Inform Policy Decisions Research Articles

Compatible alternative energy storage systems for electric vehicles: Review of relevant technology derived from conventional systems

Because of the energy crisis and environmental challenges, it is important to establish a new smart city model to offer some effective solutions. Electric vehicles are one of the primary components that may help to reduce environmental issues and intervene in the energy recovery and management process. On-board the vehicle, many methods can be used to manage the energetic flux. Hybrid arrangements are one of the strongest ways to merge two options. Arrangements can incorporate more than two separate energy sources, with the vehicle using one or both of them. Renewable energy advances these systems and provides new potential for the widespread use of hybrid and pure electric vehicles. The dynamic nature of the field, which includes varied technologies critical for renewable energy integration, justifies energy storage and recovery strategies. Its significance arises from its role in leading future research, informing policy decisions, and encouraging sustainability in energy practices across multiple industries. This work contributes to the development of robust and efficient energy infrastructures by addressing existing difficulties and optimizing energy systems. Generally, we will look at some existing energy storage methods that provide needed energy in electric vehicles. Some vehicles already employ these conventional technologies, so we will present some industry examples. And discuss the alternatives generated from these conventional techniques based on the most recent research on this subject. Energy recovery systems are also being considered as a supply system to increase range and support energy storage systems in a variety of configurations.

Economic Recovery Efforts through Tourism in the Bira Beach Area, Bulukumba Regency

Located in the enchanting province of South Sulawesi, Indonesia, lies the captivating Bulukumba Regency, a veritable haven for discerning travelers seeking to immerse themselves in a cornucopia of awe-inspiring natural wonders and a vibrant tapestry of cultural diversity. The advent of the global pandemic has undeniably caused significant disruptions within the tourism sector, thereby exerting a profound impact on the sustenance and well-being of local communities. The study utilizes qualitative methodologies to scrutinize the multifaceted role and profound influence of tourism within the designated region. This statement highlights the crucial significance of implementing sustainable tourism practices, fostering community engagement, and promoting equitable employment opportunities. The research endeavors to delineate a myriad of tactics aimed at fostering economic resurgence, encompassing initiatives such as programs focused on enhancing capabilities, the utilization of data to inform policy decisions, and harmonized endeavors to bolster the tourism sector. The research proposes a set of strategic measures aimed at maximizing the economic prospects of the tourism industry. These measures encompass the implementation of capacity-building initiatives targeted at local communities, with the objective of augmenting their skill sets and enhancing their employability. The imperative of guaranteeing equitable employment prospects and fostering sustainable practices cannot be overstated. In addition, it is imperative for the government and key players in the tourism industry to prioritize the implementation of a data-driven strategy in policymaking and coordination efforts, with the ultimate goal of rejuvenating the tourism sector in South Sulawesi Province.

How do American and British Nonsmokers Value Secondhand Smoke Health Risks?

Despite concerted efforts to enforce smoke-free laws in various countries, nonsmokers, particularly women and children, continue to be exposed to daily secondhand smoke (SHS), resulting in significant health risks. While existing studies have assessed the health effects of numerous diseases, the quantification of SHS spillovers remains understudied. This research employs choice experiments and contingent valuation techniques to rigorously quantify the attributes of SHS health risks, with a specific emphasis on facilitating cross-country comparisons. Our investigation reveals that nonsmoking individuals in the United Kingdom exhibit an attitude of indifference towards a proposed policy offering increased disposable income as compensation for SHS exposure. Conversely, nonsmoking Americans express a contrary perspective. Furthermore, our study demonstrates that nonsmoking Americans attribute a higher value to SHS health risks compared to their British counterparts. Consequently, this research uncovers a hitherto unexplored dimension of health risk-related behaviors. These findings hold the potential to significantly contribute to the development of future smoke-free policies, offering valuable insights that can inform policy decisions and address the persistent challenges associated with SHS exposure, particularly among vulnerable populations.

