bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unbiased learning of protein conformational representation via unsupervised random forest
Authors: Sahil Mohammad , Ahalawat Navjeet , Mondal Jagannath 
Published: December 2024

AbstractAccurate data representation is paramount in biophysics to capture the functionally relevant motions of biomolecules. Traditional feature selection methods, while effective, often rely on labeled data based on prior knowledge and user-supervision, limiting their applicability to novel systems. Here, we presentunsupervised random forest(URF), a self-supervised adaptation of traditional random forests that identifies functionally critical features of biomolecules without requiring prior labels. By devising a memory-efficient implementation, we first demonstrate URF’s capability to learn important sets of inter-residue features of a protein and subsequently to resolve its complex conformational landscape, performing at par or surpassing its traditional supervised counterpart and 15 other leading baseline methods. Crucially, URF is supplemented by an internal metric, thelearning coefficient, which automates the process of hyper-parameter optimization, making the method robust and user-friendly. URF’s remarkable ability to learn important protein features in an unbiased fashion was validated against 10 independent protein systems including both both folded and intrinsically disordered states. In particular, benchmarking investigations showed that the protein representations identified by URF are functionally meaningful in comparison to current state-of-the-art deep learning methods. As an application, we show that URF can be seamlessly integrated with downstream analyses pipeline such as Markov state models to attain better resolved outputs. The investigation presented here establishes URF as a leading tool for unsupervised representation learning in protein biophysics.
Fine structure of the doublet
P
levels of boron
Authors: Nasiri Saeed , Tumakov Dmitry , Stanke Monika , Kędziorski Andrzej , Adamowicz Ludwik , Bubin Sergiy 
Published: December 2024

We report high-accuracy calculations of the ground and the lowest eight excited Po2 states of the two stable isotopes of the boron atom, B10 and B11, as well as of the boron atom with an infinite nuclear mass ∞B. The nonrelativistic wave function of each of the states is generated in an independent variational calculation by expanding it in terms of a large number, 12000–17000, of all-electron explicitly correlated Gaussian (ECG) functions whose nonlinear parameters are extensively optimized with a procedure that employs analytic energy gradient determined with respect to these parameters. These highly accurate wave functions are used to compute the fine-structure splittings using the first order of the perturbation theory (∼α2), where α is the fine-structure constant, which are then corrected for the electron magnetic moment anomaly (∼α3). As the nonrelativistic Hamiltonian explicitly depends on the mass of the nucleus, the recoil corrections up to the order of α2 are automatically accounted for in the fine-structure calculations. Furthermore, the off-diagonal corrections to the fine structure (∼α4) are estimated using the multireference methods based on one-electron Gaussian orbitals. The results obtained in this paper are considerably more accurate than those available in the literature. Moreover, we report accurate splittings for a number of excited Po2 states, for which there have been no reliable experimental or theoretical data at all. The calculated values presented in this paper may serve as a valuable guide for future experimental measurements of the fine structure of the boron atom. As the fine structure of an atom provides a spectral signature that can facilitate atom's detection, our data can also aid the search for trace amounts of boron in the interstellar medium.

Published by the American Physical Society
2024
Strategies of perceived justice for added value in public–private partnership (PPP) projects
Authors: Cheng Mengyuan , Chong Heap-Yih , Liu Guoliang , Li Qian 
Published: December 2024

