bluuebunny/crossref_metadata_2025 huggingface dataset:
How to Respond to Racist Patients: Recommendations from a Literature Review
Authors: Caplan Benjamin , Mitchell-Williams Jocelyn
Published: January 2024

amed. Investigation of published recommendations for handling these situations can give victims, peers, and institutions the tools necessary to prepare, protect, and support providers through these challenging encounters.

Methods: This paper is a literature review. For inclusion in this review, studies must have met the criteria of providing recommendations for healthcare providers or institutions on how to deal with racist patients. Excluded articles did not include recommendations on how to handle such situations or did not otherwise meet inclusion criteria. PubMed Medline was searched in January 2022 using a combination of the following keywords and associated MeSH terms: “Racism” AND “Physician-Patient relations”. The resulted articles then underwent forward and backward citation searching. A total of 44 articles were included after evaluation of 272 articles via this process.

Results: For the affected individual, recommended responses include addressing the comment firmly and directly in real time, setting boundaries and behavior expectation, reporting the incident to supervisors and to the hospital, and seeking support from peers and/or professionals. At the peer level, core practices are supporting the victim, addressing the patient if necessary, debriefing with the victim and team, and checking-in with the victim in the following days. At the institution level, core practices are enacting reporting system and tracking incidents, developing specific policies and procedures about biased patients, and training staff with focused antibias and antidiscrimination sessions.

Discussion: There are steps to be taken at every level to create a supportive and inclusive practice that protects providers against racist patients. One limitation of this study was that it was not a systematic review so there may be other recommendations published that are not reflected here.
Stability and Longitudinal Resonances of the Kapitsa Pendulum
Authors: Morozov Nikita F. , Polyakova Oksana R. , Tovstik Tatyana P.
Published: January 2024

The generalized Kapitsa problem of stabilizing the upper position of a deformable pendulum under the action of small vertical oscillations of its base in a gravity field is solved. The presence of a small parameter of the problem allows us to carry out averaging and obtain approximate equations of motion of the pendulum. Two models of a pendulum are considered and compared: a flexible inextensible rod and a flexible tensile rod. The influence of each parameter of the problem on stability is studied. The limits of applicability of the model of a flexible inextensible pendulum are obtained.
Trajectory Tracking of Double-Joint Manipulator Based on Robust Adaptive Sliding Mode Control
Authors: Xia Dongmei
Published: January 2024

In the presence of strong coupling, nonlinear time-varying dynamics, and uncertainties such as unmodeled dynamics and external disturbances, it is challenging to establish an accurate mathematical model for a dual-joint robotic system. This leads to a degradation in tracking accuracy and affects system stability. In this paper, a robust adaptive sliding mode control algorithm is proposed for trajectory tracking of a dual-joint robotic arm to improve tracking accuracy and achieve good dynamic performance. Firstly, the dynamic equations of the dual-joint robotic arm are analyzed, considering inertia characteristics, Coriolis and centrifugal force characteristics, and gravity torque characteristics. A sliding function is constructed to approximate the unknown variables of the robotic arm, and a robust adaptive law is used to adjust the unknowns for stability and ensure tracking accuracy. Secondly, the stability analysis based on Lyapunov stability theory demonstrates that the proposed control algorithm enables the system to quickly track the desired trajectory and eventually achieve asymptotic stability. Finally, numerical simulations are conducted to validate the effectiveness of the proposed algorithm.
Exploring the Impact of Visual Complexity on Flow Experience in Online Visual Art Platforms: An Eye-Tracking Study
Authors: Liu Yonghan , Wang Yan
Published: January 2024

The flow experience of online platform users is an important factor affecting user stickiness and improving the quality of the platform. Analyzing the influencing factors of flow experience on online platform is a key step to improve the flow experience in the user’s use process. From the perspective of visual perception, this study analyzes the impact of visual factors on the flow experience. Starting with the complexity of the online platform interface, the eye tracking experiment was used to explore the impact of complexity and visual search efficiency on the flow experience. The experimental results show that the quantity complexity and functional layout complexity have different effects on the flow experience, and the visual search efficiency is positively correlated with the flow experience. In addition, the relationship between flow experience and quantity complexity was inverted U-shaped; It is positively correlated with the complexity of functional layout, but the impact is not significant.
Collaborative Filtering Is a Lie or Not? It Depends on the Shape of Your Data Domain
Authors: Wang Hao
Published: January 2024

Recommender systems are versatile. Algorithms such as collaborative filtering, DeepFM and Deep Matrix Factorization can be deployed in different commercial environments without a lot of fundamental modifications. Although there has been hot debate among academic scientists and industrial product owners, environment-sensitive algorithms remain a practice only in real world applications. In this paper, we discuss the topic whether collaborative filtering algorithm is a justified valid model by topological analysis of the problem structures. We claim that the validity of the algorithm is related to the shape of the input data domain.
Research on Business Continuity of Electric Power Information System
Authors: Ma Ji , Zhao Li , Zhang Chongchao
Published: January 2024

