bluuebunny/crossref_metadata_2025 huggingface dataset:
Atmospheric Dispersion Software Intercomparison Exercise and Sensitivity of Results
Authors: Salpadimos Nikos , Karfopoulos Konstantinos , Potiriadis Constantinos , Andronopoulos Spyros , Seimenis Ioannis
Published: August 2024

Abstract        The Greek Atomic Energy Commission (EEAE) is the national regulatory authority, competent for the control, regulation, and supervision in the fields of nuclear energy, nuclear technology, radiological and nuclear safety, and radiation protection. Within its mandate is to assess emergencies in or out of Greece, which may entail radiological risk for the country. To this end, studies based on atmospheric dispersion software, like JRodos, are performed [1]. To validate the performance of the software, EEAE recently participated in a JRodos intercomparison exercise. The exercise was conducted within the Rodos User Group (RUG), and was based on a hypothetical release from a nuclear icebreaker in Danish coastal waters.
This work further evaluates its results on the basis of their sensitivity in the parameter of the atmospheric dispersion models. To this end, three atmospheric dispersion models: RIMPUFF [2], LASAT [3], and DIPCOT [4], were applied. Their results were compared in different timesteps in terms of the effective gamma-dose rate at the height of 1 meter. It was found that results tend to differentiate immediately after the release due to the models’ different approaches. However, all models yield similar results at the later phases of the release.
αSPECT: Adaptation of existing radon detectors to deep-sea operation
Authors: Madesis Ioannis , Lagaki Varvara , Siltzovalis Georgios , Mertzimekis Theo J.
Published: August 2024

Among the naturally occurring radioactive materials (NORM), radon and its isotopes 222Rn and 220Rn, being the only gaseous products, have a significant role due to their unique transport properties and common chemical characteristics within the respective decay chains of uranium and thorium. Continuous monitoring of radon emissions has diverse applications in geosciences, including the potential for earthquake precursors and their association with changes in volcanic activity . In this work, we report on the development, testing, and characterization of a one-of-a-kind and innovative alpha radiation spectrometer known as αSPECT. RAMONES , a project funded by the EU H2020 FET Proactive program, aims to develop prototype instruments for continuous and in situ measurements of radioactivity, both natural and artificial, in the marine environment. These instruments will be deployed on a stationary benthic laboratory or on autonomous underwater gliders (AUG). This instrument, specifically designed for operation in the deep sea, will be hosted on the benthic laboratory. To ensure the suitability of αSPECT for deep-sea environments, the detector design is adapted to commercial cylindrical enclosures capable of withstanding harsh marine conditions. Through the deployment of αSPECT, we anticipate gaining insight into deep-sea geochemical processes related to radon emission and circulation. This includes the investigation of sediment-water interactions, water volume dynamics, and properties of submarine hydrothermal vents. Currently, αSPECT is undergoing development, and initial testing is scheduled to commence in the near future
Signatures of hadron-quark phase transition through the r-mode instability in twin stars
Authors: Laskos-Patkos Pavlos , Moustakidis Charalampos
Published: August 2024

The observation of two compact stars with equal mass but different radius (twin stars) would be a strong indication of hadron-quark phase transition in dense nuclear matter. In this work we examine the differences that appear in the r-mode instability windows and evolution of twin stars in order to investigate the possibility of identifying them through the future detection of gravitational waves. We find that two stars with an identical mass and fairly similar temperature and rotational frequency may behave differently with respect to the r-modes. Hence, the future possible detection of gravitational radiation due to unstable r-modes from a star appearing in the stable region of the frequency-temperature plane (which will be determined by the absence of gravitation wave emission from existing and future pulsar observations) would be a clear sign for the existence of twin stars. In addition, we examine the compatibility of current data from low mass x-ray binaries with the predictions from hybrid equations of state that support the existence of third stable branch of compact objects. We find that, depending on the energy density jump and the crust elasticity, hybrid equations of state may serve as a viable solution for the explanation of existing observations.
Αποτίμηση της Διαχείρισης της Στρατηγικής Έξυπνης Εξειδίκευσης 2014-2020 στην Ελλάδα: Συγκριτική Ανάλυση μεταξύ δύο Περιφερειών
Authors: Χρυσομαλλίδης Χαράλαμπος , Μουρδουκούτας Χρήστος
Published: August 2024

