bluuebunny/crossref_metadata_2025 huggingface dataset:
Interconnectedness and Volatility Dynamics in Major Cryptocurrency Markets: A Study of LTC-USD, BTC-USD, BNB-USD, and ETH-USD
Authors: Suri Ritu , Singh Pawan Kumar
Published: November 2024

This study employs an asymmetric VAR(1)-multivariate GARCH(1,1)-BEKK approach to evaluate the returns, shock, and volatility spillovers for BTC-USD, LTC-USD, BNB-USD, and ETH-USD cryptocurrencies. The findings of the current study reveal significant interconnectedness in between currencies, and notable complementarity observation between BTC and ETH. Additionally, LTC and BNB exhibit an inverse impact on BTC and ETH returns, indicating their increasing popularity among investors. The variance equation analysis demonstrates that past shocks/news significantly affect all cryptocurrencies, with lower cross-news effects compared to internal news impacts. In addition to that,  a significant short-term and long-term volatility spillovers are found among the four major cryptocurrencies market. Further, we find a substantial increase in the conditional volatility of the selected cryptocurrencies from April 2022 to November 2022. This research work emphasizes the significance of interconnectedness, and volatility dynamics of cryptocurrencies in portfolio management. Additionally, it provides suggestions for  policymaking for effective risk management strategies and regulatory  measures in market.
A CYCLICAL ANALYSIS OF THE RELATIONSHIP BETWEEN INCOME TAX AND UNEMPLOYMENT: EMPIRICAL EVIDENCE FOR TURKEY
Authors: Ay Şahin , Çelik Süleyman
Published: November 2024

Increasing tax revenues is very important for states. Among the crucial topics that require investigation in this context is the impact of certain macroeconomic variables on revenue from taxes. This study investigated the impact of Turkey's income tax revisions on the country's unemployment rate. From 2005 until 2023, information from the Ministry of Treasury and Finance's and the IMF's online databases was used for the study. The Breitung-Candelon Frequency Domain causality test was used to determine the periodic causality relationship between variables, the ADF unit root test was used to analyze unit roots, the ARDL bounds test was used to determine the long-term cointegration relationship, and the long-term coefficient was used to determine the direction and strength of the independent variable's effect on the dependent variable estimators. As a result of the research, it was determined that income tax has an effect on unemployment in the short, medium and long term. Additionally, unemployment affects income tax in the medium and long term. Finally, according to the results of OLS, FMOLS and CCR, which are long-term parameter coefficient estimation tests, the coefficients of the income tax variable were statistically significant in all estimators and it was seen that the income tax level and the unemployment level had a positive interaction. Thus, raising income taxes eventually results in higher unemployment in long term.
Intelligent Traffic Lane Management System
Authors: Ms. Rajashree Thosar  , Sarthak Pampattiwar  , Prathmesh Gidage  , Pravin Khakale
Published: November 2024

Traffic congestion in urban areas has become a significant challenge, resulting in increased travel times, environmental pollution, economic losses, and heightened stress levels among commuters. Traditional traffic management systems often struggle to adapt to dynamic traffic conditions, leading to inefficient utilization of roadways and suboptimal traffic flow. To address these pressing issues, we propose an Intelligent Traffic Lane Management System (ITLMS) designed to optimize traffic flow, enhance road safety, and reduce the environmental impact of vehicular emissions. The ITLMS leverages advanced technologies, including video acquisition, image processing, and Optical Character Recognition (OCR), to effectively manage lane utilization and monitor vehicle speeds in real-time. By capturing high-resolution video footage of traffic conditions and analyzing this data, the system can make informed decisions that improve traffic distribution across lanes. The expected outcomes of implementing the ITLMS include a significant reduction in traffic congestion, shorter travel times, enhanced road safety, lower emissions, and fuel savings. Furthermore, this system aims to increase overall road capacity, ensuring a more efficient and sustainable urban transportation network. Ultimately, the ITLMS represents a modern solution to the growing problem of urban traffic congestion
Approach To the Patient with COVID-19 With High-Fidelity Simulation Education
Authors: DOĞU ÖZLEM , BOZKURT RAMAZAN
Published: December 2024