This article introduces the classification of disaster recovery levels for power information systems and a framework for business continuity construction. Through comprehensive risk analysis and evaluation of the impact on business continuity, recovery capability assessment and disaster recovery strategies were formulated, followed by planning and designing disaster recovery plans and developing business continuity plans. In order to improve the disaster recovery capability of information systems and ensure production safety and stability, the post-disaster recovery effect of power information systems was studied in depth. The power information system disaster recovery plan can effectively ensure production continuity and stability. By using appropriate disaster recovery plans and technical means, highly reliable and continuous information systems can be achieved to ensure smooth operation of enterprises and provide important support for enterprise production.
Nature-Inspired Optimization: Optimizing Distance of Emergency Response Wagons en Route to Railway Crossing Accident Location
Authors: Agbehadji Israel Edem , Millham Richard C. , Fong Simon James , Agbehadzi Richard Koblah
Published: January 2024

The problem is that when an accident occurs at a railway crossing, emergency response wagons are unable to get to the accident location on time. In this study, we consider the location of emergency response wagons and railway accident location and apply a nature-inspired search strategy as a solution to compute the optimal distance for an emergency response wagon such that when an accident occurs the expected time to reach the accident location can be minimized. The outcome suggests the ideal objective function, haversine method, because it produced the optimal minimal distance of 994,691.90km with a computational time of 1.05s for KSA over comparative algorithms namely BAT and (Ant Colony Optimization) ACO.
Low Overhead Adaptive Channel Equalizations for Upstream Burst Reception in 200Gbps Intensity Modulation-Coherent PONs
Authors: Sun Yuanzhe , Yang Tao , Chen Xue , Xiao Yi , Huang Xingang , Ma Zhuang , Zhong Yiming , Liu Bo
Published: January 2024

This paper presents a 200Gbps PON uplink burst coherent reception system that utilizes polarization-independent 4PAM optical intensity modulation-polarization diversity. To accommodate the burst changes in the PON uplink, we propose an adaptive channel equalization algorithm based on training sequences. This algorithm is characterized by low overhead, allowing for fast convergence. Simulation results demonstrate that adaptive compensation of PMD is feasible with a mere 18.5ns of preamble overhead. Additionally, by including only one SOA as a pre-amplifier in the OLT, a system power budget exceeding 35dB can be achieved.
Combing dynamic parameter identification and singular value decomposition adaptive unscented Kalman filter for predictive state of charge of lithium-ion batteries
Authors: Li Zehao , Wang Shunli , Yu Chunmei , Qi Chuangshi , Shen Xianfeng , Fernandez Carlos
Published: January 2024

The development of a secure battery management system (BMS) for electric vehicles depends heavily on the correct assessment of the online state-of-charge (SOC) of Li-ion batteries. The ternary lithium battery is used as the research object in this paper, and a second-order RC equivalent circuit model is developed to characterize the dynamic operating characteristics of the battery. In order to solve the problem that the adaptive unscented Kalman filter (AUKF) algorithm is easy to fail SOC estimation because the error covariance matrix is not positively definite due to the incomplete accuracy of the equivalent circuit model, a corresponding solution is proposed. Considering the poor real-time battery SOC estimate caused by the battery model’s fixed parameters, therefore we propose the Variable Forgetting Factor Recursive Least Squares (VFFRLS) algorithm for joint estimation of Li-battery SOC and the Singular Value Decomposition-AUKF (SVD-AUKF) algorithm. The SVD-AUKF algorithm can accurately estimate the SOC of the battery when the error covariance is negative. The algorithm can be adaptively adjusted in both the parameter identification and SOC estimation stages, which can effectively solve the problem of poor estimation accuracy caused by fixed parameters. According to experiments, under two separate dynamic operating situations, the joint estimation algorithm’s error is less than 2%, and its stability has also been greatly enhanced. At the same time, when the initial SOC value is set incorrectly, the convergence time of the algorithm proposed in this paper can reach within 2.1 seconds for BBDST and DST conditions, which can be well adapted to complex working conditions.
Application of hedge algebras algorithm for mobile robot controller via hand gestures and wireless protocol
Authors: Nguyen Anh Tu , Bui Thanh Lam , Bui Huy Anh , Nguyen Sy Tai , Nguyen Xuan Thuan
Published: January 2024

With the superior development of technology, mobile robots have become an essential part of humans’ daily life. Consequently, interacting and dealing with them pushes us to develop and propose different suitable Human-Robot Interaction (HRI) systems that can detect the interacted user’s actions and achieve the desired output in real-time. In this paper, we propose a closed-loop smart mechanism for two main agents: the hand gloves’ controller and the mobile robot. To be more specific, the developed model employs flex sensors to measure the curve of the finger. The sensor signals are then processed by aiding the Hedge Algebras Algorithm to control the movement direction and customize the speed of the mobile robot via wireless communication. Numerical simulation and experiments demonstrate that the mobile robot could operate reliably, respond rapidly to control signals, and vary its speed continually based on the different finger gestures. Besides, the control results are also compared with those obtained from the traditional fuzzy controller to prove the superiority and efficiency of the proposed method.
A machine learning-based data-driven approach to Alzheimer’s disease diagnosis using statistical and harmony search methods
Authors: Bolourchi Pouya , Gholami Mohammadreza
Published: January 2024

