bluuebunny/crossref_metadata_2025 huggingface dataset:
The Integration of Personalized Training Program Design and Information Technology for Athletes
Authors: Hao Penghui , Qian Kun
Published: August 2024

In order to integrate the training of athletes with information technology, this paper proposes a method for evaluating the performance of athletes using training technology. HR, O2, and hemoglobin were selected as input vectors of SVM, and the corresponding values were used as outputs to generate the training model. Adjust the support vector machine to minimize measurement error based on the learning objective. Support vector machines are used to study training patterns and develop model to evaluate athletes’ performance. College athletes were taken as research subjects and the effects of training were examined in five sports: football, basketball, basketball, swimming, and running. The results show that the relative error of this type is less than 1 when measuring the performance of various sports subjects; Relative errors in measuring the academic performance of athletes in various sports using physical fitness standards and sport-specific skills 1. The proposed model proves that the athlete’s training index is incorrect and has a useful application.
Intelligent Algorithm Operation and Data Management of Electromechanical Engineering Power Communication Network based on the Internet of Things
Authors: Li Ying , Qu Wenjing , Zhang Zhenqiang
Published: August 2024

With the rapid development and gradual popularization of Internet of Things technology, it is necessary to provide necessary Operation and Maintenance (O&M) services and data control for electromechanical engineering to maintain the normal function of the power system. This paper does the following research to carry out orderly and standardized management of related communication resources in power communication networks, conduct closed-loop and process-oriented management of communication O&M work, and ensure the safe, stable, and economical operation of power grids in electromechanical engineering. Firstly, the technology selection, algorithm implementation, solutions, and other related technologies that may be used in the platform design and implementation process are introduced and selected. Secondly, the research and call logic of the design and implementation of related algorithms for intelligent O&M are introduced. It includes the design and implementation of anomaly detection algorithms to monitor equipment health status and the design and construction of fault diagnosis algorithms for abnormal analysis. Finally, the simulation experiment of the proposed processing scheme is carried out on the Mininet simulation network to prove that the proposed scheme can provide a better anonymization effect when introducing low latency. The results show that the design of the gateway system realizes the module applications of the system, such as user, data storage, O&M, and fault management. Based on the technical selection, the algorithm is implemented and optimized, and the call logic of the algorithm is implemented in the O&M module. Simulation verifies that the anonymization algorithm can complete the mapping without introducing an additional delay of more than 3%.
Research on Power Line Communication Based on Deep Learning for Electromechanical Equipment Electricity Acquisition Terminals
Authors: Qi Chengfei , Yang Xiaobo , Yang Xiaokun , Bi Chaoran , Li Wenwen
Published: August 2024

The purpose is to use power line communication technology to re-optimize the power acquisition terminals of electromechanical equipment and improve the efficiency of information acquisition and management of the system grid. This paper analyzes the power and signal composite modulation mode of power line data communication in distributed power grids. Combined with the topology of the communication network in the power transmission process, the management mode of integration of power lines and wireless communication equipment is redesigned. Firstly, the characteristics of power line communication and wireless channel are analyzed. Aiming at the problem that most communication network operators use the fixed relay for communication, the main network communication mode is selected for optimization. Then, the information fusion method is adopted to integrate the network structure of the enterprise, network, and physical layer. The management of wireless communication equipment is carried out by reasonably allocating power resources. Additionally, the structure of the power acquisition terminal model is designed based on strict standards and practice. Finally, the communication fusion method is used for experimental simulation. The results show that when the input current is 1A, the experimental, theoretical value of the system is 3A, and the actual instrument output is close to 5A. When the input current is 6A, the instrument output of the system is 7.5A. Therefore, loading a reasonable load impedance value in the system can optimize the current output value of the model. The paper has important reference value for optimizing electromechanical equipment and power acquisition terminal.
UAV Path Planning Model Leveraging Machine Learning and Swarm Intelligence for Smart Agriculture
Authors: E.  Roque -Claros Roberto , P. Flores-Llanos Deivi , R. Maquera-Humpiri Abel , Sonthi Vijaya Krishna , Sengan Sudhakar , Rangasamy Rajasekar
Published: August 2024

Smart agriculture, through precision farming, is revolutionizing traditional farming methods by optimizing resource use and enhancing yields. With the integration of technology, especially the advent of Unmanned Aerial Vehicles (UAVs) or drones, modern agriculture has attained new heights in efficient crop management, real-time data collection, and sustainable practices. UAVs play a pivotal role, offering aerial insights into crop health, soil conditions, and targeted resource application, promoting sustainable farming. However, navigating UAVs efficiently across dynamic agricultural terrains presents challenges, particularly in path planning. While traditional grid-based models have their merits, the complexities of modern farms demand more adaptive models. This work introduces a hierarchical path planning framework for UAVs, combining the “Enhanced Genetic Algorithm using Fuzzy Logic” for global planning and the “Improved D* Algorithm” for real-time local adjustments. This dual-layered approach ensures efficient, safe, and energy-conserving UAV trajectories, marking a significant advancement in UAV-based smart agriculture.
Research on Visualization and Interactivity of Virtual Reality Technology and Digital Media in Interior Space Design
Authors: Zhang Ke , Thienmongkol Ratanachote
Published: August 2024

