bluuebunny/crossref_metadata_2025 huggingface dataset:
Segmentation of tobacco shred point cloud and 3-D measurement based on improved PointNet++ network with DTC algorithm
Authors: Wang Yihang , Zheng Haiwei , Yang Jie , Wang Yan , Wang Li , Niu Qunfeng
Published: January 2025

Introduction

The three dimensions of the tobacco silk components (cut stem, tobacco silk, reconstituted tobacco shred, and expanded tobacco silk) of cigarettes directly affect cigarette combustibility; by accurately measuring the dimensions of different tobacco silks in cigarettes, it is possible to optimize combustibility and reduce the production of harmful substances. Identifying the components of tobacco shred in cigarettes is a prerequisite for three-dimensional measurement. The two-dimensional image method can identify the tobacco shred and measure its two-dimensional characteristics but cannot determine its thickness. This study therefore focuses on the identification of the tobacco shred and measuring it in three dimensions.

Methods

The point cloud data of the upper and lower surfaces of tobacco shred are segmented using the improved three-dimensional point cloud segmentation model based on the PointNet++ network. This model combines the weighted cross-entropy loss function to enhance the classification effect, the cosine annealing algorithm to optimize the training process, and the improved k-nearest neighbors multi-scale grouping method to enhance the model’s ability to segment the point cloud with complex morphology. Meanwhile, this study also proposes a dimension transformation calculation method for calculating the three dimensions of tobacco shred.

Results

The experimental results show that the precision and recall of the improved segmentation model increased from 84.27% and 83.63% to 95.13% and 97.68%, respectively; the relative errors of the length and width of tobacco shred were less than 5% and 7%, and the relative error of the standard gauge block thickness measurement reached 1.12%.

Discussion

This study also provides a new idea for implementing three-dimensional measurements of other flexible materials.
Expanding the green gaming horizon: a conceptual analysis of and proposed guidelines for upscaling environmental game usage in climate education
Authors: Fjællingsdal Kristoffer Skomsøy
Published: January 2025

Despite the now unequivocal notion that climate change is driven by anthropogenic activity, communication between concerned climate scientists and laypeople about the severity of the issue is still muddy. Although creative and more approachable venues of communication to climate change and sustainability issues are being explored more regularly than before, there is still room for improvement and upscaling in the attempts to link scientists and laypeople together in the understanding of these outstanding issues. This also applies to the field of environmental gaming, which has become more popular in the recent decade. Despite this increasing popularity, however, most environmental gaming studies exist as small-scale pilot studies that often result in generating limited, albeit promising results in terms of increasing awareness and knowledge around environmental topics. This article explores the use of games in climate- and sustainability education and provides a set of assisting guidelines to ease the process of using games as communication tools about these pressing issues, as well as providing advice on how to upscale environmental gaming from a set of limited pilot studies.
The global burden of otitis media in 204 countries and territories from 1992 to 2021: a systematic analysis for the Global Burden of Disease study 2021
Authors: Huang Guan-Jiang , Lin Bao-Rui , Li Pei-Shan , Tang Na , Fan Zhi-Jun , Lu Biao-Qing
Published: January 2025

Objectives

This study aims to analyze the global burden of otitis media and predict future trends using data from the Global Burden of Disease 2021 (GBD 2021).

Study design

A cross-sectional analysis of GBD 2021 results was conducted.

Methods

Age-standardized incidence rates (ASIR), age-standardized prevalence rates (ASPR), and age-standardized disability-adjusted life years (DALYs) rates (ASDR) were calculated. Trend analysis was conducted using estimated annual percentage change (EAPC), Joinpoint regression, age-period-cohort, and decomposition analyses. Future projections were generated using Bayesian age-period-cohort (BAPC) and auto-regressive integrated moving average (ARIMA) models.

Results

The global incidence of otitis media rose from 322.1 million cases in 1992 to 391.3 million in 2021, with ASIR increasing slightly from 5345.09 to 5529.1 per 100,000 (EAPC: 0.11%). Despite this increase, the ASPR decreased from 1786.56 to 1593.74 (EAPC: -0.43%). DALYs increased from 2.16 million to 2.48 million; however, ASDR declined from 37.68 to 32.54 per 100,000 (EAPC: −0.51%). Notably, low and low-middle SDI regions showed significant disparities, with higher ASIRs (up to 5315.08 for males) but declining trends in ASPR. Regionally, East Asia exhibited the most substantial decline in ASPR (−1.14%) and ASDR (−1.22%), while Central Sub-Saharan Africa demonstrated stable ASDR. Future projections indicate a rising ASIR and declining ASPR and ASDR through 2036.