Alzheimer’s disease (AD) is the most prevalent brain disorder which affects millions of people worldwide. Early detection is crucial for possible treatment. In this regard, machine learning (ML) approaches are widely utilized for AD detection. In this paper, we propose an ML-based method that drastically reduces the dimensionality of features while maintaining the relevant features and boosting the overall performance. To remove irrelevant features, first statistical feature extraction method is applied, and then further reduction among remaining features is applied by utilizing the harmony search method (HSM). The selected features are the most informative features that are fed to the different classifiers. To test the effectiveness of the proposed method, we deployed three classification techniques including support vector machine (SVM), k-nearest neighbor (k-NN), and decision tree (DT). The experimental results show that the proposed method has a higher performance while decreasing the dimensionality of feature space. To guarantee that the performance of the proposed method is accurate, we applied an ensemble of three classifiers (SVM, KNN, and DT) for classification. The results of the proposed method verify that this method can be successfully deployed for AD detection, due to its high performance and low dimensional features, and can help improve the accuracy and efficiency of Alzheimer’s disease diagnosis. The proposed method demonstrated a significant improvement, achieving high performance in AD/HC classification, with accuracy, sensitivity, specificity, F1-score, MCC, and Cohen’s Kappa rates reaching 95.5%, 97%, 94%, 95.56%, 0.9104, and 0.9109, respectively. AD/HC classification displayed the highest performance. Additionally, in the more challenging pMCI/sMCI classification, the method achieved an accuracy of 78.50%, sensitivity of 84.00%, specificity of 73.00%, F1-score of 79.62%, MCC of 0.57, and Cohen’s Kappa of 0.59.
TODIM-PROMETHEE method for tourism landscape planning design scheme evaluation based on the virtual reality technology under spherical fuzzy sets
Authors: Tong Mingjia
Published: January 2024

How to explore the potential value of landscape, realize the organic combination of tourism landscape, enrich landscape elements and enhance tourism experience has become an important topic of tourism landscape planning and design, which is also a practical problem that needs to be solved urgently in the process of tourism landscape development and planning in different regions of China. The tourism landscape planning design scheme evaluation based on the virtual reality technology a typical multi-attribute group decision-making (MAGDM) problem. With the complexity of economic activities, uncertain information has an increasing impact on production activities. However, due to the ambiguity and uncertainty of human cognition, the factors affecting the risk of things cannot be accurately expressed. Therefore, selecting spherical fuzzy sets (SFSs) can make the expression of information more accurate and complete. On basis of the TODIM method and the PROMETHEE method, in this study, spherical fuzzy number TOMIM-PROMETHEE (SFN-TOMIM-PROMETHEE) method is implemented to solve the MAGDM problem under SFSs. Furthermore, CRITIC method under SFSs is implemented to determine relative weights. Then a numerical example for tourism landscape planning design scheme evaluation based on the virtual reality technology is selected to illustrate the effectiveness and practicality of the method. Finally, the comparative analysis shows that the SFN-TOMIM-PROMETHEE method under SFSs is an effective method to deal with MAGDM problems. The main contribution of this paper is managed: (1) the TODIM and PROMETHEE technique was extended to SFSs; (2) CRITIC technique is employed to manage the weight values under SFSs. (3) the SFN-TOMIM-PROMETHEE technique is founded to manage the MAGDM under IVPFSs; (4) a numerical example for tourism landscape planning design scheme evaluation based on the virtual reality technology and comparison analysis are constructed to verify the feasibility and effectiveness of the SFN-TOMIM-PROMETHEE technique.
Automatic detection of epileptic seizure using machine learning-based IANFIS-LightGBM system
Authors: Saranya D. , Bharathi A.
Published: January 2024

A sudden increase in electrical activity in the brain is a defining feature of one of the severe neurological diseases known as epilepsy. This abnormality appears as a seizure, and identifying seizures is an important field of research. An essential technique for examining the features of neurological issues brain activities, and epileptic seizures is electroencephalography (EEG). In EEG data, analyzing epileptic irregularities visually requires a lot of time from neurologists. For accurate detection of epileptic seizures, numerous scientific techniques have been used with EEG data, and most of these techniques have produced promising results. For EEG signal classification with a high classification accuracy rate, the present research proposes an enhanced machine learning-based epileptic seizure detection model. The present research provides a hybrid Improved Adaptive Neuro-Fuzzy Inference System (IANFIS)-Light Gradient Boosting Machine (LightGBM) technique for automatically detecting and diagnosing epilepsy from EEG data. The experimental findings were supported by EEG records made available by the German University of Bonn and scalp EEG data acquired at Children’s Hospital Boston. The suggested IANFIS-LightGBM, according to the results, offers the most significant classification accuracy ratings in both situations.
Hybrid optimized multimodal spatiotemporal feature fusion for vision-based sports activity recognition
Authors: Amsaprabhaa M.
Published: January 2024