ÖZET
Giriş: Simülasyona dayalı öğrenme, hemşirelik eğitiminde
yaygın bir şekilde kullanılmaktadır ve simülasyona dayalı eğitim ile
hemşirelik öğrencilerinin birçok psikomotor becerilerinin geliştirilerek
kaygı düzeylerinin azaltılmasında yardımcı olabilir. Bu çalışma,
pandemi döneminde hemşirelik birinci sınıf öğrencilerine senaryo
tabanlı simülasyon eğitimi ile kişisel koruyucu ekipman kullanımının
COVID-19 hastalarına yönelik korku, memnuniyet ve beceri
durumlarına etkisini incelemek amacıyla planlanmıştır.
Yöntem: Bu çalışma randomize, kontrollü bir deneysel tasarım
yapısına sahiptir. Müdahale grubuna (n=26) senaryo tabanlı
simülasyon eğitimi, kontrol grubuna (n=26) ise rutin eğitim verilmiştir.
Çalışmanın verileri Birey Tanılama Formu, İşlem Basamakları Kontrol
Listesi, Görsel Analog Skala memnuniyet ve COVID-19 Korkusu
Ölçeği kullanılarak toplanmıştır.
Bulgular: Müdahale ve kontrol gruplarının ortalama kontrol listesi
puanları 13,76±1,60 ve 10,73±2,21’dir. Müdahale grubunun Görsel
Analog Skala Memnuniyet ve kontrol listesi puanı kontrol grubundan
daha yüksek yüksek olduğu ve istatiksel olarak anlamlı farklılık
bulunduğu saptanmıştır. COVID-19 Korkusu Ölçeği puan ortalaması
ile gruplar arasında istatiksel olarak anlamlı fark bulunmamıştır.
Sonuç: Senaryo tabanlı simülasyon eğitimi alan hemşirelik
öğrencilerinin memnuniyet ve kontrol listesi puan ortalamaları daha
yüksek bulunmuştur. Senaryo temelli eğitimin pandemi sürecinde
eğitim gereksinimlerini etkin bir şekilde karşıladığı sonucuna
varılmıştır.
Anahtar kelimeler:
Insegurança alimentar e políticas públicas de alimentação e nutrição no Brasil
Authors: Aquino Nathalia Barbosa de , Souza Nathália Paula de , Silva Catarine Santos da , Tavares Fernanda Cristina de Lima Pinto , Lira Pedro Israel Cabral de , Oliveira Juliana Souza
Published: December 2024

O objetivo deste trabalho é analisar a relação entre a insegurança alimentar no Brasil durante a pandemia da Covid-19 e os ambientes alimentares, considerando as dinâmicas socioeconômicas locais e as políticas públicas que influenciam o acesso e a disponibilidade de alimentos. Este texto foi desenvolvido na forma de um ensaio, sustentado por uma seleção bibliográfica relevante e tendo o intuito de fomentar a reflexão sobre o tema proposto. O ponto de partida deste trabalho concentrou-se no cenário político e social brasileiro durante a pandemia, avaliando decisões governamentais e o contexto de saúde pública. Em seguida, foram discutidos os motivos que destacam a importância de políticas públicas contínuas de alimentação e nutrição, visando assegurar a autonomia nas escolhas alimentares e a garantia do Direito Humano à Alimentação Adequada (DHAA) a partir do ambiente alimentar. Também foi demonstrado que a pandemia da Covid-19 intensificou substancialmente a insegurança alimentar e nutricional no Brasil, especialmente nas populações mais vulnerabilizadas do país, e que a suspensão de várias atividades comerciais, como as feiras livres e os serviços de alimentação, juntamente com a fragilidade das políticas públicas, incluindo o Programa de Aquisição de Alimentos (PAA), contribuíram para dificultar o acesso da população a alimentos adequados e para reduzir a disponibilidade destes. Assim, este ensaio sugere a importância de novas pesquisas e debates para se continuar refletindo sobre os ambientes alimentares e sobre a vulnerabilidade alimentar no Brasil — especialmente diante dos desafios desvelados pela pandemia.
Implementation Of Ship Certification Inspection By KSOP Class I Banten
Authors: Pabian Dwi Aura , Nurul Muharani  , Alivia Najwa  , Salsa Amalia  , Sonya Ritta Sitinjak  , Alva Bagus PrihadhiLahagu  , Syfia Fajar Maulani  , Rubby Rahman Tsani
Published: November 2024

In the waters of Banten, there are still many fishing vessels that should be required to have a certificate but do not have a certificate and have carried out shipping activities, the shipping activities carried out are illegal because they do not have a sailing permit, To get a sailing permit the ship owner must have a ship certificate. Therefore, the purpose of the study is to find out the implementation of ship inspection activities by marine inspectors at the Banten Class I Port Authority and Municipal Office, in order to find out what causes ships that do not have certificates. This study uses a descriptive qualitative method, as well as an interview method to obtain primary data through direct questions and answers with KSOP employees, and uses secondary data in the form of Ship Inspection SOPs and Study Literature. By increasing socialization about the importance of ship certification to ship owners through seminars, training, or socialization. KSOP can also expand information services through websites and call centers to make it easier for ship owners in the certification process.
The Government Policy with its Historical Background Through the Effort to Prevent the Jobless of Timor-Leste in Providing Job Management Opportunities in the State and Foreign Countries (A Qualitative and Quantitative Mixed Method Research Analysis on Re
Authors: João da Silva  , Asep Sunandar
Published: November 2024

Abstract: The research study with entitled is about the Government Policy with its State Historical Background through the effort to prevent the jobless of Timor-Leste in providing job Management opportunities in the state and foreign countries.” The objective of this research is to identify and search on the historical and economical background of the state in providing job opportunities to young people are employed in internal and foreign countries to fix their family’s economic conditions to support the state in reducing the unemployment and poverty in the country itself as a way to settle down the problems and obtain the solution. About this, the government of Timor-Leste has created a bilateral and multilateral cooperation agreement in the country through signing the mutual of understanding (MOU) with the foreign company’s organization in abroad. The economic problems and other matters are settled with the effort hard of the state’s government by providing funds to minimize and reduce the poverty and the economic problems of the living people in the state in the current day and the future. The method of this study is qualitative and quantitative mixed methods, observing, paraphrasing, and permutation in library research through collecting the facts by using online libraries, software, and hard book references. Some of the data files presented in this writing to complete this analytical research. The finding of this research is the jobless of the country are mostly employed by the government through mutual cooperation through bilateral and multilateral cooperation to reduce the unemployment in the internal country and abroad. From the total population are not finalized their studies in the school 30,7% and from the above population, 16,8% do their learning in the higher education level. Amongst the young between 14-24 years old do not access the education, unemployed, and training and it is hard for them to get the job competition. The total labor forces in 2009, there are 430,200 people in East Timor and the unemployment are 18% since 2010.
Bodeča žica in reka Kolpa: presečišča zgodovine in sodobnosti
Authors: Hajzler Saša
Published: December 2024

