Search Results (704)

This study investigates a novel heat pipe integrated cooling system designed for thermal management of Tesla’s 4680 cylindrical lithium–ion batteries in electric vehicles (EVs). Through a comprehensive approach combining experimental analysis, 1-D AMESim simulations, and 3-D Computational Fluid Dynamics (CFD) modeling, the thermal performance of various wick structures and working fluid filling ratios was evaluated. The experimental setup utilized a triangular prism chamber housing three surrogate heater blocks to replicate the heat generation of 4680 cells under 1C, 2C, and 3C discharge rates. Results demonstrated that a blended fabric wick with a crown-shaped design (Wick 5) at a 30–40% filling ratio achieved the lowest maximum temperature (T_max of 47.0°C), minimal surface temperature deviation (ΔT_surface of 2.8°C), and optimal thermal resistance (R_th of 0.27°C/W) under 85 W heat input. CFD simulations validated experimental findings, confirming stable evaporation–condensation circulation at a 40% filling ratio, while identifying thermal limits at high heat loads (155 W). The proposed hybrid battery thermal management system (BTMS) offers significant potential for enhancing the performance and safety of high-energy density EV batteries. This research provides a foundation for optimizing thermal management in next-generation electric vehicles. Full article

Background/Objectives: Myelofibrosis (MF) is a myeloproliferative neoplasm characterized by the replacement of healthy bone marrow (BM) with malignant and fibrotic tissue. In a healthy state, bone marrow is composed of approximately 60–70% fat cells, which are replaced as disease progresses. Proton density fat fraction (PDFF), a non-invasive and quantitative MRI metric, enables analysis of BM architecture by measuring the percentage of fat versus cells in the environment. Our objective is to investigate variance in quantitative PDFF-MRI values over time as a marker of disease progression and response to treatment. Methods: We analyzed existing data from three cohorts of mice: two groups with MF that failed to respond to therapy with approved drugs for MF (ruxolitinib, fedratinib), investigational compounds (navitoclax, balixafortide), or vehicle and monitored over time by MRI; the third group consisted of healthy controls imaged at a single time point. Using in-house MATLAB programs, we performed a voxel-wise analysis of PDFF values in lower extremity bone marrow, specifically comparing the variance of each voxel within and among mice. Results: Our findings revealed a significant difference in PDFF values between healthy and diseased BM. With progressive disease non-responsive to therapy, the expansion of hematopoietic cells in BM nearly completely replaced normal fat, as determined by a markedly reduced PDFF and notable reduction in the variance in PDFF values in bone marrow over time. Conclusions: This study validated our hypothesis that the variance in PDFF in BM decreases with disease progression, indicating pathologic expansion of hematopoietic cells. We can conclude that disease progression can be tracked by a decrease in PDFF values. Analyzing variance in PDFF may improve the assessment of disease progression in pre-clinical models and ultimately patients with MF. Full article

Traditional Chinese Kang heating systems have been used for over two millennia in northern China, yet their thermal efficiency and optimal design parameters lack scientific validation. This study aims to establish evidence-based guidelines for Kang-to-room area ratios to enhance thermal comfort and energy efficiency in rural architecture. We conducted direct measurements in a controlled experimental house (24 m²) in Huludao City, collecting temperature and humidity data from Kang surfaces and interior spaces over five-day periods. A benchmark curve for heat flux density was developed based on specific fuelwood consumption rates (1 kg/m²). TRNSYS simulations were employed to validate experimental data and analyze thermal performance in the historical Qingning Palace (352 m²) at Shenyang Imperial Palace. The benchmark curve demonstrated high accuracy with a Mean Absolute Error of 0.46 °C and Root Mean Square Error of 0.53 °C when compared to measured temperatures over the 48 h validation period; these values are well within acceptable ranges for calibrated thermal models. Simulations revealed optimal thermal comfort conditions when heat dissipation parameters were scaled appropriately for building size. The optimal Kang-to-room area ratio ranges from 0.28 to 0.69, with the existing Qingning Palace ratio (0.34) falling within this range, validating traditional design wisdom. This research provides a scientific foundation for sustainable architectural practices, bridging traditional knowledge with contemporary thermal engineering principles for both heritage preservation and modern rural construction applications. Full article