Vision-based Human Activity Recognition (HAR) is a challenging research task in sports. This paper aims to track the player’s movements and recognize the different types of sports activities in videos. The proposed work aims in developing Hybrid Optimized Multimodal SpatioTemporal Feature Fusion (HOM-STFF) model using skeletal information for vision-based sports activity recognition. The proposed HOM-STFF model presents a deep multimodal feature fusion approach that combines the features that are generated from the multichannel-1DCNN and 2D-CNN network model using a concatenative feature fusion process. The fused features are fed into the 2-GRU model that generates temporal features for activity recognition. Nature-inspired Bald Eagle Search Optimizer (BESO) is applied to optimize the network weights during training. Finally, performance of the classification model is evaluated and compared for identifying different activities in sports videos. Experimentation was carried out with the three vision-based sports datasets namely, Sports Videos in the Wild (SVW), UCF50 sports action and Self-build dataset, which achieved accuracy rate of 0.9813, 0.9506 and 0.9733, respectively. The results indicate that the proposed HOM-STFF model outperforms the other state-of-the-art methods in terms of activity detection capability.
Modified TODIM-TOPSIS technique for type-2 neutrosophic number multiple-attribute decision-making and applications to innovation and entrepreneurship education evaluation in vocational colleges
Authors: Yin Bingquan , Ouyang Shaojuan , Hou Yali , Ma Jizhao
Published: January 2024

Innovation and entrepreneurship education is an important component of cultivating the comprehensive quality of college students and an important force in promoting economic and social development. Meanwhile, due to changes in the social environment and economic structure, traditional university education is no longer able to meet the needs of contemporary society. Therefore, innovation and reform of innovation and entrepreneurship education for college students are urgent. Innovation and entrepreneurship education for college students needs to keep up with the times, constantly update concepts and techniques, in order to adapt to the ever-changing social and economic environment. The innovation and entrepreneurship education evaluation in the application-oriented vocational colleges is a multiple-attribute decision-making (MADM) problem. Recently, the TODIM and TOPSIS technique has been used to cope with MADM issues. The Type-2 neutrosophic numbers (T2NNs) are employed as a technique for characterizing uncertain information during the innovation and entrepreneurship education evaluation in the application-oriented vocational colleges. In this paper, the Type-2 neutrosophic number TODIM-TOPSIS (T2NN-TODIM-TOPSIS) technique is implemented to solve the MADM under T2NNs. Finally, a numerical case study for innovation and entrepreneurship education evaluation in the application-oriented vocational colleges and several comparative analysis is implemented to validate the proposed T2NN-TODIM-TOPSIS technique. The main research contribution of this paper is managed: (1) the TODIM and TOPSIS technique was enhanced with T2NNs; (2) Entropy technique is enhanced to manage the weight values with T2NNs. (3) the T2NN-TODIM-TOPSIS technique is founded to manage the MADM with T2NNs; (4) Algorithm framework for innovation and entrepreneurship education evaluation in the application-oriented vocational colleges and several comparative analysis are constructed based on one numerical example to verify the effectiveness of the T2NN-TODIM-TOPSIS technique.
RETRACTED: Identify novel gene signatures in atrial fibrillation by comprehensive bioinformatics analysis
Authors: Li Hai , Gao Mingjian , Lin Zhizhan , Peng Jian , Xie Liangzhen , Ma Junjie
Published: January 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
A fuzzy rough granular ensemble learning based on the feature selection with chi-square1
Authors: Hou Xianyu , Chen Yumin , Wu Keshou , Zhou Ying , Lu Junwen , Weng Xuan
Published: January 2024

Neighborhood granulation is a classical granulation method. Although it is adequate for clustering and classification tasks, its granules are more complex, and the data representation is binary. This paper proposes a new granulation method based on the neighborhood granulation. Firstly, a detailed definition of the granular form is given with fuzzy rough set theory. Then, a modified fuzzy rough discriminant function is proposed based on neighborhood systems. The samples are globally granulated on single features to construct granules and on multiple features to construct granular vectors. Also, a feature selection technique based on the Chi-square, which strikingly reduces the complexity of the fuzzy rough granular vectors, is introduced to address the disadvantage of the fuzzy rough granular vectors. An ensemble model structure is also proposed in the paper for the mixed nature of fuzzy rough granular vectors. The paper makes a detailed comparison between the fuzzy rough granulation and the neighborhood granulation. The results show that fuzzy rough granulation has higher computational efficiency and classification performance. Finally, a detailed comparison is made between the fuzzy rough granular ensemble model and various classical ensemble algorithms. The final results show that the fuzzy rough granular ensemble model has better robustness and generalization.
A novel hybrid procedure of PLS-SEM, ANN and fuzzy TOPSIS for online banking
Authors: Xhafaj Evgjeni , Qendraj Daniela Halidini , Salillari Denisa
Published: January 2024

