bluuebunny/crossref_metadata_2025 huggingface dataset:
Military Chronicles of 17th-century Egypt as an Aspect of Popular Culture
Authors: Doss Madiha
Published: May 2024

This paper deals with a group of Arabic chronicles dating from the second half of the seventeenth century in Egypt, when Egypt was under Ottoman rule. The chronicle Waqāʾiʿ Miṣr al-Qāhira and others close to it will be considered in the context of folk literature and as representatives of folk literature and of popular culture. The author’s claim is that these chronicles, which have usually been considered as historical documents, could actually be counted as part of folk literature. Both form and content seem to indicate that these chronicles are very similar to epics aimed at entertaining an audience of listeners be either the militaries or other.
Ṣūfī Magic – Graeco-Egyptian Magic
Authors: Fodor Alexander
Published: May 2024

This paper examines the current relationship of Ṣūfīs to magic, their role in propagating magical practices and their general indebtedness to Greco-Egyptian magic.
Les traces de principes d'honneur des arabes de antéislam dans les coutumes et proverbes contemporaines
Authors: Skarżyńska-Bocheńska Krystyna
Published: May 2024

The pre-Islamic Arab tribes had created a code of honour that became an unwritten, customary law, observed, and cherished by the entire tribe. The Arabic term that corresponds to the idea of honour is the word ʿirḍ. Among the many principles of honour, presented in Farès’s still relevant work (L’honneur chez les Arabes avant l’islam, Paris, 1932), the author of this article chose three for her analysis: “the chastity of women” and the principle strictly linked to it, “the non-captivity of free women” as well as “protection” (ǧiwār), whose traces or at least inspiration can be seen in the tribal laws (ʿurf) of contemporary Bedouins.
Magic, Sorcery, and Myth in Jewish Pseudepigraphic Literature (The Ethiopic Book of Enoch)
Authors: Fröhlich Ida
Published: May 2024

The first part of the Ethiopic book of Enoch (ch. 1-36) is generally called the Book of Watchers. It begins with a description of the creation of the world, then continues with the story of the Watchers, whose sin – the relationship with the daughters of men, or rather the deeds of the giants born from these relationships – provokes the punishment of the Flood. The article provides an analysis of this book, based on its Qumran fragments.
Magic and Popular Medicine in Spanish Aljamiado-Texts
Authors: Raczek Till
Published: May 2024

In this paper some parts of Aljamiado manuscripts from Spain will be presented that deal with magic and popular medicine. These Aljamiado texts were written down by the Moriscos, the last Muslims who stayed in Spain after the Reconquista of 1492. These texts were written in Arabic characters, but mostly not in Arabic, but Aljamía, i.e. Spanish, although in nearly all the manuscripts there are also passages in Arabic.
NANOMATERIALS AND NANOSTRUCTURES IN CHEMISTRY: A REVIEW OF SYNTHESIS AND CHARACTERIZATION METHOD
Authors: Kumar Umendra
Published: May 2024

Nanomaterials and nanostructures have emerged as pivotal components in the realm of chemistry, bearing profound implications for numerous scientific disciplines and applications. This comprehensive review delves into the synthesis and characterization methods underpinning the dynamic field of nanochemistry. We explore a wide array of synthesis techniques, encompassing chemical, physical, biological, and template-assisted approaches, while elucidating their fundamental principles, advantages, and constraints. Likewise, we investigate various characterization methodologies, including electron microscopy, X-ray diffraction, spectroscopy, and nuclear magnetic resonance, to unveil the structural intricacies of nanomaterials. Categorizing nanomaterials by structure, we delve into their distinctive properties and multifarious applications. Recent breakthroughs and ongoing developments are scrutinized to identify emerging trends. Furthermore, we spotlight the diverse applications of nanomaterials across medicine, electronics, energy, and environmental domains, showcasing their transformative potential. In conclusion, this review encapsulates the synthesis and characterization frontiers in nanochemistry, explores their applications, and anticipates future challenges and prospects
SELF-ACTIVATING DNA CLEAVAGE BY MONONUCLEAR COPPER COMPLEXES
Authors: Kumar Pramod , Kumar Sushil
Published: May 2024

Chemical nucleases have seen gradual growth in the field of chemistry and biomedical science. So far, a diverse range of small organic molecules as well as coordination complexes have been developed as chemical nucleases to cleave DNA mainly via three major pathways i.e., photoinduced, oxidative or hydrolytic pathways. However, most of such nucleases suffer from their practical applications in real-life samples because they require an external redox agent for functioning. In this context, small organic/inorganic compounds acting as the ‗selfactivating‘ chemical nucleases have emerged as viable alternatives as therapeutic agents for DNA cleavage activity with no exogeneous agent. The aim of this chapter is to highlight the self-activated DNA cleavage shown by mononuclear copper complexes with specific emphasis on their recent development and challenges
MOLECULAR INTERACTIONS STUDY BETWEEN BUTYL ACETATE WITH ALKANES USING ULTRASONIC TECHNIQUES
Authors: Wagh Pralhad S
Published: May 2024