This article presents empirical fragments that point to ways in which a more comprehensive set of sources can illuminate the range of interactions that materialize borders, beyond their strictly administrative or theoretical understanding. The article specifically examines transformations of the Slovenian southern border from 2015 to the present, focusing on its properties and functions in relation to irregular migration. The analysis takes into account not only the physical border, including fences, barbed wire and other border technologies, but also considers the role of state apparatus through its established institutes of bordering, such as mixed patrols, through its administrative-legal aspects, such as bilateral agreements, and through the forced returns and consequential deaths at the border. The anatomy of the border is in this part analyzed as a historical and political tool of the EU project, by juxtaposing official institutional discourse on one side, and the discourses of migrants, freedom of movement initiatives and border forensics on the other. This approach illuminates the complexity of contemporary transformations of Slovenia's southern border in the context of migration, elaborating the junction points between different political languages coming from »above« and »below« at the time of the analyzed period of time. By integrating perspectives "from below", this article calls for consideration of a broader methodological apparatus and perspectives which could bring new insights for border historiography.
İhsan Abdülkuddûs’ün Bir Filistin Hikâyesi “Dava Cadillac’ın İçinde Uyuyor”
Authors: Yazıcı Hüseyin
Published: November 2024

İhsan Abdülkuddûs (ö. 1990) Arap edebiyatının önemli bir figürüdür. Yazmış olduğu eserlerin okur tarafından ciddi anlamda kabulü, bu engin edebiyat içinde ağır eleştiriler almış olsa da onu önemli bir yere oturtmuştur. 14 Mayıs 1948 yılında İsrail Devleti’nin kuruluşundan günümüze kadar hiçbir zaman durulmayan Filistin meselesi/davası ile ilgili olarak bu meseleyi/davayı özümseyen bazı Arap yazarların yapabildikleri tek şey, farklı türdeki eserlerinde bu durumu dile getirmek olmuştur. Bunlardan birisi de zikri geçen Mısırlı yazar İhsan Abdülkuddûs’tür. 1967 yılında cereyan eden Arap-İsrail Savaşı’nın vermiş olduğu ağır yenilgi esnasında İhsan Abdülkuddûs tarafından kaleme alınan en-Nisâ’ lehunne Esnân Beyzâ (Kadınların Beyaz Dişleri Var) adlı koleksiyonda yer alan “Dava Cadillac’ın İçinde Uyuyor” adlı hikâyede Filistin sorununun edebî açıdan temsili ve bu temsilin daha çok Ğassân üzerinden yansıtılma biçimi ortaya konmuştur. Ayrıca eserdeki karakterlerin iç dünyaları, yaşadıkları çatışmalar ve Filistin meselesine olan duygusal bağları ele alınmıştır. Çalışmada, yazarın “Dava Cadillac’ın İçinde Uyuyor” adlı öyküsü esas alınarak karakter analizi yapılmış ayrıca bireyin kimlik arayışı, vatan hasreti ve kişisel idealler ile dış dünyanın gerçekleri arasındaki çatışmaları incelenmiştir. Öncelikle yazar hakkında ana hatları ile bilgi verilmiş, Filistin meselesinin kısa bir değerlendirilmesi yapılmış daha sonra da hikâyenin özeti verilerek tahliline geçilmiştir. Zaman zaman da Türk edebiyatı ile bazı mukayeselerde bulunulmuştur.
The impact of quasi-biennial oscillation (QBO) disruptions on diurnal tides over the low- and mid-latitude mesosphere and lower thermosphere (MLT) region observed by a meteor radar chain
Authors: Wang Jianyuan , Li Na , Yi Wen , Xue Xianghui , Reid Iain M. , Wu Jianfei , Ye Hailun , Li Jian , Ding Zonghua , Chen Jinsong , Li Guozhu , Tian Yaoyu , Chang Boyuan , Wu Jiajing , Zhao Lei
Published: December 2024

