bluuebunny/crossref_metadata_2025 huggingface dataset:
A hybrid evolutionary JAYA algorithm based on global optimization for 5G e-commerce logistics
Authors: Liu Hui , Zhong Xiaohui
Published: March 2024

With the increasing demand for logistics in modern society, how to achieve low-cost and efficient logistics delivery has become an urgent research topic. A hybrid evolutionary JAYA algorithm (H-JAYA) based on global optimization was designed to address the complex path planning problem of electric vehicles. This algorithm introduces a reverse learning mechanism to calculate the current optimal and worst individuals, while using differential perturbation mechanism and sine cosine operator to update the individual’s position. In addition, the study used the H-JAYA algorithm to construct a corresponding mathematical model for the optimization problem of electric vehicle paths. The results showed that in the three examples, the H-JAYA algorithm tested the optimal curve convergence speed, and it tended to stabilize after about 30 iterations. Meanwhile, in the RCDP5001 example, the total cost of the H-JAYA algorithm reached the lowest value of 623 yuan. The H-JAYA algorithm has significant advantages in solving the distribution path problem of electric vehicles, and can be well applied to practical logistics distribution, providing effective technical support for modern e-commerce logistics planning.
Urban ecological human settlements design based on green and low-carbon concept
Authors: Zhou Jianhua
Published: March 2024

In recent years, the continuous growth of global carbon emissions has brought about climate change and global ecological environment problems, as well as severe challenges to the development of human settlements. Based on the concept of low carbon, this paper analyzes and summarizes the current situation of green space in typical residential areas, and quantifies its annual carbon sequestration. Then this paper discusses the design optimization strategy to improve its carbon sink efficiency based on the current situation. Finally, the effectiveness and enforce ability of the optimization strategy are verified by estimating the annual carbon sequestration increase value of the green space after the optimization strategy is applied to an example. The method has a certain reference value for the design and research of urban ecological human settlements with the concept of green and low carbon.
Application of deep learning in English translation of children’s picture books
Authors: Chen Yafang
Published: March 2024

This study aims to explore the application of deep learning technology in the translation of children’s picture books. By analyzing the existing translation of children’s picture books, we extract the key factors to be considered in the translation process, and design a deep learning model to deal with these factors to achieve high-quality translation. At the same time, a picture book image recognition system is also implemented, which can understand the image content in the picture book and integrate these contents into the translation. Through continuous training and optimization of the model, an efficient picture book translation tool is obtained. In addition, the performance of the model in practical applications was evaluated, and the practical impact and value of deep learning in children’s picture book translation was explored through user feedback and surveys.
Sci-tech innovation, industrial structure transformation and economic development: An empirical study based on province panel data of China
Authors: Shao Mingzhen , Yuan Pei , Zhao Rui , Gu Yanyan
Published: March 2024

Based on panel data of 31 provinces in China from 2000 to 2019, this study explores the complex dynamic interaction between scientific and technological innovation, industrial structure transformation and economic development by building PVAR model. After GMM estimation, impulse response function analysis and variance decomposition analysis, the following conclusions are drawn: Technological innovation has a significant promoting effect on economic development, and economic development can also promote technological innovation; Technological innovation has a positive impact on industrial structure transformation, while industrial structure transformation has a slight negative impact on technological innovation; Economic development can lead to industrial structure transformation, but the impact of industrial structure transformation on economic development is not significant.
Mechanism of action of Geobacillus stearothermophilus on different shapes of residual oil
Authors: Han Hongyan , Shi Ruiying , Zhang Yaoyao , Li Na , Fan Linghe , Zhang Xing
Published: March 2024

Feeding on crude oil and activator in porous medium, microbes remain active on the Oil-water interface under simulated reservoir conditions. At the same time, microbes degrade the residual oil and change the wettability of pore wall. Consequently, the displacement exhibits a decrease of 51.86% in membrane residual oil and an increase of 17.44% in recovery compared with water flooding. The Geobacillus stearothermophilus producing bio-emulsifier and its metabolic products can effectively emulsify reservoir crude oil and reduce the oil-water interfacial tension. In the end and the formed emulsion featured high viscosity can improve the oil flow rate and expanded wave volume of injected fluid. Correspondingly, the cluster-like, columnar residual oil were reduced by 64%, 68% respectively. In the micro porous test cell, the in-situ cultured microbes rely on specific life activities (interfacial tropism and in situ metabolism, etc.) to strip the residual oil off the wall of orifice deep inside the blind-ends, which cannot be achieved by the exogenous injection method. After the in-situ microbial culture process, the residual oil in deep blind-ends was reduced by about 47%, and the recovered oil was increased about 15% compared with exogenous injection method.
A study on the innovative model of foreign language teaching in universities using big data corpus
Authors: Zhao Ying , Liang Genshun
Published: March 2024