PurposePerceived justice is crucial to achieving public–private partnership (PPP) projects’ goals, but little is known about the transmission mechanism of perceived justice that affects added value in PPP projects. Therefore, this research intends to investigate the link between perceived justice and PPP projects’ added value and their underlying mechanism by analysing the mediating role of cooperative behaviour.Design/methodology/approachBased on 246 valid survey data collected from the Chinese PPP professionals, structural equation modelling was adopted to analyse and test the proposed hypotheses.FindingsThe results show all three dimensions of perceived justice positively correlated with PPP projects’ added value. The influence effect from high to low was determined to be as follows: interactive, distributive and procedural justice. Moreover, both perfunctory and consummate performance were found to be positively correlated with and thus of great importance to PPP projects’ added value, but perfunctory performance was found to have a greater influence coefficient. The relationship between perceived justice and PPP projects’ added value is mediated by perfunctory and consummate performance. Therefore, the strategies of perceived justice in improving added value are verified in the context of Chinese PPP projects.Research limitations/implicationsThe findings of this study can help realise added value in three ways. Firstly, new perspectives for PPP project added value should be proposed by combining the improvement of project basic objectives and the realisation of the participants’ implicit demands. Secondly, the effects of different perceived justice on added value should be analysed instead of a single dimension of perceived justice. Thirdly, the mediating effects of different types of cooperative behaviour that may influence the relationship between perceived justice and added value should be evaluated.Practical implicationsThis study contributes to a better understanding of the relationship between perceived justice and PPP projects’ added value and provides a reliable reference for project managers to achieve added value outcomes in PPP projects. In addition, this study reveals the impact of perceived justice on PPP projects’ added value and the path of perceived justice transformation. This provides a useful reference for project managers to take advantage of the positive effects of distributive, interactive and procedural justice to enhance inter-organizational cooperative behaviour. This study thus helps improve the practice and value of PPP projects by using the right strategy of perceived justice.Originality/valueThe research clarifies the impacts of multidimensional perceived justice for added value of PPP projects throughout the implementation process. It offers a new perspective on PPP projects’ added value by combining the improvement of the realisation of participants’ implicit claims.
Learning pathways of necessity and opportunity-driven women entrepreneurs: a qualitative study
Authors: Lingappa Anasuya K. , Rodrigus L.R. Lewlyn , Shetty Dasharathraj K. 
Published: December 2024

Purpose
This paper aims to provide insights into the learning approaches of necessity (NEC)-driven and opportunity (OPP) driven women entrepreneurs (WEs) in the Indian context. It investigates the various pathways small business owners use to acquire knowledge and develop competencies. Additionally, it examines the potential differences between the two groups to better understand their learning processes. This understanding, particularly from the perspective of an emerging nation, can inform policymakers, WE organizations, NGOs and families in creating a supportive environment that fosters positive and effective learning experiences for WEs.

Design/methodology/approach
Qualitative research study using semi-structured, in-depth interviews with 16 micro, small and medium enterprises entrepreneurs in the state of Karnataka, India. Thematic analysis was used to draw out the themes from the rich textual data collected using the computer assisted qualitative data analysis software (CAQDAS) tool, ATLAS.ti 23.

Findings
Thematic analysis identified four major themes, namely, routinized learning, learning through critical experiences, self-driven mechanisms and learning from others. The findings reveal that NEC and OPP women entrepreneurs do not greatly differ in their pathways to learning except for some minor dissimilarities.

Originality/value
This study provides a unique viewpoint on the learning mechanisms of women entrepreneurs in small businesses in the context of an emerging economy. It additionally deliberates on the similarities and differences among NEC and OPP motivated WEs, where studies are rare.
Always on emails and employee wellbeing: the role of subjective norm of connectivity
Authors: Tatar Berivan , Erdil Oya 
Published: December 2024

PurposeIn recent years, technological advancement has radically changed the landscape of work by creating an “always-on” workplace. As a result, many employees use their information and communication technologies (ICTs) to perform work-related tasks during personal times. This constant availability then paves the way for harming the employee’s wellbeing. Nevertheless, research on ICTs usage after-hours has received limited consideration in organizational scholarship. To address this gap in the literature, current study aims to examine the relationships between workplace telepressure and employee wellbeing with the role of work-related email (WRE) use after-hours and subjective norm of connectivity.Design/methodology/approachData were collected from 421 employees from different sectors. The hypotheses were tested using structural equation modeling and PROCESS macro for SPSS.FindingsThe results showed that (1) workplace telepressure positively relates to work-related email use after-hours; (2) work-related email use after-hours negatively relates to employee wellbeing; (3) the subjective norm of connectivity moderates the link between workplace telepressure and work-related email use after-hours and (4) work-related email use during nonwork hours mediates the link between workplace telepressure and employee wellbeing.Originality/valueThis study contributes to overcoming the lack of studies by investigating underlying mechanisms and boundary conditions for ICTs during nonwork hours. In this expanded sense, this study broadens our understanding of WRE use after-hours by delineating the impact of workplace telepressure, subjective norm of connectivity and employee wellbeing.
Strength assessment and lightweight optimization design of a bogie frame based on the structural stress method
Authors: Ding Long , He Zhengping , Chen Bingzhi 
Published: December 2024

