bluuebunny/crossref_metadata_2025 huggingface dataset:
A Workable Balance: Maternity Leave and Female success in the Workplace in Finland and the United States
Authors:   , Murphy Karey
Published: October 2024

The Family and Medical Leave Act was signed into law in 1993. FMLA, allowing for a few exceptions and criteria, provides unpaid leave for certain health conditions or for the birth or adoption of a child. While the United States offers a gender-neutral policy unlike most other nations, the leave is not required to be paid. This can have enormous impacts on not only a female’s decision to return to work after the birth of a child but her continued decision to pursue leadership roles within the workforce. The purpose of this study is to examine the relationship between female leadership and compare the paid and unpaid parental leave policies in the US and Finland. Additionally, this study will explore the relationships between additional barriers to female leadership and parental leave policies, as it exists within the two countries. Utilizing a qualitative research methodology the findings suggest that motherhood was found to lead to substantial changes in each woman’s life on both personal and professional level. Finnish women reported a more positive overall experience with motherhood, leadership and paid leave. Women in the United States however reported very different experience to include feelings of struggling, issues with 3 balancing work and childcare needs and a feeling of inadequacy and guilt when it came to taking time off after the birth of their children.
An Analysis Study on the Effect of the Use of Electronic Medical Records on the Effectiveness and Efficiency of Services at Public Health Centers (Puskesmas) in Indonesia: A Systematic Review
Authors: Nathan Daniel Setiawan , Rostiaty Erti
Published: October 2024

Background: EMR utilize electronic systems to store, manage, and share patient health information more efficiently and accurately. Given the importance of using EMR in improving the quality and efficiency of health services in Indonesia, this study aims to systematically review the existing evidence related to the effectiveness of EMR implementation on the effectiveness and efficiency of services at Puskesmas in Indonesia. This study follows the PRISMA 2020 standard, examining English literature from 2014 to 2024. The study excluded editorials, reviews from the same journal, and submissions without DOI. PubMed, SagePub, SpringerLink, and Google Scholar are used as literary sources. Results: Initially getting 360 articles from online databases (PubMed, SagePub, SpringerLink, and Google Scholar), eight relevant papers were selected after three rounds of screening for full-text analysis. Conclusion: Overall, the use of Electronic Medical Records at primary healthcare in Indonesia provides many advantages in terms of the effectiveness and efficiency of health services, especially in accelerating queue waiting time, registration, service in the police, and drug taking. However, to achieve optimal implementation, efforts to improve technology infrastructure, training for health workers, and good network management are needed to overcome technical obstacles and ensure smooth service flow at the primary healthcare.
Atenção primária no cuidado do pé diabético
Authors: Campos Rafael Camargo , Silva Francisco Vandeir Chaves da , Ferreira Barbara Andressa Silva , Filho José Eldo dos Santos , Gomes Ana Valquíria Santos e , Filho Welson Leal Duarte , Miranda Luja de Carvalho , Campelo Amanda de Oliveira , Marin Bruna Torrezan , Moraes Luís Gustavo de , Gama Karina Machado , Macêdo Karine Silva de , Medeiros Roberta de Lima , Pereira Nicoly , Santos Alice Priscila Amorim
Published: October 2024

O presente estudo revisou a influência do cuidado ao pé diabético a partir da atenção primária à saúde, utilizando uma abordagem de revisão integrativa. Foi definido como objetivo explorar a prevenção, diagnóstico precoce e manejo eficaz das complicações relacionadas ao pé diabético, visando reduzir a incidência de úlceras, infecções e amputações. A metodologia consistiu em uma revisão integrativa realizada nas bases de dados Scientific Electronic Library Online (SCIELO) e Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS), utilizando descritores em ciências da saúde relacionados à temática, como “diabetic foot”, “diabetes mellitus” e “primary health care”. Os resultados evidenciaram que fortalecer os cuidados na atenção primária e promover a conscientização sobre o pé diabético são passos essenciais para enfrentar esse desafio de saúde pública e melhorar a saúde dos indivíduos com diabetes, através de medidas preventivas, tratamento e abordagem.
Sistem Cerdas Rekomendasi Klinik Pratama di Kota Medan Berbasis Data Mining Dengan Metode K-Means Untuk Pasien BPJS dan Umum
Authors: Dedi Leman  , Elvin Syahrin
Published: October 2024