Το παρόν άρθρο εξετάζει την εφαρμογή της Στρατηγικής Έξυπνης Εξειδίκευσης στην Ελλάδα. Βασιζόμενο στην απόφαση της Ελλάδας να αναπτύξει στρατηγικές έξυπνης εξειδίκευσης τόσο σε εθνικό όσο και σε περιφερειακό επίπεδο, το άρθρο ερευνά το πώς η νέα αυτή πολιτική εφαρμόστηκε από τις/στις Περιφέρειες της χώρας και τις διαφορές που αναδεικνύονται μεταξύ τους. Χρησιμοποιώντας ως ερμηνευτικό πλαίσιο τη θεωρία των περιφερειακών συστημάτων καινοτομίας και προχωρώντας σε μία συγκριτική ανάλυση των Στρατηγικών Έξυπνης Εξειδίκευσης των Περιφερειών Πελοποννήσου και Δυτικής Ελλάδας, η παρούσα έρευνα προχωρά σε μία αποτίμηση της ανάπτυξης, της διαχείρισης, της εφαρμογής και των αποτελεσμάτων των Στρατηγικών. Η ανάλυση καταλήγει στο συμπέρασμα ότι οι περιφερειακές Στρατηγικές Έξυπνης Εξειδίκευσης, αν και παρουσίασαν αδυναμίες στην ανάπτυξη και υλοποίησή τους, συνέβαλαν στην αλληλεπίδραση τηςεπιχειρηματικής και ερευνητικής κοινότητας. Επίσης, μέσω της χρηματοδότησης στοχευμένων δράσεων διαφαίνεται ότι συνέβαλαν και στη βελτίωση των επιδόσεων καινοτομίας των Περιφερειών, ο οποίος όμως δεν είναι δυνατόν να εντοπιστεί επακριβώς με βάση τα έως τώρα διαθέσιμα δεδομένα.
A guide to selecting high-performing antibodies for human Midkine for use in Western blot and immunoprecipitation
Authors: Ayoubi Riham , Southern Kathleen , Laflamme Carl ,   NeuroSGC/YCharOS Collaborative Group
Published: August 2024

Midkine is a secreted protein that acts as a growth factor or cytokine involved in cell survival and inflammatory processes. It accumulates in amyloid plaques, which are hallmarks of Alzheimer’s Disease (AD). The reproducibility of Midkine research would be enhanced if the community had access to well-characterized anti-Midkine antibodies. In this study, we characterized 8 commercial Midkine antibodies for Western blot and immunoprecipitation, using a standardized experimental protocol based on comparing read-outs in a knockout cell line and isogenic parental control. These studies are part of a larger, collaborative initiative seeking to address the antibody reproducibility issue by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.
Demographic status and training needs of aesthetic plastic surgeons in government and private hospitals: evidence from Guangdong, China
Authors: Yi Yanhua , Wang Zhifeng , Hu Guijie , Zhao Shiwei , Li Yongbin , Chen Bo , Xiang Zhen , Zhang Qiaojun , Lu Wei , Liu Jian , Xue Yongping , Li Hongmian , Wu Cimin , Shi Wuxiang , Gong Zhenyu
Published: August 2024

Purpose: This study aims to survey the demographic status of aesthetic plastic surgeons in an economically developed region and to investigate their continuing training needs in contents, training methods, and barriers in private and government hospitals.   Methods: A cross-sectional survey with a self-administered questionnaire was conducted from January to December, 2022 in Guangdong, China. In-depth interviews were conducted with key informants to gain insights on the current demographic status. Demographic data and training needs assessment were collected and compared with the chi-square test, Fisher’s test, Mann-Whitney U-test using R software. Results: The disparity of surgeons’ demographic data between private and government hospitals was small. Over 60% of practicing aesthetic plastic surgeons transferred from other specialties, and one third of them had less than three years of working experience. Half of surgeons attended training less than three times with an affordable expense of 1000-5000RMB. Almost 80% of them had strong willingness to attend a continuing training program. They prefer to attend further study in a tertiary hospital, with a short topic-focused training course and operation demonstrations. Their favorable training contents were rhinoplasty, eye surgery, and new technologies. Our questionnaire survey revealed the likelihood that the surgeons had a graduate degree in government hospitals outweighed those in private hospitals (P<0.05). Results also showed that the government hospitals focused more on repair and reconstructive surgery and academic research, whereas, private hospitals focused on market needs and were more profit-driven, where the organizational needs had influence on their different training needs for aesthetic plastic surgeons. Conclusion: It would be favorable to take the demographic status of aesthetic plastic surgeons and organizational needs into consideration in designing a continuing training program in plastic surgery.
Time to sense biofield (Prana) experiences between hands: A preliminary single blinded randomized placebo controlled trial
Authors: Vijayakumar Vinu , Nagaraja Jois Srikanth , Mallikarjuna Majgi Sumanth , Prasad Krishnamurthy Nagendra , Nanjunda swamy Roopa
Published: August 2024