Ultrasonic velocities for binary mixtures of butyl acetate as a main component with alkanes like heptane, decane, dodecane and tridecane have been measured at 303.15, 308.15 and 313.15K temperatures with different compositions. The obtained experimental data have been utilized to find out excess or deviation properties such as deviations in ultrasonic velocity (Δu), and intermolecular free length (Lf). The deviation in ultrasonic velocities and excess intermolecular free length convey prevailing trends of curves that are both positive and negative which attributes the different molecular interactions for proposed binary mixtures
GREEN AND SUSTAINABLE CHEMISTRY
Authors: Saroha Mohit , Swami Renu , Singh Bhupinder , Kumar Akshay , Tomar Deepak
Published: May 2024

Increase in global warming and pollution due to chemicals increase the demand for Green and sustainable chemistry. There is a need for more environmentally benign process in chemical industry, which become known as ‗green chemistry or sustainable chemistry‘.1- 3 In traditional, the concept of efficiency is basically focus on money, time and yield of product but green chemistry shift this paradigm to eliminating waste at source and avoid the use of toxic/ hazardous chemicals and/ or solvents
THEORETICAL EXPLORATION OF THE ELECTRONIC PROPERTIES AND REACTIVITY OF NITROGEN-CONTAINING HETEROCYCLES
Authors: Mittal Soni
Published: May 2024

This research is concerned with a theoretical exploration of the electronic properties and reactivity of nitrogen-containing heterocycles, pivotal constituents in organic chemistry. Employing advanced quantum chemical methods, we conducted a detailed molecular orbital analysis, unraveling the intricate electronic structures and distribution of electron density in these compounds. Through case studies, we demonstrated the profound impact of substituents on electronic properties and reactivity, showcasing predictive models and quantitative parameters. Molecular dynamics simulations provided dynamic insights, capturing transient states and dynamic responses during reactions. Looking forward, we propose future directions, including the exploration of novel heterocycles, the application of advanced computational techniques, and enhanced collaboration between theoretical and experimental approaches. Addressing challenges in handling complex systems and improving solvent models, this study not only advances our understanding of nitrogen-containing heterocycles but also sets the stage for a more integrated and predictive theoretical framework in organic chemistry
A CASE STUDY ON INCREASING FAST FOOD PREFERENCES AMONG YOUTH AND ITS EFFECT ON HEALTH AND WELL-BEING
Authors: Ahmad Mr. Parvez , Singh Prof. (Dr.) Vikas , Kumar Mr. Amit , Singh Mr. Yazuvendra , Mishra Prof. (Dr.) Rajiv
Published: May 2024

This review article aims to investigate the increasing fast-food preferences among youth and its effect on their health and well-being. Junk foods are unhealthy foods that are high in calories from fat or sugar and low in essential nutrients such as minerals, vitamins, protein and fibre. The exact definition of unhealthy food here varies by use. Some foods high in protein, such as meat prepared with saturated fat, are known as unhealthy foods. They are high in sugar, high in salt, and high in fat. Fast food restaurants are often equated with or cannot be described as successful junk food. It takes less time and served easily is known as fast food. This paper brings out the food preferences of the youth and various factors that are involved in their likes and dislikes
RELATION OF TPB MODEL ON ENTREPRENEURSHIP INTENTION AMONG HOSPITALITY MANAGEMENT GRADUATES IN BANGALORE
Authors: Kumari Vineeta , Sharma Dr. Ankita Sakhuja , N Sampath
Published: May 2024

The current research aims to undertake a study on the impact of the Theory of planned behavior on the entrepreneurial intentions among Hospitality Management graduate students in Bangalore, Karnataka. Based on the theoretical background, factors shape an individual to have entrepreneurial intentions such as personal and social factors (Bird,1988). This research aims to evaluate which variable has more impact on entrepreneurial intentions. The current research adopted a quantitative method by distributing a questionnaire among Hospitality Management graduate students. Data was gathered through a Google form and used JMP to find TPB‘s impact on EI for data analysis. The finding shows that Perceived Attitude has more impact on entrepreneurial intention compared to subjective norms. This research concluded that Personal Attitude has more impact, after perceived Behavioral Control, and a weak and less impact from the subjective norm on entrepreneurial intentions. Using the above theoretical model this study offers detailed insights into how entrepreneurship intention is formed among the Hospitality Management graduate students
A NOVEL APPROACH TO DETECT SENTIMENTS BASED ON SOCIAL MEDIA USING MACHINE LEARNING
Authors: Nema Neetesh kumar , Choudhary Bharat , Patel Dileshwar
Published: May 2024

It might be helpful to estimate a product or service's future scope by doing a sentiment analysis of it. However, it might be tedious and difficult to manually analyse a lot of papers in a short amount of time. As a result, several attempts have been made to address this issue in the literature, and various sentiment analysis approaches have been put forth. Various machine learning methods that use supervised or semi-supervised techniques are currently available. These algorithms can use a hybrid, unigram, bigram, ngram, or other suitable approach. This study makes advantage of semi-supervised learning. This study combines many approaches to create a unique model that employs a number of approaches and yields results. This fictional method produced greater result. People frequently post a lot of stuff on social media with the goal of discovering memes that capture their emotions. Because people are more inclined to convey their feelings through pictures and written descriptions, image and textual sentiment analysis (SA) is advancing at a rapid rate. Social media users are increasingly expressing themselves and sharing their experiences through photos and videos
STUDY OF INNOVATIVE DEEP LEARNING ARCHITECTURES/ ALGORITHMS FOR TIME SERIES DATA AND IOT
Authors: DaljeetKaur Mr. , Khan Husnara
Published: May 2024

