Current trends of water use in Brazil are dangerous and unsustainable. This fresh-water-endowed country’s nearly 30-year old legal framework is conducive to sound governance, in principle. In practice, fair and sustainable freshwater governance faces steep obstacles and requires new institutions. Too much responsibility is left to voluntary processes and to a disempowered and largely demobilized public as the motor for change, while national decision makers allow dangerous wastefulness and prioritize large-scale use of water as a commercial commodity over the legally sanctioned purpose of sustaining human and animal well-being. Purely voluntary processes are insufficient to counter this. Top-down governmental authority and enforcement mechanisms are needed to ensure wise use and compliance by all, as is greater general access to system-critical knowledge. Needed collective pressure for fair and sound water governance is obstructed by power-inflected information and education structures that leave Brazilians uninformed about the true costs of Brazil’s commodities-centered economic model and about the reality of water insecurity and its avoidability. New institutions are vitally needed to empower the citizenry and generally improve decision-making in the public interest.

Family Caregiver Perspectives on Advance Care Planning Discussions for Residents With Dementia Led by Trained Nursing Home Staff: Insights From the APPROACHES Project.

Cost-consequence Analysis of Secukinumab vs Adalimumab in Moderate-to-severe Hidradenitis Suppurativa.

Prioritization of sub-watersheds based on hydro-morphometric assessment in relation to soil erosion: A case study in Haora Drainage Basin, Tripura

Satisfying ethical principles of voluntary consent within workflow constraints can be challenging, particularly for anesthesia research, where patients are met on the day of surgery. For parents, the added burden of being a surrogate decision maker may impact willingness to be approached for research on the day of surgery. Our aims were to determine parental attitudes to day of surgery approach for research consent and if study type had any influence. We iteratively developed a questionnaire using stakeholder interviews regarding day of surgery approach for research consent. Particular attention was given to (a) research study designs, (b) previous research experience, and (c) types of surgeries. Participants were stratified according to a child's age, child's previous surgical experience, and any family research experience. Enrolment continued until saturation was reached. Interviews were transcribed and analyzed for themes. The final questionnaire included questions designed to determine parental perceptions of the appropriateness of the same day approach, and whether ethical principles would be satisfied if approached on the day of surgery. The second section presented a series of scenarios describing different study types designed to determine if studies with increasing levels of perceived risk would impact parental perception. Most parents reported that this approach would satisfy ethical principles for voluntary informed consent. Study type was not a determinant except for RCTs, where only half felt a day of surgery approach would be appropriate. The most cited reason for reluctance for RCTs was insufficient time to review details. Parents of younger children (61.1% infants, 56.2% toddlers) were more likely to prefer an alternative time of approach compared to teenagers (36%). The results of this study are reassuring for pediatric researchers, identifying majority acceptance for day of surgery research consent approaches for most studies. We identified subgroups who preferred alternative timing for approach. Alternate strategies are advised to target these subgroups. ClinicalTrials.gov identifier: NCT04613505.

• Some road freight transportation decisions remain uninvestigated. • Paucity of application to real-world road freight transportation decisions. • Operationalisation of a framework to investigate data-driven decisions. • A possible theoretical lens is proposed to further expand the research on the topic. Road freight transportation represents the dominant mode for inland freight transportation and is a critical component of logistics systems. Decisions in this domain are inherently complex due to the scale of operations, the numerous actors involved, and the dynamic operating environment. Machine learning (ML) represents a valid tool to address this complexity. However, literature on the topic is largely technical and focused on specific applications, lacking broader managerial insights that researchers and practitioners can leverage when applying ML to road freight transportation management (RFTM) decisions. To address this gap, this paper presents a systematic literature review investigating the characteristics of decision making when ML is applied to RFTM, encompassing both the managerial and technical aspects. The findings indicate that, while numerous studies focus on vehicle routing problems, other decisions within RFTM remain largely underexplored. Furthermore, only a limited number of studies develop and validate machine learning (ML) solutions using real-world data, thereby constraining the assessment of their practical applicability and impact. In addition, drawing from the analysis of the review results, this study proposes a conceptual framing of ML applications in RFTM, depicting ML as a potential mitigator of the limitations associated with bounded rationality in RFTM decision-making. This paper lays the foundation for future research on the application of ML for RFTM. It also proposes a replicable approach for analysing data-driven decisions in other contexts. Moreover, it offers practical guidance to decision makers by highlighting the elements that ML can act upon, thus supporting its adoption in practice.

An e-delivery system based on pick-up points: demand forecast, system design and scenario assessment

The impacts of organochlorine pesticides on adverse human health outcomes: A second-order synthesis of mean effects and heterogeneity.

