bluuebunny/crossref_metadata_2025 huggingface dataset:
Faecal Calprotectin: A reliable biomarker in Inflammatory bowel disease
Authors: Barua Ripon , Sarker Jogendra Nath
Published: November 2024

Calprotectin a calcium and zinc binding protein, is a breakdown product of WBC which can be detected and quantified in both stool and plasma and is markedly elevated in infectious and inflammatory conditions, including inflammatory bowel disease (IBD). Reference ranges for faecalcalprotectin (FC) have been established in healthy adults and children and elevated concentrations of FC have been demonstrated in numerous studies of patients with IBD. The overall sensitivity and specificity for FC in IBD found to be as high as 78-100% and 76-100% respectively. The FC correlates well with histological inflammation as detected by colonoscopy with biopsies and has been shown successfully to predict relapses in patients with IBD. The FC has been shown to consistently differentiate IBD from irritable bowel syndrome (IBS) because it has excellent negative predictive value in ruling out IBD in undiagnosed, symptomatic patients. The FC may be also useful in determining whether clinical symptoms in patients with known IBD are caused by disease flares or non inflammatory complications/underlying IBS and in providing objective evidence of response to treatment. Although more studies are needed to define fully the role of FC, convincing studies and growing clinical experience point to an expanded role in the diagnosis and management of IBD.
J. Dhaka National Med. Coll. Hos. 2013; 19 (02): 58-64
New biomarkers in kidney transplant
Authors: Salvadori Maurizio , Rosso Giuseppina
Published: November 2024

Recently, new interesting and important novel biomarkers have allowed the evidence based medicine to move to a new field called precision medicine. In particular, this apply to organ transplantation and to the diagnosis of rejection.
Among these novel biomarkers are the study of donor-derived cell-free DNA when present in the blood of the recipients, the study of gene expression profiling again in the recipient, and the study of several urinary cytokines. All these novel biomarkers have several advantages over the old biomarkers. Indeed, they are non-invasive, are able to detect renal damage before the appearance of histological abnormalities, and are able to distinguish antibody-mediated rejection from cell-mediated rejection. The aim of this study is to identify the most recent findings on these biomarkers and to describe their utility and their limitations in particular in the field of kidney acute rejection.
From Complexity to Clarity: Fellows’ perspective on Comprehensive Canopy Concept-‘The 3 Step Technique’ of Total Laparoscopic Hysterectomy
Authors:   Director, Department of Obstetrics and Gynecology, Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Jain Nutan , Sureddi Priyanka ,   Fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Srivastava Sakshi ,   Fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Gulati Divyanee ,   Fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Sareen Shweta ,   Ex fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Jain Vandana ,   Consultant, Department of Obstetrics and Gynecology, Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh,, Mann Sonika ,   Ex fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Agarwal Chetna ,   Ex fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Singh Shalini ,   Ex fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India., Bayya Prasanna ,   Ex fellow in Gynae Endoscopy at Vardhman Trauma and Laparoscopy Centre Pvt. Ltd., Uttar Pradesh, India.
Published: November 2024

Total Laparoscopic Hysterectomy (TLH) is pivotal in gynecological surgeries, offering advantages like decreased blood losses, faster recovery, shorter operative time and reduced hospital stays. The Comprehensive Canopy Concept: ‘The 3 Step Technique’ emerges as a three-step strategy for streamlining TLH procedures in complex cases, characterized by extensive bladder adhesions and ventrifixed uterus. As fellows under the guidance of a distinguished gynaecology laparoscopic surgeon, we recount the evolution of this approach. The first step challenges conventional norms by advocating for a posterior approach to uterine artery, dissection and ligation before bladder dissection. The second step involves meticulous dissection to create a bloodless uterovesical space creating a bladder canopy. The culmination of this technique lies in the third step, employing an anterior approach to dissect and coagulate the contralateral uterine artery. As fellows, we share our experience in adopting the Comprehensive Canopy Concept: ‘The 3 Step Technique’ emphasizing its positive impact on surgical outcomes in densely adherent bladder and patient care in cases of complex TLH. This technique not only transcends traditional approaches but also addresses persistent challenges, offering a systematic approach that ensures safety and reproducibility
Feasibilty of a Double Blind Randomised Controlled Trial to Compare Post-operative Recovery following Laparoscopic Hysterectomy with Post-operative Recovery following Laparoscopic Sub-total Hysterectomy - The LaHoST Study
Authors:   Medway Maritime Hospital, ME7 5NY Kent, UK, Ahmed Abu Imad Hasib , Wisa Hany ,   Associate Specialist Obstetrician and Gynaecologist, Medway Maritime Hospital ME7 5NY Kent UK, Wright Jeremy ,   University of Surrey GU2 7XH, Guildford UK.
Published: November 2024

