bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Security, Decarbonization, and the Environmental Justice Movement
Authors: Leal-Arcas Rafael , Gasimov Ahad , Reddy Vundhyala Shanthan
Published: May 2023

This article will analyse two key challenges of today: 1) energy security and decarbonization in the context of the United Nations’ sustainable development goals, and 2) decarbonization and energy security from the perspective of environmental justice. Energy security and decarbonization are integral components of the United Nations’ Sustainable Development Goals (SDGs). Specifically, they are addressed in SDG 7, which aims to ensure universal access to clean and affordable energy. Access to energy is crucial for the development of vital sectors such as agriculture, business, communications, education, healthcare, and transportation, and a lack of access to energy can impede human and economic development. In addition, the effects of climate change are disproportionately borne by those residing in the developing world. This inequity needs to be at the core of any climate change research – both at a practical and theoretical level. However, some scholars have argued that dominant modes of thinking about climate change and environmental hazards have often chosen to ignore this inequity or have not placed such inequity at the core of their analysis. This is where the Environmental Justice movement acts as a game-changer. We argue that it provides an alternative rationality to approach environmental hazards, with the social injustices and inequities at its center that are direct or indirect effects of environmental degradation and climate change.
The Impact of Ambidextrous Leadership on Firm Performance: An Empirical Analysis of Syrian SMEs
Authors: Hmedan Abd Elkareem
Published: May 2023

This study investigates the impact of ambidextrous leadership on firm performance among Syrian small and medium-sized enterprises (SMEs). Ambidextrous leadership, which entails the ability to adapt and balance between competing demands, has been identified as a key driver of organizational success. Using a sample of 381 SME business owners in Syria, the study employs multiple linear regression analysis to test the relationship between ambidextrous leadership and firm performance. The results indicate a positive and significant relationship between ambidextrous leadership and firm performance, thus suggesting that business owners who effectively balance both exploratory and exploitative activities are better positioned to enhance their firms' performance. The findings contribute to the existing literature on ambidextrous leadership and provide practical recommendations for business owners and policymakers in the Syrian context.
The Moor and the fair lady- An analysis of Othello, Shakespeare’s play through the lens of marginalisation
Authors: Tharakan Alen
Published: May 2023

William Shakespeare’s play Othello features the life of Othello, a black Moor, a Muslim, who although is the most trusted man of the King of Venice, struggles to fit in with the prominent White, Christian medieval framework of Venice. He indirectly subscribes to the prevailing morality and thinks himself inferior to the rich, white European Christians. He tries to be like them, imbibing their values and their codes, but still struggles with his different color and has an inferiority complex. This ultimately leads to his downfall and it results in him killing his beloved wife, Desdemona and it ultimately led to his suicide.
IoT based School Bus Monitoring System
Authors: S Srinivas , V B Shreyas , . Sriram , PY Vishnuraata , Sudha Dr. PN
Published: May 2023

Abstract: An IoT-based school bus monitoring system is a technology solution that utilizes the Internet of Things (IoT) to monitor and track school buses in real-time. These systems use Internet of Things (IoT) devices and sensors to track the location, speed, and safety of school buses in real-time, allowing schools and parents to monitor their children's travel to and from school. In this literature survey, we will explore the past studies on IoT-based school bus monitoring systems, including their benefits, challenges, and areas for future research. Through a review of the existing literature, we aim to provide a comprehensive overview of the state of the art in this field and identify opportunities for further study.
Visualization of Data Structure and Algorithm
Authors: P Keerthana , Afthab Mohammed , Shetty Meghanath , M Arvind
Published: May 2023

Abstract: Nowadays, Data Structure and Algorithms are an essential part of computer science because they help us to store, process, and analyse large amount of data. In Data Structure we use serval technics to organize the data. We believe the best way to understand Data Structure and Algorithms is to see them in action. We developed interactive visualization for a variety of algorithms where human brain can easily understand and work on it. The purpose of developing this project is to make human understand Algorithms easily. And this project helped us to understand, DataStructure and Algorithms efferently. The analysis of data structures and algorithms has traditionally been theoretical and mathematical. This makes it time-consuming, challenging to study, and lacking in comprehension of how a problem is implemented in real life. To assist students and teachers in visualising data structures and algorithms with their actual execution, we have designed and provided an idea, data structures,and algorithm.
Endangered Bird Species Classification Using Machine Learning Techniques
Authors: R Suhas Reddy B , Nikhil Veluri Raviram , Reddy P V Bhaskar , S Vikramadhitya P , C Abhilash
Published: May 2023

Abstract: Birds are a diverse class of warm-blooded creatures, with around 10,000 living species presenting a range of characteristics and appearances. Although though individuals frequently enjoy viewing birds, accurate bird species identification requires an understanding of the field of ornithology. To address this issue, we offer a CNN-based automated model that can distinguish between several bird species using a test dataset. Our model was trained using a dataset of 7,637 pictures representing 20 distinct bird species, of which 1,853 were selected for testing. The deep neural network's design was developed to analyse the images and draw out traits for categorization. We tested a variety of hyperparameters and techniques, such data augmentation, to improve performance. According to our findings, the suggested model evaluated on the dataset had a promising accuracy of 98%. Our study also emphasises the value of utilising technology to safeguard and maintain endangered bird populations as well as the promise of convolutional neural networks for bird species identification. In summary, the suggested methodology can help with bird population identification and tracking, which will ultimately help with their preservation and protection. The model's accuracy may be increased, and its application can be broadened to cover other bird species
Fabric Property and Defect Detection using Deep Learning Model
Authors: M Kumuthini , J Shre Subasine , U Veenaloshini , D Rajeswari
Published: May 2023

