bluuebunny/crossref_metadata_2025_split huggingface dataset:
The level of conscientiousness trait and technostress: a moderated mediation model
Authors: Ariño-Mateo Eva , Venegas Matías Arriagada , Mora-Luis Carlos , Pérez-Jorge David 
Published: February 2024

AbstractAs organizations increasingly rely on technology for the management, planning, and execution of activities and tasks. The consequence of technology use is technostress, which can ultimately affect workers’ mental and physical health. This study aimed to explore the factors influencing technostress in relation to conscientiousness and the mediating effects of organizational dehumanization based on hierarchical levels within the organization. The sample consisted of 190 adults, with the majority being teachers (57.4%). A moderated mediation analysis was employed using the PROCESS software. This study reveals that organizational dehumanization is a mechanism through which conscientiousness can foster technostress, mainly when the hierarchy level is situated at lower levels. Organizations should develop an approach to addressing technostress based on the hierarchical roles and competencies assumed by workers to promote healthier work environments and decrease the stress caused by technology.
Mapping the evolution of algorithmic HRM (AHRM): a multidisciplinary synthesis
Authors: Cameron Roslyn , Herrmann Heinz , Nankervis Alan 
Published: February 2024

AbstractHigh levels of confusion persist around the term “algorithm” in general; and in addition to this, there is also conceptual confusion around the application of algorithms to human resource management (HRM) strategy and functions. Although there are several systematic reviews of various algorithmic applications to HRM and many of its functions, no comprehensive evolutionary map of the emergent field of algorithmic HRM (AHRM) could be found in the academic literature. This study has dual aims. The first is to provide conceptual clarity for the field of AHRM, and the second is to map the evolution of AHRM from 2000 to 2022. To address the first aim, we conduct a multidisciplinary synthesis of the concepts related to algorithms which results in a General Framework for Algorithmic Decision-Making. This framework then informs the empirical part of the study which addresses the second aim. A science mapping review is employed to chart and assess the extant literature on algorithmic HRM from 2000 to 2022. This study presents a General Framework for Algorithmic Decision-Making across all business functions and then a Framework for Algorithmic AHRM Tools. This provides conceptual clarity and distinguishes between automated and augmented HR decision-making. Findings also reveal the multidisciplinary nature of this emergent field of inquiry and point to current research, which focuses on specialized applications for HR functions such as workforce planning, learning and development, allocation and scheduling, and recruitment; but lacks emphasis on more integrative strategic HRM contexts. The study also has implications for organizational strategic decision-making. HR practitioners may need to form project teams with their information technology (IT) and data analyst colleagues when making strategic decisions about algorithmic applications for HR strategy and HR functions. This also lends itself to future research with multidisciplinary research teams including HR researchers along with computer scientists, computational engineers, and data analysts.
Civil liability for the actions of autonomous AI in healthcare: an invitation to further contemplation
Authors: Eldakak Ahmed , Alremeithi Abdulla , Dahiyat Emad , El-Gheriani Moatasem , Mohamed Hassan , Abdulrahim Abdulla Mohammad Ibrahim 
Published: February 2024

AbstractThere are already a number of autonomous robots that play a significant role in improving the quality of healthcare in different areas ranging from basic health diagnosis to complex surgeries. However, using robots and machine learning applications in the healthcare context poses concerns over liability for patient injury. This paper will thus attempt to investigate the potential legal problems that might arise if AI technology evolves or is commonly used in clinical practice. It also examines whether the traditional doctrines of liability can adequately address the liability for the injuries stemming from acts of autonomous robots. As such, this paper adopted both descriptive and analytical methodologies to explore the main focus of the study. while the descriptive methodology was used to spot light on various theories of liability, the analytical methodology was used to critically examine the main theories that have been advanced to deal with autonomous robots and predict the necessity of legal reform. Throughout this paper, the authors insist on the importance of distinguishing between robots in light of their degree of autonomy and then drafting liability rules depending on whether the action was done autonomously by an unattended robot or whether it was done automatically by an attended robot. Finally, the paper concludes with the proposal of a series of factors to be considered for the future regulation of AI Robots in the healthcare context.
Teachers’ perceived work ability: a qualitative exploration using the Job Demands-Resources model
Authors: Hlado Petr , Harvankova Klara 
Published: February 2024