The Centers for Diseases Control (CDC) light trap is widely used for malaria vector surveillance, but its acquisition logistics pose challenges in Africa. Evaluating new traps can improve surveillance tools. This study compared the efficiency of the BG-Pro UV and Silver Bullet 2.1 UV (SB 2.1 UV) against the UV LED CDC trap in western Kenya’s rice irrigation area. The traps were tested indoors in eight houses over 64 nights. Light properties and fan speed were analyzed using spectrometry and an anemometer. The BG-Pro UV trap performed better than the UV LED CDC trap for An. gambiae s.l. (RR 2.0, 95% CI 0.9–3.9) and An. funestus s.l. (RR 3.5, 95% CI 1.9–6.4). The SB 2.1 UV trap was more effective in capturing An. gambiae s.l. (RR 4.3, 95% CI 2.5–7.3) and An. funestus s.l. (RR 7.1, 95% CI 3.9–13.1), and also caught three times more Culex spp. (RR 2.7, 95% CI 1.2–6.0). SB 2.1 UV had the highest downstream force, and all traps emitting UV-A light had consistent wavelengths. Overall, the BG-Pro and SB 2.1 traps’ trapping efficiency was three to six times more than the CDC trap, making them promising surveillance tools, particularly in low-density malaria settings. Full article

As shared micromobility grows quickly in metropolitan settings, e-scooter safety issues have become more urgent. This paper uses a Bayesian hierarchical model applied to census block groups in several Texas metropolitan areas to construct a spatial risk assessment methodology for e-scooter crashes. Based on crash statistics from 2018 to 2024, we develop a severity-weighted crash risk index and combine it with variables related to land use, transportation, demographics, economics, and other factors. The model comprises a geographically structured random effect based on a Conditional Autoregressive (CAR) model, which accounts for residual spatial clustering after capture. It also includes fixed effects for covariates such as car ownership and nightlife density, as well as regional random intercepts to account for city-level heterogeneity. Markov Chain Monte Carlo is used for model fitting; evaluation reveals robust spatial calibration and predictive ability. The following key predictors are statistically significant: a higher share of working-age residents shows a positive association with crash frequency (incidence rate ratio (IRR): ≈1.55 per +10% population aged 18–64), as does a greater proportion of car-free households (IRR ≈ 1.20). In the built environment, entertainment-related employment density is strongly linked to elevated risk (IRR ≈ 1.37), and high intersection density similarly increases crash risk (IRR ≈ 1.32). In contrast, higher residential housing density has a protective effect (IRR ≈ 0.78), correlating with fewer crashes. Additionally, a sensitivity study reveals that the risk index is responsive to policy scenarios, including reducing car ownership or increasing employment density, and is sensitive to varying crash intensity weights. Results show notable collision hotspots near entertainment venues and central areas, as well as increased baseline risk in car-oriented urban environments. The results provide practical information for targeted initiatives to lower e-scooter collision risk and safety planning. Full article

With the rapid advancement of urbanization, the increasing demand and insufficient supply of public service facilities for children have become urgent problems requiring resolution. This study employs the Shannon diversity index, the location entropy, spatial autocorrelation, and the Geographically Weighted Regression (GWR) to analyze the spatial distribution characteristics and influencing factors of children’s public service facilities in the central urban area of Shenyang. The findings of the study are as follows: (1) There are significant differences in the spatial distribution of children’s public service facilities. Higher quantity distribution and diversity index are observed in the core area and Hunnan District compared to the peripheral areas. The Gini coefficient of various facilities is below the fair threshold of 0.4, but 90.32% of the study units have location entropy values below 1, indicating a supply–demand imbalance. (2) The spatial distribution of various facilities exhibits significant clustering characteristics, with distinct differences between high-value and low-value cluster patterns. (3) The spatial distribution of facilities is shaped by four factors: population, transportation, economy, and environmental quality. Residential area density and commercial service facility density emerge as the primary positive drivers, whereas road density and average housing price act as the main negative inhibitors. (4) The mechanisms of influencing factors exhibit spatial heterogeneity. Positive driving factors exert significant effects on new urban areas and peripheral zones, while negative factors demonstrate pronounced inhibitory effects on old urban areas. Non-linear threshold effects are observed in factors such as subway station density and public transport station density. Full article

China’s rapid urbanization has given rise to the phenomenon of “urban villages”, which are often regarded as chaotic fringe areas in traditional studies. With the rise of the concept of resilient cities, the value of urban villages as potential carriers of sustainable development has been re-examined. This study adopted research methods such as field investigations, in-depth interviews, and conceptual sampling. By analyzing the interlinked governance relationship between Xiamen City and the urban villages in the Bay Area, aspects such as rural housing improvement, environmental governance, residents’ feedback, geographical pattern, and spatial production were evaluated. A field investigation was conducted in six urban villages within the four bays of Xiamen. A total of 45 people in the urban villages were interviewed, and the spatial status of the urban villages was recorded. This research found that following: (1) Different types of urban villages have formed significantly differentiated role positionings under the framework of regional governance. Residential community types XA and WL provide long-term and stable living spaces for migrant workers in Xiamen; tourism development types DS, HX, BZ, and HT allow the undertaking of short-term stay tourists and provide tourism services. (2) These urban villages achieve the construction of their resilience through resisting risks, absorbing policy resources, catering to the expansion of urban needs, and co-construction in coordination with planning. The multi-cultural inclusiveness of urban villages and their transformation led by cultural shifts have become the driving force for their sustainable development. Through the above mechanisms, urban villages have become the source of resilience and sustainability of healthy cities and provide a model reference for high-density urban construction. Full article