Abstract: Textile manufacturing errors waste a lot of resources and lower the quality of the end products [2]. Visual image analysis using machine learning (ML) techniques may be quite useful in identifying fabric properties and defects. One of the most essential and difficult computer vision jobs in textile smart manufacturing is the automatic fault evaluation of these fabric materials. The objective of the proposed work is to develop effective deep learning models that are trained on fabric photos for quick fabric property and defect identification Convolutional Neural Network (CNN). A modified CNN architecture is used for the fault detection procedure. If the device detects a probable fault in the cloth roll, it stops operating and alerts the adjacent operator who then decides whether to accept or reject the results of the system evaluation, provides the go-ahead for the process to proceed, and switches to the next fabric picture. These findings demonstrate a system that can operate swiftly and effectively while precisely identifying a wide range of faults.
Design and Implementation of an Automatic Physiotherapy Device for Ankle
Authors: A. K Nivedha , C Anisha , K Anjana Sunilkumar , Shaji Jilsha , T Kamalini
Published: May 2023

Abstract: The design and development of the entire system, which includes an automatic device worn over the affected body part (such as the ankle) to assist with physical therapy exercises, has been successfully completed. The device is equipped with a Driver module and switches for setting the desired duration, and it stores the direction and speed of motion, which is periodically followed by the device. The Motion control feature ensures safe and accurate movement within set limits. The switches send speed and angle inputs to an On-board Micro-controller, which analyzes the data and repeats the action based on a predetermined algorithm. A high-torque DC-Gear motor controls the mechanical axes of the device.
Detection of PCOS using Ensemble Models
Authors: A Prof Ajil , Jain Tanvi , Namratha T M , S Vismaya , Lakshmi Thummaluru Ganga
Published: May 2023

Abstract: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that affects women of childbearing age. It is characterized by a range of symptoms, including irregular monthly cycles, hirsutism, and childlessness. Early diagnosis and detection of PCOS is vital for successful management of this condition. In the last few years, machine learning algorithms have shown great results in the diagnosis of various medical conditions. The proposed model is an ensemble model consisting of XG Boost and Random Forest to detect PCOS in women by analysing a dataset of 541 women, including 177 patients with PCOS. We analyse a dataset of clinical and demographic variables from women with and without PCOS and use various machine learning algorithms such as Ada boost, Random forest ,XG boost, Decision tree and a hybrid model to predict the presence of the condition. We evaluate the accuracy of our models by comparing the performance of the above listed algorithms. The proposed method consists of a hybrid model which is a combination of two algorithms that is Random forest and XGBoost and is yielding one of the highest accuracies of 97.2%.This early detection could potentially improve the level of care for women with this condition.
Generation of Electricity using Trash
Authors: Sharanabasappa Aladalli , S V Kiran , S V Arun , . Sharanabasava , . Kiranakumara
Published: May 2023

Abstract: The gigantic growth in the amount of waste materials produced in India and their potentially dangerous results in the environment and human health Which have led to create several diseases in Human bodies, so we need to ingurgitate scholarly methods for safe arrangement of garbage. This is an innovative idea of generating electricity Using solid waste. Which lead to decrease pollution by stopping to produce almost all dangerous gasses like CO2, CO, SO2, NO2 and Heavy metals such as mercury to a huge number. With a population of millions India produces large number of wastes every day to Contemplate about this idea. So, we felt that it is valuable working on this project and it is high time to inject the idea of Waste to Energy in India. Firstly, a map plan was carried out for research to collect the fact of total waste generation in India. During this research it was found that some locals were generating electricity using this process ago which encouraged the researchers to carry forward this Project.
Enhancement in ATM Machine Facility Using Face Recognition Security and OTP with Shuffle Keyboard
Authors: More Anjali S.
Published: May 2023

Abstract: To enhance the security of the ATM. To avoid ATM robberies and the wrong person misusing the ATM so that they can lead a secure and reliable life. The system is to support the intelligence system. Without hesitation, use ATMs to make the world a conversion community. Once the client inserts the cardboard into the ATM, a session is processed, so the system can start a face detection victimization camera placed close to the ATM and builds short-lived identity information of the clients, and the user face verification to perform on the ATM. A good user would use the traditional method because the invalid user cannot access the ATM card, they offer the secondary identification to the system mechanically, and the unauthorized person would continue the transactions. The objective of the proposed study in this paper is to prevent ATM fraud as well as secure transactions from the user side.
Review on Machine Learning for Resource Usage Cost Optimization in Cloud Computing
Authors: Tanwar Navdeep , K V Dr. Praveen Kumar
Published: May 2023

