bluuebunny/crossref_metadata_2025 huggingface dataset:
Ecomorphology of yellowtail lambari (Characiformes: Characidae) in the neotropical semi-arid region, Brazil
Authors: França Elton José de , Magalhães Pedro Henrique Marins , Mendes Renata Akemi Shinozaki , Ribeiro Leonardo Barros
Published: May 2024

The ecomorphological patterns of the Astyanax lacustris in different environments (lotic and lentic) of the semiarid region of Pernambuco were analyzed using 25 linear morphometric measurements on 240 specimens (120 males and 120 females), with standard lengths ranging from 24.25 to 91.50 mm. These data were converted into 16 ecomorphological attributes and correlated with environmental characteristics. The principal component analysis (PCA) explained 81.64% (first and second components) of the data variation, highlighting sexual dimorphism in specimen size and noticeable variation among individuals of the same sex in different environments. Specimens from lotic environments showed higher caudal peduncle compression index (CPCI) values, while the pectoral fin aspect ration (PFAR) was more pronounced in lentic environments. Overall, females exhibited a wide morphometric variation. Analysis of linear morphometry in different water bodies indicated an intrinsic variation related to hydrodynamics linked to sexual dimorphism and water flow speed. Further studies are suggested to investigate whether factors such as macrophytes and different levels of water depth and flow contribute to this morphometric variation of species in the semi-arid region.
Distraction Osteogenesis Reconstruction Following Resection of Bone Sarcomas
Authors: Bozzo Anthony , Aysola Varun , Yeung Caleb M. , Healey John H. , Prince Daniel E.
Published: May 2024

Background:

While sustainable long-term function has been established for biological reconstruction with distraction osteogenesis (DO) following osseous resections, there is a paucity of published data informing surgeons and patients on important milestones in the reconstructive process. The objectives of this study were to determine when to expect complete bone healing and full weight-bearing as well as to quantify the influence of chemotherapy on the osseous regeneration process.

Methods:

Prospectively, pathological and clinical data were collected for 30 consecutive patients who underwent primary or secondary DO-based reconstruction following osseous resection from 2018 to 2021. Serial radiographs indicated the times to cortex formation and full union. An unpaired t test was used to compare the time required for full bone remodeling of segments transported with and without concurrent chemotherapy.

Results:

The average resection length was 13.6 cm (range, 4 to 22 cm). Patients underwent an average of 6.1 procedures (range, 1 to 14 procedures). Half (50%) of all procedures were planned, while half were unplanned procedures. All patients achieved full, independent weight-bearing at a median of 12 months (interquartile range [IQR], 9 to 16 months). For the 34 segments transported concurrently with chemotherapy, the mean bone healing index (BHI) was 2.3 ± 0.7, and the mean BHI was 1.2 ± 0.4 for the 25 segments without chemotherapy at any point during their transport (p < 0.0001).

Conclusions:

All 30 patients achieved full bone healing and independent weight-bearing at a median of 1 year postoperatively and continued to show functional improvement afterward. Surgeons and patients can expect bone healing to be nearly twice as fast for segments transported after completion of systemic chemotherapy compared with segments transported concurrently with adjuvant chemotherapy.

Level of Evidence:

Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.
A Successful Clinical Outcome 29 Months Following Improper Placement of the Compress Implant
Authors: Schultz Kathryn , Tadepalli Vaibhav , Domson Gregory
Published: May 2024

Case:

A 24-year-old woman presented with dedifferentiated parosteal osteosarcoma of the proximal femur and was treated with limb salvage surgery using the Compress implant. It was implanted with a technical error, was not revised, and has demonstrated no negative outcomes 29 months postoperatively.

Conclusion:

An instance of incorrect pin placement during the implantation of a Zimmer Compress implant is presented with good survivorship. This report acts as information for other surgeons who might inadvertently obtain unicortical fixation. In this patient, revision surgery was avoided and an excellent, short-term outcome was achieved while avoiding the potentially devastating complications associated with revision implantation.
Electric Vehicle Adoption for Sustainable Economic Growth in Greater Madura
Authors: Saadah Siti , Ahmadi Raden Khaeru , Ainorofiqi Ainorofiqi
Published: May 2024

In the context of global sustainability challenges, the transition from fossil fuel dependency to greener alternatives in transportation is vital. The Greater Madura region of Indonesia, with its substantial natural resources and escalating mobility needs, presents a unique opportunity for implementing electric vehicles (EVs) as a sustainable solution. This study explores the barriers to and facilitators of EV adoption in this region through qualitative methods including interviews and expert judgements with stakeholders across government, industry, academia, and the consumer base. The findings reveal that while there is significant potential for EVs to contribute to green economic growth, challenges such as inadequate charging infrastructure and limited public awareness persist. However, strategic investments in infrastructure, comprehensive policy support, and enhanced public engagement are identified as critical drivers for successful EV integration. The study underscores the importance of multi-stakeholder collaboration in achieving sustainable mobility and economic development in Greater Madura.Highlights: The study identifies critical infrastructural and regulatory barriers to electric vehicle adoption in Greater Madura. It highlights the role of multi-sectoral collaboration in fostering a supportive environment for electric vehicles. The research emphasizes the need for increased public awareness and engagement to facilitate the shift to electric vehicles. Keywords: electric vehicles, green economy, sustainable development, infrastructure development, stakeholder collaboration
Revealing Global Influences on Organizational Behavior
Authors: Julianto Julianto , Sari Herlinda Maya Kumala
Published: May 2024