Aims There is minimal research on the duration of biofield experiences. This preliminary study used the experiential learning practice of Master Choa Kok Sui's hands sensitisation to determine the duration to experience biofield sensations in between hands and to find the relationship between learning style preferences and biofield sensations. Methods This randomized placebo controlled, single blinded trial included 88 male and female pre-service teachers, aged 22.8±1.2 years. Participants completed a ruler drop test for reaction time, and Six Letter Cancellation test for measuring attention, learning style questionnaire for preferred method of learning, before randomization. The experimental (hands facing each other as introduced by Master Choa Kok Sui) and sham (hands facing opposite) groups practiced hands sensitisation. A semi-structured questionnaire was provided to gather information about biofield sensations and the time it took to experience these sensations between the hands. Results All (N=44) the participants in the experimental group and 13 participants in the sham group reported experiencing biofield sensations. A significant difference was noticed in experiencing magnetic (X2 = 38.247, p ≤ .001), physical sensations of energy (X2 = 12.02, p ≤ .001) and pain (X2 = 62.259, p ≤ .001) among the experimental and sham group . In the experimental group, the average time taken to first experience magnetic sensation, other biofield sensations and temperature variation was 34.84±12.97seconds, 40.28±20.96 seconds and 42.50±19.79 seconds, respectively. Minimum time taken to first experience biofield sensation was 5 seconds and lasted up to study duration of 120 seconds. There was no correlation found between reaction time, sustained attention, and the time needed to experience biofield sensations. Conclusions This study highlights importance of Master Choa Kok Sui hand sensitization in controlled setting revealing differences in experiences of various biofield sensations, showing valuable time-related insights and variability of sensation based on preferred learning.
Hand clasping induced thermogenesis and heart rate variability
Authors: Subudhi Debadutta , Routray Prasanna K. , Manivannan M , Deepak K K
Published: August 2024

Background Heat induced by thermogenesis is an essential therapeutic intervention in medical practice. Moreover, thermogenesis improves the innate immune response. This study focuses on hand-clasping with a raised thumb (HCRT) as a thermogenic source and its effect on heart rate variability (HRV). Methods The study analyzed the ECG, thermal images of the upper body, axillary temperature, and breath exergy of 15 participants. The metabolic effect of thermogenesis is an important factor in type II diabetes mellitus (type II DM). Therefore, the clinical application included recording capillary blood glucose of 12 type-II DM subjects before and after the HCRT intervention. Results The mean axillary temperature slope increased by 11.5 %. The spatial change in temperature gradient (∇2T) at hot and cold spots also slightly increased by 3.42 % and 2.53 %, respectively. HRV improved as the VLFHF ratio decreased significantly (p < 0.05) by 52.62 %. The very low frequency (VLF) component of HRV has a relationship to thermoregulation, which is reflected through a significant increase (p < 0.05) of 41.7 % for the power under sub-VLF at 0.0327-0.04 Hz during HCRT. The spot width (SW), range, and norm of ∇2T reduces insignificantly during HCRT. There was a significant (p < 0.001) increase in the exhaled temperature by 0.5 ° C in both nostrils during 1st phase of HCRT. The standard deviation of exergy in the right nostril showed a significant increase (p < 0.05) of 72.72 % during HCRT. The Clinical tests showed a significant reduction (p < 0.001) of 24.14 % in capillary blood glucose (CBG) after HCRT. Conclusions HCRT aids in thermogenesis with higher exergy and HRV owing to a significant reduction in the VLFHF ratio.
Enhancing Academic Success: A mixed Study on the Influencing Factors among Pharmacy Students in Syrian Universities
Authors: Qattan Mohab , Dashash Mayssoon , S. Malek Zeina
Published: August 2024

Background Academic achievement is the result of both effort and perseverance exerted by the students. This mixed-methods study aims to investigate the factors affecting the academic achievement of pharmacy students in Syrian universities. Methods A convergent parallel mixed-methods study was utilized. In the quantitative phase, a cross-sectional study was conducted on 1008 students (773 females and 235 males) from 23 Syrian universities. A questionnaire consisting of 48 items was designed to be completed by pharmacy students using a 5-point Likert scale. In the qualitative phase, twelve questions were developed to interview thirty pharmacy students from five Syrian universities to obtain in-depth insights into the factors influencing their academic achievement. Results A significant number of students lacked effective time management skills, identified as a weakness among students. The majority of students faced challenges in maintaining a consistent study routine, averaging a score of (2.0). Motivation towards learning emerged as a crucial factor in enhancing academic performance. Lecturers in the pharmacy faculty employed traditional teaching methods (2.01), and the pharmacy curriculum was perceived as lacking modernity (1.92). Quantitative findings demonstrated that pharmacy students experienced exam-related anxiety (2.05), identified as a weakness in the qualitative phase. Factors associated with the Syrian crisis, like unreliable electricity (1.87) and transportation issues (1.83), could have an impact on academic achievement. Economic conditions were identified as challenging to students’ academic performance, negatively affecting the learning process (1.98). Conclusion The results of the study demonstrate that personal factors, lecturers, educational environment, exams, and the Syrian crisis influence the academic achievement of pharmacy students in Syrian universities.
Protocol for the systematic review of age and sex in preclinical models of age-correlated diseases
Authors: Diederich Kai , Steinfath Matthias , Bannach-Brown Alexandra , Bert Bettina , Butzke Daniel , Wildner Paul Lucas , Wurm Maximilian , Schadock Ines , Heinl Céline
Published: August 2024

