bluuebunny/crossref_metadata_2025 huggingface dataset:
"Strategic Communication of Nanotechnology Innovations: Navigating Consumer Market Challenges and Opportunities"
Authors: Dr. Vijay Uprikar  , Dr. Shirisha Deshpande  , Dr. Krunal Parekh  , Dr. Parag Jawarkar  , Dr. Maajid Mohi Ud Din Malik  , Dr Samrudhi Churad
Published: December 2024

The rapid advancement of nanotechnology presents unprecedented opportunities for innovation across various industries, including consumer markets. However, the commercialization and marketing of nanotechnology-based products pose unique challenges due to factors such as consumer awareness, ethical concerns, and regulatory frameworks. This paper aims to explore the key challenges and opportunities associated with marketing nanotechnology innovations in the consumer market. Through a comprehensive literature review and case study analysis, the research identifies critical factors influencing consumer acceptance and adoption of nanotechnology products. The study highlights the importance of transparent communication, consumer education, and ethical considerations in building trust and driving market growth. Additionally, the paper examines the role of government regulations and industry standards in shaping the market landscape. The findings provide insights for marketers, policymakers, and researchers on effective strategies to navigate the complexities of promoting nanotechnology innovations, ultimately contributing to the sustainable growth of this emerging sector.
Predicting Portfolios Using Fuzzy Logic And Optimization Techniques: A Case Study Of BSE-IT Listed Companies
Authors: Challa Madhavi latha  , Dr. S. Bhuvaneswari  , Dr. K.L.S. Soujanya
Published: December 2024

Stock price trends were considered in this study, the companies in the BSE-IT index, with a view to optimizing portfolio allocation based on risk tolerance. The GARCH model has been applied here to allow an investigation into the volatility of the stock returns and to set up different clusters using K-Means clustering that group together companies owning the same attributes related to volatility for strategic classification. Data collection and processing occur between April 1, 2014, and March 31, 2024, for reasons of reliability and relevance. Descriptive statistics report on the variance of stock performance across companies; different risk-return profiles are thus exposed. The GARCH model measures each stock's long-term variance, along with sensitivity to past shocks, and overall volatility persistence, making this an excellent inventory for risk assessment. K-Means clustering groups companies based on similar volatility patterns, thereby informing portfolio construction. Findings present how clustering with econometric modeling may assist in the production of optimal portfolios that depend on specified risk capacities, thus efficiently managing and implementing an IT investment strategy.
Application State And Trend Of Artificial Intelligence Generated Content In Design And Art
Authors: Ouyang Shuangping  , Norfarizah Mohd Bakhir  , Lyu Ziwei  , Xu Yang
Published: December 2024

This study provides a comprehensive bibliometric review of Artificial Intelligence Generated Content (AIGC) applications in design and art, analysing publication trends from 2022 to 2024. Using data from the SCOPUS database, the study examines 472 publications, identifying key themes such as generative models, large language processing, and educational applications. The findings reveal a sharp increase in research interest, with prominent contributions from the United States and China. Major journals in this field include Documentation, Information & Knowledge and Computers and Education: Artificial Intelligence. This review highlights current research trajectories and underscores the need for ethical guidelines and improved models to ensure responsible integration of AIGC in creative industries. The insights gained here aim to inform future research directions, contributing to the sustainable and innovative application of AIGC in design and art.
Resectoscopic Versus Office Chemical Endometrial Ablation: Cohort Study
Authors: Lamiaa M Bakheet  , Safwat Abdelrady Mohammed  , Ibrahiem Ibrahiem Mohammed  , Ahmed M Kamel
Published: December 2024

Background: Menorrhagia is menstrual bleeding that is heavy in amount or duration and that occurs at regular intervals. Aim: To compare office chemical endometrial ablation using TCA compared to resectoscopic procedures, estimating cost effectiveness, and evaluating quality of life before and after the procedure.Patients & methods: This retrospective cohort study was carried out on 80 patients aged > 35 years old, with dysfunctional uterine bleeding and were randomly subdivided into either group I (underwent chemical endometrial ablation by TCA or group II (resectoscopic endometrial ablation) during the period of March 2016 to March 2020.Results: Majority of patients in each group had improved family care and were very satisfied with the treatment with no significant differences between both groups (p> 0.05). Majority of patients either had been cured with treatment acceptable or had acceptable improvement in symptoms. Treatment wasn't acceptable in only 5 (27.5%) patients of group I and 7 (17.5%) patients of group II with insignificant difference between both groups (p> 0.05). It was found that group I had significantly lower theater cost (28.50 ± 5.33 vs. 452.50 ± 50.57; p= 0.000) and total health service cost (61.00 ± 4.41 vs. 485.75 ± 52.28; p=0.000) in comparison to group II. Meanwhile, both groups were comparable as regard recovery cost (31.00 ± 4.41 vs. 33.25 ± 7.97; p= 0.12).Conclusion: Tri-cloro-acitic acid (TCA) is a safe and efficient method for treating dysfunctional uterine bleeding, particularly in non-conception women, without hospital admission or increased morbidity.
Enhanced Fuzzy Radial Basis Neural Network With Genetic Process Using Fuzzy Inferences
Authors: Dr. Muniyappan P  , Mr. Balasankar M  , Dr. Janarthanam S
Published: December 2024