PurposeAchieve a lightweight design for a bogie frame while ensuring it meets strength requirements by conducting static and fatigue strength assessments and optimizing plate thickness.Design/methodology/approachEstablish a finite element model and determine loads according to the UIC615-4 standard. Fatigue strength assessments are conducted using the structural stress method. Size optimization for plate thickness is performed with constraints on maximum static strength and total fatigue damage of the weld. Multi-objective optimization design is carried out using Isight software, with sensitivity analysis to identify key plates. The neural network model is chosen as the approximation model, and the NSGA-II multi-objective genetic algorithm is selected as the optimization algorithm.FindingsThe strength assessment reveals a significant margin. Through size optimization of plate thickness with constraints on static strength and fatigue damage, the frame’s mass is reduced by 9.59%, achieving a lightweight design while meeting strength requirements.Originality/valueIn many lightweight studies, the inclusion of fatigue assessment through the structural stress method in the optimization process is often overlooked. However, this paper addresses this gap by incorporating it and providing a detailed operational procedure. Such consideration holds reference value for the design of lightweight optimization, especially when fatigue strength is a critical consideration.
Identification and application of dynamic parameters of manipulator based on improved IRLS algorithm
Authors: Meng Xiangchang , Xu Shuo , Han Ming , Li Tiejun , Liu Jinyue 
Published: December 2024

Purpose
To overcome the shortcomings of traditional dynamic parameter identification methods in accuracy and efficiency, this paper aims to propose a dynamic parameter identification method based on improved iterative reweighted least squares (IIRLS) algorithm.

Design/methodology/approach
First, Newton–Euler method is used to establish the dynamic model of the robot, which is linearized and reorganized. Then, taking the improved Fourier series as the excitation trajectory, the optimization model with objective function is established and optimized. Then, the manipulator runs the optimized trajectory and collects the running state of the joint. Finally, the iterative process of iterative reweighted least squares (IRLS) algorithm is improved by combining clustering algorithm and matrix inversion operation rules, and the dynamic model of robot is identified by using the processed collected data.

Findings
Experimental results show that, compared with the IRLS algorithm, the root mean square of the proposed IIRLS algorithm is reduced by 4.18% and the identification time is reduced by 94.92% when the sampling point is 1001. This shows that IIRLS algorithm can identify the dynamic model more accurately and efficiently.

Originality/value
It effectively solves the problem of low accuracy and efficiency of parameter identification in robot dynamic model and can be used as an effective method for parameter estimation of robot dynamic model, which is of great significance to the research of control method based on robot model.
How virtual reality influences collaboration performance: a team-level analysis
Authors: Suh Ayoung 
Published: December 2024