Abstract: Small and medium-sized enterprises are increasingly adopting cloud computing, and optimizing the cost of cloud resources has become a crucial concern for them. Although several methods have been proposed to optimize cloud computing resources, these methods mainly focus on a single factor, such as compute power, which may not yield satisfactory results in real-world cloud workloads that are multi-factor, dynamic, and irregular. This paper proposes a new approach that utilizes anomaly detection, machine learning, and particle swarm optimization to achieve a cost-optimal cloud resource configuration.
Simulation of a Battery Charging and Discharging Using Matlab
Authors: S Shandeep Vignesh H , M Arun Prasad P , R Santhosh Raju
Published: May 2023

Abstract: The modelling and simulation of the batteries are the subjects of this study. It requires using MATLAB to understand the mathematical link between the battery input, output, and simulator parameters. Currently, we observe an increase in interest in the power system from entities like electric utilities, energy service providers, auto manufacturers, etc. This paper demonstrates how to simulate charging or discharging using Simulink and MATLAB. Since its development over the past century, electricity has become the most adaptable and common type of energy used worldwide. With the help of batteries, we may store electrical energy in the form of chemical energy, which can later be used to produce electricity once more
Fundraising Tracking System for NGOs Using Blockchain
Authors: Raut Ajay , Shevtekar Prof. Sumit
Published: May 2023

Abstract: NGOs in developing nations get financing from donor agencies for various goals, including disaster assistance, education advancement, women’s empowerment, and economic development. However, due to reports of fund misuse and record irregularities, some donor agencies have lost faith in these NGOs.For example, in education funding, some students appear onthe records of multiple NGOs as beneficiaries, even though only one NGO should be paying for a specific student, so here blockchain plays an important role, The lack of transparencyin charities has resulted in a decrease in social investment and a decrease in donor confidence, as donors are frequently uninformed of how their donations are being used. Corruption exacerbates this skepticism. To address these challenges, the Charity-Chain decentralized network has been suggested, which will use the Ethereum blockchain and smart contract-based incentives to validate the impact of social organizations. This improved transparency would help funders, such as charitable organizations, impact investors, and small donors, to more readily monitor their transactions and re-establish trust in these social organizations.
Personality Detector
Authors: Shukla Shivankar , Mishra Siddharth , Pandey Shubhankar , Sharma Divyansh , Verma Dr. Neeta
Published: May 2023

Abstract: Personality detection has become an important area of research due to its potential applications in various fields such as marketing, psychology, and human resource management. In this paper, we present a personality detector that utilizes the Big Five personality traits model to analyze and predict the personality traits of individuals. The Big Five personality traits model is widely used in personality psychology, and it consists of five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. Our system utilizes a machine learning algorithm that analyzes various features such as text, social media posts, and speech to predict an individual's personality traits. The front-end of the system is developed using Python and Django, making it easy to use and accessible to anyone with an internet connection. We evaluated our system using a dataset of 1000 individuals and achieved an accuracy of 85% in predicting their personality traits
Stock Market Forecasting
Authors: Phatangare Sheetal , Madhvaswala Abbas Taherbhai , Rahate Kashish , Nogamawala Mohammed , Ahmed Mohamed Maged Mohamed
Published: May 2023

Abstract: Stock market forecasting seeks to determine the worth of a firm’s financial stocks in the future. Machine learning is being used in recent developments in stock market forecasting technology to produce forecasts based on the values of current stock market indices by training on their previous values. Future stock price projections can be difficult to make when trying to anticipate the stock market. It is incredibly challenging to forecast the stock market since shares fluctuate so frequently. Every day and frequently, stock. Foreseeing trends in the stock market is often correct using this method. This study forecasts the closing prices of numerous corporations using Long-Short Term Memory (LSTM) methodologies. These models are assessed using RMSE, which is one of the commonly used error measures. LSTM works better than SVR, as shown by the experiment's findings
Numerical Investimation of Heat Transfer in A Rectangular Channel with Triangular Vortex Generators in the Channel at Blade Angle 30° for Reynolds no. of 1500, 2000
Authors: Kumar Manoj , Sumita  , Jain Pramod , Kumar Sunil , Sharma Nikhil , Suhaib Md.
Published: May 2023

Abstract: The compact heat exchanger is widely used in fields such as automobile industry, heating and air conditioning, power system, chemical engineering, electronic chip cooling and aerospace, etc. The subject of heat transfer enhancement is of significant interest in developing compact heat exchanger to meet the desire of high efficiency and low cost with the volume as small as possible and the weight as light as possible. The use of ribs/baffles placing in the cooling channels or channel heat exchangers is one of the commonly used passive heat transfer enhancement technique in single-phase internal flows. Periodically positioned ribs/baffles in the channels interrupt hydrodynamic and thermal boundary layers. Downstream of each rib/baffle the flow separates, recalculates, and impinges on the channel wall and these effects are the main reasons for heat transfer enhancement in such channels. the effect of vortex generators in the spanwise averreged nusselt number. The comparison between the plots of spanwise avereged Nusselt number with and without vortex generators shows that there is a considerable increase in Nusselt number near the vortex generator region and this effect decreases as we move far from the vortex generator region in the stream wise direction.
Research Paper on Android Application for Diet Recall
Authors: Ingle Gaurang , Parimal Sarthak , Gulhane Sakshi , Shribate Dhiraj , Zanwar Prerna , Ghatol Prof. A. P.
Published: May 2023

