bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Response Characteristics Analysis of Biomimetic Foot during Ground Contact Instant
Authors: Song Mengjun , Zhang Liping , Wei Jinggong 
Published: July 2024

Abstract

In this paper, the dynamic substructure method is applied to analyze the touch instant response characteristics of commonly used materials for foot mechanism, and the touch instant of quadrupedal mechanism is taken as an example for corresponding analysis. This paper firstly takes a walking mechanism as the research object, simplifies the contact model, and introduces the dynamic substructure solving method to construct the corresponding numerical model; then the dynamic substructure method is used to solve the transient corresponding characteristics of the leg components under different materials and different loading conditions, and obtain the corresponding transient corresponding characteristics of the collision force, etc. At the same time, the material characteristics are synthesized to analyze the transient response characteristics of different materials for the bionic mechanism, so as to provide a comprehensive analysis for the transient response characteristics of different materials for the bionic mechanism. At the same time, in order to analyze the transient response characteristics of different materials, the material characteristics are synthesized, so as to provide a basis for the study of transient mechanical properties of different materials of the bionic mechanism. Finally, the transient characteristics of foot-ground contact are experimentally verified by a high-speed camera system. Finally, this paper provides some theoretical support and methodological reference for the mitigation of transient response of foot-ground contact.
Enhancement of Long-Horizon Task Planning via Active and Passive Modification in Large Language Model
Authors: Hori Kazuki , Suzuki Kanata , Ogata Tetsuya 
Published: July 2024

Abstract

This study proposes a method for generating complex, long-horizon off-line task plans using large language models (LLMs). Although several studies have been conducted in recent years on robot task planning using LLMs, the planning results are often simple. In the proposed method, the LLM actively collects missing information by asking questions, and the task plan is upgraded with a one-shot dialog example. In addition, the robustness of the task planning is enhanced by using the method that modifies the plan results based on human instructions. The effectiveness of the proposed method is demonstrated through dialogue experiments using a cooking task as the subject. Furthermore, the proposed method can be applied to instructions that include images.
Yangtze finless porpoise sexual behavior object detection algorithm based on YOLOv8
Authors: Chen Huiyan , Ge Panyuanyuan , Hao Yujiang 
Published: July 2024

Abstract

Traditional studies on Yangtze finless porpoise behavior rely on manual observation mainly, posing challenges such as low efficiency, high labor costs and visual fatigue. To address these issues, the Baiji Dolphinarium at the Institute of Hydrobiology, Chinese Academy of Sciences, has deployed a monitoring platform supporting accelerated playback to enhance observation efficiency and conduct researches on Yangtze finless porpoise sexual behaviors leading to reproduction and conservation. The plantform gives a new way to monitor Yangtze finless porpoises` behavior by using computer vision, which means real-time object detection algorithm on recognizing sexual behaviors of Yangtze finless porpoises is essential. However, existing models suffer from imbalance categories problem in finless porpoise sexual behavior dataset, background noise in images, occlusion and overlap sections of Yangtze finless porpoises.. In this paper, we established the first Yangtze Finless Porpoise Sexual Behavior dataset (YFPSB) in artificial rearing environments, consisting of 4900 images in different camera views for reaserchers to train and test new vision algorithms. We also propose an improved method based on YOLOv8 to tackle theseproblems. Specifically, we introduce Expanded Window Multi-Head Self-Attention (EW-MHSA) into the backbone network to enhance the model's spatial awareness. EW-MHSA also lightened origin model and meet the demand of capturing long-distance dependency in the images with 9.7% decrease of the model parameters, smaller than the smallest model in yolov8 series. Through experiments and tests, our model achieves the result of 96.6% mAP, demonstrating its accuracy and potential application in marine ecological monitoring and conservation.
Exploring the Bond, Flexure, and Shear Behaviour of Bundled Bars in Concrete Structures
Authors: Ponni M , Rajkumar Shobha 
Published: July 2024