Observational studies suggest faster recovery and quicker return to normal activities following laparoscopic supracervical hysterectomy (LSH) compared with laparoscopic hysterectomy (LH) in women with benign uterine disease. Data from the only randomised controlled trial (RCT) on the topic does not support this observation. We have investigated the feasibility of a double blind RCT comparing post-operative recovery following LH with that following LSH. 70 women were invited to participate from a single gynaecological surgeon’s caseload 20 women were excluded. Web based randomisation was carried out at the time of study laparoscopy. Surgery was performed using a standardised technique. Participants and the data handler were blinded to treatment allocation. Primary outcome was feasibility of recruitment. Secondary outcomes included validated post-operative recovery and mood questionnaires at baseline, prior to discharge and at weekly intervals for 12 weeks. Validated questionnaires regarding pelvic floor function and sexual function were assessed at baseline, 6 weeks and 6 months. Recruitment and treatment of 50 women was completed within 18 months. Less than 30% of eligible invitees were excluded and the commonest reason for exclusion was a strong opinion regarding conservation or removal of the cervix (8/70 = 11.4%). 96% of participants received treatment according to randomisation. Data collection was complete at 6 weeks for 88%. Recovery scores were similar to pre-op at 3 weeks for LSH and at 4 weeks for LH. Subjects had returned to normal activity ‘all of the time’ by 6 weeks for LSH and by 8 weeks for LH. In conclusion the definitive study appears feasible. The observed advantage in short term recovery following LSH compared to LH appears to be supported. If a difference in QoR score of 5 is clinically significant and power is set at 0.8 with α at 0.05 the definitive study will require 186 women in either arm.
PITCHEYE: YOLOV5 AND BYTETRACK FOOTBALL PLAYER TRACKING SYSTEM IN FOOTBALL VIDEOS
Authors:   Khoury College of Computer Sciences Northeastern University Vancouver, Canada, Zhou Jiawei
Published: November 2024

Football, a universally beloved sport, captivates mil- lions of spectators worldwide. This paper explores the challenges of tracking football action in videos and presents the PitchEye project—a revolutionary initiative integrating YOLOv5 and ByteTrack algorithms for enhanced football video analysis. We detail the methodologies, results, and discussions on the performance of these algorithms, showcasing their strengths and limitations in tracking players, goalkeepers, footballs, and referees. YOLOv5, using the best.pt model, achieves mean detection rates of over 0.8 for goalkeepers, referees, players, and footballs, with notable improvements over default model results. In contrast, ByteTrack excels in accurately predicting trajectories for players and goal- keepers but faces challenges with smaller objects like footballs and swiftly moving referees. Despite these challenges, ByteTrack demonstrates commendable overall performance, showcasing its potential as a valuable tool for comprehensive object tracking in dynamic football video environments
ANALYSIS OF BIOMASS GASIFICATION USING ASPEN PLUS SIMULATION TOOL
Authors:   Department of Chemical Engineering Chandigarh University, Gharuan, Punjab, India, Sharma Ritik , Yatin Lodh Palak ,   Department of Chemical Engineering Chandigarh University, Gharuan, Punjab, India, Chand Suruj ,   Department of Chemical Engineering Chandigarh University, Gharuan, Punjab, India, Kumar Chaudhary Vikas ,   Department of Chemical Engineering Chandigarh University, Gharuan, Punjab, India
Published: November 2024

Biomass gasification stands as a beacon of hope in the quest for sustainable energy, offering a pathway to utilize organic matter for power generation while mitigating environmental impact. By converting biomass into a versatile syngas, this process holds immense potential in transitioning towards cleaner energy alternatives. Employing Aspen Plus, a robust process simulation tool, this study delves deep into biomass gasification, employing an equilibrium non-stoichiometric model at a precise temperature of 850°C. Through meticulous analysis, the focus lies on optimizing operational parameters to maximize both syngas production and subsequent power generation in a turbine. The findings underscore the efficacy of the approach, revealing key insights through sensitivity analysis and optimization techniques. By fine-tuning operational parameters, an optimal balance is achieved, yielding significant enhancements in syngas output and consequent power generation. These results not only serve as a practical guide for aspiring chemical engineers but also offer invaluable insights for industry professionals seeking to harness biomass resources for sustainable energy production
DESIGN AND SIMULATION OF ELEVATOR CONTROLLER USING VERILOG HDL AND IMPLEMENTATION ON FPGA
Authors:   Department of ECE Dr AIT, BANGALORE, Karnataka, India, V Kesthara , K Divyashree ,   Department of ECE Dr AIT, BANGALORE, Karnataka, India, MK Kushala ,   Department of ECE Dr AIT, BANGALORE, Karnataka, India, R Varsha ,   Department of ECE Dr AIT, BANGALORE, Karnataka, India, R Aishwarya ,   Department of ECE Dr AIT, BANGALORE, Karnataka, India
Published: November 2024

This project report presents the comprehensive design, simulation, and implementation of an elevator controller using Verilog HDL and its deployment on an FPGA board. The elevator controller system is a critical component in modern buildings, ensuring efficient and safe vertical transportation. By leveraging the capabilities of Verilog HDL and FPGA technology, this project aims to develop a robust and versatile elevator controller system that can handle multiple elevator requests effectively. Elevator systems play a crucial role in vertical transportation within buildings, impacting efficiency, safety, and user experience. Traditional elevator controllers are often implemented using complex hardware circuits or microcontrollers, which may limit flexibility and scalability. By utilizing Verilog HDL for design and FPGA for implementation, this project seeks to overcome these limitations and create a more efficient and adaptable elevator controller system. The design phase involves developing the elevator controller logic using Verilog HDL. This includes defining the behavior of the elevator system, implementing control algorithms, and incorporating safety features. Simulation tool such as Vivado is utilized to verify the functionality of the design, ensuring that it meets the specified requirements and operates correctly under various scenarios
PARTICULATE MATTER (PM2.5) RADIATIVE FORCING OVER THREE DIFFERENT CITIES IN INDIA
Authors:   Indian Institute of Tropical Meteorology, Pune, India, Panicker A. S. , Athulya S. ,   Laboratoire d'Optique Atmosphérique, Université de Lille, France, Ramakrishna K. ,   King Abdullah University of Science & Technology, Saudi Arabia, Beig G. ,   National Institute of Advanced Science, Bangalore, India, Das S. ,   National Institute of Technology, Rourkela, India
Published: November 2024