Abstract: In today’s modern world people all around the globe are becoming more interested in their health and lifestyle. But just avoiding junk food and doing an exercise is not enough, we require a balanced diet. A balanced diet based on our height, weight and age can lead a healthy life. Combined with physical activity, your diet can help you to reach and maintain a healthy weight, reduce your risk of chronic diseases (like heart disease and cancer), and promote your overall health. A balanced diet is one that gives your body the nutrients it needs to function correctly.’ Our aim is to make a system that helps users to make personalized diet plan and recall them for their meal time to time and help them to create a balance in overall calorie intake throughout the day. The system would remind the user on a daily basis to have their meal and with many options to choose from for a personalize meal plan for a day. Also, the user will be able to choose any type of healthy food they want as per their convenience out of the options that will be there to them by the system. Our body use calories for basically everything like breathing, walking, running etc. On average a person needs 2000 calories per day but specifically intake of calories depends upon persons physical aspects like weight, height, age and gender. So, your food choices each day affect your health — how you feel today, tomorrow, and in the future. Thus, a proposed system gives required calories for a diet plan based on your physical aspects and your end goal.
A Review on the Influence of Test Bed Dynamic Characteristics on Thrust measured during Static Fire Testing of Solid Rocket Motor case
Authors: Muhammed Safna K , Raj Prof. Indu Susan
Published: May 2023

Abstract: Solid propelled rocket motors (SRMs) static firing tests are crucial tests in the aerospace industry while developing new motors as well as to ensure the quality of a motor batch. The operator can use this sort of test to determine whether the motor performance meets the project criteria by obtaining the measured "thrust versus time of burning" graphic the motor produces while burning. In this paper over all thrust measurement uncertaintyof a solid propellant rocket motor test bed is studied. During static test of solid motors requires the dynamic characteristics of the Static test configuration. To find out the magnitude of thrust oscillation, characterization of test setup and force transfer characteristics from motor case to load cell are required.
Transportation Payment by using Smart Card
Authors: Suki Jidnyasa , Pahade Ishwari , Sawant Snehal , Bhosale Vikram , Joshi Prof. Shweta
Published: May 2023

Abstract: It is often notice in a public transportation that the conductor face a lot of problems in collecting the fare from the passengers. Money handling and returning the access amount to the passengers after deducting the fare amount, inspecting a travel pass becomes complex when the congestion that is the number of passengers are very large in numbers is high and this complexity cannot be managed effectively. Productivity in the urban areas is much dependent on how efficient the transport system is to move a travelling groups from multiple origins to multiple destinations. Importance of this smart system helps in enhancing the process and increases the efficiency of fare collection and congestion management.The system consist of a scanner system to scan the smart card which can be topped up by the recharge centers and GPS module to track the distance travel by the passengers. Thus amount gets deducted from the passenger’s smart card for only the distance travel. This enhances the proper utilization of the resources , reduces time and serves to be economic for the citizens.
Detection and Classification of Leukemia And Myeloma Using Soft Computing Techniques
Authors: Shrivastav Kriti , Souza Clenzila De , Desai Nidhi , Patil Pratibha , Sayyed Nausheen , Dessai Manisha Fal
Published: May 2023

Abstract: Blood cancer is a type of cancer that affects the blood cells. Medical image processing technology is essential in both early disease identification and cancer cell analysis. Blood cancer can impact the lymph nodes, bone marrow, blood cells, lymph nodes, and other lymphatic system components. A primary cause of blood cancer is an unusual and excessive amount of white blood cellular proliferation. Traditional cancer cell detection is time-consuming and inaccurate to a large extent, hence an automated approach based on soft computing techniques is presented to predict cancer cell presence and identify two types of blood cancer which are leukemia and myeloma. The dataset for Myeloma is acquired from TCIA (The Cancer Imaging Archive) repository and the Leukemia dataset comes from Kaggle-Blood Cell Images, both of which are available to the public. The datasets are already pre-processed. In our study, we have compared different hybrid models like DenseNet with XGBoost, InceptionResNet with SVM, etc from which the combination of VGG-19 for feature selection and SVM for classification gives the best performance. We have achieved Classification Accuracy of 96.4%(0.964), Precision(0.964), F1 Score(0.964) and Recall(0.964) for SVM.
Arabic Language Learning Approach Using Smart Technology in Higher Education
Authors: Arifin Zainul , Desrani Ayu , Ritonga Apri Wardana , Ibrahim Faisal Mahmoud Adam
Published: May 2023