This study examines the impact of work motivation, career development, and work environment on Organizational Citizenship Behavior (OCB) among employees of PT Coca Cola Europacific Partners Indonesia Pasuruan Plant. Using a quantitative approach with 60 respondents selected through saturated sampling, data analysis was conducted using SPSS version 24. The results indicate that work motivation and work environment significantly influence OCB, while career development has a positive but non-significant effect. Additionally, the combined effect of these factors significantly influences OCB. These findings underscore the importance of fostering a supportive work environment and promoting work motivation to enhance OCB, while also emphasizing the need for providing adequate career development opportunities. Understanding these factors can aid in developing strategies to promote a positive organizational culture and improve overall organizational performance.
Hightlight:

Work motivation and environment influence OCB significantly.
Career development positively affects OCB but not significantly.
Understanding OCB factors enhances organizational performance.

Keywords: Work Motivation, Career Development, Work Environment, Organizational Citizenship Behavior (OCB), PT Coca Cola Europacific Partners Indonesia.
Instagram Marketing Boosts Sales for Small Businesses
Authors: Rahmah Fiqih Arina , Rochmaniah Ainur
Published: May 2024

This study explores the utilization of Instagram as a promotional tool for Dhe Gedangku, a small-scale microbusiness in Gempol District. Through qualitative descriptive analysis and case study method, data were gathered from in-depth interviews with the owner and followers of @dhegedangkuofficial. Findings reveal that Instagram significantly increases product awareness and sales, with a 45% sales increase noted. However, there is a gap in maximizing product promotion, particularly in terms of innovation and packaging. Dhe Gedangku offers products at affordable prices, targeting students and young adults, and utilizes strategic location selection and Instagram's geo-tagging feature to attract customers. The study underscores the importance of businesses focusing on innovation, packaging, pricing strategies, and strategic location selection to maximize Instagram's potential in marketing small businesses, offering insights for businesses seeking to enhance their social media marketing strategies.
Hightligh:

Instagram Promotion: Boosts sales and product visibility for small businesses.
Affordable Pricing: Targets students and young adults with budget-friendly prices.
Strategic Location: Uses geo-tagging to attract customers to small business locations.

Keywords: Instagram, Small Business, Promotional Tool, Social Media Marketing, Microbusiness
Global Impact of Top Management on Branding and Performance
Authors: Rochman Saiful , Hermawan Sigit
Published: May 2024

This study explores how top management commitment to ISO 9001:2015 quality management system influences company branding and employee performance, with employee commitment moderating this relationship. Conducted in a cardboard packaging industry in Sidoarjo, East Java, Indonesia, the research involved 105 employees selected through purposive sampling. Data was collected via personal questionnaire surveys and analyzed using Structural Equation Modeling Partial Least Square (SEMPLS). Results show that top management commitment significantly impacts company branding and employee performance. However, employee commitment's moderating effect on the relationship between top management commitment and company branding was found insignificant due to incomplete socialization of the quality management system among employees, while it significantly moderated the relationship between top management commitment and employee performance. This study underlines the importance of top management commitment in ISO 9001:2015 implementation for improving company branding and employee performance and suggests the need for comprehensive socialization of quality management systems.
Hightligh:

Top management drives branding and performance.
Employee commitment moderates top management's influence.
Incomplete socialization affects employee commitment's moderating effect.

Keywords: ISO 9001:2015, Top management commitment, Company branding, Employee performance, Moderation.
Global Impact of Musical Extracurriculars on Cultural Enrichment
Authors: Solikha Nurul Lailiyatus , Linggo Wati Tri
Published: May 2024

This study explores how musical extracurricular activities at SD Muhammadiyah 1 Taman foster cultural appreciation and patriotism among elementary students in Indonesia. Using qualitative methods like observation, interviews, and document analysis, the research unveils effective collaboration between stakeholders, student enthusiasm, and character development. The findings underscore the importance of such activities in promoting cultural awareness and preserving local heritage, highlighting the need for continued support and integration in educational curricula.
 
Highlight:

Collaborative stakeholders ensure successful musical extracurricular implementation.
Activities nurture tolerance, patriotism, and cultural appreciation among students.
Integration into curricula vital for preserving and promoting local cultural heritage.

 
Keyword: Musical extracurricular activities, Cultural appreciation, Elementary education, Stakeholder collaboration, Character development
Interactive Media Revolutionizes Education, Boosting Global Student Engagement
Authors: Seto Armanda Bayu Rangga , Hasanah Fitria Nur
Published: May 2024

This study focuses on developing desktop-based interactive learning media, "MISTAR," to address challenges such as student boredom and comprehension difficulties in computer lab settings. Using the ADDIE method, the research involved interviews with a network systems administration teacher, observations of X-grade TKJ students, and expert validation. Results showed high feasibility (88% media expert validation, 91% subject matter expert validation, and 90.8% average from limited-scale trials), indicating strong potential for improving engagement and understanding in educational environments. Further research is recommended to explore implementation and effectiveness in schools.
 