AbstractTeaching is a highly demanding profession; therefore, it is necessary to address how teachers cope with the demands of their job and how these demands affect their work ability. This study aims to investigate teachers’ perceptions of work ability and the underlying mechanisms through which job demands influence their perceived work ability. The Job Demands-Resources (JD-R) model serves as the theoretical framework for this investigation. A qualitative approach was employed, utilizing in-depth interviews with a sample of 14 upper secondary school teachers in the Czech Republic. The teachers had an average age of 46.9 years (SD = 9.22). The findings revealed a limited awareness among teachers regarding the holistic nature of work ability. Job demands emerged as a factor indirectly impacting perceived work ability through the health impairment process. High job demands and obstacles contributed to teacher stress, resulting in fatigue, impaired physical or mental health, and reduced perceived work ability. Moreover, the study showed how tough job demands extend beyond the professional realm, leading to work-family conflicts that further impair work ability. This study provided empirical support for the inclusion of perceived work ability as an outcome influenced by job demands within the JD-R model. Additionally, it emphasized the need for a comprehensive framework that considers both organizational and individual factors in both work and non-work domains to effectively investigate perceived work ability among teachers.
The appeal of the circular economy revisited: on track for transformative change or enabler of moral licensing?
Authors: Eickhoff Hans 
Published: February 2024

AbstractThe proposal of an economy that is circular and without the need for material or energy input has an irresistible appeal to those who recognize the precautionary concept of planetary boundaries and acknowledge that resources are limited. Thus, in the public discourse, its narrative outperforms other lines of arguments when it comes to keeping radical critics of destructive extractivism and the growth imperative in check and averting discussion of degrowth, post-growth, or other systemic alternatives by larger segments of the population and government bodies. Moreover, the myth of a circular economy has the additional benefit that it can win over parts of the environmental movement that is apprehensive of radical and transformative change, particularly in the urban milieus of a middle class that enjoys the privileges of the current social order. In this paper, I argue that the circular economy narrative tends to hinder the necessary systemic transformation while entailing a wide range of specific measures that deserve to be recognized for their merit.
Optical properties and exciton transfer between N-heterocyclic carbene iridium(III) complexes for blue light-emitting diode applications from first principles
Authors: Lebedeva Irina V. , Jornet-Somoza Joaquim 
Published: February 2024

N-heterocyclic carbene (NHC) iridium(III) complexes are considered as promising candidates for blue emitters in organic light-emitting diodes. They can play the roles of the emitter as well as of electron and hole transporters in the same emission layer. We investigate optical transitions in such complexes with account of geometry and electronic structure changes upon excitation or charging and exciton transfer between the complexes from first principles. It is shown that excitation of NHC iridium complexes is accompanied by a large reorganization energy ∼0.7 eV and a significant loss in the oscillator strength, which should lead to low exciton diffusion. Calculations with account of spin–orbit coupling reveal a small singlet–triplet splitting ∼0.1 eV, whereas the oscillator strength for triplet excitations is found to be an order of magnitude smaller than for the singlet ones. The contributions of the Förster and Dexter mechanisms are analyzed via the explicit integration of transition densities. It is shown that for typical distances between emitter complexes in the emission layer, the contribution of the Dexter mechanism should be negligible compared to the Förster mechanism. At the same time, the ideal dipole approximation, although giving the correct order of the exciton coupling, fails to reproduce the result taking into account spatial distribution of the transition density. For charged NHC complexes, we find a number of optical transitions close to the emission peak of the blue emitter with high exciton transfer rates that can be responsible for exciton–polaron quenching. The nature of these transitions is analyzed.
Corrigendum: Exploring the role of beyond mean-field interaction in the structure and dynamics of one-dimensional quantum droplets (2023 J. Phys. B: At. Mol. Opt. Phys. 56 165302)
Authors: Gangwar Sonali , Ravisankar Rajamanickam , Muruganandam Paulsamy , Mishra Pankaj Kumar 
Published: February 2024