This research aimed to analyze the implementation framework of smart technology in learning Arabic at the Nusantara Islamic University of Bandung. Researchers adopted a mix-method, namely quantitative and qualitative. Quantitative data was obtained from distributing questionnaires from the application of the smart technology used, and qualitative data were obtained from interviews with students studying the Arabic language and literature at the Nusantara Islamic University of Bandung. Quantitative data were analyzed descriptively, namely calculating the percentage of technology use. The results of this study indicate that the use of technology uses smart technology as a teaching and learning tool. The use of smart technology makes learning easier, more interactive, and more effective. Other technologies are used such as social media, and language laboratories with different hardware and software facilities that support learning Arabic. The use of smart technology is overshadowed by positive and negative impacts that must be the main concern of all users.
Special Issue: Biologic ACL Repair - Augmentation
Authors: Dallo Ignacio , Murrell William D.
Published: May 2023

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A Critical Interpretation and Research Data Analysis On Urdhvag Amlapitta
Authors: Yadav Deepak , Borkar Preeti , Mhaiskar Bhushan , Khaire Utkarsha
Published: May 2023

Amlapitta is a vyadhi of annavahasrotas induced by a vitiated Agni. Amlapitta is a condition in which the Pachaka pitta rises owing to samata. Pitta is considered Amlapitta—Tridoshaja Vyadhi Kapha Pradhana (a compound disease caused by multiple factors). Acharya Kashyap has recognized the participation of three Doshas in Amlapitta, although Madhav Kara has accepted Pitta's dominance in this ailment. Amlapitta is not listed as a separate ailment by Acharya Charka, but it is included as one of the Lakshanas in Grahani. Along with those stimulating stimuli, worry and stress have exacerbated the condition, especially Urdhwanga Amlapitta. The Study aims to find out, compare and analyze the results of different published articles on Urdhwanga Amlapitta and the Objectives of the Study to analyze different results of published results of Urdhwanga Amlapitta. To analyze the result and conclusion of the study. This study was conducted to assess the effectiveness of Ayurveda treatment for Urdhwaga Amlapitta in terms of improvement in symptoms, cure rate, satisfaction, and side effects if any. Important results all the published study are given significant results on Urdhwanga Amlapitta. Discussion of the study should reveal that all the studies of Urdhwanga Amlapitta have given significant results and the dose of different drugs shown significant results. Conclusion of the study, i.e., Research investigations on the management of Amlapitta, are presented in this article, all of which were conducted on Shamana Chikitsa. In lifestyle-dependent disorders like Amlapitta, research suggests that Shamana Chikitsa combined with Pathya-Apathya produces greater results. Here, an attempt has been made to analyze the research work about managing Amlapitta. This article conducted a systemic review of 6 research (at different Ayurved colleges & Hospitals in India).
Quantitative investigation on the deformation modes and cracking behavior during cyclic torsional loading of extruded pure Mg and Mg-3Y alloy
Authors: Zheng Jiang , He Liuyong , Wen Guilan , Shi Rong , Xia Lihong , Li Tianjiao , Jiang Bin
Published: May 2023

This study explores the effect of adding 3wt.% Y to pure magnesium (Mg)
on its mechanical behavior under cyclic torsional loadings at room
temperature. The research examines deformation and cracking modes in
both pure Mg and Mg-3Y samples. Deformation modes are monitored using
quasi-in-situ EBSD observations coupled with slip trace analysis. The
findings reveal that basal slip dominates the cyclic deformation
throughout the fatigue life of the pure Mg sample, while both basal and
pyramidal slip dominate the cyclic deformation in the Mg-3Y sample.
Intergranular cracking is the primary cracking mode for both samples
under cyclic torsional loadings. Basal and pyramidal slip PSB cracking
serves as a primary transgranular cracking mode in the pure Mg and Mg-3Y
samples, respectively. The study also investigates the underlying
mechanism governing the activity of various deformation modes, cracking
modes, and mechanical behavior.
Deformation effect of melt pool boundaries on the mechanical property anisotropy in the SLM AlSi10Mg
Authors: Liang Yu , Jiang Zihao , Xu Pingwei , Liang Yilong
Published: May 2023

The effect of microstructure characteristic on the anisotropy of
mechanical properties has been studied for a selective laser melt (SLM)
AlSi10Mg material. The cell structure and fine grains at the melt pool
boundarie (MPB) are gradually eliminated by different heat treatment
processes. Althought the cell structure of MPB has been eliminated, it
is found that the mechanical properties of the transverse specimen and
longitudinal specimen are still different due to the heterogeneity of
grain. In the process of plastic deformation, when the tensile direction
perpendicular to the MPB, the deformation incompatibility between fine
grains and columnar grains lead to the excessive stress concentration
and rapid fracture along the zone boundary. The change of loading
direction can alleviate strain localization and improve the uniform
deformation ability of the sample. The heterostructure of SLM AlSi10Mg
is related to the remelting and resolidification of MPBs. The results
provide guidance for the design of SLM AlSi10Mg material with better
mechanical properties.
Expert System For Maintenance and Rehabilitation of All Types Of Pavements (ExFMRAP)
Authors: musa muhammad
Published: May 2023