This paper discusses the estimates of radiative forcing exerted by particulate matter (PM2.5) over three different polluted cities in India. The PM2.5 concentrations were measured during Mar 2013 - Feb 2014 periods over Chennai, Guwahati and Jabalpur in south, central and North-eastern India. PM2.5 concentrations varied from 22.39±2.83 μg m-3 to 66.19±12.93 μg m-3 in Chennai. In Guwahati concentration ranged between 12.51±2.03μg m-3 to 100.69±21.41μg m-3 and it varied between 17.95±2.83 μgm-3 to 73.29±12.38 μg m-3 over Jabalpur. The Optical properties of aerosols and clouds (OPAC) model was used to obtain optical properties of PM2.5. The obtained optical properties were further used in Santa Barbara Discrete Ordinate radiative transfer model (SBDART) model to estimate Radiative Forcing of PM2.5. The radiative forcing was estimated at the surface and Top of the atmosphere (TOA) and hence the net atmospheric forcing was calculated. The estimated Atmospheric forcing (difference between surface and TOA forcing) values for PM 2.5 found to be + 5.61 Wm-2 to +8.69 Wm-2 , +3.49 Wm-2 to +15.86Wm -2 , +4.62 wm-2 to +9.61 Wm-2 respectively over Chennai, Guwahati, and Jabalpur, inducing significant climate warming over the region.
HIGGS BOSON DETECTION USING MACHINE LEARNING
Authors:   Department of Computer Engineering Xavier Institute of Engineering, Mahim, Mumbai, Narkar Prof. Nilambari , Shinde Shantanu ,   Department of Computer Engineering Xavier Institute of Engineering, Mahim, Mumbai, Jeyamurgan Pon Adityan ,   Department of Computer Engineering Xavier Institute of Engineering, Mahim, Mumbai, Rayan Chris ,   Department of Computer Engineering Xavier Institute of Engineering, Mahim, Mumbai, Tharakan Melvin ,   Department of Computer Engineering Xavier Institute of Engineering, Mahim, Mumbai
Published: November 2024

The Higgs boson is a cornerstone of modern particle physics, playing a crucial role in our understanding of the fundamental forces and particles that make up the universe. To comprehend its significance, let’s break down the concepts involved. Fundamentally, the Higgs boson is intimately connected to the Higgs field. The Higgs field is a theoretical framework proposed to permeate all of space, imbuing particles with mass as they interact with it. Imagine it as a sort of cosmic molasses through which particles move, and their interactions with this field give rise to their mass properties. This is a fundamental departure from earlier theories where mass was simply an intrinsic property of particles. The mass of a particle determines how it responds to forces. According to Newton’s second law, force equals mass times acceleration. So, a particle with more mass will accelerate less for a given force. This resistance to acceleration is what we typically think of as "mass." Crucially, not all particles possess mass. Photons, for example, are massless particles that travel at the speed of light and play a vital role in the electromagnetic force. However, many other particles, such as electrons and quarks, do have mass, and it’s the Higgs field that endows them with this property. The idea of the Higgs boson was proposed in 1964 by a group of physicists including Peter Higgs and François Englert, among others. They postulated its existence as a consequence of the Higgs field. The Higgs boson is essentially a manifestation of the Higgs field’s energy, similar to how a photon is a manifestation of the electromagnetic field. This discovery was a monumental achievement in particle physics, confirming a central piece of the Standard Model, which describes the fundamental particles and forces of the universe. For their groundbreaking theoretical work, Higgs and Englert were awarded the Nobel Prize in Physics in 2013. In summary, the Higgs boson and the Higgs field provide a fundamental mechanism for understanding why particles have mass, shedding light on one of the most fundamental questions in physics: the origin of mass itself.
SOUND-BASED WILDLIFE PROTECTION WITH MACHINE LEARNING
Authors:   Assistant Professor Department of Master of Computer Applications Vivekananda College of Engineering and Technology Puttur, India, M Mrs. Rajeshwari , B C Shodhan ,   II MCA, Department of Master of Computer Applications Vivekananda College of Engineering and Technology Puttur, India, V S Gahan ,   II MCA, Department of Master of Computer Applications Vivekananda College of Engineering and Technology Puttur, India
Published: November 2024

This research presents an automated system using acoustic and ML technologies to detect wildlife poaching. Utilizing Streamlit for user interface, users can upload and analyze audio files from restricted areas. The system alerts conservation officials via Telegram upon detecting suspicious sounds like gunfire or footsteps, ensuring swift responses. It comprises a user friendly interface for uploading and processing recordings, a ML algorithm trained to identify poaching-related noises using spectrograms, and real-time notification via Telegram for immediate action. This innovative approach enhances anti-poaching efforts efficiently and affordably, underscoring technology’s pivotal role in biodiversity conservation.
A NOTEON STRONG OPENSETS IN GTS VIA HEREDITARY CLASS
Authors:   Department Of Mathematics, Dwaraka Doss Goverdhan Doss Vaishnav College, Chennai, Tamil Nadu, India, Shankar R.
Published: November 2024