Deep learning is a recent area of study in machine learning (ML). There are numerous hidden layers of artificial neural networks. The deep learning approach uses high-level model abstractions and nonlinear transformations in large databases. Artificial intelligence has benefited greatly from the recent huge advancements achieved by deep learning architectures in a number of fields. An up-to-date overview of the contributions and cutting-edge uses of deep learning is provided in this article. The review that follows shows, in chronological order, the primary applications that deep learning algorithms have been used in. The advantages and benefits Compared with those of the more conventional algorithms utilised in everyday applications, the nonlinear operations and hierarchy of layers of the deep learning technique are also discussed. How is the state of In this study, we assess the best deep learning architectures for forecasting and recognising trends over time using data collected by IoT sensors. It is advised to assist applications in this strategy industries like smart cities, industry 4.0, sustainable agriculture, robotics, etc. where IoT is advancing technologyCNN (Convolutional Neural Networks) are primarily used to recognise human activity; LSTM (Long-Short Term Memory) and RNN (Recurrent Neural Networks) are hybrid architectures with a convolutional layer for data preprocessing and CNN (Convolutional Neural Networks) are used for data fusion from various sensors and time series data
FRAUD DETECTION OF CREDIT CARD USERS IN THE BANKINGSYSTEM USING A RANDOM FOREST AND ANN DEEP LEARNING MODEL: A REVIEW
Authors: Kori Rohit , Tamrakar Deepesh , Choudhary Sapna Jain
Published: May 2024

In opposition to invasion attacks (where/during/in what way/however a conventional firewall fails), a detection gadget provides indications and symptoms of illness. Using supervised and unsupervised (success plans/ways of achieving goals) learning techniques, device learning sets of computer instructions aim to discover (strange, unexpected things). Ability want (success plans/ways of accomplishing objectives) identify highly vital talents and get rid of supplementary and superfluous features to reduce the intriguing quality of (typical and expected) location. The work presents a skills choice (a strong fundamental foundation upon which larger things may be constructed) for unnatural community (strange, unexpected item) identification using excellent machine learning classifiers. The clean out and wrapper functions, which are preferred methods of accomplishing things, are applied in the (solid fundamental framework on which greater things may be constructed) together with good helpful helpful useful thing/valuable supply. To select the (nearly nothing/extremely little) form of functions that benefit the wonderful (quality of being very close to the truth or correct number), which is the basis for this (firm basic structure on which greater things may be constructed), is the purpose of this (solid basic structure). The proposed (solid fundamental framework on which larger items can be constructed) is tested and evaluated using a dataset in experimental effects. The results demonstrate that a (quality of being very
APPLICATION OF DEEP LEARNING-BASED TECHNIQUES FOR PRECISION AGRICULTURE
Authors: Farooq Bazila
Published: May 2024

Agriculture is a vital industry that adds significantly to the global economy. Researchers are currently starting to investigate the prospect of integrating deep learning techniques and machine learning into agriculture, due to recent developments in technologies for deep learning. The paper examines several deep neural network designs and machine learning techniques used in agriculture, including irrigation, weeding, pattern recognition, and crop disease identification. The primary goal of this study is to determine multiple uses of deep learning in agriculture and to summarise existing state-of-the-art approaches. The review addresses the particular deep learning algorithms utilized, the sources of data used, study achievement, the equipment used, and the possibility for immediate application as well as integration with autonomous mechanical platforms. According to the results of the chapter, the use of deep learning research outperforms typical machine learning techniques in terms of reliability. In general, the study indicates the enormous potential of deep learning and machine learning in agriculture and the necessity for additional study in this field. It may be able to improve agricultural efficiency, decrease waste, and raise the yields of crops by utilizing the potential of these methods, ultimately enhancing the worldwide availability of food
INTEGRATED MULTI TROPHIC AQUACULTURE (IMTA) SYSTEM: WAY FORWARD TOWARDS SUSTAINABLE AQUACULTURE
Authors: Keer Dr. Naresh Raj , Dar Dr. Showkat Ahmed , Abhiman Dr. , Chandra Gyan , Khan Md. Idrish Raja , Garg Chetan Kumar , Kumar Rajesh , Kumar Manmohan
Published: May 2024