Highlight:

Improved Learning Experience: Interactive media development enhances student engagement effectively.
Expert Validation: High feasibility validated by media and subject matter experts.
Educational Impact: Interactive media improves understanding in computer lab environments.

 
Keyword: Interactive Learning Media, ADDIE Method, Feasibility Evaluation, Engagement Improvement, Educational Research
Temporal Context Modeling for Enhanced Video Content Retrieval and Moment Detection
Authors: Singh Pratibha , Kushwaha Alok Kumar Singh
Published: May 2024

Identifying relevant moments in video content using natural language queries is a challenging task, especially in the era of exponential growth in video content. Existing solutions need to detect relevant moments by capturing the global context of videos and surpassing local temporal correlations. In this paper, we propose a novel and comprehensive framework for video content retrieval and moment detection based on natural language queries. Our framework centers on a novel temporal context modeling approach that captures and exploits long-range dependencies and contextual information across different time scales. We also integrate a specialized encoder-decoder model with multi-modal intent to extract intricate temporal patterns and context from video data and understand the user's intent. To address the challenge of temporal variance, a prominent obstacle in moment retrieval, we harness the power of our temporal context modeling. Our approach handles these changes, resulting in more accurate content retrieval and analysis. We conducted a comprehensive comparative study on available datasets using recall (R@1, R@5) emphasize ranking accuracy for top highlights and mean average precision (map) assesses overall ranking quality, prioritizing relevance to the query across multiple recall levels. Our experimental findings show the superior performance of the proposed framework compared to existing methods. Incorporating the multi-modal intent technique and the innovative temporal context modeling enhance the ability to identify relevant moments and highlights. Our proposed framework is a novel approach to video content retrieval and moment detection that has the potential to revolutionize the way we interact with video content.
Inhibition of primary cilia-hedgehog signaling axis triggers autophagic cell death and suppresses malignant progression of VHL wild-type ccRCC
Authors: Huang Yan , Tian Shuo , Du Songliang , Wang Chenfeng , zhang yu , Wang Hanfeng , fan yang , gao yu , Gu Liangyou , Huang Qingbo , Wang Baojun , ma xin , Zhang Xu
Published: May 2024

Primary cilia are present on renal tubules and are implicated to play pivotal role in transducing signals during development; however, the oncogenic role of cilia in clear cell renal cell carcinoma (ccRCC) has not been examined. Here we show that VHL wild-type ccRCC cell lines have high incidence of primary cilia, and high frequency of primary cilia is positively correlated with VHL expression and poor prognosis. Besides, depletion Kif3a or Ift88, genes required for ciliogenesis, significantly inhibited tumor proliferation and metastasis in vitro and in vivo. Further analysis found that mutations of key genes in hedgehog signaling are enriched in VHL wild ccRCC, its downstream signaling activation depends on ciliogenesis. Moreover, depletion of primary cilia or suppression of hedgehog pathway activation with inhibitor induced robust autophagic cell death. Collectively, our findings revealed that primary cilia could serve as a diagnostic tool and provide new insights into the mechanism of VHL wild-type ccRCC progression. Targeting primary cilia-hedgehog pathway may represent an effective therapeutic strategy for VHL wild-type ccRCC.
Carbon Management in Large-Scale Electric Vehicle Temporal and Spatial Scheduling with Automotive Electronic Forensics
Authors: Cao Yongsheng , Zeng Guangquan , Zhao Caiping
Published: May 2024

Electric vehicles (EVs) offer a promising and environmentally friendly solution to reduce reliance on fossil fuels. As the adoption of electric vehicles and solar power grows, both opportunities and challenges are presented for power systems. An increasing EV fleet, paired with more distributed solar generation, brings both promise and complexity to grid operations. High penetration levels of EVs and rooftop photovoltaics will complicate load forecasting and add variability that power systems were not traditionally designed to accommodate. This study focuses on the collaborative optimization scheduling of generators, EVs, and solar power to address this issue. A novel approach is proposed in this paper, involving a two-layer optimization problem for the distribution systems. This strategy aims to optimize the charging and discharging schedules of EVs in both time and space domains while considering solar power and digital evidence collection. In the upper layer problem, the coordination between EVs, thermal generators, and base load is optimized in the transmission grid, taking into account the availability of solar power. This optimization problem aims to determine the optimal periods for EV charging with digital evidence collection in the time domain. We focus on the spatial scheduling of EV load in the distribution grid in the lower layer problem. To evaluate the proposed two-layer optimization strategy, simulations were performed using a benchmark power system model. This model incorporates an 8-unit transmission network interconnected with an IEEE 33-bus distribution feeder. Through the simulations, the impacts of various factors are assessed. The analysis considers different electricity pricing scenarios and EV adoption levels. It also examines how the placement of EV charging load across the distribution grid affects results. The simulation results demonstrate that the proposed strategy effectively integrates solar power and improves the economic efficiency of grid operation, while also benefiting EV users by optimizing the charging and discharging of electric vehicles. Furthermore, the performance highlights the significance of considering the location of EV load in distribution network planning. The strategy also considers forensic data collection from electric vehicles, which can provide valuable insights for distribution network operators. The location-specific forensic data collection allows network constraints and opportunities to be assessed based on real-world EV usage at the distribution level.
Use of CPT and other Parameters for Estimating Soil Unit Weight Using Optimised Machine Learning Models
Authors: Roy Swaranjit , Abir Abrar Rahman , Ansary Mehedi A.
Published: May 2024

