work, an Al/PTFE-based triboelectric nanogenerator (AP-TENG) is used as a sensor. A pendulum impact device and a force hammer were used to apply the impact loads. The bolt status and the applied torque can be monitored under impact loading conditions by using the output voltage results of the AP-TENGs.

Findings
The output voltage results of the current AP-TENG sensor under five different bolt torques, i.e. from 0.5 to 2.5 N m, were measured. The measurements revealed that a thicker buffer layer significantly contributed to the generation of higher voltages. Besides, the AP-TENG was also used to light ten commercial green LEDs in series, and the brightness of the LEDs was high enough even for the daytime, which showed that it can be used as the alarm device. In addition, a sudden loose test was also carried out, and the obvious voltage spikes can be seen without the external impact. The force hammer impact tests have expanded the application scope of the AP-TENG in the bolt loosening detection.

Originality/value
The bolt loosening monitoring is important and useful for the safe operation. The application of TENG technology for detecting bolt loosening remains relatively unexplored. In addition, ten commercial green LEDs can be driven by the AP-TENG sensor, which can be used for the early warning of the bolted loosening status.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0216/
Trends in digital transformation (DT) of higher education institutes (HEI): bibliometric and systematic review of 13 years
Authors: Joshi Sujata , Srivastava Anugamini Priya , Prabhu Sandeep , Pathak Pankaj , Chirputkar Abhijit , Pillai Samaya 
Published: November 2024

PurposeThe objective of this paper is to investigate the digital transformation (DT) trends in higher education institutes (HEI) (from 2010 to 2023) and examine the role of upcoming technologies in the HEI and their impact on user experience and social inclusiveness.Design/methodology/approachThe middle-range research method is adopted, wherein the Scopus database is used for publication searches. The bibliometric analysis is done on a dataset of 408 articles to determine research trends in DT, top-cited articles, top journals, key authors, country-wise contribution, keyword analysis, bibliographic coupling and co-occurrence analysis. Additionally, content analysis was done on 51 articles that were finally selected to identify the upcoming DT themes in HEI.FindingsThree key themes emerged from the analysis: digital technologies (for teaching, learning, assessment and administration), user experience and social inclusiveness, based on which we propose a conceptual model for DT in HEI.Originality/valueThis study contributes to the ongoing studies in the following way: (1) it proposes a conceptual model for DT in HEI. (2) It provides an understanding of the impact of DT on user experience and social inclusiveness in the context of HEI. (3) It paves the way for future research by providing future research themes, future research directions and future research questions, providing a groundwork for upcoming investigations which will help researchers develop this area further.
Teaching ICT to pre-schoolers in the global south using indigenous knowledge patterns
Authors: Armah Michael , Tetteh Andrew , Nkrumah Felicia 
Published: November 2024

PurposeThe study addresses the challenges of limited access to technology and gender inequality in Ghana's education system, particularly science, technology, engineering, and mathematics/information and communications technologies (STEM/ICT) education. It focuses on the culturo-techno-contextual approach (CTCA), which has been shown to improve student outcomes and reduce educational gender inequality in Africa. Thus, this study addressed two research objectives: whether the CTCA will improve basic school students’ understanding of ICT and reduce the gender gap without ICT facilities.Design/methodology/approachThe study was conducted using a quantitative method and a quasi-experimental design. 120 participants (44 in the experimental group and 76 in the control group) were selected using purposive and random sampling techniques. Data were collected using the Windows Interface Achievement Test (WIAT) and analysed using ANCOVA analysis.FindingsThe study found that the CTCA improved students’ understanding of ICT without ICT resources. The study also found that using the CTCA, there were no differences between male and female students in their understanding of ICT without ICT resources.Practical implicationsBased on the study’s findings, the researchers recommend the use of the CTCA in teaching basic school ICT, particularly in rural areas where access to ICT resources is problematic.Originality/valueResearchers typically experiment with alternate teaching strategies to overcome obstacles in learning issues. This study’s originality stems from applying an indigenous teaching method (CTCA) to break down learning difficulties in ICT education.
Changing heritage imageability of an ancient Indian sacred city – a case of Puri
Authors: Mohanty Rabi Narayan , Mohanta Ashaprava , Chani Prabhjot Singh 
Published: November 2024

