Study Analyses Research Articles

Supporting Sustainability of City Coastlines with Multi-Criteria Analysis Approach

City coastlines are places that enhance the wellbeing of citizens, promote sociality and enhance the city's aesthetic andquality of life due to the variety of activities, visuality and air supplement. It also contributes to urban sustainability with allthese aspects. (The Gonzales et al., 2023) study's multi-criteria analysis approach was applied to evaluate how sustainableurban coastlines are. The study covered two primary aspects of sustainability. These elements include the social activitiesand the environmental features of the coastal districts. With this method, it is aimed to reveal the daily use of the KarşıyakaCoastline and to examine the impact of these activities on the sustainability of there. Through the method, the contributionof city coastlines to the quality of urban life and city sustainability can be revealed with numerical data and it is expectedto guide in the site selection, design and implementation stages of new planning.

Ransomware Early Detection using Machine Learning Approach and Pre-Encryption Boundary Identification

The escalating ransomware threat has catalysed the formation of a sophisticated network of cybercriminal enterprises. Addressing this issue, our research provides a detailed exploration of the ransomware menace and an evaluation of contemporary detection methodologies. A successful ransomware attack leverages many factors: robust encryption methods that defy decryption, the anonymity of cyber currencies, and the widespread availability of ransomware kits that enable even inexperienced actors to launch attacks. Such dynamics have cultivated a niche for cybercriminal specialists in the digital underworld. In response to these challenges, our study proposes a detection framework based on machine learning, a domain where regression algorithms have gained popularity without yielding a definitive protective model. We employ API call analysis as the foundation to assess various machine learning classifiers' efficiency in identifying ransomware. The evaluation demonstrates that the Naive Bayes classifier underperforms due to suboptimal accuracy, making it unsuitable for this application. Conversely, Logistic Regression, with an AUC of 0.951, minimal training time, and substantial efficacy gains, emerges as a strong contender. The Decision Tree and Random Forest classifiers exhibit comparable proficiency; however, the Decision Tree's interpretability and Random Forest's computational swiftness present unique advantages. Superior still, SVM and Gradient Boosted Trees command the highest AUC and gains, albeit at the cost of increased training duration. Our findings affirm the pivotal role of API call analysis in ransomware detection and the potency of machine learning approaches in learning from extensive datasets to identify novel malware strains. Given the continual evolution of malware, detection methodologies must adapt correspondingly. This study's comparative analysis elucidates the trade-offs between accuracy, computational speed, and training time, guiding the selection of the optimal machine learning algorithm for robust ransomware detection.

Evaluating the Performance of ETSI-ITS Multi-Stack Protocols for V2V Communication in VANETs: A Simulation Study

The research evaluates various multi-stack protocols for Vehicular Ad-hoc Networks (VANETs), focusing on Vehicle-to-Vehicle (V2V) communication scenarios with Emergency Vehicle (EV) simulations. The study uses the ns-3 network and SUMO (Simulation of Urban MObility) traffic simulators to test these protocols in diverse scenarios, including fluctuating data rates and dense network conditions. By implementing the IEEE 802.11p protocol alongside vehicular message dissemination stacks compliant with ETSI (European Telecommunications Standards Institute) ITS (Intelligent Transport Systems) standards, the study performs simulation experiments with varying vehicle counts, ranging from 20 to 35. It employs two distinct data rate configurations while maintaining a constant transmission power of 23 dBm. The results indicate a decline in the average Packet Reception Ratio (PRR) as vehicle density increases, indicating heightened contention and interference. At the same time, there is an observed increase in average latency, contributing to increased message transmission and reception delays. The quantitative analysis demonstrates an inverse relationship between the average PRR and the total vehicle count when the SEND_CAM message is enabled. On the other hand, disabling SEND_CAM maintains a relatively consistent average PRR across scenarios. Additionally, a positive correlation between vehicle count and average latency underlines the impact of network congestion and interference on communication efficacy within VANETs. Despite suboptimal PRR values falling between 41% and 47%, latency performance remains satisfactory, with average latency durations ranging from 0.154 s to 0.187 s. Notably, the SEND_CAM parameter status shows negligible impact on protocol performance, suggesting that network density plays a more pivotal role. Finally, this study offers valuable insights into the trade-offs and challenges of multi-stack protocols in V2V communication within VANETs. Further optimization efforts are recommended to improve packet reception ratios, especially in high-vehicle-density environments, while maintaining acceptable latency levels. These findings contribute to the ongoing efforts to enhance the reliability and efficiency of communication protocols in VANETs, thus advancing the development of intelligent transportation systems. The study's quantitative protocol performance analysis under varying network conditions provides valuable guidance for optimizing V2V communication deployments in VANETs.

