Search Results (158)

Urban road networks in Sub-Saharan Africa diverge from the sensor-rich, lane-disciplined environments conventional models assume. This paper establishes an empirical baseline of network efficiency and velocity decay along the 8.0 km Mile 17 to Governor’s Roundabout corridor in Buea, Cameroon, marked by a 25 m/km inbound gradient, unsignalized intersections, and a taxi share of 59.55% inbound and 65.27% outbound. Fifteen-minute PCU counts were recorded at three points across three peak windows over three consecutive weekdays (1–3 April 2026), yielding 18 h of counts and 36 floating-car GPS runs. Volume-to-capacity ratios (v/c), Peak Hour Factors, and space-mean speeds were derived for both directions, with SD, coefficient of variation, and 95% confidence intervals computed to quantify sampling uncertainty. Results show near over-saturation (v/c: 0.98–1.06) at Bonduma, particularly during the afternoon outbound window. However, the 95% confidence intervals span v/c = 1.00, indicating significant uncertainty in Level of Service classifications. Mean Travel Time Ratios ranged from 1.10 to 2.04. At Bonduma in the evening, an elevated Informal Transport Disruption Factor (ITDF = 0.96) co-occurred with only moderate volume (v/c = 0.87), consistent with, though not proof of, informal-transport-related delay. Finally, the paper introduces two new indicators, the Directional Flow Asymmetry Index (DFAI) and Corridor Velocity Decay Rate (CVDR), to quantify directional imbalances that standard v/c analysis misses. Alongside the ITDF, these metrics serve as empirical calibration inputs for a future reinforcement learning traffic control framework (BACATC). Because no AI controller was built or evaluated in this study, the findings establish a quantified field baseline rather than a demonstration of AI-based control. Full article

Developing countries, including Indonesia, are characterized by Heterogeneous Disordered Traffic (HDT), making traditional technology adoption models for autonomous vehicles (AVs) unsuitable. To bridge this gap, this study surveyed 204 urban early adopters using a rigorous psycho-statistical framework. Utilizing t-tests, ANOVA, and bootstrapped ordinal regression, we validated three behavioral pillars: safety-first prioritization, educated critical adoption, and a direct mode shift to shared AVs. Subsequent market segmentation via a CHAID decision tree yielded empirical AV market penetration rates (MPR) of 20%, 40%, and 70%. MPRs were evaluated in a calibrated PTV VISSIM microsimulation of the A.P. Pettarani Arterial Road in Makassar, Indonesia. A tree-based ensemble framework (XGBoost, CatBoost, and Random Forest) with SHAP diagnostics and a Double Machine Learning causal protocol assessed infrastructure trade-offs. With an R² of 0.99 and MAPE of 9.9%, XGBoost strongly predicted intersection delays and road section speeds. Causal analysis shows that putting dedicated lanes in place too soon, when the penetration rate is low (≤20% MPR), makes traffic worse. At an intermediate 40% MPR, dedicated lanes reduce intersection bottlenecks. Mixed non-dedicated traffic wins at 70% widespread saturation. The AV fleet acts as macroscopic pacemakers, smoothing traffic shockwaves and reducing intra-lane oversaturation to maximize global network efficiency without spatial segregation. Full article

In this work, a post-annealing rapid cooling and aging treatment process is innovatively proposed to build high-performance zinc tin oxide (ZTO) thin-film transistors. The relaxation effect on the abundant oversaturated oxygen vacancy deep-level traps contributes to the shallow donor formation during the aging period. The TFTs aged in an air environment for 10 days possess significantly improved electrical performance, including a clearly increased on/off current ratio of 7 × 10⁶ from 2 × 10⁴ and a markedly increased saturation mobility of 5.9 from 2.2 cm²·V⁻¹·s⁻¹, verifying the facile method to improve the electrical property of polycrystalline TFTs, and the method has been investigated using the grain boundary defect relaxation model and energy band theory. It is worth mentioning that the TFTs aged under vacuum conditions realized more effective regulation and control on off-state current and demonstrated a wider aging time window. The distinctive illumination interface stability was studied in depth using a charge trapping model and electron–hole pair model, which embody the potential application in photoelectric detectors. Full article