The Perception of Students on the Use of ICT Tools to Learn Mathematics in Gasabo Selected Public Secondary Schools

Studying students' perception toward the use of ICT tools to learn mathematics is significant for improving education, informing policy decisions, and ensuring that students are adequately prepared for the digital age. It can contribute to more effective teaching and learning strategies. Within the purpose of determining how students felt about using ICT tools to learn mathematics, the present investigation was carried out in two public secondary schools in Rwanda's Gasabo District. A survey design was used for the investigation. The population of the study was 241 students. A simple random sampling technique was employed to select the sample of 150 students in the senior six who participated in this study. Questionnaires were used to collect the data that was displayed. The collected data was weighed using the mean. The 136 students who handed back the questionnaires for the current study had an average mean of 3.66, indicating that they had an overall positive perception of using ICT tools to learn mathematics. Nevertheless, the ability to learn mathematics using ICT tools remained below baseline. The results of this study add to the body of knowledge on the efficient use of ICT tools in mathematics teaching and learning

Structured analysis of broader GMO impacts inspired by technology assessment to inform policy decisions

If genetically modified organisms (GMOs) are approved in the EU for experimental release or marketing authorization (placing on the market), a risk assessment (RA) is carried out beforehand to determine whether this may be associated with negative effects on human health, nature or the environment. Applications are reviewed by the European Food Safety Authority (EFSA) and the national Competent Authorities of the Member States. However, the potential ramifications of the GMOs that are systematically addressed in the current RA context are limited. Broader consideration can include environmental and health aspects beyond the scope of the statutory RA, as well as societal, ethical and cultural impacts. These other levels of impact may be considered during the comitology process of authorisation, but how this is done is typically not made explicit in a systematic way. However, with the dynamic developments of new kinds of GMOs, these considerations as well as transparency regarding the role of broader considerations in political decision-making become more and more relevant. Against this backdrop, we identified the requirements and suggest the main elements for such a broader assessment. We use insights from the field of Technology Assessment (TA) to explore the requirements for operationalising a rapid but still systematic, transparent and broad case-by-case GMO assessment compatible with the existing legislative framework.

From Text to Insight: A Natural Language Processing-Based Analysis of Topics and Trends in Neurosurgery.

Neurosurgical research is a rapidly evolving field, with new research topics emerging continually. To provide a clearer understanding of the evolving research landscape, our study aimed to identify and analyze the prevalent research topics and trends in Neurosurgery. We used BERTopic, an advanced natural language processing-based topic modeling approach, to analyze papers published in the journal Neurosurgery . Using this method, topics were identified based on unique sets of keywords that encapsulated the core themes of each article. Linear regression models were then trained on the topic probabilities to identify trends over time, allowing us to identify "hot" (growing in prominence) and "cold" (decreasing in prominence) topics. We also performed a focused analysis of the trends in the current decade. Our analysis led to the categorization of 12 438 documents into 49 distinct topics. The topics covered a wide range of themes, with the most commonly identified topics being "Spinal Neurosurgery" and "Treatment of Cerebral Ischemia." The hottest topics of the current decade were "Peripheral Nerve Surgery," "Unruptured Aneurysms," and "Endovascular Treatments" while the cold topics were "Chiari Malformations," "Thromboembolism Prophylaxis," and "Infections." Our study underscores the dynamic nature of neurosurgical research and the evolving focus of the field. The insights derived from the analysis can guide future research directions, inform policy decisions, and identify emerging areas of interest. The use of natural language processing in synthesizing and analyzing large volumes of academic literature demonstrates the potential of advanced analytical techniques in understanding the research landscape, paving the way for similar analyses across other medical disciplines.

Exploring the economic impact of institutional entrepreneurship, social Innovation, and poverty reduction on carbon footprint in BRICS countries: what is the role of social enterprise?