Pertumbuhan jumlah klinik di Kota Medan seiring dengan peningkatan jumlah penduduk memicu kebutuhan akan pelayanan kesehatan yang lebih efisien dan tepat sasaran. Namun, pasien sering kali mengalami kesulitan dalam memilih klinik yang sesuai dengan kebutuhan medis mereka, terutama bagi pengguna BPJS Kesehatan dan pasien umum. Hal ini disebabkan oleh minimnya informasi mengenai fasilitas, kualitas layanan, dan lokasi klinik yang optimal. Untuk mengatasi permasalahan ini, diperlukan sebuah Sistem Cerdas Rekomendasi Klinik Pratama yang mampu memberikan saran klinik berdasarkan profil dan kebutuhan pasien. Penelitian ini bertujuan untuk mengembangkan sistem rekomendasi klinik Pratama di Kota Medan berbasis data mining menggunakan metode K-Means Clustering. Metode K-Means digunakan untuk mengelompokkan klinik berdasarkan beberapa kriteria penting, seperti lokasi, jenis layanan, ketersediaan dokter, serta kemampuan klinik dalam menerima pasien BPJS maupun umum. Data pasien yang dianalisis meliputi riwayat medis, jarak tempat tinggal dari klinik, dan preferensi pelayanan. Hasil penelitian menunjukkan bahwa sistem rekomendasi berbasis K-Means dapat secara efektif mengelompokkan klinik dan memberikan rekomendasi yang relevan sesuai dengan profil pasien. Sistem ini tidak hanya memudahkan pasien dalam menentukan pilihan klinik yang tepat, tetapi juga membantu meningkatkan efisiensi distribusi pasien di Klinik Pratama di Kota Medan. Dengan penerapan sistem ini, diharapkan akses terhadap layanan kesehatan dapat lebih merata dan kualitas pelayanan meningkat, baik bagi pasien BPJS maupun umum.
HUBUNGAN PENGETAHUAN DAN MOTIVASI DENGAN KEPATUHAN MINUM OBAT PADA PASIEN TB PARUDI WILAYAH KERJA PUSKESMAS MATANI
Authors: Mamangkei Maria , Akay Tinny , Killing Maykel
Published: October 2024

Pengetahuan dan motivasi pasien TB akan berdampak pada kepatuhannya dalam melaksanakan program pengobatan. Semakin baik  pengetahuan seseorang maka akan semakin patuh dalam menjalankan pengobatan berkualitas dan semakin tinggi  motivasi seseorang maka akan semakin tinggi antuasiasme seseorang untuk mencapai kesembuhan. Jenis penelitian cross-sectional. Populasi pada penelitian ini adalah pasien dengan tubekulosis di wilayah kerja Puskesmas Matani dengan jumlah sampel sebanyak 177. Alat ukur yang digunakan berupa kuesioner, panduan wawancara dan form TB.01. Analisa data menggunakan analisa univariat dan bivariat dengan uji chi-square. Variabel independen adalah pengetahuan dan motivasi dan variabel dependen adalah kepatuhan minum obat anti tuberkulosis. Hasil menunjukan pengetahuan dengan kepatuhan minum obat menunjukan ada hubungan dengan (p value 0,000), motivasi dengan kepatuhan minum obat menunjukan hubungan (p value 0,000). Dengan signifikan 0.000 < a = 0.05, kesimpulan H1 diterima H2 ditolak. Perawat Puskesmas perlu melakukan pendidikan kesehatan mengenai TB dan memberikan motivasi pada pasien TB dengan menggunakan pendekatan terapeutik.
Artificial general intelligence in industry 4.0, 5.0, and society 5.0: Applications, opportunities, challenges, and future direction
Authors: Rane Jayesh , Kaya Ömer , Mallick Suraj Kumar , Rane Nitin Liladhar
Published: October 2024

Artificial General Intelligence (AGI) is a giant step ahead of narrow Artificial Intelligence (AI), and in a wonder-form, it can really revolutionize Industry 4.0, 5.0, and Society 5.0. For instance, in Industry 4.0, AGI will permit absolutely autonomous fabrication procedures, optimizing supply chains and personalizing products with efficiency like never before. While bringing about Industry 5.0, the integration of AGI with human intelligence foresees fostering a collaborative, sustainable industrial environment more oriented to human-centric innovation and well-being. Society 5.0 has a vision of harmoniously blending cyberspace and physical space but leaves out the role AGI could play in dealing with the complex societal challenges of healthcare, education, and urban management with its intelligent solution tailoring to the needs of individuals and communities. However, there are big challenges to the use of AGI in these domains, and there are ethical concerns. Key issues to be tackled include risks of autonomy without accountability, possible biases of decision-making, and socio-economic effects from large-scale automation. Above all, safety, transparency, and fairness in using AGI systems are important to avoid undesirable consequences. The ethical concerns of AGI, like privacy issues, possible misuse, and the requirement for solid regulatory frameworks, are getting urgent considering major steps we are taking toward such a highly evolved paradigm in society and industries.
Emerging trends and future directions in machine learning and deep learning architectures
Authors: Rane Nitin Liladhar , Mallick Suraj Kumar , Kaya Ömer , Rane Jayesh
Published: October 2024

The machine learning (ML) and deep learning (DL) field is quickly progressing due to improvements in computational power, data access, and algorithmic advancements. Recent developments indicate a significant change toward models that are more effective, adaptable, and easy to understand. Federated learning and edge computing are becoming more popular, allowing for decentralized data processing and improved privacy. Transformer architectures, originally made popular in natural language processing (NLP), are now being utilized in various applications, showing better effectiveness in image and time-series analysis. Moreover, the combination of quantum computing and ML offers the potential for exponential enhancements, which could lead to the resolution of problems that were previously unsolvable. Explainable AI (XAI) is becoming increasingly important, as it tackles the opaque characteristics of DL models, fostering confidence, and guaranteeing adherence to ethical guidelines. Moreover, the integration of ML with new technologies like Internet of Things (IoT), blockchain, and 5G is opening doors for creative uses in smart cities, healthcare, and autonomous systems. Researchers are investigating the use of hybrid models that combine symbolic AI with neural networks to improve reasoning abilities. The advancements in ML and DL architectures have the potential to tackle complex global issues and foster technological innovation at an unprecedented level, signaling a major step towards smarter and independent systems.
Applications of deep learning in healthcare, finance, agriculture, retail, energy, manufacturing, and transportation: A review
Authors: Rane Nitin Liladhar , Mallick Suraj Kumar , Kaya Ömer , Rane Jayesh
Published: October 2024