This paper aims to explore unsupervised cross-lingual word representation learning methods with the specific task of acquiring a bilingual translation lexicon on a monolingual corpus. Specifically, an unsupervised cross-lingual word representation co-training scheme based on different word embedding models is first designed and outperforms the baseline model. In this paper, we adeptly tackles the obstacles encountered in higher education foreign language teaching and underscores the necessity for inventive teaching methods, and design and implement a linear self-encoder-based principal component acquisition scheme for the interpoint mutual information matrix obtained from a monolingual corpus. And on top of this, a collaborative training scheme based on linear self-encoder for cross-language word representation is designed to improve the learning effect of cross-language word embedding. The results of the study show that the most obvious rise in the pre and post tests of the experimental class in the practical application of the foreign language teaching model based on the method of this paper is the word sense guessing, which rose by 23.12%. Sentence meaning comprehension increased by 23.39%, main idea by 16.61%, factual details by 15.47%, and inferential judgment by 10.28%. Thus, the feasibility of the unsupervised cross-linguistic word representation learning collaborative training method is further verified.
Application of BPNN’s intelligent ETQ model in network English teaching
Authors: Wu Qianqian
Published: March 2024

Teaching evaluation is a key initiative to improve the quality of education and teaching. The research significance of this study is rooted in addressing the limitations of the traditional evaluation of teaching quality (ETQ) model, which often relies on a single evaluation index, exhibits a one-sided perspective, and suffers from pronounced subjectivity. In this context, this paper delves into the application of the backpropagation neural network (BPNN) to enhance and refine the ETQ model. The intelligent ETQ model was constructed and utilized in network English teaching to enhance the effect and quality of network English teaching. By analyzing the characteristics and needs of network English teaching, the advantages of BPNN in the ETQ were explored. The intelligent evaluation model was constructed, and its application effect in network English teaching was studied and evaluated. The total number of students satisfied with the BPNN based network English ETQ model was 151, with a total satisfaction rate of 75.5%. The ETQ model on the basis of BPNN was applied to network English teaching, which helped the average final score of Class 2 improve by 5.44 points compared to the division exam. The ETQ model based on BPNN was applied to network English teaching, which can improve the rationality of teaching evaluation and help improve students’ school English proficiency.
Validation study of Yunnan ethnic culture industry stock model under epidemic situation based on chaotic particle swarm optimization neural networks
Authors: Jiang Jiaying , Wang Zhixiu , Tao Sha , Tan Xinyi , He Ying , Pan Wenchao
Published: March 2024

The new crown pneumonia epidemic is raging, in the context of global integration, the scope of the impact of this sudden event spread around the world, the stock market has not been spared, the financial risk has increased dramatically compared with the past, the emergence of the epidemic has led to the spread of investor panic, March 2020, the U.S. S&P 500 index appeared in the four plunge, and led to the market trading meltdown, the world’s financial markets have had an extremely serious impact. The study of the impact of Xin Guan Pneumonia on the company’s stock returns is not only conducive to enriching the theoretical study of public health emergencies, but also conducive to improving the coping strategy, stabilizing the general economic market, and enhancing the public’s awareness of risk response. This paper compares the effect of the four intelligent algorithms of chaotic particle swarm algorithm, chaotic bee colony algorithm, chaotic fruit fly algorithm and chaotic ant colony algorithm combined with neural network on the prediction of the stock price trend of Yunnan national culture, and the study shows that the speed of convergence of the chaotic particle swarm optimization neural network and the speed of descent is better than that of the two models of chaotic fruit fly and chaotic bee colony, and the coefficients of decision of the chaotic particle swarm optimization neural network are higher than that of the other three models, and the errors are lower than the other three models. Indexes are lower than the other three models and have high accuracy in stock prediction of Yunnan ethnic culture, this finding emphasizes the potential of PSO-BP model to provide robust stock market prediction, which is important for both investors and policy makers in dealing with volatile market conditions.
A research on inversion of water quality parameters in the mulan river based on GF-1B\C\D remote sensing images
Authors: Lin Zhuo , Song Jinling , Kang Yan , Huang Da , Zhu Meining
Published: March 2024

Remote sensing inversion technology can be used for water quality parameter inversion to realize water quality monitoring in large scale space. The current research on water quality parameter inversion is only for a single satellite. In order to make full use of satellite image resources, the remote sensing images of GF-1B\C\D satellite group are taken as the research object. The Mulan River is taken as the research area. The linear regression method is used to construct the regression equations of total phosphorus and ammonia nitrogen, and the inversion model of total phosphorus and ammonia nitrogen is determined according the evaluation parameters. The MSE of the total phosphorus inversion model is 0.049, and the correlation between the inversion value and the measured value is 0.701. The MSE of the ammonia nitrogen inversion model is 0.063, and the correlation between the inversion value and the measured value is 0.813. These data show that the inversion effect is good. The inversion models are applied to the GF-1D satellite remote sensing image on March 15, 2021 to obtain the large-scale spatial distribution maps of total phosphorus concentration and ammonia nitrogen concentration. The water quality classification maps of the the Mulan River in Putian urban area are obtained too, which are convenient for further analysis and evaluation of the water quality.
Personality traits changes in the training process of Chinese airline transport pilots
Authors: Zhu Shouxi , Chen Jian
Published: March 2024