The world is facing challenges to reduce carbon emissions, the complex interplay between socioeconomic dynamics and environmental sustainability is of utmost importance. In the context of the BRICS nations-Brazil, Russia, India, China, and South Africa-this study explores the intricate interactions between institutional entrepreneurship, institutional innovation, poverty reduction, social globalization, urbanization, and social entrepreneurship as well as their combined effects on the carbon footprint over the period of 1990 to 2021. This work examines the multi-dimensional interactions inside this nexus using a thorough analytical strategy that includes the Generalized Method of Moments (GMM), Three-Stage Least Squares (3SLS), and Robust regression approaches. Institutional entrepreneurship and innovation are the main forces behind institutional change and may have an impact on how people behave in terms of the environment. Strategies for reducing poverty frequently involve greater resource usage, which has an impact on carbon footprint. Examining social globalization's impact on carbon footprints is necessary given how it affects consumer habits and economic activity. Rapid urbanization is a dual problem because it spurs both increased energy demand and novel sustainability measures. With its emphasis on community-driven solutions, social entrepreneurship can provide regional solutions to reduce poverty and carbon emissions. The study's findings provide policymakers, practitioners, and researchers with insights into the complex web of socio-economic factors that underlies carbon footprint fluctuations. This research paves the way for informed policy decisions, sustainable business practices, and the pursuit of harmonious development that addresses both economic aspirations and environmental imperatives within the BRICS countries by illuminating the connections between institutional entrepreneurship, innovation, poverty reduction, social globalization, urbanization, social entrepreneurship, and carbon emissions.

Spatial attribution of aircraft mass balance experiment CO2 estimations for policy-relevant boundaries: New York City

To effectively address the unprecedented acceleration of climate change, cities across the United States are leading efforts to reduce greenhouse gas emissions. Coherent, aggressive, and lasting mitigation policies in controlling carbon emissions are beginning to be adopted to help strengthen climate resilience across different sectors. However, evaluating the effectiveness of current climate legislation requires careful monitoring of emissions through measurable and verifiable means to inform policy decisions. As a part of this effort, we developed a new method to spatially allocate aircraft-based mass balance carbon dioxide (CO2) emissions. In this work, we conducted 7 aircraft flights, performed downwind of New York City (NYC) to quantify CO2 emissions during the nongrowing seasons between 2018 and 2020. We used an ensemble of emission inventories and transport models to calculate the fraction of enhancements (Φ) produced by sources within the policy-relevant boundaries of the 5 NYC boroughs and then applied that to the bulk emissions calculated using the mass balance approach. We derived a campaign-averaged source-apportioned mass balance CO2 emission rate of (57 ± 24) (1σ) kmol/s for NYC. We evaluated the performance of this approach against other top-down methods for NYC including inventory scaling and inverse modeling, with our mean emissions estimate resulting in a 6.5% difference from the average emission rate reported by the 2 complementary approaches. By combining mass balance and transport model approaches, we improve upon traditional mass balance experiment methods to enable quantification of emissions in complex emission environments. We conducted an assessment using an ensemble of emission inventories and transport models to determine the sources of variability in the final calculated emission rates. Our findings indicate that the choice of inventory accounted for 2.0% of the variability in the emission estimates and that the atmospheric transport model contributed 3.9% at the campaign level. Additionally, on average, at the daily scale, the transport model contributed 7.6% and the inventory accounted for 14.1%. The daily flight-to-flight variability contributed a significant portion, at 42.1%. This approach provides a solution to the difficulty of interpreting aircraft-based mass balance results in complex emission environments.

DEVELOPMENT STRATEGY FOR MICRO, SMALL AND MEDIUM ENTERPRISES OF PALEMBANG CITY

Micro, Small, and Medium Enterprises (MSMEs) play a pivotal role in bolstering the economy, particularly in employment, contributing significantly to the stability of both regional and broader financial systems. This research, employing a qualitative approach involving observation, interviews, and documentation studies, seeks to identify and map potential MSME areas in Palembang City. The study's findings encompass the thorough identification and mapping of these enterprises across each sub-district in Palembang City, elucidating 22 strategic issues such as capital, marketing, infrastructure, licensing, and innovation. Furthermore, the research sheds light on the spatial distribution of MSMEs, categorizing them based on zoning and business type. Notable examples include the culinary business center in Bukit Kecil sub-district, the cracker and kemplang business center in Sukarami sub-district, the songket business center in Ilir Barat II sub-district, and the jumputan business center in Kertapati sub-district. This comprehensive analysis contributes valuable insights into the multifaceted dynamics of MSMEs, offering a foundation for informed policy decisions and strategic planning to enhance economic sustainability.