Data-driven evaluation of constraints and adaptation priorities in Asian and African rice systems: Outcomes from the PAiCE toolkit

Index tracking models considering interval fuzzy preference relations of decision makers for portfolio optimization

ABSTRACT Race-conscious redistricting is often viewed as a morally defensible mechanism for enhancing the descriptive representation of historically disadvantaged groups. However, in Chicago’s Chinatown, community decision makers adopted different strategies for redistricting at the state and city levels. Civic leaders and nonprofit organizations consistently supported race-conscious redistricting, while business elites endorsed a unified legislative district at the state level but opposed the creation of the city’s first Asian-majority ward. Through a case study of Chicago’s Chinatown, this paper argues that redistricting outcomes are shaped by a tension between the moral imperatives of racial representation and the practical interests of political and economic actors. State-level redistricting in Illinois was driven primarily by partisanship, with Democrats using Chinatown symbolically to advance reforms that consolidated partisan advantage, creating an opening for a unified state legislative district. By contrast, Chicago’s city-level redistricting was more vulnerable to personalized politics and transactional relationships between powerful elected officials and business elites, prioritizing economic development over creating an Asian-majority ward that might disrupt existing coalitions. The study contributes to the literature on descriptive representation and Asian American politics by showing how political scale and institutional context shape the strategies of ethnic community decision makers.

ABSTRACT Throughout the COVID‐19 pandemic, militaries mobilized at an unprecedented scale to support domestic response efforts. This was consistent with the growing trend of asset mobilization for military operations other than war during public health emergencies. However, the global scale and vast breadth of civil‐military cooperation invites new considerations regarding the authority and scope of domestic operations of militaries during public health emergencies. We aimed to identify how each UN member state codifies their military's roles and responsibilities in domestic emergencies. We systematically analyzed each nations' domestic military deployment, focusing on the authority, execution and scope of military involvement pertaining to domestic public health emergencies. We then analyzed legally enforceable policies and categorized them respectively. We found that of countries with active military forces, nearly all (170/171) have codified rules on domestic military deployment and 90.59% (154/170) allow domestic military mobilization for any domestic emergency through executive orders. Furthermore, 58.48% (100/171) of countries with an active military have codified the separation of powers to ensure that civilian decision makers are exclusively empowered to mobilize military forces. Finally, we found that 74.85% (128/171) of countries included language that explicitly authorized military involvement in domestic operations, including support for public health emergency response and humanitarian operations. Our findings provide critical data for analyzing the relationship between military operations and public health outcomes. This will enable future research, including how specific domestic military deployment policies impact the effectiveness of military involvement in public health emergencies for population health and civil order.

Abstract Trust in artificial intelligence (AI) remains a central concern as autonomous systems become increasingly embedded in everyday life. This study investigates how users evaluate AI in two distinct roles—supportive decision aid vs. autonomous decision maker—across four societal domains: healthcare, finance, workplace decision-making, and education. Across all domains, participants reported substantially higher comfort with supportive AI, revealing a robust trust asymmetry in affective trust-related responses. We further examined whether individual differences, including personality traits, value orientations, demographics, and prior AI experience, predicted trust in either AI role. Experience with AI and openness-to-change emerged as meaningful predictors of trust in autonomous AI, suggesting that familiarity and value-driven dispositions shape acceptance of more independent systems. These findings underscore the importance of psychological mechanisms, such as exposure and value alignment, in shaping trust in AI and offer implications for the design of human-centered, trustworthy AI systems.

Decision-making problems in complex environments are often characterised by uncertainty, vagueness, and dynamically evolving information. In such contexts, decision makers may express hesitant and fluctuating evaluations over time, which cannot be adequately captured by classical hesitant fuzzy frameworks. To address this limitation, time-sequential hesitant fuzzy sets (TSHFSs) have been introduced as an effective tool for modelling temporal hesitancy. However, the development of information measures for TSHFSs, particularly entropy measures for quantifying uncertainty and deriving criteria weights, remains limited. In this paper, we propose a novel class of entropy measures for TSHFSs by constructing transformation mechanisms based on proximity-driven formulations derived from similarity structures. The proposed measures are developed using arithmetic and algebraic operators to capture the dispersion of information across time sequences, enabling a more refined representation of temporal uncertainty. These entropy measures are further integrated into a multi-criteria decision-making (MCDM) framework, where they are employed to determine criteria weights under incomplete information and combined with the TOPSIS method for ranking alternatives. The effectiveness of the proposed framework is validated through comparative analysis with existing TSHFS entropy measures and sensitivity analysis under varying decision conditions. The results demonstrate that the proposed measures maintain ranking consistency while providing improved discrimination and interpretability of alternatives. In particular, the framework effectively captures fluctuating hesitancy and enhances the robustness of decision outcomes in dynamic environments. The proposed approach contributes to the advancement of TSHFS-based decision analysis by offering a mathematically grounded and practically applicable entropy-driven framework for handling time-dependent uncertainty in complex decision-making problems.