Fuzzy Inference-Based Hybridization of a Genetic Algorithm to Enhance the Performance of an Enhanced Fuzzy Radial Basis Neural Network for Better Pattern Recognition and Prediction This proposed framework is comprises fuzzy logic in the body of a regular RBFNN-structured frame that has been optimized through a genetic algorithm. Experimental results shows that the Machine Learning Repository Air Quality data sets offered by the UCI with regular RBFNN, SVM, and Multilayer Perceptron as reference points in comparison with the EFRBNN models. The results are such that EFRBNN outperforms the mentioned methods with 12% accuracy, 9% improvement in F1-score, and 15% mean squared error compared to the standard RBFNN. The genetic process enhanced the optimization of parameters to attain a 20% faster convergence rate. Therefore, it has improved the abilities of this model to confront uncertainties better, and that in the context of noise involved in data, its strengths are 17% robust than these ones in SVM and MLP techniques. These results affirm the fact that EFRBNN may be utilized to manage complex real-time applications based on uncertain data in an imprecise setting.
Unveiling the Human-Nature Relationship: An Analysis of Ted Hughes’ Poetry
Authors: S. Vidhyalaskshmi  , Dr. S. Karthikkumar
Published: December 2024

Humans are a part of nature, yet relationship marketing and sustainable marketing fail to fully understand the interaction between people and the environment. Ted Hughes, a prominent figure in modern poetry, explore the complex relationship between man and nature in this works. This paper examines how Hughes portrays primal instincts within humans and animals, and their connection to the natural world. This paper also discusses how Hughes uses vivid imagery and metaphors to depict nature as a powerful force that can inspire and consume humanity. Additionally, the paper analyzes how Hughes highlights the destructive aspects of nature in his poems. Overall, this paper aims to provide a comprehensive understanding of the interconnectedness between man and nature, as portrayed in Hughes’s poetry.
Theological Reflections on Female Strength and Faith: An Analysis of Women in Lynn Austin’s Hidden Places
Authors: Rabeka Mary. A  , Dr. J. Arul Anand
Published: December 2024

Lynn Austin's historical romance novel Hidden Places is set in the Great Depression. Eliza Wyatt, a young widow with little experience and growing debt following her husband's death, is the protagonist of the novel. She is trying to maintain her family's apple farm. Eliza, who has to provide for her three small children, is completely overwhelmed until a strange drifter named Gabriel Harper and his name as Gabe. He shows up and offers to help with the orchards in exchange for housing and food. Initially apprehensive of Gabe, Eliza eventually learns to rely on his easy talent with the trees and his compassionate manner with her kids. Despite Gabe's past secrecy, an unmistakable attraction blossoms as they work side by side. Eliza has to stop the ruthless orchards foreman from plotting to steal the land for himself. Eliza gets the fortitude to endure when one of her children has a medical emergency that calls for a dangerous treatment because of Gabe's unwavering support. In the end, Gabe's difficult past comes to light, enabling them to get past their pasts. In the endearing denouement, their budding romance blooms as they work together to restore the family orchards. In the end, Hidden Places is an uplifting reflection on the human spirit's tenacity and a reminder that, even in the midst of hardship, we may find meaning, regeneration, and modest pleasures by continuing to be aware of the tiny rays of beauty, generosity, and fulfilment. It encourages us to steadfastly manage our own spiritual orchards, believing that even in the most desolate settings, the most profound blessings in life can blossom again.
Intelligent Real-Time Helmet and License Plate Detection Device for Traffic Monitoring
Authors: Dr. G. Revathy  , Dr. N. Seethalakshmi  , Dr. S. Prabhu  , Dr. P. Nithiyanantham
Published: December 2024

In response to growing safety concerns on urban roadways, this study provides an intelligent real-time system for detecting helmets and license plates that is especially tailored to improve traffic monitoring and enforcement. Using YOLOv8's improved capabilities in conjunction with Spatial Pyramid Pooling (SPP), the suggested system reliably recognizes motorcycle helmet use and detects car license plates with high precision and speed. The addition of SPP improves the system's feature extraction capabilities, allowing for robust detection over a wide range of environmental situations, including different lighting and weather scenarios. This approach, which focuses on real-time processing, enables traffic officials to efficiently enforce helmet compliance and identify offenders, contributing to a safer urban transportation ecology. Experimental findings show that the device has excellent detection accuracy and processing efficiency, making it appropriate for use in intelligent transportation systems (ITS). The outcomes of this study show that AI-powered enforcement tools have the potential to increase road safety and expedite traffic monitoring activities.
A Systematic Review Of Credit Card Fraud Detection And Prevention Techniques
Authors: Marouane Ben Boubker  , Ahmed Eddaoui  , Sara Ouahabi  , Kamal El Guemmat  , Tarik Chafik
Published: December 2024