The development of sustainable culture practices needs to minimize environmental degradation with intent towards horizontal and vertical expansion of aquaculture system. Integrated multi trophic aquaculture (IMTA) system is a novel integrated slant similar as polyculture system that involves the culture of two or more species together. IMTA is the exercise that integrates the suitable proportions of fed species (finfishes /shrimps) with organic extractive (shellfishes/herbivorous fishes) and inorganic extractive species (seaweed cultivation) in a particular culture system. IMTA stands as a fully sustainable technology with environmental benefits. Mainly, this chapter highlighted the introduction, history, present status, concept behind the integration, advantages and disadvantages, design and nutrients flow and future prospective of IMTA. The technology ensures the eco-biological balance by controlling the organic and inorganic pollution in the cultural environment. In conclusion, the IMTA can be an eco-friendly and sustainable technology that can be done in open water (marine and freshwater) to benefit the farmers as additional revenue
DESERT AQUACULTURE
Authors: Yadav Dr. M. K , Chauhan Dr. R.S , Ojha Dr. M.L , Yadav Mr. N.K , Keer Dr. Naresh Raj
Published: May 2024

he practices of aquaculture in semi-arid areas had a significant social and economic impact by provided that a means of food production, contributing to the livelihoods of individuals, and generating income. ―The primary goal of aquaculture is achievement of productivity and particularly batter utilization of water resources for integrated aquaculture and animal husbandry. The integrated aquaculture systems in arid and Sami-arid regions to produce quality food thought year for peoples. These types of activity (in Arid and Sami-arid) are basically involved in the desert aquaculture; it is covered application of salt affected soil or area. Desert aquaculture technologies is used to enhancing the fish production as well as treat the salt affected soil through the saline aquaculture. The creation of helophytes via saline water is further most appropriate method of transforming desert ecosystem and food production for inhabits living in coastal regions
INTRODUCTION TO COASTAL A QUACULTURE AND MARICULTURE
Authors: Swathi Mrs.
Published: May 2024

Coastal aquaculture and mariculture are indispensable components of the global seafood industry, serving as sustainable solutions to meet the increasing demand for aquatic products. This chapter provides a comprehensive overview of coastal aquaculture and mariculture, exploring their methods, significance, and impacts on food security and environmental sustainability. Diverse aquatic species are cultivated in highly regulated settings as part of coastal aquaculture, which is carried out in nearshore locations. A specific subgroup known as mariculture reaches out into the ocean, presenting special difficulties and chances for the cultivation of aquatic life. These methods are essential to ensuring a steady supply of premium seafood and promoting global food security. The chapter explores the basic ideas of aquaculture systems, with a focus on sustainable methods, site selection criteria, and water quality management. It discusses sustainability and environmental challenges, bringing attention to problems like habitat loss, water pollution, and overfishing, and it also looks at mitigation and conservation measures
Explainable AI (XAI): Interpretable Model Architectures
Authors: B.R Prasath. , V Priya.
Published: May 2024

In the rapidly advancing landscape of artificial intelligence, the need for transparent and comprehensible decisionmaking has become increasingly evident. Interpretable Model Architectures (IMAs) emerge as a pivotal solution within the realm of Explainable AI (XAI). IMAs encompass a class of machine learning models intentionally designed to prioritize human interpretability, thereby bridging the gap between complex AI algorithms and the imperative for transparent decision processes. This abstract delves into the foundational principles and significance of IMAs within the context of XAI. It explores notable IMA approaches, including decision trees, rule-based models, linear models, and Bayesian networks. By embracing simplicity, interpretability, and clear decision paths, IMAs empower users to comprehend and trust the decision- making mechanisms of AI systems. This exploration not only accentuates the potential applications of IMAs in diverse domains, such as healthcare, finance, and legal sectors, but also underlines their crucial role in fostering ethical and accountable AI deployment. Ultimately, IMAs contribute to the broader goal of enhancing humanAI collaboration by affording users the capacity to make informed decisions grounded in AI insights while maintaining a transparent and comprehensible decision landscape
Navigating the Digital Gold Rush: An In-depth Analysis of Crypto Currency Markets through Machine Learning Techniques
Authors: Singh Ashish Kumar , Kumar Mukesh
Published: May 2024

The proliferation of digital currencies has ignited a global frenzy, attracting a diverse array of participants from traders and investors to entrepreneurs. This unprecedented boom, particularly highlighted by Bitcoin's record-breaking performance in 2021, marks a seismic shift in financial paradigms. Coupled with the rise of new exchange platforms, cryptocurrencies have become more accessible to the public, thereby broadening their appeal and adoption rates. Notably, mainstream corporations like Tesla, Dell, and Microsoft have also begun to integrate virtual currencies into their business models. This chapter aims to elucidate the intricate dynamics of this burgeoning market by offering comparative studies and insights derived fromcryptocurrency price data. Leveraging machine learning techniques, such as Artificial Neural Networks (ANN) and Support Vector Machines (SVMs), we delve into predictive modeling to capture market trends and behaviors. Our analyses reveal that these advanced computational methods offer superior accuracy in forecasting market fluctuations, outperforming other traditional models.As decentralized digital currencies continue to gain traction, it becomes imperative to equip the public with nuanced understandings of these novel financial instruments. This chapter serves as both a primer and a detailed guide, offering actionable insights for potential investors and policy-makers. In sum, as the cryptocurrency market continues to expand and evolve, this chapter provides a timely and critical resource for navigating its complex landscape
Numerical Simulation and Design of Stock Market Forecasting Using Neural Networks and Machine Learning Method
Authors: Awasthi Sunil , Kumar Mukesh
Published: May 2024