Abstract
In our recent paper (Gangwar et al 2023 J. Phys. B: At. Mol. Opt. Phys.
56 165302), we noticed a minor mistake in equations (1) and (2). In this corrigendum, we provide the corrected equations and necessary modified figures. However, overall results and conclusions of our original paper remain unchanged.
Archimedes’ principle experimental apparatus for remote physics laboratory
Authors: Indratno T K , Ishafit  , Prabowo Y D 
Published: February 2024

Abstract
The latest developments in information technology have made it possible to have experimental activities that can be accessed remotely. This article offers an explanation about the development of experimental tools that can be accessed remotely based on Archimedes’ principle. The equipment has been developed by adding a stepper motor to control the object to submerge in liquid. The stepper motor is controlled by Arduino Uno using the graphical user interface (GUI) developed using LabVIEW. Data sampling process uses a force sensor that is controlled using the same GUI. Based on the equipment that has been developed, experiments on the principle of Archimedes’ can be done online through websites. The experimental results agree with theoretical calculations and with previous research. Therefore, the developed apparatus can be used as an experimental-based learning tool in an online platform.
Measurement of the charge-to-mass ratio of particles trapped by the Paul trap for education
Authors: Saito R J , Tanaka T A , Sakemi Y , Yagyu M , Tanaka K S 
Published: February 2024

Abstract
Paul traps are devices that confine particles using an alternating electric field and have been used in undergraduate experimental classes at universities. Owing to the requirement of a high voltage (

>

103 V), Paul traps are not used in middle and high schools. Therefore, we developed an all-in-one-type Paul trap, including a high-voltage transformer. The Paul trap can be equipped with two different types of electrode attachments, ring-type and linear-type, and the trap image can be observed using a built-in web camera. For example, the charge-to-mass ratio of particles was measured with different types of attachments, and reasonable values were obtained. These types of trap devices are currently used at several educational facilities in Japan.
Burning facial tissue and corroding graphite rods of recycled batteries: two simple experiments in preparation of nanomaterials
Authors: Quang Ngo Khoa 
Published: February 2024

Abstract
This report presents two hands-on activities for high school students that focus on the preparation of nanomaterials in a relatively simple manner. Carbon dots (CDs) were chosen as a demonstration. The article is categorised into two parts. The first part roughly performs the same work as a previous publication by Jumeng Wei, in which ultrasonication was utilised to cleave paper ash. Furthermore, we also attempted to use magnetic stirring or even hand stirring as an alternative method. The second section offers a perspective on the use of an electrochemical method to prepare CDs using graphite rods from recycled batteries. In the scope of this article, instead of using high-analysis techniques to prove the availability of CDs at the nanoscale, our work aims to illustrate green, sustainable physics and demonstrate the way that synthetic physicists utilise waste materials via practical education. The designed experiment suggests an integration between physics and chemistry that might be used for the science, technology, engineering, and mathematics experience of high school students.
DRFNet: a deep radiomic fusion network for nAMD/PCV differentiation in OCT images
Authors: Shen Erwei , Wang Zhenmao , Lin Tian , Meng Qingquan , Zhu Weifang , Shi Fei , Chen Xinjian , Chen Haoyu , Xiang Dehui 
Published: February 2024