In this research, we explore the prediction of soil unit weight using five advanced machine learning algorithms: AdaBoost with Random Forest, Multi-Layer Perceptron (MLP), Random Forest (RF), Support Vector Regression (SVR) and XGBoost. Random Forest serves as a weak learner within AdaBoost. We optimize the hyperparameters of these algorithms using randomized search cross-validation (RSCV) and evaluate their performance using mean average error (MAE), root mean square error (RMSE), and R2 metrics. The input features consist of soil sample depth (D), moisture content (MC), fine content (FC), cone tip resistance (QC), and cone local resistance (FS). Additionally, we employ an autoencoder-based feature augmentation technique to enhance the models' ability to capture complex patterns in the data. Before feature augmentation, AdaBoost with Random Forest achieves the highest performance (R2 = 0.896), while SVR exhibits the lowest accuracy (R2 = 0.7402) on the test dataset. Post-augmentation, both AdaBoost with RF and SVR show improvements in R2, MAE and RMSE values, indicating that augmented features capture more variability. XGBoost, Random Forest, and Multi-Layer Perceptron rank 2nd, 3rd, and 4th, respectively, in terms of R2 value. SHAP analysis reveals that QC and FS negatively impact model accuracy, while FC and MC have both positive and negative effects. D emerges as the most influential feature contributing positively to model accuracy. In conclusion, AdaBoost with Random Forest yields the highest accuracy in predicting soil unit weight, with D being the most critical feature.
Diffraction-driven parallel convolution processing with integrated photonics
Authors: Chen Hongwei , Huang Yuyao , Liu Wencan , Sun Run , Fu Tingzhao , Wang Yaode , Huang Zheng , Yang Sigang
Published: May 2024

Traditional electronic processors face challenges such as bandwidth limitations and high power consumption when handling extensive linear operations for deep learning tasks. As an alternative, optical computing has garnered attention for its potential in parallel and energy-efficient computations. However, the exploration of high-density optical computing architectures on integrated photonic platforms has been limited, primarily due to constraints in neuron numbers and control engineering complexities. In response to these challenges, we report a diffraction-driven multi-kernel optical convolution unit (MOCU) to enable on-chip parallel convolution processing. Utilizing cascaded silica 1D metalines as pre-trained large-scale weights and employing spatial multiplexing at the output facet, MOCU enables simultaneous computing of diverse convolutions passively within one single unit. With MOCU, we build optical convolutional neural networks (OCNNs), enabling efficient processing of machine visions with concise architecture. To address fabrication errors inherent in MOCU-embedded OCNN, a lightweight electronic neural network runs concurrently with the OCNN to calibrate systematic deviations via low-rank adaptation (LoRA) algorithm with negligible overhead. The fabricated MOCU chip achieves the highest independent 8-kernel convolutions in parallel, with each kernel size of 3 × 3 and occupying a footprint of merely 0.06mm^2. The proposed architecture synergistically leverages the benefits of both photonic and electronic technologies, offering a potential design methodology for next-generation deep learning hardware aimed at achieving high compute density and prominent energy efficiency.
Effects of Liquid Urea Rates on Nitrogen Dynamics, Growth, and Yield of Grain Corn (Zea Mays L.)
Authors: Mota Ahmmed Md , Samsuri Abd. Wahid , Sukor Arina Shairah Abdul , Amaily Akter , Adibah Mohd. Amin
Published: May 2024

Arbitrary use of urea fertilizer reduces nitrogen use efficiency (NUE) and increases the risk of environmental pollution. An experiment was conducted at the Universiti Putra Malaysia from November 2019 to March 2020 to evaluate the application methods and rates of liquid urea(LU) on the yield performance of corn. The treatments were, U0 = control, GU100 = Granular urea(GU) 100%, LU100 = LU 100%, LU50 = LU 50% and LU33 = LU 33%, in two equal splits at 10th and 28th days after sowing (DAS) in randomized completely block design, replicates four. Results showed that plant height (206.99cm, 216.92cm, 214.61cm), ear height (88.13cm, 88.63cm, 86.00cm), days of maturity (88.75, 89.00, 86.75), number of seeds per kernel row (32.25, 34.50, 33.75), fresh cob weight (10886.60kg/ha, 10946.60kg/ha, 10927.93kg/ha) and 100-grain weight (20.51g, 22.50 g, 21.39 g) of corn were not different significantly(p ≤ 0.05) in GU100, LU100 and LU50 treatments, respectively. The highest yield of corn was found with LU100 (6249.03kg/ha) treatment whereas the yield in LU50 (5666.50kg/ha) and GU100 (5746.64kg/ha) were not different significantly. Nitrogen(%) in plants was the highest in LU100 followed by LU50 treatment which was significantly higher than GU100 treatment. The total N content was also the highest in LU100 (102.83kg/ha) though the total N content was not different significantly in LU50 (77.62kg/ha) and GU100 (83.84kg/ha) treatments. The NUE was the highest in LU50 (66.92%) treatment followed by LU100 (51.47%) treatment. The results of the study suggested that the LU100 was the best application rate while LU50 treatment was comparable to GU100 in corn cultivation.
Age-related hearing loss and dementia risk causality: two-way Mendelian randomization analysis
Authors: Tian Yu , Leng Hui , Wang Bo Shen , Dong Ye , Sun Jia Wei , Yuan Yi Lin
Published: May 2024