The modern stock market is a complex and dynamic system, influenced by a multitude of factors such as economic indicators, market sentiment, and geopolitical events. Predicting its behavior is notoriously difficult but immensely valuable for various stakeholders, including individual investors, financial analysts, and policymakers. This study aims to develop a robust and accurate stock market forecasting model by leveraging the capabilities of neural networks and machine learning algorithms. The paper explores various machine learning techniques, including feedforward neural networks, recurrent neural networks (RNNs), and long short-term memory networks (LSTMs), and compares their performance against traditional timeseries models like ARIMA. Real-world historical data is used to train and validate the models. The study also involves feature engineering to incorporate external variables like trading volume, interest rates, and social media sentiment. Numerical simulations are conducted to evaluate the efficacy of each model in terms of predictive accuracy, robustness, and computational efficiency. The results indicate that machine learning-based models, particularly LSTMs, outperform traditional models in forecasting stock market indices with a higher degree of accuracy. Sensitivity analyses further reveal that the performance of the machine learning models is significantly improved by tuning hyperparameters and including external feature variables The study opens up new avenues for employing advanced machine learning techniques in financial market analytics and offers practical guidelines for developing more reliable and efficient stock market prediction systems
Population Improvement Approach
Authors: Deshmukh S. S. , Sargar P. R. , Naik G. H.
Published: May 2024

Population improvement is an accumulation of desirable alleles in a population through various breeding procedures. Population improvement approaches such as Mass selection& its modification, Progeny selection, Ear to row method& its modification, Recurrent selection, Disruptive selection, Biparental mating, Diallel selective mating system are used to for development of superior genotypes in a population. Cross pollinated crops are highly heterozygous and heterogeneous. Consequently, they show varying degrees of inbreeding depression. Therefore, inbreeding should be avoided or kept to a minimum in cross pollinated crops. Individual plants are heterozygous and their progeny would be heterogeneous and usually different from the parent, due to segregation and recombination. Therefore, desirable genes can be seldom fixed through selection in cross pollinated crops except for highly heritable qualitative characters. Therefore, the breeder's goal is to increase the population's frequency of beneficial alleles. In cross-pollinated crops, the genotype of the individual plants is typically not very significant, especially in population improvement programmes. Instead, it is more significant to look at the frequency of desirable alleles or genes in the population as a whole
Polyploidy: An Evolutionary Plant Breeding Approach
Authors: Shinde A. V.
Published: May 2024

Plants have a favourable impact on human life and supply food, medicine, and fuel. To address the issue of the need to diversify crop plants, modern breeding techniques are developed. These techniques significantly reduce the length of the breeding period and also have an impact on the breeding of some plants whose improvement is not possible using conventional techniques. The new sources of germplasm that can be exploited to create new cultivars or in breeding programmes are haploid, double haploid, and polyploid plants. Artificial polyploidy induction is one of the breeding techniques used to enhance the desirable traits of plants. Improvements in varieties, creation of sterile lines, the recovery of hybrid fertility, growth and increased vigour, an increase in allelic diversity, heterozygosity etc. All of these aspects must be taken into account in a genome-wide context to maximize marker-assisted selection and crop plant improvement. Plants with all of their chromosomes duplicated (instead of only some) have more distinguishing characteristics, such as altered phytochemical properties, a higher concentration of therapeutic compounds, and unique plant shapes, colours, sizes, scents, and flowering times. The genotype of the plant and the type of sample must be taken into account in order to create an effective protocol for chromosomal duplication. Principal aspects that must be taken into account include the kind, quantity and length of mitotic inhibitors
Backcross Breeding: Conventional & Molecular Approach
Authors: Saharia Niharika , Bora Richa , Behera Partha Pratim
Published: May 2024

The population of the globe will increase to 9.8 billion people by the year 2050. With the ever-increasing demand of the rising population, it is very important to increase food production. Transforming the elite cultivar through backcrossing can be a vital approach. Backcrossing is a common technique in plant breeding that is most frequently used to introduce one or more traits -such as disease resistance, high yielding, etc. in to a superior or adapted variety. Genetics engineers are working on transforming their laboratories and breeders are backcrossing the transgenes into elite cultivars. On the other hand, markerassisted backcrossing (MABC) proves to be the most promising approach with the use of molecular markers to identify and select genes controlling resistance in the cultivars. Now with the help of MABC, the recovery of the recurrent parent genotypes is quite possible from large population size, using only two or three backcrosses. These procedures are crucial to the development of new varieties with much higher precision and accuracy
Breeding for Abiotic Stress Resistance
Authors: Yadav Rakesh Kumar , Asat Ruchi , Soni Ayushi , Yadav Pradeep Kumar , Tripathi Niraj , Tiwari Sushma , Tripathi Manoj Kumar
Published: May 2024