OBJECTIVE: To study the personality changes of Chinese airline transport pilots in the training process from cadets to captains. METHODS: In This paper, we used the Cattell 16 Personality Factor Questionnaire (16PF) to track and record the personality traits of 200 students majoring in flight technology and 200 “college graduates to pilot” in five different periods from the beginning of aviation theory training to becoming captains. RESULTS: Before the aviation theory training, for the 16 factors of 16PF, there was a significant difference in 11 factors (including Warmth (A), Reasoning (B), etc.) between the students majoring in flight technology and “college graduates to pilot” (p< 0.05). After the completion of theory training, there were only four factors (Sensitivity (I), Openness to Change (Q1), Self Reliance (Q2) and Perfectionism (Q3) (p< 0.05) between the students majoring in flight technology and “college graduates to pilot”, then after the flight training, there is no significant difference between them. When they became captains, compared with when they were flying cadets, 13 factors of students majoring in flight technology and 7 factors of “college graduates to pilot” had changed significantly. From the perspective of the growth of flying cadets, in the process of becoming a captain, there are three stages that have a great influence on the personality of the participants. The first stage is the university study. The second stage is the flight training, and the third stage is the copilot growing into a captain. CONCLUSION: During the process of a pilot growing from a cadet to a captain, his or her personality is constantly developing and changing, and on the whole, develops towards a personality direction conducive to flight safety. In particular, when a copilot grows into a captain, the personality traits of a qualified airline pilot, including Emotional Stablity (C), Rule-Consciousness (G), Social Boldness (H), Privateness (N), Self-Reliance (Q2), etc., have been greatly strengthened at this stage.
Multi-distribution bi-deniable inner product encryption based on Decision-LWE
Authors: Ding Hangchao , Tang Huayun , Jia Chen , Wang Yanzhao
Published: March 2024

Bi-deniable Encryption scheme means that when the sender and the receiver are coerced, the coercer can obtain fake plaintext, random numbers, and secret keys. It’s a solution strategy in the case of information leakage. Compared with traditional encryption, deniable encryption can provide secret communications in situations of coercion in the Post-Quantum era. Compared with sender-deniable encryption and receiver-deniable encryption, bi-deniable encryption can achieve secret communications in the situation that both sender and receiver are coerced by the coercer. So, we propose to design a bi-deniable encryption scheme under the multi-distribution model. In our bi-deniable encryption scheme, we construct a bi-deniable encryption scheme based on the assumption of Decision-Learning With Errors (DLWE) under the multi-distribution model. Firstly, the principle of Inner Product Predicate Encryption (IPPE) is applied in our scheme. Secondly, we apply the framework of Bi-Translucent Set (BTS), combined with inner product predicate encryption. Thirdly, we construct a series of probabilistic polynomial time algorithms, which apply linear transformation between different lattice structures, and Regev dual encryption. Fourthly, the statistical indistinguishability between the sampling algorithm with discrete Gaussian sampling algorithm, and the computational indistinguishability between LWE’s ciphertext samples with uniform samples, the property of indistinguishability is applied in theorem proving, which obtain Indistinguishability under Chosen Plaintext Attacks (IND-CPA) security and the property of bi-deniability. Given the value range of the Gaussian parameter and security parameter in our scheme, the correctness of the bi-deniable encryption scheme is guaranteed. We also give the security proof of IND-CPA and bi-deniability’s property by a series of games. The ‘Inner-Product Bi-Translucent Set’ Bi-Deniable Encryption scheme under the multi-distribution model is based on Decision-LWE assumption, and can avoid quantum-resistant attacks. The bi-deniable encryption scheme is firstly constructed by the inner product with the Decision-LWE assumption, which can provide better properties of security and deniability.
RETRACTED: GAITBOOST: Boosting gait recognition performance with BAT-extreme learning machines algorithm
Authors: Premalatha G. , Chandramani Premanand V. , Panimalar K.
Published: March 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
RETRACTED: Epileptic seizure detection using improved empirical mode decomposition and improved weight updated KNN
Authors: Saichand N. Venkata , Naik S. Gopiya
Published: March 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
CADC-FPRLE: Content-aware deduplication clustering analysis using file partitioning and a running length encoder for cloud storage optimization
Authors: Shakkeera L. , Dhiyanesh B. , Asha A. , Kiruthiga G.
Published: March 2024

To address this storage issue, we propose a Content-Aware Deduplication Clustering Analysis for Cloud Storage Optimization (CADC-FPRLE) based on a file partitioning running length encoder. At first, preprocessing was done by indexing, counting terms, cleansing, and tokenizing. Further multi-objective clustering points are analysed based on the bisecting divisible partition block, which divides a set of documents. The count terms are filtered from the divisible blocks and make up the count terms content block. Using Content-Aware Multi-Hash Ensemble Clustering (CAMH-EC) to group the similar blocks into clusters. This creates a high-dimensional Euclidean interval to create the number of clusters, and points are performed randomly to set the initial collection. Then, the Magnitude Vector Space Rate (MVSR) estimates the similarity distance between the groups to select the highest scatter value content for indexing. Finally, the Running Block Parity Encoder (RBPE) generates similarity parity in order to reduce the content to a redundant, singularized file in order to optimise storage. This implementation proves a higher level of storage optimization compared to the previous system than other methods.
Performance study of fuzzy C-mean clustering algorithm based on local density in network security
Authors: Song Can
Published: March 2024