The Economic Impact of Canada's Aging Population

Canada is a country with an aging population, especially in cities with small populations, such as Winnipeg and Yukon. The aging population trend is a double-edged sword, as it has both benefits and drawbacks. The downside is that it leads to a number of economic problems, including a reduced workforce and increased health care costs, while the upside is that it can boost demand for specific services, such as nursing homes and hospitals. Specifically, the paper aims to examine the factors that contribute to Canada's aging population trend and its effect on the workforce in these cities, including the retirement of baby boomers and declining birth rates. Also, it investigated the economic implications of an aging population, such as reduced labor supply and increased healthcare and insurance costs. Additionally, assessing the impact of population aging on these urban emerging industries and identifying potential policy solutions to mitigate the negative economic impact of population aging are presented in detail to provide readers with a clear framework. It can be inferred that the aging population trend in Canada is a complex issue that has both benefits and drawbacks. While it may boost demand for specific services, such as nursing homes and hospitals, it can also lead to a decline in the labor supply, increased healthcare costs, and challenges for emerging industries in smaller cities. It is important to study the impact of Canada's aging population trends on the economy to inform policy decisions aimed at promoting economic growth and stability in the face of demographic change.

Commentary: Some water in the data desert: the Cancer Intervention and Surveillance Modeling Network's capacity to guide mitigation of cancer health disparities.

Despite significant progress in cancer research and treatment, a persistent knowledge gap exists in understanding and addressing cancer care disparities, particularly among populations that are marginalized. This knowledge deficit has led to a "data divide," where certain groups lack adequate representation in cancer-related data, hindering their access to personalized and data-driven cancer care. This divide disproportionately affects marginalized and minoritized communities such as the U.S. Black population. We explore the concept of "data deserts," wherein entire populations, often based on race, ethnicity, gender, disability, or geography, lack comprehensive and high-quality health data. Several factors contribute to data deserts, including underrepresentation in clinical trials, poor data quality, and limited access to digital technologies, particularly in rural and lower-socioeconomic communities.The consequences of data divides and data deserts are far-reaching, impeding equitable access to precision medicine and perpetuating health disparities. To bridge this divide, we highlight the role of the Cancer Intervention and Surveillance Modeling Network (CISNET), which employs population simulation modeling to quantify cancer care disparities, particularly among the U.S. Black population. We emphasize the importance of collecting quality data from various sources to improve model accuracy. CISNET's collaborative approach, utilizing multiple independent models, offers consistent results and identifies gaps in knowledge. It demonstrates the impact of systemic racism on cancer incidence and mortality, paving the way for evidence-based policies and interventions to eliminate health disparities. We suggest the potential use of voting districts/precincts as a unit of aggregation for future CISNET modeling, enabling targeted interventions and informed policy decisions.

RECCAP2 Future Component: Consistency and Potential for Regional Assessment to Constrain Global Projections

AbstractProjections of future carbon sinks and stocks are important because they show how the world's ecosystems will respond to elevated CO2 and changes in climate. Moreover, they are crucial to inform policy decisions around emissions reductions to stay within the global warming levels identified by the Paris Agreement. However, Earth System Models from the 6th Coupled Model Intercomparison Project (CMIP6) show substantial spread in future projections—especially of the terrestrial carbon cycle, leading to a large uncertainty in our knowledge of any remaining carbon budget (RCB). Here we evaluate the global terrestrial carbon cycle projections on a region‐by‐region basis and compare the global models with regional assessments made by the REgional Carbon Cycle Assessment and Processes, Phase 2 activity. Results show that for each region, the CMIP6 multi‐model mean is generally consistent with the regional assessment, but substantial cross‐model spread exists. Nonetheless, all models perform well in some regions and no region is without some well performing models. This gives confidence that the CMIP6 models can be used to look at future changes in carbon stocks on a regional basis with appropriate model assessment and benchmarking. We find that most regions of the world remain cumulative net sources of CO2 between now and 2100 when considering the balance of fossil‐fuels and natural sinks, even under aggressive mitigation scenarios. This paper identifies strengths and weaknesses for each model in terms of its performance over a particular region including how process representation might impact those results and sets the agenda for applying stricter constraints at regional scales to reduce the uncertainty in global projections.