Abstract

Objective. Neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV) present many similar clinical features. However, there are significant differences in the progression of nAMD and PCV. and it is crucial to make accurate diagnosis for treatment. In this paper, we propose a structure-radiomic fusion network (DRFNet) to differentiate PCV and nAMD in optical coherence tomography (OCT) images. Approach. The subnetwork (RIMNet) is designed to automatically segment the lesion of nAMD and PCV. Another subnetwork (StrEncoder) is designed to extract deep structural features of the segmented lesion. The subnetwork (RadEncoder) is designed to extract radiomic features from the segmented lesions based on radiomics. 305 eyes (155 with nAMD and 150 with PCV) are included and manually annotated CNV region in this study. The proposed method was trained and evaluated by 4-fold cross validation using the collected data and was compared with the advanced differentiation methods. Main results. The proposed method achieved high classification performace of nAMD/PCV differentiation in OCT images, which was an improvement of 4.68 compared with other best method. Significance. The presented structure-radiomic fusion network (DRFNet) has great performance of diagnosing nAMD and PCV and high clinical value by using OCT instead of indocyanine green angiography.
Highly robust reconstruction framework for three-dimensional optical imaging based on physical model constrained neural networks
Authors: Chen Xueli , Meng Yu , Wang Lin , Zhou Wangting , Chen Duofang , Xie Hui , Ren Shenghan 
Published: February 2024

Abstract

Objective. The reconstruction of three-dimensional optical imaging that can quantitatively acquire the target distribution from surface measurements is a serious ill-posed problem. Traditional regularization-based reconstruction can solve such ill-posed problem to a certain extent, but its accuracy is highly dependent on a prior information, resulting in a less stable and adaptable method. Data-driven deep learning-based reconstruction avoids the errors of light propagation models and the reliance on experience and a prior by learning the mapping relationship between the surface light distribution and the target directly from the dataset. However, the acquisition of the training dataset and the training of the network itself are time consuming, and the high dependence of the network performance on the training dataset results in a low generalization ability. The objective of this work is to develop a highly robust reconstruction framework to solve the existing problems. Approach. This paper proposes a physical model constrained neural networks-based reconstruction framework. In the framework, the neural networks are to generate a target distribution from surface measurements, while the physical model is used to calculate the surface light distribution based on this target distribution. The mean square error between the calculated surface light distribution and the surface measurements is then used as a loss function to optimize the neural network. To further reduce the dependence on a priori information, a movable region is randomly selected and then traverses the entire solution interval. We reconstruct the target distribution in this movable region and the results are used as the basis for its next movement. Main Results. The performance of the proposed framework is evaluated with a series of simulations and in vivo experiment, including accuracy robustness of different target distributions, noise immunity, depth robustness, and spatial resolution. The results collectively demonstrate that the framework can reconstruct targets with a high accuracy, stability and versatility. Significance. The proposed framework has high accuracy and robustness, as well as good generalizability. Compared with traditional regularization-based reconstruction methods, it eliminates the need to manually delineate feasible regions and adjust regularization parameters. Compared with emerging deep learning assisted methods, it does not require any training dataset, thus saving a lot of time and resources and solving the problem of poor generalization and robustness of deep learning methods. Thus, the framework opens up a new perspective for the reconstruction of three-dimension optical imaging.
Cn
-symmetric quasi-periodic Chern insulators
Authors: Han Ying , Zhou Yuan , He Ai-Lei 
Published: February 2024

Abstract
Chern insulators have been recently extended to quasicrystal systems, namely the quasi-periodic Chern insulators (QCIs). Here we study the topological properties and topological response of QCIs on two-dimensional singular surfaces. Such singular QCIs with arbitrary

n
−

fold rotational symmetry (i.e. C

n
-symmetric QCIs) can be constructed by ‘cutting and gluing’ unit sectors on the Dürer’s pentagonal tiling. Chiral edge states and real-space Chern number can well characterize the topological properties of C

n
-symmetric QCIs. Intriguingly, we numerically identify the emergence of charge fractionalization in unit of

e

/

10

around the singular center in Cn
-symmetric QCIs though their bulk densities are inhomogeneous. In addition, we explore the phase transitions of these C

n
-symmetric QCIs.
Conical holes arrays for 2 × 2 ports division
Authors: Huang Yusen , Wang Bo 
Published: February 2024