PurposeIn the wake of the COVID-19 pandemic, the interest in the use of virtual reality (VR) for organizational collaboration has dramatically increased. However, empirical research on the optimal types of VR and avatar designs for effective collaboration remains limited. To address these gaps, this study investigates how VR types (immersive vs non-immersive) and avatar similarity (high vs low) impact collaboration performance, with a focus on the mediating roles of somatic, psychological and behavioral engagement.Design/methodology/approachDrawing on embodied cognition theory and grounded in user engagement theory, we developed a research model that delineates the factors influencing collaboration performance. This model was empirically tested with data collected from a laboratory experiment involving 195 participants, employing a 2 × 2 factorial design. The Engage VR was used for the experiment because it supports the same virtual environment for collaboration between immersive and non-immersive VR contexts. The data were analyzed at the team level (n = 65).FindingsThe results of this study reveal that both immersive VR and high avatar similarity significantly enhance collaboration performance by augmenting somatic engagement, which subsequently boosts psychological and behavioral engagement.Originality/valueThis research deepens the scholarly understanding of the intricate interplay among VR types, avatar design and user engagement. The study’s theoretical implications underscore the conceptualization of somatic engagement as a critical dimension of user engagement in virtual collaboration, enriching the extant literature on VR-based collaboration. It also provides pragmatic insights to enhance virtual collaboration in the workplace.
Enhancing portfolio decision-making: a capital asset pricing model-based clustering analysis
Authors: Pooja R. , Kayal Parthajit , Maiti Moinak 
Published: December 2024

PurposeTo enhance portfolio decision-making using a capital asset pricing model-based clustering analysis.Design/methodology/approachCapital asset pricing model (CAPM); K-means clustering; agglomerative clustering.FindingsEmploying clustering along with CAPM to identify varying levels of risk appetite among customers enables the customization of security recommendations, enhancing client satisfaction and portfolio performance.Originality/valueBy employing multi-factor models as the foundation for clustering, thereby integrating additional dimensions of risk and return.
Audit firms’ entry into H-share audit market and mainland audit pricing: evidence from China
Authors: Zhang Rui , Tian Gaoliang , Tian Zichen , Li Liuchuang 
Published: December 2024

Purpose
This study aims to investigate whether mainland Chinese audit firms’ entry into the H-share market to provide audit services affects their mainland audit pricing.

Design/methodology/approach
Using data on A-share listed companies in China from 2008 to 2018, a difference-in-differences model to test the research question is designed. Robustness tests are conducted to rule out alternative explanations and additional tests to shed light on the extent and inner workings of the main effect.

Findings
The entry of mainland audit firms into the H-share audit market leads to a significant decrease in mainland audit pricing. Moreover, this main effect is (i) growing with the importance of H-share audit services to mainland auditors, (ii) stronger for mainland auditors with lower industry specialisation and shorter tenures, (iii) partially mediated by audit efficiency and (iv) greater when mainland clients have higher bargaining power. Furthermore, mainland auditors’ entry into the H-share audit market does not result in significant deterioration in their mainland audit quality, and significantly increases their market share in the mainland audit market.

Originality/value
This study provides new empirical evidence of the relationship between audit firms’ development strategy for internationalisation and audit pricing, extends the literature on auditing issues in emerging markets and should be of potential interest to regulators and investors.
Clinical characterization of mycosis fungoides with abnormal light reactions induced by narrow‐band UVB therapy: A review of a single‐center experience
Authors: Mizawa Megumi , Makino Teruhiko , Furukawa Fumina , Shimizu Tadamichi 
Published: December 2024

AbstractNarrow‐band UVB (NB‐UVB) therapy at a wavelength of 311 nm is often used to treat mycosis fungoides (MF). However, we occasionally encounter cases of erythema induced by low doses of NB‐UVB, known as an abnormal light reaction (ALR). We investigated the incidence of ALR in patients with MF and the association between ALR and clinical and laboratory findings. Forty patients (30 men and 10 women) with MF (excluding patients treated with bexarotene or etretinate) who received NB‐UVB therapy at the Department of Dermatology, University of Toyama, from January to December 2022 were analyzed. ALR was defined as erythema caused by NB‐UVB irradiation of the nonlesional skin at a dose of ≤0.5 J/cm2. ALR occurred in six of 40 patients (15%). The main symptoms of ALR are erythema, irritation, and itching. ALR was observed in patients with Fitzpatrick skin types II and III, and was more common in patients with T2 and T4 disease than in others. The mechanism underlying its occurrence is unknown; however, it has been suggested that ALR is more likely to occur in patients with extensive skin lesions. In addition, treatment can be continued by reducing the dose of NB‐UVB or switching to a 308‐nm excimer laser, even when ALR occurs. Accumulation of additional cases is required because there were only six patients with ALR in this study.
Evaluating restoration success using metric‐based indicators of ecosystem recovery in tidal marshes along the northern Gulf of Mexico
Authors: Dybiec Jacob M. , Ledford Taylor , Rinehart Shelby , Tatariw Corianne , Mortazavi Behzad , Cherry Julia A. 
Published: December 2024