Conclusion

The global burden of otitis media shows significant regional disparities, with stable incidence but declining prevalence and DALYs rate. Public health interventions have been effective in higher SDI regions, but targeted efforts are needed in low and low-middle SDI regions to further reduce the burden of otitis media.
A holistic and sustainable approach to public health staffing and workforce development
Authors: Mui Paulani , Maiorana Ruth , Resnick Beth
Published: January 2025

Public health in the United States faces a continuous cycle of “neglect, panic, repeat.” As seen with 9/11, H1N1, and COVID-19, public health emergencies create a flurry of attention and resources, but once the crisis passes, focus quickly shifts to other matters until the next emergency, when the cycle repeats. This leaves the nation's public health system chronically under-resourced and ill-equipped to respond, resulting in a strained workforce that must remain nimble. Maintaining responsiveness to community needs requires a sustainable system with adequate worker supports. This perspective discusses findings from an assessment of short-term COVID-19 investments on long-term U.S. public health workforce needs, highlighting the need for a holistic approach to staffing and workforce development. Temporary staffing addressed immediate response needs, but presented challenges such as difficulties transitioning temporary staff into permanent roles and cohesively integrating temporary staff into ongoing agency operations, which often inadvertently increased administrative burdens on existing staff, exacerbating burnout and dampening morale. Ensuring a sustainable workforce necessitates innovative recruitment and retention strategies. Recommended strategies include holistic recruitment efforts in collaboration with community and academic partners, enhanced leadership training, staff compensation reviews, flexible work arrangements, and worker wellbeing initiatives. These findings guided the creation of the Putting Our People First Discussion Guide to empower agencies to engage workers in collective dialogue to improve workforce mental health, wellbeing, and retention. Bolstering a culture of worker wellbeing and retention alongside sustained funding and infrastructure is critical for the nation's public health agencies to effectively address current and future challenges.
Gender-specific dual effects of physical activity on depression and mortality: a nine-year cohort study in Chinese adults aged 45 and above
Authors: Shan Dan , Yang Meina , Zhou Kunyan
Published: January 2025

Background

Regular participation in physical activity (PA) reduces all-cause mortality (ACM) in the general population. However, the effects of PA on depressed patients and potential gender-specific responses have not been fully elucidated. In this study, we aimed to investigate the role of PA on new-onset depression and ACM in Chinese adults aged 45 year and older, with particular emphasis on gender differences.

Methods

This was a longitudinal cohort study that took place over a nine-year period and featured 2,264 participants drawn from the China Health and Retirement Longitudinal Study (CHARLS). PA levels were categorized into quartiles using metabolic equivalents (MET; minutes/week), and depression was evaluated according to the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) scale. Specific relationships between PA, depression, and mortality were then investigated by applying multivariate logistic regression and Cox proportional hazards models.

Results

Highest quantile levels of PA were correlated with a 37% increase in the risk of new-onset depression in middle-aged (45–59 years) and older adults (>60 years). This association was predominantly influenced by a significant increase in the risk of mild depression (a score of 10–14 on the CESD-10) (odds ratio [OR]: 1.76; 95% confidence interval [CI]: 1.29–2.42, p < 0.001), with a more pronounced effect observed in women (OR: 1.83; 95% CI: 1.26–2.66, p = 0.002). A critical threshold for PA was identified at 4536 MET-minutes/week, beyond which the risk of depression increased significantly (p < 0.05). Conversely, higher levels of PA were linked to a 90% reduction in ACM (HR: 0.10; 95% CI: 0.02–0.44, p = 0.002), with the effect being more pronounced in men.

Conclusion

While PA reduces mortality, excessive activity may increase the risk of mild depression, particularly in women. These findings highlight the need for gender-specific PA guidelines that balance physical and mental health outcomes.
Engaging the private sector as part of HIV pre-exposure prophylaxis service delivery in Vietnam: a comparative analysis of uptake, persistence and HIV seroconversion from 2018 to 2023
Authors: Vu Bao Ngoc , Green Kimberly , Phan Huong , Tran Long , Phan Phuong , Tran Tham , Doan Linh , Vu Yen , Pham Chau , Nguyen Dao , Doan Anh , Ngo Trang , Tran Phuong , Nguyen Vuong , Nguyen Bieu , Phan Thai , Nguyen Ha
Published: January 2025

Background

In Vietnam, PrEP was introduced in 2017 and scaled up from 2019. Private sector engagement (PSE) in PrEP service delivery was deployed as a strategy from the start to increase PrEP access. We assessed the effectiveness of this approach to inform ongoing efforts to accelerate epidemic control by 2030.

Methods

We implemented a process evaluation with longitudinal design using retrospective programmatic data collected and uploaded onto a secure online system (HMED) from 23 public and 17 private PrEP clinics in Hanoi, Ho Chi Minh City (HCMC), and Dong Nai. We measured the effectiveness of PrEP service delivery by PrEP initiation/reinitiation, uptake, persistence, discontinuation, and HIV seroconversion. We used the Kaplan-Meier time-to-event approach to estimate PrEP persistence and mixed-effects logistic regression analysis to assess factors associated with the PrEP persistence.