There are numerous obstacles in the construction industry today,
including those related to technical and financial issues as well as
those that have an influence on human health and the environment. It
takes professionals from several disciplines to solve these challenges
since they are not simple. Expert systems provide sophisticated and
intriguing answers for the issues. There is a lot of enthusiasm about
knowledge-based expert systems (KBES) in the engineering world. Numerous
uses for civil engineering have been noted. This paper reviews expert
systems applications in engineering transportation. The Expert System
(ES) offers advantages over human experts such as accessibility,
consistency, time constraints, stability, and efficiency. The Purpose of
this paper is to explain information and methods about creating new
Expert system for maintenance and rehabilitation of all types pavement
(ExFMRP). In this Ex we used C# C sharp (Visual studio) programming for
Created Expert system. This Ex include the description, causes, testing,
prevention, degree of severity, measurement, treatment and repair And
Video for all types of pavement (rigid pavement, flexible pavement,
composite, continues reinforced concrete pavement block or brick
pavement and subbase and subgrade supports. This study highlighted that
expert system is very useful approach for rehabilitation, repair and
maintenance of all types of pavements, this expert system was created to
aid all civil engineers in the description evaluation causing,
measurement degree of severity, testing and repair and maintenance of
all types of pavements
ANN: Adversarial News Net
Authors: Maham Shiza , Shoaib Muhammad
Published: May 2023

With the ease of access to social media platforms, the spread of fake
news has become a growing concern in today’s society. Classifying fake
news is an important task, as it can help prevent its negative impact on
individuals and society. In this work, an end-to-end framework for fake
news detection is developed by utilizing the power of adversarial
training to make the model more robust. This framework is named “ANN:
Adversarial News Net”. The performance of ANN is evaluated using four
publicly available datasets, and it is found to outperform previous
studies after adversarial training. Furthermore, emoticons have been
extracted from the dataset to understand their meanings in relation to
fake news. This information is then fed into the model, which helped to
improve its performance in classifying fake news. The proposed framework
has the potential to be used as a tool for detecting fake news in
real-time, thereby mitigating its harmful effects on society.
A Critical Activist Orientation Predicts Lower Latent Anti-disability Bias
Authors: Gravelle Donnan , Sawyer Jeremy E. , Rualo Gavin , Brooks Patricia
Published: May 2023

INTRODUCTION: Despite legal efforts to reduce societal barriers, people
with disabilities still face anti-disability bias, stereotyping, and
stigma. According to the social movement hypothesis, people’s
participation in and identification with activist movements may reduce
bias towards social outgroups. Alternatively, people’s intergroup
attitudes and bias may influence their participation in activist
activities. METHODS: This study used structural equation modeling to
investigate whether reduced bias towards people with disabilities is
associated with critical activism and/or personal, familial, or work
experience with disability. Undergraduates (N = 497) completed an online
survey including measures of anti-disability bias, critical activist
orientation, experience with disability, and demographic
characteristics. RESULTS: The relation between having a critical
activist orientation and lower anti-disability bias was bidirectional,
suggesting reciprocal influences between individual-level attitudes and
participation in social movements. Aligning with intergroup contact
theory, personal and familial experience with disability correlated with
reduced anti-disability bias, and familial and work experience with
having a critical activist orientation. Male gender correlated with
increased anti-disability bias, and male gender, White race, and higher
social class with lower endorsements of a critical activist orientation.
CONCLUSION: The results suggest that disability experience and social
status influence critical activist identity, which predicts lower bias.
Impact of Childhood Rural Residence Experience on Health in Old Age: Evidence from China
Authors: Li Haoyin , He Yuhang , He Huawei
Published: May 2023

The challenge of population aging is currently a pressing global issue,
with the health status of elderly individuals playing a critical role in
determining whether governments can meet the challenges of this
demographic shift. This study analyzes the relationship between
childhood rural life experiences and health status in old age in the
context of China’s underdeveloped rural areas and lagging public
services. Specifically, it examines whether childhood educational
resources and socioeconomic status play a mediating role in this
relationship. Employing data from 2823 elderly individuals in CGSS2021,
this paper uses OLS regression to analyze the effect of growing up in a
rural area during childhood on health in old age. Additionally,
Bootstrap methodology was used to analyze the sequential mediation of
childhood educational resources and socioeconomic status. The findings
revealed a negative association between growing up in a rural area
during childhood and health status in old age, with childhood
educational resources and socioeconomic status sequentially mediating
this relationship. This study emphasizes the importance of analyzing the
impact of growing up in a rural area during childhood on the health of
elderly individuals and designing targeted interventions to improve
their health and quality of life.
The Staff Question in German Plantations in the British Cameroons during World War II: The Employment of Staff from Jamaica and Malaya
Authors: Muojama Olisa Godson
Published: May 2023

Unlike the British and French territories in West Africa, the German territories of Cameroons and Togoland witnessed massive investment in plantations. These properties were taken over by the British and French during the First World War, 1914-1918. In the interwar years, 1919-1939, a good number of them were purchased and repossessed by the Germans who returned to West Africa after the war. Thus, the internment of German subjects in the Cameroons under the British mandate during the Second World War, 1939-1945, had implications for these German plantations. Earlier studies on the history of Cameroons and on the impact of World War II on West Africa have omitted this phenomenon. This paper is, therefore, designed to examine the staff question in the management of the German plantations in the British sphere of the Cameroons during the Second World War. Primary archival sources provided data for this historical reconstruction. It is a contribution to knowledge in the areas of impact of the global conflict on the periphery economy.
PRE-SERVICE EFL TEACHERS' EXPERIENCE IN INTEGRATING TPACK DURING TEACHING PRACTICE PROGRAM
Authors: Pradita Linda , Mardiana Wiwik , Mustpa Deni
Published: May 2023