Abstract. A quasi-biennial oscillation (QBO) disruption is a very rare phenomenon in which QBO westward wind is temporarily interrupted by the occurrence of a band of westward wind in the tropical stratosphere. This phenomenon is important as it could greatly affect the global atmospheric circulation, especially in the mesosphere. Past observational and modelling studies have shown the QBO varying mesospheric diurnal tide, but the mechanism is still not fully understood. In this study, we report on the strong response of mesospheric diurnal tides to the two QBO disruptions that occurred in 2015–2016 and 2019–2020 and their possible mechanisms. The diurnal tidal winds are observed by a meteor radar chain, consisting of meteor radars located at Kunming (25.6° N, 103.8° E), Wuhan (30.5° N, 114.2° E), Mengcheng (33.4° N, 116.5° E), Beijing (40.3° N, 116.2° E), and Mohe (53.5° N, 122.3° E) in China. These observations provide clear evidence that mesospheric diurnal tides are unusually weakened (by ∼ −6 m s−1) during these QBO disruptions, over Kunming, Wuhan, Mengcheng, and Beijing. Using the Specific Dynamics version of the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (SD-WACCM-X) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) dataset, the analysis indicates that the QBO wind affects mid-latitude mesospheric diurnal tides by modulating both the solar radiative absorption by subtropical stratospheric ozone (∼ 5 to 0.5 hPa) and the tidal–gravity wave interaction in the mesosphere (∼ 60 to 100 km). Thus, these unexpected QBO disruptions provide an opportunity to better understand the coupling between climate change and middle-atmospheric dynamics.
Towards Gridded Nighttime Aerosol Optical Thickness Retrievals Using VIIRS Day/Night Band Observations Over Regions with Artificial Light Sources
Authors: Zhang Jianglong , Reid Jeffrey S. , Sorenson Blake , Miller Steven D. , Román Miguel O. , Wang Zhuosen , Spurr Robert J. D. , Jaker Shawn , Eck Thomas F. , Rubin Juli I.
Published: December 2024

Abstract. Using observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB), we examined the feasibility of developing a gridded nighttime aerosol optical thickness (AOT) data set based on the spatial derivative of measured top-of-atmosphere attenuated upwelling artificial lights at night (ALAN) over the US, Middle-East and Indian Subcontinent regions for 2017. We also studied the potential of using NASA’s standard operational Black Marble nighttime lights product suite (VNP46) for estimating the spatial derivatives of surface artificial light emissions, that is one of the key lower boundary conditions for the retrieval process. Sensitivity of nighttime aerosol retrievals to observing conditions and different methods of estimating the spatial derivative of surface artificial light emissions were also explored. Root-Mean-Square Errors (RMSEs) of ~ ~0.15 and ~0.18 and correlations of ~0.8 and ~0.6 were found between VIIRS nighttime AOT and Aerosol Robotic Network (AERONET) nighttime and daytime data, respectively, suggesting that the proposed gridded nighttime AOT retrievals have reasonable skill levels for potential data assimilation, air quality and climate studies of significant events. We also found that NASA Black Marble products can be used to estimate the spatial derivative of surface artificial light emissions for nighttime AOT retrievals over regions that are not frequently contaminated by aerosol plumes, such as the USA. This study demonstrated the feasibility of constructing a gridded nighttime AOT data, using artificial lights, for monitoring of nighttime aerosol events over large spatial and temporal domains. Given the deployment of VIIRS instruments (currently in orbit and forthcoming) on board the NOAA Joint Polar Satellite System series satellites, this study can be viewed as a precursor for gridded nighttime AOT retrievals at both regional and global scales in the future. We also show that the use of the NASA Black Marble products, which would greatly save processing time of this method, is challenging over regions with frequent aerosol pollution such as the Indian Subcontinent and further exploration is required.
A fast surrogate model for 3D Earth glacial isostatic adjustment using Tensorflow (v2.8.0) artificial neural networks
Authors: Love Ryan , Milne Glenn A. , Ajourlou Parviz , Parang Soran , Tarasov Lev , Latychev Konstantin
Published: December 2024

Abstract. Models of glacial isostatic adjustment (GIA) play a central role in the interpretation of various geologic and geodetic data to understand and simulate past and future changes in ice sheets and sea level, as well as to infer rheological properties of the deep Earth. During the past few decades, a major advance has been the development of models that include 3D Earth structure, as opposed to 1D spherically symmetric (SS) structure. However, a major limitation in employing 3D GIA models is their high computational expense. As such, we have developed a method using artificial neural networks (ANNs) and the Tensorflow library to predict the influence of 3D Earth models with the goal of more affordably exploring the parameter space of these models, specifically the radial (1D) viscosity profile to which the lateral variations are added. Our goal is to test whether the use of an ANN to produce a fast surrogate model can accurately predict the difference in GIA model outputs (i.e., relative sea level (RSL) and uplift rates) for the 3D case relative to the SS case. If so, the surrogate model can be used with a computationally efficient SS (Earth) GIA model to generate output that replicates that from a 3D (Earth) GIA model. Evaluation of the surrogate model performance for deglacial RSL indicates that it is able to provide useful estimates of this field throughout the parameter space when trained on only ≈15 % (≈50) of the parameter vectors considered (330 in total). We applied the surrogate model in a model–data comparison exercise using RSL data distributed along the North American coasts from the Canadian Arctic to the US Gulf Coast. We found that the surrogate model is able to successfully reproduce the model–data misfit values such that the region of minimum misfit either generally overlaps the 3D GIA model results or is within two increments of the radial viscosity model parameter space (defined here as lithosphere thickness, upper-mantle viscosity, and lower-mantle viscosity). The surrogate model can, therefore, be used to accurately explore this aspect of the 3D Earth model parameter space. In summary, this work demonstrates the utility of machine learning in 3D Earth GIA modelling, and so future work to expand on this initial proof-of-concept analysis is warranted.
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Authors: Kang Eui-Jong , Sohn Byung-Ju , Kim Sang-Woo , Kim Wonho , Kwon Young-Cheol , Kim Seung-Bum , Chun Hyoung-Wook , Liu Chao
Published: December 2024