The combination of digital media and Virtual Reality (VR) technology has become a disruptive force in the interior space design industry, changing the way that design is explored and augmenting its experiential aspects. Examining the substantial effects of deep visualization and technological interaction on the conception and interaction with interior environments, this research explores the junction of these dynamic domains. This study intends to uncover the interactions that drive internal designing spaces into a new era of creativity and engagement with users through a thorough investigation of state-of-the-art VR tools and multimedia services and technologies. The research approach entails a thorough examination of popular virtual reality systems and digital media strategies used in the interior design industry. We’ll carry out user feedback surveys and real-world case studies to see how well these tools work at communicating design ideas and encouraging group decision-making. Considering aspects like accessibility, visual dedication, and real-time interaction, the study aims to identify the main opportunities and obstacles associated with the combination of VR and electronic media inside interior space design. This research will lead to the proposal of a framework for the best possible use of digital media and virtual reality in interior space design. The framework is intended to serve as a guide for designers, architects, and other relevant parties as they fully utilize these technologies to improve visualization, collaboration, and user experience. Furthermore, the study will provide insightful information to the larger conversation on how emerging technologies are reshaping design disciplines.
Research on Cryptography-based Data Security and Trustworthiness in Digital Construction of Water Resources and Hydropower
Authors: Yue Chao , Liu Wei , Chen Licheng , Zuo Chong
Published: August 2024

This study aims to strengthen data security and establish credibility using novel cryptography-based techniques in the context of the digital revolution in the water resource and hydropower development industry. Protecting sensitive data and guaranteeing the confidentiality of digital assets becomes crucial as the sector depends more and more on digital technology for communication, monitoring, and project management. The goal of this work is to create developed cryptographic protocols and structures that have been tailored to the needs of the water resources and hydropower industry. This study offers a thorough investigation into the use of cryptographic methods to tackle the difficulties presented by the digital construction surroundings in these projects. The research process combines algorithm creation, theoretical advancements, and real-world application. The efficiency and viability of the suggested cryptographic approaches in resolving trust and security issues intrinsic in digital building environments will be evaluated using actual-life scenarios and simulations. The results of this study should offer a strong basis for improving data security, reliability, and integrity in digital construction projects related to water resources and hydropower. Through the development of cryptography techniques specifically suited to this vital infrastructure industry, the research helps to build digital ecosystems that are resilient and secure, which is important for the sustainable growth of hydropower and water resources.
Transformer Fault Diagnosis and Location Method Based on Fault Tree Analysis
Authors: Wu Zhiwu , Huang Tianfu , Wang Chunguang , Wu Xiang , Tu Yanzhao
Published: August 2024

Fiber optical current transformer (FOCT) is widely used in power systems for fault diagnosis and analysis, which can improve its operational reliability. Construct fault modes and fault trees based on fault data of all fiber current transformers, and construct a fault feature space. Constructing a fault diagnosis expert system using fault trees and fault feature space clustering centers to achieve accurate diagnosis of fault types, patterns, and components. The proposed method was validated using fault data and case studies of all fiber current transformers in a regional power grid, and the results showed that: The on-site fault case is closest to the cluster center of drift deviation fault, so it belongs to drift deviation fault. Further extract the on-site maintenance report, which indicates that the operating temperature of the all fiber current transformer is relatively high. The diagnostic results of the fault diagnosis expert system for the faulty all fiber current transformer are consistent with the actual results on site, verifying the accuracy and reliability of this method.
Ethical Evaluation and Optimization of Artificial Intelligence Algorithms Based on Self Supervised Learning
Authors: Deng Ruoyu , Zhao Yang
Published: August 2024