The data science community has shown significant interest in credit card fraud (CCF) due to its growing prevalence and the significant financial losses it causes. However, existing systematic reviews have not thoroughly explored the various techniques used in CCF beyond mere comparisons.The objective of this research is threefold. First and foremost, it aims to provide a clear definition and classification of CCF. Furthermore, it aims to provide a comprehensive overview of the standard techniques currently employed to prevent CCF, ensuring strict adherence to industry and international payment network standards. The study also seeks to explore alternative tools proposed in existing literature. Lastly, the research aims to conduct a systematic analysis of advanced techniques using different aspects of machine learning and deep learning models. This analysis includes considering the type of model, estimation metrics, model comparison, as well as the challenges encountered during the process.A comprehensive search was conducted across multiple electronic databases to review studies published between 1990 and 2021. The review concentrated on two primary categories: studies focused on the classification of credit card fraud and those that examined the key techniques used for its prevention and detection.Deep learning (DL) models show great potential in the detection and prevention of CCF. However, their use in industry remains limited, highlighting the need for further efforts and incentives to support their implementation. Based on our review, we offer targeted recommendations for researchers and practical guidelines for industry professionals.
A Novel Wetland Detection and Classification Using Invasive Weed Optimization Algorithm with Deep Learning Model
Authors: Daniel Arockiam  , Azween Abdullah  , Valliappan Raju
Published: December 2024

This research shows some of the worthy ecosystem services provided by wetlands are biodiversity support, water regulation, and carbon sequestration. These ecosystems are under threat due to human activities such as urbanization and industrialization, so their identification and classification are very important for their conservation. Synthesis aperture radar has been successful in detecting wetlands since it can penetrate through cloud covers and is sensitive to moisture content. Although promising Support Vector Machine (SVM) and Random Forest (RF) approaches, this still often requires high preprocessing and exhaustive handcrafted feature extraction. Deep learning models, especially Convolutional Neural Networks (CNNs), manage to improve classification performance but have problems with slow convergence rates and serious overfitting in big data. Based on these gaps, the paper presents a new approach proposing the integration of the modified Invasive Weed Optimization (IWO) algorithm with CNN-based detection for Synthetic Aperture Radar (SAR) images, focusing on wetland classification. Addressing the slow convergence problem and possible entrapment into a local optimum, enhanced IWO parameters in the CNN include learning rate and batch size. Also, to test the applied model, SAR data demonstrates a classification accuracy of about 90%, with key metrics such as precision at 88% and recall at 91% showing superior performance compared to that obtained using traditional techniques. Conclusively, the study states that the combination of CNN and the improved IWO algorithm highly enhances the accuracy of wetland detection, thereby providing a more robust solution for conducting environmental monitoring and conservation efforts.
A Novel Deep Learning Lacunarity Texture Analysis System Using Mid-Point ROI Extraction Algorithm for Palmprint Recognition System
Authors: Abirami B  , Krishnaveni K
Published: December 2024

The palmprint comprises multiple unique patterns that are distinct in detecting human identity. There are numerous algorithms proposed by past researches for recognizing Two-dimensional Palmprint Region of Interest (2DPROI) images. In this research, an innovative Deep Learning Lacunarity Texture Analysis System (D2LTA) is developed for recognizing the accredited persons at higher recognition rate. To impart the D2LTA model, Two-dimensional palmprint hands’ ROI images are segmented using Mid-point ROI generation algorithm, produced a peculiar feature vector using lacunarity approach in a state-of-the-art manner, and then Deep Learning ConvNet classifier is proposed for D2LTA system to justify the accredit person. The key principle of the Mid-point ROI generation approach is to determine the perfect straight line on the center of the palm. Based on the straight line in the palm, determine the pixel values of the ROI’s rectangular box. To catch the perfect straight line, line mid-point method is used. To do this research, 2D-palm hands are procured from three different datasets such as BMPD, CASIA and IIT palm datasets and 2DPROI images are secured from PolyU, Hong Kong Polytechnic University, Hong Kong. The proposed model has been assessed with diverse dimensions to prove the acquirement 99.25% of higher precious authentication rate.
Testing The Use Of Phosphate Materials And Glass Fines In Concrete Production
Authors: Mohmd Sarireh
Published: December 2024

The research focuses on the testing production of concrete through comparison with control concrete mix for phosphate materials from two sources (Al Shedyah and Abiad mining plants) and glass fines that were used in replacement with fine sand in concrete mix on specific mixing ratios (15%, 30%, 45%, and 60%). The program of concrete testing included fresh concrete properties (slump), and hardened concrete properties (unit weight, compressive, tensile, and flexure strengths). The results were sorted through calculating of averages, standard deviations, and analysis using ANOVA and box plot to test the difference in samples averages. Results showed slump of concrete increases with the increase of phosphate or glass fines ratios. Generally, unit weight is stable using phosphate materials, and decreasing using glass fines materials. The initial analysis of compressive strength showed stability, similar talk can be withdrawn on flexure strength, but tensile strength decreases with increase of material ratio in concrete mix. Similar indication can be withdrawn on unit weight of concrete. But for slump value, it increases with the increase of materials ratios in concrete mix. All properties were tested and reported at 28-day period in current research. Also, a box plot was presented for all properties studied in current research to show the range of properties versus the ratios of phosphates and glass fines materials. Also ANOVA analysis was conducted for the properties of fresh and hardened concrete. ANOVA analysis showed that slump values are significant different and null hypothesis is rejected, but for unit weight null hypothesis is accepted that the unit weight is not significant different. Also, results of ANOVA analysis showed that for compressive, tensile and flexure strengths are significantly different and null hypothesis is rejected accept for 60% mixing ratio of phosphate and glass fines, the results are equal and the null hypothesis is accepted. The results of current research presented a different procedure to document, test, and interpret results to be used in future extend of research.
Efficacy Of Nano Hydroxyapatite Derived From Marine Sources On Remineralization Of Enamel: A Systematic Review
Authors: Dr. Mounika Veeraiyan  , Dr. Jayalakshmi Somasundaram  , Dr. Saravanan Poorni  , Dr. Sharanpriya Sathnoorkar  , Dr. Praveena Kannabiran  , Dr. DelphiaThomas
Published: December 2024