Results

From October 2017 to September 2023, 29,944 individuals initiated PrEP, and among these, 79.3% started PrEP at a private sector clinic while 20.7% initiated in a public sector clinic. The median duration of PrEP use persistence at private clinics was significantly longer than that at public clinics (268 days vs. 148 days, respectively). Mixed-effects logistic regression analysis results indicated a significant statistical association between PrEP persistence for at least three months and initiating PrEP at a private clinic [adjusted odds ratio [aOR] = 4.28; 95% confidence interval [CI]: 2.96–6.19], opting for TelePrEP (aOR = 3.42; 95% CI: 2.12–5.53), or being 20 years of age or older (aOR = 1.86; 95% CI: 1.62–2.13). HIV seroconversion was significantly lower among PrEP users at private clinics compared to public clinics (0.03 vs. 0.13 per 100 person-years, respectively; p < 0.01).

Conclusion

Offering choice in PrEP service delivery options is essential to increase access and uptake. Private-sector PrEP providers play a pivotal role in increasing PrEP uptake and coverage in Vietnam, and will be critical to delivery of new long-acting options.
An 8-week physical exercise intervention for e'athletes improves physical performance rather than short-term esports performance parameters - a randomized controlled trial
Authors: Wachholz Felix , Gamper Nicole , Schnitzer Martin
Published: January 2025

Introduction

Esports have been suggested to enhance hand-eye coordination, fine motor skills, and reaction times. While physical exercise is known to improve these abilities, its impact on short-term esports performance is under-researched. This study aims to evaluate the effects of specific and general physical training on gaming performance, hypothesizing improvements in both physical and gaming-related variables.

Methods

Baseline and follow-up tests measured global coordination, grip strength, Aimlabs performance, single and 4-fold reaction times, and anticipation. Participants completed a weekly and an ending questionnaire. Twenty-eight participants (12.3 ± 10.1 h gaming/week) were assigned to specific (N = 10), general (N = 9), and no training (N = 9) groups for an 8-week intervention. Variable changes over time and between groups were analyzed using a repeated measures ANCOVA.

Results

Training significantly improved the overall coordination of those participants engaging in physical training compared to the control group [F(2,25) = 3.858, p = 0.035, η2 = 0.236]. Grip strength also showed significant improvement [F(2,25) = 6.084, p = 0.007, η2 = 0.327]. There were no significant time or group effects for the gaming variables, but the hours played by participants positively influenced Grid Shot [F(1,24) = 4.746, p = 0.039, η2 = 0.165] and Track Point [F(1,24) = 9.613, p = 0.005, η2 = 0.286] performance. The weekly questionnaire indicated a significant improvement in participants' well-being.

Discussion

While training improved physical variables, no effects were observed in suggested short-term performance. However, gaming hours and experience during the intervention positively influenced performance. Future research should consider the amount of time spent playing as it may affect short-term performance. Furthermore, future research should strive to differentiate between various types of esports performance, such as short-term vs. long-term outcomes. Participants reported that engaging in physical activity within the context of esports and gaming positively contributed to their overall well-being.

Clinical Trial Registration

ClinicalTrials.gov, identifier (NCT06264375).
Citizens' acceptance and use of new technology: the case of improved fuel in Ulaanbaatar
Authors: Batkhuyag Undrakh
Published: January 2025

Introduction

In accordance with the government's pollution reduction policy, this study examines the acceptance and usage of improved fuel in a mandatory situation among citizens in Ulaanbaatar, Mongolia. The city struggles with air pollution due to high coal consumption, especially in its Ger districts.

Methods

Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the research explores the determinants influencing the behavioral intention and actual use of improved fuel. The study integrates additional factors, namely environmental impact, risk perception, and autonomous as well as controlled motivation, into the UTAUT framework. Data was collected through a cross-sectional online survey of 198 adult residents.

Results

The study identified performance expectancy, effort expectancy, and social influence as significant predictors of intention to adopt improved fuel. Performance expectancy had the strongest positive effect, while social influence negatively impacted intention, reflecting citizens' disapproval of improved fuel. Intention significantly predicted actual usage, but facilitating conditions were insignificant, likely due to the mandatory context. Autonomous motivation positively influenced intentions, highlighting the importance of understanding benefits. Controlled motivation, environmental impacts, and risks showed no significant effects.

Conclusion

The findings underscore the importance of targeted policies and public awareness in enhancing the adoption of cleaner technologies to mitigate air pollution and improve public health in the city.
Research on Broiler Mortality Identification Methods Based on Video and Broiler Historical Movement
Authors: Hao Hongyun , Zou Fanglei , Duan Enze , Lei Xijie , Wang Liangju , Wang Hongying
Published: January 2025