Deep Learning (DL), a branch of Artificial Intelligence (AI), has transformed many sectors by allowing groundbreaking progress in automation, predictive analytics, and smart decision-making. In the manufacturing industry, DL algorithms improve quality control by detecting defects in real-time and predicting maintenance needs, ultimately decreasing downtime and operational expenses. The healthcare industry uses DL to enhance patient outcomes and operational efficiency through improved diagnostics, personalized treatment plans, and accelerated drug discovery. Within the finance sector, DL models are utilized for detecting fraud, executing algorithmic trading, and managing risks, delivering strong and precise financial analysis. The retail industry uses DL for advanced recommendation systems, inventory management, and customer sentiment analysis, which boosts sales and enhances customer satisfaction. Self-driving cars in the automotive sector depend on DL for immediate image recognition and decision-making, leading to safer and more effective transportation. In addition, the telecommunications sector utilizes DL for improving network performance, forecasting analytics, and enhancing customer satisfaction. Applications in crop monitoring, yield prediction, and pest detection in the agriculture sector encourage sustainable farming practices. The advancement of DL will lead to innovation, increased efficiency, and transformative growth in different sectors.
Influence of digitalization on business and management: A review on artificial intelligence, blockchain, big data analytics, cloud computing, and internet of things
Authors: Rane Jayesh , Kaya Ömer , Mallick Suraj Kumar , Rane Nitin Liladhar
Published: October 2024

This systematic literature review aims to discuss how digital transformation and digitalization have influenced businesses and management by synthesizing the latest research trends and findings. The digital transformation, defined as the integration of digital technologies in all business areas, has reshaped conventional business models, operational processes, and value propositions. On the other side, digitalization is a subcategory of digital transformation, referring to a process for the conversion of information from an analogue into a digital format for the automation and optimization of business processes. The review brings out that digital transformation is no longer a technological pursuit but a strategic compulsion impacting organizational culture, leadership, and customer engagement. It is found from emerging trends that only those businesses which are using sophisticated technologies such as Artificial Intelligence, Blockchain, Big Data Analytics, Cloud Computing, and Internet of Things are now gaining competitive advantage through resilience, innovation, and customer-centricity. This research calls for a holistic approach to the integration of technology into the strategic vision with organizational change management for successful digital transformation.
Artificial Intelligence, Machine Learning, and Deep Learning for Sustainable Industry 5.0
Authors: Rane Nitin Liladhar , Kaya Ömer , Rane Jayesh
Published: October 2024

This book offers an insight into the applications of Artificial Intelligence (AI)- Machine Learning Algorithms and Deep Learning (DL) in Bigdata Analytics to Industry 4.0/5.0 and Society 5.0 with transformative power responsibly. It has delved into how these technologies are disrupting industries, fostering innovation, and solving age-old social problems-so that readers have an understanding of where the digital world is headed. These chapters cover the big picture subjects of using AI with Big data analytics aimed mostly at increasing industrial efficiency, healthcare optimization, retail transformation, construction industry transformation, autonomous vehicles development and environmental sustainability improvement. The book covers each of these technologies extensively applied to full chapters devoted to detail studies, methodologies and practical usages. One of the central concepts in the book is how we evolve from industry 4.0 to industry 5.0. Therefore, Industry 4.0 relies on the automation and data exchange in manufacturing technologies using cyber-physical systems, the Internet of Things and cloud computing route to intelligent factories. During this phase, it improves operational efficiency, predictive maintenance and real-time monitoring which lowers down time and other operating costs by considerable amount.
Artificial intelligence, machine learning, and deep learning applications in smart and sustainable industry transformation
Authors: Rane Nitin Liladhar , Kaya Ömer , Rane Jayesh
Published: October 2024

Continued integration of artificial intelligence (AI), machine learning (ML), and deep learning (DL) with modern, smart and sustainable industry domain provide a springboard to the Industry 4.0, Industry 5.0, and Society 5.0. These technologies revolutionize operational efficiency, sustainability, and innovation in many industries. Predictive maintenance scheduling powered by AI lowers downtime and reduces operation expenses. ML algorithms help effective demand forecasting and inventory management to make better use of available resources. Through the use of DL practices, robust quality control and defect identification for example are possible all due to the advancement in manufacturing product quality. In addition, AI-powered automation in manufacturing has the ability to scale and flex fuelling an agile industrial world. A smart grid with AI integration helps in bringing energy sustainability and efficiency by optimizing the energy distribution and pattern of consumption. AI and ML powered autonomous systems reinforce the systems that analyse data in real-time, that improve delivery performance and reduce carbon footprints in logistics and supply chain management. Moreover, the AI applications in the environmental monitoring, supports sustainability, which provides the actionable results in controlling the pollution and managing the resources. We see them working along with human individuals such as cobots which shows AI is supporting the human-centric design in Industry 5.0. The AI, ML and DL convergence has played a key role in the transformation towards the smart and sustainable industry and paved way for innovative as well as sustainable solution in the contemporary industrial scenario.
Artificial Intelligence and business intelligence to enhance Environmental, Social, and Governance (ESG) strategies: Internet of things, machine learning, and big data analytics in financial services and investment sectors
Authors: Rane Nitin Liladhar , Rane Jayesh , Paramesha Mallikarjuna
Published: October 2024

