Search Results (1,492)

Animals with knockout of the dopamine transporter gene (DAT-KO) display hyperdopaminergic phenotypes, including attention-deficit/hyperactivity-like behaviors. A previous behavioral analysis of heterozygous rats with partial knockout (DAT-HET) suggested increased susceptibility to addictive behaviors. The aim of this study was to investigate elements of addictive behaviors and the mechanisms underlying dopamine release in DAT-HET rats. Offspring derived from DAT-knockout breeding underwent genotyping and behavioral assessment using the marble burying test, a manipulative behavior test using nesting material, and a modified version of the Iowa Gambling Task. Feeding behavior was studied using a binge-eating model. Reinforcing properties were investigated using intracranial self-stimulation under fixed-ratio (FR) and variable-ratio (VR) schedules. Dopamine (DA) release and clearance dynamics were assessed using fast-scan cyclic voltammetry (FSCV). DAT-HET rats exhibited moderate hyperactivity, increased impulsive choice, and compulsive responses. Male DAT-HET rats also showed increased compulsive overeating compared with wild-type (WT) rats of both sexes and female DAT-HET rats. In addition, DAT-HET rats demonstrated a preference for VR self-stimulation, which resembles risk- and thrill-seeking behavior in humans. In DAT-KO rats, impaired DA clearance resulted from complete loss of dopamine transporter function. In DAT-HET rats, increased DA release amplitude was observed, and dopamine persisted longer in the extracellular space than in WT rats. These findings underscore the importance of the DAT-HET model for studying impulsivity, compulsivity, and factors underlying the predisposition to addictive behavior. Full article

Urban healthcare systems are fundamentally constrained by the mismatch between static resource configurations and dynamically evolving patient demand. Under the tiered healthcare system, traditional static planning methods struggle to capture the complexity and randomness of patient flows. While recent reinforcement learning (RL) approaches enable adaptive decision-making, they suffer from dimensionality explosion and unstable convergence due to massive action spaces and delayed spatiotemporal credit assignment in city-scale environments. To address this gap, we propose Twin–Game: a digital twin-driven hierarchical reinforcement learning (HRL) framework that formulates adaptive healthcare resource optimization as a “Twin Game” between a simulation-based game environment (Strategic Sandbox) and a hierarchical decision policy. First, we construct the “first twin”—an offline digital twin that serves as the Strategic Sandbox parameterized with Wuhan’s observed facility, population, and transportation data, while patient arrivals and disease profiles are generated synthetically under documented assumptions because individual-level clinical flow data are not publicly available. This environment integrates a dynamic gravity model with a two-way referral mechanism to represent the nonlinear coupling between hospital attractiveness, crowding levels, and patient choice behaviors. Second, we build the “second twin”—an Option-based HRL policy. The Manager (Macro-level Strategic Layer) uses a Deep Q-Network (DQN) for discrete spatial attention allocation; the Worker (Micro-level Execution Layer) uses Proximal Policy Optimization (PPO) for continuous, fine-grained controls such as bed expansion ratios and personnel scheduling. The two twins interact in a closed-loop game, performing strategy search and game evolution under complex constraints to optimize allocation. Experimental results from the Wuhan case indicate that the Twin–Game framework outperforms static baselines and single-layer RL in reducing average travel times, enhancing resource utilization, and improving tiered diagnosis and treatment within the simulation setting. The results should be interpreted as simulation-based decision-support evidence rather than direct clinical validation. This study provides a data-driven, game-theoretic decision support tool for building resilient urban healthcare systems. Full article

Copulas are widely used in financial economics, as well as in other areas of applied mathematics. Yet, there is much arbitrariness in their choice. The author proposes a “natural copula” concept that minimizes the Wasserstein distance between distributions in a space in which both distributions are embedded. Transport properties and hydrodynamic interpretation are discussed with two examples of distributions of financial significance. In 2D, a natural copula can be parsimoniously estimated by linear programming methods. A discussion of the construction of multivariate copulas follows. Finally, the quality of the multivariate copula approximation is investigated using the Kolmogorov–Arnold neural network (KAN). Full article