The aim of this paper is to introduce and study the strongσ^*-H-open set in a generalized topological space (X,λ) with a hereditary class H. We give discuss and some of their properties strongσ^*-H-open set and strongπ^*-H- open set in a generalized topological space (X,λ) with a hereditary class H. Also discuss various characterization strongσ^*-H-open set in a generalized topological space (X,λ) with a hereditary class H are given and its properties of such sets are discussed. Also we establish state some characterize of strong π^*-H-open set in a generalized topological space (X,λ) with a hereditary class H.
A COMPARATIVE STUDY BETWEEN GRILLAGE AND GIRDER SUPPORTING DECK STRUCTURES SUBJECTED TO A UNIFORM DECK LOADING USING FINITE ELEMENT METHOD
Authors:   Department of Naval Architecture and Marine Engineering Military Institute of Science and Technology, Dhaka, Bangladesh, Arafat Md. Yasin , Ahmed Faraz ,   Department of Naval Architecture and Marine Engineering Military Institute of Science and Technology, Dhaka, Bangladesh
Published: November 2024

This paper presents the design and strength assessment of several grillage and girder-supported structures under uniformly distributed load to find the one that saves materials without compromising the structural integrity. For this study, the initial design idea is derived from the deck structure of an existing ship. Then it is redesigned according to the desired load applying to several design combination cases planned with various spacing between the structural members. Each of the cases is optimized at around maximum allowable stress by altering various design variables, such as girders’ height and thickness, flanges’ width and thickness, the thickness of deck plating, and the inclusion of stiffeners and pillars. For estimating initial design parameters and local strength analytical formulas have been used and detail Strength performance is investigated utilizing the finite element method for each case. The study explores cost-effective design options, their applications, and limitations across various scenarios.
INTELLIGENT SURVEILLANCE SYSTEM
Authors:   Department of Computer Science FAST NUCES, Lahore, Asim Abdullah , Javed Hammad ,   Department of Computer Science FAST NUCES, Lahore
Published: November 2024

Watchful surveillance is one of the crucial aspects when it comes to ensuring security in any surroundings. Be it a shopping mall, a densely populated residential area or even busy roads vigilant surveillance is inevitable to ensure security and safety of citizens. This work focuses on the design and development of an Intelligent Surveillance System. It aims to enhance the security measures by identifying abnormal behavior like fight and fire in real-time scenarios. The proposed framework for fight detection includes 3 major functionalities/ components. i.e., preprocessing, Feature extraction and anomaly detection. Preprocessing is applied to optimize the data and get efficient results from the model. After Preprocessing this frame stream is passed to Mobilenet (A variation of CNN developed by google and using pretrained weights of imagenet) and Bi-LSTM that detect the fight in it. The fire use case has also been handled by using a CNN. The work done highlights the effectiveness of the proposed framework in accurately detecting anomalies, and contribution to enhanced security in surveillance systems.
A REVIEW OF CHALLENGES AND SOLUTIONS FOR USING MACHINE LEARNING APPROACHES FOR MISSING DATA
Authors:   Department of Engineering Cornell University, Ithaca, NY, USA, Ayaz Wani Aasim
Published: November 2024

Missing data poses significant challenges to the reliability of statistical analyses and predictive modeling across diverse research fields. This paper provides an in-depth review of both traditional and machine learning imputation techniques, enabling researchers to navigate the complexities of missing data with greater efficacy. We evaluate simple imputation methods, such as mean, median, and mode, and delve into more sophisticated strategies including regressionbased, hot and cold deck, and probabilistic models like Gaussian Mixture Models and K-Nearest Neighbors. Furthermore, the paper explores cutting-edge machine learning approaches like Random Forest, Multiple Imputation by Chained Equations, and deep learning models such as autoencoders and Generative Adversarial Networks. Our comprehensive analysis highlights the effectiveness of each method, tailored to various missing data mechanisms MCAR, MAR, and NMAR providing actionable insights for researchers to enhance data integrity and improve the outcomes of their studies.
SMART COLLEGE SYSTEM
Authors:   Assistant Professor, Computer Science & Application Department, George College, 𝑆𝑒n 𝐴𝑛𝑘𝑖𝑡a , 𝑆ℎ𝑎w 𝑅𝑎𝑛𝑖t ,   Pursuing BCA, George College, 𝐵𝑜𝑠e 𝑇𝑎𝑛𝑖𝑦𝑎 ,   Pursuing BCA, George College, 𝐷𝑎s 𝐴𝑑𝑟𝑖𝑏 ,   Pursuing BCA, George College, 𝑃𝑎l 𝑆𝑢𝑛𝑎𝑚𝑖 ,   Pursuing BCA, George College, 𝐶ℎ𝑜𝑤𝑑ℎ𝑢𝑟y 𝑉𝑎𝑟𝑠ℎ𝑎 ,   Pursuing BCA, George College, 𝐶ℎ𝑎𝑡𝑡𝑒𝑟𝑗𝑒e 𝐴𝑛𝑖𝑛𝑑𝑖𝑡𝑎 ,   Pursuing BCA, George College, 𝑆𝑖𝑛𝑔ℎ 𝑆𝑎ℎ𝑖𝑙 ,   Pursuing BCA, George College
Published: November 2024