In response to the ongoing debate in clinical studies about the relationship between age-related hearing impairment and dementia, a two-sample Mendelian randomization (MR) study using a genome-wide association study (GWAS) database was conducted to elucidate the genetic effects of age-related hearing loss on four types of dementia (dementia, vascular dementia, and Parkinson's dementia，Alzheimer's disease).MR analyzed data from two independent sources on age-related hearing loss (exposure) and four dementias (outcome). We used the inverse variance weighting (IVW) method, the MR Egger method, and the weighted median (WM) method to investigate the impact of age-related hearing loss on dementia.In addition, we analyzed heterogeneity, horizontal diversity, and stability through Cochran's Q-test, MR-Egger intercept, and leave-one-out sensitivity analysis, respectively.Age-related hearing loss was associated with dementia (OR=1.054, 95% CI:0.633-1.754, P=0.840), vascular dementia (OR=1.985, 95% CI:0.550-7.169), P=0.295), Parkinson's dementia (OR=2.263, 95% CI:0.235-21.774, P=0.480), andAlzheimer's disease (OR=1.001, 95% CI:0.999-1.004, P=0.392), but no causal effect was found.The results of our study indicate that there is no statistically significant responsible association between age-related hearing loss and any of the four dementias, in accordance to our two-sample MR analysis.
Towards Visually Interpreting Variational Autoencoders
Authors: Li Runze , Liu Wenqian , Zheng Meng , Torop Max , Rajadhyaksha Milind , Dy Jennifer , Kose Kivanc , Karanam Srikrishna , Wu Ziyan , Bhanu Bir , Radke Richard , Camps Octavia
Published: May 2024

Recent advances in convolutional neural network (CNN) interpretability have led to a wide-variety of gradient-based visual attention techniques for generating visual attention maps. However, most of these methods require a classification-type design architecture, and consequently concentrate on classification/categorization-type tasks. Extending these methods to generate visual attention maps for other kinds of computer vision models, e.g., variational autoencoders (VAE) is not trivial. In this paper, we present a method that helps bridge this crucial gap, proposing to compute VAE attention as a means for interpreting the latent space learned by a VAE. We first present methods to generate visual attention maps from the learned latent space, and then show how they can be used in a variety of applications: localizing anomalies in images, including medical imagery, and improved latent space disentanglement. We conduct extensive experiments on a wide-variety of benchmark datasets to demonstrate the efficacy of the proposed VAE attention.
Analytical modelling of cutting force in pulsed laser-assisted turnings of SiCp/Al composites
Authors: Mingming Lu , Qiao Zhun , Chen Shuang , Lin Jieqiong , Zhai Shuaijie , Gong Hong
Published: May 2024

Particle-reinforced composites (SiCp/Al) are widely used in aerospace and military industries due to their excellent properties. Heating SiCp/Al with a pulsed laser softens the material, which reduces cutting forces, decreases tool wear and improves surface quality. During pulsed laser heating-assisted cutting of SiCp/Al, the modeling of cutting force prediction is complicated by the laser's involvement in the material temperature increase and its property changes. Therefore, a cutting force prediction model was developed considering the effect of laser heating on the properties of SiCp/Al materials. First, the source of cutting force of common cutting SiCp/Al is analyzed and the cutting force model of common cutting SiCp/Al is established. Secondly, the cutting temperature of pulsed laser heating-assisted cutting of 25% SiCp/Al was measured experimentally. Finally, the temperature-susceptible parameters were correlated with the temperature of pulsed laser heating-assisted cutting of SiCp/Al and introduced into the cutting force model for ordinary cutting of SiCp/Al, so as to obtain a cutting force model that takes into account the effect of laser heating on the performance of SiCp/Al, and experimental verification was carried out. The error between the predicted and experimental values is within 20%, which proves the feasibility of the prediction model and provides a theoretical basis for the back-sequence pulsed laser heating-assisted cutting of SiCp/Al.
Research on series arc fault detection methodHousehold loads based on voltage signals
Authors: Li Bin , Shu Jiahui , Cui Feifan
Published: May 2024