Active learning solves the problem of requiring a large amount of manpower and resources due to the large size of training samples. The core problem is how to select valuable samples to reduce annotation costs. Using neural networks as classifiers, most methods choose samples with large amounts of information without considering the issue of information redundancy between the selected samples. Through the study of redundancy issues, the author proposes a sample selection optimization method to reduce information redundancy. Using uncertainty methods to select samples with high information content to form a candidate sample set, and using latent variable vectors calculated in the network to represent sample information, the cosine distance between candidate samples is calculated using this vector to select subsets with large interval distance and low information redundancy. Compared with several uncertainty methods in the Mnist, Fashion mnist, and Cifar-10 datasets, this method reduces labeled samples by a minimum of 11% with the same sample accuracy. The higher the dimensionality of the feature vector calculated by CNN, the more candidate samples it contains, and the more information it contains. After being improved by self supervised learning algorithms, the effect becomes more significant. The more candidate samples are selected, the stronger the information redundancy. The better the performance of self supervised learning algorithms.
The Machine Learning Algorithms in Supply Chain Coordination Simulation and Optimization
Authors: Zhang Qingping , He Yi
Published: August 2024

In response to the current situation of poor adaptive learning performance in Agent production and sales negotiation and dynamic changes in negotiation environment, the author proposes a method based on machine learning algorithms. Consider the impact of conflict level, cooperation possibility, and negotiation remaining time on negotiations in a dynamic negotiation environment, and use the entropy method to determine the weights of three influencing factors and perform linear weighting. Based on the differences in current negotiation topics, a concession amplitude prediction model based on dynamic selective ensemble learning is constructed, and an optimization strategy for supply chain production and sales negotiation is proposed. The experimental results indicate that, in the adaptive negotiation strategy of a regular SVM single learning machine, the joint utility of the most successfully negotiated agents falls within the interval [0.55, 0.70], while the author’s ensemble learning strategy mainly focuses on [0.6, 0.8], the author’s strategy is relatively superior to ordinary learning strategies in terms of both the number of successfully negotiated agents and the joint utility. Compared with the single learning machine negotiation strategy, this strategy improves the success rate and joint utility of Agent adaptive learning, and ensures the benefits of both production and sales in the supply chain, achieving a mutually beneficial situation for both parties in cooperation.
A Nonlinear Convolutional Neural Network Algorithm for Autonomous Vehicle Lane Line Detection
Authors: Lyu Kanhui
Published: August 2024

The traditional lane line detection algorithm relies on artificial design features, which has poor robustness and cannot cope with the complex urban street background. With the rise of deep learning technology, the algorithm model with convolutional neural network as the mainstream is widely used in the field of computer vision, which provides a new idea for lane line detection. In order to improve the disadvantages of traditional lane line detection methods that are vulnerable to environmental impact and poor robustness, a nonlinear convolution neural network algorithm for driverless lane line detection is proposed. Firstly, the pretreatment method of extracting the region of interest and enhancing the contrast of lane lines is used to reduce the unnecessary image background and enhance the feature details of the image. Existing deep learning-based lane line detection algorithms still have difficulties. First, accumulated wear and tear will cause lane line to fade and fade; roadside trees and buildings can interfere with the performance of lane line detection algorithm. In addition, compared with the pixels of the whole picture, the lane line pixels are too few, and the deep convolution neural network of layer convolution is easy to lead to the loss of details. In addition, when the traffic flow is large, the lane line is easily blocked, which makes it more difficult to detect the lane line. Then the model is built based on the lane line image features extracted by CNN, and the DBSCAN clustering algorithm is used to post-process the lane line segmentation model; Finally, the least square method is used to fit the quadratic curve of the pixel peak points of the lane line, and the fitting results are regressed to the original image. The experimental results show that the accuracy and recall of the lane line detection model verification set are 91.3% and 90.6%, respectively, indicating that the model has a good segmentation effect. It is proved that the lane line detection method based on CNN combined with post-processing can effectively reduce the defects of artificial experience, and has better robustness and accuracy than the traditional lane line detection method.
Optimization of Logistics Distribution Network based on Ant Colony Optimization Neural Network Algorithm
Authors: Yang Jing
Published: August 2024

In order to improve the timeliness of logistics distribution, based on the theory of road network smoothness and reliability, the author conducted a study on the optimization of urban logistics distribution and transportation networks based on smoothness and reliability. The concept of logistics distribution and transportation network smoothness and reliability was proposed, and a logistics distribution and transportation network optimization model was established. The solving process of ant colony algorithm was given, and finally, a comparative analysis of a case was conducted. The results showed that: With a 6% increase in total delivery distance, the reliability of the delivery network has increased by 30%. This indicates that when using the model built by the author for distribution network optimization, effective optimization of network smoothness and reliability can be achieved, while only increasing the distance by a small amount. The optimal reliability of a smooth distribution network means that the probability of delivery delays is minimized, which is the most powerful guarantee for the effective accessibility of delivery. Verified the practicality of the constructed model. The proposed logistics distribution network optimization model has practical significance in guiding decision-making for optimizing urban logistics distribution transportation networks and reducing uncertainty in the process of urban logistics distribution.
Trimming the Tangle of Legend: Heroic Haircuts, Materialising Meals, and the Legitimisation of Dynastic Succession in Norwegian and Polish Foundation Narratives
Authors: Allport Ben , Rutkowski Rafał
Published: August 2024