Environmentally modified housing [EMH; windowless, insulated sidewalls and ceiling, thermostatically controlled ventilation fans) versus conventional housing [CVH; cross-ventilated, insulated ceiling, ceiling fans) improved broiler performance in the summer. The objective of this investigation was to determine whether social behaviors differed between two population densities (0.06 m²/chick [HD] or 0.07 m²/chick [LD]) in these houses. We used a randomized block statistical design, involving houses, population densities, observation times, and bird age. Behaviors were observed weekly, during the morning and the afternoon. Individual observers focused on the group of broilers in one of three defined 26.76 m² areas in each of the four pens in each house. Aggressive encounters, tail and back pecking, feather eating, thermoregulatory, preening, and flock mobility were recorded. Feather pecking, eating and aggressive encounters were expressed at greater rates in HD birds in CVH. A salt-deficient diet caused increased feather pecking and aggressive encounters, which decreased after correction of the mistake. Increased heat indices (HIs), HD, and greater light intensity in CVH influenced behaviors and mortality more severely than in EMH. In CVH and EMH, burrowing/thermoregulatory/resting activity increased with increasing HIs. Afternoon preening was elevated significantly in EMH. It was concluded that broilers reared in EMH were more comfortable and experienced improved welfare compared to those reared in CVH. Full article

Although the benefits of rational grazing by polygastric animals are well known, little is understood about how chicken grazing affects soil biological health and its capacity to store organic matter. This study aimed to assess the impact of long-term free-range chicken grazing in an olive grove on the soil chemical and biochemical properties, including the total organic carbon (TOC), total nitrogen (TN), microbial biomass (Cmic), basal respiration, and microbial community structure, as well as the soil’s capability to stock organic carbon and total nitrogen. A field experiment was conducted in an olive grove grazed by chickens for over 20 years, with the animal load decreasing with distance from the poultry houses. At 20 m, where the chicken density was highest, the soils showed reduced OC and TN contents and a decline in fungal biomass. This was mainly due to the loss of both aboveground vegetation and root biomass from intensive grazing. At 50 m, where grazing pressure was lower, the soil OC, TN, and microbial community size and activity were similar to those in a control, ungrazed area. These findings suggest that high chicken density can negatively affect soil health, while moderate grazing allows for the recovery of vegetation and soil organic matter. Rational management of free-range chicken grazing, particularly through the control of chicken density or managing grazing time and frequency, is therefore recommended to preserve soil functions and fertility. Full article

Jobs–housing balance is a critical concern in urban planning and sustainable economic development. Urban rail transit, as a key determinant of employment and residential location decisions, plays a pivotal role in shaping jobs–housing dynamics. Beijing, the first Chinese city to develop a subway system, offers a comprehensive rail network, making it an ideal case for exploring the effects of transit density on jobs–housing balance. This study utilizes medium-scale panel data from Beijing (2009–2022) and employs a fixed-effects model to systematically examine the impact of rail transit station density on jobs–housing balance and its underlying mechanisms. The results indicate that increasing transit station density tends to aggravate jobs–housing separation overall, with pronounced effects in central and outer suburban areas but negligible effects in near suburban areas. Mechanism analysis reveals two primary pathways: (1) improved accessibility draws employment toward transit-rich areas, reinforcing the attractiveness of central districts; (2) rising housing prices elevate residential thresholds, pushing lower-income populations toward outer suburbs. While enhanced transit density improves commuting convenience, it does not effectively reduce jobs–housing separation. These findings offer important policy implications for optimizing transit planning, improving jobs–housing alignment, and promoting sustainable urban development. Full article

The real estate market significantly influences individual lives, corporate decisions, and national economic sustainability. Therefore, constructing a data-driven, interpretable real estate market prediction model is essential. It can clarify each factor’s role in housing prices and transactions, offering a scientific basis for market regulation and enterprise investment decisions. This study comprehensively measures the evolution trends of the real estate markets in Beijing, Shanghai, Guangzhou, and Shenzhen, China, from 2003 to 2022 through three dimensions. Then, various machine learning methods and interpretability methods like SHAP values are used to explore the impact of supply, demand, policies, and expectations on the real estate market of China’s first-tier cities. The results reveal the following: (1) In terms of commercial housing sales area, adequate housing supply, robust medical services, and high population density boost the sales area, while demand for small units reflects buyers’ balance between affordability and education. (2) In terms of commercial housing average sales price, growth is driven by education investment, population density, and income, with loan interest rates serving as a stabilizing tool. (3) In terms of commercial housing sales amount, educational expenditure, general public budget expenditure, and real estate development investment amount drive revenue, while the five-year loan benchmark interest rate is the primary inhibitory factor. These findings highlight the divergent impacts of supply, demand, policy, and expectation factors across different market dimensions, offering critical insights for enterprise investment strategies. Full article