Medium-sized cities in the Global South are at the center of future urban growth, yet their transportation systems remain dominated by car-dependent trajectories. This paper examines how urban infrastructure shapes inclusive access to active commuting using a latent class model across three Mexican cities. We identify two distinct commuter environments defined by infrastructure quality. In low-infrastructure settings, active commuting is concentrated among younger men, consistent with existing literature. In contrast, in high-infrastructure environments, the baseline probability of active commuting is nearly three times higher, so that women and older individuals commute actively at substantially higher absolute rates even though demographic penalties remain present in both environments. Attitudinal variables, often emphasized in policy discourse, are not significant predictors of mode choice. These findings suggest that infrastructure investment is not only a tool for increasing active commuting rates but also a mechanism for expanding mobility access across demographic groups. For rapidly growing medium-sized cities, prioritizing non-motorized infrastructure can play a central role in building inclusive, low-carbon transportation systems. Full article

Shopping mobility accounts for a significant share of total travel, while the growth of e-commerce is reshaping consumer purchasing behaviour and retail dynamics. Comprehending how territorial and sociodemographic factors shape the choice between physical and digital retail channels is therefore a key issue for transport planning and sustainable urban mobility. In this context, it is important to understand how accessibility to different classes of retailers is configured and how it can impact purchasing choices. Through a discrete choice analysis, this study examines the sociodemographic and territorial determinants of purchasing behaviour, focusing on the clothing market. Four purchase alternatives are considered: medium-sized and small urban retail stores, shopping malls, online purchasing, and no purchase. This multi-alternative framework enables the direct estimation of substitution patterns not only between physical and digital retail, but also between distinct forms of physical retail. Data were collected through a survey conducted in Southern Italy, providing empirical evidence from a territorial setting that is structurally underrepresented in the existing literature. A multinomial logit model and a two-level hierarchical logit model incorporating pedestrian accessibility—measured as walking time from residence to the nearest clothing store—alongside sociodemographic and territorial attributes were calibrated to analyse alternative choice behaviour. The calibrated models show interesting results, highlighting the role of pedestrian accessibility in the choice of clothing stores in city centres. Age, income, and territorial variables further differentiate channel preferences across population segments. The findings offer relevant implications for policymakers, governance managers, urban planners, and researchers concerned with retail location, sustainable accessibility, and consumer behaviour. These insights are highly valuable for developing planning that addresses the United Nations 2030 Agenda, particularly Sustainable Development Goal 11. Full article

This article reviews the linear solvers available in OpenFOAM and assesses their impact on the convergence behaviour of the SIMPLE algorithm. The discretisation of transport equations in CFD results in large and sparse linear systems, for which the choice of linear solver strongly influences the computational time. Although the solver does not change the final discrete solution, the difference in speed and robustness between the solvers can be more than one order of magnitude. A brief overview is given concerning how the velocity and pressure fields are decoupled in OpenFOAM, followed by a detailed review of the main linear solver families, including direct methods, basic iterative methods, multigrid methods and Krylov subspace methods, with attention to their practical strengths and weaknesses. The performance of the most advanced solvers is evaluated on a full-scale non-reacting kiln case consisting of 2.3 million cells. The pressure-corrector equation is identified as the main bottleneck in the SIMPLE algorithm. The conjugate gradient (CG) solver with a multigrid (MG) preconditioner is found to be the fastest and most stable method, achieving speed-ups of up to a factor of 7 compared to the slower advanced methods. Using MG as a preconditioner also improves the robustness of the Bi-CGStab method. Full article

To address the global water crisis, desalination technologies contribute about 1% of the global freshwater supply. Membrane-based desalination technologies offer high performance, operational ease, cost-effectiveness and high scalability compared to conventional thermal desalination modes. Among all membrane-based technologies, reverse osmosis is prevailing globally. However, the high energy demand of the reverse osmosis process and fouling in case of hypersaline feed streams motivate the exploration of alternative technologies, i.e., pervaporation. Pervaporation desalination involves dense hydrophilic polymer membranes to deal with high salt streams at low cost, along with less fouling than a few other membrane processes, i.e., reverse osmosis and membrane distillation. Mass transport through pervaporation desalination membranes is well-explained by solution-diffusion theory involving a tri-stage transfer, i.e., sorption, diffusion and evaporation. Since the last few decades, a green approach in all domains has offered chemical products and processes with the least hazards and minimal waste production. Application of biodegradable materials like poly(lactic acid) in combination with suitable green solvents, e.g., ethyl lactate, methyl lactate, cyrene, dimethyl isosorbide and gamma valerolactone for pervaporation desalination would be a good roadmap to meet the sustainability criterion. Some intrinsic features of poly(lactic acid) that make it a ‘material of choice’ for pervaporation desalination include hydrophilicity imparted by the presence of polar ester groups, high salt rejection, biodegradability with simple mineralization products, i.e., H₂O and CO₂, sustainable production, low toxicity, low carbon footprint, ease of processing and versatility. Poly(lactic acid) undergoes four interrelated degradation mechanisms: hydrolytic degradation, biodegradation, thermal degradation and photodegradation. The concern for poly(lactic acid) based pervaporation desalination is increased hydrolytic cleavage of poly(lactic acid) at high temperatures, which requires some modifications, e.g., nanoenhancement, additions of crosslinkers, surface modifications, addition of other polymers to prepare blends and post-treatments. These modifying strategies result in an increased stability and better performance of poly(lactic acid) films. However, optimization of various parameters relevant to such modifications leaves room for further research. This review offers a critical analysis of the need for biodegradable polymers with special focus on poly(lactic acid) rather than their fossil fuel-based alternatives, the environmental and health effects of all these polymers, cost estimation and possible performance-efficient, green and eco-friendly solutions. Full article

