bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effects of Robot-Asssissted Gait Training on Balance and Fear of Falling in Patients with Stroke: A Randomized Controlled Clinical Trial
Authors: GUNDUZ Merve SEVINC , MUSTAFAOGLU Rustem , URAL Ibrahim Halil 
Published: December 2024

ABSTRACT

Objective
The aim of this study was compare the effects of Combined Training (CombT), which included Robot-Assisted Gait Training in addition to Traditional Balance Training (TBT), and TBT alone on balance and fear of falling (FoF) in patients with stroke based on objective assessment methods.

Design
Patients were randomized into CombT Group (CombTG) (n = 21) and TBT Group (TBTG) (n = 21) for duration of 5-weeks. Balance were assessed with EncephaLog App recorded stand-up time (SUT), sit-down time (SDT), and directional sways during walking, Berg Balance Scale (BBS) and Timed Up and Go Test (TUG). International Fall Efficacy Scale (FES-I) measured fear of falling (FoF). Fugl Meyer Assessment-Lower Extremity (FMA-LE) assessed limb impairment. Foot posture were assessed with Foot Posture Index (FPI-6).

Results
After the treatments, EncephaLog sways (anterior, medial, lateral: P = 0.04, P = 0.01, P = 0.02), SUT (P = 0.006), SDT (P = 0.002); BBS (P < 0.001); FES-I (P = 0.002) improved in CombTG. TUG (P = 0.01) and FMA-LE (P < 0.001) improved in TBTG. SUT (P = 0.01) and SDT (P = 0.04) showed statistically significant improvement in CombTG compared to TBTG; FMA-LE (P = 0.002) demonstrated statistically significant improvement in TBTG compared to CombTG.

Conclusion
Objective assessment indicated that combined treatments in subacute and chronic stroke rehabilitation enhance balance and reduce FoF more effectively than isolated approaches.
The relationship between HIV and reading performance for children in Tanzania
Authors: Bonacina Silvia , Lichtenstein Jonathan D. , Niemczak Christopher , Magohe Albert , Fellows Abigail , Nicol Trent , Massawe Enica , Kraus Nina , Buckey Jay C. 
Published: December 2024

Objective:
Children living with HIV (CLWH) are at increased risk for cognitive and developmental delays, although HIV's influence on reading development remains unclear. Research using internationally validated reading measures with control for factors known to influence literacy outcomes is needed. The Early Grade Reading Assessment (EGRA) is a tool for assessing students’ progress toward reading that has been validated across countries. It was administered to a cohort of children living with and without HIV (CLWH/CLWOH) and data on other factors that might affect literacy were also measured.

Design and methods:
388 children (217 children living without HIV (CLWOH) and 171 CLWH; ages 3–8) drawn from a longitudinal study in Dar es Salaam, Tanzania completed the EGRA. EGRA performance between CLWH and CLWOH was compared adjusting for age socioeconomic status, years of education, English learning, and type of school (public or private).

Results:
Despite the biological and environmental confounders, CLWH performed significantly worse than CLWOH on the Letter Name Knowledge subtest, the Syllable subtest, the Non-Word subtest, and the Reading Comprehension subtest. The difference approached significance for the Oral Reading Fluency subtest.

Conclusions:
CLWH performed worse than CLWOH on the EGRA, indicating literacy skill development in CLWH needs early intervention. Longitudinal analyses, including electrophysiological and behavioral data, are needed to find the factors associated with poor reading and literacy performance in CLWH.
High-Throughput Quantification of miRNA-3′-Untranslated-Region Regulatory Effects
Authors: Mastriano Stephen , Kanoria Shaveta , Rennie William , Liu Chaochun , Li Dan , Cheng Jijun , Ding Ye , Lu Jun 
Published: December 2024

AbstractMicroRNAs (miRNAs) regulate gene expression post-transcriptionally, primarily through binding sites in 3′ untranslated regions (3′ UTRs). While computational and biochemical approaches have been developed to predict miRNA binding sites on target messenger RNAs, reliable and high-throughput assessment of the regulatory effects of miRNAs on full-length 3′ UTRs can still be challenging. Utilizing a miniaturized and high-throughput reporter assay, we present a ‘pilot miRNA-targeting map’, containing 4,994 successfully measured miRNA:3′ UTR regulatory outputs by pairwise assays between 461 miRNAs and eleven 3′ UTRs. This collection represents a large experimental miRNA:3′ UTR dataset to date on a single platform. The methodology can be generally applied to studies of miRNA-mediated regulation of critical genes. We found that seedless sites can lead to substantial downregulation. We utilized this dataset in the development of a quantitative total score for modeling the total regulatory effects by both seed and seedless sites on a full-length 3′ UTR. To assess the predictive value of the total score, we analyzed data from mRNA expression and proteomics studies. We found that the score can discriminate the potent miRNA inhibition from the weak inhibition and is thus useful for quantitative prediction of miRNA regulation. The score has been added to the STarMir program of the Sfold package now available via GitHub athttps://github.com/Ding-RNA-Lab/Sfold.
Development and testing of a dual-frequency real-time hardware feedback system for the hard X-ray nanoprobe beamline of the SSRF
Authors: Jiang Zhisen , Jiang Hui , He Yinghua , He Yan , Liang Dongxu , Yu Huaina , Li Aiguo , Signorato Riccardo 
Published: December 2024