This work—mixing an original experimental approach, as well as numerical simulations—proposes to study film boiling modes around a small nickel sphere. While dealing with a simple looking phenomenon that is found in many industrial processes and has been solved for basic quenching regimes, we focus on describing precisely how vapor formation and film thicknesses, as well as vapor bubble evacuation, affect cooling kinetics. As instrumenting small spheres may lead to experimental inaccuracies, we optically captured, using a high-speed camera, the vapor film thickness at mid height, the vapor bubble volume, and the bubble detachment frequency, along with the heat flux. More precisely, an estimation of the instant sphere temperature, in different conditions, was obtained through cooling time measurement before the end of the film boiling mode, subsequently facilitating heat flux evaluation. We encountered a nearly linear decrease in both the vapor film thickness and vapor bubble volume as the sphere temperature decreased. Notably, the detachment frequency remained constant across the whole temperature range. The estimation of the heat fluxes confirmed the prevalence of conduction as the primary heat transfer mode; a major portion of the energy was spent increasing the liquid temperature. The results were then compared to finite element simulations using an in-house multiphysics solver, including thermic phase changes (liquid to vapor) and their hydrodynamics, and we also captured the interfaces. While presenting a challenge due to the contrast in densities and viscosities between phases, the importance of the small circulations along them, which improve the heat removal in the liquid phase, was highlighted; we also assessed the suitability of the model and the numerical code for the simulation of such quenching cases when subcooling in the vicinity of a saturation temperature. Full article

The optimization of land development requires a deep understanding of end-user expectations to ensure that new residential environments are both market-responsive and socially sustainable. This paper presents a novel prioritization-based technique for identifying and ranking property features according to buyer preferences. Using the MoSCoW method in combination with conjoint analysis, the study evaluates the relative importance of various housing attributes, such as layout, number of rooms, access to transportation, and availability of parking or green areas. The results provide structured insights into demand-side priorities and offer actionable guidelines for developers, urban planners, and decision-makers engaged in land use planning. By linking individual housing preferences with broader planning strategies, the proposed framework contributes to the creation of better-aligned, user-centric urban developments. The approach is tested on a local property market, and its potential applications in strategic zoning, infrastructure placement, and residential density modeling are discussed. Full article

Heat waves affect the health and quality of life of older adults, particularly in urban environments. However, there is limited understanding of how extreme temperatures influence their mobility. This research aims to understand the pedestrian mobility patterns of older adults during heat waves in Madrid, analyzing environmental and sociodemographic factors that condition such mobility. Geospatial data from the mobile phones of individuals aged 65 and older were analyzed, along with information on population, housing, urban density, green areas, and facilities during July 2022. Multiple linear regression models and Moran’s I spatial autocorrelation were applied. The results indicate that pedestrian mobility among older adults decreased by 7.3% during the hottest hours, with more pronounced reductions in disadvantaged districts and areas with limited access to urban services. The availability of climate shelters and health centers positively influenced mobility, while areas with a lower coverage of urban services experienced greater declines. At the district level, inequalities in the availability of urban infrastructure may exacerbate the vulnerability of older adults to extreme heat. The findings underscore the need for urban policies that promote equity in access to infrastructure and services that mitigate the effects of extreme heat, especially in disadvantaged areas. Full article

The COVID-19 pandemic has profoundly influenced urban planning and disease management in residential areas. Focusing on Beijing as a case study (3898 communities), this research develops a big data analytics framework integrating anonymized mobile phone signals (China Mobile), location-based services (AMAP.com), and municipal health records to quantify COVID-19 transmission dynamics. Using logistic regression, we analyzed 15 indicators across four dimensions: mobility behavior, host demographics, spatial characteristics, and facility accessibility. Our analysis reveals three key determinants: (1) Population aged 65 and above (OR = 62.8, p < 0.001) and (2) housing density (OR = 9.96, p = 0.026) significantly increase transmission risk, while (3) population density exhibits a paradoxical negative effect (β = −3.98, p < 0.001) attributable to targeted interventions in high-density zones. We further construct a validated risk prediction model (AUC = 0.7; 95.97% accuracy) enabling high-resolution spatial targeting of non-pharmaceutical interventions (NPIs). The framework provides urban planners with actionable strategies—including senior activity scheduling and ventilation retrofits—while advancing scalable methodologies for infectious disease management in global urban contexts. Full article