The presence of dead broilers within a flock can be significant vectors for disease transmission and negatively impact the overall welfare of the remaining broilers. This study introduced a dead broiler detection method that leverages the fact that dead broilers remain stationary within the flock in videos. Dead broilers were identified through the analysis of the historical movement information of each broiler in the video. Firstly, the frame difference method was utilized to capture key frames in the video. An enhanced segmentation network, YOLOv8-SP, was then developed to obtain the mask coordinates of each broiler, and an optical flow estimation method was employed to generate optical flow maps and evaluate their movement. An average optical flow intensity (AOFI) index of broilers was defined and calculated to evaluate the motion level of each broiler in each key frame. With the AOFI threshold, broilers in the key frames were classified into candidate dead broilers and active live broilers. Ultimately, the identification of dead broilers was achieved by analyzing the frequency of each broiler being judged as a candidate death in all key frames within the video. We incorporated the parallelized patch-aware attention (PPA) module into the backbone network and improved the overlaps function with the custom power transform (PT) function. The box and mask segmentation mAP of the YOLOv8-SP model increased by 1.9% and 1.8%, respectively. The model’s target recognition performance for small targets and partially occluded targets was effectively improved. False and missed detections of dead broilers occurred in 4 of the 30 broiler testing videos, and the accuracy of the dead broiler identification algorithm proposed in this study was 86.7%.
Applications of Raspberry Pi for Precision Agriculture—A Systematic Review
Authors: Joice Astina , Tufaique Talha , Tazeen Humeera , Igathinathane C. , Zhang Zhao , Whippo Craig , Hendrickson John , Archer David
Published: January 2025

Precision agriculture (PA) is a farm management data-driven technology that enhances production with efficient resource usage. Existing PA methods rely on data processing, highlighting the need for a portable computing device for real-time, infield decisions. Raspberry Pi, a cost-effective multi-OS single-board computer, addresses this gap. However, information on Raspberry Pi’s use in PA remains limited. This review consolidates details on Raspberry Pi versions, sensors, devices, algorithm deployment, and PA applications. A systematic literature review of three academic databases (Scopus, Web of Science, IEEE Xplore) yielded 84 (as of 22 November 2024) articles based on four research questions and screening criteria (exclusion and inclusion). Narrative synthesis and subgroup analysis were used to synthesize the results. Findings suggest Raspberry Pi can be a central unit to control sensors, enabling cost-effective automated decision support for PA, particularly in plant disease detection, site-specific weed management, plant phenotyping, biomass estimation, and irrigation systems. Despite focusing on these areas, further research is essential on other PA applications such as livestock monitoring, UAV-based applications, and farm management software. Additionally, Raspberry Pi can be used as a valuable learning tool for students, researchers, and farmers and can promote PA adoption globally, helping stakeholders realize its potential.
Detecting Malicious .NET Executables Using Extracted Methods Names
Authors: Thabit Hamdan , Ahmad Rami , Abdullah Ahmad , Abualkishik Abedallah Zaid , Alwan Ali A.
Published: January 2025

The .NET framework is widely used for software development, making it a target for a significant number of malware attacks by developing malicious executables. Previous studies on malware detection often relied on developing generic detection methods for Windows malware that were not tailored to the unique characteristics of .NET executables. As a result, there remains a significant knowledge gap regarding the development of effective detection methods tailored to .NET malware. This work introduces a novel framework for detecting malicious .NET executables using statically extracted method names. To address the lack of datasets focused exclusively on .NET malware, a new dataset consisting of both malicious and benign .NET executable features was created. Our approach involves decompiling .NET executables, parsing the resulting code, and extracting standard .NET method names. Subsequently, feature selection techniques were applied to filter out less relevant method names. The performance of six machine learning models—XGBoost, random forest, K-nearest neighbor (KNN), support vector machine (SVM), logistic regression, and naïve Bayes—was compared. The results indicate that XGBoost outperforms the other models, achieving an accuracy of 96.16% and an F1-score of 96.15%. The experimental results show that standard .NET method names are reliable features for detecting .NET malware.
In a Changing World—An Economical Comparison Between Traditional and Wet-And-Drought-Resistant Grasses in Swedish Cattle Production Under Different Weather Scenarios
Authors: Holmström Kristina , Kumm Karl-Ivar , Andersson Hans , Jardstedt Mikaela , Sousa Dannylo , Hessle Anna
Published: January 2025

This study compared the profitability when feeding silages of different grass species in enterprises with either dairy cows, beef breed bulls, or beef suckler cows. Traditional (TR) grasses timothy and meadow fescue was compared to the alternative wet-and-drought-resistant (WD) grasses tall fescue, festulolium, and reed canary grass in three different weather scenarios with either normal conditions (Ref), delayed late harvest time due to wet weather conditions (Wet), or decreased grass yield due to dry weather conditions (Dry). Contribution margin calculation was conducted for three geographical regions in Sweden. In the Ref and Wet scenarios, TR was more competitive than WD for dairy cows and beef bulls in all regions. Also in the Dry scenario, TR was more competitive than WD for dairy cows, as the lower production cost of the WD was outweighed by a lower milk yield of cows fed WD compared to cows fed TR. Contrary, for beef bulls, WD gave a higher contribution margin than TR did in the Dry scenario, where the break-even for WD being superior over TR occurred when more than every second year was dry. WD reed canary grass was always more competitive than TR and WD festulolium for beef cows.
Antimicrobial Resistance and Environmental Health
Authors: Abia Akebe Luther King
Published: January 2025

If left unaddressed, the casualties due to or associated with antimicrobial resistance (AMR) may surpass those associated with all pandemics humanity has ever experienced [...]
Evaluation of Residues of Amazonian Fruit Piquia (Caryocar villosum) as Sustainable Ingredient for Sunscreen and Cosmetic Formulations
Authors: de Souza Izadora , Grimmelprez Gabriella C. P. , Yamaguchi Klenicy K. L. , Schleusener Johannes , Lohan Silke B. , Meinke Martina C. , Gaspar Lorena R.
Published: January 2025