This research investigates the convergence of business intelligence (BI), artificial intelligence (AI), and sustainable development, with a focus on integrating the Internet of Things (IoT), machine learning (ML), and big data analytics. Initially, a co-occurrence analysis of keywords is conducted to identify significant themes and emerging trends within sustainable business practices. Subsequently, the study explores the application of AI in promoting business sustainability, illustrating how AI-powered solutions can enhance resource efficiency and reduce environmental footprints. This research investigates the transformative potential of artificial intelligence (AI) in enhancing Environmental, Social, and Governance (ESG) strategies, meeting the increasing demand for sustainable and ethical investment practices. Current trends indicate the rising use of AI in ESG due diligence, where sophisticated algorithms evaluate risks and opportunities related to environmental impact, social responsibility, and corporate governance practices.
Artificial intelligence, machine learning, and deep learning for sustainable and resilient supply chain and logistics management
Authors: Rane Nitin Liladhar , Desai Pravin , Rane Jayesh , Paramesha Mallikarjuna
Published: October 2024

Integrating artificial intelligence (AI) and machine learning (ML) into logistics and supply chain management is crucial for enhancing resilience and efficiency in today's unpredictable global market. This research explores the latest advancements and applications of AI and ML technologies that are transforming logistics and supply chain operations. AI-driven predictive analytics and real-time data processing have enabled companies to anticipate disruptions, optimize routes, and improve demand forecasting accuracy. Machine learning algorithms are essential in identifying patterns and anomalies within large datasets, supporting proactive decision-making and risk management. Current trends indicate a growing use of AI in autonomous delivery systems, which aim to reduce human error and improve delivery times. Additionally, AI-enhanced blockchain technology is becoming more popular for its ability to increase transparency and traceability across the supply chain, ensuring ethical sourcing and reducing fraud. AI in inventory management has significantly minimized overstocking and stockouts by providing accurate inventory levels and automating replenishment processes. Furthermore, AI-powered supply chain management systems are increasingly adopted to streamline supplier selection and performance evaluation, creating more resilient supplier networks.
Artificial intelligence and generative AI, such as ChatGPT, in transportation: Applications, technologies, challenges, and ethical considerations
Authors: Patil Dimple , Rane Nitin Liladhar , Rane Jayesh , Paramesha Mallikarjuna
Published: October 2024

The transportation industry is undergoing a major transformation driven by artificial intelligence (AI) and generative AI technologies, delivering new solutions to several traditional problems of the transport industry including congestion, security, and environmental concerns. This study examines key areas that highlight the transformative impact of AI on transportation: Features may include AI traffic control, predictive maintenance, optimal maintenance across infrastructures, self-driving automobiles, reinforcement of public transport systems, smart freight and shipping, natural language processing for customer care services, safety improvement through AI, and sustainability solutions. The incorporation of generative AI technologies, such as ChatGPT, encompasses a notable breakthrough particularly within urban environments. This review presents various uses of generative AI in transportation, that is, conversational agents for passengers, predictive maintenance, improved security measures, and efficient traffic control. Automated customer service chatbots help passengers book tickets online, select routes, and receive real-time information, increasing satisfaction. Predictive maintenance identifies potential breakdowns, enabling proactive corrective measures. However, it is important to note that AI incorporation presents ethical considerations, including fairness, data protection, privacy, and the prevention of biases.
Recovery rates of Eimeria oocysts from cattle feces by Wisconsin sugar flotation method
Authors: Tookhy Nazir Ahmad , Nakamura Yoshio , W Wakil Ahmad
Published: October 2024

The purpose of this study was to know the recovery rates of Eimeria oocysts through the course of flotation in sugar solution by WSFM. A fecal sample was collected from a calf infected with Eimeria bovis. Stage one of this study involved recovering oocysts from surface of sugar solution in a test tube with cover slips replaced at time points of 10, 20, 30, 40, 50, 60, 90 min, 2, 3, 4, 5, 6, 24, 48 hr., and 5 days. Oocysts were continuously detected up to 48 hr, with a linear increase in recovery counts for the first 2 hr and the average total count was 953 per gram. Recovery rates of oocysts were 8.1%, 13.3% and 16.4% at 10, 20 and 30 min, respectively. Stage 2 involved a set of 3 tubes. Cover slips were put at intervals of 10, 20 and 30 min on the first tube, while one cover slip was kept for 20 min on the second tube and one for 30 min on the third tube. No significant differences were detected in oocyst counts at 20 min between the first and second tubes, and at 30 min between the first and third tubes. Stage 3 involved the comparison of recovery rates at 10 min between sugar solutions with specific gravities of 1.200 and 1.266. There was no significant difference in oocyst counts between the two solutions. These results indicated that it takes time to recover all Eimeria oocysts from cattle fecal samples by WSFM, but total oocyst counts per gram can be estimated by counting oocysts detected at any sampling time points, such as 10, 20 or 30 min using one cover slip. No improvement of recovery rates was seen by using a higher concentrated sugar solution.
Keywords: WSFM, Oocyst, Cattle
Vital Pulp Therapy in Permanent Teeth
Authors: Taka Gulbahar , Qasemian Elham
Published: October 2024