The development and utilization of network big data is also accompanied by data theft and destruction, so the monitoring of network security is particularly important. Based on this, the study applies the fuzzy C-mean clustering algorithm to the network security model, however, the algorithm has major defects in discrete data processing and the influence of feature weights. Therefore, the study introduces the concept of local density and optimizes the initial clustering center to solve its sensitive defects as well as empirical limitations; at the same time, the study introduces the adaptive methods of fuzzy indicators and feature weighting, and uses the concepts such as fuzzy center-of-mass distribution to avoid problems such as the model converging too fast and not being able to handle discrete data. Finally, the study does a simulation analysis of the performance of each module, and the comparison of the overall algorithm with the rest of the models. The experimental results show that in the comparison of the overall algorithm, its false detection rate decreases by 8.57% in the IDS Dataset dataset, compared to the particle swarm algorithm. Therefore, the adaptive weighted fuzzy C-Means algorithm based on local density proposed in the study can effectively improve the network intrusion detection performance.
An improved arithmetic optimization algorithm with multi-strategy for adaptive multi-spectral image fusion
Authors: Mi Xiaodong , Luo Qifang , Zhou Yongquan
Published: March 2024

Panchromatic and multi-spectral image fusion, called panchromatic sharpening, is the process of combining the spatial and spectral information of the source image into the fused image to give the image a higher spatial and spectral resolution. In order to improve the spatial resolution and spectral information quality of the image, an adaptive multi-spectral image fusion method based on an improved arithmetic optimization algorithm is proposed. This paper proposed improved arithmetic optimization algorithm, which uses dynamic stochastic search technique and oppositional learning operator, to perform local search and behavioral complementation of population individuals, and to improve the ability of population individuals to jump out of the local optimum. The method combines adaptive methods to calculate the weights of linear combinations of panchromatic and multi-spectral gradients to improve the quality of fused images. This study not only improves the quality and effect of image fusion, but also focuses on optimizing the operation efficiency of the algorithm to have real-time and high efficiency. Experimental results show that the proposed method exhibits strong performance on different datasets, improves the spatial resolution and spectral information quality of the fused images, and has good adaptability and robustness. The source code is available at: https://github.com/starboot/IAOA-For-Image-Fusion.
Multi-label text classification of cardiovascular drug attributes based on BERT and BiGRU
Authors: Cui Hongzhen , Zhang Longhao , Zhu Xiaoyue , Guo Xiuping , Peng Yunfeng
Published: March 2024

Extracting and digitizing drug attributes from medical literature is the first step to build a knowledge computing system for precision disease treatment. In order to build a cardiovascular drug knowledge base, this paper proposes a multi-label text classification method for cardiovascular drug attributes from the Chinese drug guideline. The drug attributes are characterized by a BERT pre-trained model, and a dual-feature extraction structure is proposed based on the BiGRU neural network to capture high-level semantic information. Label categorization of cardiovascular drug attributes, such as indications and mode of administration, is accomplished. The F1 score of 0.8431 was obtained using 5-fold cross-validation. Comparing KNN and Naïve bayes, and conducting CNN and BiGRU control experiments on the basis of Word2Vec characterization of medication guidelines, the proposed multi-label text classification method is effective and the F1 value is significantly improved. Proved by analysis of ablation and crossover experiments, the proposed method can achieve a high accuracy rate averaged at 0.8339.
The improved strategy of BOA algorithm and its application in multi-threshold image segmentation
Authors: Wang Lai-Wang , Hung Chen-Chih
Published: March 2024

In response to the low efficiency and poor quality of current seed optimization algorithms for multi-threshold image segmentation, this paper proposes the utilization of the normal distribution in the cluster distribution mathematical model, the Levy flight mechanism, and the differential evolution algorithm to address the deficiencies of the seed optimization algorithm. The main innovation lies in applying the BBO algorithm to image multi threshold segmentation, providing a new perspective and method for image segmentation tasks. The second significant progress is the combination of Levy flight dynamics and differential evolution algorithm (DEA) to improve the BBO algorithm, thereby enhancing its performance and image segmentation quality. Therefore, a multi-threshold image segmentation model based on the optimized seed optimization algorithm is developed. The experimental results showed that on the function f1, the iteration of the improved seed optimization algorithm was 53, the Generational Distance value was 0.0020, the Inverted Generational Distance value was 0.098, and the Spacing value was 0.051. Compared with the other two algorithms, the improved seed optimization algorithm has better image segmentation performance and clearer image segmentation details. In summary, compared with existing multi-threshold image segmentation methods, the proposed multi-threshold image segmentation model based on the improved seed optimization algorithm has a better image segmentation effect and higher efficiency, can significantly improve the quality of image segmentation, has positive significance for the development of image processing technology, and also provides references for the improvement and application of optimization algorithms.
Whether search directions number affects the efficiency of the path planning algorithm: Taking an improved ACO algorithm with 32 directions for example
Authors: Zhang Jianhua , Liu Chan , Geng Na , Zhang Yixuan , Yang Liqiang
Published: March 2024