Background and Aim: Nano Hydroxyapatite (nHA) is a biocompatible material similar to natural bone and is used in dentistry to prevent and remineralize dental caries, etc. Marine sources like seashells, mollusk shells, crab shells, shrimp shells, fish bones, etc can create Nano-hydroxyapatite (nHA), a biomimetic material potentially useful for remineralization. This study aimed to systematically review the literature on the efficacy of marine-derived nHA in enamel remineralization compared to other remineralizing agents (e.g., fluoride, CPP-ACP, amorphous calcium phosphate)Materials and Methods: This systematic review followed PRISMA guidelines, searching electronic databases from 1990 to July 2024 (Medline, Scopus, Cochrane). Only in vitro studies with Nano-hydroxyapatite from marine sources compared to other remineralizing agents were included. Two reviewers (VM, TGJ) screened articles, extracted data, and assessed study quality using the Quality Assessment Tool For In Vitro Studies (QUIN tool).Results: Out of 43 identified articles, eight in vitro studies published between 2019 and 2023 were included, evaluating nHA from blood cockle shells, fish bone/scale, and oyster shells. Most of the included articles compared with commercially available CPP-ACP remineralizing agents. The QUIN tool revealed a medium risk of bias in seven studies and a low risk of bias in one. Conclusion: While marine-derived nHA has shown promising results in remineralizing enamel lesions, the current evidence is limited by methodological shortcomings. Further well-designed research is needed to draw more definitive conclusions.
Solid Waste Management – A Case Study in Puducherry
Authors: T. Dhivya  , Dr. A. Royal Edward Williams
Published: December 2024

In modern era the technological improvement, urbanization, migration and huge population have increased the waste generation. Increasing population will leads to lack of infrastructure facility like water sanitation, sewage and solid waste management. People are not properly disposing their waste into the common waste bin as well as bins are not sufficient with the increasing population level. Due to improper disposal of solid waste, it ultimately reached into sewage channels and ends with blockage of sewage channels. It leads to cause more environmental and health issues. Improper waste management in the landfill of Puducherry district cause more heat in the landfill as well as increase in the leachate generation and it will leads to the contamination of soil and ground water quality. This paper focused on health and environmental issues owing to improper disposal solid waste and its management practised.
Experimental Investigation to Evaluate Mechanical Properties on Nano Graphene Added CFRP Laminates
Authors: V. Nikil Murthy  , Dr. Ashwin C Gowda  , Dr. Santhosh N  , Dr. Dhanunjaya Munthala  , Dileep B. P
Published: December 2024

Polymers are regularly supported by different estimated fillers to lighten a portion of the constraints of the polymers. The use of nanoscale fillers to work on mechanical and thermal properties of polymers have prompted to an extreme option for the conventional polymer composites. Their high strength-to-weight ratio, excellent mechanical properties, and resistance to corrosion make them ideal for use in creating lightweight and durable structures. The present work mainly focused on the carbon fibre(CFRP) added with Graphene filler with 3mm thickness and a layer thickness of 0.5mm in vacuum impingement moulding process with vacuum bagging at different pressures directions , number of layers and curing temperatures. Graphene Nano particles taken as filler content of 2% which has been done previously as pilot experiments and form literature. The design of experiments selected from Taguchi L9 orthogonal array to prepare samples. A three factorial study from Taguchi has been optimized to check the best parameters for improved mechanical properties in the composite. The direction of injection is taken as top, and diagonal as well as pressure 20 bar, 25 bar and 30 bar with curing temperatures after lamination is 60, 80 and 100℃.
Use of Lab Scale Reactor for Performance Evaluation of Anaerobic Digestion Through Cane Grass and Buffalo Pats
Authors: Tripti Gupta  , Ajinkya Dharaskar
Published: December 2024

The aim of present research is to check performance of cane grass with buffalo pats and its slurry in anaerobic digester. Lab scale based reactors were modeled to evaluate the biogas production potential of organic-waste. The reactors are made up of synthetic cans. After several changes in the components, these models are used for biogas production. The study found the production of biogas was 0.45m3/kg for the cane grass (CG) to buffalo pats (BP) with ratio of CG:BP as 50:50 at 35oC. Similarly for the different combination ratios of CG:BP-60:40, CG:BP-70:30, CG:BP-80:20 and CG:BP-90:10 same methodology was followed. In this ratios production of biogas were found 0.50, 0.42, 0.27, 0.23 m3/kg respectively.
Control Alternatives for Dactylonectria Torresensis in Blackberry
Authors: Ana K. Pincay-Vedezoto  , Cristina M. Tello-Torres  , Pablo Llumiquinga  , Karina Marin  , Cynthia I. Oña-Malataxi  , William F. Viera Arroyo
Published: December 2024