This review article aimed to evaluate the outcome of vital pulp therapy procedures including indirect pulp capping (IDPC), direct pulp capping (DPC), miniature pulpotomy (MP), partial pulpotomy (PP) and full pulpotomy (FP) in permanent teeth even with signs of reversible and irreversible pulpitis. Instead of complete pulp tissue removal by pulpectomy, vital pulp therapy has been considered as an alternative approach. Articles published after 2000 were searched in PubMed and GoogleScholar online databases according to PRISMA guidelines. Forty articles were selected according to the inclusion and exclusion criteria. Eighty-five cases from case series and case report studies and also results of 20 clinical articles were included in this study. The success rate of partial and full pulpotomy in permanent teeth with signs of reversible and irreversible pulpitis was 98.8%. The success rate for both partial and full pulpotomies with mineral trioxide aggregate and calcium silicate-based cements in the current review of clinical studies was 84.6%-100% and 78.9%-100%. Partial and full pulpotomies demonstrated favourable outcomes and a high success rate in treating permanent teeth. So the vital pulp therapy procedures in permanent teeth with signs of pulpitis can be more successful, cost-effective and time-saving compared to traditional root canal treatment. However further well-designed studies with longer follow-up periods are required to validate these findings.
Privacy Risk in Recommender Systems
Authors: Rahmany Khadija , Hosseini Seyyed Kamran
Published: October 2024

Nowadays, recommender systems are mostly used in many online applications to filter information and help users in selecting their relevant requirements. It avoids users to become overwhelmed with the massive amount of possible options. To provide an efficient and accurate personalized recommendation, such systems require a large amount of data of user’s personal data which can provide by collecting privacy sensitive data from users such as ratings, consumption histories, and personal profiles. However, the privacy risks in gathering and processing personal data are often underestimated or ignored. The common privacy risks associated with recommender systems are the lack of adequate implementation of privacy protection principles. This review article aimed to evaluate the privacy risks in recommender systems. This paper discusses recommender systems and privacy concepts. Then, it gives an overview of the data that are used in recommender systems and examines the associated risks to data privacy. After that, the paper discusses relevant research areas for privacy-protection techniques and their applicability to recommender systems. The paper discussed various insights of user privacy, in both technical and non-technical environments, privacy design strategies, and privacy engineering approaches for developing a privacy-friendly recommender system. Finally, the paper concludes with a discussion on applying and combining different privacy-protection techniques. The results indicated that better user privacy can be achieved if privacy is considered by design and by default. Moreover, prediction accuracy is not limited by better user privacy when the privacy by architecture is considered alongside the privacy by design.
Keywords: Recommender systems, Privacy risk, Privacy design strategies.
Field evaluation of Trichogramma ostriniae (Hymenoptera: Trichogrammatidae) and T. brassicae as biocontrol agents of the European corn borer, Ostrinia nubilalis (Lepidoptera: Crambidae), in fresh market sweet corn
Authors: Etilé Elsa , Cabrera Paula , Boisclair Josée , Cormier Daniel , Todorova Silvia , Lucas Éric
Published: October 2024

The efficiency of two Trichogramma species as biocontrol agents against the European corn borer (ECB) Ostrinia nubilalis (Lepidoptera: Crambidae) was investigated under field conditions. Five inundative releases of Trichogramma ostriniae and T. brassicae (Hymenoptera: Trichogrammatidae) were done in sweet corn plots. Ostrinia nubilalis sentinel egg masses were placed on corn plants in order to compare the efficiency of the two Trichogramma species. The parasitism rate of O. nubilalis egg masses by T. ostriniae was 13% higher than egg masses parasitized by T. brassicae. Likewise, the percentage of eggs parasitized per mass by T. ostriniae was significantly higher following two of the five releases. Attacked egg masses showed an average of 29% of eggs parasitized by T. ostriniae, versus 14% of eggs parasitized by T. brassicae. The rate of parasitoid emergence from sentinel egg masses was also significantly higher for T. ostriniae than for T. brassicae. Damages to plants due to ECB did not differ significantly in presence of the two parasitoid species. However, plants in plots receiving parasitoids showed less damage than plants in control plots. Overall, T. ostriniae was clearly more efficient than T. brassicae to parasitized egg masses of O. nubilalis in sweet corn.
DISEÑO DE UNA INFRAESTRUCTURA DEL AGUA PARA UNA CIUDAD LLUVIOSA El paisaje húmedo de San José de la Mariquina
Authors:   , Brito Muranda Josefa
Published: October 2024