An improved Ant Colony Optimization (ACO) algorithm, named IACO, is proposed to address the inherent limitation of slow convergence, susceptibility to local optima and excessive number of inflection in traditional ACO when solving path planning problems. To this end, firstly, the search direction number is expanded from 4 or 8 into 32; Secondly, the distance heuristic information is replaced by an area heuristic function, which deviated from the traditional approach that only considers pheromone information between two points; Then, the influence of path angle and number of turns is taken into account in the local pheromone update. Additionally, a reward and punishment mechanism is employed in the global pheromone update to adjust the pheromone concentrations of different paths; Furthermore, an adaptive update strategy for pheromone volatility factor adaptive is proposed to expand the search range of the algorithm. Finally, simulation experiments are conducted under various scenarios to verify the superiority and effectiveness of the proposed algorithm.
Fatigue load spectrum generation of Indonesian high-speed trains
Authors: Setiawan Hery , Putra Ichsan Setya , Nurrahman Latif , Wiragunarsa I. Made , Sibarani Intan , Jusuf Annisa , Raharjo Bambang
Published: March 2024

The high-speed trains designed and constructed in Indonesia will use Aluminum alloy Al 6061-T6 as a structural material. Aluminum alloys are prone to fatigue failure due to the absence of endurance limit of the material, hence fatigue life prediction has to be carried out. Fatigue cracks could initiate at the defects of welded joints. Analyzing the fatigue load spectrum of critical locations in the train structures is crucial to predicting fatigue life. These critical locations are selected from areas with high static stress and stress concentration. The loads are analyzed using the multibody dynamic with rigid body assumptions and track roughness following UIC Standard Code 518. The finite element method is used to calculate the stresses from the loads generated by the multibody dynamic. The load sequence is further analyzed with rainflow counting method, and the load exceedance curve can be constructed. Finally, the Miner Linear Cumulative Damage Model is used to predict fatigue life.
Similarity joins and clustering for SPARQL
Authors: Ferrada Sebastián , Bustos Benjamin , Hogan Aidan
Published: March 2024

The SPARQL standard provides operators to retrieve exact matches on data, such as graph patterns, filters and grouping. This work proposes and evaluates two new algebraic operators for SPARQL 1.1 that return similarity-based results instead of exact results. First, a similarity join operator is presented, which brings together similar mappings from two sets of solution mappings. Second, a clustering solution modifier is introduced, which instead of grouping solution mappings according to exact values, brings them together by using similarity criteria. For both cases, a variety of algorithms are proposed and analysed, and use-case queries that showcase the relevance and usefulness of the novel operators are presented. For similarity joins, experimental results are provided by comparing different physical operators over a set of real world queries, as well as comparing our implementation to the closest work found in the literature, DBSimJoin, a PostgreSQL extension that supports similarity joins. For clustering, synthetic queries are designed in order to measure the performance of the different algorithms implemented.
Impacts of the COVID-19 pandemic on health and social professionals working with people with disabilities: A qualitative study
Authors: Fortin-Bédard Noémie , Bouchard David , Ladry Naomie-Jade , Lettre Josiane , Normand Boucher , Beaulieu-Bonneau Simon , Lecours Alexandra , Perreault Kadija , Annie LeBlanc , Routhier FranÇcois , Lamontagne Marie-Eve
Published: March 2024

BACKGROUND: Since the beginning of the COVID-19 pandemic, protection and isolation measures established by the Canadian and Quebec governments have directly affected the work of health and social professionals (HSPs). These measures have added pressure on HSPs, complexified their work and added tasks to their already busy workload. However, few studies have explored in depth the impacts of the pandemic on HSPs working with people with disabilities. OBJECTIVE: The objective of this study was to qualitatively explore the experiences of HSPs working among people with disabilities in the province of Quebec, Canada, during the COVID-19 pandemic (January and February 2021), including the impact on their work, the relationships with their colleagues, and on their immediate social and familial environment. METHODS: HSPs participated in a semi-structured interview. A mixed thematic analysis approach, combining inductive and deductive coding, was carried out using N’Vivo 12. RESULTS: Fifty-five HSPs participated in the interviews (mean [SD] age, 42 [9]). They mostly identified as women (91%). Three main themes representing the impacts of the pandemic were identified, including 1) Health and Well-being; 2) Family and social networks including the subthemes; 2.1) Fear of being a vector of contamination for their loved ones; 2.2) Work-family balance; 2.3) Social Network, and finally 3) Work, highlighting, including 3.1) Workload and adaptative strategies developed; 3.2) Relationship with colleagues; 3.3) Perceived support received at work, and 3.4) Services offered to patients. CONCLUSIONS: These findings highlight the importance of closely tracking and supporting the well-being of HSPs.
A thematic analysis of how men and women post 56 years unwind from work during their free time
Authors: Cropley Mark , Da Silva Isabella N. , Rydstedt Leif W. , Olsson Maria I.T.
Published: March 2024