In order to accurately detect series arc fault, this paper proposes a series arc fault detection method based on voltage signal which introduces Inception with multi-scale parallel convolution operation, and combines Bidirectional Long Short-Term Memory Recurrent Network (BiLSTM) with attention mechanism. Firstly, a household experimental platform was built, and the line voltage signal obtained by the experiment was subjected to wavelet transform and Principal Component Analysis (PCA) dimensionality reduction to construct a dataset. Secondly, Inception is introduced to extract the multi-level features of the samples, and the parallel output is input into BiLSTM after global max pooling layer. Then, self-attention is used to perform reinforcement learning on the hidden state vector. Finally, the output results are classified by the fully connected layer. Compared with the detection results of various algorithms, it is verified that this method has more advantages in the identification of series arc fault. In addition, additional experiments at different sampling frequencies show that the method has good adaptability, and the identification accuracy has better performance when the sampling frequency is 10KHZ, which has certain theoretical guiding significance for the development of the series arc fault detection device in the next step.
A usability study on the inGAIT-VSO: effects of a variable-stiffness ankle-foot orthosis on the walking performance of children with cerebral palsy
Authors: Noort Luc van , Crey Nikko Van , Rouse Elliott J. , Martínez-Caballero Ignacio , Asseldonk Edwin H.F. van , Bayón Cristina
Published: May 2024

Background Ankle-foot orthoses (AFOs) are commonly used by children with cerebral palsy (CP), but traditional solutions are unable to address the heterogeneity and evolving needs amongst children with CP. One key limitation lies in the inability of current passive devices to customize the torque-angle relationship, which is essential to adapt the support to the specific individual needs. Powered alternatives can provide customized behavior, but often face challenges with reliability, weight, and cost. Overall, clinicians find certain barriers that hinder their prescription.In recent work, the Variable Stiffness Orthosis (VSO) was developed, enabling stiffness customization without the need for motors or sophisticated control.
Methods This work evaluates a pediatric version of the VSO (inGAIT-VSO) by investigating its impact on the walking performance of children with CP and its potential to be used as a tool for assessing the effect of variable stiffness on pathological gait. Data was collected for three typical developing (TD) children and six pediatric participants with CP over two sessions involving walking/balance tasks and questionnaires.
Results The sensors of the inGAIT-VSO provided useful information to assess the impact of the device. Increasing the stiffness of the inGAIT-VSO significantly reduced participants' dorsiflexion and plantarflexion. Despite reduced range of motion, the peak restoring torque increased with stiffness. Overall the participants' gait pattern was altered by reducing crouch gait, preventing drop-foot and supporting body weight. Participants with CP exhibited significantly lower (p<0.05) physiological cost when walking with the inGAIT-VSO compared to normal condition (own AFO or shoes only). Generally, the device did not impair walking and balance of the participants compared to normal conditions. According to the questionnaire results, the inGAIT-VSO was easy to use and participants reported positive experiences.
Conclusion The inGAIT-VSO stiffnesses significantly affected participants' plantarflexion and dorsiflexion and yielded objective data regarding walking performance in pathological gait (e.g. ankle angle, exerted torque and restored assistive energy). These effects were captured by the sensors integrated in the device without using external equipment. The inGAIT-VSO shows promise for customizing AFO stiffness and aiding clinicians in selecting a personalized stiffness based on objective metrics.
Bioinformatics-based pan-cancer analysis of UBE2C
Authors: Zhang Yi-xuan , Hu Ming-guang , Yang Chunbaixue , Peng Jia , Wei Hui-ping , Wang Yan-bing , Li-ning Su , Xue-liang Wu
Published: May 2024

Ubiquitin-conjugating enzyme E2C(UBE2C) is a significant member of the ubiquitin-conjugating enzyme family, playing a crucial role in the Ubiquitin-Proteasome Pathway and being essential for cell cycle regulation and cyclin degradation. It is highly expressed in various tumor tissues, and this expression is closely associated with the occurrence and development of tumors, particularly UBE2C-related tumors. Currently, there are no studies on pan-cancer analysis of UBE2C.Therefore, the objective of this study was to present comprehensive pan-cancer analysis data on UBE2C for clinical research and to offer data-driven support for early cancer diagnosis. In this study, we performed pan-cancer analysis of UBE2C by bioinformatics, explored and collated the data of many types of tumors in TCGA-based databases, performed differential analysis, expression and prognostic value analysis, immunoassay and mutation analysis, screened the cancer species by applying different methods in the R programming language, and analyzed the genomic heterogeneity and gene expression of UBE2C in the pan-cancer. In addition, we plotted UBE2C-associated survival curves for eight cancer types. Finally, we validated the changes of UBE2C in pan-cancer by downloading the images of UBE2C immunohistochemistry results integrating normal and tumor tissues from 8 sites through The Human Protein Atlas Version: 23.0 (https://www.proteinatlas.org/) database. Through the pan-cancer analysis of UBE2C, the gene was analyzed in terms of clinical prognostic value, tumor immunotherapeutic value, and immunoassessment value, which will provide a reference for subsequent research based on UBE2C to explore the aspects of tumor diagnosis, treatment, assessment and management.
Study on Routing and Scheduling for Unmanned Electric Loaders Considering Charging
Authors: Wei Xiaoxu , Niu Chen , Zhao Lianzheng , Wang Yongsheng
Published: May 2024