San José de la Mariquina, una ciudad pequeña de la región de Los Ríos y con una antigüedad mayor a la de Valdivia, y sin embargo, con un sistema urbano deficiente que se hace notar a lo largo de sus meses lluviosos. Las condiciones climáticas de esta ciudad ubicada en una geografía de valle, y posicionada entre el extenso río Cruces y el estero Quechuco, del cual deriva su nombre original, la dotan de una fertilidad favorecedora para diversas actividades económicas, al mismo tiempo que pone a prueba su infraestructura urbana ante los eventos (mal llamados desastres) del agua. Más específicamente, las inundaciones de los ríos y los anegamientos en las calles y veredas de San José, hacen evidente un sistema de drenaje obsoleto y la baja permeabilidad que existe al interior, resultando en una ciudad que ignora su propia naturaleza húmeda y esencialmente vinculada al agua, que la califican estructuralmente como un paisaje del agua vulnerable. Sumado a esto, la reciente expansión y densificación poblacional, ha extendido la trama urbana a una zona de riesgo hídrico, que no cuenta con equipamiento ni espacios verdes, contribuyendo a precarizar la rutina de los sanjosinos.La investigación pretende re-conocer el territorio de San José de la Mariquina, esta vez entendiéndolo como un paisaje del agua: una ciudad fundamentalmente ligada a los sistemas del agua y sus procesos. Finalmente, se hace una propuesta de arquitectura que actualice y fortalezca la infraestructura urbana de San José, con herramientas receptivas a los procesos naturales y ecosistémicos que la condicionan; al mismo tiempo que haciéndose cargo de las necesidades de la población del sector emergente.
Efficacy of Vasantik Vaman Karma (Therapeutic Emesis) on Oxidative Stress Markers in Healthy VolunteersA Pilot Randomised Controlled Study
Authors: Dandekar Pradnya D , Kuchewar Vaishali
Published: October 2024

Introduction: Vamana karma is a therapeutic emesis procedure recommended for maintaining health in healthy individuals. It is said to be conducted during the Vasant rutu (spring season) and is referred to as Vasantik Vaman. During this season, there is an aggravation of Kapha dosha, which can lead to various diseases. The bio-purification of the body in Vasant rutu through the Vaman procedure helps to detoxify and rejuvenate the body. To make this practice evidence-based, the present study was planned to evaluate the efficacy of Vamana karma, which is also considered a shodhana karma, in reducing oxidative stress. Aim: To compare the efficacy of Vasantik Vamana karma on Malondialdehyde (MDA) and Superoxide Dismutase (SOD) levels as markers of oxidative stress in healthy volunteers, compared to a non interventional group. Materials and Methods: The present randomised controlled study was conducted in the Department of Kriyasharir, Mahatma Gandhi Ayurved College, Hospital and Research Centre, under the auspices of Datta Meghe Institute of Higher Education University, Wardha, Maharashtra, India, from March 2023 to April 2023 during the Vasant rutu. A total of 58 healthy individuals aged between 20 years and 40 years were sensitised regarding the procedure and benefits of Vasantik Vamana karma. After sensitisation, 30 volunteers who provided written consent for participation in the study were enrolled, examined and randomly divided into two groups: Group A (non interventional) and Group B (interventional). Both groups were assessed on the 0th day and the 15th day for oxidative stress markers, specifically free radicals (MDA) and antioxidant (SOD) levels. Statistical analysis was done using descriptive and inferential statistics, including Student’s paired and unpaired t-tests. Results: The mean±Standard Deviation (SD) age of participants was 21.23±0.37 years, with participation almost equal from both genders. Before the intervention, SOD and MDA levels were similar in both the control and interventional groups. After the intervention of Vasantik Vamana karma, Group B showed an increase in SOD levels and a decrease in MDA levels, which were statistically highly significant according to the paired t-test (p-value≤0.001) in comparison to the non interventional group. In the non interventional group, p-value=0.951 for SOD levels and 0.551 for MDA levels by paired t-test, which were not significant. When both groups were compared using an unpaired test, at pre-intervention, both groups were at the same level, but after the intervention, statistically significant results were observed in Group B (p-value≤0.001). Conclusion: The present study concluded that Vasantik Vamana karma, as a bio-purification process, Vasantik Vamana karma has proven to be highly effective in detoxifying the body by reducing oxidative stress in healthy volunteers.
Assessing the Process of Written Informed Consent for Surgical Procedures among Inpatients: A Cross-sectional Study from a Tertiary Care Teaching Hospital in Southern India
Authors: Dinesh PV , Ismail Imaad Mohammed , Azeez Kahkashan
Published: October 2024