A prototype of a smart college system is developed. It provides a real time Deep Learning based surveillance system at the surroundings of any college to find out the criminal (if any).And this system will generate an alarming message to inform the proper security person. This Deep Learning based system would also activate a Face Detection & Recognition system for the students, college teachers and college employees at the entrance. So that only the genuine registered persons will be allowed without restriction. The teachers and employees attendance will be marked automatically. And there will be a Deep Learning based automatic Smart Attendance System for every student in every classroom.
A HYBRID MODEL FOR CLASSIFICATION OF CARDIAC ARRHYTHMIAS USING CNN AND LSTM
Authors:   PG Scholar, Department of Computer Science, PSG College of Technology, Coimbatore, Tamil Nadu,, V S Mrudhhula , Thirumahal Mrs R. ,   Assistant Professor Department of Computer Science, PSG College of Technology, Coimbatore, TamilNadu,
Published: November 2024

Electrocardiograms (ECGs) are vital tools for monitoring heart activity and diagnosing a wide range of heart conditions, including arrhythmias, which are characterized by irregular heartbeats. Arrhythmias, if not properly diagnosed and treated, can result in serious complications such as stroke, heart failure, or even sudden cardiac arrest. Given these risks, the accurate detection and classification of arrhythmias is critical for ensuring timely and effective medical interventions. This project aims to tackle this challenge by using the MIT-BIH Arrhythmia Database, a wellestablished resource for arrhythmia classification, which contains data for five types of arrhythmias: Normal beat (N), Supraventricular ectopic beat (S), Ventricular ectopic beat (V), Fusion beat (F), and Unknown beat (Q). These different types of heartbeats present varying levels of difficulty in classification, and one of the key challenges is the imbalance in the dataset, where some arrhythmia types are significantly underrepresented. The project uses a hybrid deep learning model that blends Long Short-Term Memory (LSTM) networks with Convolutional Neural Networks (CNNs) to overcome these obstacles. CNNs are wellsuited to capture the minute changes in heartbeats that are indicative of various arrhythmia types because they are very good at spotting spatial characteristics and patterns within the ECG signal. On the other hand, LSTMs are designed to handle the temporal relationships in sequential data, which is critical when dealing with ECG signals and other time-series data. The hybrid model can handle the ECG data more efficiently and increase classification accuracy by fusing the advantages of both CNNs and LSTMs. Furthermore, to improve the quality of the input signals and lessen the consequences of dataset imbalance, sophisticated signal processing techniques are applied to the raw ECG data. This all-encompassing strategy not only enhances the model's overall performance but also strengthens its ability to detect uncommon arrhythmias that conventional techniques frequently miss. Ultimately, this project demonstrates the potential of using large, annotated medical databases and cutting-edge computational methods to improve automated arrhythmia diagnosis's precision and dependability, paving the way for better management of cardiovascular health.
HUMANOID ROBOT ON MILITARY APPLICATIONS
Authors:   Department of ECE SJB Institute of Technology, Bengaluru, Karnataka, India, Bharadwaj Sujendra G , B Shruthi ,   Department of ECE SJB Institute of Technology, Bengaluru, Karnataka, India
Published: November 2024

The rapid advancement of technology has heightened the demand for developing robots capable of performing complex tasks akin to human abilities. Humanoid robotics is at the forefront of current robotics research, as it aims to enable robots to interact with the environment and people in complex, dynamic ways. This field emphasizes social interactions, like gesture-based communication and collaborative activities, which integrate both physical and social engagement. This integration, essential for three-way interaction, seeks to merge physical and social dynamics at fundamental levels. In military contexts, technological innovation has created a need for robots capable of performing tasks akin to those of a soldier. This project focuses on building a humanoid robot designed to execute essential military operations through the use of speech recognition technology.
SOLID WASTE MANAGEMENT - A REVIEW
Authors:   Assistant Professor Department of Civil Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, India., Survase Mr. Niteen M. , Thorat Sakshi ,   Bachelors of Engineering Students Department of Civil Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, India., Wani Manas ,   Bachelors of Engineering Students Department of Civil Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, India., Bhargude Shweta ,   Bachelors of Engineering Students Department of Civil Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, India., Kalaskar Pratik ,   Bachelors of Engineering Students Department of Civil Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, India., Jagtap Suraj ,   Bachelors of Engineering Students Department of Civil Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, India.
Published: November 2024