Amazonian fruit residues like piquia shells are often discarded despite their antioxidant potential for sustainable cosmetic use. This study evaluated the photostability, phototoxicity, and photoprotection of hydroalcoholic piquia shell extract (PqSE) combined with UV filters in solutions and cosmetic formulations. PqSE formulations were photostable, even stabilizing photounstable UV filters. Phototoxicity tests (OECD TG 432) showed no phototoxic potential (MPE < 0.15) and reduction in the phototoxic potential of UV filters, while ocular irritation potential via HET-CAM assay indicated no irritant effects. The extract combined with UV filters enhanced protection against UVA-induced reactive oxygen species (ROS) production, achieving 60.9% effectiveness, outperforming commercial photostabilizers. Against UVB radiation, it showed cellular viability above 80%, comparable to benzophenone-3. PqSE formulations exhibited a radical protection factor (RPF) nine times higher than controls and reduced radical production by 64% after visible/near-infrared (VIS/NIR) irradiation on porcine skin, compared to 38% for controls. Confocal Raman microspectroscopy showed penetration depths below 12 µm for all time points. This study highlights the potential of reusing fruit residues like PqSE as sustainable, effective ingredients in sunscreen formulations, offering enhanced photoprotection and reduced environmental waste.
Dual-Band Shared-Aperture Antenna with Pattern and Polarization Diversity
Authors: Cheng Jia , Gao Tianyu , Han Dongpeng , Zhou Changfei
Published: January 2025

This paper proposes a dual-band co-aperture antenna, which covers 2.09–11.61 GHz (9.52 GHz, 138.9%) and 21.6–29.6 GHz (8 GHz, 31%). The overall size of the proposed antenna is 0.76 × 0.76 × 0.37 λ03, where λ0 is the free space wavelength of the lowest operating frequency of 2.09 GHz. By removing the internal metal of the monopole antenna and adding a Vivaldi antenna at the bottom of the bowl monopole antenna, dual-band radiation characteristics can be achieved. A medium polarization converter is used to achieve circular polarization and improve the broadside gain in the high-frequency band. The simulation results show that the antenna has a stable omnidirectional radiation pattern in the low-frequency band and a directional radiation pattern in the high-frequency band.
Intramedullary Stress and Strain Correlate with Neurological Dysfunction in Degenerative Cervical Myelopathy
Authors: Rahman Mahmudur , Banurekha Devaraj Karthik , Chauhan Omkar , Harinathan Balaji , Yoganandan Narayan , Vedantam Aditya
Published: January 2025

Degenerative cervical myelopathy (DCM) is characterized by progressive neurological dysfunction, yet the contribution of intramedullary stress and strain during neck motion remains unclear. This study used patient-specific finite element models (FEMs) of the cervical spine and spinal cord to examine the relationship between spinal cord biomechanics and neurological dysfunction. Twenty DCM patients (mean age 62.7 ± 11.6 years; thirteen females) underwent pre-surgical MRI-based modeling to quantify von Mises stress and maximum principal strains at the level of maximum spinal cord compression during simulated neck flexion and extension. Pre-surgical functional assessments included hand sensation, dexterity, and balance. During flexion, the mean intramedullary stress and strain at the level of maximum compression were 7.6 ± 3.7 kPa and 4.3 ± 2.0%, respectively. Increased intramedullary strain during flexion correlated with decreased right-hand sensation (r = −0.58, p = 0.014), impaired right-hand dexterity (r = −0.50, p = 0.048), and prolonged dexterity time (r = 0.52, p = 0.039). Similar correlations were observed with intramedullary stress. Patients with severe DCM exhibited significantly greater stress during flexion than those with mild/moderate disease (p = 0.03). These findings underscore the impact of dynamic spinal cord biomechanics on neurological dysfunction and support their potential utility in improving DCM diagnosis and management.
Personal Identification Using Embedded Raspberry Pi-Based Face Recognition Systems
Authors: Pecolt Sebastian , Błażejewski Andrzej , Królikowski Tomasz , Maciejewski Igor , Gierula Kacper , Glowinski Sebastian
Published: January 2025