Examining Soft and Hard Attributes of Health Care Service Quality and Their Impacts on Patient Satisfaction and Loyalty.

Many studies have confirmed the influences of various service quality dimensions on patient satisfaction and loyalty, but no existing theoretical model accounts for variation in how different types of patients evaluate service quality's soft and hard attributes. This research gap may cause problems for administrators needing to decide how to distribute resources appropriately across multiple departments. Therefore, this study establishes a theoretical model of the differences between inpatients' and outpatients' evaluations of hard and soft qualities and compares such evaluations' influences on patient satisfaction and loyalty. Also, to supplement statistical analysis and respond to scholars' calls for more mixed-methods studies of health care quality, this research incorporates analysis of online reviews to provide a holistic, close to real-time picture of patients' service experience perceptions. This study's survey sample comprised 292 inpatients and 137 outpatients from a Taiwanese hospital. We used partial least squares structural equation modeling to test the hypothetical model and importance-performance map analysis to identify factors that were significant to the service process but performed poorly. Finally, we used a text-mining technique to scrape 536 reviews posted on Google Maps, and Leximancer Portal to perform automated content and sentiment analyses on those data, as a means of mapping the critical concepts and themes that influenced patient experiences. This study's analyses support the ideas that both hard and soft qualities are critical dimensions of service quality, and that each has different influences on inpatients' and outpatients' satisfaction and loyalty. Specifically, the sampled inpatients strongly valued the hard qualities of the hospital but were not satisfied with it. On the other hand, soft qualities attracted outpatients' attention and influenced their satisfaction and loyalty. In addition, content analysis revealed that soft qualities were the main reason patients left comments, whether positive or negative. Waiting time emerged as another critical element in triggering patients' unfavorable reviews. Patient population type, whether inpatient or outpatient, has been found to impact perceptions of service quality within health care institutions. As such, health care administrators should be cognizant of this phenomenon and make informed and tailored decisions when addressing quality within their respective services. Emphasis on the development of both interpersonal and professional skills among health care personnel may prove beneficial in enhancing the patient experience and ultimately fostering positive online reviews.

Deciphering Elevator Purchase Decisions: A Feasibility Analysis Using the Technological Acceptance Model

This study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) to understand consumer behavior in the hydraulic elevator market. Emphasizing Performance Expectation (PE) and Effort Expectation (EE), the research highlights hydraulic elevators' reliability and ease of maintenance as key factors influencing consumer preferences. Contrary to conventional UTAUT findings, Social Influence (SI) is less influential compared to practical considerations such as cost and efficiency. A comprehensive feasibility analysis identified strong technical and operational feasibility for hydraulic elevators, but raised concerns in legal and scheduling aspects, indicating potential adoption barriers. The study's comparative analysis with newer elevator technologies provides insights into consumer preferences across different elevator systems. The findings have significant implications for industry stakeholders, suggesting the need for focused marketing strategies and streamlined regulatory frameworks. This research contributes to a deeper understanding of the hydraulic elevator market, underscoring the importance of adapting technology adoption models to specific industry contexts.