With the increase in population, the management of municipal solid waste in India emerged as a severe problem not only because of the environmental and aesthetic concerns but also because of the total quantities of solid waste generated every day. The study was undertaken to study the existing system of collection, storage, transportation and disposal of MSW in Narhe, which is significantly progressing and growing village in population on the peripheral part of Pune. This study was carried out to access the quantity and quality of MSW. The study indicates that the solid waste management system is not proper. The present system is focused on collection and transportation of largely mixed unsegregated waste. The segregated collection of solid waste is needed to be planned. Awareness related to home composting should be spread across the community. The facility for composting and material recovery can be provided. The waste which does not undergo any physical, chemical or biological transformation which is inert in nature can be used as landfilling material.
RAILWAY TRACK CRACK DETECTION ROBOT
Authors:   Department of Electronics and Communication, Ahalia School of Engineering and Technology, Palakkad, Kerala-678557, A Arya , P Megha ,   Department of Electronics and Communication, Ahalia School of Engineering and Technology, Palakkad, Kerala-678557, S Shijila ,   Department of Electronics and Communication, Ahalia School of Engineering and Technology, Palakkad, Kerala-678557, M Sreelakshmy ,   Department of Electronics and Communication, Ahalia School of Engineering and Technology, Palakkad, Kerala-678557, Balamurugan Dr. V. ,   Department of Electronics and Communication, Ahalia School of Engineering and Technology, Palakkad, Kerala-678557, C Swetha ,   Department of Electronics and Communication, Ahalia School of Engineering and Technology, Palakkad, Kerala-678557
Published: November 2024

Cracks in railway tracks can be a serious safety concern for Indian Railways, which has one of the largest railway networks in the world. Cracks can develop in railway tracks due to seasonal changes, which cause the tracks to contract and expand.Ourrailbot presents a railway track crack detection system utilizing Raspberry Pi and Arduino Uno for efficient monitoring of track integrity. The increasing frequency of railway accidents underscores the need for reliable detection methods to identify cracks and defects in railway infrastructure. Our system employs an array of sensors, including ultrasonic and IR sensors, connected to the Arduino Uno for realtime data collection. The Raspberry Pi processes this data, implementing machine learning algorithms to analyze patterns and detect anomalies indicative of potential cracks. The system is designed to provide immediate alerts, allowing for timely maintenance and reducing the risk of accidents. This innovative solution aims to enhance railway safety and operational efficiency, ensuring a more reliable transportation network.
UNISYNC: UNLEASH THE CAMPUS SPIRIT – SHARING, SHAPING, SUSTAINING FOR A GREENER TOMORROW
Authors:   Department of MCA GL Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India., Rai Kajal , Kumar Vikas ,   Department of MCA GL Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India.
Published: November 2024

This paper presents UniSync, a web application platform designed to facilitate the buying, selling, and exchanging of used textbooks, stationery, and related materials among university students. The platform aims to promote sustainability and reduce waste on university campuses by encouraging the reuse and recycling of these items. Through an analysis of user behavior, satisfaction, and environmental impact, this study evaluates the effectiveness of UniSync in mitigating waste and fostering a more sustainable campus environment. Additionally, the paper explores UniSync's role in building a socially engaged student community and its potential for broader impact in promoting sustainability initiatives within universities.
TOOTHBRUSH BRISTLE DISTRIBUTION: A NOVEL APPROACH FOR MACHINE LEARNING MODELS TO ACHIEVE FASTER RESULTS IN EMERGENCY SITUATIONS
Authors:   Student at R.V.R. & J.C. College of Engineering Department of Computer Science and Engineering (Data Science) Guntur, Andhra Pradesh, India, Eppakayala Sathvik
Published: November 2024

Toothbrush bristle distribution: A new approach for machine learning models for faster results in emergency situations. This new method is designed to reduce the response time of machine learning models and improve the training process. The goal is to reduce the data requirements for training the model. This allows resources to be allocated to alternative learning methods. This will ultimately enhance response efficiency in crisis situations.
Modeling of Heart Failure with Cyclophosphamide
Authors: Evgenieva E. M. , Chernomordova A. V. , Okovitiy S. V. , Kulikov A. N.
Published: November 2024

The article presents the results of reproduction of the cyclophosphane model of heart failure. Outbred mice weighing 18–26 g at the onset of the experiment were used. All mice were divided into two groups with 10 animals in each. The first group was injected intraperitoneally with cyclophosphamide at a dose of 15 mg/kg, five times for 21 days (day 1, 5, 10, 15, and 21). The second group was intact animals. EchoCG was performed on the animals twice: baseline before the experiment (point 1) and one week after the last injection (point 2, day 28). The presented experimental model may be used for the study of drug toxicity prevention methods, as well as a model of heart failure with preserved left ventricular ejection fraction.
Comparative Analysis of Effects of Chloral Hydrate and Tribromoethanol on Electroneuromyographic Parameters in Mice
Authors: Prikhodko V. A. , Matuzok T. M. , Selizarova N. O. , Okovitiy S. V.
Published: November 2024

Selection of an optimal general anesthesia regimen is an essential prerequisite for the conduction of electrophysiological tests in laboratory animals. In this work, we compared the effects of two general anesthetic drugs commonly used in preclinical studies, i.e., chloral hydrate (CH) and tribromoethanol (TBE), on the parameters of neuromuscular function in outbred mice. CH and TBE were found to distinctly affect peripheral nerve conductivity and skeletal muscle contractility recovery following electrical stimulation-induced fatigue.
PENGENALAN DAN PELATIHAN PENGGUNAAN INTERNET OF THINGS PADA PESERTA DIDIK PANTI ASUHAN AL HUSNA UNTUK MENGIMBANGI PEMAHAMAN REVOLUSI INDSUTRI
Authors: Azam Muzakhim Imammuddin  , Yoga Septriandi Wirayoga , Hadiwiyatno  , Atik Novianti
Published: November 2024