The adoption of online banking is a big challenge as well as an emergent paradigm which is evolving quickly. The study develops a new exploration model that is used to determine significant constructs of the UTAUT theory that influence the adoption of online-banking. A study was conducted through an online survey of online banking users. Three methods were used; firstly, PLS-SEM was used to determine which of the constructs have a significant impact on behavioral intention to use e-banking, secondly, an incorporated neural network model was used to classify the relative impact of significant variables obtained from PLS-SEM, and finally a hybrid procedure is incorporated from PLS-SEM to initialize the Fuzzy TOPSIS. The findings of the research paper constitute the ranked results and a comparison between them. The results of PLS-SEM and ANN analysis showed the same ranking for the constructs, while the decision making method Fuzzy TOPSIS introduced some changes in the ranking. This study presents valuable insights for the banking system to bring effective projects that increase the possibilities of using online banking.
RETRACTED: Deep attention transformer nets for accurate analysis of oil spilled images to minimize pollution in the marine environment
Authors: Sathya S. , Senthil Murugan J. , Surendran S. , Sundar R.
Published: January 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Addressing data scarcity issue for English–Mizo neural machine translation using data augmentation and language model
Authors: Khenglawt Vanlalmuansangi , Laskar Sahinur Rahman , Pakray Partha , Khan Ajoy Kumar
Published: January 2024

Low-resource language in machine translation systems poses multiple complications regarding accuracy in translation due to insufficient incorporation of linguistic information. The difference in the linguistic information between the language pair also significantly impacts the dataset creation for improving translation accuracy. Although neural machine translation achieves a state-of-the-art approach, dealing with low-resource language is challenging since it struggled with limited resources. This paper attempts to address the data scarcity problem using augmentation of synthetic parallel sentences, source-target phrase pairs, and language models at the target side for English-to-Mizo and Mizo-to-English translation via transformer-based neural machine translation. We have attained state-of-the-art results for both directions of translation.
A 2TLNS-based exponential TODIM-EDAS approach for evaluating sustainable development of cross-border e-commerce platforms under uncertainty
Authors: Xu Fang
Published: January 2024

In the context of globalization, cross-border e-commerce platforms have become the main way for enterprises to achieve international trade transformation and overseas investment. From this, it can be seen that cross-border e-commerce platforms are of great importance to the development of enterprises, and the development of cross-border e-commerce platforms is also a necessary choice for the development of the times. In the new era, in order to make cross-border e-commerce platforms better serve enterprises and bring economic benefits to their development. The sustainable development capability evaluation of third-party cross-border e-commerce (TPCBEC) platform is a MAGDM. Recently, the Exponential TODIM (ExpTODIM) technique and Evaluation Based on Distance from Average Solution (EDAS) technique has been employed to cope with MAGDM issues. The 2-tuple linguistic neutrosophic sets (2TLNSs) are employed as a tool for portraying uncertain information during the sustainable development capability evaluation of TPCBEC platform. In this paper, the 2-tuple linguistic neutrosophic number Exponential TODIM-EDAS (2TLNN-ExpTODIM-EDAS) technique is implemented to manage the MAGDM under 2TLNSs. Finally, a numerical study for sustainable development capability evaluation of TPCBEC platform is constructed to validate the implemented technique. Thus, the main advantages of the proposed 2TLNN-ExpTODIM-EDAS technique are outlined: (1) the proposed 2TLNN-ExpTODIM-EDAS technique not only handles the distances information from the 2TLNNAS, but also portrays the DMs’ psychological behavior during the sustainable development capability evaluation of TPCBEC platform. (2) the proposed 2TLNN-ExpTODIM-EDAS technique analyze the behavior of the TODIM technique and EDAS technique as MADM techniques when they are hybridized.
RETRACTED: Enhanced group decision-making framework for financial performance evaluation of high-tech enterprises under interval neutrosophic environment
Authors: Li Heng
Published: January 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Truthful mechanisms to maximize the social welfare in real-time ride-sharing
Authors: Shi Bing , Li Shun , Luo Yikai , Zhu Liquan
Published: January 2024

Ride-sharing contributes significantly to lowering trip expenses, easing traffic congestion and decreasing air pollution. However, current order pairing approaches in ride-sharing usually focus on minimizing total trip distances or maximizing platform profits, overlooking the drivers’ desire for increased earnings. As a result, drivers might provide dishonest information to gain higher profits, leading to inefficient order pairing for the ride-sharing platform and potential losses for both the platform and drivers. In this paper, we address this challenging issue by developing efficient order pairing mechanisms that maximize the social welfare of the platform and drivers. Specifically, we introduce two truthful auction-based order pairing mechanisms, SWMOM-VCG and SWMOM-GM, where drivers bid on platform-published orders to complete them and earn profits. We provide theoretical proof that both mechanisms fulfill the criteria of individual rationality, profitability, truthfulness and so on. Using real taxi order data from New York City, we assess the performance of both mechanisms and show that they achieve greater social welfare compared to existing methods. Additionally, we find that SWMOM-GM requires less computation time than SWMOM-VCG for order pairing, with only a minor reduction in social welfare.
Factors influencing employers’ support for employees with acquired brain injuries or mental illness to return to- and stay in work: A qualitative systematic review
Authors: Craven Kristelle , De Dios Pérez Blanca , Holmes Jain , Fisher Rebecca , Radford Kathryn A
Published: January 2024