Target firm's integrity culture and M&A performance

AbstractThis study investigates whether the attribute of integrity culture (derived from target firms’ annual reports) influences merger and acquisition (M&A) performance. We find that a target firm's integrity culture, measured from its 10‐K reports, has a positive and significant effect on market reaction to the bidder firm's M&A announcement. Our study's analysis is found to be robust to sample selection bias by utilising the entropy balancing technique and to endogeneity concerns by employing an instrumental variable approach. Our results are also robust to alternative measures of integrity culture and when controlling for a target firm's religiosity and corporate social responsibility, an acquirer firm's fixed effects, chief executive officer's fixed effects, governance for corporate control and advisor quality. We identify the retention of a target firm's directors and of its customers as channels that underlie our main findings. Furthermore, we find that acquisition synergies improve, with decreased time taken to complete the deal, for acquisitions of target firms with a higher integrity culture.

A hybrid SWAT-ANN model approach for analysis of climate change impacts on sediment yield in an Eastern Himalayan sub-watershed of Brahmaputra

The current study focuses on analyzing the impacts of climate change and land use/land cover (LULC) changes on sediment yield in the Puthimari basin, an Eastern Himalayan sub-watershed of the Brahmaputra, using a hybrid SWAT-ANN model approach. The analysis was meticulously segmented into three distinct time spans: 2025–2049, 2050–2074, and 2075–2099. This innovative method integrates insights from multiple climate models under two Representative Concentration Pathways (RCP4.5 and RCP8.5), along with LULC projections generated through the Cellular Automata Markov model. By combining the strengths of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) techniques, the study aims to improve the accuracy of sediment yield simulations in response to changing environmental conditions. The non-linear autoregressive with external input (NARX) method was adopted for the ANN component of the hybrid model. The adoption of the hybrid SWAT-ANN approach appears to be particularly effective in improving the accuracy of sediment yield simulation compared to using the SWAT model alone, as evidenced by the higher coefficient of determination value of 0.74 for the hybrid model compared to 0.35 for the standalone SWAT model. In the context of the RCP4.5 scenario, during 2075-99, the study noted a 29.34% increase in sediment yield, accompanied by simultaneous rises of 42.74% in discharge and 27.43% in rainfall during the Indian monsoon season, spanning from June to September. In contrast, under the RCP8.5 scenario, for the same period, the increases in sediment yield, discharge, and rainfall for the monsoon season were determined to be 116.56%, 103.28%, and 64.72%, respectively. The present study's comprehensive analysis of the factors influencing sediment supply in the Puthimari River basin fills an important knowledge gap and provides valuable insights for designing proactive flood and erosion management strategies. The findings from this research are crucial for understanding the vulnerability of the Puthimari basin to climate and land use changes, and by incorporating these findings into policy and decision-making processes, stakeholders can work towards enhancing resilience and sustainability in the face of future hydrological and environmental challenges.

BEYOND THE GAME: INTERNATIONAL MEDIA ATTITUDES TOWARD INDONESIA'S CANCELLATION OF THE U20 WORLD CUP

In March 2023, Indonesia was confronted with a situation that was also a worldwide concern. The hosting of the U20 World Cup in Indonesia has been cancelled. This study, however, will not address the reasons why this could happen but rather the attitudes of the world's newspapers in reporting on the subject. It is significant because, as a nation which constantly seeking global recognition, Indonesia should be introspective by understanding the global community's perspectives on the problems that exist in Indonesia, which can be illustrated by news about Indonesia that exists in foreign newspapers. Furthermore, attitude analysis can be done using Appraisal Theory. This study sampled three articles from online news: BBC, CNA, and The Straits Times. The data were analyzed by adopting a mix-method. The results obtained that the three news articles had negative attitudes perspective. Furthermore, the findings of this study's analysis can be used as teaching material for language and communication students interested in becoming journalists or writing articles for print and online publications.

Exploring the Underlying Mechanisms of Qingxing Granules Treating H1N1 Influenza Based on Network Pharmacology and Experimental Validation.