The translation of animal-based biomedical research into clinical research is often inadequate. Maximizing translation should be central to animal research on human diseases, guiding researchers in study design and animal model selection. However, practical considerations often drive the choice of animal model, which may not always reflect key patient characteristics, such as sex and age, impacting the disease's course. Despite diseases affecting both sexes, researchers frequently use male mice. To address this imbalance, journals and funding agencies have begun questioning the sex of animals used in studies and issued new guidelines. Conversely, the age of rodents is rarely discussed, even though many diseases primarily affect older patients. Young mice are commonly used, even in studies of diseases affecting older adults. Systematic comparisons between the age of rodents used and the age of patients in clinical trials are lacking. In this review, we systematically analyze the age and sex of mice used to model the five leading causes of global disability-adjusted life-years over the age of 75. We compare the results with the age and sex of patients in clinical trials focusing on Alzheimer's disease, stroke, type 2 diabetes mellitus, ischemic heart disease, and chronic obstructive pulmonary disease. We also analyze whether the age of the mice used has changed over the past decade. By systematically assessing the age and sex of the mice, we aim to initiate a discussion on the appropriate choice of animal model to improve the translatability of research results.
Social vectors and body-biographical itineraries: Indigenous students’ health in the diaspora space in Brazilian universities
Authors: Afonso da Silva Rafael , Shirley Lelis Andrade Hellen , Natalice Vilharva Kellen , Maia Barbosa Mariane , Prado Arantes Tatiane , de Castro e Silva Ricardo , Figueiredo da Silva Geovane , Soares Assis Érica , Fabrini M. Almeida Verônica , da Silva Lopes Vanessa , Oliveira Galvão da Silva Yurica , Castro Andrade Joelson , Filice de Barros Nelson
Published: August 2024

The presence of Indigenous students in the university is a very recent event in the Brazilian academic culture. Their presence produces intercultural borders in the diaspora space in universities. This article analyzed the health production of Indigenous students in the universities’ diaspora space, considering dynamics in which social vectors and body-biographical itineraries intersect. The qualitative project adopted the co-labor principles and the technique of semi-structured interviews. A total of 13 interviews were carried out, recorded in audio and video, with Indigenous students, conducted by Indigenous researchers participating in the project. The transcription and analysis of information took place co-laboratively. The experience of Indigenous students in the university diaspora is a complex process that involves immersion in new physical, cultural, political and social climates. These experiences involve multiple dimensions that affect health, requiring the reinstitution of its margins, in the production of new forms of resistance, both physiological and emotional, affective, social, and political. Racism, with different degrees of intensity and in different forms, permeates these experiences, which vary, in each case, due to: (1) the social, cultural, and political climate of the place of origin; (2) the intersection of social markers of difference, such as gender, age and phenotypic characteristics; and (3) the differences between academic environments. To the same extent that racism is perceived and evaluated by Indigenous students as one of the main pathogenic factors in the university’s diaspora space, the construction of “Indigenous identity” is perceived as a general resource of resistance and health production. We conclude that the reinstitution of the conditions and possibilities for the production of healthy subjectivities and collectivities at the university depends on the pluri-ethnic and pluri-epistemic refounding of the academic space, which must be carried out with and not for Indigenous students.
ML-CSFR: A Unified Crop Selection and Fertilizer Recommendation Framework based on Machine Learning
Authors: Bhola Amit , Kumar Prabhat
Published: August 2024

Sustainable and substantial crop production is essential globally, especially considering the increasing population. To achieve this, selecting appropriate crops and applying necessary fertilizers are pivotal for ensuring satisfactory crop growth and productivity. Farmers have relied heavily on intuition when choosing which crops to cultivate and suitable fertilizers to use in a given season. However, this traditional approach often needs to consider the significant impact of current environmental and soil conditions on crop growth and yield. Overlooking these factors can have far-reaching consequences, impacting not just individual farmers and their households but also the entire agricultural sector. The integration of machine learning offers a promising avenue for addressing these challenges and providing practical solutions. The core contribution of this research lies in proposing a unified framework termed Machine Learning-enabled Crop Selection and Fertilizer Recommendation (ML-CSFR). This framework’s primary objective is to predict appropriate crops accurately and subsequently suggest corresponding fertilizers based on specific agricultural conditions. The initial phase involves the identification of proper crops for individual farmlands, considering local input variables. This phase employs artificial neural networks (ANN) to filter crops effectively using the available choices. The next phase utilizes soil and environmental parameters to anticipate the optimal fertilizer for the selected crops. This phase leverages the XGBoost (XGB) model to predict the most suitable fertilizers accurately. This two-phase approach ensures a comprehensive and effective recommendation system for enhancing agricultural outcomes. Experimental results demonstrate the effectiveness of this framework, achieving an accuracy score of 99.10% using ANN and 97.66% for XGB. The framework's capability to deliver tailored recommendations for individual farms and its potential to integrate real-time sensor data positions it as an effective tool for improving agricultural decision-making.
A Hybrid Image Fusion and Denoising Algorithm based on Multi-scale Transformation and Signal Sparse Representation
Authors: Sheng Dajun
Published: August 2024

In response to the problem of denoising in image fusion, the author proposes a hybrid image fusion and denoising algorithm based on multi-scale transformation (MLT) and signal sparse representation (SRS). A hybrid model is constructed for shear transformation, and the coefficients after MLT decomposition are thresholded. Sliding window technology and translation invariance are used to form sparse representation for image fusion, and SRS algorithm is used to remove noise from the source image. The experimental results show that the algorithm reduces the contrast and spectral information distortion of the fused image, displays high-quality visual fusion effects, maintains high PSNR values under different noise levels, can provide a more complete description of the features in the image, accurately judge the focus area, maintain the structural correlation of the image, and strengthen the description of fusion edges and details in the fused image. It has been proven that the methods of multi-scale transformation and sparse signal representation can fuse and denoise images.
High-resolution Holographic Image Reconstruction Based on Deep Learning
Authors: Li Fangju
Published: August 2024