BackgroundThe toxic unregulated drug supply in North America continues to produce high rates of drug deaths. In response, several harm reduction interventions have been introduced and/or expanded, including take-home naloxone (THN). Estimating the impact is challenged by a lack of complete reporting data.ObjectiveThe aim of this study was to estimate the impact of interventions on drug deaths in British Columbia from January 2019 to September 2024.MethodsWe extended on a Bayesian hierarchical Markov chain model of drug poisoning events including interventions for overdose prevention sites and opioid agonist treatment. The extended model uses the reported number of THN kits used and distributed and all kits shipped to sites. These data are incorporated into the likelihood to estimate THN kit use during an opioid poisoning event by region and site type. Simulation studies evaluated the model's performance.ResultsThe estimated probability of THN kit use during an opioid poisoning event was 42.98% (95% credible interval [CrI]: 41.12-44.84) for kits distributed from community sites and 13.41% (95% CrI: 12.57-14.40) for overdose prevention sites. Correctional centers, pharmacy, and emergency department THN kits all had the lowest probability of use at 0.12% (95% CrI: 0.11-0.13), 1.04% (95% CrI: 0.96-1.13), and 0.65% (95% CrI: 0.60-0.71), respectively. The combined rate of deaths averted was 1,294 (95% CrI: 1,138-1,438) per 100,000 persons who inject drugs, which represents 78% (95% CrI: 76-80) of potential deaths.ConclusionDespite the increasing toxicity of the illegal drug supply, harm reduction interventions including THN have had a large impact on the number of drug deaths. Estimates of the impact of THN based on reported use alone would greatly underestimate the total impact.HighlightsWe developed a novel Bayesian hierarchical model to estimate take-home naloxone (THN) kit use during opioid poisonings using incomplete but complementary program and surveillance data.The model provides site-specific and regional estimates of kit use, highlighting significant differences by site type and geography.Simulation studies show the model can estimate the probability of THN kit use under realistic data limitations, supporting its use in policy evaluation.Public health decision makers can use this method to better assess and optimize harm reduction programs when direct usage data are scarce.

The climate protection goals and regulatory mechanisms of the world’s leading economic powers are accelerating the transition towards electric cars. The most important cornerstone of the successful transition to electric based mobility and product sale is that the value expected and the value perceived by the customer are matched. For understanding these values, it’s unavoidable to examine that what kind of factors are influencing the decision making process of the potential e-car buyers. This study focuses on the influencing factors examined in the Visegrad (V4) countries with the methodology of the systematic literature review (SLR). The research question is: “What are the key factors affecting consumers’ decisions to purchase electric vehicles in Hungary, Poland, the Czech Republic, and Slovakia?” Beside of the research question, the following hypothesis is validated: “The same influencing factors play a role in the electric car purchasing decisions in the Visegrad countries.” The analysis also use the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) as theoretical lens for analyzing customer decision making process. Based on the research results, it can be concluded that in the Visegrad countries, the electric car purchase process is primarily influenced by the purchase price, the inadequacies of the charging infrastructure and the insufficient range of electric vehicles. Environmental awareness is present in the decision-making process, but it plays only secondary role. Despite the fact that there are numerous differences (e.g. country size, GDP, e-car purchase support policy, purchasing power parity etc.) between the Visegrad countries. As having conclusion, the observations enable us to formulate hypotheses regarding the key influencing factors of electric car purchase decision making process. It also helps us to understand these influencing factors and based on them, all of the stakeholders like car manufacturers and dealers, political decision makers, local governments etc. could modify their strategies and take actions to promote the transition to electric vehicles.