BACKGROUND: People with acquired brain injuries (ABIs) often experience residual limitations and co-morbid mental illnesses that restrict work participation. Employers are key in enabling successful return-to-work and job retention. OBJECTIVE: This review aimed to explore employers’ perspectives of factors influencing their support for people with ABIs and/or mental illness to return to- and stay in work. Review questions focused on barriers and facilitators to their support, and contextual characteristics present at the time. METHODS: Five databases were searched from October 2010 until November 2023 for relevant qualitative studies published in English. Findings from included studies (N = 25) were synthesised using thematic synthesis. RESULTS: Included studies focused on employees with ABI or mental illness, rather than dually diagnosed ABI and mental illness. Employers’ support was influenced by their awareness/knowledge of- and attitudes towards the employee’s condition/illness; their skills and experience in supportive strategies; factors related to provision of work accommodations; and stakeholder influence. Similarities and differences in influential factors were observed across the ABI and mental illness literature. Contextual characteristics related to organisational characteristics, cultural taboo, and involvement of certain stakeholders. CONCLUSIONS: ABI survivors (with and without co-morbid mental illness) and their employers may benefit from specialist support and resources to guide them through the return-to-work process. Further research is needed to investigate employers’ knowledge of ABI and mental illness and supportive strategies. Exploration of the influence of other stakeholders, socio-demographic characteristics, and contextual factors on employers’ return-to-work and retention support for ABI survivors with co-morbid mental illness is warranted.
A classification of human resource management bundles for the inclusion of vulnerable workers
Authors: Kersten Amber , van Woerkom Marianne , Geuskens Goedele , Blonk Roland
Published: January 2024

BACKGROUND: Despite the societal importance to improve understanding of the role of employers in the inclusion of workers with a distance to the labor market, scant knowledge is available on the effectiveness of human resource management (HRM) bundles for the inclusion of vulnerable workers. OBJECTIVE: This paper studies which HRM bundles are applied by employers that hired people with a distance to the labor market, and to what extent these different bundles of HRM practices are related to employment of workers with specific vulnerabilities, such as people with disabilities or people with a migration background. METHODS: A latent class analysis of 1,665 inclusive employers was used to identify HRM bundles based on seven HRM practices: financial support practices, specialized recruitment, promotion and career opportunities, training opportunities, part-time work, job crafting, and adaptations to the workplace. RESULTS: Six bundles were identified: a recruitment and development bundle (34.4% of employers), a development bundle (24.8%), maintenance-focused practices (16.5%), a recruitment bundle (9.4%), a sustainable employment bundle (8.9%), and passive HRM (6.0%). Post-hoc analyses showed the probability of hiring specific vulnerable groups for each bundle (e.g., sustainable employment bundles showed the highest overall probability to hire people with a physical disability). CONCLUSION: Nuancing what is suggested in strategic HRM literature, we conclude that both extensive HRM and focused HRM bundles can be successful for the employment of vulnerable workers. In conclusion, there is no one-size-fits-all approach to inclusive employment and employers, large or small, can tailor their HRM systems to include vulnerable workers.
The EFEKTIFITAS PELAKSANAAN BIMBINGAN MANASIK HAJI TERHADAP PENINGKATAN KUALITAS IBADAH JAMAAH HAJI (KBIH) JABAL RAHMAH LAMPUNG TIMUR
Authors: Savinca Eka Lidia , Zahrofunnisa Fatimatus , Bustomi Ahmad
Published: January 2024

Guidance on the Hajj rituals is a very important form of service or guidance provided to prospective Hajj pilgrims by the Government as provision or guidance regarding all matters related to the Hajj pilgrimage, so that the pilgrims gain insight or knowledge so that during the implementation they can achieve a prosperous Hajj. The purpose of this research is to find out the effectiveness of the implementation of Hajj ritual guidance on improving the quality of congregational worship carried out by the KBIH Jabal Rahmah Office. The method used in this research is a qualitative descriptive research method, namely research that produces data in the form of words or speech from people or observed behavior. Meanwhile, data collection uses interview methods and also documentation collection. The results of the research were conducted through surveys and data analysis which also involved people who had taken part in the hajj ritual guidance program. The results show that the implementation of guidance involves learning about the hajj. Improving the quality of the hajj is aimed at sincere intentions in performing the hajj, obeying the hajj procedures and rules of the hajj, being patient in facing physical and emotional challenges.
The Structural-Genetic Theory Programme as General Theory to Social Sciences
Authors: Oesterdiekhoff Georg
Published: January 2024

The structural-genetic theory programme is an offshoot of Piagetian theory and Piagetian Cross-Cultural Psychology. It resorts to the application of stage theory to history, that is to parallels between ontogenetic and historical stages. Accordingly, the adolescent stage of formal operations evolved late in history, usually not before the 17th century, making and causing the Age of Enlightenment, with its manifestations: rise of physical sciences, industrial economy, formulation of liberty rights and humanistic philosophy, emergence of classical music, etc. The new theory offers possibilities to unify all human disciplines and social sciences under one common roof as they all need a general theory of the human being which stage theory can provide. They all deal with historical developments such as the history of language, law, sciences, economy, morals, philosophy, arts, worldview, religion, and politics that is shaped and carried by psychogenetic stage developments of humans in history.
Synthesis, Characterization and Ameliorative Effect of Iron Oxide Nanoparticles on Saline-Stressed Zea Mays
Authors: Iheme Callistus Izunna , John Peace Mmachukwu , Charleswalter Gift , Ohaeri Evangelina Ozoemena , Elemike Elias Emeka , Winifred Nsofor , Igwe Chidi Uzoma
Published: January 2024