Aiming at the shortcomings of existing holographic reconstruction algorithms, which are complex and easily affected by noise, this project proposes a semantic partitioning U-Net for high-resolution reconstruction. Firstly, a method based on the edge-neural network is proposed to obtain more image semantic information and improve the model training effect. Secondly, the effective channel attention mechanism of deep neural networks is introduced to enhance the attention to the detailed information in the holographic image. This further improves the accuracy of the neural network. The convergence rate of the neural network is accelerated by introducing a linear element with leakage correction. Experimental results show that this method can quickly reconstruct phase and brightness images with better detail, better edge texture and flat background. Holographic images of various sizes can be reproduced. The research of this project will lay a foundation for applying holographic image enhancement technology based on deep learning.
High Speed Low Power Analysis of 12 Transistors 2×4 line Decoder using 45GPDK Technology
Authors: Javvadi Sruthi Pavani , Hanuman C R S , Parasa Sivadurgarao , Naraganeni Sannajah
Published: August 2024

This paper proposes the high speed low power analysis of 12 transistors 2×4 Low Power (LP) and Low Power Inverting (LPI) Decoders by using Dual Value Logic (DVL) and Complementary Metal Oxide Semiconductor (CMOS) Logic. A huge challenge faced by this era of developing is power reduction. The LP circuit design is a requesting issue in high performance digital frameworks, for example, microchips, DSPs and other different applications. Power and speed are the main highlights considered while comparing any design. Diminishing chip area is additionally truly impressive factor, designers need to recall when suggesting any novel design. 2×4 LP and LPI Decoders using 12T (Transistor) is used for conversion of binary inputs to associated output bits in a pattern. A novel design (CMOS logic and DVL logic) of 2×4 LP and LPI Decoders using 12T is proposed with area optimization, LP and high speed in this paper. Delay and power is evaluated between the novel design and CMOS logic. The novel design of 12T LP and LPI 2×4 Decoders is 60.72% optimized for power in contrast to CMOS logic design at a typical value of 1.8V. The proposed method has been validated using Cadence 45 GPDK (Generic Product Design Key) Virtuoso Tool.
Deep Learning Model Construction of Urban Planning Image Data Processing and Health Intelligence System
Authors: Xu Can
Published: August 2024

In order to study the deep learning model of urban planning image data processing and health intelligent system, based on existing remote sensing image change detection methods, the author introduces and proposes the use of deep belief networks in deep learning to classify high-resolution remote sensing images and analyze urban expansion change detection. Compared with traditional methods, deep learning has the highest overall accuracy and Kappa coefficient. Deep learning has the highest producer accuracy and relatively low misjudgment rate, making it the most suitable for studying the trend of urban built-up areas. By calculating the information entropy of the image to predict the number of hidden layer nodes, the time for deep learning is greatly reduced. Under the same experimental conditions, the training time for each image can be shortened by 12 525 seconds has improved classification efficiency and made a significant contribution to research on urban expansion applications. Finally, the improved deep belief network was applied to classify and detect changes in the three phase remote sensing images of Beijing, and the urban expansion trend and characteristics of Beijing were analyzed. Provide technical reference and inspiration for urban planning and land use protection.
The Construction and Application of Residential Building Information Model Based on Deep Learning Algorithms
Authors: Zhao Shuang , Yang Yu
Published: August 2024

In order to explore the construction and application of building BIM models, the construction industry is actively exploring a method that can quickly reshape the 3D information model of existing buildings in the wave of digital twins and smart cities. Starting from the perspective of deep learning 3D object detection algorithms, the author starts with the generation of large-scale building datasets and the theory of point cloud deep learning, analyzes the input data types required for point cloud deep learning frameworks, and focuses on the creation process of 3D bounding boxes and 3D point clouds for various building components. The author compares different point cloud datasets with the same data structure and implements an object detection algorithm based on the ScanNet dataset, furthermore, a feasible technology route for automatic generation of BIM models from 3D point clouds based on deep learning is integrated. Through this technology route, the trained neural network can input unknown building 3D point clouds and output BIM model parameters.
Research on the Influencing Factors of Commercial Pension Insurance for Rural Residents in the Context of Population Aging Based on Big Data Analysis
Authors: Feng Shitang
Published: August 2024