Black foot disease (Dactylonectria torresensis) in blackberry cultivation (Rubus glaucus) is a recent problem in Ecuador, where its management has based on agrochemicals, which can be harmful to health and the environment. This study aimed to evaluate more sustainable alternatives for controlling the disease caused by this pathogen. Initially, different propagules were evaluated to induce the disease in plants of blackberry Castilla. Subsequently, biological products (three strains of Trichoderma spp.), organic products (flavonoids and Myrtaceae extract), and chemical products (azoxystrobin, propiconazole, carbendazim, and copper sulfate pentahydrate) were tested under greenhouse conditions. The main results indicated that carbendazim, Myrtaceae extract, Trichoderma spp., propiconazole, and copper sulfate pentahydrate were effective in reducing the pathogen severity, showing root collar necrosis percentages of 21.25%, 35.50%, 43.58%, 44.92%, and 47.92%, respectively, which was, significantly lower than the untreated control, which presented 73.75%. This study provides valuable guidance for developing more sustainable and effective management strategies for controlling black foot disease in blackberries, integrating the identified products into a fungicide rotation scheme as a component of integrated crop management.
Economic Dispatch for Optimal Management of Isolated Microgrids Using Random Input Data
Authors: Jhoao Rea  , Diego L. Jiménez  , Carlos Veloz  , Roberto Salazar Achig
Published: December 2024

This work presents the economic dispatch of an isolated non-conventional renewable energy (NCRE) microgrid in conjunction with a diesel generator and a BESS battery bank. For the development of the model, random input scenarios were used based on real measured data of solar radiation and wind speed. Three evaluation scenarios were established using the Monte Carlo method, with synthetic series less than, equal to, and greater than the average. Likewise, the economic dispatch is proposed as a mixed integer linear optimization model MILP, which includes the use of the diesel generator by means of linearization by sections. The economic dispatch is solved for 24 hours for the three possible scenarios, where in the first scenario the demand is supplied in 31.7% by solar power, 12.2% based on the BESS, 1.2% of wind power and 54.9% from the diesel generator, in the second scenario there is 32.5% of solar power, 21.3% of BESS, 4.2% of wind power and 41.9% from the diesel generator. Finally, in the third scenario, 57.7% of the demand is met by solar power, 21% by BESS, 7.7% by wind power and 41.9% by the diesel generator, thus meeting the demand in its entirety for all the proposed scenarios.
Effects of Motivation When Learning: A Case Study in Valledupar Secondary Education
Authors: Edilmer Jiménez Anicharico  , Erica Estebana Baldovino Mercado  , Luis Eduardo Ardila Brugés  , Deimer Jesus Dominguez Ojeda  , Ernet Guillermo Maestre Orozco  , Gilberto José Cujia Romero
Published: December 2024

During adolescence, students face various emotional confrontations that influence their perception of the subjects they study. This process can give rise to fears of subjects that are unfamiliar in previous educational stages. In this context, the present research aims to determine the value of motivation as an essential element for learning in secondary education. To support this study, prominent authors in the field of psychology and education have been taken as references, such as Allport (2011), Atkinson (2008), Bandura (2008) and Llorems (2011). The methodology used is documentary, with a bibliographic design that includes an exhaustive review of various texts, documents and writings relevant to the construction of the work. The findings of this research indicate that motivation towards learning is crucial for students' academic development. In this sense, it is concluded that it is essential that teachers in the schools investigated introduce motivating elements into their educational practice that facilitate the establishment of meaningful connections between students. This involves fostering a cooperative learning environment, where mutual support and teamwork are valued, taking advantage of each student's individual talents and aptitudes. By integrating motivational strategies into teaching, it is hoped not only to improve academic performance, but also to cultivate a lasting interest in the subject, which will contribute to the integral development of students in their educational journey.
A Systematic Literature Review of Counterfeit Currency Detection using Modern Methods
Authors: Dr. K. Sundravadivelu  , S. Muthukumar  , P.A. Subi  , E. Subananthini
Published: December 2024

The escalating issue of counterfeit currency, fuelled by sophisticated printing and scanning technologies, poses a substantial threat to global economies, undermining financial systems and eroding public trust. Effective counterfeit detection has become imperative for mitigating this growing problem and safeguarding monetary integrity. This paper provides a comprehensive review of current and emerging methodologies in counterfeit currency detection, with a primary focus on image processing techniques. Key approaches, including Ultra Violet (UV) detection, polarization analysis, advanced edge detection, and machine learning algorithms, are explored in depth. Specific image processing techniques, such as the canny edge detection algorithm, image segmentation, and feature extraction, are analyzed for their effectiveness in identifying subtle differences between genuine and forged currency features. The paper also emphasizes the integration of these techniques into automated systems, which enhance accuracy, speed, and scalability in real-world applications. Leveraging both traditional and advanced technologies, this study proposes a robust framework for cost-effective, reliable, and scalable solutions in counterfeit detection, aiming to strengthen defences against increasingly complex forgeries.
The Impact of Subsurface Tillage Techniques and Irrigation Methods on Soil Dynamics, Growth, and Potato Crop Yield
Authors: Faisal G.H.Ali  , Arkan M. A.Sedeeq  , Hussien J. M. AL-Bayat
Published: December 2024