The application of unmanned electric loader technology facilitates safe and efficient enterprise production. By framing the cargo transport from multiple bins to electric loader hoppers as an MDVRPTW-EV issue, this paper proposes the SPBO-ACO hybrid metaheuristic algorithm, which combines the local search capability of the Student Psychology Optimization algorithm with Ant Colony Optimization principles to address path planning challenges. The SPBO-ACO algorithm leverages route length classification, strong and weak perturbations, and learning operators to enhance solution exploration.Testing based on standard MDVRPTW benchmark test instances shows high scalability and stability with 25% of results exceeding or approaching optimal solutions in 20 benchmark cases while 85% have errors compared to optimal solutions that do not exceed 10%. When applied to an industrial setting, the algorithm significantly reduces the unmanned loader's driving distance during raw material feeding and filling, demonstrating its practical effectiveness.
On The Determination of the Position of the Mental Foramen Based on the Eruption of the Third Molar
Authors: Yarkan İlda Sinem , Ozdogmus Omer
Published: May 2024

The primary objective of this study is to ascertain whether third molars manifest a perceptible impact on the localization of the mental foramen. In this study, we conducted an extensive investigation utilizing panoramic radiographs to examine the morphology and spatial relationships of the foramen mentale in a diverse patient population. There are three prominent factors studied in the radiograph analyses: mental foramen position in both vertical and horizontal orientations, gonial angles, and the eruption status of the third molar. The statistical analyses of the data reveal that there exists a relationship between full eruption of third molar and the vertical and horizontal position of mental foramen. In addition, the findings imply that there is no statistically significant relationship between gonial angles and eruption status of third molar. This study paves also that way of future research endeavors which aim to investigate in detail both anatomical and physiological aspects to unravel the underlying mechanisms governing such complex relationships.
Highly porous carbonaceous aerogel for symmetric supercapacitor with dual-redox active electrolyte revealing high performance pseudo-capacitance
Authors: Vijayan Divyadharsini , Kumaresan Thileep Kumar , Subashchandrabose Raghu , Gnanamuthu RM , Vediappan Kumaran , Gunasekaran Sivagaami Sundari
Published: May 2024

Due to the increasing global energy demand, there is an urgent need for more efficient energy storage systems. Redox-active electrolytes offer a promising, long-term solution for high-energy-density supercapacitors, as they enhance energy density and pseudo-capacitance through redox reactions. This study introduces a symmetric supercapacitor utilizing a dual redox-active electrolyte, achieving the highest levels of pseudo-capacitance and energy density with a biomass-derived carbonaceous aerogel (BCA) electrode. The BCA electrode's unique flower-like cubic-sphere structure, partially graphitized edges, and high specific surface area of around 1299 m²g⁻¹ enable efficient access for electrolyte ions, enhancing charge storage. The dual-redox electrolyte, comprising KBr and methyl Viologen dichloride (MVCl2), enhances the performance of both electrodes through redox reactions, resulting in a maximum half-cell specific capacitance of about 887 Fg⁻¹ at 1 Ag⁻¹ current density. When incorporated into a supercapacitor device, this dual-redox-electrolyte system achieves a maximum specific capacitance of 560 Fg⁻¹ and an energy density of approximately 77 WhKg⁻¹ at the same 1 Ag⁻¹ current density, with outstanding capacitance retention of approximately 93% over 10,000 charge-discharge cycles. Thus, the combination of KBr and MVCl2 in the KOH electrolyte, as demonstrated in this work, enhances redox behaviour, leading to significantly more efficient energy storage solutions.
LCSA-Fed: A low cost semi-asynchronous federated learning based on lag tolerance for services QoS prediction
Authors: Cai Lingru , Liu Yuelong , Xu Jianlong , Jin Mengqing
Published: May 2024

As a distributed training method, federated learning (FL) has been widely used in the field of quality-of-service (QoS) prediction. However, existing FL-based QoS prediction methods ignore the unreliability of end devices, which will lead to wasted training resources and high communication costs. Considering that the instability of end devices in real training environments, we propose a low cost semi-asynchronous federated learning method (LCSA-Fed) based on lag tolerance to overcome the lower convergence rate and suboptimal prediction accuracy of models. LCSA-Fed is able to reduce model communication costs and training costs by tolerating relatively lagging local models. At the same time, we employ innovations in both the user selection phase and the model aggregation phase to improve prediction accuracy while reducing overheads. By conducting relevant validation experiments on a publicly available QoS dataset, we conclude that our model LCSA-Fed can effectively reduce overhead and improve prediction accuracy.
The evolution of sex reconsidered: Resource limits offset the twofold cost of males
Authors: Yasui Yukio , Hasegawa Eisuke
Published: May 2024