The medieval origin narratives of both Poland and Norway feature dynastic founders who came to power following a ritualistic haircut. In the Polish tradition, Siemowit of the Piast dynasty is anointed duke after his coming-of-age haircut, which is administered by two mysterious strangers; in the Norwegian version, Harald Fairhair vows to only cut his hair after he has united the realm. In both traditions, the transfer of power to these new rulers is also symbolised by a feast that vanishes from the table of a previous ruler and materialises before the dynastic founder. This chapter examines these narratives and compares their use of haircutting and feasting motifs to explore the transmission of royal authority both within and between ruling dynasties. Two traditions are explored from each arena: Gallus Anonymus’s Gesta principum Polonorum and Kadłubek’s Chronica Polonorum from Poland; and Fagrskinna and Snorri Sturluson’s Heimskringla from Norway. In comparing how the haircutting tradition in each polity evolved, we gain profound insights into their authors’ approach towards the development of dynastic power and the structure of dynastic history. In particular, we consider how these authors rationalised the concept of dynastic fragmentation and the rise of rival claimants as these elements came to dominate the political struggles of the twelfth and thirteenth centuries. Broadly speaking, we conclude that Polish historiography sought to cut away rival dynasts, whereas Norwegian traditions visualised competing dynastic branches as locks of hair cascading from one head.
Concluding Remarks: Languages of Power and Elite Legitimisation in Poland and Norway, 1000–1300
Authors: Berend Nora
Published: August 2024

The articles in the volume demonstrate that comparative history can break out of the straight-jacket of supposed geographical constraints, and show how more detailed comparative studies of various aspects of legitimisation can reveal the nuances behind seemingly uniform patterns. The concluding remarks further elaborate on these points and raise questions concerning the terminology of centre and periphery.
Proposta de uma Sequência Didática da Atividade Laboratorial da Queda Livre de um Corpo para Estudantes do Ensino à Distância.
Authors: Machado Natália , Carvalho Paulo , Alan de Oliveira Cruz Frederico
Published: August 2024

Nos cursos de graduação relacionados com temas de ciências da natureza, como física, química e biologia, as atividades experimentais desempenham um papel essencial na compreensão dos diversos fenómenos apresentados ao longo das disciplinas. Essas atividades são componentes fundamentais presentes nas grades curriculares. Nos cursos ministrados na modalidade de ensino à distância, essas práticas ocorrem num ambiente inicialmente pouco conhecido pelos estudantes, conduzidas geralmente por tutores em horários pré-determinados. Em muitos casos, há limitações que impedem a repetição da atividade, dificultando uma compreensão mais aprofundada do conteúdo abordado. Dentro dessa perspetiva, uma vez que, nos cursos de ensino à distância, as atividades laboratoriais devem ser realizadas presencialmente, torna-se crucial pensar em propostas que preparem os estudantes para essas atividades, utilizando recursos complementares. Neste artigo, propomos uma sequência didática para a atividade experimental de queda livre de um corpo, que incorpora vídeos e simulações. Essa abordagem visa contribuir de maneira eficaz para a construção do conhecimento do estudante, capacitando-o melhor para a realização da atividade prática.
Perancangan Busy Book Pengenalan Emosi Pada Anak Sebagai Media Alternatif Pembelajaran
Authors: Dalmi Kealyn Din , Dwitasari Putri , Sabar Sabar , Alamin Rabendra Yudistira
Published: August 2024

Childhood is the most important phase for the intellectual and emotional development of children. At the age of 18 months to 3 years, children begin to recognize emotions, other people's feelings, and other people's facial expressions regarding an emotional experience. Emotions in children turn out to play a very large role in shaping the structure of the brain; apart from that, recognizing emotions in children is a key to helping control emotions so that they grow up to be happy children and have good qualities. Therefore, it is important for parents to provide proper stimulation according to the growth and development of their children, one of which is playing. In carrying out play activities, learning media are needed that accommodate the needs of children not only to learn but also to play. So media is needed in the form of a busy book as a form of effort to introduce emotions to children with an approach through games, because if "emotions" are not introduced, it can have an impact on the growth, development, and character of the child. In this design, several methods are used, namely, literature studies through journals and online media, in-depth interviews with relevant sources, observation, and experimental studies, to support content and design development. The result of this design is a busy book with a game concept that is strengthened in content with the aim of making it easier for the target audience to follow the information and activities regarding emotion recognition contained in the book. This medium is expected to be a supportive alternative for parents in introducing emotions to their children from an early age.
Perancangan Video Explainer Tentang Toxic Masculinity Untuk Menghindari Kekerasan Berbasis Gender
Authors: Rasyid Aslam Arethusa Maneezyaa , Sabar Sabar
Published: August 2024