Abstract

Bundled bars, also known as bundled reinforcement, involve grouping multiple steel bars together to form a single unit, which is then embedded within concrete structures. We aim to comprehensively understand the behavior of bundled bars in reinforced concrete structures. This study investigates the behavior of bundled reinforcement bars in concrete beams, aiming to assess their influence on structural performance. A series of experiments were conducted, including pullout tests on bundled bars and flexural and shear tests on concrete beams with and without stirrups. The study evaluated various parameters such as peak load, displacement, ductility, stiffness, and energy absorption capacity for different bundling configurations. Results indicate that bundling enhances the peak load capacity and energy absorption of beams, with minimal impact on displacement and stiffness. However, beams without stirrups exhibit higher stiffness compared to those with stirrups, suggesting a trade-off between shear capacity and structural rigidity. Overall, the findings provide insights into the behavior of bundled reinforcement bars in concrete structures, informing design practices for enhanced structural performance and resilience. Contrary to IS code recommendations, findings from this study indicate that such recommendations are not essential and could even be counterproductive.
Anesthetic Challenges of Caring for an Adult with Moebius Syndrome: A Case Report
Authors: Vegunta Geetasravya , DO Giovanna Patafio , Gade Swata , Awuku Kwame , Kalyoussef Evelyne , Shah Shridevi Pandya 
Published: July 2024

Abstract

Background Moebius syndrome is a rare congenital disorder with facial nerve palsies and craniofacial malformations, increasing the risk of a difficult airway during anesthesia. We report a difficult airway in an adult with Moebius syndrome during an elective procedure, which is unique as most reports of Moebius syndrome are in children.
Case Presentation Our patient was a 30-year old male diagnosed with Moebius syndrome at birth, and presented with craniofacial and orthopedic malformations, intellectual disability, and facial nerve palsies. Although our patient had prior successful intubations, their airway exam deteriorated from a Mallampati Class II to IV after many surgeries. After fiberoptic intubation with nebulized lidocaine to maintain spontaneous ventilation failed, an attempt with dexmedetomidine and video laryngoscopy was successful.
Conclusion Our case demonstrates the necessity of preparing for a difficult airway and strategies for airway management in an adult with Moebius Syndrome.
A mixed sample data augmentation method based on sparse adversarial attack
Authors: Xu Xiaojun , Zhang Xiaolin , Wang Yongping , Liu Lixin , Xu Enhui 
Published: July 2024

Abstract

To enhance the generalization ability of deep neural networks in image classification tasks, advanced data augmentation strategies have been widely studied. Information deletion guides the model to focus on less discriminative parts by removing regions of the image, but this can lead to the loss of important information from the training samples. Recent studies have explored randomly cutting and mixing patches and their labels between training images. However, this random patch selection strategy may not accurately represent relevant information about the corresponding objects. Using saliency maps to guide patch selection also has drawbacks, as it may not fully align with the model's internal decision-making mechanisms. To solve those problems, we propose a novel data augmentation method, AdvMix.First, AdvMix accurately finds the most sensitive pixels in the decision-making process of the model through sparse adversarial attacks, selects the points as the center, and expands them into sensitive areas. Next, equally important sensitive regions from a patch image are used to replace the corresponding sensitive regions in the original image. The mixed samples generate new images. AdvMix forces the model to find other relevant features when the most discriminative content is modified, thereby enhancing the model's generalization ability. Experimental results across various datasets and image classification models validate that this method outperforms previous data augmentation techniques, significantly improving the performance of classification models.
PKDG: Prior Knowledge based Domain Generalization Model for fundus image segmentation
Authors: Xia Jianan , Zeng Lili , Li Tengfei , Xue Jingyan , Zhao Chuanchuan , Zhou Xuezhong 
Published: July 2024

Abstract

Convolutional neural network performance is prone to be significantly affected by the domain difference between the training data (source domain) and the test data (target domain).To address this issue and simultaneously to meet the multi-institutional healthcare data privacy protection needs, we propose a Prior Knowledge based Domain Generalization (PKDG) model for segmenting the optic cup and disc regions. Unlike existing methods, we incorporate clinical a priori knowledge into two phases. In the model training phase, a Priori Knowledge Module (PKM) is introduced to fuse client-side high-level information with server-side shared feature to generate a new dataset that simulates the differences between different domains. Further, A priori knowledge constraints are imposed on the model training process to enhance its generalization capability. In the model generalization phase, the Visualization Module (VM) reconstructs the shape of the segmentation results based on the intermediate representations, thus improving the visual interpretability. The proposed PKDG model provides a framework for optic cup and disc segmentation that enables privacy-preserving multicenter collaborative disease supporting diagnosis while ensuring robustness and superior performance in terms of accuracy and visual interpretability.
Facial and Palm-Based Biometric Authentication and Data Security
Authors: Tiwari Chandra Sekhar , Jha Vijay Kumar 
Published: July 2024