A holistic analysis of China's consumption-based water footprint (2012–2017) from a multilevel perspective

As the world's second-largest economy, rapid socioeconomic development in China has exerted unprecedented pressure on water resources. However, there is still uncertainty regarding consumption-based water footprint (CWF) assessment across different spatiotemporal scales, especially those differentiated by green, blue, and grey water footprints. To address this knowledge gap, this study employed a multi-regional input–output (MRIO) model and structural decomposition analysis (SDA) to quantify the spatiotemporal dynamics and key drivers of consumption-based green (GCWF), blue (BCWF), and grey (HCWF) water footprints in mainland China during 2012–2017. The main findings of the study are as follows. (1) The HCWF is approximately 4.4 times greater than the sum of the GCWF and BCWF, with water consumption caused by pollution significantly exceeding direct consumption. However, there was a significant decrease in all three CWFs after 2015, particularly HCWF. (2) The spatial distribution pattern of the CWF shows high values in the east and south and low values in the west and north, while virtual water (VW) transfer through commodity trade occurs mainly from inland to coastal regions. (3) The three highest water-consuming sectors were agriculture, food and tobacco processing, and construction, accounting for over 70% of the total water consumption. (4) Water efficiency and consumption patterns are crucial factors in reducing CWF, while affluence levels have the greatest impact on increasing CWF, followed by changes in industrial structure after 2015. Overall, the results of this study contribute to a comprehensive understanding of China's regional and sectoral water consumption throughout the supply chain. In addition, our findings identified regions and sectors with high water consumption and their drivers, which can inform policy decisions and contribute to synergistic cross-regional regulation and sustainable water resources management.

NON-VIOLENT CRIME VICTIMS’ PERCEPTIONS OF POLICE BEHAVIOR, LEGITIMACY, AND ITS INFLUENCE ON COOPERATION WITH POLICE OFFICERS IN ANGELES CITY

This research explores the perceptions of trust, legitimacy, and cooperation with the police among victims of non-violent crimes in Angeles City, Philippines. Grounded in Tylers theoretical framework and Procedural Justice Theory, the study examines how these factors influence non-violent crime victims willingness to cooperate with law enforcement. It assesses how victims views of police response relate to their perception of police legitimacy. The research employs a quantitative approach, utilizing descriptive surveys and correlation analysis. A referral sampling method is used to access reluctant participants. Data is collected through a survey checklist questionnaire with Likert scale items. Statistical tools, including mean, percentage, standard deviation, variance, and Pearsons correlation coefficient, aid in data analysis. This study sheds light on the dynamics between crime victims, police behaviour, and perceptions of legitimacy, informing policy decisions in the realm of law enforcement. This research delves into public perceptions of procedural justice and its impact on trust and cooperation with law enforcement agencies. Findings reveal a prevalent negative perception of procedural justice among the general population, significantly diminishing trust in authorities and fostering a sense of inadequate respect for individual rights within the justice system. The study uncovers mixed feelings about cooperating with the police, indicating a prevailing reluctance to engage actively. Moreover, the research highlights the importance of aligning law enforcement agencies moral values with those of the community to enhance perceptions of legitimacy. Policymakers are urged to devise comprehensive strategies to improve police performance and bolster public trust, considering diverse societal and cultural dynamics. The study emphasizes the need for further research to unravel the complexity of public perceptions and enhance community-police relations, ultimately fostering a more just and equitable society. KEYWORDS: Trust, Legitimacy, Cooperation, Perceptions, Non-violent crimes