A novel dual-frequency real-time feedback system has been developed to simultaneously optimize and stabilize beam position and energy at the hard X-ray nanoprobe beamline of the Shanghai Synchrotron Radiation Facility. A user-selected cut-off frequency is used to separate the beam position signal obtained from an X-ray beam position monitor into two parts, i.e. high-frequency and low-frequency components. They can be real-time corrected and optimized by two different optical components, one chromatic and the other achromatic, of very different inertial mass, such as Bragg monochromator dispersive elements and a pre-focusing total external reflection mirror. The experimental results shown in this article demonstrate a significant improvement in position and energy stabilities. The long-term beam angular stability clearly improved from 2.21 to 0.92 µrad RMS in the horizontal direction and from 0.72 to 0.10 µrad RMS in the vertical direction.
Cylindrically bent Laue analyzer in an X-ray Raman/emission spectrometer: performance tests and a comparison with spherically bent Bragg analyzers
Authors: Hiraoka Nozomu 
Published: December 2024

The performances of a spherically bent Bragg analyzer and a cylindrically bent Laue analyzer in an X-ray Raman/emission spectrometer are compared. The reflectivity and energy resolution are evaluated from the intensity of the elastic scattering and the width of the energy distribution on a SiO2 glass sample. Widely used, Bragg analyzers display excellent performance at the photon energy E ≤ 10 keV. However, at higher E, the reflectivity and the resolution gradually deteriorate as E increases, showing poor performance above 20 keV. On the other hand, the reflectivity of the Laue analyzer gradually increases at E > 10 keV, displaying excellent reflectivity and good resolution around 20 keV. The Laue analyzer is suitable for X-ray absorption spectroscopy in high-energy-resolution fluorescence-detection mode or X-ray emission spectroscopy on 4d transition metal compounds. Furthermore, the X-ray Raman features of the lithium K-edge in LiF and the oxygen K-edge feature in H2O, measured by nine Bragg analyzers (2 m radius) at E ≃ 9.9 keV and by five Laue analyzers (1.4 m radius) at E ≃ 19.5 keV, have been compared. Similar count rates and resolutions are observed.
Rayleigh waves in thermoelastic medium based on a novel nonlocal three-phase-lag diffusion model with double porosity
Authors: Mahato Chandra Sekhar , Biswas Siddhartha 
Published: December 2024

Purpose
This paper is concerned with the study of the propagation of Rayleigh waves in a homogeneous isotropic, generalized thermoelastic medium with mass diffusion and double porosity structure using the theoretical framework of three-phase-lag model of thermoelasticity.

Design/methodology/approach
Using Eringen’s nonlocal elasticity theory and normal mode analysis technique, this paper solves the problem. The medium is subjected to isothermal, thermally insulated stress-free, and chemical potential boundary conditions.

Findings
The frequency equation of Rayleigh waves for isothermal and thermally insulated surfaces is derived. Propagation speed, attenuation coefficient, penetration depth and specific loss of the Rayleigh waves are computed numerically. The impact of nonlocal, void and diffusion parameters on different physical characteristics of Rayleigh waves like propagation speed, attenuation coefficient, penetration depth and specific loss with respect to wave number for isothermal and thermally insulated surfaces is depicted graphically.

Originality/value
Some limiting and particular cases are also deduced from the present investigation and compared with the existing literature. During Rayleigh wave propagation, the path of the surface particle is found to be elliptical. This study can be extended to fields like earthquake engineering, geophysics and the degradation of old building materials.
Peering into the mechanism: uncovering critical drivers of green entrepreneurial orientation through total interpretive structural modelling
Authors: Shivani Shivani , Datta Manisankar , Sharma Seema , Singh Shveta 
Published: December 2024