Abiotic stresses, responsible for yield reduction by up to 50%, are the primary drivers of yield losses in crop plants. Abiotic stress, which damage plant growth and development and have a large detrimental effect on agriculture production globally, include low or high temperatures, droughts, floods, high salinity, heavy metals, and UV radiation. As traditional crop development approaches reach their limits, the age of genomics research has come, bringing with it new and interesting possibilities for breeding superior cultivars against abiotic challenges. With improving selection accuracy, the molecular-assisted selection method anticipates rapid improvement in the selection of agricultural plants that have adapted to stress. It is encouraging that molecular-assisted selection can target features in a single progeny more quickly and precisely in a few selected generations with few unexpected consequences. This chapter provides an overview of the fundamentals of cutting-edge technologies, including molecular mapping, molecular-assisted mapping, transcriptomic, metabolomic, transgenic, and genome editing, and how they are used to enhance crop plants with a focus on stress tolerance
A MACHINE LEARNING APPROACH TO EARLY DETECTION AND PREDICTION OF ALZHEIMER'S DISEASES FROM MRI SCAN IMAGES
Authors: Latha N. , Priyadharshini R. , Kurinjimalar K. , Shobana K.
Published: May 2024

Alzheimer's disease (AD) is classified as a debilitating neurological disorder that primarily impacts individuals in advanced age. Individuals diagnosed with Alzheimer's disease experience significant cognitive impairment, particularly in the domain of memory. Memory loss in individuals diagnosed with Alzheimer's disease is attributed to the progressive degeneration and shrinkage, known as atrophy, of certain regions within the brain, including the hippocampus, amygdala, and other associated areas. The identification and classification of Alzheimer's disease pose significant challenges in the realm of research, primarily due to the considerable number of individuals affected by the disease and the lack of reliable diagnostic methods. Furthermore, the conventional process of identifying Alzheimer's disease is becoming increasingly time-consuming. To address this problem, it is imperative to employ Artificial Intelligence systems that leverage machine learning techniques for AD categorization and identification. This study presents a methodology for AD classification utilising image-based techniques, specifically employing the Speed-Up Robust Feature (SURF) algorithm. In addition, the values of the SURF features are inputted into a machine learning classifier. The system's performance was evaluated by comparing it with five distinct machine learning classifiers, namely Support Vector Machine, Random Forest, Decision Tree, Logistic Regression and XGBoost classifiers. In order to assess the proposed Alzheimer's disease (AD) system, it is necessary to gather a benchmark OASIS longitudinal dataset. This dataset has two distinct classifications, namely AD disease and Normal. The experimental findings demonstrated that the Logistic Regression classifier exhibited superior accuracy compared to other four classifiers
SMART PREDICTORS: ADVANCING HEART STROKE DETECTION THROUGH MACHINE LEARNING TECHNIQUES
Authors: Kumar S. Bavan , Deepan Dr. P. , Santhoshkumar Dr. R. , Rajalingam Dr. B.
Published: May 2024

Currently, the number of deaths that are attributed to heart strokes is steadily rising on a daily basis. Sadly, identifying such disorders in human beings is a difficult and time-consuming endeavour. Data sets are a useful tool for managing jobs that are of such a complicated nature. Because it is necessary to continue monitoring the heart rate, the only way to accurately anticipate the incidence of heart strokes is through the use of automation. This particular article makes use of the MITBIH arrhythmia dataset since it is one of the datasets that is helpful to us. A number of different data mining strategies can be utilised in order to achieve automation for the work that was specified. In this article, the methodologies that were utilised include decision trees, naïve bayes, k-nearest neighbors algorithm, and Random Forest algorithm. Therefore, the purpose of this research is to establish a comparison between the algorithms that have been discussed above and to determine which one is more accurate in terms of completing the assignment. At the end of the day, after all of the evaluations, we are able to declare that the algorithm Random Forest has achieved a level of accuracy that is 99%, which is the greatest level of accuracy among all of the algorithms
DESIGN AND IMPLEMENTATION OF AUDIO STEGANOGRAPHY IN HEALTHCARE USING IOT
Authors: K. Revathi K. , Mohideen S. Kaja
Published: May 2024

Audio Steganography is a technique to hide data inside an audio file of type WAV, MIDI, AVI, MPEG, and MP3 files. Audio Files have acted as a cover for secretly communicating multimedia files (text, images, audio, and video). Least Significant Bit Algorithm (LSB) is the standard and traditional algorithm in audio steganography. The patient’s medical record is in the text file concealed in an audio file of type WAV using the LSB algorithm. The resulting stego audio file is exchanged within or outside the organization to facilitate the remote diagnosis with security and imperceptibility. Merging audio steganography with IoT enhances secured communication in medical records with confidentiality and integrity. The similarity within the cover and stego audios is measured using normalized cross-correlation. Mean Squared Error (MSE), Peak signal-tonoise ratio (PSNR), and Bit Error Rate (BER) performance metrics evaluate the distortion within the cover audio and stego audio files. The Audio Steganography utilizing IoT with Telemedicine model surpasses stego audio clearness with an average PSNR of 34.5dB and a lower BER of 0.00035
Contribution of the Strategic Economic Plan to Singapore’s Long-term Growth: A Synthetic Control Approach
Authors: Uhr Júlia Gallego Ziero , Weizenmann Felipe , Uhr Daniel de Abreu Pereira , Ferreira Mariana Fialho , Moraes Igor Serpa
Published: May 2024