This study was conducted in the field of the College of Agriculture and Forestry/ University of Mosul during the spring agricultural season of 2023 to examine the effect of three irrigation systems (drip, sprinkler, and surface irrigation) and the use of a subsoil plow at depths of 25-35 cm and 35-45 cm on the potato crop. The split-plot design was used once in a Randomized Complete Block Design (RCBD) with three replications. Data were then recorded and statistically analyzed. The results were as follows: The drip irrigation system significantly outperformed in the leaf area of the plant and the yield per plant. The sprinkler irrigation system significantly outperformed in irrigation costs, while the surface irrigation significantly outperformed in pump operating time. The 35-45 cm tillage depth significantly outperformed in plant height, leaf area per plant, yield per plant, and marketable tuber yield, with an increase of 17.32%, 12.56%, 25.14%, and 12.63% respectively. The 25-35 cm tillage depth recorded the lowest significant values in operating costs and pump operating time, at 18.02% and 12.88% respectively. The interaction between drip irrigation and 35-45 cm tillage depth recorded the highest significant values in plant height, leaf area per plant, yield per plant, and marketable tuber yield, while the interaction between sprinkler irrigation and 25-35 cm tillage depth recorded the highest values in operating costs and pump operating time.
Analyzing Covid’19 diseases from Ultrasound Image Report using Natural Language Processing compared with Novel Conditional Random Filed Algorithm
Authors: Logu K  , S. John Justin Thangaraj
Published: December 2024

Improving the quality of ultrasound report in image for Covid’19 disease detection using deep learning in novel Conditional random fields (CRFs) Algorithm over natural language processing (NLP) Algorithm. A Novel Conditional Random Fields Algorithm (NCRFA) is pattern recognition and structured prediction algorithm and a branch of deep learning. This algorithm should be able to improve accuracy compared to the natural language processing algorithm. The data set needed for ultrasound report for disease prediction is acquired from the Juypter. Analysis, design for various proposed algorithm is natural language processing and deep learning application are performed for conditional random fields and natural language processing algorithms. In this tested data sets are imported in two algorithms for enhance and framework. Those testing size are calculated various statistical power test for different t and f test are calculated in two groups and 400 data used in each algorithm. Results: The final output are obtained in convex and linear in ultrasound image report for supplied process. The statistical package for the social sciences programmer is generate the process. There is apparent between NCRFA and its accuracy, which is 87.50%, 81.17%, p= 0.04 (P<0.05), NLP algorithm that provide accurate value. According to the findings, the conditional random fields have a more processing exact the natural language processing.
EFFECT OF LONG-TERM STORAGE OF FRUIT EXTRACTS ON ANTIOXIDANT ACTIVITY AND ANTOCYANINS CONTENT
Authors:   Bioengineering Laboratory, Baku State University, Baku, Azerbaijan, Agalarov R.
Published: December 2024

In present article, we investigated the quality effect of long-term storage for ethanol/water extracts of local fruits. The quality parameters were based on antioxidant activity and anthocyanin content in extracts. Comparative analysis of antioxidant activity in the initial period and after one year of storage for technological extracts showed a decrease from 27 to 51% for different fruits. A quantitative comparison with anthocyanin degradation showed a positive correlation with DPPH activity degradation.
THE STUDY OF GENETIC EFFECTS OF COMBINING ABILITY IN DIALLELIC COTTON HYBRIDS WITH IMPROVED FIBER TRAITS
Authors:   Genetic Resources Institute, Ministry of Science and Education, Baku, Azerbaijan, B. Mammadova R.
Published: December 2024

The genetic variability of important fiber quality traits of cotton such as: uniformity Index (UI); fiber elongation before breaking (Elongation, Elg) and micronaire (Mic) were studied. Qualitative characteristics were tested on the HVI (High Volume Instrument) system, in accordance with the international classification. Local cotton varieties (Agdash-3, AP-317 and Elekberi), Turkish testers (Sezener 76, Naz 07, Ozbek and GSN 12) and 12 incomplete diallelic hybrid combinations were evaluated to determine the potential of parental varieties, F1 and F2 hybrids using effective method - combining ability. Analysis of variance, carried out on the basis of data from all studied combinations, made it possible to identify one local line (AP-317) and two foreign testers (Naz 07 and GSN 12), which had, to varying degrees, positive effects of total combining ability (TCA). This indicates additive types of expression of non-allelic genes responsible for the formation of the studied qualitative properties of cotton fiber. Variations in the SCS of hybrid combinations were generally lower than the effects of the GCS. When assessing second-generation hybrids, we determined that lines and testers with positive effects of GCA and hybrid combinations with their participation were distinguished by high indicators of the fiber quality in the next generation. Consequently, selection of genotypes with improved fiber quality carried out in early generations can be effective, which will accelerate the creation of new promising varieties and lines of cotton.
THE CHANGES OCCURRED IN THE WINTERING BEHAVIOR OF THE MIGRATORY-WINTERING RED BOOK SPECIES OF THE ANSERIFORMES IN THE GIZILAGHAJ BAY
Authors:   Department of Zoology and Physiology, Baku State University, Baku, Azerbaijan, N. Taghiyev A.
Published: December 2024