Background and Objectives: Muscle symptoms are the most visible adverse event attributed to statins, but terminology is often imprecise. Most patients report myalgia or nonspecific aches, whereas objective myopathy, inflammatory or necrotizing myositis, rhabdomyolysis, and anti-HMGCR immune-mediated necrotizing myopathy are uncommon and clinically distinct entities. To provide a clinically oriented narrative synthesis of statin-associated muscle symptoms (SAMS) and severe statin-associated myotoxicity, and to propose a practical prevention, evaluation, and management algorithm. The classification of muscle events is used to standardize terminology and avoid diagnostic confusion, not to create a new formal taxonomy. Materials and Methods: A clinically oriented narrative review was performed using PubMed, Google Scholar, and major society documents published from January 2021 to April 2026. Eligible sources addressed SAMS, statin myopathy/myositis, rhabdomyolysis, anti-HMGCR immune-mediated necrotizing myopathy, nocebo/drucebo effects, pharmacogenetics, drug interactions, diagnosis, or management. The final evidence set comprised 55 verifiable sources, including blinded randomized or n-of-1/crossover evidence; meta-analyses; clinical statements and reviews; pharmacovigilance analyses; pharmacogenetic guidance; mechanism-focused reviews; anti-HMGCR series; and lipid-lowering guideline/treatment studies. Because the review was narrative, no pooled estimate or formal PRISMA screening log was generated. Results: Blinded evidence indicates only a small absolute excess of muscle pain with statins, concentrated mainly in the first year of therapy, and that most muscle symptoms reported during statin therapy are not pharmacologically caused by the statin. N-of-1 and crossover trials show that symptom intensity is often similar during statin and placebo periods, consistent with an important nocebo/drucebo contribution. Severe muscle toxicity can nevertheless occur, especially when systemic statin exposure is increased by a high dose, interacting drugs, frailty, renal or hepatic impairment, hypothyroidism, transporter or metabolic genotypes, or intense unaccustomed exercise. Statin choice matters chiefly through dose, pharmacokinetics, and interaction burden. Conclusions: SAMS are common as reported clinical problems, but confirmed statin-caused muscle injury is substantially less frequent than routine clinical attribution suggests. Permanent discontinuation should be reserved for carefully assessed cases. A structured approach—baseline risk assessment, selective CK measurement, exclusion of alternative causes, correction of modifiable risks, dechallenge/rechallenge, statin switching, dose reduction, and combination with non-statin therapy—preserves cardiovascular benefit while protecting the rare patient with genuine toxicity. Full article

Background: Battery Electric Vehicles (BEVs) are often proposed as a promising solution to increase sustainability in the transport sector. Whilst BEVs may solve some of the negative effects of traffic problems in cities, those models predominantly sold nowadays do not alleviate, among other things, congestion or parking pressure in cities, and may not offer the most affordable mode of transport available. Methods: The effective accessibility levels provided by BEVs and quadricycles (i.e., L6e and L7e) were compared in England and Wales. Effective accessibility not only includes driving time as an impedance but also accounts for the hours required to earn the funds to pay for the commute. Results: The lower speeds of L6e and L7e quadricycles certainly limits the number of jobs reachable when compared to a BEV in a time-based accessibility comparison. However, once the time spent at work is taken into account, then L6e and L7e quadricycles often win the ‘competition’—especially for people with modest means. Conclusions: This study shows that for some, commuting by BEV is the most time-efficient mode of transport. For individuals constrained by time or income, L6e and L7e quadricycles may serve as a more expedient choice of travel. Full article