High soil salinity induces osmotic and ionic stress that threaten crop production worldwide and affect food security. Iron oxide nanoparticles were synthesized using an aqueous leaf extract of _Diodella sarmentosa_, and the results of the characterization using FTIR, XRD, EDX, TEM, UV-vis, and SEM revealed the presence of polydisperse spherical iron oxide nanoparticles (FeONPs) with a maximum light absorption wavelength of 380 nm, and a size ranging from 2.22 to 27.83 nm. Foliar application of FeONPs on the salinized _Zea mays_ significantly (p<0.05) improved the plant's photosynthetic pigments (total chlorophyl (175.71%), chlorophyll a (256.34%), chlorophyll b (77.01%), carotenoid (39.36%), root length (9.87%), and antioxidant enzyme activities. From the findings, it can be deduced that FeONPs can improve the growth and development of saline-stressed _Zea mays _by lessening the negative effects that salt has on the plant.
Research of Competitive Pressure on Undergraduates' Intention to Study Abroad in Chinese Non-elite Universities
Authors: Sun Wei , Kang Lisa , Li Bingyan , Cheng Wenyue
Published: January 2024

With the development of the Chinese economy, it is difficult to find an ideal job after graduating from undergraduate studies, and more and more students are choosing to take the postgraduate entrance examination. Due to the limited academic resources of non-elite universities, many students encounter relatively more difficulties during the postgraduate entrance examination process. China is the world's largest exporter of international students, and hundreds of thousands of Chinese students choose to study abroad every year. At the same time, there are also fierce marketing challenges for study abroad agents and overseas universities serving Chinese students. In the context of the increasing competitive pressure of Chinese college students, this study conducted an empirical study on the intention of students from non-well-known universities in China. A total of 345 questionnaires were collected in 17 non-elite universities in 4 Chinese provinces, and the results showed that social influence, innovativeness, perceived risk and competitive pressure have significant effects on studying abroad intention. Innovativeness positively moderates the relationship between competitive pressure and students’ studying abroad intention. The results of the study not only provide practical advice for university students to study abroad, but also detailed marketing recommendations for study abroad agents and overseas universities.
Adjectives and Adverbs in Arabic
Authors: Ech-Charfi Ahmed
Published: January 2024

This paper discusses parts of speech in Classical and Modern Standard Arabic (‘Arabic’ for short), with a particular focus on the categories of Adjective and Adverb. Throughout the paper, we argue that there seems to be no distributional criteria that set adjectives or adverbs from substantives. In particular, neither morphological nor syntactic criteria can be used successfully to isolate a class of items used exclusively for noun or verb modification. The words used for these two functions seem to be part of the class of nouns and only semantic constraints determine which can be used as noun modifiers or as verb modifiers. Therefore, a theory that uses gross distribution only to identify syntactic categories must lump these together in a single class of substantives, as traditional Arab grammarians do.
An Explanation for Dark Energy from Whittaker Potential Theory
Authors: Titleman Mark
Published: January 2024

A recent article found that black holes with posited vacuum energy interior solutions alongside cosmological boundaries have a cosmological coupling constant of k=3, meaning that black holes gain mass proportional to a3 in a parameterization equation within a Robertson Walker cosmology – thus making black holes a cosmological dark energy species (Farrah et al. 2023). The mechanism for this is unknown. Two papers by E. T. Whittaker in 1903 and 1904 showed that all force potential could be understood as resulting from standing waves (static non-local solution) and propagating waves (local solution changing in time). This unification of gravitational and electromagnetic potential has been neglected even though it opens up new mathematical avenues and physical features. The mass-proportionality and preferred direction of the longitudinal waves within the two underlying Whittaker potentials can explain many features of General Relativity (Titleman 2022). They also offer a simple Newtonian explanation for dark energy stemming from Whittaker potential theory – it is produced as longitudinal motion within the Whittaker potentials only when dynamic electromagnetism is separate from time-static gravity in intergalactic space.
Exploring Birth Year as a Self-Identity Marker and Target for Nostalgia in YouTube Comments on Video Content from 1950 – 2019
Authors: Areni Charles
Published: January 2024

Automated text analysis of YouTube comments on videos featuring content indexed by year for each year between 1965 – 1981 (Study 1), each year between 1980 – 2005 (Study 2), and 56 of the 70 years between 1950 – 2019 (Study 3), identified key words associated with users’ disclosing their age in the year of the video (e.g., “I was _11 years old_ in 1974”). Reported ages ranged from -59 to 45, but 42.1% of the age-related comments referred to the birth year (e.g., “I was _born_ in 1963”). Birth also appeared more frequently than other major life events (e.g., birth of a sibling, high school graduation, marriage, birth of a child, etc.). One’s birth year is the opening chapter of their life story and an important aspect of self-identity, for which people have no autobiographical memories. Social media like YouTube may fill this psychological void by allowing users to view the world as it was in their birth year and publicly acknowledge the connection with their life story.
Two-Body Problem With Finite Speed of the Interaction Propagation
Authors: Onoochin Vladimir
Published: January 2024

Using one result of general relativity, namely the finiteness of the speed of gravity, it is considered how the finiteness of this speed can change behavior of two-body system, for example, wide binary stars. For such a system, when bodies move in circular orbits, one property of these orbits makes it possible to calculate the exact positions of the bodies at retarded time and, therefore, the forces acting on the bodies at the present instant, but taking into account the effect of gravitational retardation, namely, that these forces were created by sources located in retarded positions.