Coping With Stressors and General Resistance Resources Used by Individuals Experiencing Homelessness in Minneapolis Tent Camps

Homelessness remains a significant public health issue across the United States, particularly in urban areas. Individuals become and remain homeless for multifaceted and complex reasons that are linked to well-being. The aim of this study was to understand the well-being of persons experiencing homelessness (PEH) and living in tent camps using Aaron Antonovsky’s salutogenic model of health (SMH). To address well-being, we conducted a basic qualitative study with thirty adults over age 18 who self-identified as homeless and living in tent camps within the city of Minneapolis. With a semi-structured interview guide that centered on the SMH, we analyzed data using Johnny Saldaña’s qualitative coding method. Sources of stress themes, including (1) “family trauma” (depression/trauma related to the death of a loved one and drugs, imprisonment, and abuse), (2) “mental health” (depression/trauma related to the death of a loved one, loneliness living in tent camps, substance use, mental illness), and (3) “change and threats” (constant fear of aggression, lack of stability of the tent camp, bad people causing problems, cliques in the camp). Themes of general resistance (GRRs) resources (coping with stress), or GRRs emerged, including (1) “systems knowledge,” (2) “coping strategies,” (3) “sense of community,” (4) “camp stability,” and (5) “human dignity” emerged during data collection and analysis. These findings can inform policy decisions related to increasing services to exit homelessness, funding for sustainable tent camps, and sweeps of tent camps in the city of Minneapolis and beyond.

PROGRESSIVE HEALTH SPENDING AND MALARIA OUTCOMES IN NIGERIA: UNVEILING THE IMPACT

This study delves into the relationship between progressive health spending and malaria outcomes in Nigeria, aiming to uncover the impact of financial investments on disease management. Malaria remains a significant public health challenge in Nigeria, with substantial resources allocated to combat the disease annually. However, the effectiveness of health spending in curbing malaria incidence and mortality rates remains unclear. Through a comprehensive analysis of healthcare expenditure trends and malaria outcomes, this research seeks to elucidate the extent to which progressive health spending influences malaria prevention, treatment, and control measures. Drawing upon national health expenditure data and malaria surveillance statistics, the study employs quantitative methods to examine the association between health expenditure patterns and malaria incidence and mortality rates over time. The findings shed light on the effectiveness of financial investments in mitigating the burden of malaria and inform evidence-based policy decisions aimed at improving disease management strategies in Nigeria.

SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R.

Environmental epidemiology studies aim to understand the impact of mixed exposures on health outcomes while adjusting for covariates. However, traditional statistical methods make simplistic assumptions that may not be applicable to public policy decisions. Researchers are ultimately interested in answering causal questions, such as the impact of reducing toxic chemical exposures on adverse health outcomes like cancer. For example, in the case of PFAS, a class of chemicals measured simultaneously in blood samples, identifying the shifts that result in the greatest reduction in thyroid cancer rates can help more directly inform policy decisions on PFAS. In mixtures, nonlinear and non-additive relationships call for new statistical methods to estimate such modified exposure policies. To address these limitations, the open-source SuperNOVA package has been developed to use data-adaptive machine learning methods for identifying variable sets that have the most explanatory power on an outcome of interest. This package applies non-parametric definitions of interaction and effect modification to these variable sets in a mixed exposure, enabling researchers to explore modified treatment policies using stochastic interventions and answer causal questions. The SuperNOVA software implements the data-adaptive discovery of variable sets and estimation using optimal estimators for stochastic interventions described in our paper "Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions" (McCoy et al., 2023).