Toxic masculinity grows from a patriarchal background, where men are considered as the highest subject in social construction. Toxic Masculinity refers to concepts, beliefs, and actions commonly associated with masculinity, which are harmful to women, men, children, and society. Toxic masculinity is formed from social constructions and stereotypes instilled in men, such as emotional suppression, urges to commit violence, perpetuation of rape culture, and misogyny. With the stereotype labeling of women always inferior to men, men become arrogant and play around with women who in their eyes are considered weak and helpless. This leads to sexual harassment and violence, household neglect, and gender-related violence or Gender-Based Violence. This design was carried out through several research methods. Literature study on the topic of toxic masculinity and explainer videos. Depth interviews were conducted with design stakeholders and target segment samples. Questionnaires were conducted to collect data on a wider target segment. Experimental studies to determine design concepts consisting of communication concepts, visual concepts, and media concepts, then an evaluation of the designs was carried out with expert sources. The purpose of this design is as a source of information to foster insight into the community so as to foster public insight about the importance of avoiding toxic masculinity actions so as to prevent all the adverse effects that can result from this. In addition, through this design it is hoped that it can provide education, new insights, and knowledge to the Indonesian people so they can work together to prevent gender-based violence from occurring. The implementation of the media used in this design includes explainer video, short videos, and YouTube channel.
The power of motivational interviewing in healthcare
Authors: Butler Sarah
Published: August 2024

Sarah Butler outlines the basic principles of MI, highlighting its effectiveness and highlighting the importance of a collaborative and non-judgemental approach in facilitating positive changes in health care.

Motivational Interviewing (MI) is a pivotal approach in healthcare, utilising collaboration, empathy, and individual empowerment. This article focuses on the foundational principles of MI, focusing on its effectiveness in promoting positive outcomes by acknowledging resistance to force, addressing the elements of positive change, and fostering collaborative relationships. MI recognizes the importance of capability, opportunity, and motivation in achieving sustainable outcomes, highlighting the role of healthcare professionals as guides rather than authoritative figures.
Kinematic alignment recreates femoral trochlear geometry more closely than mechanical alignment in total knee arthroplasty
Authors: Borukhov Ilya , Ismailidis Petros , Esposito Christina I. , LiArno Sally , Lyon Jenna , McEwen Peter J.
Published: August 2024

Aims

This study aimed to evaluate if total knee arthroplasty (TKA) femoral components aligned in either mechanical alignment (MA) or kinematic alignment (KA) are more biomimetic concerning trochlear sulcus orientation and restoration of trochlear height.

Methods

Bone surfaces from 1,012 CT scans of non-arthritic femora were segmented using a modelling and analytics system. TKA femoral components (Triathlon; Stryker) were virtually implanted in both MA and KA. Trochlear sulcus orientation was assessed by measuring the distal trochlear sulcus angle (DTSA) in native femora and in KA and MA prosthetic femoral components. Trochlear anatomy restoration was evaluated by measuring the differences in medial, lateral, and sulcus trochlear height between native femora and KA and MA prosthetic femoral components.

Results

Femoral components in both MA and KA alignments exhibited a more valgus DTSA compared to native femora. However, DTSA deviation from native was significantly less in KA than in MA (4.8° (SD 2.2°) vs 8.8° (SD 1.8°); p < 0.001). DTSA deviation from native orientation correlated positively with the mechanical lateral distal femoral angle (mLDFA) in KA and negatively in MA (r = 0.53, p < 0.001; r = -0.18, p < 0.001). Medial trochlear height was not restored with either MA or KA, with MA resulting in lower medial trochlear height than KA in the proximal 20% of the trochlea. Lateral and sulcus trochlear height was not restored with either alignment in the proximal 80% of the trochlea. At the terminal arc point, KA replicated sulcus and lateral trochlear height, while MA led to over-restoration.

Conclusion

Femoral components aligned in KA demonstrated greater biomimetic qualities than those in MA regarding trochlear sulcus orientation and trochlear height restoration, particularly in valgus femora. Variability across knees was observed, warranting further research to evaluate the clinical implications of these findings.

Cite this article: Bone Joint J 2024;106-B(8):817–825.
Functional assessment in patients undergoing total hip arthroplasty
Authors: Rivera Richard J. , Karasavvidis Theofilos , Pagan Cale , Haffner Rowan , Ast Michael P. , Vigdorchik Jonathan M. , Debbi Eytan M.
Published: August 2024

Aims

Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA.

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests.