Anak-anak yang tinggal atau hidup dalam pembinaan panti asuhan, mereka bisa dikatakan anak-anakyang tidak berdaya, karena hidup dalam serba kesederhanaan bahkan kekurangan mereka perlu diberdayakan dalam semua hal agar menjadi berdaya. termasuk dalam penguasaan teknologi informasi. Setiap individu masyarakat mutlak harus menguasai teknologi informasi seperti penggunaan komputer, laptop dan HP berbasis andoroid, oleh karena itu, di Panti Asuhan dikembangkan pelatihan teknologi informasi khsusunya tentang Internet of Things yang menjadi tren di era Industri Digtial saat ini. Adapun teori yang digunakan dalam pengabdian ini yaitu teori pemberdayaan, teori pelatihan, dan teori tekonologi informasi, Dalam penelitian ini peneliti menggunakan metode deskriptif kualitatif dengan teknik pengumpulan data melalui wawancara dan observasi. Penelitian ini dilakukan di Panti Asuhan Al Husna Perum Pondok Lestari Indah, Dusun Klandungan, Landungsari, Kec. Dau, Kabupaten Malang yang menjadi subjek pengabdian adalah seluruh anak yang tinggal dipanti asuhan.  Hasil dari penelitian ini yaitu: (1) Mengetahui kemampuan penguasaan teknologi informasi anak-anak yang tinggal di Panti Asuhan, (2) Memberikan penjelasan kepada pihak Panti Asuhan Kuncup tentang tata cara penyelenggaraan pelatihan teknologi informasi, (3) Membantu pihak Panti Asuhan menjalin kemitraan dengan lembaga atau organisasi yang bersedia bekerja sama dalam penyelenggaraan pelatihan teknologi informasi. Kesimpulan dari pengabdian ini adalah pelatihan teknologi informasi mampu meningkatkan kemampuan penguasaan teknologi komunikasi bagi anak-anak yang tinggal di Panti Asuhan Al Husna Kabupaten Malang.
Integrating Artificial Intelligence in Education:
Authors: Wangdi Pema
Published: November 2024

Artificial Intelligence (AI) is transforming educational practices by facilitating personalized learning, automating grading processes, and enhancing support through intelligent tutoring systems. This systematic review explores AI's integration in educational settings, highlighting its contributions to increased productivity and tailored learning experiences. It addresses key challenges including data privacy, algorithmic bias, and the need for enhanced accountability and transparency in AI applications. The review also discusses strategic recommendations for embedding ethical AI into curriculum design and emphasizes the importance of professional development for educators. Collaboration among educational stakeholders is vital for advancing responsible AI utilization. By synthesizing recent literature, this review provides insights into AI tools' effectiveness, explores ethical dimensions of technology in classrooms, and suggests future directions for research and practice in educational AI. This analysis serves as a resource for educators, policymakers, and technologists aiming to optimize AI benefits in education.
A streamlined proximity extension assay using POEGMA polymer-coated magnetic beads for enhanced protein detection
Authors: Hu Jiumei , Zhang Pengfei , Shao Fangchi , Wang Tza-Huei
Published: November 2024

The detection of protein biomarkers presenting at low concentrations in biological fluids is essential for disease diagnosis and therapeutic monitoring. While magnetic beads-based solid-phase immunoassays have shown promise in achieving high sensitivity for detecting low-abundance proteins, existing protocols suffer from limitations such as the cumbersome need for bead blocking and washing steps to minimize adsorption of non-specific biomolecules. These extra requirements lead to increased assay complexity and the risk of procedural errors. In this study, we present a streamlined magnetic proximity extension assay (MagPEA) using poly (oligo (ethylene glycol) methacrylate) (POEGMA)-coated beads. The polymer brush on bead surface, on the one hand, provides an effective mechanism for repelling non-specifically bound biomolecules that contribute to background signal generation without performing any bead blocking and washing steps. On the other hand, it facilitates the immobilization of capture antibodies on bead surface by simply embedding the antibodies onto the porous polymer under vacuum. Using the human inflammatory factor IL-8 as a demonstration, we show that the incorporation of POEGMA beads into MagPEA workflow significantly simplifies assay procedure while maintains high sensitivity.
Integrated analysis of lncRNA and mRNA expression profiles in cutaneous leishmaniasis lesions caused by Leishmania tropica
Authors: Hadifar Shima , Masoudzadeh Nasrin , Andersson Björn , Heydari Hossein , Mashayekhi Goyonlo Vahid , Kerachian Mohammadali , Persson Josefine , Rahimi-Tamandegani Hasan , Erfanian Salim Reza , Rafati Sima , Harandi Ali M.
Published: November 2024

Background

Cutaneous leishmaniasis (CL), caused by Leishmania (L.) species, remains a neglected tropical disease in many developing countries. We and others have shown that different Leishmania species can alter the gene expression profile of human host cells. Long non-coding RNAs (lncRNAs) have been found to play a role in the pathogenesis of leishmaniasis through dysregulation of transcriptome signatures. Understanding the regulatory roles of lncRNAs in the biological networks involved in leishmaniasis can improve our understanding of the disease.

Methods

Herein, we used our previous RNA sequencing data (GSE216638) to investigate the profile of lncRNAs in the skin lesions of L. tropica-infected patients. We employed the weighted gene correlation network analysis (WGCNA) algorithm to establish co-expression networks of shared genes between CL patients and infer the potential role of lncRNAs in CL patients. We identified hub genes and trans- and cis-acting lncRNAs, and carried out functional enrichment analysis on a key co-expressed module related to L. tropica-infected patients.