We assess the impact of the Strategic Economic Plan on Singapore’s long-term GDP per capita. To our knowledge, we are the first to evaluate the effect of the 1991 plan on Singapore’s successful growth trajectory using methodologies aimed at causal identification. In other words, this article applies the Synthetic Control method and World Bank data from 1970 to 2018. We estimate an average increase of 6,641.71 US$ in Singapore’s GDP per capita. Results remain robust to placebo and leave-one-out tests and the Synthetic Difference-in-Differences method.
Cloud computing and extensive margins of exports: Evidence for manufacturing firms from 27 EU countries
Authors: Wagner Joachim
Published: May 2024

The use of cloud computing by firms can be expected to go hand in hand with higher productivity, more innovations, and lower costs, and, therefore, should be positively related to export activities. Empirical evidence on the link between cloud computing and exports, however, is missing. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union taken from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate this link. Applying standard parametric econometric models and a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), we find that firms which use cloud computing do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated cloud computing premium for extensive margins of exports is statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of this premium can be considered to be large. Extensive margins of exports and the use of cloud computing are positively related.
Pengaruh Kualitas Layanan dan Fitur Produk BSI Mobile terhadap Kepuasan Nasabah Bank Syariah Indonesia KCP Veteran Makassar
Authors: Masykur Nur Ahlamiah Tri Putri , Fathurrahman Fathurrahman , Muslihati Muslihati
Published: May 2024

This research aims to determine the influence of service quality and BSI mobile product features on customer satisfaction at Bank Syariah Indonesia KCP Veteran Makassar. The sample in this research is customers who use BSI mobile at Bank Syariah Indonesia KCP Veteran Makassar. The method used in this research is a quantitative method with a survey method that uses a questionnaire as a data collection instrument. Based on the research results, it was found that the first hypothesis was accepted, namely that service quality has a positive and significant impact on customer satisfaction in using BSI mobile. Likewise with the second hypothesis, where product features have a positive and significant impact on customer satisfaction in using BSI mobile. And with that, the third hypothesis is also accepted, which shows that together or simultaneously service quality and product features have a positive and significant impact on customer satisfaction at Bank Syariah Indonesia KCP Veteran Makassar.
Studi Identitas Regional untuk Pariwisata Berkelanjutan di Kecamatan IV Koto Kabupaten Agam
Authors: Fadhillah Abdul Khaliq , Syarief Azhari
Published: May 2024

Tourism is growing rapidly globally, making an important economic contribution in Indonesia. However, it is necessary to focus on sustainable tourism that considers ecological and cultural aspects. This research aims to identify regional identity for sustainable tourism in IV Koto Sub-district, Agam Regency based on the potential of natural and cultural resources. The research method used in this research is quantitative and qualitative approaches, this research analyzes primary and secondary data to evaluate the attractiveness of natural attractions and cultural elements of interest to local communities. The results showed that the Great Wall of Koto Gadang was the natural attraction with the highest potential as a regional identity, while traditional ceremonies, particularly batagak gala, became the most significant cultural identity. The findings emphasize the importance of utilizing natural and cultural resources in a sustainable manner, involving the active participation of local communities in tourism development.
Peningkatan Kinerja Manajemen Pendidik dan Tenaga Kependidikan untuk Mewujudkan Sekolah Unggul di SMPN 15 Gresik
Authors: Anggraini Della Rana Maulidia , Mazidah Ifrochaini Al , Windasari Windasari
Published: May 2024

This research aims to analyze strategies that can improve the performance of teaching staff and education staff at SMPN 15 Gresik. The research method used is a case study with a qualitative research approach. Data was obtained through observation, interviews and document analysis. The findings show that the implementation of professional training and development, welfare development, as well as improving learning facilities and environments are the main factors in improving the performance of teaching and education staff. The results of this research can contribute to school administrators in designing effective strategies to improve the quality of education at SMPN 15 Gresik.
Redesigning America’s Community Colleges: How Guided Pathways Has Promoted Workforce Training and Devalued the Humanities
Authors: Kroll Keith
Published: May 2024

In minimizing and narrowing students’ opportunities for exploration, discovery, deliberation, and thoughtfulness—the educational gold standard of our nation’s most elite educational institutions—by offering them a rationed education that is designed to facilitate quick completion of a degree or certificate, “redesigning” and Guided Pathways reforms and recommendations have promoted “workforce training” and devalued the humanities.
Cikkismertetés: Az ivóvíz mint a fogyás kulcsa? – a kaliforniai Water First kutatás eredményei
Authors: Devosa Iván
Published: May 2024

Közismert, hogy a víz egészségesebb ital, mint a cukorral édesített italok, amelyekről köztudott, hogy - rendszeres fogyasztás esetén - növelik a túlsúlyt és az elhízást. Kérdésként merült fel, hogy az ivóvíz esetén is működhet-e az „hogy az egészségesebb választás egyben a könnyebb választás is legyen” (Grossmann és Scala, 2004, 17. o.) célkitűzés egészségi állapotot javító hatása.
Cikkismertetés: A „színházsport” – új módszertani eszköz a fiatalok pozitív neveléséhez
Authors: Devosa Iván
Published: May 2024