Data Pension Explorer (DAPE) introduces an innovative approach to delve into the intricacies of commercial pension insurance adoption within rural communities in China, particularly amid the challenges posed by an aging population. Leveraging advanced Deep Long Short-Term Memory (LSTM) techniques within the domain of big data analysis, this study pioneers the analysis of extensive datasets. It systematically unravels intricate patterns, correlations, and pivotal determinants shaping the landscape of pension insurance adoption in rural areas. Going beyond conventional analyses, this research provides a nuanced understanding of the multifaceted factors influencing both the sustainability and uptake of pension insurance. The culmination of these efforts yields valuable insights that extend beyond the theoretical realm, directly informing strategic decision-making processes. These insights prove instrumental in designing and implementing policies tailored to address the unique challenges faced by rural communities in China. Thus, DAPE not only navigates the complexities of population aging but also serves as a guiding force in fostering widespread adoption and sustainability of pension insurance within rural landscapes in the Chinese context.
Optimization of Weighting Algorithm in Enterprise HRMS based on Cloud Computing and Hadoop Platform
Authors: Zhao Genliang
Published: August 2024

As enterprises increasingly rely on cloud-based Human Resource Management Systems (HRMS) deployed on the Hadoop platform, the optimization of weighting algorithms becomes imperative to enhance system efficiency. This paper addresses the complex challenge of load balancing in the cloud environment by proposing Effective Load Balancing Strategy (ELBS) a hybrid optimization approach that integrates both Genetic Algorithm (GA) and Grey Wolf Optimization (GWO). The optimization objective involves the allocation of N jobs submitted by cloud users to M processing units, each characterized by a Processing Unit Vector (PUV). The PUV encapsulates critical parameters such as Million Instructions Per Second (MIPS), execution cost α, and delay cost L. Concurrently, each job submitted by a cloud user is represented by a Job Unit Vector (JUV), considering service type, number of instructions (NIC), job arrival time (AT), and worst-case completion time (wc). The proposed hybrid GA-GWO aims to minimize a cost function ζ, incorporating weighted factors of execution cost and delay cost. The challenge lies in determining optimal weights, a task addressed by assigning user preferences or importance as weights. The hybrid algorithm iteratively evolves populations of processing units, applying genetic operators, such as crossover and mutation, along with the exploration capabilities of GWO, to efficiently explore the solution space. This research contributes a comprehensive algorithmic solution to the optimization of weighting algorithms in enterprise HRMS on the cloud and Hadoop platform. The adaptability of the hybrid ELBS to dynamic cloud environments and its efficacy in handling complex optimization problems position it as a promising tool for achieving load balancing in HRMS applications. The proposed approach provides a foundation for further empirical validation and implementation in practical enterprise settings.
Research on the Design of a System based on Machine Learning Algorithms for Automatic Scoring of English Writing Ability
Authors: Zhao Shan
Published: August 2024

The development and implementation of an innovative system designed to automatically score English writing ability using advanced machine learning algorithms is challenging task. The core objective of the study is to establish a reliable and efficient method for assessing written English, which is crucial in educational and professional settings. The paper begins with an overview of the existing methods of English writing assessment, highlighting their limitations, such as time consumption and potential biases in human evaluation. The main focus of the study is the design and testing of a machine learning-based system. Various algorithms, including Natural Language Processing (NLP) techniques and neural network models, are explored and integrated to assess writing quality, grammar, coherence, and content relevance. The system’s architecture is detailed, explaining how these algorithms work in tandem to evaluate and score writing. An experimental setup is described where the system is trained and validated using a large dataset of English writing samples, ranging from beginner to advanced levels. The performance of the system is measured against traditional scoring methods, with emphasis on accuracy, consistency, and the ability to handle diverse writing styles and complexities. The results demonstrate the system’s proficiency in accurately scoring English writing, with a notable reduction in scoring time compared to human evaluators. The paper discusses the implications of these findings for educational institutions and language testing organizations, suggesting that this system could revolutionize how English writing is assessed.
The Application of Intelligent Welding Robots and Visual Detection Algorithms in Building Steel Structures
Authors: Zhang Wei , Li Junhua
Published: August 2024

In order to understand the application of welding robots in building steel structures, the author proposes a research on the application of intelligent welding robots in building steel structures. The author first analyzed the characteristics of complex and diverse structural forms of building steel structure components, small batches, no repetitive components, diverse welding joint forms, low precision of components and assembly control, and proposed specific requirements for the application of intelligent welding robots, such as fast programming to meet diverse structural forms, rich and powerful welding process databases, and high adaptability to parts and assembly deviations. Secondly, it is described that existing welding robots have mature contact sensing and arc tracking functions, have offline programming software, and can achieve thick plate groove welding. They already have the technical foundation to achieve automatic welding in building steel structural components. Finally, combined with practical cases, taking a commercial building project as an example, the construction land area is 31689m2, using Q460GJC steel, with a maximum plate thickness of 100mm, the steel structure includes extended arm honing frame, radial separation frame, ring separation frame, and other contents, and is connected to the core tube as a whole. Describe the application content and methods of robot technology in the manufacturing of building steel structures, including parameter selection, programming methods, welding processes, and more. In order to achieve the goal of automatic welding of building steel structure robots. According to the application results, compared with traditional manual welding, intelligent Robot welding welding has higher efficiency and better quality, which is worth popularizing and applying comprehensively. Comprehensive comparative analysis, compared with manual welding, intelligent Robot welding has the advantages of higher efficiency and more stable quality, and has the technical conditions for comprehensive promotion.
Workforce Scheduling with Heterogeneous Time Preferences: Effective Wages and Workers’ Supply
Authors: Besbes Omar , Goyal Vineet , Iyengar Garud , Singal Raghav
Published: August 2024