Results

We found substantial involvement of lncRNAs in the CL patient dataset. Using the WGCNA method, we classified all included genes into seven modules, with a module (turquoise) being significantly correlated with the studied clinical traits and identified as the key module. This module was mainly involved in the “interferon gamma signaling” and “cytokine signaling” pathways. We highlighted several lncRNAs and their co-expressed mRNA pairs, like SIRPG-AS1, IL21R-AS1, IL24, and TLDC2, as hub genes of the key module. Quantitative RT-PCR validated the expression of several genes in the lesions of an independent cohort of L. tropica-infected patients.

Conclusions

These findings enhance our understanding of the human skin response to L. tropica infection. Furthermore, the hub genes identified in this study are worthy of further evaluation as potential targets in the development of more effective treatments and preventive measures for CL caused by L. tropica.
A study on the intervention effect of a case management model that breaks through spatiotemporal characteristics in home-based phase II exercise rehabilitation post PCI
Authors: Jin Haiqin , Wu Lingsha , Huang Ping , Zheng Yeping , Sun Yan , Lu Qin , Meng Xiaoqin , Yu Zhifang
Published: November 2024

Objective

This study aims to explore the effect of a case management model that breaks through the temporal and spatial characteristics on the at-home phase II exercise rehabilitation of postoperative patients treated with percutaneous coronary intervention (PCI).

Methods

We used the convenience sampling method to select 103 patients with coronary artery disease (53 in the observation group and 50 in the control group) who were admitted to the Department of Cardiovascular Internal Medicine at the Jiaxing No. 2 Hospital in January 2022 and January 2023 and underwent PCI treatment as study subjects. Patients in the control group were managed by the conventional continuity of care model, and those in the observation group were managed by the case management model that breaks through the temporal and spatial characteristics. Both groups of patients were intervened and followed up for 6 months, comparing the adherence to home II exercise rehabilitation and regular follow-ups, coronary heart disease risk factor indexes, unplanned readmission rate, and the incidence of adverse cardiovascular events between the two groups of patients.

Results

Exercise adherence and regular follow-up adherence of patients discharged from the hospital at 1, 3, and 6 months after PCI were higher in the observation group than in the control group (P < 0.05). The comparison of risk factor indicators of patients in both groups at 6 months after discharge with those of patients before discharge showed different degrees of improvement, and the difference was statistically significant (P < 0.05). However, the difference in fasting blood glucose in the control group at 6 months after discharge compared with that before discharge was statistically significant (P < 0.05), whereas there was no statistical significance in the observation group (P > 0.05). The incidence of major adverse cardiovascular events and unplanned readmission at 6 months after discharge between the two groups was lower in the observation group than in the control group, and the difference was statistically significant (P < 0.05).

Conclusion

The case management mode that breaks through the spatiotemporal characteristics can improve the exercise adherence and regular follow-up adherence of post-PCI patients’ at-home phase II exercise rehabilitation, which can effectively control the indexes of body mass index (BMI), triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) and reduce the rate of unplanned readmission and the incidence of adverse cardiovascular events.
NESZ effects on wind retrievals from Gaofen-3 SAR wave mode data
Authors: Ren Lin , Dai Jinyuan , Yang Jingsong , Jiang Chong , Zheng Gang , Chen Peng , Li Xiaohui
Published: November 2024

This study analyzes the effects of noise equivalent sigma zero (NESZ) on wind retrieval accuracy based on the estimated NESZ and wind retrievals from Gaofen-3 (GF3) synthetic aperture radar (SAR) wave mode data. The NESZ was estimated from the normalized radar cross-section (NRCS) bottom envelope from the calm sea (winds <1 m/s). The data used included GF3 SAR wave mode data, collocated NOAA/NCEP Global Forecast System (GFS), Advanced Scatterometer (ASCAT) and National Data Buoy Center (NDBC) buoy wind data. First, the GF3 data were recalibrated using a numerical weather prediction method in which the recalibration coefficients at four polarizations and different incidence angles were estimated. The NESZ trends were then estimated along with the in-orbit time and incidence angles based on the recalibrated GF3 NRCS. NESZ trends show no obvious change with in-orbit time, whereas it shows significant fluctuations with the incidence angle. Moreover, wind speed and direction were retrieved by the CMOD5.N model using the optimal scheme (for co-polarized data, VV, and HH data) and a linear model (for cross-polarized data, VH, and HV data). The wind retrieval accuracy was estimated by comparison with ASCAT and NDBC winds. Finally, the wind retrieval accuracy with the NESZ for different incidence angle bins was analyzed. The root mean square error (RMSE) of the wind speed and direction increase with the NESZ for each polarization. For the NESZ effects, the co-polarized data are more evident than the cross-polarized data for wind speed retrieval, whereas the two co-polarized data are close for wind direction retrieval. When the NESZ increases from −41 dB to −29 dB, there is a wind speed RMSE degradation of 1.5 m/s, 1.2 m/s, 0.7 m/s and 0.5 m/s for VV-, HH-, VH-, and HV-polarized data respectively, while there is a wind direction RMSE degradation of 5o for co-polarized data. This reveals the necessity of reducing the SAR NESZ to improve wind retrieval accuracy.