In anisogamy (sexual reproduction by egg and sperm), the population growth rate is half that of thelytoky (all-female parthenogenesis) because half of the offspring are males, which do not lay eggs1,2. The present dominance of anisogamy in multicellular organisms despite this “twofold cost of male production” is the greatest enigma in evolutionary biology3-8. Various proposed benefits (e.g., Red Queen) of sex are insufficient to compete with thelytoky, which increases 210 = 1024-fold in 10 generations over anisogamy. Why is anisogamy protected from thelytoky invasion? However, the 1024-fold increase requires the 1024-fold resources and resources are finite in the real world. Here, using a very simple mathematical model and simulations, we show that the twofold cost disappears under resource limitations. Thelytoky can exhibit a twofold increase only at low densities with abundant resources, but anisogamy can coexist with thelytoky because competitive exclusion does not occur in such an unsaturated population. Once the population reaches the carrying capacity, thelytoky and anisogamy have the same realized fitness. If males offer slight advantages (e.g., lower resource requirements or greater resource competitiveness than thelytokous females), anisogamy has greater fitness than thelytoky and will displace thelytoky. Therefore, twofold benefits to compensate for the twofold cost are unnecessary.
Effects of Assisted Consolidation in Cross-Anisotropy Shear Ratio of Texcoco Clay From Field and Laboratory Tests
Authors: Claudia CHAMORRO-ZURITA , Alfonso FERNÁNDEZ-LAVÍN , Efraín OVANDO-SHELLEY
Published: May 2024

In this research we look at the variation of cross anisotropy as a result of the application of vacuum assited consolidation in very soft clays that underlie a trial embankment that was built at a site in the former Texcoco Lake, some 11 km north-east of central Mexico City. Cross anisotropy was evaluated making refrence to the cross-anisotropy index, VSH/VSV. Velocities of shear waves propagated horizontally, VSH, were obtained from cross hole tests, and the velocities of shear waves propagated vertically, VSV, from seismic dilatometer and suspension logging tests. These tests were performed two months after the vacuum pumps were shut down so the shear wave velocities obtained then reflect the changes induced by the vacuum assisted consolidation on soil properties. The VSH/VSV ratio was also evaluated from resonant column tests performed on soil specimens retrieved from a site nearby the trial embankment. Samples were trimmed horizontally and vertically and were then tested in the resonant column. Field and laboratory test results showed that cross anisotropy of the studied soft lacustrine soils is barely affected by the stress state variation induced by vacuum assisted consolidation or by loading direction, as observed in the resonant column tests. Laboratory tests also showed that the VSH/VSV is related to liquidity index through an empirical equation that can be used to estimate fairly well field values of VSH/VSV.
The Effect of Paid Maternity Leave Reformation on Korean Women’s Labor Supply
Authors: Economics Seoyeon Jo
Published: May 2024

This study examines the impact of changes in two major paid family leave policies on female labor force participation in Korea. Using Regression Discontinuity (RD) methods and five datasets spanning the period from 2007 to 2018, this paper investigates the impact of paid parental leave policy reforms on labor force attachment and log wages. The findings suggest that the 2012 extension of paid parental leave made it more challenging for mothers to return to work after giving birth, resulting in a significant decrease in labor market attachment compared to the policy amendments in 2007 and 2014.
JEL Classification: H4 , J08 , J13 , J16
Energetics of the OH radical H-abstraction reactions from simple aldehydes and their geminal diol forms
Authors: Salta Zoi , Schaefer Thomas , Tasinato Nicola , Kieninger Martina , Katz Aline , Herrmann Hartmut , Ventura Oscar N.
Published: May 2024

Context: Carbonyl compounds, especially aldehydes, emitted to the atmosphere, may suffer hydration in aerosols or water droplets in clouds. At the same time, they can react with hydroxyl radicals which may add or abstract hydrogen atoms from these species. The interplay between hydration and hydrogen abstraction is studied using density functional and quantum composite theoretical methods, both in the gas phase and in simulated bulk water. The H-abstraction from the aldehydic and geminal diol forms of formaldehyde, acetaldehyde, glycolaldehyde, glyoxal, methylglyoxal and acrolein are studied to determine whether the substituent has any noticeable effect in the preference for the abstraction of one form or another. It is found that abstraction of the H-atom adjacent to the carbonyl group gives a more stable radical than same abstraction from the geminal diol in the case of formaldehyde, acetaldehyde and glycolaldehyde. The presence of a delocalizing group in the Ca (a carbonyl group in glyoxal and methylglyoxal, and a vinyl group in acrolein), reverts this trend and now the abstraction of the H-atom from the geminal diol gives more stable radicals. A further study was conducted abstracting hydrogen atoms from the other different positions in the species considered, both in the aldehydic and geminal diol forms. Only in the case of glycolaldehyde, the radical formed by H-abstraction from the –CH2OH group is more stable than any of the other radical species. Abstraction of the hydrogen atom in one of the hydroxyl groups in the geminal diol is equivalent to the addition of the •OH radical to the aldehyde. It leads, in some cases, to decomposition into a smaller radical and a neutral molecule. In these cases, some interesting theoretical differences are observed between the results in gas-phase and (simulated) bulk solvent, as well as with respect to the method of calculation chosen.
Methods: DFT (M06-2X, B2PLYP, PW6B95), CCSD(T) and composite (CBS-QB3, jun-ChS, SCVECV-f12) methods using Dunning basis sets and extrapolation to the CBS limit were used to study the energetics of closed shell aldehydes in their keto and geminal-diol forms, as well as the radical derived from them by hydrogen abstraction. Both gas-phase and simulated bulk solvent calculations were performed, in the last case using the Polarizable Continuum Model.