H1N1 is one of the major subtypes of influenza A virus (IAV) that causes seasonal influenza, posing a serious threat to human health. A traditional Chinese medicine combination called Qingxing granules (QX) is utilized clinically to treat epidemic influenza. However, its chemical components are complex, and the potential pharmacological mechanisms are still unknown. QX's effective components were gathered from the TCMSP database based on two criteria: drug-likeness (DL ≥ 0.18) and oral bioavailability (OB ≥ 30%). SwissADME was used to predict potential targets of effective components, and Cytoscape was used to create a "Herb-Component-Target" network for QX. In addition, targets associated with H1N1 were gathered from the databases GeneCards, OMIM, and GEO. Targets associated with autophagy were retrieved from the KEGG, HAMdb, and HADb databases. Intersection targets for QX, H1N1 influenza, and autophagy were identified using Venn diagrams. Afterward, key targets were screened using Cytoscape's protein-protein interaction networks built using the database STRING. Biological functions and signaling pathways of overlapping targets were observed through GO analysis and KEGG enrichment analysis. The main chemical components of QX were determined by high-performance liquid chromatography (HPLC), followed by molecular docking. Finally, the mechanism of QX in treating H1N1 was validated through animal experiments. A total of 786 potential targets and 91 effective components of QX were identified. There were 5420 targets related to H1N1 and 821 autophagy-related targets. The intersection of all targets of QX, H1N1, and autophagy yielded 75 intersecting targets. Ultimately, 10 core targets were selected: BCL2, CASP3, NFKB1, MTOR, JUN, TNF, HSP90AA1, EGFR, HIF1A, and MAPK3. Identification of the main chemical components of QX by HPLC resulted in the separation of seven marker ingredients within 195 min, which are amygdalin, puerarin, baicalin, phillyrin, wogonoside, baicalein, and wogonin. Molecular docking results showed that BCL2, CASP3, NFKB1, and MTOR could bind well with the compounds. In animal studies, QX reduced the degenerative alterations in the lung tissue of H1N1-infected mice by upregulating the expression of p-mTOR/mTOR and p62 and downregulating the expression of LC3, which inhibited autophagy. According to this study's network pharmacology analysis and experimental confirmation, QX may be able to treat H1N1 infection by regulating autophagy, lowering the expression of LC3, and increasing the expression of p62 and p-mTOR/mTOR.

Liberalization vis-à-vis non-liberalization trade policy: Exploring the impact of price volatility on producer share price and cocoa supply response in Nigeria and Ghana

Cocoa producers respond differently to volatile price shocks, but the nature of these responses remains unknown, especially in the liberalized and non-liberalized markets in Nigeria and Ghana, respectively. Therefore, we assess the extent to which price volatility affects the supply of cocoa while also analyzing the effect of price volatility on Nigeria's cocoa producer price share vis-à-vis Ghana's cocoa producer price share. We further analyze how producers react given the asymmetric nature of price volatility in Nigeria and Ghana. Annual secondary data were obtained from the World Development Index, National Bureau of Statistics, International Cocoa Organization, Central Bank of Ghana, Nigeria, and so on, from 1970 to 2019. We used the Ordinary Least Squares method, generalized autoregressive conditional heteroskedastic (GARCH) model, extensions, and the Vector Error Correction Model (VECM) for this study's analysis. Our results show the presence of volatility in price series and that volatility is asymmetric in nature. The results of the supply response show that price volatility has no significant relationship with cocoa supply in Ghana. In contrast, price volatility has a significantly positive relationship with the supply of cocoa in Nigeria at the 1 % level. The results of the VECM show that, in the long run, the cocoa producer price in Ghana will be negatively affected by both international price volatility and inflation rates at 5 % and 1 %, respectively. We suggest that cocoa farmers should have licensing to sell commodities to the international market directly without interference from the marketing board.