BACKGROUND: Recent research indicates that as men age, their tendency to ruminate about work decreases, while ruminating remains high in women, which poses an increased risk for impaired health among older women. OBJECTIVE: This study explored gender differences/similarities in the process of unwinding from work in men and women aged between 56–65 years. METHODS: Semi-structured qualitative interviews were conducted online with eight men and eight women, recruited from a UK leading organization that provides health care solutions between May and June 2022. Participants were asked about their job role and responsibilities, their leisure time activities, how they unwind post work, and their experiences of thinking about work related thoughts outside of work. Transcripts were analyzed using an inductive analysis. RESULTS: Three superordinate themes were identified that underpinned their ability to unwind: ‘Work style’, ‘Creating work-life balance’ and ‘Switching off from one’s responsibilities’. Women reported a more perfectionist approach, they set high standards for themselves, were worried about making mistakes, and demonstrated, if in a supervisory role, a more nurturing and holistic approach to their colleagues/subordinates, while men, were more focused on task completion. Most women, but not men, also described difficulties in psychologically switching off from work, and stated they could only truly relax outside the home, when they are away from household activities. CONCLUSION: The study provides nuanced insights into the experiences of unwinding from work, and the findings suggest the need for person-centric approaches in developing interventions to help workers over 56 years to psychologically disengage from work.
The impact of transition programs on well-being, experiences of work environment and turnover intentionamong early career hospital nurses
Authors: Eklund Annika , Sterner Anders , Nilsson Maria Skyvell , Larsman Pernilla
Published: March 2024

BACKGROUND: Transition programs for newly graduated nurses in hospital settings are reported to provide learning opportunities, strengthening confidence, workplace integration and skills, retention and job satisfaction. Still, our knowledge of long-term effects is scarce and few studies have used control groups. OBJECTIVE: To explore the long-term impact of having attended a transition program on the nurses’ experiences of the first years of practice. More specifically, ideology-infused psychological contract, ethical stress, perceived organizational support, job satisfaction, opportunities for learning, and intention to stay in the nursing profession, were explored as outcome variables. METHODS: A questionnaire survey was carried out among registered nurses from November 2019 to January 2020, with a 54% response rate. The analysis was based on 149 nurses who had attended a transition program, and 72 who had not attended. The nurses had seniority between one and three years. Independent samples t-test were used to investigate differences between the groups. RESULTS: The two groups showed small and non-significant differences in the outcome variables. However, regarding the frequency of ethical value conflicts induced by insufficient resources, as well as experiences of ethical value conflict distress, the group of nurses who had attended a transition program showed statistically significantly higher mean values, although the effect sizes were small. CONCLUSION: Newly graduated nurses need more than transition programs and skills training to progress in their nursing role and develop competence, increase job satisfaction, and reduce stress. Achieving these goals requires a long-term supportive learning environment that is integrated into everyday work.
The impact of customized employment on the competitive integrated employment outcomes of transition age youth with intellectual and developmental disabilities: A randomized controlled trial study
Authors: Inge Katherine J. , Wehman Paul , Avellone Lauren , Broda Michael , McDonough Jennifer
Published: March 2024

BACKGROUND: Customized employment (CE) is recognized in the Workforce Innovation and Opportunity Act (2014) as a strategy for promoting competitive integrated employment. However, the existing body of evidence supporting CE is mainly descriptive rather than experimental research. OBJECTIVE: This study examined the impact of CE on the employment outcomes, hours worked per week, and wages of transition-age youth with intellectual and developmental disabilities. METHOD: The outcomes of transition-age youth participating in a CE intervention were compared to those receiving treatment-as-usual using a randomized controlled trial design. RESULTS: Participants receiving CE were significantly more likely to secure competitive integrated employment than controls who received treatment-as-usual. Participants in the intervention and control conditions earned similar wages. Participants in the control condition worked more hours per week than those in CE. CONCLUSION: The findings from this study demonstrate the effectiveness of CE to assist transition-age youth with intellectual and developmental disabilities in obtaining competitive integrated employment, but future research is needed to examine factors impacting weekly hours and wages of participants in CE.
INFLUENCE OF ENVIRONMENTAL, SPATIAL AND TEMPORAL FACTORS ON BLUE SHARK, Prionace glauca, CATCH RATE IN THE SOUTHWESTERN ATLANTIC OCEAN
Authors: Mourato Bruno Leite , Amorim Alberto Ferreira , Arfelli Carlos Alberto , Hazin Fábio Hissa Vieira , Hazin Humberto Gomes , Carvalho Felipe Correia
Published: March 2024