Introduction: Informed Consent (IC) is a decision-making process wherein patients are provided with all necessary information regarding treatment to make an uncoerced, educated choice. There are gaps in the implementation of the IC process that need to be identified and addressed. Aim: To estimate the proportion of patients/surrogates who read, understood, and signed the IC form before undergoing surgical procedures; to identify the different healthcare team members involved in explaining the IC form; to evaluate the extent to which different components of the IC form were explained to patients/surrogates; and to determine the influence of the IC form on surgical decision-making, and the overall satisfaction with the IC process. Materials and Methods: This cross-sectional study was conducted at a tertiary care hospital in the Dakshina Kannada District of Southern India from April 2020 to March 2021. It included 100 adult patients admitted to the postsurgical wards of general surgery, orthopaedics, obstetrics and gynaecology, otorhinolaryngology, and ophthalmology. Ethical clearance was obtained from the Institutional Ethics Committee. The parameters studied included socio-demographic variables, administration of the IC form, details on the person explaining the IC form along with its content, and the influence of the IC form on decisionmaking, as well as overall satisfaction with the IC process. Data were collected using a predesigned questionnaire and analysed using descriptive statistics in Statistical Package for the Social Sciences (SPSS) version 27.0. Categorical variables were presented as frequencies and proportions, whereas continuous variables were presented as means and standard deviations. Results: All participants received the IC form; however, only 21% read, understood, and signed it. The explanation of the IC form was given to 59% of the patients, with only 15% of these explanations provided by the treating surgeon. The components of the IC form, such as the surgical procedure and its benefits, were explained to the majority of the patients; however, the risks of the surgical procedure and alternative options were explained to only 53% and 7% of patients, respectively. The IC form had a minor influence on surgical decision-making for 61% of patients, and 43% expressed satisfaction with the IC process. Conclusion: The study revealed that the implementation of IC was inadequate. Surgeons should provide and explain the IC form well in advance, allowing time for patients to read, understand, and clarify their doubts. Hospital Ethics Committees need to enforce strict adherence to IC guidelines to ensure informed decision-making
A Note on Sum Formulae of Generalized Pentanacci Sequence
Authors: Soykan Yuksel , Tasdemir Erkan
Published: October 2024

During this paper, we first demonstrate the closed forms of sum formulae both \(\sum^\eta_{\lambda=0}\lambda z^\lambda A_\lambda\) and \(\sum^\eta_{\lambda=1}\lambda z^\lambda A_{-\lambda}\) for the generalized Pentanacci numbers. Then, we grant summation formulae for the sequences such as Pentanacci, Pentanacci-Lucas and other fifth-order iteration sequences.
Analysis of Growth Trends, Regional Variations and Productivity Metrics of Apple Cultivation in Himachal Pradesh, India
Authors: Raj Dev , Raina Aditi , Dev Kapil , Shubham
Published: October 2024

India has seen a spatial escalation on apple growth and it fostered the country’s economy and employment opportunities of the apple growing states. States of Jammu & Kashmir, Himachal Pradesh, Uttarakhand and Arunachal Pradesh are primarily known for apple production. Therefore, we worked on the secondary data on apple growth trends, its production from the different sources and analyzed it through growth rate, decomposition analysis and instability index techniques to quantify the production metrics and trend shift. Our findings reported that between1973–1974 to 2021–2022, there was an increase found in the global area, productivity and production of apples in Asia and India. The output of apples worldwide has found to be escalated at a compound annual growth rate of 2.51%, whereas, India has experienced a notable rise of 3.40 percent annually. The majority of the apple's area, output and productivity came from the Asian region, with growth rates of 3.38, 5.97, and 2.59 %, respectively. Furthermore, Worldwide scenario on apple cultivation reported that Poland had the highest relative instability in apple productivity (21.44%), followed by India (15.96%), China (12.53%), Turkey (11.18%) and USA (8.61%). Area yield effect was used to explain the rise in apple output in Asia, however, area expansion was found as the primary cause of increase in area under apple production. In Himachal Pradesh, Zone III has the greatest average yearly productivity (4.78%), followed by Zone II (3.35 %) and Zone IV (0.57%). In zones III and IV, the expansion of area (96.93%) and yields (85.13%) was the reason for the increase in apple production, however, in zone II, the yield effect (102.05%) was the only cause found for the increase in apple’s production.
Organoleptic Evaluation of Aonla (Emblica officinalis G.) Ready-To-Serve during Storage
Authors: Uikey Ashwini , Bhavna  , Gawade Pranali , Gupta Purvi , Thakre Pallavi , Uikey Mrinalini , Gurjar P.K.S. , Gurjar R.S.
Published: October 2024

A research experiment was conducted during the year 2019-20 and 2020-21 in the Fruit and Vegetable Processing Unit Laboratory, Department of Horticulture, College of Agriculture, Gwalior with seven different varieties of aonla viz., NA-4, NA-5, NA-6, NA-7, NA-10, Laxmi and Chakaiya for preparation of aonla RTS. Hence an attempt was made to standardized non-alcoholic based products viz., ready-to-serve with different varieties. 9 hedonic scale, out of there. From the findings, Laxmi and Chakaiya varieties were found superior with respect to colour, appearance, taste and aroma as well as flavor. The overall acceptability of processed items has been found to be significantly higher with storage periods of 30, 60, 90, and 120 days. To overcome present national and international prohibitions on the use of chemical food additives in food processing and preservation, research into biological and plant-derived food additives has considerably increased. With respect to the sensory evaluation of different aonla products was concerned, the Laxmi and Chakaiya varieties are found to be superior for the purpose of the processing industry.
Dew Point Characteristics at Synoptic Stations in Northern Benin
Authors: Kougbeagbede Hilaire , Onah Mamadou Waïdi , Houeto Arnaud , Hounvou Ferdinand
Published: October 2024