Exploring the impact of natural Resource utilization on human capital development: A sustainable development perspective

The COVID-19 pandemic has had a profound impact on societies worldwide, highlighting the need for sustainable development practices. This study focuses on the N-11 countries, aiming to investigate the influence of coal rent, oil rent and mineral rent on human capital by controlling the role of economic growth and financial development from 1990 to 2021. The study analysis begins by conducting preliminary tests to address cross-section dependency, slope heterogeneity, unit root, and cointegration to ensure robust and accurate findings. The study employed the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) techniques for the panel data analysis. The LM cointegration method results reveal the existence of long-run relationship among the study variables. These test findings revealed that natural coal rent, oil rent and mineral rent are positively and significantly associated with human capital. We observe that economic growth and financial development also helpful to increase the human development level in these group of countries. Based on these finding, this study suggests different policy implication for these group of countries which will help policymakers to reach on consensus. Exploring the impact of natural resource utilization on human capital development from a sustainable development perspective during COVID-19 highlights the need for informed policy decisions. By considering the economic, social, and environmental dimensions, policymakers can create a resilient and sustainable future. Integrating sustainable development principles, embracing technology and innovation, and fostering international cooperation are essential to ensure a positive impact on human capital development in the face of resource utilization challenges.

Exploring the link between drought‐related terms and public interests: Global insights from LSTM‐based predictions and Google Trends analysis

AbstractEffective drought monitoring is of paramount importance in hydrology. It aids in mitigating the detrimental effects of water scarcity, facilitates sustainable resource management, and informs policy decisions. Therefore, it is crucial to comprehensively comprehend the dynamics and trends of drought‐related phenomena. This study aims to explore the relationship between six low water quantity terms including drought, water crisis, water scarcity, water shortage, water stress, and water insecurity and some socio‐economic, geographic, and demographic parameters for different regions of the world and to predict the future trend of public interest in the mentioned terms using Long Short‐Term Memory neural network (LSTM) models. Google Trend data analysis was used to examine the public interest in these terms from 2017 to 2022. The LSTM models were trained using historical data on the studied terms, and their performance was evaluated using Root Mean Square Error (RMSE) indicator. The Google Trend data analysis showed that public interest in water shortage and water insecurity increased significantly from 2017 to 2022. The LSTM models showed promising results for predicting future trends in the mentioned water related issues, with RMSE scores (dimensionless) ranging from 0.04 to 0.43. The most significant socio‐economic, geographic and demographic parameters were found to be population, life expectancy, access to drinking water, and access to Internet while there was no correlation between precipitation and searched terms. The results suggest that LSTM models can be an effective tool for forecasting water related issues and emphasizes the importance of socio‐economic, geographic and demographic parameters in the public search behaviour around the world. The study also highlights the increasing public awareness of water related issues and the need for sustainable water management practices, particularly in regions with high water shortage and insecurity. The LSTM‐based prediction models in this study have practical applications in early warning systems for droughts, community education on water conservation, prioritizing vulnerable areas, assessing public perception of climate change's relation to droughts, and evaluating water policies. Further research is needed to improve the accuracy of these models incorporating the effective parameters and to develop effective strategies for managing water resources in regions facing water scarcity.

Analysis of Research Management by the National Research and Innovation Agency: Politicization of Research or Opportunities for Realizing Evidence-Based Policy?

Numerous experts recommend the adoption of evidence-based policy concepts to ensure the high quality of policy decisions and practices. Research plays a crucial role in this context, serving as an instrumental process to inform policy decisions at various levels. In contrast to some countries that have established independent, autonomous, and decentralized research institutions, Indonesia's recent shift towards centralization through the creation of the National Research and Innovation Agency has raised concerns about potential politicization of research. This article seeks to analyze the risk of research politicization and explore prospects for future research management to support the implementation of evidence-based policies. Employing a qualitative approach, this study relies on a thorough literature review, drawing from reputable journals, books, and other credible references. The results indicate that the existence of the National Research and Innovation Agency offers a dual perspective: while it enables government control over research implementation aligned with political agendas, it also opens avenues for utilizing research findings in diverse policy decisions and practices. Emphasizing objectivity is essential as research must remain impartial. Therefore, future research management should prioritize objectivity, and the format of the National Research and Innovation Agency presents an opportunity to promote evidence-based policies and policy practices grounded in unbiased research outcomes.