Results

A total of 130 studies using 15 distinct objective functional assessment methods (FAMs) were identified. The most frequently used method was instrumented gait/motion analysis, followed by the Timed-Up-and-Go test (TUG), 6 minute walk test, timed stair climbing test, and various strength tests. These assessments were characterized by their diagnostic precision and applicability to daily activities. Wearables were frequently used, offering cost-effectiveness and remote monitoring benefits. However, their accuracy and potential discomfort for patients must be considered.

Conclusion

The integration of objective functional assessments in THA presents promise as a progress-tracking modality for improving patient outcomes. Gait analysis and the TUG, along with advancing wearable sensor technology, have the potential to enhance patient care, surgical planning, and rehabilitation.

Cite this article: Bone Joint J 2024;106-B(8):764–774.
Managing more than bones: the psychological impact of a recurrent fracture-related infection
Authors: Walter Nike , Loew Thomas , Hinterberger Thilo , Alt Volker , Rupp Markus
Published: August 2024

Aims

Fracture-related infections (FRIs) are a devastating complication of fracture management. However, the impact of FRIs on mental health remains understudied. The aim of this study was a longitudinal evaluation of patients’ psychological state, and expectations for recovery comparing patients with recurrent FRI to those with primary FRI.

Methods

A prospective longitudinal study was conducted at a level 1 trauma centre from January 2020 to December 2022. In total, 56 patients treated for FRI were enrolled. The ICD-10 symptom rating (ISR) and an expectation questionnaire were assessed at five timepoints: preoperatively, one month postoperatively, and at three, six, and 12 months.

Results

Recurrent FRI cases consistently exceeded the symptom burden threshold (0.60) in ISR scores at all assessment points. The difference between preoperative-assessed total ISR scores and the 12-month follow-up was not significant in either group, with 0.04 for primary FRI (p = 0.807) and 0.01 for recurrent FRI (p = 0.768). While primary FRI patients showed decreased depression scores post surgery, recurrent FRI cases experienced an increase, reaching a peak at 12 months (1.92 vs 0.94; p < 0.001). Anxiety scores rose for both groups after surgery, notably higher in recurrent FRI cases (1.39 vs 1.02; p < 0.001). Moreover, patients with primary FRI reported lower expectations of returning to normal health at three (1.99 vs 1.11; p < 0.001) and 12 months (2.01 vs 1.33; p = 0.006).

Conclusion

The findings demonstrate the significant psychological burden experienced by individuals undergoing treatment for FRI, which is more severe in recurrent FRI. Understanding the psychological dimensions of recurrent FRIs is crucial for comprehensive patient care, and underscores the importance of integrating psychological support into the treatment paradigm for such cases.

Cite this article: Bone Jt Open 2024;5(7):621–627.
Single-photon generation at room temperature using molecular optomechanics in a hybrid photonic-plasmonic cavity
Authors: Abutalebi Shabnam , Ashrafi Seyed Mahmoud , Ranjbar Askari Hassan , Bahrampour Alireza
Published: August 2024

We propose an integrated structure for single-photon generation at room temperature based on a molecular optomechanics system in a hybrid photonic-plasmonic cavity. The proposed structure comprises a single molecule within a plasmonic cavity, coupled to a 2D photonic crystal resonator. In this paper, we theoretically identify the ability of the scheme through calculating the second-order correlation function g2 (0) for four different coupling regimes. We demonstrate the quantum paths and the destructive interference mechanism through the selection of efficient and preferred basis. Furthermore, we find that the unconventional photon blockade effects can occur in weak molecular optomechanics coupling. This structure holds the potential to serve as an integrated single-photon source for quantum networks at room temperature.
Measurement of optical rotation as a function of temperature using a common-path heterodyne polarimeter
Authors: Chiu Ming-Hung , Liu Dong-Xian , Chiu Chao-Ching
Published: August 2024

We employ a common-path heterodyne polarimeter to measure the variation of optical rotation (OR) with temperature. A heterodyne beam with two orthogonal polarizations is incident on a sample and a half-wave plate set at an azimuth angle of 22.5°. Any change in the sample's OR results in a large phase shift between the two polarizations. We measure this phase shift using a lock-in amplifier and compare it with a reference signal. Our experimental results show that the OR increases with temperature.
Exploring the motivations of female community health volunteers in primary healthcare provision in rural Nepal: A qualitative study
Authors: Panday Sarita , Teijlingen Edwin van , Barnes Amy
Published: August 2024