A Generalized Additive Model (GAM) was fitted to blue shark, Prionace glauca (Linnaeus, 1758), CPUE data (shark numbers per 100 hooks) from tuna longliners based in São Paulo State, Brazil, between 1998 and 2006, with the aim to observe their relationship with environmental, spatial and temporal information. GAM model accounted for 42% of the variance in nominal CPUE. Stepwise GAM revealed the relative importance of eight variables by decreasing magnitude, namely latitude, year, month, longitude, chlorophyll-a concentration, sea surface temperature, wind speed and ocean depth. Spatial and temporal factors accounted for 91.5% of the cumulative deviation explained by the model, while environmental factors responded for only 8.5%. The highest blue shark relative abundance was observed between January and June, with a peak in April. It increasedsoutheastward, below 20°C, between 1,500 and 4,000 meters depth. Chlorophyll-a showed highest CPUE values between 0.35 and 0.90 mg.m -3 . Wind speed presented a positive effect on catch rate up to 2 m.s -1 , followed by a steep decline. Standardized yearly CPUE trend was stable, with two peaks, one in 2001 and another in 2006. Both were followed by a high variance.
REGISTRO DE OCORRÊNCIA DE Himantura schmardae (CHONDRICHTHYES: DASYATIDAE) NA COSTA NORTE DO BRASIL
Authors: De Almeida Maurício Pinto , Almeida Patricia Charvet , Rincon Getulio , Barthem Ronaldo
Published: March 2024

A distribuição das espécies do gênero Himanturaé conhecida para a região do Indo-Pacífico e  América Central (Oceanos Atlântico e Pacífico) em águas doces e estuarinas. Este é o primeiro registro do gênero e da espécie Himanturaschmardae na costa do Brasil. Quatro exemplares desta espécie foram capturados em diferentes pescarias com rede-de- arrasto de fundo nos meses de setembro de 1996 e abril de 1997 na foz do Rio Amazonas. Um exemplar macho imaturocom comprimento total de 128 cm e largura de disco de 54 cm encontra-se depositado na Coleção Ictiológica do Museu Paraense Emílio Goeldi (número de registro MPEG 3547). A espécieH. schmardae é conhecida pelo nome vulgar eminglês de chupare stingray e regionalmente recebe nome de arraia-redonda. O registro de ocorrência desta espécie na foz do Rio Amazonas pode ser significativo para auxiliar a esclarecer uma das hipóteses sobre a origem das raias de água doce(Potamotrygonidae).
REGISTRO DA OCORRÊNCIA DO TUBARÃO-DUENDE, Mitsukurina owstoni JORDAN, 1898 (LAMNIFORMES: MITSUKURINIDAE) NA REGIÃO NORTE DO BRASIL
Authors: Holanda Francisco Carlos A. Fonteles , Filho Mutuso Asano
Published: March 2024

O tubarão-duende, Mitsukurina owstoni Jordan, 1898, é uma espécie que habita águas profundas, raramente sendo vista ainda com vida. Pertence à família Mitsukurinidae, atinge até 4 m de  comprimento e é encontrado em zonas com até 1.200 m de profundidade. Para o desenvolvimento desta pesquisa, as pescarias foram realizadas na plataforma e no talude continental da região Norte do Brasil, com arrastos em profundidades entre 236 m e 1.246 m. As estações distribuídas nesta região estão entre as latitudes 01º23N e 05º09’N. As operações de arrasto de profundidade foramrealizadas em barcos de pesca, nos períodos agosto de 2002 a maio de 2003, e junho de 2003 a julho de 2004, tendo-se utilizado cinco diferentes tipos de rede. Entre as espécies de peixes cartilaginosos, em cinco lances realizados na costa norte, foram capturados seis exemplares do tubarão-duende. Entre o material coletado durante as pescarias e enviado para uma coleção ictiológica, constam 14 registros fotográficos com os respectivos dados da captura e um exemplar do tubarão-duende (o único da América do Sul).
An Exhaustive Examination of the Motor System’s Reliability in Electric Vehicles
Authors: Roy Dhanush , Kumar Chin Chun
Published: March 2024

Due to their unique zero carbon emission feature, electric vehicles (EVs) have garnered increasing interest in recent years. However, concerns persist regarding their reliability, particularly concerning critical components. Efforts have been made to assess the reliability of drive motors in EVs. Yet, given the integration of drive motors and motor controllers as a single system in EVs, a combined assessment is essential for a more accurate reliability prediction. Additionally, considering the multiple components within both drive motors and motor controllers, their structure, type, and characteristics may influence the overall reliability of the motor system, a factor overlooked in previous research. To bridge this knowledge gap, this study investigates the reliability of the entire motor system in pure electric vans, encompassing both drive motors and motor controllers. The research begins with predicting the theoretical failure rates of subassemblies and components within the drive motor and motor controller. Subsequently, based on these predictions, the reliability of the entire motor system is assessed. The findings highlight vulnerable subassemblies and components within the motor system, shedding light on potential shortcomings in existing reliability research. These new insights are deemed crucial for informing future reliability design and maintenance practices for pure electric vans. This study undertakes an exhaustive investigation into the reliability of the motor system in EVs. As EVs gain prominence for their environmental benefits and increasing market share, concerns regarding the reliability of critical components, such as the drive motor and associated control systems, become paramount. While prior research has addressed component-level reliability, this study takes a holistic approach by assessing the entire motor system. Through theoretical modeling and empirical analysis, the study predicts failure rates of subassemblies and components within the drive motor and control systems, culminating in an evaluation of the overall motor system reliability. By uncovering vulnerabilities and potential areas for improvement, this research offers valuable insights to advance the design, development, and maintenance of reliable electric vehicles.
Boletín Económico Regional : Costa Caribe, IV trimestre de 2023
Authors:   Departamento Técnico y de Información Económica,   Sección de Sucursales Regionales de Estudios Económicos
Published: March 2024