Abstract. Sea surface temperature (SST) is a crucial parameter in climate, weather, and ocean sciences due to its decisive role in ocean–atmosphere interactions. Identifying errors in the prognostic scheme used by the current European Centre for Medium-range Weather Forecasts (ECMWF) model for predicting the diurnal variation in ocean skin temperature led to a revisit and revision of the ocean mixed layer (OML) model. Validation of the revised model was conducted by comparing simulated temperatures at the sub-skin level and 1 m depth with observations from shipborne infrared measurements and buoys. These comparisons revealed a strong correlation, with an absolute mean deviation of less than 0.1 K and a standard deviation under 0.5 K, which are found to be comparable to errors in satellite observations of SST. Given that these results are derived from the same model simulations, the error statistics for the simulated skin temperature and its diurnal variation should have the same degree of accuracy. Furthermore, the simulation results closely align with anticipated solar radiation distributions, whereas ERA5 ocean skin temperature shows a significant lack of alignment with solar radiation. Consequently, the revised OML model shows promising potential for improving the simulation of diurnal SST variations in weather and climate models.
The Four Types of Stablecoins: A Comparative Analysis
Authors: Hafner Matthias , Henriques Pereira Marco , Dietl Helmut , Beccuti Juan
Published: December 2024

Stablecoins have gained significant popularity recently, with their market cap rising to over $180 billion. However, recent events have raised concerns about their stability. In this paper, we classify stablecoins into four types based on the source and management of collateral and investigate the stability of each type under different conditions. We highlight each type’s potential instabilities and underlying tradeoffs using agent-based simulations. The results emphasize the importance of carefully evaluating the origin of a stablecoin’s collateral and its collateral management mechanism to ensure stability and minimize risks. Enhanced understanding of stablecoins should be informative to regulators, policymakers, and investors alike.
Dissecting the NFT Market: Implications of Creation Methods on Trading Behavior
Authors: Beikzadeh Pegah , Mosharraf Maedeh
Published: December 2024

Amidst the frenzy surrounding Non-Fungible Tokens (NFTs) in 2021, the concept of digital assets and trading was redefined. Although the initial hype may have subsided, NFTs continue to drive innovation in ownership, with substantial revenue streams flowing through the market. This transformative shift underscores the importance of discerning the factors that shape this ecosystem. This paper delves into the intricate dynamics of the NFT market, particularly focusing on the impact of creation methods—whether hand-drawn or artificial intelligence (AI)-generated—on market behavior. In a comprehensive analysis of the NFT market, we have analyzed a vast dataset comprising 1,478,556 transactions of NFT art from the OpenSea marketplace in 2023 to explore correlations and patterns between key transactional features. Furthermore, we employed regression models to predict the sales of an NFT and classification models to distinguish between hand-drawn and AI-generated NFTs. Finally, by comparing different machine learning models, we identified the most appropriate model for analyzing the market, considering the non-linear relationships and complex nature of the NFT market. Overall, the results provided in this research can lead to making more informed decisions regarding investment, creation, and trading.
Efektivitas Media dan Teknologi Berbasis Aplikasi dalam Pembelajaran: Sebuah Tinjauan Literatur
Authors: Dedi Harianto  , Nuraisyiah  , Hasyima Sitti Hajerah , Azisa Fajriani
Published: December 2024

Perkembangan kemajuan teknologi informasi dan komunikasi, penggunaan media dan teknologi berbasis aplikasi dalam pembelajaran semakin penting dan menjadi kebutuhan untuk memudahkan kegiatan pembelajaran. Berbagai literatur tentang penggunaan aplikasi dalam proses pembelajaran dan bagaimana hal itu berdampak pada efektivitas belajar dikaji dalam penelitian ini. Pada penelitian ini menggunakan metodologi deskriptif kualitatif berbasis tinjauan literatur. Penelitian ini berfokus pada penelitian sebelumnya tentang penggunaan aplikasi pembelajaran di berbagai jenjang pendidikan. Hasil tinjauan menunjukkan bahwa penggunaan aplikasi dapat meningkatkan keterlibatan siswa yang mendukung pembelajaran mandiri, kemampuan tenaga pengajar dalam membuat materi pembelajaran lebih mudah diakses. Namun, hal-hal seperti kesiapan tenaga pendidik untuk terus meningkatkan kemampuannya dalam menggunakan teknologi, ketersediaan infrastruktur teknologi, dan desain aplikasi pembelajaran yang mudah digunakan juga memengaruhi keberhasilan implementasi.
Smaller Formats of Volleyball Lead to Greater Improvements in Lower Limb Strength and Power, As Well As Reductions in Landing Forces: A Randomized Controlled Study in Girls
Authors: Duan YuQing , Wang Li , Liu Qi , Huang Wanyu
Published: December 2024