PurposeThe growing pressure on businesses to balance environmental sustainability with profit maximisation has led to the development of green entrepreneurial orientation (GEO), which proactively integrates green practices into core business operations. Grounded in the ecological modernisation theory, GEO acts as a green management practice which helps in achieving competitiveness through environmental innovation. However, despite the growing emphasis on GEO, there remains a gap in understanding how specific drivers influence the organisational structures and processes that lead to GEO. Therefore, the study addresses this gap by analysing the key drivers of GEO using an integrated approach.Design/methodology/approachIn this study, total interpretive structural modelling (TISM) and cross-impact matrix multiplication applied to classification (MICMAC) were used to identify and interpret the interrelationship between key drivers of GEO. Here, TISM technique aided in constructing a contextual relationship-based structural model of drivers, whereas MICMAC assisted in categorising the drivers based on their driving and dependence power. A case evaluation was also carried out in the Indian textile industry to validate the TISM model.FindingsThe result indicates that institutional pressure, managerial environment concern, organisational resilience and big data analytical capabilities are the most influential drivers of GEO at organisational level, and other drivers act as secondary and linked variables in this process. The MICMAC analysis further supports the results of TISM. In addition, the overall TISM model is validated in the Indian textile sector.Practical implicationsThe study findings will assist researchers and policymakers in adopting a systematic approach to prioritise GEO in pollution intensive industries. Moreover, it will help managers in leveraging GEO to achieve strategic advantages amid environmental challenges.Originality/valueThis study is amongst the first to employ an integrated qualitative approach to analyse drivers of GEO.
Learning mechanisms and firms’ performance in the global south: reflections from Ludhiana’s manufacturing firms
Authors: Kaur Manpreet , Mehta Swati 
Published: December 2024

PurposeThis study examines the impact of doing, using and interacting (DUI) and science, technology and innovation (STI) learning mechanisms on firm performance, investigating their influence on financial performance through innovative performance in machine tools and textile manufacturing firms in Ludhiana, Punjab, India.Design/methodology/approachPrimary data was collected through a survey of 202 manufacturing firms across two industries, as secondary data inadequately captures learning mechanisms, particularly for DUI mode. The study employed structural equation modelling (SEM) alongside descriptive analysis to examine the impact of STI–DUI learning mechanisms on performance.FindingsThe study reveals that firms, despite minimal investment in formal R&D, effectively learn through networking and imitation (DUI mechanisms). They also benefit from local industrial training institutions. Notably, innovative performance mediates the relationship between learning mechanisms (imitation, networking and industry institutions) and firms' financial performance.Originality/valueThe literature was found to be scant in terms of understanding the nature of firms learning mechanism, especially for the firms undertaken for the analysis. Although having distinguished nature of knowledge and learning required to compete for the products manufactured in machine tools and textiles industries, local conditions, domestic national institutions and regional aspects makes the industries unique case to understand the challenges amidst unique features of these industries. The study is expected to fill-in the gap in the literature of manufacturing industries belonging to developing countries in the era of increasing technological competition in the integrated world economies.
Monitoring by a single banker and accounting conservatism: evidence from India
Authors: Pradeep Kavitha , Baag Pankaj Kumar 
Published: December 2024

PurposeThis paper aims to investigate the effect of bank monitoring on conditional conservative accounting of Indian listed firms. Drawing on bank monitoring and relationship lending literature, the study hypothesizes that monitoring by a single bank reduces the bank’s demand for conservatism-facilitated control transfers.Design/methodology/approachThe empirical design is composed of three steps. In the first step, using data on Indian firms listed in NSE and BSE for the period 2000–2019, market-based firm-year measure and accrual cash flow-based firm-year measure of conditional conservatism is estimated. In the second step, we test the hypothesis using multivariate panel regression corrected for heteroskedasticity and incorporating firm and year-fixed effects. In the third step, we test for the robustness of the results using Heckman’s correction approach.FindingsResults indicate that firms which are monitored by a single bank tend to be less conservative. Also, the negative association between single bank monitoring and conservatism is stronger when the firm’s debt structure is dominated by bank debt.Research limitations/implicationsThe study’s scope does not include analyzing the influence of characteristics of the single banker monitoring the firm. Future research could investigate attributes like ownership of the banker as a possible source of variation in the relationship documented in this study.Practical implicationsAccounting standard-setting boards are now discouraging implementation of conservatism to avoid bias in financial reporting. This paper finds that a strong bank–firm relationship can be a possible substitute for conservatism.Originality/valueThe study sheds new light on the debt structure–conservatism relationship. Bank’s availability of inside information through the transaction account and its impact on lending relationships is established in the literature. However, the literature on the determinants of conservatism has not examined how the benefit enjoyed by the firm’s single banker, possessing all the information in the transaction account can lead to bank’s reduced dependence on financial statements and subsequently reduced accounting conservatism of borrowing firms.
Beyond the transaction: exploring resources stewardship, relational connectedness and co-creation in B2B marketing
Authors: Saragih Harriman Samuel 
Published: December 2024

Purpose
This study aims to explore the interplay between resource stewardship, relational connectedness and value co-creation in business-to-business (B2B) marketing, addressing gaps in understanding how these elements collectively influence stakeholder relationships and organizational outcomes. Drawing on stewardship theory, social exchange theory and service-dominant logic, the study develops a model that highlights the synergies between ethical resource management, strategic relational engagement and co-creative value processes.