Abstract
The 2 × 2 ports division is introduced based on novel conical holes arrays in this paper. Under the normal incidence of wavelength 780 nm, the grating can achieve high efficiency in the orders (±1, 0) and (0, ±1) which are 24.28% and 24.33%. The uniformity (E
U) and the extinction rate (E
T) are 0.10% and 21.10 dB. Furthermore, the numerical analysis indicates that the proposed grating exhibits a large angular bandwidth of 11° and a wavelength bandwidth of 34 nm when the target condition has diffraction efficiency above 20% for all main diffraction orders. What’s more, the results demonstrate that the proposed grating is feasible for practical manufacturing by exhibiting good manufacturing tolerances and high performance. The performance of the grating is so excellent that it has a wide application prospect in interferometers, spectroscopy, optical communications, etc.
Simulation study on the effect of operating and materials parameters on electrocaloric device for battery cooling
Authors: Rabadiya Ridhamkumar , Saurabh Nishchay , Patel Satyanarayan 
Published: February 2024

Abstract
The present simulation work discusses the effect of different electric pulses, operating temperatures, electrodes and substrate materials on electrocaloric(EC) performance. The electrocaloric effect (ECE) is analyzed using poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) P(VDF-TrFE-CFE) polymer with electrode. The P(VDF-TrFE-CFE) film (100 μm) shows an effective adiabatic temperature change (ΔT
ad)effective (considering losses) of 4.01 K at 100 MV m−1 when a square electric field (E) pulse is used. An effect of electrode and substrate layer thickness is also analyzed; the electrocaloric performance decreases with an increase in the thickness of the substrate layer. A smartphone battery’s surface (7 cm × 3 cm) is considered for cooling by the proposed design. The simulation study shows battery’s surface/source temperature dropped from 313.15 K to ∼298 K, ∼297.5 K, and ∼293.5 K when air cooling, the EC device in contact with the battery (no ECE, E = 0) and EC device in contact with battery (with ECE, E = 100 MV m−1), respectively are used in ∼6.5 s. The proposed EC device design can provide new insight for mobile or other electronic cooling applications.
Bethe ansatz solutions of the 1D extended Hubbard-model
Authors: Hou 侯 Haiyang 海洋 , Sun 孙 Pei 佩 , Qiao 乔 Yi 艺 , Xu 许 Xiaotian 小甜 , Zhang 张 Xin 鑫 , Yang 杨 Tao 涛 
Published: February 2024

Abstract
We construct an integrable 1D extended Hubbard model within the framework of the quantum inverse scattering method. With the help of the nested algebraic Bethe ansatz method, the eigenvalue Hamiltonian problem is solved by a set of Bethe ansatz equations, whose solutions are supposed to give the correct energy spectrum.
Rogue waves for the (2+1)-dimensional Myrzakulov–Lakshmanan-IV equation on a periodic background
Authors: Wang Xiao-Hui , Zhaqilao  
Published: February 2024

Abstract
In this paper, the rogue wave solutions of the (2+1)-dimensional Myrzakulov–Lakshmanan (ML)-IV equation, which is described by five component nonlinear evolution equations, are studied on a periodic background. By using the Jacobian elliptic function expansion method, the Darboux transformation (DT) method and the nonlinearization of the Lax pair, two kinds of rogue wave solutions which are expressed by Jacobian elliptic functions dn and cn, are obtained. The relationship between these five kinds of potential is summarized systematically. Firstly, the periodic rogue wave solution of one potential is obtained, and then the periodic rogue wave solutions of the other four potentials are obtained directly. The solutions we find present the dynamic phenomena of higher-order nonlinear wave equations.
Electrical characteristics of a fractional-order 3 × n Fan network
Authors: Tan Zhi-Zhong , Wang Xin 
Published: February 2024

Abstract
In this article a new achievement of fractional-order 3 × n Fan networks is presented. In the first step, the RT-I method is used to derive the general formulae of the equivalent impedance of fractional-order 3 × n Fan networks. In the second part, the effects of five system parameters (L, C, n, α and β) on amplitude-frequency and phase-frequency characteristics are analyzed. At the same time, the amplitude-frequency and phase-frequency characteristics of the fractional order 3 × n Fan network are revealed by Matlab drawing. This work has important theoretical and practical significance for resistor network models in the field of natural science and engineering technology.