Abstract

Habitat restoration is commonly used to recover ecosystem services, but due to resource constraints, post‐project monitoring often fails to fully evaluate the recovery of important ecosystem functions. Metric‐based indicators use simple‐to‐measure variables to assess ecosystem health and function, thereby providing a time‐ and cost‐effective method to improve monitoring.

We used a tidal‐marsh data set to develop metric‐based indicators of ecosystem recovery. In 2021 and 2022, we surveyed eight restored/created and three natural reference tidal marshes in the northern Gulf of Mexico to assess the recovery of ecosystem attributes (e.g. above‐ and below‐ground biomass, soil organic matter [SOM] and sediment total carbon [C] and total nitrogen [N]). To determine what combinations of variables best predicted recovery, we split our data into model training and testing data sets, used backwards model selection and then created and tested a metric‐based indicator of ecosystem recovery.

Recovery of plant above‐ and below‐ground biomass and sediment structure (i.e. SOM, C and N)—important measures of wetland carbon sink capacity and biogeochemical functioning—could be predicted through a combination of simpler to measure variables, such as time since restoration, percent plant cover and sediment bulk density. The indicator constructed from these relationships was highly effective in predicting the development of ecosystem attributes (r = 0.85, p < 0.001).

Synthesis and applications. This indicator approach provides an effective but simple method to assess the recovery of ecosystem attributes in tidal marshes, and it can be used to develop similar indicators in other ecosystems. By overcoming resource constraints of post‐project monitoring, metric‐based indicators of ecosystem recovery may serve as a key strategy to improve restoration outcomes.
Preparation and characterization of polyphenol–chitosan conjugate–eugenol essential oil microcapsule and its effect on storage behavior of cherry tomato
Authors: Yu Xiaohong , Hu Erhu , Liu Fengyi , Zhang Yan , Li Wangwang , Lyu Yongmei , Li Fengwei , Wang Dujun , Jin Wenbin 
Published: December 2024

AbstractGiven the high volatility, low water solubility, and oxidative sensitivity of essential oils, this study synthesized microcapsules of essential oil (EEO) (quercetin–chitosan–EEO [QE–CS–EEO]) using a QE–CS graft copolymer as the wall material and EEO as the core material. Research findings indicate that QE–CS exhibits superior in vitro antioxidant activity, with scavenging abilities for 2,2‐diphenyl‐1‐picrylhydrazyl and 2,2′‐azino‐bis(3‐ethylbenzothiazoline‐6‐sulfonic acid) ABTS+ radicals being 58.71% and 77.03% greater than those of CS, respectively, thereby providing more effective protection for the essential oil. In comparison to CS essential oil, microcapsules (CS–EEO), QE–CS–EEO demonstrated an 18.65% increase in EEO encapsulation efficiency, achieving a total encapsulation efficiency of 41.29%. Based on these results, various edible coating solutions were formulated, including Control, E1 (1% CS), E2 (0.5% CS + 0.5% CS–EEO), E3 (0.5% CS + 0.5% QE–CS–EEO), and E4 (1% EEO), to extend the shelf life of cherry tomatoes. Notably, cherry tomatoes treated with the E3 formulation maintained superior freshness indicators, exhibiting an extended shelf life of approximately 9–12 days compared to the control group. This study aims to explore a novel microcapsule wall material and provide a strategy for extending the shelf life of fruits and vegetables, thereby minimizing food waste.