Design/methodology/approach
Using an abductive qualitative approach, the study focuses on the B2B service sector in an emerging economy. Data were collected through in-depth interviews with 30 management professionals and analyzed thematically, supported by a network view to visualize the interconnected dynamics.

Findings
Resource stewardship emerges as a key driver of trust and relational connectedness, which facilitates collaborative innovation and value co-creation. Relational connectedness enhances loyalty and cooperative problem-solving, while active participation in co-creation fosters shared ownership, satisfaction and long-term engagement.

Research limitations/implications
The study’s context-specific focus on an emerging economy limits broader applicability, suggesting future cross-industry, cross-cultural approach and quantitative validation.

Originality/value
This study presents an empirically grounded framework that advances theoretical understanding and offers practical insights for optimizing B2B marketing strategies through resource stewardship, relational connectedness and co-creative practices.
Development of the new machine-learning approach in pipeline condition assessment prediction and optimizing rehabilitation strategies
Authors: Sabamehr Ardalan , Amani Nima , Boateng Solomon , Sommer Adam 
Published: December 2024

Purpose
This paper aims to outlines a model for water main rehabilitation in Kitchener, Ontario, using a machine-learning approach. Water main networks are vital infrastructure, requiring regular condition assessments to ensure consistent service. Budgets are often allocated for nondestructive testing methods, but using machine learning to predict network conditions offers cost benefits.

Design/methodology/approach
The study focuses on a prediction approach that includes the rehabilitation requirement model. The Decision Tree machine learning method was applied to predict water main pipe breaks in 2024. Based on the predictions, 24 pipes were identified for rehabilitation, and the appropriate Trenchless Rehabilitation Method was selected accordingly.

Findings
The model, applied to data from Kitchener, successfully predicted 24 water main pipe breaks for 2024. The largest pipe diameter was 1200 mm, and the longest length was 6977 m. A cost comparison, factoring in Environmental and Social (E&S) costs, showed that open-cut methods were 25% more expensive than Cured-in-Place Pipe (CIPP). When E&S costs were included, the total cost of the open-cut method increased by approximately 300% compared to sliplining.

Originality/value
Based on the pipe characteristics, CIPP lining and sliplining are recommended for rehabilitation by the City of Kitchener. This study presents a novel approach using Decision Tree machine learning techniques to predict pipe breaks, with a 97% prediction accuracy, making it a promising alternative to traditional models.
Structural equation modelling of the critical barriers influencing the adoption of green building concepts and technologies in Ghana
Authors: Anzagira Lee Felix , Duah Daniel Yaw Addai , Badu Edward , Simpeh Eric Kwame , Marful Alexander B. , Amos-Abanyie Samuel 
Published: December 2024

Purpose
In Ghana, the adoption and application of green building concepts and technologies have not been fully explored. The study aimed to look into the key barriers and how they affect this.

Design/methodology/approach
Purposive and snowball sampling techniques were used to select a total of 292 construction industry stakeholders in Ghana who provided information via a questionnaire survey used for the data collection. Exploratory factor analysis and Partial least squares structural equation modelling (PLS-SEM) were used for computing the data analyses.

Findings
According to the study findings, the top five most critical barriers to the uptake of green building concepts and technologies (GBCs and Ts) in Ghana are: lack of government incentives/supports for implementing green building technologies (GBTs), lack of knowledge and awareness of GBTs and their benefits, lack of GBTs databases and information, Lack of green building (GB) expertise/skilled labour and Higher costs of GBTs. Principal Component Factor Analysis was used to further analyse the data, which allowed for the reduction of the 27 (27) factors to just four (4) underlying critical barriers: (1) government and knowledge-associated barriers, (2) technical barriers, (3) cost and finance barriers and (4) stakeholders’ attitude barriers. PLS-SEM techniques were used to analyse this collection of barriers, and the results showed that stakeholders’ attitude-associated barriers and cost and finance-related barriers have a significant negative influence on the uptake of GBCs and Ts in Ghana. This study’s findings have provided empirical evidence of the critical barriers to the uptake of GBCs and Ts from all stakeholders. Stakeholders desirous of implementing GBCs and Ts would work against the negative influences on the uptake of GBCs and TS.

Originality/value
Although there has been an abundance of research to examine the critical barriers to GB, however, the uniqueness of this study is nested in modelling the influence of the barriers on the adoption of GBCs and Ts using the PLS-SEM path modelling.