The global transition to electric mobility is crucial for reducing transportation-related emissions, although there is a scarcity of empirical research on customer adoption psychology in transition economies in Central Asia. This study investigates the economic and structural drivers of electric vehicle purchase intention in the Republic of Uzbekistan. Data collected from prospective customers across large city hubs were analyzed using a dual hierarchical multiple linear regression model, supported by an empirical bootstrapping procedure with 2000 resamples, based on the rational choice theory and bounded rationality. The structural model shows that baseline socio-demographics explain insignificant initial variance ($R^2$ = 0.105); however, the integration of primary theoretical constructs yields a significant incremental variance change ($\Delta R^2$ = 0.096), explaining 20.1% of the total variance. Inferential tracking confirms that government incentives are the only statistically significant driver of the purchase intention (p = 0.009). Conversely, purchase cost (p = 0.251) and charging infrastructure (p = 0.475) lack direct significance. However, partial collinearity and infrastructure expectation effects systematically change these localized contact points. The study concludes that consumer intent in this emerging marketplace is primarily anchored to macro-level institutional policy signaling rather than immediate vehicle-specific characteristics or current physical network constraints. Full article

Why are essential workers (also known as key workers) priced out of the urban areas where essential services are concentrated? This paper addresses that question by linking residential sorting to the governance of land and housing markets in Auckland, New Zealand. Drawing on bid rent theory and motivated by Crane’s theoretical framework, this study examines how households trade off urban accessibility against housing costs with varying degrees of job location uncertainties and time pressure. The analysis uses the micro-level household data from Statistics New Zealand (Stats NZ)’s Integrated Data Infrastructure (IDI) to examine how key-worker households position themselves within the city’s rental market relative to other working households. The results show a clear urban land rent gradient: rents fall with distance from the city centre. However, access to the central location is not evenly distributed across workers. Key workers, whose jobs are typically tied to more fixed workplaces, are more inclined to live farther from the city centre to lower housing costs. By contrast, workers facing tighter time constraints, especially those working longer hours, show a stronger preference for living near the CBD to improve work proximity and reduce commuting burdens. This pattern remains evident among private vehicle commuters, suggesting that time pressure, rather than transport mode alone, is an important factor shaping residential location choice. The paper argues that this is not simply a housing market outcome but also a land-governance problem. When central land values rise without corresponding housing options for key workers, cities risk pushing socially necessary labour towards peripheral areas. The findings highlight the need for land-use and housing interventions that improve the spatial match between where key workers live and where urban services are most needed. Full article

This review presents a process-based decision-making framework for chlorinated vapor intrusion (CVI) mitigation. CVI mitigation refers to the set of engineered strategies aimed at interrupting, attenuating or transforming vapor fluxes before they reach indoor environments. Existing literature and technical guidelines typically classify mitigation strategies according to technological configuration (active versus passive), rather than physical and chemical processes governing vapor transport and attenuation, which may lead to suboptimal design choices and reduced system resilience. To address this limitation, this framework proposes a process-based classification of CVI mitigation strategies based on the dominant mechanisms controlling vapor migration in subsurface. Five mechanistic categories are identified: driving-force control through pressure manipulation, dilution via air exchange, diffusive flux control through physical barriers, density-driven attenuation in permeable sub-slab layers, and in situ transformation based on sorption or degradation. By explicitly linking mitigation technologies to transport and transformation processes, the proposed framework provides a structured basis for mechanism-oriented selection, integrating performance, longevity, climate resilience, and lifecycle energy demand. In addition to established mitigation approaches, such as sub-slab depressurization, this work highlights emerging passive strategies, including high permeable granular layers and horizontal reactive or adsorbing barriers, as potential low-energy alternatives for durable management. Overall, the proposed framework supports site-specific, sustainability-oriented decision-making on CVI mitigation. Full article