In 2018-2024, the effect of the lowering of the water level in the Caspian Sea on the wintering behavior of the migratory-wintering species from the order of Anseriformes included in the 3rd edition of the Red Book of the Republic of Azerbaijan (2023) was studied in the Gizilaghaj Bay which is one of the largest wintering places of the birds in Eurasia. 10 migratory-wintering species (Branta ruficollis, Anser erythropus, Cygnus olor, Cygnus bewickii, Marmaronetta angustirostris, Aythya ferina, Aythya nyroca, Clangula hyemalis, Melanitta fusca, Oxyura leucocephala) from the Anseriformes order were included in the Red Book of Azerbaijan. 9 of them are the migratory-wintering species. Only Aythya nyroca has a migratory-wintering population as well as a sedentary one. The migratory-wintering species included in the Red Book come to the research area from the Northern European countries, Russia and the North of Kazakhstan. The lowering of the water level in the Caspian Sea caused a change in the wintering behavior of the migratory-wintering species in the Gizilaghaj Bay.
Ámbito competencial autonómico en materia de patrimonio cultural. Especial referencia al Pazo de Meirás
Authors: Novo Castro María Isabel
Published: December 2024

Análisis de la competencia de las comunidades autónomas en relación con el patrimonio cultural y la confluencia con las competencias concurrentes del Estado en la materia, partiendo de un estudio de la normativa y la jurisprudencia, con especial referencia a la situación competencial existente sobre el Pazo de Meirás.
Medidas de fomento del patrimonio cultural. Especial referencia a los beneficios fiscales
Authors: Rivera Frade María Dolores
Published: December 2024

El riguroso régimen de protección de los bienes que integran el patrimonio cultural y las rigurosas limitaciones a las que están sujetos los propietarios justifican la necesidad de que las Administraciones públicas adopten medidas de fomento y de estímulo para la conservación, restauración, protección, puesta en valor y difusión de estos bienes. Entre estas medidas ocupan un lugar destacado las de carácter económico, pues con ellas se trata de compensar el sacrificio y los gastos que deben asumir los propietarios de estos bienes en cumplimiento de las obligaciones de conservación que les impone la legislación protectora del patrimonio cultural. En este trabajo se recoge una breve explicación de alguna de las medidas de fomento con las que las Administraciones públicas tratan de proteger este patrimonio, dedicando un estudio particularizado a los beneficios fiscales, que de forma indirecta suponen un importante incentivo para la conservación, restauración y difusión del patrimonio histórico.
Recurso de casación: diálogo entre tribunales. Aspectos procesales (2023)
Authors: Villegas García María de los Ángeles
Published: December 2024

La reforma, en el año 2023, de algunos aspectos de la casación penal redibuja el papel que los órganos de instancia están llamados a jugar en su preparación. Resulta, pues, imprescindible conocer cuáles son los extremos fundamentales de dicha reforma. En esta línea, es también relevante la exposición de algunos pronunciamientos de la Sala de lo Penal del Tribunal Supremo sobre la posibilidad de recurrir en casación ciertos autos dictados por tales órganos, así como sobre determinadas cuestiones procesales, ajenas propiamente a la tramitación de la casación, pero igualmente relevantes.
El juez en las redes sociales: perfil, posibilidades y límites
Authors: Portillo Rodrigo Fernando Germán
Published: December 2024

Los retos que las redes sociales plantean a los jueces que queremos participar en ellas no son pocos. Desde cómo presentarnos en la red social hasta el modo en que debemos conducirnos una vez estamos dentro. Aquí entran en juego los límites que tenemos a nuestra libertad de expresión, tanto jurídicos (disciplinarios, fundamentalmente) como éticos. Pero estos últimos, ampliamente expuestos por instituciones nacionales e internacionales, no deben conducir a una restricción real de un derecho fundamental como es la libertad de expresión, so pena de convertir a los jueces en ciudadanos de segunda categoría.
The Complementary Relationship between the Legal and Customary Rules of Aflaj in the Sultanate of Oman - A Comparative Study –
Authors: Al-Khamisi Khalid Abdullah Khamis , Al-Shuaili Mohamed Saif Duwaim
Published: December 2024