Teachers’ Readiness in Developing Special Needs Students Entrepreneurial Mindset

Members of the World Health Organization have committed not to neglect anyone, including persons with disabilities, by including them in all sectors. The significant increase in the number of special needs students by 26.5% in 2022 reflects the reality in Malaysia, where the number of persons with disabilities continues to rise over time. Education serves as the primary foundation for special needs students, and the role of special education teachers becomes increasingly significant when entrusted to teach, educate, and guide special needs students, as well as prepare entrepreneurial-minded special needs students. Thus, this study was conducted to identify the level teachers' readiness in terms of self-efficacy and to test the relationship between readiness in shaping the entrepreneurial mindset of special needs students. A quantitative study using survey method was conducted on 300 Integrated Special Education Program teachers working in primary schools in Selangor. Data from the Likert 5-point scale questionnaire as the research instrument were analyzed using the Statistical Package for the Social Sciences version 28.0. The study's analysis used descriptive statistics involving mean, standard deviation, and percentage while for inferential statistics, correlation coefficient tests were used. The findings show self-efficacy of Integrated Special Education Program teachers are at a high level. The study results show a significant relationship between readiness and the formation of an entrepreneurial mindset The implications of this study define that educators should integrate self-efficacy to prepare students who have a tendency toward innovation, opportunities, and creative outcomes. Entrepreneurship programs and activities can also be designed as complements in teaching and learning to enhance entrepreneurial mindset among special needs students.

Teaching English Speaking through Discourse in the State Islamic Universities in Borneo

Introducing accurate discourses and understanding the discourses that students encounter in their daily lives is crucial for enhancing the teaching of spoken English language. To enhance students' linguistic proficiency, the method of teaching speaking through discourse involves immersing them in authentic dialogues and diverse communication scenarios. This is a descriptive qualitative research, employing a case study approach. The participants of the research are the teachers and students of the State Islamic University of Sultan Aji Muhammad Idris Samarinda and the State Islamic University of Antasari Banjarmasin. To collect data for the study, the researcher used a variety of research instruments, such as interviews, field notes, and questionnaires. This study's data analysis method adheres to the principles of qualitative research. The interactive model was used for the data analysis, which included stages for data collecting, data condensation, data display, and conclusion drawing. Research findings indicate that students have a preference for teachers who not only teach English language curriculum but also demonstrate how to achieve a successful future. For English teachers, it is important to teach students not only English-speaking materials but also proper behaviour and politeness. In terms of English language proficiency, students highlight that speaking is the primary skill in acquiring English since it demonstrates their mastery of the language.

Peran Unsur Meta-Utaut, Penerimaan Paylater dan Persepsi Penggunaan Terhadap Antropomofisme Indonesia

Purpose: Applying the integration of UTAUT and MTAM theories, this study investigates the acceptance and usage of paylater from the Indonesian anthropomorphism perspective. Methodology/approach: Quantitative research strategy using methods for gathering data via questionnaires. Using the Lameshow formula, which yields 384.16, the sample size was calculated and rounded to 400 individuals. The combined strategy of the SEM-ANN method is used in this study's data analysis. Findings: The research presented here demonstrates that behavioral intentions are mostly determined by their performance expectations. The elements of effort expectancy, social influence, facilitating condition, hedonic motivation, habit, and trust in shaping user behavioral intentions all support this. However, perceived risk and perceived cost have the effect of decreasing behavioral intention to use. One of the things that encourages usage behavior is its goal. Practical implications: This empirical study breaks out the paylater adoption-influencing aspects from an Indonesian social perspective. IT developers can create user-friendly or widely approved paylater applications in this approach. Originality/value: This study builds pricing value components by combining the UTAUT and MTAM methodologies with structural equation modeling (SEM) and analysis of neural network (ANN) techniques. In recognizing connections that are linear and non-linear.

Video analysis of bicyclist and pedestrian movement on shared-use paths under daylight and electric lighting conditions—Method exploration

This study introduces a progressive methodology for examining the travel behaviour of bicyclists and pedestrians under both daylight and electric lighting conditions. By analysing data from naturalistic/undisturbed settings, we aimed to assess the representativeness of participant behaviour in an invited context compared to that of typical road users. This paper expands upon the methodological exploration initiated in the original Video Analysis of Pedestrian Movement (VAPM) study by analysing the microscopic movements of both pedestrians and bicyclists in outdoor environments under both natural and electric lighting conditions. Furthermore, the paper investigates bicyclists’ bi-directional interactions in a naturalistic setting, adding a valuable dimension to the study's comprehensive analysis. Our research introduces an effective approach to data collection through the use of drone technology to obtain microscopic data from video analysis. This method has the potential to enhance travel quality for bicyclists during the hours of twilight and darkness and increase the likelihood of short motor vehicle trips being replaced by active, sustainable forms of transport.