Motivating Community Health Workers (CHWs)—many of whom are volunteers—is crucial for achieving Universal Healthcare Coverage (UHC) for Primary Healthcare (PHC) in resource-poor areas. In rural Nepal, PHC is mostly delivered by female CHWs, locally known as Female Community Health Volunteers (FCHVs), but little is known about them. This paper explores experiential factors influencing FCHVs’ motivations, including how motivation intersects with women’s livelihoods and consider what this means for achieving PHC in Nepal and globally. We conducted qualitative research in the hill and the Terai (flatland bordering India) areas of Nepal. Data were purposively collected through 31 semi-structured interviews (20 volunteers, 11 paid local health workers) and three focus group discussions with additional 15 volunteers. All interviews were audio-recorded, transcribed verbatim in Nepali and translated into English. Data were coded using NVivo10, analysed thematically at individual, organisational and community levels. FCHVs’ motivations to volunteer was affected in several ways. At the individual level, participants wanted and were committed to voluntary work, yet the opportunity costs of volunteering, out-of-pocket expenditure and inadequate family support strained many of the women who were already overburdened. At the community level, perceived lack of appreciation of volunteer efforts by community members, who saw volunteers as paid health workers, undermined FCHVs motivation to volunteer. Finally, at the organizational level, a bureaucratic emphasis on recording and reporting, and lack of respect from local health workers undermined their motivation at work. Our paper illustrates how FCHVs from some of the poorest backgrounds can be highly motivated to volunteer, yet inadequate social and economic support across individual, organisational and community levels undermined this motivation, the security of their livelihoods, and thus wider efforts to achieve PHC. Financial investments are needed to compensate FCHVs, so that they remain motivated to deliver global health goals for PHC.
Prevalence and intensity of soil-transmitted helminth infections among school-aged children in five districts in Uganda
Authors: Tinkitina Benjamin , Beinamaryo Prudence , Kyarisiima Hilda , Nabatte Betty , Arinaitwe Moses , Mubangizi Alfred , Emerson Paul , M. Sullivan Kristin
Published: August 2024

Background

Soil-transmitted helminth (STH) infections, commonly caused by roundworms (Ascaris lumbricoides), whipworms (Trichuris trichiura), and hookworms (Necator americanus and Ancylostoma duodenale), were widespread among Ugandan schoolchildren in the late 1990s and early 2000s. Since 2003, the Ugandan Ministry of Health has administered biannual preventive chemotherapy to children aged 1–14 years to control these infections. Twenty years after the program’s inception, there is scant data to show the long-term impact of these national deworming efforts.

Methods

To estimate the prevalence and intensity of STH infections among 10–14-year-old primary school children, school-based, cross-sectional surveys were conducted in November 2023 across five districts (Kamwenge, Sheema, Adjumani, Lamwo, and Zombo). Sixty-five children from five schools per district were selected for inclusion. Fecal egg counts were determined using the Kato-Katz microscopy technique, performed in duplicate by trained laboratory technicians.

Results

The survey findings revealed a high prevalence of any STH infection in Kamwenge District (21.2%, 95% confidence limits (CL): 5.7%, 36.6%), while the remaining four districts exhibited lower prevalences, ranging from 0.4% (95% CL: 0.0%, 1.2%) in Adjumani District to 5.6% (95% CL: 0.0%, 11.4%) in Sheema District. The prevalence of moderate-to-heavy-intensity infections was below 1% across all districts. A. lumbricoides was identified infrequently. Hookworm infections were primarily identified in the western districts of Kamwenge and Sheema, while T. trichiura infections were common only in Kamwenge District. Hookworm and T. trichiura infections were uncommon in the northern districts of Adjumani, Lamwo, and Zombo.

Conclusions

These surveys suggest that morbidity due to STH infections among schoolchildren may be well controlled in these five districts, as evidenced by low moderate-to-heavy-intensity infection prevalence. However, the prevalence of any intensity infection remains elevated in some districts, indicating the need for continued preventive chemotherapy distribution. A reduction from biannual treatment may be warranted in four districts, per World Health Organization recommendations.
Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data
Authors: Hotta Shinji , Kytö Mikko , Koivusalo Saila , Heinonen Seppo , Marttinen Pekka
Published: August 2024

Background

In recent years, numerous methods have been introduced to predict glucose levels using machine-learning techniques on patients’ daily behavioral and continuous glucose data. Nevertheless, a definitive consensus remains elusive regarding modeling the combined effects of diet and exercise for optimal glucose prediction. A notable challenge is the propensity for observational patient datasets from uncontrolled environments to overfit due to skewed feature distributions of target behaviors; for instance, diabetic patients seldom engage in high-intensity exercise post-meal.

Methods

In this study, we introduce a unique application of Bayesian transfer learning for postprandial glucose prediction using randomized controlled trial (RCT) data. The data comprises a time series of three key variables: continuous glucose levels, exercise expenditure, and carbohydrate intake. For building the optimal model to predict postprandial glucose levels we initially gathered balanced training data from RCTs on healthy participants by randomizing behavioral conditions. Subsequently, we pretrained the model’s parameter distribution using RCT data from the healthy cohort. This pretrained distribution was then adjusted, transferred, and utilized to determine the model parameters for each patient.