Problem definition: Motivated by the debate around workers’ welfare in the gig economy, we propose a framework to evaluate current practices and possible alternatives. We study a setting in which customers seek service from workers and a platform facilitates such matches over the course of the day. The platform allocates time slots to workers using an allocation policy, and the workers are strategic agents (with respect to “when to work”) who maximize their expected utility that depends on their preferred times to work, the allocated slots, and the total availability time. The platform seeks to ensure that a sufficient number of workers is available to satisfy demand, whereas the workers aim to maximize their wage-driven utility. Methodology/results: We evaluate policies on two dimensions critical to any firm: the supply of workers across the day, and the effective wages of workers. We illustrate that several families of currently deployed policies have serious limitations. We find these limitations exist because the policies do not let workers fully express their preferences and/or cannot account for heterogeneity in such preferences. We propose a new allocation policy and establish strong performance guarantees with respect to both the workers’ supply and effective wages. The policy is simple and fully leverages the market information to reach better market outcomes. We supplement our theory with numerical experiments in the context of ride-hailing calibrated on various New York City data sets that illustrate performance across a range of markets. Managerial implications: We highlight a fundamental inefficiency of policies currently deployed that limit workers’ ability to express their preferences. By allowing workers to express their temporal preferences, and by judiciously prioritizing “full-time” workers over “part-time” workers, we can obtain a potentially significant Pareto improvement, maintaining (or even increasing) workers’ supply while increasing their effective wages.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0414 .
Transforming midwifery care
Authors: Oshiyemi Ayoola , Majérus Zoé Chantreau
Published: August 2024

WONDER Foundation has trained 13 women in the Democratic Republic of Congo, the country's first midwives to meet international standards, enabling high-quality, woman-centred maternity care
Midwifery students' experiences of learning to be ‘with woman’: a scoping review
Authors: Guerin Ashlee , Geraghty Sadie , McChlery Sheena , Byrne Mary
Published: August 2024

Background/Aims

Being ‘with woman’ is a fundamental concept of midwifery and profoundly impacts maternal and infant wellbeing and outcomes. Understanding student midwives' experiences is vital in shaping learning strategies for positive and effective student-centred learning outcomes. This scoping review's aims were to gain meaningful insight into existing literature on students' experiences of learning to be ‘with woman’.

Methods

The scoping review searched the CINAHL, PubMed, AusHealth, Medline and PsycInfo databases in July 2023, October 2023 and April 2024. The search included qualitative and quantitative research studies published in English between 2018 and 2024. Articles were screened for eligibility by title, abstract and full-text review by three reviewers.

Results

A total of 1172 articles were screened, with nine articles included in the review from various countries. Key themes identified were ‘continuity of care’, ‘partnership with woman’, ‘preceptor and practitioner impact’ and ‘context and contrast’.

Conclusions

Limited literature exists to explore and provide an understanding of the learning experiences and outcomes of midwifery students providing woman-centred care and developing a midwifery philosophy to be ‘with woman’.
Proximal humeral fractures with vascular compromise
Authors: Kriechling Philipp , Whitefield Reiss , Makaram Navnit S. , Brown Iain D. M. , Mackenzie Samuel P. , Robinson C. M.
Published: August 2024

Aims

Vascular compromise due to arterial injury is a rare but serious complication of a proximal humeral fracture. The aims of this study were to report its incidence in a large urban population, and to identify clinical and radiological factors which are associated with this complication. We also evaluated the results of the use of our protocol for the management of these injuries.

Methods

A total of 3,497 adult patients with a proximal humeral fracture were managed between January 2015 and December 2022 in a single tertiary trauma centre. Their mean age was 66.7 years (18 to 103) and 2,510 (72%) were female. We compared the demographic data, clinical features, and configuration of those whose fracture was complicated by vascular compromise with those of the remaining patients. The incidence of vascular compromise was calculated from national population data, and predictive factors for its occurrence were investigated using univariate analysis.

Results

A total of 18 patients (0.5%) had a proximal humeral fracture and clinical evidence of vascular compromise, giving an annual incidence of 0.29 per 100,000 of the population. Their mean age was 68.7 years (45 to 92) and ten (56%) were female. Evidence of a mixed pattern neurological deficit (brachial plexus palsy) (odds ratio (OR) 380.6 (95% CI 85.9 to 1,685.8); p < 0.001), complete separation of the proximal shaft from the humeral head with medial displacement (OR 39.5 (95% CI 14.0 to 111.8); p < 0.001), and a fracture-dislocation (OR 5.0 (95% CI 1.6 to 15.3); p = 0.015) were all associated with an increased risk of associated vascular compromise. A policy of reduction and fixation of the fracture prior to vascular surgical intervention had favourable outcomes without vascular sequelae.