Mivel kevés kutatás született a „színházsport” ifjúságra gyakorolt előnyeiről, ez a tanulmány e módszertani eszköz eredményeit vizsgálta, mint az ifjúság pozitív nevelésének megvalósításához felhasználható új eszközt. A Keith Johnstone (2017) által kifejlesztett „színházsport” egy olyan színházművészeti forma, amelyben improvizatív csapatok versenyeznek egymással a színpadon zajló jelenetekben és eseményekben.
Cikkismertetés: A halálozási okok sokféleségének tendenciái és meghatározó tényezői globális perspektívában (1990-2019)
Authors: Devosa Iván
Published: May 2024

Míg a vezető halálozási okokról és azok időbeli alakulásáról sokat tudunk, a halálozási okok sokféleségéről sokkal kevesebb ismerettel rendelkezünk. A halálozási okok sokfélesége a népesség egészségi állapotának heterogenitását jelzi, amelyet a jelenlegi egészséggel kapcsolatban megfigyelhető változások tanulmányozása során eddig nagyrészt figyelmen kívül hagytak.
Cikkismertetés: A szupermarketek promóciói Nyugat-Svédországban összeegyeztethetetlenek a skandináv táplálkozási ajánlásokkal
Authors: Devosa Iván
Published: May 2024

A nagy áruházláncok heti rendszerességgel készítenek reklámokat az élelmiszerek népszerűsítésére és a fogyasztói vásárlások befolyásolására. Ezáltal a hirdetések széles fogyasztói elérése lehetőséget kínál az étrendi ajánlásokkal összhangban lévő élelmiszerek népszerűsítésére. Az ismertetésre kerülő tanulmány célja az volt, hogy megvizsgálja a szupermarketek heti élelmiszerreklámjainak egészségügyi minőségét Svédország nyugati régiójában, figyelmet fordítva a kedvezőbb és kevésbé kedvező társadalmi-gazdasági indexű területekre.
Szakdokumentum: Alapvetések az egészség és jóllét javításához. Fehér könyv a magyar népegészségügy 21. századi megújításáról
Authors: Vitrai József
Published: May 2024

Az egészségügyi rendszerünkben nagy változások történtek az utóbbi években, és még többre számíthatunk a közeljövőben. Ennek a népegészségügy területén is lesznek következményei, ezért egy új szakmai koncepció kidolgozását kezdeményezte a Magyar Népegészségügy Megújításáért Egyesület, más néven a Népegészségügy 3.0 Egyesület.
Covert Crusade
Authors: Whyte Jeffrey
Published: May 2024

This chapter details the Central Intelligence Agency’s (CIA) stewardship of American psychological warfare between 1948 and the formation of the United States Information Agency in 1953. It narrates these events through the so-called ‘Crusade for Freedom,’ a long-running covert CIA campaign fronted by the ostensibly private citizens of the National Committee for a Free Europe (NCFE). While the CIA’s ruse against American citizens was spectacular, this chapter goes beyond revelation to analyse the ways in which the Crusade for Freedom encouraged regular Americans to imagine themselves as engaged in a personalised ‘spiritual war’ against the Soviet Union. This chapter considers the pastoral nature of American psychological warfare both at home and aboard, detailing its use of Christian ‘technologies of the self,’ notably confession and catechism. It concludes that the early years of the Cold War were deeply formative of the enduring perceptions and mythologies that continue to surround psychological war.
Bibliometric Analysis of Drainage System Performance Against Urban Flooding Using Vosviewer
Authors: Lubis Ahmad Mawardi , Rifai Andri Irfan , Savitri Amanatullah
Published: May 2024

Drainage is a channel that serves to drain excess water from one point to another.  This journal is in the form of a Bibliometric Analysis of the performance of the drainage system on urban tires. Bibliometric analysis of this study was carried out with the help of VOS Viewer and Publish or Perish software or applications. Publish or Perish helps to collect similar journals around the world that have links to the research under review. Next, bibliometric mapping is performed using VOS viewer software. The results obtained a lot of data such as Research Development by year, influential Authors and Publishers, and others that have a relationship with the research studied. The keywords "System" and "Drainage Capacity" were the densest keywords in this study. 2014 was also the year with the most related research with 79 total published studies.
Is greener really better? Stock market reaction to green bond announcements, Evidence from Europe
Authors:   , Somkerd Niya
Published: May 2024

Employing an event-study approach, we examine how the stock market responded to the offering of green bonds by non-financial companies listed on the European stock market from January 2013 to September 2022. We observed a drop, on average about 0.28%, in the company stock prices on the day they announced these offerings and the day after. Moreover, we found that investors react in the same manner for green bond announcements as for conventional bond announcements. We also studied if the Gavriilidis (2021)'s climate policy uncertainty index has any relationship with the market reactions. Our findings suggest that the index is positively related to the market's reaction to green bond offerings only before the COVID-19 pandemic hit.