For Keplerian orbits, the effect of the gravitational retardation leads to an increase in the angular momentum of the two-body system. As applied to binary stars, the increase in the angular momentum over time can explain a disruption of wide binary stars into two single ones.

This effect has not previously been described in the scientific literature.
Profil pengobatan sindrom koroner akut di salah satu rumah sakit Tasikmalaya
Authors: Nur Aulia Iva Fadia , Rahayuningsih Nur , Sukmawan Yedy Purwandi
Published: January 2024

Sindrom Koroner Akut (SKA) merupakan salah satu penyakit mematikan di dunia dan penyebab utama terjadinya kematian secara mendadak pada seseorang dengan penyakit kardiovaskular. Sampai saat ini penelitian terkait profil demografi dan pengobatan pada pasien SKA di Indonesia masih sangat terbatas. Tujuan dari penelitian ini untuk melihat gambaran demografi serta profil pengobatan dari SKA di salah satu rumah sakit di Tasikmalaya periode Januari 2021 sampai dengan Juni 2022. Metode penelitian yang digunakan adalah penelitian cross-sectional dengan pengambilan data secara retrospektif. Berdasarkan penelitian ini diperoleh sebanyak 67 pasien dengan pasien terbanyak berjenis kelamin laki-laki (80,60%), usia 45-55 tahun (38,81%), tekanan darah <120/80 mmHg (35,82%), gejala nyeri dada (44,04%) dan riwayat penyakit edema paru (28,07%). STEMI menjadi jenis SKA terbanyak yang dialami (62.69%) dibandingkan dengan NSTEMI (11,94 %), dan UAP (25,37%), sedangkan profil pengobatan meliputi penggunaan fibrinolitik dengan obat-obatan lainya yang mendukung terapi SKA dengan penyakit penyerta lainya. STEMI, jenis kelamin laki-laki, gejala nyeri dada dan tekanan darah <120/80 mmHg mendominasi profil pasien SKA. Oksigen, dual terapi anti platelet, fibrinolitik, antikoagulan dan isdn paling banyak digunakan untuk tatalaksana NSTEMI dan UAP.
SOSIALISASI PENGENALAN PENDIDIKAN TINGGI KEPADA SISWA-SISWI SMA N 1 KERITANG KABUPATEN INDRAGIRI HILIR, PROVINSI RIAU
Authors: Khairul Ihwan  , Bindas Asniati , Amin Muhammad , Usman  , Sawitri Nina
Published: January 2024

Pendidikan Tinggi adalah jenjang pendidikan setelah pendidikan menengah yang mencakup program diploma, program sarjana, program magister, program doktor, dan program profesi, serta program spesialis, yang diselenggarakan oleh perguruan tinggi berdasarkan kebudayaan bangsa Indonesia.Tridharma Perguruan Tinggi yang selanjutnya disebut Tridharma adalah kewajiban Perguruan Tinggi untuk menyelenggarakan Pendidikan, penelitian, dan pengabdian kepada masyarakat. Tujuandarikegiataniniadalahuntukmemperkenalkantridarma dan suasanaperkuliahanbagisiswa-siswi SMA Negri 1 Keritang agar dapatmudahberadaptasinantinyadengan Pendidikan Tinggi yang suasananyaberbedadengan Pendidikan tingkat SLTA.Kesimpulan dariKegiatanPengabdianKepada Masyarakat iniadalahSiswa – Siswi SMA Negri 1 Keritang sangat antusiasuntukmelanjutkan Pendidikan tinggidalammengejarcita-citamembangundaerah.  Disarankankepada SMA Negri 1 Kerintanguntukmelakukan expo ataupamerah Pendidikan tinggidenganmengundangperguruantinggiternama di Riau, Sumatera Barat, Jambi, dan PulauJawa.
Weather-Climate Forecasting System for Early Warning in Crop Protection
Authors: Kataria Bhavesh
Published: January 2024

Weather and Climate forecasting is the application of science and technology to predict the state of the atmosphere for a given location. This provide occurrence or change in severity of plant diseases. At the field scale, these systems are used by growers to make economic decisions about disease treatments for control. Often the systems ask the grower a series of questions about the susceptibility of the host crop, and incorporate current and forecast weather conditions to make a recommendation. Forecasting system provide information about plants disease which happen due to Weather and Climate changes and it happen in such a fashion that disease can occur and cause economic losses.
Variant of RSA-Multi prime RSA
Authors: Kataria Bhavesh
Published: January 2024

Variant of RSA - Multi prime RSA that is backwards compatible that is a system using multi prime RSA can interoperate with systems using standard RSA and this variant is used to speed up RSA decryption.