La economía de Caribe continuó mostrando una desmejora anual en el cuarto trimestre de 2023, con base en los resultados sectoriales de sus principales indicadores. La baja demanda interna y externa y los altos inventarios en la producción de alimentos y bebidas afectaron la industria. Paralelamente, las altas tasas de interés y el incremento de precios en algunos rubros desalentaron el gasto de los hogares, reflejado en los indicadores de comercio, turismo, transporte y construcción. Asimismo, las menores ventas de carbón, ferroníquel y manufacturas de aluminio, así como de compras de materias primas para la industria, incidieron en la caída del comercio exterior. En contraste, el aumento en los despachos de alimentos, sacrificio de ganado y acopio de leche fomentaron la actividad agropecuaria. Por último, la tasa de desempleo disminuyó en la mayoría de las ciudades de la región, aunque con una menor población dentro de la fuerza laboral, y la inflación continuó a la baja, con predominio de los alimentos.
Phases of human development: Comparing Western and Islamic theories and the implication in Islamic education
Authors: Mahmud Salami , Nurul Fajri Ulfah  , Syiva Fitria  , Fatmawati Fadli
Published: March 2024

The physical, cognitive, and socio-emotional development determine every aspect of human life, including education. Providing appropriate education for children is determined by the child's developmental stage. The current study aims to describe the stages of human development according to Western and Islamic concepts and their implications in Islamic education. To ensure a comprehensive investment in human beings, attention to religious education and introducing religious instruction from the prenatal stage is deemed necessary, as this period forms the foundation for further development. The research methodology employed in this study is a Systematic Literature Review (SLR). After reviewing various literature sources, the researchers selected several references that were relevant to the topic. The study's results indicate that the prenatal phase in Islamic psychology is more extended than Western psychology's. The tamyiz and amrad phases, viewed in Islamic psychology as preparations for entering adulthood, correspond to the Western psychological perspective of puberty. The futuh phase, or the phase of wisdom in Islamic psychology, occurs when a person ages 40, whereas Western psychology labels this as the adult phase. The phase of the Hereafter is considered crucial in Islamic psychology, while Western psychology lacks an afterlife phase. Consequently, Muslims undergo lifelong education from early birth to death. In conclusion, every phase of human life must be educated according to the level of maturity, starting from prenatal, infant, early childhood, school age, adolescent, young adult, mature adult, to late adult.
Системы вентиляции в зданиях промышленного назначения
Authors: Абдукаликова Гульнара , Апенов Асылбек
Published: March 2024

Системы вентиляции в зданиях промышленного назначения
Ұлттық өнердің танымдық қасиетінің ерекшеліктері
Authors: Самуратова Таттигуль
Published: March 2024

Ұлттық өнердің танымдық қасиетінің ерекшеліктері
Автоматты басқару жүйесінде негізделген бағдарламалық редакторларға шолу
Authors: Садыкова Жанна , Жұмабаев Атағали , Артықбаев Алмас
Published: March 2024

Автоматты басқару жүйесінде негізделген бағдарламалық редакторларға шолу
Использование графических редакторов при создании единого информационного пространства
Authors: Байдабеков Ауез , Янишевская Анна , Фомин Алексей
Published: March 2024

Использование графических редакторов при создании единого информационного пространства
Студенттің сабаққа қатысу деңгейін арттыру жолдары
Authors: Әбдірасілов Лесбек , Әбдірасілов Дулат , Қазмағамбетов Жәнібек
Published: March 2024

Студенттің сабаққа қатысу деңгейін арттыру жолдары
Влияние гранулометрического состава сырья на процессы получения золокерамических стеновых материалов
Authors: Бейсекеева Сайран , Жумагалиев Азамат
Published: March 2024

Влияние гранулометрического состава сырья на процессы получения золокерамических стеновых материалов
Білім берудің басты факторы-ақпараттық және коммуникациялық технологиялар
Authors: Бозтай Зәмзәгүл
Published: March 2024

Білім берудің басты факторы-ақпараттық және коммуникациялық технологиялар
Инфракрасное отопление - эффективное решение
Authors: Рывкина Наталья , Конарбаева Жанылган
Published: March 2024

Инфракрасное отопление - эффективное решение
Өнеркәсіптік ғимараттардың желдету жүйелері
Authors: Абдукаликова Гульнара , Жарасов Мурагер
Published: March 2024

Өнеркәсіптік ғимараттардың желдету жүйелері
Далалық өлшемдердің өндірісі бойынша ұсыныстар
Authors: Наурызбай Аманбек
Published: March 2024

Далалық өлшемдердің өндірісі бойынша ұсыныстар
"Тұрғын үйлер сәулеттік тұрпаттануы" пәнінің "сәулетші" мамандығын дайындаудағы алатын ғылыми-әдістемелік орны
Authors: Дүйсебай Есболат
Published: March 2024

"Тұрғын үйлер сәулеттік тұрпаттануы" пәнінің "сәулетші" мамандығын дайындаудағы алатын ғылыми-әдістемелік орны