The purpose of this study was to compare the adaptations in muscular strength, power, and landing forces of young female volleyball players enrolled in two experimental programs: one using smaller formats of the game (SFG) and the other using larger formats of the game (LFG), with a third group serving as a control. This study employed a randomized controlled design, with an 8-week intervention period and pre- and post-intervention evaluations. Fifty-six trained/developmental participants (age: 14.7 ± 0.5 years) voluntarily participated in this study. Each experimental group received additional training twice a week. The SFG group participated in 2v2 and 3v3 formats on smaller courts (covering 2/6 of the court's available zones) with a regular net, while the LFG group played in 4v4 and 5v5 formats on larger courts (covering 4/6 of the court's available zones). Assessments were conducted using force platforms and included the following tests: (i) isometric mid-thigh pull test (IMTP), measuring peak force; (ii) squat jump test (SJ), measuring peak force; (iii) countermovement jump test (CMJ), measuring peak power and landing force; and (iv) drop jump test (DJT), measuring the reactive strength index. Significant differences emerged post-intervention across all outcomes (p < 0.05). The SFG exhibited significantly greater IMTP peak force compared to both the LFG (p = 0.012) and control groups (p = 0.035). Additionally, the SFG showed significantly greater SJ peak force than the LFG (p = 0.036) and control groups (p = 0.023). Regarding CMJ peak power, significantly higher values were observed in the SFG compared to the LFG (p = 0.042) and control groups (p = 0.046). Moreover, the SFG had significantly lower CMJ peak landing force than both the LFG (p = 0.049) and control groups (p = 0.046). Finally, RSI was significantly higher in the SFG than in the LFG (p = 0.046) and control groups (p = 0.036). This study highlights the significant benefits of incorporating 2v2 and 3v3 SFG formats to enhance muscular strength, power, and landing forces in young female volleyball players, contrasting with less effective outcomes observed with 4v4 and 5v5 LFG formats, suggesting potential neuromuscular advantages crucial for improving volleyball performance.
Antifeminismo en la red. Un estudio de la estructura ideológica de la networking masculina
Authors: Del Pino Díaz David
Published: December 2024

Introducción: Se investiga la estructura ideológica de la networking masculina en la que afloran discursos de odio y violencia contra las mujeres. Objetivos y metodología: mediante una metodología de naturaleza teórica, desde la hermenéutica y crítica de textos científicos, se identifica la lógica política, histórica y cultural que está detrás de emplear una retórica contracultural dentro de las subculturas masculinas que componen la manosfera. Asimismo, se profundiza en la crisis del ideal de la masculinidad como telón de fondo de la creciente reacción antifeminista en la red. Resultados: el uso de un lenguaje políticamente incorrecto, el empleo de una retórica contracultural, el odio visceral contra las mujeres y la crisis del ideal de la masculinidad domina la estructura ideológica de la networking masculina. Conclusiones: la evolución de la networking masculina presenta las características de una crisis del ideal de la masculinidad en consonancia con las transformaciones estructurales y superestructurales de las últimas décadas. El paso de la subcultura Pick Up Artist (PUA) a la hegemonía de los Incels muestra claramente este tránsito.
The Progression of Natural Language Processing: A Journey from Syntax Parsing to Deep Sentiment Analysis
Authors: Kosaraju Deekshitha
Published: November 2024

The field of Natural Language Processing (NLP) has made progress moving beyond basic syntax analysis to delve into complex sentiment understanding and more. This significant evolution has empowered machines not to analyze and comprehend language structures but also to interpret and respond to the emotional nuances and contexts conveyed by humans. The evolution of NLP has seen a series of innovations that have bridged the gap between human language expression and artificial intelligence enabling interactions between humans and computers. This piece explores the milestones in NLP development the technologies driving its progress and its practical applications across various industries. By highlighting NLPs capabilities, such as automating customer service aiding real time decision making and enabling personalized communication this article emphasizes NLPs crucial role, in pushing the boundaries of technology and society forward.

Keywords: Natural Language Processing, Syntax Parsing, Sentiment Analysis, Machine Learning, AI Applications
Efficacy of Legal Aid: Bridging the Justice Gap
Authors: Mukherjee Anubhab
Published: November 2024

The legal resource is the supply of help to those who are not able to come up with the money for felony illustration and get admission to the courtroom docket system. Ensuring that legal aid is available for everyone especially to the economically weaker sections of the society where this access to justice is so important. This paper investigates the judicial attitude and role towards legal aid, with a special but not exclusive focus on its elevation to a constitutional right under Article 21 of the Indian Constitution through adjudication. In fact, Justice P.N. Bhagwati defined legal aid as “not merely a repaint of law in favour of the strong.” Thus, it prospers on equal justice. As per him, legal aid is one type of emergency call for the help of law. Moreover, legal aid involves a broader concept of social justice, which affords a societal climate in which equality of status and opportunity will be secured to all, thus making the power of the judiciary accessible and in everyone’s grasp during the critical point at which the citizen must assert his rights.

Keywords: Legal Aid, Unbiased Justice System, Law, Constitutional Provisions, Other Legal Provisions
Digital Tourism Communication to Strengthen the Attractiveness of Destinations
Authors: Imran Maharani
Published: November 2024

Digital transformation presents new opportunities and challenges in the tourism sector. With digital tourism communication, the tourism sector can now leverage digital platforms to improve operational efficiency and expand marketing reach. This study aims to describe digital tourism communication strategy to strengthen the attractiveness of destinations. The research method used in this study is a literature study method. The result of this study is that the government and private sector can enhance the attractiveness of tourist destinations by using digital tourism communication strategies such as creating inspirational content, collaborating with influencers, utilizing advanced technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), and managing online reputation and campaigns on social media to reach a wider audience and encourage tourist engagement.