PurposeIndia is an abode of several ancient heritage and sacred cities. However, limited heritage sites have been appropriately documented to date. Hence, limited information is available on the historical development, existing settings and challenges of ancient heritage cities. Puri, a prime sacred and heritage city, is selected to demonstrate the historical and spatial development and current issues of ancient Indian heritage cities.Design/methodology/approachSite visits, documentation of the existing settings and interviews with stakeholders and historians were conducted to understand this city's evolution and existing issues. Also, content analysis is administered to rank the stakeholders’ perceptions of the current challenges in the town.FindingsThe results reveal that the scarcity of resources, encroachment of public spaces, insufficient infrastructure and lack of maintenance of heritage structures are the major challenges for Puri. Also, the absence of collaboration between the involved agencies and heritage site-specific guidelines hinders the city’s redevelopment.Practical implicationsThis research discusses the development phases and current issues of a prime heritage city in India. This knowledge will help urban planners and policymakers formulate policies for Puri's holistic development.Originality/valueThis is the first comprehensive research on historical development, current issues, and the reasons for any heritage city in Odisha state of India. This paper will help the academic literature to understand the chronological growth pattern in ancient, medieval, colonial, and post-colonial periods, as well as current issues and changing heritage imageability of Indian heritage sites of a similar nature.
Effectiveness of EHR systems on decision support in primary healthcare: a technology acceptance model 3 perspective
Authors: Mwogosi Augustino , Kibusi Stephen 
Published: November 2024

PurposeThis study aims to evaluate healthcare practitioners’ perceptions of electronic health record (EHR) systems and their effectiveness in supporting clinical decision-making in Tanzanian Primary Healthcare (PHC) facilities.Design/methodology/approachA mixed-methods approach was employed, combining quantitative data from structured questionnaires and qualitative insights from open-ended responses. The study was conducted in the Dodoma region of Tanzania, focusing on a diverse representation of PHC facilities, including district hospitals, health centres and dispensaries. Data were analysed using multiple linear regression for quantitative data, and thematic analysis was applied to qualitative responses.FindingsThe results revealed that while EHR systems are widely used in Tanzanian PHC facilities, their impact on clinical decision-making remains limited. Only a moderate portion of practitioners perceived EHR systems as effective in decision support, and frequent system use was negatively correlated with user satisfaction. Challenges such as inadequate training and support, system crashes, slow performance and poor usability and integration into clinical workflows were significant barriers to effectively utilising EHR systems.Originality/valueThis study contributes to the limited literature on EHR system implementation in low-resource settings, specifically Tanzania, by focusing on decision-support features within EHR systems. The findings offer valuable insights for healthcare policymakers, system designers and practitioners to optimise EHR implementation and improve healthcare outcomes in resource-constrained environments.
How does electricity trading affect the carbon emission reduction of electric vehicles from the perspective of electricity consumption?
Authors: Zhang Linling , Li Shuangqun , Zhang Wei 
Published: November 2024