The Reasons on Rapid Recovery of Shanghai Disneyland

The outbreak of the COVID-19 pandemic severely impacted many industries, and Disney theme parks were among the hardest hit, suffering significant losses. However, as the pandemic gradually subsided, Shanghai Disneyland, being the first Disney theme park to reopen, experienced a much faster recovery than other Disney theme parks. The purpose of this study was to explore why Shanghai Disneyland was able to recover quickly and what strategies it adopted. This article combines marketing mix theory with operational data and visitor flow statistics from Shanghai Disneyland to analyze the reasons for its rapid recovery. Firstly, Shanghai Disneyland accelerated its recovery by increasing prices, and it can also mitigate risks in the future by implementing advanced ticket sales. Secondly, the park increased ticket sales through various distribution channels and can further improve by refining its ticket refund and exchange policy. Lastly, Shanghai Disneyland enhanced its promotion through various social media channels and can apply this to disseminate everyday knowledge and prevent the risk of pandemic recurrence. This study's analysis of Shanghai Disneyland's swift recovery can provide suggestions and references for the recovery and development of theme parks facing similar pandemic issues in the future, helping to minimize losses.

Interplay between Children's Electronic Media Use and Prosocial Behavior: The Chain Mediating Role of Parent-Child Closeness and Emotion Regulation.

In the contemporary digital milieu, children's pervasive engagement with electronic media is ubiquitous in their daily lives, presenting complex implications for their socialization. Prosocial behavior, a cornerstone of social interaction and child development, is intricately intertwined with these digital experiences. This relation gains further depth, considering the significant roles of parent-child relationships and emotion regulation in shaping children's social trajectories. This study surveyed 701 families to examine the association between children's electronic media use and prosocial behavior, specifically exploring the mediating roles of parent-child closeness and emotion regulation. Structural equation modeling was employed for the analysis. Children's electronic media use negatively correlated with prosocial behavior, parent-child closeness, and emotion regulation. In contrast, a positive association emerged between parent-child closeness, emotion regulation, and prosocial behavior. Emotion regulation also correlated positively with prosocial behavior. Statistical analyses revealed that parent-child closeness and emotion regulation function as both individual and sequential mediators in the relation between electronic media use and prosocial behavior. The study's analyses reveal that fostering children's prosocial behavior in the digital era requires strong family ties, effective emotional management, and balanced digital exposure, which are pivotal for their comprehensive development.

Migration and controls of Shenhu submarine canyons in the upper continental slope of northern South China Sea: Insights from three‐dimensional seismic data mapping

AbstractSubmarine canyons, prominent features on continental margins, hold significant scientific and engineering implications. Despite extensive research on various types of submarine canyons, current understanding of those canyons developed on the upper continental slope, recognized as the most common type globally, remains limited. The Shenhu Canyons on the upper continental slope of the northern South China Sea, comprising over 19 subparallel features persistently developed from the Late Miocene to Quaternary, offer an excellent opportunity for in‐depth study. Previous assumptions suggested a unidirectional eastward migration of these canyons parallel to the host margin, primarily based on observations from two‐dimensional transverse seismic profiles. However, this study's analysis using three‐dimensional seismic data mapping reveals that not all canyons have migrated eastward; 28% display an opposite or a zigzag patterned migration, challenging previous assumptions. The eastward migration of the Shenhu Canyons on the eastern slope of the palaeo‐Pearl River shelf‐edge delta can be linked to the south‐east–southward progradation of the host margin and the palaeo‐shelf‐edge delta. However, the overall eastward migration pattern is complicated by submarine landslides and turbidity current processes. Landslides can influence the direction and magnitude of canyon migration through four mechanisms: turbidity current diversion; retrogressive development of canyon‐wall landslides; retrogressive landslides on surrounding open slopes; and emplacement of landslides in canyon thalwegs. These mechanisms may result in widening, bifurcation, confluence or obstruction of canyons, contributing to canyon migration. Erosion by turbidity currents can trigger canyon‐wall failures, which in turn promote the lateral migration of the canyons. If overspilled turbidity currents lead to the growth of levées in the lower reaches, canyon confinement increases, suppressing lateral migration. The inherited high‐gradient Palaeogene syn‐rift tectonic slope, combined with the depositional delta‐front slope of the palaeo‐shelf‐edge delta, creates favourable conditions for the initiation and persistent development of the straight Shenhu Canyons. This comprehensive analysis provides valuable insights into the complex dynamics and factors influencing the migration of upper continental slope submarine canyons.