This study explains the experience of Pre-service EFL teachers in integrating TPACK during teaching practice programs. This case study was to investigate twelve Pre-service EFL teachers in English education at the Universitas Islam Majapahit who has carried out a teaching practice program and applied technology. Data collected from their interviews, lesson plans, and teaching videos were analyzed using thematic analysis. The finding indicates that (1) Pre-service EFL teachers familiar with TPACK from its various classifications for teaching English; (2) Pre-service EFL teachers integrated TPACK for learning activities and doing assessment; (3) the contribution of TPACK for Pre-service EFL teachers during the teaching process has a positive impact on students and makes it easier Pre-service EFL teachers in administrative management.
Potential Benefits of Enhance Motivation on English Language Learners’ Performance
Authors: Sulaiman Asiri Maram
Published: May 2023

Motivation is a critical element in the teaching process. It makes students care more, attend more, put more effort, and pay more attention to what is going on. Essentially, they will learn more, making teaching them much easier and more enjoyable. In addition, motivation can significantly affect the educational experience and outcomes. Nonetheless, teachers can enhance or corrupt students’ motivation if they use improper methods in class. That is due to the fact that motivation is a fundamental human trait, as is adapting thinking to the domain-specific situations of education; what works outside the classroom may not work inside and vice versa. Furthermore, instilling motivation in students is difficult. They could be easily engaged, but how can learners be motivated to become better learners and fulfill their potential? Thus, this research aims to gain a better understanding of the critical role that teachers play in explaining why learners are motivated to learn. To help students explore information and new concepts in settings in which they feel competent and motivated. This could encourage teachers also to make decisions about the best methods to educate their students and how to put those methods into practice. Thirty-eight EFL English teachers at Taif University’s Faculty of Arts participated in this descriptive-analytical study, which concluded that teachers’ personality, attitude and way of speaking affected learners’ motivation.
Silicon dioxide nanoparticles inhibit the effects of cold exposure on metabolism and inflammatory responses in brown adipocytes
Authors: Zhang Yongqiang , Zhang Li , Wu Shuai , Zhang Guanyu , Wei Xiaodie , Li Xi , Yang Danfeng
Published: May 2023

Objective

Nanoparticles (NPs) in haze are potentially hazardous to health, which is more severe in the winter. Brown adipose tissue (BAT) plays important roles in obesity, insulin resistance, and diabetes. Though the toxicology of NPs has been intensively studied, few studies have been reported on the antagonistic effects between Silicon dioxide(SiO2) NPs and cold exposure in brown adipocytes.

Materials and methods

We evaluated changes by quantitative real-time reverse-transcriptase polymerase chain reaction (qRT-PCR) on metabolism genes, plasticity genes and the inflammatory responses genes in brown adipocytes in vitro.

Results

The expression of adipogenic genes PRDM16, Dio2, PGC-1α and UCP1 was upregulated upon cold exposure (P < 0.05), but downregulated by SiO2 NPs (P < 0.05). The results demonstrated that there was antagonistic effect between SiO2 NPs and cold exposure on the plasticity genes and metabolism genes in brown adipocytes, where the main effects of SiO2 NPs or cold exposure on the plasticity genes and metabolism genes were significant (P < 0.05). Moreover, the levels of interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α were upregulated by SiO2 NPs or cold exposure (P < 0.05). The factorial analysis indicated that there was also antagonistic effect between SiO2 NPs and cold exposure on the toxic effects in brown adipocytes, in which the main effects of cold exposure and/or SiO2 NPs on the toxic effects were significant (P < 0.05).

Conclusion

SiO2 NPs inhibit the effect of cold exposure on metabolic genes and inflammatory responses genes in brown adipocytes.
Advances in the application of cryotherapy to the treatment of breast cancer
Authors: Ma Tianfei , Fan Yueren , Zhao Yihang , Liu Bin
Published: May 2023

Cryotherapy is a minimally invasive treatment. With increasing rate of breast cancer detection, ablation therapy has become an alternative approach for the treatment of this pathology due to its advantages of minimally invasive, fewer complications, good efficacy, and repeatability. Preclinical and clinical studies of cryotherapy for breast cancer published through December 2022 were identified through a literature search using PubMed, ClinicalTrials.gov, and CNKI. This article reviews the progress of cryoablation in the treatment of breast cancer.
Profiling Mycoplasma hyopneumoniae Infection in Commercial Pig Farms Using Serology and Lung Lesions Assessment
Authors: Angjelovski Branko , Orenga Clara Marin , Janevski Aleksandar , Dodovski Aleksandar , Prodanovic Radisa , Bojkovski Jovan
Published: May 2023