Abstract

Biometric Authentication (BA) is frequently used for authentication owing to its high recognition rate. The existing biometric hiding algorithms execute data embedding on areas that do not encompass key features of the biometric. Moreover, these techniques lacked authorization. Thus, a Secure Data Transfer model with BA and Blockchain (BC)-based authorization is proposed. Primarily, the data owner registers their details and the registered face and palm image undergoes pre-processing. By employing Pruned Residual Network 50 (PRESNET 50), the facial landmarks are extracted from the pre-processed face image. Next, Digit Folding based Log Facial Jaw Points Curve Cryptographic (DF-LFJPCC) is executed based on the jaw points to generate a secret key. Then, the Tan Sigmoid-based Convolutional Neural Network (TS-CNN) classifier is trained with the features of the pre-processed images and facial landmarks. After registration, the user logins, and their processed face and palm features are given to the trained TS-CNN for authenticating the user. The secret is also used to improve the authentication process. After successful login, the file to be uploaded is converted into cipher, which is then encrypted using Log Facial Jaw Points Curve Cryptographic (LFJPCC) and uploaded to the cloud server. In the end, authorization is performed in the BC based on the hashcode generated using Faro shuffle -Tiger (FS-Tiger) when a user requests data. As per the experimental analysis, the proposed technique outperforms prevailing models.
Effect of chemical absorption on Jeffery Fluid Flow in saturated Porous Media with variable thermal conductivity
Authors: Disu Akeem Babatunde , Omokhuale Emmanuel , Salawu Sulyman Olakunle 
Published: July 2024

This study investigates the impact of species absorption of Jeffery fluid flow through a saturated permeable medium with variable thermal conductivity. The dimensional partial nonlinear derivative model controlling the chemical reacting fluid flow is transformed to invariant form. The resulting flow equations are computed numerically using an approximated finite implicit Crack-Nicolson. A chemical absorption of fluid reactant occurs in a boundless vertical device. Computations are performed for different parameters to examine their sensitivity under isothermal temperature conditions. The computed results are offered graphically for qualitative and quantitative insights into the flow behaviour. The obtained outcomes revealed that the fluid flow rate rises with an increasing values of the parameters and, and it damps with upsurge in the values of the parameters, and. The heat transfer field is reduced with enhancing values of the thermal source, viscous dissipation and time, but declines for a boosted value of the terms suction and Prandtl number. Also, the mass transfer field is higher when mass absorption and time are increased, and diminish with an elevate in the values of Schmidt number and chemical reactions.
Antioxidant activity assay of Roselle (Hibiscus sabdariffa) seeds Ethanol extract with DPPH radical scavenging using UV-Vis Spectrophotometer
Authors: Syahara Muhammad Alwi , Helilusiatiningsih Nunuk , Irawati Titik 
Published: July 2024