Facial recognition technology has significantly advanced in recent years, with promising applications in fields ranging from security to consumer electronics. Its importance extends beyond convenience, offering enhanced security measures for sensitive areas and seamless user experiences in everyday devices. This study focuses on the development and validation of a facial recognition system utilizing a Haar cascade classifier and the AdaBoost machine learning algorithm. The system leverages characteristic facial features—distinct, measurable attributes used to identify and differentiate faces within images. A biometric facial recognition system was implemented on a Raspberry Pi microcomputer, capable of detecting and identifying faces using a self-contained reference image database. Verification involved selecting the similarity threshold, a critical factor influencing the balance between accuracy, security, and user experience in biometric systems. Testing under various environmental conditions, facial expressions, and user demographics confirmed the system’s accuracy and efficiency, achieving an average recognition time of 10.5 s under different lighting conditions, such as daylight, artificial light, and low-light scenarios. It is shown that the system’s accuracy and scalability can be enhanced through testing with larger databases, hardware upgrades like higher-resolution cameras, and advanced deep learning algorithms to address challenges such as extreme facial angles. Threshold optimization tests with six male participants revealed a value that effectively balances accuracy and efficiency. While the system performed effectively under controlled conditions, challenges such as biometric similarities and vulnerabilities to spoofing with printed photos underscore the need for additional security measures, such as thermal imaging. Potential applications include access control, surveillance, and statistical data collection, highlighting the system’s versatility and relevance.
Acute Effects of a Simulated Karate Bout on Muscular Strength Asymmetries of the Lower Limbs in Elite Athletes of Different Age Categories
Authors: Gaweł Eliza , Drozd Miłosz , Maszczyk Adam , Zając Adam
Published: January 2025

This study aimed to assess the acute impact of a simulated kumite bout (WKF formula) on peak isometric strength performance of the dominant and non-dominant lower limbs in elite karate athletes of different age categories (U16, U18, Senior), in the context of inter-limb asymmetry. Sixty-one elite male and female athletes (age = 17.48 ± 3.26 [years], body height = 1.72 ± 0.08 [m], body mass = 63.79 ± 10.00 [kg]) participated in this study, which included a randomized crossover design (two experimental sessions under two different conditions). Inter-limb asymmetry was assessed based on the isometric mid-thigh pull test. Friedman’s test indicated significant differences in the mean values of the peak vertical force (PVF) between the assessed limbs (test = 10.8; p = 0.013; Kendall’s W = 0.059). Elite karate athletes, regardless of the age category, tend to have inter-limb strength asymmetries in the lower extremities; however, the impact of a simulated kumite bout was not fully confirmed. A kumite bout seems to have a favorable impact on bilateral asymmetries in U16 and U18 athletes, but not in Seniors, who seem to be at increased risk of injury after completing the bout (asymmetry > 15%). Limb dominance is not necessarily related to greater values of PVF.
Exploring Embodiment Form Factors of a Home-Helper Robot: Perspectives from Care Receivers and Caregivers
Authors: Tsui Katherine M. , Baggett Rune , Chiang Carol
Published: January 2025

Society’s aging is a worldwide crisis that affects many countries, as the Older Adult (OA) population is growing faster than younger populations. With this, there are fewer caregivers (CGs), and more care receivers (CRs) exist. It is vital to understand how we can ease the burden of caregiving on both the care receivers’ and caregivers’ sides. Our research focuses on robotic mobility and stability assistance for independent living OAs. We draw upon best practices from Occupational Therapy for sit-to-stand (STS) transfer techniques and question what sit-to-stand could look like if performed by a robot. Drawing inspiration from assistive devices, we designed 3 robot embodiments: a humanoid robot, a pair of robots, and a simple pole robot. We conducted a cross-cultural study with 24 CR and CG focus groups in both the United States and Japan to understand OAs’ preferences and expected functionality for continued independence in their homes. Our findings show that, from the perspectives of both CRs and CGs in both countries, TRIbot, the humanoid robot was the most preferred (Japan 34 of 48 participants; 70.8% and US 24 of 43 participants; 55.8%) for caregiving tasks as it was perceived to be the most capable of providing increased assistance as OAs age. Additionally and unsurprisingly, OAs expected the robot to perform general household tasks and that they would speak to the robot. We contextualize our results within the rising popularity of humanoid robots and the desire for general purpose Artificial Intelligence.
FANT: Flexible Attention-Shifting Network Telemetry
Authors: Cui Mingwei , Peng Yufan , Yang Fan
Published: January 2025

As data center networks grow in scale and complexity, the active inband network telemetry (AINT) system collects a broader range of network status metrics to provide comprehensive visibility for AINT-related network applications, but it also leads to higher measurement costs. To address this issue, we introduce the Flexible Attention-shifting Network Telemetry (FANT), which dynamically focuses on critical links in each measurement cycle. Specifically, FANT employs a metric categorization strategy that divides all measurement metrics into two categories: basic measurements, which are lightweight but cover fewer metrics, and detailed measurements, which are comprehensive but incur higher overhead. Based on the analysis of the previous cycle’s measurements, FANT identifies which links are suspicious and then activates certain probe traces through an attention-shifting mechanism to collect detailed measurements of these links in the current cycle. To further save bandwidth, we model the attention-shifting process and apply heuristic algorithms to solve it. Our experiments show that FANT effectively supports the operation of ANT network applications. In a fat-tree topology with 30 pods, FANT significantly reduces bandwidth usage to 42.6% of the state-of-the-art solution. For scenarios requiring rapid computation, FANT can accelerate algorithm execution 105× by setting acceleration factors, with only a 6.4% performance loss.
Calcium-Rich Biochar Derived from Cactus Feedstock and Its Efficient Adsorption Properties for Industrial Dye
Authors: Maaoui Assia , Chagtmi Raouia , Apicella Barbara , Cerciello Francesca , Senneca Osvalda , Trabelsi Aida Ben Hassen
Published: January 2025