Background: Health accessibility is a key determinant of equitable cancer care. In many countries, specialized oncology services are concentrated in urban and socioeconomically advantaged regions, forcing many patients to travel long distances for treatment. Consequently, geographic and social characteristics may be impactful in determining cancer healthcare outcomes. Objective: The aim of this study was to evaluate the association between the municipal-level Social Progress Index (SPI) and geographic travel burden, stage at diagnosis, treatment, and survival in patients with pancreatic cancer in São Paulo state, Brazil. Methods: We conducted a population-based study using data from “Fundação Oncocentro” on adults with pancreatic adenocarcinoma (2005–2025). The SPI (0–100 scale), a composite measure of municipal social and environmental development, was the primary exposure. It is structured into 3 dimensions and 12 components: Basic Human Needs (nutrition, medical care, water and sanitation, housing, safety); Foundations of Well-being (education, information access, health, environmental quality); and Opportunity (rights, freedom of choice, social inclusion, higher education). Municipal residence and cancer center locations were geocoded, and travel distance (km) was estimated. Multivariable Cox, logistic, and linear regression models assessed associations between SPI and overall survival, stage IV at diagnosis, surgery, and travel distance. Results: A total of 13,478 patients were included (mean follow-up 15.1 ± 27.2 months; mean age 62.3 years; 50.4% male). Stage IV disease was frequent (46.3%), and surgery was performed in 33% of cases. Over half of patients (53.2%) traveled more than 10 km for treatment. Increasing SPI was strongly associated with shorter travel distance (β −62.6 km per SPI unit; p < 0.001) and higher odds of surgery (OR 1.04; p < 0.001) and remained independently associated with a higher likelihood of undergoing surgical treatment (adjusted OR 1.04; p < 0.001). The proportion of stage IV disease did not decrease with increasing SPI and was slightly higher in the highest quartile (49.3%). In survival analysis, SPI demonstrated a protective effect in univariate modeling (HR 0.987; p < 0.001), but lost significance in multivariable analysis (p = 0.125). Travel burden was not retained as an independent predictor of survival after adjustment. Conclusions: Municipal-level SPI was a strong determinant of healthcare access and the likelihood of receiving surgical treatment for pancreatic cancer. Social and geographic vulnerability directly influence care pathways, revealing structural inequities in access to treatment. SPI-based stratification may serve as a practical tool to identify priority regions for transport support and equitable allocation of oncology services. Full article

Background: Live-streaming e-commerce has emerged as a significant retail channel, especially in the apparel industry, characterized by high impulse-driven purchase rates and elevated product returns. Reverse logistics processes associated with these returns generate considerable environmental impacts that require systematic evaluation. Methods: This study performs a gate-to-gate Life Cycle Assessment (LCA) using SimaPro software, with a functional unit of 1 kg for one pair of returned jeans. Secondary inventory data were obtained primarily from the Ecoinvent database and supplemented with literature-based estimates for transport distances and packaging masses. Results: Key hotspots analyzed include transportation modes, packaging materials, and waste disposal pathways. Transportation mode selection was the dominant environmental hotspot, with air freight exhibiting the highest impacts across most midpoint and endpoint categories. Low-density polyethylene (LDPE) packaging and landfill disposal of textile waste were also major contributors to global warming, ozone formation, and resource depletion. Conclusions: The findings underscore the necessity of integrating Circular Supply Chain (CSC) principles into reverse logistics network design for live-streaming platforms. Optimizing transportation modes and packaging choices can effectively balance operational responsiveness with environmental sustainability. This study offers empirical evidence and practical decision-supporting insights for more sustainable return management in high-return digital retail environments. Full article

High-density commercial interchange hubs are important components of transit-oriented urban regeneration. However, high passenger flow does not necessarily generate sustained underground-space vitality. This study examines the Licun high-density commercial interchange hub in Qingdao, China. It explores how amenity supply influences sustainable underground-space vitality through user behavioral responses. Based on 426 valid questionnaire responses, an amenity evaluation system was developed across five dimensions. These dimensions include natural-environment, facility-and-service, consumption-experience, socio-cultural, and transport-connection amenities. The entropy weight method was used to identify the perceptual differentiation of amenity indicators. PLS-SEM was then applied to examine the pathway of “amenity supply–user behavioral response–underground-space vitality.” The results show that natural-environment amenities present the strongest perceptual differentiation, while facility-and-service amenities play a fundamental role in supporting user behavioral responses. Consumption-experience amenities promote visit choice, stay duration, and satisfaction, but may weaken interaction and participation, indicating a potential tension between commercial vitality and public interaction. Transport-connection amenities mainly affect visit choice rather than sustained use. Among user behaviors, stay duration, interaction and participation, and satisfaction feedback are positively associated with underground-space vitality, whereas simple visit choice is not. These findings suggest that sustainable vitality in a high-density commercial interchange hub should not be understood as passenger volume alone. It should be understood as the transformation of transit flow into voluntary stay, interaction, satisfaction, and repeated use. This study contextualizes amenity theory in a high-density commercial interchange hub. It also offers planning implications for underground-space regeneration. Full article