Conclusion

The classic signs of distal ischaemia are often absent in patients with proximal injuries to major vessels. We were able to identify specific clinical and radiological ‘red flags’ which, particularly when present in combination, should increase the suspicion of a fracture with an associated vascular injury, and facilitate early diagnosis and appropriate combined orthopaedic and vascular intervention.

Cite this article: Bone Joint J 2024;106-B(8):842–848.
Adjacent venous tumour thrombus in primary osteosarcoma of the pelvis and limbs
Authors: Broida Samuel E. , Sullivan Mikaela H. , Rose Peter S. , Wenger Doris E. , Houdek Matthew T.
Published: August 2024

Aims

Venous tumour thrombus (VTT) is a rare finding in osteosarcoma. Despite the high rate of VTT in osteosarcoma of the pelvis, there are very few descriptions of VTT associated with extrapelvic primary osteosarcoma. We therefore sought to describe the prevalence and presenting features of VTT in osteosarcoma of both the pelvis and the limbs.

Methods

Records from a single institution were retrospectively reviewed for 308 patients with osteosarcoma of the pelvis or limb treated between January 2000 and December 2022. Primary lesions were located in an upper limb (n = 40), lower limb (n = 198), or pelvis (n = 70). Preoperative imaging and operative reports were reviewed to identify patients with thrombi in proximity to their primary lesion. Imaging and histopathology were used to determine presence of tumour within the thrombus.

Results

Tumours abutted the blood vessels in 131 patients (43%) and encased the vessels in 30 (10%). Any form of venous thrombus was identified in 31 patients (10%). Overall, 21 of these thrombi were determined to be involved with the tumour based on imaging (n = 9) or histopathology (n = 12). The rate of VTT was 25% for pelvic osteosarcoma and 1.7% for limb osteosarcoma. The most common imaging features associated with histopathologically proven VTT were enhancement with contrast (n = 12; 100%), venous enlargement (n = 10; 83%), vessel encasement (n = 8; 66%), and visible intraluminal osteoid matrix (n = 6; 50%). Disease-specific survival (DSS) for patients with VTT was 95% at 12 months (95% CI 0.87 to 1.00), 50% at three years (95% CI 0.31 to 0.80), and 31% at five years (95% CI 0.14 to 0.71). VTT was associated with worse DSS (hazard ratio 2.3 (95% CI 1.11 to 4.84).

Conclusion

VTT is rare with osteosarcoma and occurs more commonly in the pelvis than the limbs. Imaging features suggestive of VTT include enhancement with contrast, venous dilation, and vessel encasement. VTT portends a worse prognosis for patients with osteosarcoma, with a similar survivability to metastatic disease.

Cite this article: Bone Joint J 2024;106-B(8):865–870.
Outcomes after hip fracture surgery in patients receiving non-steroidal anti-inflammatory drugs alone, acetaminophen alone, or both
Authors: Hatano Masaki , Sasabuchi Yusuke , Ishikura Hisatoshi , Watanabe Hideaki , Tanaka Takeyuki , Tanaka Sakae , Yasunaga Hideo
Published: August 2024

Aims

The use of multimodal non-opioid analgesia in hip fractures, specifically acetaminophen combined with non-steroidal anti-inflammatory drugs (NSAIDs), has been increasing. However, the effectiveness and safety of this approach remain unclear. This study aimed to compare postoperative outcomes among patients with hip fractures who preoperatively received either acetaminophen combined with NSAIDs, NSAIDs alone, or acetaminophen alone.

Methods

This nationwide retrospective cohort study used data from the Diagnosis Procedure Combination database. We included patients aged ≥ 18 years who underwent surgery for hip fractures and received acetaminophen combined with NSAIDs (combination group), NSAIDs alone (NSAIDs group), or acetaminophen alone (acetaminophen group) preoperatively, between April 2010 and March 2022. Primary outcomes were in-hospital mortality and complications. Secondary outcomes were opioid use postoperatively; readmission within 90 days, one year, and two years; and total hospitalization costs. We used propensity score overlap weighting models, with the acetaminophen group as the reference group.

Results

We identified 93,018 eligible patients, including 13,068 in the combination group, 29,203 in the NSAIDs group, and 50,474 in the acetaminophen group. Propensity score overlap weighting successfully balanced patient characteristics among the three groups, with no significant difference in in-hospital mortality rates observed among the groups (combination group risk difference 0.0% (95% CI -0.5 to 0.4%); NSAIDs group risk difference -0.2% (95% CI -0.5 to 0.2%)). However, the combination group exhibited a significantly lower risk of in-hospital complications than the acetaminophen group (risk difference -1.9% (95% CI -3.2 to -0.6%)) as well as a significantly lower risk of deep vein thrombosis (risk difference -1.4% (95% CI -2.2 to -0.7%)). Furthermore, total hospitalization costs were higher in the NSAIDs group than in the acetaminophen group (difference USD $438 (95% CI 249 to 630); p < 0.001). No significant differences in other secondary outcomes were observed among the three groups.

Conclusion

The combination of acetaminophen with NSAIDs appears to be safe and advantageous in terms of reducing in-hospital complications.

Cite this article: Bone Joint J 2024;106-B(8):849–857.