The leather industries are large producers of industrial wastewater. The present work investigated the performance of calcium-rich biochar derived from cactus cladodes (CCB) as an adsorbent in the treatment of this wastewater. Biochar samples (CCB500, CCB600, and CCB700) were produced by slow pyrolysis at 500, 600, and 700 °C and tested as adsorbents of Repanil Blue (RB) dye. The tests were carried out under various experimental conditions. The RB dye removal increased with the contact time, adsorbent dose, and concentration. With dye concentrations between 10 and 125 mg/L, removal efficiencies of 80, 80 and 100% were reached using CCB500, CCB600, and CCB700, respectively. The Langmuir model and the pseudo-second-order model described chemisorption with a high correlation factor (R2). The highest adsorption capacity of 56 mg/g was obtained with CCB700 within 5 min. The results strongly suggest that calcium-rich biochars are promising adsorbents for the removal of RB dye from aqueous solutions.
Hybrid-Driven Dynamic Position Prediction of Robot End-Effector Integrating Parametric Dynamic Model and Machine Learning
Authors: Ni Hepeng , Xu Cong , Ye Yingxin , Chen Bo , Luo Shuangsheng , Ji Shuai
Published: January 2025

Accurate dynamic model and response prediction of industrial robots (IRs) are prerequisites for production optimization before actual operation. In this study, a hybrid-driven dynamic position prediction (HDPP) approach integrating a parametric dynamic model (PDM) and learning-based residual error compensators (RECs) is developed to estimate the actual position of a robot end-effector based on the reference input trajectory. Firstly, a PDM consisting of a flexible dynamic model of the mechanical system and a servo system model is constructed as the primary predictor in HDPP. Meanwhile, a reinforcement learning (RL)-based parameter identification method is presented to obtain independent dynamic parameters, which integrates a CAD model, least squares estimation, and RL. Then, an REC based on the temporal convolutional network long short-term memory (TCN-LSTM) is proposed for each joint to compensate for the residual error after PDM prediction. A TCN is employed as the input of LSTM to extract and compress the discontinuous features, which can enhance the compensator’s accuracy and stability. Additionally, a dynamics-integrated (DI) dataset construction scheme is developed for network training to boost the prediction accuracy. Finally, a series of experiments and comparative analysis are preformed to validate the performance of HDPP in terms of prediction accuracy and stability.
Impact of Branch Pipe Valve Closure Procedures on Pipeline Water Hammer Pressure: A Case Study of Xinlongkou Hydropower Station
Authors: Li Zilong , Jin Jin , Pan Zhanpeng , Sun Jianren , Geng Kaiqiang , Qiao Yu
Published: January 2025

To investigate the impact of different valve closure strategies on water hammer pressure variations in pipelines and terminal valves under accident conditions, this study focuses on the Xinlongkou Hydropower Station water conveyance project. The Bentley Hammer calculation software was used to simulate the changes in water hammer pressure in the pipeline and unit terminal valves under various valve closure scenarios. Additionally, computational fluid dynamics (CFD) was applied to analyze the dynamic effects of different factors on the water hammer in the branch pipelines of the station. The results showed that shorter valve closure times resulted in higher peak water hammer pressures, with the maximum pressure occurring at the terminal valve. Extending the valve closure time effectively reduced both the peak pressure and number of pressure oscillations at the terminal valve, with pressure fluctuations stabilizing within approximately 30 s. Two-stage valve closures led to water hammer pressures 8–14.1% higher than those from one-stage linear closures. Based on these findings, it is recommended that stations adopt a valve closure time greater than 9 s during load shedding or implement a combined strategy of fast closure (60%) and slow closure (40%). The study also revealed that the primary factors influencing the water hammer are valve closure time, number of valves, valve diameter, and valve distance, in that order, with the distance having a relatively minor impact. The results of this study provide valuable insights into valve closure strategies for water conveyance projects.
Automated Fillet Weld Inspection Based on Deep Learning from 2D Images
Authors: Diaz-Cano Ignacio , Morgado-Estevez Arturo , Rodríguez Corral José María , Medina-Coello Pablo , Salvador-Dominguez Blas , Alvarez-Alcon Miguel
Published: January 2025

This work presents an automated welding inspection system based on a neural network trained through a series of 2D images of welding seams obtained in the same study. The object detection method follows a geometric deep learning model based on convolutional neural networks. Following an extensive review of available solutions, algorithms, and networks based on this convolutional strategy, it was determined that the You Only Look Once algorithm in its version 8 (YOLOv8) would be the most suitable for object detection due to its performance and features. Consequently, several models have been trained to enable the system to predict specific characteristics of weld beads. Firstly, the welding strategy used to manufacture the weld bead was predicted, distinguishing between two of them (Flux-Cored Arc Welding (FCAW)/Gas Metal Arc Welding (GMAW)), two of the predominant welding processes used in many industries, including shipbuilding, automotive, and aeronautics. In a subsequent experiment, the distinction between a well-manufactured weld bead and a defective one was predicted. In a final experiment, it was possible to predict whether a weld seam was well-manufactured or not, distinguishing between three possible welding defects. The study demonstrated high performance in three experiments, achieving top results in both binary classification (in the first two experiments) and multiclass classification (in the third experiment). The average prediction success rate exceeded 97% in all three experiments.
Perspectives on Soft Actor–Critic (SAC)-Aided Operational Control Strategies for Modern Power Systems with Growing Stochastics and Dynamics
Authors: Liu Jinbo , Guo Qinglai , Zhang Jing , Diao Ruisheng , Xu Guangjun
Published: January 2025