Hibiscus sabdariffa (Roselle) is known to have a strong antioxidant compound. Thus, the calyx becomes the most important area to research. Another part of this plant that was starting to be known for its benefits is rosella seeds. Roselle seeds are a source of fat-soluble antioxidants. The aim of this study was to investigate the antioxidant activity of Roselle Seed Ethanol Extract (RSEE) with the DPPH (1,1-Diphenyl-2 Picrylhidrazyl) radical scavenging method. This research begins by doing the extraction of Roselle seeds using ethanol (96%) as a solvent and then assessing the antioxidant activity (Radical Scavenging Activity/RSA) of the extract, which is compared with the ascorbic acid standard at several concentrations (5-200 ppm). Antioxidant activity was assessed with DPPH Radical Scavenging using UV-Vis spectrophotometer and IC50 value parameters. The results of this study were the absorbance of DPPH from spectrophotometer at 517 nm was 0,824 (purple color). The absorbance of RSEE and ascorbic acid at 5 ppm to 200 ppm, respectively 0.523-0.124 and 0.594-0.112. The antioxidant activity (RSA) of the RSEE and ascorbic acid, respectively was 57.93% and 59.24%. The IC50 value of RSEE was 30.158 μg/ml and as comparison is ascorbic acid, the IC50 value was 26.948 μg/ml. Thus, the antioxidant activity of roselle seeds ethanol extract (RSEE) belongs to a very strong category (50 μg /ml). This is due to the presence of several phenolic compounds and unsaturated fatty acid derivatives.
Assessing the availability and necessity of menstruation-friendly toilets in public and private sector sites in Kathmandu, Nepal
Authors: Mathew Esther Elsa , Reed Elisabeth , Karki Jasmine , Chhantel Rubina , Jolly Pauline , Lhaki Pema , Shrestha Sadeep 
Published: July 2024

ABSTRACT
Much of the world's public toilet infrastructure does not consider the needs of menstruators. Nepali menstruators, 18–52 years old, were surveyed at 40 different sites in three major cities in Nepal. During a random site visit, 20 eligible participants at each site were selected by convenience sampling to complete a quantitative survey assessing the importance of the eight aspects of a menstruation-friendly toilet, as outlined by the government of Nepal. Only one of 40 of the toilets assessed met all eight indicators of a menstruation-friendly toilet. None of the survey participants felt comfortable using a public toilet when menstruating, and 88.8% reported facing challenges using public toilets when menstruating.
Município de Interesse Turístico
Authors: Cunha Souza Mariana Cristina , Neves Guimaro Ana Carolina 
Published: July 2024

No estado de São Paulo, o turismo é considerado vetor de desenvolvimento, tanto que políticas públicas específicas são propostas para fomentar a atividade. Um exemplo é a Lei Complementar Nº 1.261, de 29 de abril de 2015, que estabelece requisitos para a classificação de Estâncias e Municípios de Interesse Turístico (MITs). Nesse cenário, o governo do município de Presidente Prudente iniciou o processo de candidatura em 2015 e em 2018 enviou a proposta revisada, desde então obteve duas negativas. Na última solicitação, os critérios de potencial turístico e serviço de informação turística não foram atendidos. O objetivo geral deste artigo é analisar a trajetória do governo municipal de Presidente Prudente no processo de solicitação do MIT. A pesquisa, classificada como aplicada, explicativa e de abordagem qualitativa, baseou-se em revisões bibliográficas e documentais, a partir de consultas nas plataformas científicas do SciELO, Periódicos CAPES e Google Acadêmico. Igualmente, dados e informações foram solicitados ao Governo do Município de Presidente Prudente, nos departamentos que participaram e/ou estão atuando na condução do título de MIT. Realizaram-se entrevistas com roteiro semiestruturado, junto aos profissionais que atuam diretamente no processo de solicitação do título. Todo material foi organizado por temas e analisado por meio da técnica da Análise de Conteúdo. Os resultados demonstram que há necessidade de conformidade com critérios técnicos e legais, uma vez que a aprovação do título tem sido influenciada pela não sistematização de informações e apresentação documental conforme a legislação exige. Com as negativas, o processo encontra-se em revisão, com possibilidades de parecer favorável em nova solicitação da titulação pelo governo municipal.
Therapeutic Potential of Nanocarriers in the Management of Rheumatoid Arthritis
Authors: Mittal Vishnu , Sharma Anjali , Sharma Devkant 
Published: July 2024