Mycoplasma hyopneumoniae (Mhyo) is primary pathogen involved in porcine respiratory diseases complex (PRDC). The objective of this study was to evaluate Mycoplasma hyopneumoniae (Mhyo) infection in five commercial pig farms by using serology and lung lesion scoring at slaughter. Five Macedonian pig herds with a history of respiratory diseases were included in the study. Blood samples were taken from pigs at 6, 10, 14, 18, and 22 weeks of age. Ten animals per age group from each farm were sampled and tested for antibodies to Mhyo. At abattoir, 50 lungs per farm were scored for lesions associated with enzootic pneumonia (EP). All farms were seropositive to Mhyo. Higher seroprevalence to Mhyo was observed in grower and finisher pigs, while significant difference (p<0.001) was detected among farms in 10-, 14-, and 22-week-old pigs. Enzootic pneumonia-like lesions were detected in 91.2% of all tested lungs with range of 82 to 98% on farm level. Mean lung lesion score (LLS) obtained for all farms was 11.5 (8.04–14.4). Significant difference for LLS and significantly higher percentage of severe LLS grade (>10) were found among some of the farms (p<0.001). In conclusion, high seroprevalence to Mhyo in finishing pigs in most of the farms was most likely due to vaccination. Farms with higher seroprevalence to Mhyo obtained lower LLS. Serology monitoring of different pig categories and lung assessment at slaughterhouse is a practical tool for assessing vaccine efficacy of Mhyo in pig farms.
Challenges in the diagnosis of leptomeningeal dissemination of glioblastoma in a patient with fever and xanthochromic CSF: a case report
Authors: Neagu Andrei , Niculae Cristian-Mihail , Lăpădat Irina , Hristea Adriana
Published: May 2023

Background

Leptomeningeal spread with carcinomatous meningitis is a severe complication of glioblastoma, with a poor prognosis. Diagnosis is challenging, as the sensitivity of classic diagnostic investigations remains low for detecting cerebrospinal fluid (CSF) tumor spread and exclusion of infectious causes is mandatory, especially if unusual clinical findings are present.

Case presentation

A 71-year-old woman was admitted to our hospital for recurrent episodes of high fever and xanthochromic meningitis, with subacute onset. Her past medical history was significant for a left temporal glioblastoma, treated with surgical resection and adjuvant chemo- and radiotherapy, with associated systemic immunosuppression secondary to chemotherapy. An extensive workup especially with molecular microbiology testing for exclusion of infectious causes was performed. CSF was analyzed for typical bacterial and viral causes, but also pathogens associated with immunosuppression, such as Listeria monocytogenes and Cryptococcus neoformans. A therapeutic trial of standard antituberculous drugs with repeated lumbar punctures were needed in order to exclude Mycobacterium tuberculosis and to confirm the diagnosis of carcinomatous meningitis by cytopathological examination of the CSF.

Conclusions

The case describes an unusual clinical presentation of a patient with glioblastoma associated leptomeningeal dissemination, as high fever and xanthochromic CSF could raise important diagnostic and therapeutic challenges in the clinical practice. The diagnosis of carcinomatous meningitis requires an extensive workup for exclusion of infectious causes which is important for urgent oncologic treatment.
The correlation between Body Mass Index and histological features of Nonalcoholic Fatty Liver Disease
Authors: Calin-Necula Ana , Enciu Vlad , Ologeanu Priscila , Moldoveanu Alexandru Constantin , Braticevici Carmen Fierbinteanu
Published: May 2023

Introduction: NAFLD is strongly associated with metabolic syndrome, and for many years, fatty liver was an exclusive feature of obese patients. The study tries to assess whether the body mass index (BMI) and body circumference is correlated to steatosis, fibrosis, or inflammatory activity of the liver.

Methods: 81 patients with recent hepatic biopsy were included in the study and were weighed and measured. The biopsy results were compared to the measurements.

Results: The average BMI overall for the whole lot was 30.16. There was a significant difference in BMI across the inflammatory activity categories (p = 0.009): groups with higher necro inflammatory activity tended to have higher BMI values (average values per grade: 0–28, 1–29, 2–33, 3–32, 4–29). There was no significant difference for grades of steatosis (p = 0.871). With regards to waist circumference, the overall average was 90.70cm/35.70in. There was a significant difference across the steatosis categories (p < 0.001): groups with higher steatosis scores had higher waist circumferences (average values per grade: 1–77cm / 30 in, 2–95 cm / 37 in, 3–94 cm / 37 in). There was no significant difference for grades of activity (p = 0.058).

Conclusion: BMI and waist circumference are easy to measure, non-invasive parameters, which could be useful in screening patients at higher risk for necro inflammatory activity or severe steatosis.
Neue Hieracium-Taxa aus dem Burgenland (Österreich)
Authors: Gottschlich Günter , Brandstätter Gerald
Published: May 2023

Two species (Hieracium sibaricum, H. pillii) and 3 subspecies (H. diaphanoides subsp. semiorbiculare, H. glaucinum subsp. semibasalticum, H. glaucinum subsp. domimontis) are described as new for science from the Burgenland (Austria).