The dew point temperature is a very important parameter for hydro and agro-climatological research. This work studied the temporal variability of dew point temperature in Northern Benin. The dew point data comes from three synoptic stations in Northern Benin and covers the period from January 1980 to February 2019. After, correction and homogenization of the data, statistical methods are employed to analyze its structure, distribution, and temporal variability. The average of the dataset is 16.607°C with a standard deviation of 6.871 and a coefficient of variation of 0.414. The distribution is negatively skewed without extreme values, with an interquartile range of 10.284. The analysis by days of month indicates an irregular change in values at the beginning of month. The days of week show a minimum at the beginning and a maximum at the end of week. The analysis of dew point temperature data by months of the year shows a bell-shaped distribution with a plateau covering the months from May to September. The average dew point temperature has been increasing over the years. The data also describe a non-stationary periodic series approved by statistical tests. The absence of an inflection point in the data and in the trend means that the distribution is evolving and cyclical but not regular.
Drawback And Its Contributions To Exports: Analysis Of The Special Regime In Brazilian Companies In The Piracicaba/Sp Region
Authors: Piacente Fabrício José , Silva Vanessa De Cillos , Duarte Keila Borges , Albuguergue Robson G. De , Mauro Rafael Herman
Published: October 2024

Background: The drawback is a special customs regime designed to allow companies to exempt or defer taxes and fees on imported raw materials, inputs, packaging materials, and intermediate products that are used in the production of goods intended for export. This mechanism helps lower the cost of finished products, thereby enhancing their competitiveness in the global market. As an export incentive, the drawback plays a significant role in alleviating the tax burden on manufacturers. This study sought to explore the concept of drawback, its different modalities, and the key benefits it offers. Materials and Methods: The research methodology included a literature review and a case study involving two companies located in the Piracicaba/SP region that utilize this customs regime. Data was gathered through a questionnaire with open-ended questions directed at the Foreign Trade managers of these companies. Results: The findings reveal that the companies studied leverage the drawback regime to significantly reduce the prices of their export products, taking advantage of the tax benefits to lower costs and enhance product competitiveness Conclusion: Both theory and practice show that this special customs regime serves as a stimulus to imports and exports, thus enabling the growth of companies in the international market. It can be said that it is an important mechanism for promoting the internationalization process of companies.
The Phases Of Showalter’s Feminist Criticism Prefigured In Henrik Ibsen’s A Doll’s House
Authors: Augustine Dr Roger
Published: October 2024

Elaine Showalter (1941- ) is one of the most influential American literary critics and feminists who influenced feminist literary criticism by developing the concept and practice of gyno-criticism. She published A Literature of Their Own: British Women Novelists From Brontë to Lessing in 1977 and whose expanded edition came out in 1999. By and large this book explicates Showalter’s groundwork to revive the interest in long-forgotten women writers in British literature history. It was a monumental work, indeed a kind of rediscovery, mapping widely rather than mining deeply the territory of women’s writing. In a sense, feminist criticism came of age with this book. Showalter suggests that women themselves were slowly growing aware of their separateness from men and leaving a record of that awareness in their works. It is the growth of a collective selfconsciousness—the history of a distinct literary subculture—that A Literature of Their Own sets out to record. ‘Towards a Feminist Poetics’ (1979) is one of her well known essays that focused on the feminist literary criticism of the literature. In this essay, Showalter has rejected the inevitability of the male theories and male models by tracing the history of women’s literature in the present writing. 'Toward a Feminist Poetics' by Showalter also refers to the three phases of feminist literary criticism. The first phase is the feminine phase where women aimed to compete with male writers, and compared their craft with that of their male contemporaries. The second phase is the feminist phase where the critics focus on the injustices and wrongs done to women in literary texts, and reject the conventional roles of females. Finally, the female phase is independent of the dependency on and obsession with the male literature. It instead aims to focus on creating a female literary tradition that includes women's internal experiences and personal history. This theoretical literary presentation of Showalter can be dramatically viewed in the evolution of character Nora in A Doll’s House by Henrik Ibsen (1828 -1906). Ibsen was a Norwegian playwright and theatre director. He was one of the founders of modernism in theatre and often called “the father of realism” and the most influential playwright of the 19th century. A Doll’s House is a three acts play through which Ibsen challenged the stereotypical representation of women in literature with his female characters and remains a great contribution to feminist literature
Socio, Economic And Infrastructural Impact Of MGNREGA: Lessons From Two Decades Of Public Policy
Authors: Srinivasulu Dr. Vukkala
Published: October 2024

The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) also famously known as the National Rural Employment Guarantee Act (NREGA) is an Indian Laboure’s law which was exceedingly recognised as the social safety net in the post independent era. Since its inception 2005, the scheme has been providing employment to the rural households during vulnerable situations particularly in the lean seasons. The objectives of directive principle of state policy (DPSP) have been fulfilled through this scheme to establish economic and social democracy in the country. Over the years, the cumulative total exceeds 50 billion persondays since the program's inception. The present paper attempts analyse the MGNREGA’s impact on the different sectors