Feature Evaluation of Emerging And E-Learning System

With the development of artificial intelligence, adaptive e-learning has gained more and more attention. As every approach to e-learning becomes less appealing and the quality of as the popularity of online courses grows, they switch to more customized, flexible learning to work with students and achieve better learning results. The focus of the schools is on organization, awareness, and examination. pupils and achieve better learning results The focus of the schools is Methods for bringing creativity into the curriculum and vision E-learning worries are widespread. It is an exam issue for each and every one of us. The goal of this study's analysis is to identify potential outcomes from assessing e-learning models with artificial intelligence (AI) methodologies like supervised, semi-supervised, and unsupervised reinforcement learning advancements.

Global Trends in Kidney Stone Awareness: A Time Series Analysis from 2004-2023.

Despite the prevalence and incidence of kidney stones progressively increasing worldwide, public awareness of this condition remains unclear. Understanding trends of awareness can assist healthcare professionals and policymakers in planning and implementing targeted health interventions. This study investigated online search interest in "kidney stone" by analyzing Google Trends, focusing on stationarity of the trends and predicting future trends. We performed time series analysis on worldwide Google monthly search data from January 2004 to November 2023. The Augmented Dickey-Fuller (ADF) test was used to assess the stationarity of the data, with a p-value below 0.05 indicating stationarity. Time series forecasting was performed using the autoregressive integrated moving average to predict future trends. The highest search interest for "kidney stone" (score 100) was in August 2022, while the lowest was in December 2007 (score 36). As of November 2023, search interest remained high, at 92. The ADF test was significant (p = 0.023), confirming data stationarity. The time series forecasting projected continued high public interest, likely reflecting ongoing concern and awareness. Notably, diverse regions such as Iran, the Philippines, Ecuador, the United States, and Nepal showed significant interest, suggesting widespread awareness of nephrolithiasis. This study highlighted that "kidney stone" is a consistently relevant health issue globally. The increase and stationarity of search trends, the forecasted sustained interest, and diverse regional interest emphasize the need for collaborative research and educational initiatives. This study's analysis serves as a valuable tool for shaping future healthcare policies and research directions in addressing nephrolithiasis related health challenges.

SOLAR AND WIND LEADS THE CHARGE: ANALYZING INDIA'S DYNAMIC GROWTH IN RENEWABLE ENERGY CAPACITY FROM 2016 TO 2023

With a focus on significant advancements in solar, wind, and hydropower capacity, this report offers a thorough analysis of the growth trajectory of India's renewable energy industry from 2016 to 2023. The analysis highlights the exponential increase in solar installations, especially in regions like Rajasthan, which will account for over half of the nation's renewable energy mix by 2023. Solar energy emerged as the dominating force in this regard. Even if solar energy was rising faster, wind energy continued to expand steadily, highlighting its crucial place in the renewable portfolio. The report also explores the hydropower industry, highlighting the minor differences in growth patterns between small- and large-scale projects. The study's thorough data analysis shows a significant increase in the production of renewable energy, particularly in 2023, demonstrating the industry's strong reaction to India's challenging clean energy targets. The study of solar capacity at the state level reveals notable regional differences that may be ascribed to policy, geographic, and infrastructure variations. These findings indicate potential areas for focused policy interventions. The results support a multifaceted strategy for developing renewable energy, highlighting the significance of balanced growth from many sources. To maintain the sector's pace, recommendations include improving legislative frameworks, making infrastructural investments, and encouraging innovation. To support strategic choices and propel India's transition to a sustainable energy future, this research offers insightful information to stakeholders, investors, and policymakers.