Abstract:
RA is characterized by chronic inflammation, joint damage, and systemic complications.
Despite available treatments, many patients experience inadequate responses or adverse effects.
Novel therapeutic strategies are needed to address these challenges. Nanoparticulate technologies
offer promising opportunities to enhance drug delivery and targeting in RA treatment.
The main objective is to explore recent advancements in nanoparticulate technologies for RA treatment,
focusing on their potential to improve drug delivery and efficacy while minimizing adverse
effects. This review examines recent studies on nanoparticulate technologies for treating rheumatoid
arthritis (RA), focusing on the use of nanocarriers for targeted drug delivery. Studies investigating
the effectiveness of nanocarriers in delivering drugs specifically for RA treatment were included
in the analysis. Nanoparticulate technologies have shown promise in improving the delivery
and efficacy of RA treatments. Various nanocarriers, such as liposomes, polymeric nanoparticles,
and micelles, have been developed to enhance drug delivery to inflamed joints. These nanocarriers
loaded with curcumin, Aceclofenac, Boswellic acid, methotrexate, resveratrol, etc. can improve
drug stability, prolong circulation time, and enhance targetability to inflamed tissues. By
overcoming the limitations of traditional therapies, these technologies have the potential to improve
patient outcomes and quality of life. Future research should focus on optimizing nanocarrier
design, evaluating long-term safety, and conducting clinical trials to validate their efficacy in RA
management.
The Influence of Phytoconstituents for the Management of Antipsoriatic Activity in Various Animal Models
Authors: Yadav Ravina , Yadav Tejpal , Upadhayay Ashutosh , Alam Md. Sabir , Dubey Gaurav , Kumar Vikram , Sahu Adarsh 
Published: July 2024

:
It is possible for psoriasis to manifest at any point in a person's life, regardless of their age, gender, or geographic location. It is a chronic immune-linked inflammatory skin ill-ness that affects individuals of various racial and ethnic origins. It is recognized to be a long-lasting condition. Because of the significant contribution that natural products have made, there has been a significant advancement in the treatment of skin illnesses such as psoriasis. The biggest number of phytochemicals derived from a wide range of plants and herbs are now being used in a variety of applications throughout the whole world. Additionally, a number of phyto-chemicals, including aloe-emodin, psoralen, curcumin, and others, have been effectively ex-tracted in pure or clear form, and they have shown a great deal of efficacy in the treatment of psoriasis illness. There is evidence that few herbal remedies are effective, and the occurrence of these phytochemicals provides more proof. When synthetic medications are used for chronic therapy, they may cause a variety of adverse consequences; hence, the exploration of natural pharmaceuticals can give a successful natural treatment with a minimal amount of adverse ef-fects. Within the scope of this concise review, a number of plant sources that possess anti-pso-riatic activity are investigated, and the antipsoriatic effects of these plant sources are shown on a number of animal models using particular pathways.
Deciphering the Causality between Gut Microbiota Dysbiosis and Poisoning by Narcotics and Psychodysleptics: A Mendelian Randomization Analysis
Authors: Wang Ning , Su Zhenbo 
Published: July 2024

Background:
This study investigates the connection between gut microbiota and poisoning
caused by narcotics and psychodysleptics, using Mendelian randomization (MR) to explore possible
causal relationships.

Methods:
The study employed the MR analysis, leveraging genetic variants as instrumental variables
to facilitate robust causal inference. Data for gut microbiota was extracted from the MiBioGen study,
integrating genome-wide genotyping data with 16S fecal microbiota profiles. Outcome metrics were
based on the Finngen study. Genetic instruments were meticulously extracted based on stringent criteria,
and harmonized with SNP outcomes associated with "Poisoning by narcotics and psychodysleptics
[hallucinogens]". The inverse-variance weighted (IVW) method was utilized for MR analysis, supplemented
by sensitivity analyses including MR-Egger Regression, Weighted Median Approach, and
Leave-One-Out Cross-Validation.

Results:
Among various microbial groups, nine showed significant statistical links. Specifically, Class
Negativicutes (OR 5.68, 95% CI 2.13-15.16, p = 0.0005) and Order Selenomonadales (OR 5.68, 95%
CI 2.13-15.16, p = 0.0005) were notably associated. These findings were consistent across different
sensitivity analyses.

Conclusion:
The relationship between gut microbiota and the adverse effects of narcotics and psychodysleptics
is an emerging area of research. Our MR study identifies certain microbes that might influence
the body's response to these substances. These insights could help in predicting and treating the
effects of narcotics and psychodysleptics in the future.