Resorting to adopting interdisciplinary studies has become urgent in light of the rapid developments in various aspects of life in the world, including social, economic, cultural and others, in addition to the legislative and regulatory vacuum for some sectors and services, especially those that depend on the prevailing societal norms in each environment and society, based on the sovereignty of those norms in families, organizations and societies. Among the sectors that are linked to the fabric of life in the Sultanate of Oman is Aflaj system, which is considered the first water resource in terms of economic, social and livelihood importance in the Sultanate. The governing norms for regulating the exploitation of this resource in the Sultanate have varied according to what is palatable to villages and countries, as attention to it in Omani jurisprudential encyclopedias was clearly evident. In light of the modern legal legislation in the Sultanate regulating this resource, there seems to be a need to shed light and demonstrate the cognitive integration between theoretical aspects, judicial applications, and established norms in this regard, while clarifying the important relationship of the type of legal research methods appropriate in the production of this study; As an picture and manifestation of interdisciplinary studies between law and other sciences, we ask Allah for success and guidance.
Optimizing Village Economic Potential: A Sustainable Development Framework for Rural Areas in Bantan Subdistrict, Bengkalis Regency
Authors: . Taryono , Iyan Rita Yani , Sari Lapeti
Published: December 2024

This study explores a novel framework for optimizing village economic potential, emphasizing sustainability in Bantan Subdistrict, Bengkalis Regency. Utilizing a unique dataset from the Village Potential Survey (PODES) combined with in-depth interviews, the research identifies tourism, agriculture, and cultural heritage as key economic drivers. A detailed analysis highlights opportunities and challenges in leveraging coastal and peatland resources, particularly concerning infrastructure gaps and market isolation. The findings propose a collaborative model involving governments, communities, and private sectors to foster rural economic growth while ensuring environmental sustainability. The study’s interdisciplinary approach contributes to existing literature by offering localized strategies tailored to the socio-economic and ecological characteristics of rural areas.
Quarantine and its Impact on the Environment
Authors: Hussein Zahraa Ahmad , Shehab Marwa Abdelsattar , Abdulkader Abdulkader Salam
Published: December 2024

Quarantine is a common public health strategy used to help prevent the spread of highly contagious diseases. According to the Centers for Disease Control and Prevention, quarantine is a preventive measure that separates and restricts the movement of people who have been exposed to an infectious disease to find out whether they are sick or not. Some positive phenomena have been observed on the environment, varying from place to place. There has been an increase in air quality, and the satellites have recorded a significant decline in toxic gas emissions. The positive impact has been extended to include water. In addition, noise has been reduced due to the disruption of the movement of trains, buses and cars. Other positive effects included clarifying the importance of a healthy lifestyle such as exercises, healthy food, staying away from smoking and paying attention to cleanliness, all of which are effective factors in reducing the spread of the epidemic, in addition to promoting a sense of responsibility towards society, dealing positively with crises, flexibility in changing the routine of life and leisure time, learning to refrain from things that people used to and disappeared with the current situation, in addition to contributing to the return of the spirit of humanitarian cooperation and teamwork.
Evaluating green initiatives: advancing environmental responsibility in global business operations
Authors: Paudel Ram , Yedgarian Vahick A. , Faisal Ahmed Md , Hasan Md Jaowad , Kumar Koirala Raj
Published: December 2024

This paper assesses green practices and corporate environmentalism in international business management. It examines sustainability activities in different industries, emphasizing the strategies companies adopt to achieve sustainability and economic performance simultaneously. Drawing on corporative environmental reports, sustainability audits and green performance indicators, this study reveals the motivators and barriers to implementing environmentally sustainable practices. The study sheds the light on how firms can adopt eco-efficient technologies, waste management, and resource optimization to enhance their competitive advantage and meet organizational environmental responsibilities. The proposed research advances the knowledge of corporate stewardship and offers practical recommendations for organizations interested in improving environmental responsibility.
Caught in the whirlwind of market power: The impact of WhatsApp's 2021 update on users' privacy in India
Authors: Shah Nikita
Published: December 2024

WhatsApp's entrenched market power has culminated in Indians being obliged to give up their privacy. This paper reports on an empirical study of WhatsApp to prove that it has been able to infringe consumers' privacy because of its market power, which has become insidious due to network effects, consumer inertia and asymmetry of information. Throughout this study, the author has not tried to quantify privacy or develop parameters of privacy, since the responses would have been flawed by subjectivity. Instead, the author has conducted this quantitative study to prove that consumers value privacy on paper but not when faced with the counteraction of free services. The researcher used questionnaires to understand the behaviour of Indian users towards privacy. The respondents were chosen based on a stratified sampling method, and analysis was done using descriptive statistics to quantitatively summarise the challenges faced by the respondents in switching away from WhatsApp.
The study concluded that users cannot exercise constraints due to the privacy paradox, consumer inertia and asymmetry of information. WhatsApp has the largest consumer base in India, and hence, its pervasiveness is considered extensively in this paper.
Bridging compliance and innovation: A comparative analysis of the EU AI Act and GDPR for enhanced organisational strategy
Authors: Musch Sean , Borrelli Michael Charles , Kerrigan Charles
Published: December 2024

This paper conducts a comparative analysis of the GDPR and the EU AI Act, focusing on their approaches to innovation, compliance and risk management. It examines how the GDPR's data protection framework intersects with the AI Act's broader ethical considerations, highlighting their complementary roles in fostering responsible technology use. Key findings reveal that while both regulations aim to protect individuals and promote ethical practices, harmonising these frameworks is crucial for effective compliance, despite inherent differences between the two. The paper underscores the need for integrated strategies and adaptive policy-making, in a global context, to navigate the complex regulatory landscape, ensuring both innovation and accountability in AI development.