Rare diseases affect more than 400 million people globally with only a small number having currently approved treatments. Drugs for rare diseases (medications developed to treat conditions affecting small patient populations), which may include innovative drugs (medications with novel mechanisms/new active ingredients) can face access challenges as they are often found not to be cost-effective under conventional health technology assessment methods. In this review we provide a comprehensive and up-to-date understanding of challenges associated with the economic evaluation of innovative drugs for severe-rare diseases, and any proposed solutions and associated barriers to solution adoption. This review included searches of electronic databases and select health technology assessment agency websites to identify relevant publications, guidelines or recommendations from 1st January 2014 to 29th July 2024. A pre-authorised protocol, including detailed eligibility criteria, was used to ensure robust methodology in the capture of materials. Relevant data extracted from included publications were synthesised thematically to support identification of the most prominent concepts within current literature. Of the 1,803 records identified, 31 publications and eight health technology assessment guidance were included. Main challenges were related to the utilitarian principle underlying cost-effectiveness analysis, the limited scope of the quality-adjusted life year and the value elements assessed. Associated solutions included the incorporation of a societal willingness-to-pay or inclusion of equity in healthcare decision making, reduced weighting of the economic evaluation in resource allocation, consideration of additional value elements, and introducing a quality-adjusted life year weighting or alternative measures of health outcomes. While some payers have implemented modifications to economic evaluation guidelines in an attempt to address the challenges, for example including the consideration of additional value elements, the solutions employed are not consistent across payers and often do not address the root issue. Economic evaluation as part of health technology assessment therefore remains challenging for manufacturers of drugs for rare diseases. Conventional methods of economic evaluation contribute to the access challenge for innovative drugs for rare diseases. Collaboration between payers, manufacturers, and healthcare decision makers to foster greater understanding of how to evolve and adopt these novel solutions will be key to ensuring timely patient access.

ABSTRACT Greywater reuse is the most viable method for augmenting scarce freshwater resources worldwide. However, it is limited in Kuwait due to a lack of reliable information about its characteristics. This study characterised the light greywater (bathroom greywater) produced in residential apartments in Kuwait and evaluated its potential for potable water savings through reuse for toilet flushing. In the studied apartments, the production rate of light greywater was found to be considerably high, accounting for approximately 50% of potable water consumption. The treatment of light greywater using a simple physicochemical system (sand filtration, carbon filtration, and ultraviolet disinfection) produced water that satisfied the WHO standards for toilet flushing. Reusing treated light greywater for toilet flushing only saved approximately 9% of a household’s potable water consumption, underscoring its potential for other domestic applications to achieve greater potable water savings. This information can help decision makers develop strategic plans for greywater reuse.

ABSTRACT Biodiversity loss is a major environmental challenge, and limited resources require conservation actions to be strategically prioritized. Buenos Aires Province, Argentina, is one of the most transformed, with over 60% of its territory altered by agriculture and urbanization and only 5% formally protected. This study identifies priority areas for the conservation of terrestrial and freshwater vertebrates in the province. We compiled extent of occurrence maps for all native vertebrate species using IUCN assessments, national red lists, field surveys, and biodiversity databases. Distributions were mapped across the 135 districts that serve as administrative units. To estimate conservation importance, species were weighted by threat status and endemism, and potential ranges were delineated under the precautionary principle. The province hosts 708 vertebrate species: birds (55%), freshwater fish (22%), mammals (11%), reptiles (8%), and amphibians (4%). Ten are strict endemics, and many are threatened. We identified 18 districts with high species richness and 15 with the highest conservation priority, concentrated in the Paraná Delta, the Atlantic coast, and the Ventania and Tandilia highlands. Our results provide an updated, province-wide assessment to support decision makers in developing conservation strategies. Strengthening connectivity, safeguarding freshwater ecosystems, and fostering science–policy–community strategies will be crucial.

Bioinvasions are considered mostly as a biodiversity and conservation hazard, but in specific situations, introduced species can bring ecological or socioeconomic benefits. We assessed the social-ecological role of marine introduced species in the eastern Mediterranean Sea-a global hotspot of bioinvasions and extirpations-and their potential relevance for achieving conservation and sustainability targets set by the Kunming-Montreal Global Biodiversity Framework (GBF). The adverse effects of introduced species include predation and competition with native species, alteration of food webs, habitat degradation, disruption of fisheries and coastal infrastructure, and risks to human health. Their beneficial effects on biodiversity, ecosystem functions, and services include the creation of novel habitats, trophic support for native species, partial functional compensation for declining native taxa, and substantial contributions to fisheries production and food provision. These effects can co-occur and generate trade-offs. Conservation practice should move beyond rigid origin-based assumptions and explicitly account for the context-dependent impacts of introduced species, particularly in regions where native biodiversity and associated functions are rapidly declining due to ocean warming. Introduced species considerations need to be integrated in conservation planning to meet the goal of protecting 30% of the land, sea, and inland waters (GBF Targets 1 and 3) and to sustain ecosystem services, such as food provision, through fisheries (GBF Targets 10 and 11) amid rapid climate change. Incorporating the positive and negative aspects of introduced species into systematic conservation planning can optimize conservation investments through transparent trade-off analyses. By adopting a pragmatic, holistic approach to conservation that recognizes the varied and dynamic roles of introduced species, decision makers can more effectively achieve the GBF conservation and sustainability targets in the eastern Mediterranean.