Results

The efficacy of the proposed method was appraised using data from 68 gestational diabetes mellitus (GDM) patients in uncontrolled settings. The evaluation underscored the enhanced performance attained through our method. Furthermore, when modeling the joint impact of diet and exercise, the synergetic model proved more precise than its additive counterpart.

Conclusion

An innovative application of the transfer-learning utilizing randomized controlled trial data can improve the challenging modeling task of postprandial glucose prediction for GDM patients, integrating both dietary and exercise behaviors. For more accurate prediction, future research should focus on incorporating the long-term effects of exercise and other glycemic-related factors such as stress, sleep.
Impact of prolonged social crisis on resilience and coping indicators
Authors: Marciano Hadas , Kimhi Shaul , Eshel Yohanan , Adini Bruria
Published: August 2024

The current study examines, longitudinally, (i.e., on the same sample), to what extent an acute political/social crisis in Israel affected the resilience, distress, and additional psychological indicators of the Jewish population, along with three repeated measurements: The first was conducted shortly before the last elections (in October 2022), the second in February 2023, about two and a half months after the elections, following the formation of a right-wing government, and the third measurement about nine months after the election (August 7–10, 2023). The main results indicated the following: (a) the mean societal resilience among coalition voters increased significantly throughout the three measurements, while it declined significantly among opposition voters. (b) significant differences were identified between coalition and opposition voters, mostly at T2 and T3: opposition supporters reported significantly lower levels of societal resilience and hope, and higher levels of distress symptoms and sense of danger, compared to those of coalition supporters. We concluded that the continued social/political conflict in Israel is multidimensional and impacts diverse areas such as values, perspectives, and supporting as well as suppressing coping indicators. The differences between the two voter groups may be primarily the result of political radicalization and polarization processes, that aim to widen gaps to achieve political power. As many countries are currently facing acute political crises and similar radicalization, similar studies should be conducted in varied societies to investigate the generalizability of the findings.
An efficient power decoupling topology circuit based on a novel three-port three-switches flyback series circuit
Authors: Jinpeng Wang , Yufang Kang , Qingxue Yao , Gillbanks Jeremy , Xin Zhao
Published: August 2024

Both filter inductors, electrolytic capacitors, and radiators play a significant role in the inverter of a PV (Photovoltaic) power generation system. These three parts are the largest in an inverter, which affects the performance of the inverter. Aimed to improve the power density of a single-phase PV grid-connected inverter with a decoupling function. This paper derived the control principle that can reduce the volume of the inductor, decoupling capacitor, and the loss of the switching device to begin with the mathematical function of power processing of the filter inductor. And then, the authors deduced a boost-type power decoupled single-phase inverter topology. Based on a novel three-port three-switches flyback series circuit, this paper proposed an efficient power decoupling topology circuit for extracting the maximum power density of a single-phase grid-connected PV inverter. Finally, this article operated the simulation and experiment. Both the simulated and experimental results verified that the proposed method works well.
The impact of an educational intervention on neonatal intensive care unit nurses’ knowledge, attitudes, and perceptions of parental participation in kangaroo mother care
Authors: Abuhammad Sawsan , Karimeh Roaa , Mahadeen Alia
Published: August 2024

Aim

The aim of this study is to evaluate the effectiveness of the education interventions on NICU nurses’ knowledge, attitudes, and perceptions of parental participation in kangaroo mother care (KMC) in NICU.

Method

A quasi-experimental pretest/posttest nonequivalent group design was used to evaluate the effectiveness of the education interventions on NICU nurses’ knowledge, attitudes and perceptions of parental participation in KMC delivered in the neonatal intensive care units at three hospitals. 160 nurses participated in the study, with a division of 80 in the educational group, and 80 in the non-educational group.

Results

The results showed that the educational group was statistically different in knowledge post-intervention (t = -2.819, df = 79, p≤0.001). The pre-intervention mean attitude for the educational group was 19.81 (SD = 4.3). The findings expressed that the educational group was statistically different in attitude in the post-intervention phase (t = -3.66, df = 79, p≤0.001). The results reflect a significant effect in the educational group regarding nurses’ perspectives of parental participation post-intervention (t = 5.496, df = 79, p≤0.001).

Conclusion

Our findings showed that providing nurses with additional education increased their knowledge, improved their attitudes, and enhanced their perceptions of parental support in NICU. Providing staff with an educational intervention about KMC in NICU can enhance nursing knowledge, attitudes, and perceptions of parental participation in neonate care in the NICU.