Keywords: digital tourism communication, digital transformation, social media, virtual reality
AI-Driven Rehabilitation: Personalizing Cardiac Care Post-Diagnosis
Authors: Kosaraju Deekshitha
Published: November 2024

The integration of Artificial Intelligence (AI) into cardiac rehabilitation diagnosis goes beyond advancement; it marks a notable stride, towards personalized medical treatment. This groundbreaking approach harnesses AIs potential to develop custom rehabilitation plans designed to cater to the requirements of each patient. By utilizing a range of data sets that include detailed physiological parameters, comprehensive medical histories and real time monitoring results AI driven algorithms and machine learning methods carefully design treatment plans that greatly improve the effectiveness of rehabilitative treatment. Additionally, this approach does not enhance patient outcomes by optimizing therapeutic interventions but also significantly boosts the efficiency of resources within healthcare systems. This article explores the applications of AI in cardiac rehabilitation addressing complex issues offering sophisticated solutions showcasing its versatility highlighting its profound impact on patient care and outlining opportunities for future integration into standard clinical practices. Through an in-depth examination the review emphasizes AIs role, in enhancing the accuracy of cardiac care and promoting a proactive healthcare environment that prioritizes individualized patient well-being and preventive measures establishing a new benchmark in the field of cardiac rehabilitation.

Keywords: Artificial Intelligence, Cardiac Rehabilitation, Personalized Medicine, Machine Learning, Real-time Monitoring, Patient Outcomes.
Quantum Computing and Artificial Intelligence:
A Fusion Poised to Transform Technology
Authors: Kosaraju Deekshitha
Published: November 2024

The intersection of Quantum Computing and Artificial Intelligence (AI) signifies a moment in the advancement of computing technologies. While both technologies have individually made progress in their respective domains their combination is poised to redefine the limits of computational capabilities. This piece delves into the merger of quantum computing with AI promising not only to boost computational speeds but also to tackle intricate problems that current classical computing methods struggle to solve. We will explore how this integration is anticipated to drive progress across various sectors such as healthcare, potentially enabling quicker and more precise diagnostic systems; finance, capable of transforming risk evaluation and fraud detection; and cybersecurity, presenting opportunities for unbreakable encryption. The conversation extends to the effects on drug discovery, climate prediction and artificial general intelligence envisioning a future where quantum technologies exponentially enhance AIs capabilities. This summary sets the stage for an examination of how the amalgamation of quantum computing and AI could herald an era of technological innovation fundamentally reshaping our problem-solving approaches, for some of society’s most urgent issues.

Keywords: Quantum Computing, Artificial Intelligence, Super Artificial Intelligence, Quantum AI, Technology Transformation
The Role of AI and Machine Learning in the Future of Remote Education
Authors: Kosaraju Deekshitha
Published: November 2024

The fast development of Artificial Intelligence (AI) and machine learning (ML) technologies has had an influence, on different industries with education being one of the most changed. Incorporating AI and ML into education platforms has transformed conventional teaching and learning methods making personalized learning experiences easier automating administrative duties and improving the efficiency of educational delivery. This article delves into the role played by AI and ML in shaping the future of online education focusing on their practical applications, advantages, and the potential obstacles they may present. By examining implementations across different educational levels this research underscores how these technologies have the power to revolutionize education by making it more accessible, engaging, and efficient in an ever-evolving global environment. Additionally, it delves into the implications of these technologies such as their influence on educational equality, teacher responsibilities and the integration of data driven decision making, in designing curricula and teaching approaches. The discourse also touches upon considerations surrounding data usage in educational contexts to ensure that AI and ML contribute positively while upholding student privacy rights and fairness.

Keywords: Artificial Intelligence, Machine Learning, Remote Education, Personalized Learning, Educational Technology
The Effect of Statin in Managing Cholelithiasis:
A Systematic Review
Authors: Ginting Zulqadri
Published: November 2024

Introduction: Gallstone disease is a prevalent condition leading to numerous hospitalizations worldwide, with cholesterol gallstones comprising 80–90% of cases. While cholecystectomy remains the primary treatment, statins, known for reducing low-density lipoprotein cholesterol, may influence gallstone formation by altering biliary cholesterol levels. However, findings regarding their effectiveness in humans are inconsistent. This systematic review evaluates the role of statins in managing cholelithiasis.
Methods: A systematic review adhering to PRISMA guidelines included randomized controlled trials, cohort studies, and case-control studies examining statin use in adults without prior gallstone disease. Searches were conducted in Medline, Embase, and Cochrane Library. Data extraction and quality assessments were performed by two independent reviewers, resolving discrepancies by consensus.
Results: Among 1,007 references, eight studies involving 590,086 participants met inclusion criteria. Statin users, categorized by duration and usage status, exhibited a reduced risk of gallstone disease and cholecystectomy. Medium- and long-term statin users had the most significant protective effects, although findings varied due to differences in study designs, definitions of statin use, and gallstone outcomes.
Discussion: Statins demonstrated a potential protective role against gallstone formation and severity, consistent with previous meta-analyses. However, limitations, including observational study biases, variability in definitions, and confounding factors like lifestyle and comorbidities, necessitate cautious interpretation. Prospective studies are required to confirm these findings and address gaps such as the impact of statin discontinuation on gallstone recurrence.
Conclusion: Medium- and long-term statin use reduces gallstone and cholecystectomy risks, highlighting their potential in managing cholelithiasis. Future research should explore these effects further to refine clinical recommendations.