The ever-growing penetration of renewable energy with substantial uncertainties and stochastic characteristics significantly affects the modern power grid’s secure and economical operation. Nevertheless, coordinating various types of resources to derive effective online control decisions for a large-scale power network remains a big challenge. To tackle the limitations of existing control approaches that require full-system models with accurate parameters and conduct real-time extensive sensitivity-based analyses in handling the growing uncertainties, this paper presents a novel data-driven control framework using reinforcement learning (RL) algorithms to train robust RL agents from high-fidelity grid simulations for providing immediate and effective controls in a real-time environment. A two-stage method, consisting of offline training and periodic updates, is proposed to train agents to enable robust controls of voltage profiles, transmission losses, and line flows using a state-of-the-art RL algorithm, soft actor–critic (SAC). The effectiveness of the proposed RL-based control framework is validated via comprehensive case studies conducted on the East China power system with actual operation scenarios.
Implementation Aspects in Simulation Extrapolation-Based Stocking–Lord Linking
Authors: Robitzsch Alexander
Published: January 2025

Stocking–Lord (SL) linking is commonly used for group comparisons based on dichotomous item responses. Recently, the simulation extrapolation (SIMEX) method for SL linking has been introduced within the two-parameter logistic (2PL) model to reduce the bias due to the presence of random differential item functioning (DIF). However, the original SIMEX approach can be computationally complex. This article evaluates two computational shortcuts to SIMEX-based SL linking through a simulation study: a quasi-Monte Carlo method that replicates items and a proposal using an approximate noniterative estimation instead of the iterative one in the SIMEX application of SL linking. The results demonstrate that these shortcuts yield linking parameter estimates with comparable statistical properties.
Effects of a 12-Week Semi-Immersive Virtual Reality-Based Exercise Program on the Quality of Life of Older Adults Across Different Age Groups: A Randomized Controlled Trial
Authors: Wang Li-Ting , Wang Yu-Wen
Published: January 2025

Aging may affect quality of life (QOL). This study aimed to evaluate the impact of semi-immersive VR-based exercise on the QOL of young-old and middle-old adults. This study was a randomized controlled trial involving older adults aged 65–85 years. Methods: Two age groups were each randomly assigned to experimental (EG) and control (CG) groups. The EG underwent a 75–90 min semi-immersive VR-based exercise intervention twice a week for 12 weeks, whereas the CG continued with their usual daily activities. Each participant’s psychological QOL was assessed using the World Health Organization’s QOL Instrument-Older Adults Module (WHOQOL-OLD). Results: Compared with their CG counterparts, the EG older adults exhibited significantly higher QOL scores in four WHOQOL-OLD dimensions (i.e., sensory abilities, autonomy, social participation/isolation, and death and dying) and had a superior overall QOL. Furthermore, we observed significant decreases in the autonomy and overall QOL dimensions in CG older adults. On comparing the young-old and middle-old adults, a significant decrease in the past, present, and future activity QOL dimension was exclusively found in CG young-old adults. Conclusions: Semi-immersive VR-based exercise is a promising digital tool for supporting the psychological QOL of older adults across different age groups. This suggests that older persons, particularly young-old adults, should be encouraged to maintain physical activity habits in their daily lives in order to improve their QOL.
Influence of the Radial Gap on the External Gear Pump Performance
Authors: Mitov Alexander , Nikolov Nikolay , Kralov Ivan
Published: January 2025

The paper presents a numerical and experimental study of the radial gap influence on the external gear pump performance. The numerical study is performed with a two-dimensional (2D) computational fluid dynamics (CFD) model developed and advanced in previous authors’ works. The experimental study is carried out on a laboratory test bench. The presented numerical results are accurate in the entire operating range (500–3500 RPM) of the pump, which is confirmed by comparisons between the CFD results, experimental data, and manufacturer’s technical documentation. The comparative analysis shows that the differences obtained during the verifications are in the range of −6.44% to 2.48%. An original methodology has been developed that allows us to obtain the volumetric efficiency and overall efficiency characteristics as a function of the rotation frequency of the pump at different values of the radial gap, using the manufacturer’s data for the same characteristics at a nominal radial gap and the results of CFD simulations. The analysis of the numerical and experimental results shows that a gap size of 0.04 mm is close to the limit value for the investigated pump, if it is not operated at a rotational frequency above the nominal. The presented methodology can also be applied to other types of hydraulic displacement pumps in order to evaluate their performance in the wear process and to predict the maximum allowable value of a specific design parameter under different operating modes.