PurposeThe purpose of this paper is to explore carbon emission reduction of electric vehicles from the perspective of electricity consumption.Design/methodology/approachElectric vehicles (EVs) consume large amounts of electricity, thereby generating large amounts of carbon dioxide (CO2) emissions, so there is an urgent need to consider whether EVs have greater potential for reducing carbon emissions than other modes of transport. In this paper, the carbon emission reduction potential (CERP) coefficients of EVs are examined under three different scenarios from an interprovincial electricity trading perspective. Scenario analysis was used to quantify the CERP of EVs in 18 provinces in China.FindingsThe results show the following: (1) The higher the proportion of general-fuel vehicles in all transportation, the higher the CERP of EVs. (2) Interprovincial power trading affects the proportion of coal power consumed in a province, and the higher the proportion of clean power in the purchased power, the lower the proportion of coal power consumed in that province. (3) The proportion of coal power in the electricity consumption of a province is correlated negatively with the CERP of EVs in that province.Originality/valueThis paper quantifies the CERP of EVs compared with other modes of transport and gives provinces a more intuitive understanding of the CERP of EVs. Furthermore, we derive the carbon emission shift out of each province via the electricity trading paths among provinces, analyzing the impacts of the variability between different provinces on EV carbon emissions.
Quantifying seed rain patterns in a remnant and a chronosequence of restored tallgrass prairies in north central Missouri
Authors: Wynne K. Carter , Parker‐Smith Maya J. , Murdock Erica M. , Sullivan Lauren L. 
Published: November 2024

Abstract

Seed rain is an influential process related to plant community diversity, composition and regeneration. However, knowledge of seed rain patterns is limited to those observed in forests and late‐assembling grasslands, which might not reflect early assembling communities such as newly restored grasslands. Resolving this gap in our understanding provides further insight into the role of seed dispersal.

Here, we measured seed rain in a remnant tallgrass prairie, which was the site of the foundational grassland seed rain study in 1978, and a nearby chronosequence of tallgrass prairie restorations. We sought to determine how the quantity, seed mass traits, timing, diversity and composition of seed rain changed (1) long‐term and (2) during community assembly. To do so, we deployed artificial turf grass seed traps into 2‐year‐old, 5–6‐year‐old and 15‐year‐old restored prairies and the remnant prairie, replacing traps every 2 weeks from May to December 2019.

We captured over twice the density and richness of seed rain in the remnant prairie in 2019 compared to 1978. We also found that seed rain patterns changed as prairies aged, with each prairie possessing a distinct community of dispersing species. Significantly more seeds, seed biomass, and species were captured in the youngest restored prairie. However, seed mass traits were similar in all prairies. Except for composition, all other seed rain metrics in the oldest restoration were eventually comparable to the remnant prairie.

Synthesis and applications: Our results revealed that grasslands, notably young prairies, produce larger quantities of seed rain than previously known (124,806 seeds m−2 year−1, 97.24 g m−2 year−1), and seed input in all sampled prairies far exceeded restoration broadcast seeding densities. We further found that decreases in seed rain quantity across the chronosequence did not correspond with increases in seed mass, suggesting a lack of trade‐offs between these metrics. Furthermore, tallgrass prairie restorations have not replicated the composition of seed rain seen in remnant systems. Increasing restoration seeding rates of desirable species may be needed to meet composition goals since current rates may not compete with the propagule pressure of undesirable species found in newly restored prairies.
UBER IN EXURBIA: Peripheral Platformization, Post‐Suburbanization and the Public–Private Ridehail Partnership in the Toronto City Region
Authors: Namberger Fabian 
Published: October 2024

AbstractAfter their widespread legalization, ridehailing companies Uber and Lyft soon embarked on a new stage of their respective business models: the initiation of a wave of strategic partnerships with local and regional transit agencies across the North American continent. This article accounts for this trend by putting forward the concept of the public–private ridehail partnership (PPRP). It aims to render visible the PPRP as a variously contradictory attempt to splice Uber and Lyft's platform‐based business models with the existing social and physical realities of North American post‐suburban space. While conceived as a strategic response to pressing sub‐ and exurban problems such as low physical densities, widespread car centrism and extensive transit undersupply, the PPRP, as I argue, is neither able to adequately address these dilemmas nor to ultimately resolve them. Rather, the PPRP latches onto old—and sets in motion new—powerful dynamics of heightened uneven development and continued urban entrepreneurialism. Each of these two dynamics is explored through empirical analyses of two recent PPRPs in the Toronto city region: the Lyft–Metrolinx pilot carried out between July and December 2019; and Uber's ongoing partnership with the town of Innisfil, located about 80 km north of downtown Toronto.