Keywords: Statin, cholelithiasis, gallstone disease
Chronic Back Pain as a Clinical Manifestation of Myofascial Pain Syndrome
Authors: Suryanata I Wayan , Widyadharma I Putu Eka
Published: November 2024

Introduction: Myofascial pain syndrome (MPS) is a condition of muscle or fascial pain, acute or chronic, involving sensory, motor or autonomic function, which is associated with myofascial trigger points (TrP). The pain caused by TrP can cause various symptoms of chronic diseases, such as tension-type headaches, migraines, temporomandibular pain, shoulder pain, or lower back pain. Back pain that persists for more than 12 years is called chronic back pain.
Case Report: A 24-year-old man came to the clinic with complaints of low back pain that had been intermittent for the previous month and felt worse for the last week. For 1 year, the patient has been diagnosed with non-specific back pain due to muscle stiffness. Since the last 1 week, the back pain has not improved, and the patient has begun to find it difficult to carry out activities such as sitting and squatting, and his hands cannot touch his feet when bending. The pain is said to be like pressure and radiates from the right buttock and back of the right thigh. The pain is aggravated if the patient stands and sits for a long time, the pain is reduced if the patient sleeps on his back. Complaints accompanied by tingling in the right buttock area spreading to the back of the right thigh. The Numeric Rating Scale (NRS) was found to be 7 out of 10 for headaches. The patient is then given dry needling therapy and then observed for 30 minutes. The patient's NRS after the procedure was 2 out of 10.
Discussion: In an epidemiological study, women experienced MPS more often than men, and it was found that the prevalence in women was 6 times higher than in men. Poor posture is a risk factor for chronic back pain. The diagnosis of myofascial pain is best made through a carefully analyzed pain history, which is confirmed by a consistent physical examination. TrP in the Piriformis muscle, Gluteus Minimus, and Gluteus Medius will cause symptoms of referred pain in the waist, buttocks, thighs and calves. MPS treatment in dry needling aims to restore functional ability by reducing pain caused by TrP.
Conclusion: Chronic back pain can be a syndromic manifestation of MPS. A complete history and careful physical examination are significant in diagnosing MPS, the treatment given can reduce pain, rigidity and increase mobility in patients with MPS.

Keywords: Chronic back pain, myofascial pain syndrome, myofascial trigger points.
Crossing Domains: The Role of Transfer Learning in Rapid AI Prototyping and Deployment
Authors: Kosaraju Deekshitha
Published: December 2024

In the changing world of technology today it's crucial for AI advancements to meet the increasing need for efficiency and top-notch performance. One major hurdle in developing and implementing AI solutions is the requirement, for sets of specialized data and computing power which often slows down progress. Conventional machine learning models usually demand starting from scratch with each project result in significant time and financial investments. Transfer learning is a game changer as it allows the sharing of expertise and pre-existing models from one area to assist with tasks in another domain seamlessly bridging the gap between them This method significantly lessens the reliance on datasets lowers computational requirements and speeds up the overall process of developing AI technologies In this piece we delve into how transfer learning is pivotal in transferring knowledge across domains especially beneficial, for quickly prototyping and deploying AI solutions In our analysis of different uses like natural language processing and medical diagnostics as well as computer vision applications we show how transfer learning boosts effectiveness in scenarios with limited data availability and speeds up the implementation of models while also allowing for better adjustments to pre trained models for particular tasks. Additionally, we explore the potential ahead for transfer learning to support the development of AI models that are easily customized for new tasks, in various fields rapidly. The growing access to trained models and the ongoing progress, in transfer learning methods are setting the stage for AI to be more user friendly and effective – enabling industries to drive innovation and roll out solutions at an unprecedented speed.

Keywords: Transfer Learning, AI Prototyping, AI Deployment, Pre-trained Models, Cross-Domain Applications, Machine Learning, Natural Language Processing, Computer Vision, Medical Imaging, Model Fine-tuning, Data Scarcity, Scalability in AI.
Integrating Reasoning with Learning: Neurosymbolic AI's Impact on NLP
Authors: Kosaraju Deekshitha
Published: November 2024

In the changing realm of Natural Language Processing (NLP) the rise of deep learning has brought about a notable advancement enabling machines to understand and produce human language with impressive accuracy. However, despite these strides current NLP systems encounter hurdles in tasks that demand intricate reasoning, nuanced comprehension, and the ability to draw conclusions from limited or unclear data. To tackle these challenges the emerging field of Neurosymbolic AI suggests a blend of approaches by combining the learning capabilities of deep neural networks with the precise rule-based reasoning of symbolic AI. This fusion aims to develop systems that do not excel in language processing tasks but also possess a deeper understanding resembling human cognition intuitively. By harnessing the strengths of both paradigms— learnings efficiency in handling extensive datasets and symbolic AIs skill in logical deduction—Neurosymbolic AI offers potential solutions to current barriers in NLP. It opens up possibilities for AI systems to undertake complex tasks like grasping metaphors detecting sarcasm and interpreting context sensitive language with finesse. This piece explores the principles of Neurosymbolic AI evaluates its influence, on NLP and discusses how it could reshape AIs analytical and decision-making frameworks in intricate real-world scenarios.

Keywords: Neurosymbolic AI, Natural Language Processing, Symbolic AI, Deep Learning, Machine Reasoning.