Sustainable and resilient road infrastructure requires the early identification of pavement deterioration mechanisms that emerge under complex urban traffic conditions, particularly at signalized intersections where repeated stop–go operations, queue persistence, and lane-wise freight concentration generate highly nonuniform structural loading. However, most existing intelligent transportation studies emphasize crash prediction, traffic-state estimation, or mobility optimization, while the infrastructure-performance consequences of freight-dominant interrupted flow remain insufficiently addressed. To support proactive pavement management and resilient urban road operation, this study proposes a traffic simulation-driven deep learning framework for predicting lane-level pavement deterioration under freight loading and stop–go urban traffic conditions. A high-resolution PTV Vissim 2024 microscopic simulation environment was developed for a four-leg signalized urban intersection, and a structured multi-scenario design was used to generate progressively increasing operational stress regimes, ranging from baseline flow to freight-dominant oversaturated operation. The resulting lane-wise dataset integrates direct traffic variables with pavement-oriented descriptors, including the Lane Freight Loading Index (LFLI), Stop–Go Severity Index (SGSI), ESAL proxy, queue persistence, and Loading Asymmetry Index (LAI). To learn the complex relationship between traffic operation and infrastructure degradation, a new Freight-Aware Lane Interaction Transformer Network (FLIT-Net) is introduced. The proposed model combines feature embedding, lane-interaction self-attention, freight-aware gating, residual refinement, and multi-task regression to jointly predict rutting risk, fatigue-cracking risk, and the Pavement Deterioration Index (PDI). Experimental results show that FLIT-Net outperforms MLP, CNN, LSTM, Bi-LSTM, and generic Transformer baselines, achieving RMSE/MAE/$R^2$ values of 0.041/0.032/0.9687 for rutting risk, 0.044/0.034/0.9635 for fatigue-cracking risk, and 0.031/0.024/0.9824 for PDI. Sensitivity and scenario-wise analyses further confirm that deterioration increases monotonically with freight intensity, stop–go severity, and queue persistence, highlighting the importance of lane-resolved deterioration intelligence for sustainable maintenance prioritization. The proposed framework bridges traffic microsimulation, pavement-oriented feature engineering, and freight-aware deep learning, providing a decision-support basis for improving the performance, safety, and resilience of urban pavement infrastructure. Full article

This study investigates place-based barriers to initial teacher training (ITT) recruitment in rural-coastal regions of England, focusing on Cornwall as a case study. Utilizing semi-structured interviews with nine ITT provider leaders and nine trainee teachers, the research applies the concept of educational isolation to ITT providers in areas that are geographically remote, socioeconomic disadvantaged, and culturally isolated. The analysis is framed by the critical pedagogy of place and social capital theory, moving beyond deficit-based interpretations of rurality to critically examine how place-based inequities are produced through urban-normative policy and resource allocation. Primary data were analyzed using reflexive thematic analysis. Four substantive themes emerged: transport dependency and accessibility constraints that structurally exclude lower-income and disabled trainees; housing displacement driven by the tourist economy, which compounds financial insecurity; an “employment precarity problem” where localized primary school oversaturation coexists with secondary teacher shortages; and cultural and professional isolation that disproportionately impacts ethnically diverse trainees in demographically homogeneous communities. The research further identifies that community resilience, while enabling individuals to navigate structural barriers, can obscure infrastructural inadequacy and diminish impetus for systemic policy reform. This paper contributes to international scholarship on spatial justice and rural teacher education by presenting an integrated conceptual framework with transferable relevance to similar rural-coastal and peripheral contexts globally and by offering policy recommendations for place-weighted ITT funding, infrastructure investment in educationally isolated areas, and the development of collaborative provider models. Full article

Background: The impact of overweight and adipocyte size on the development of type 2 diabetes mellitus (T2DM) remains unclear. Aim: We studied (1) the relationship between the state of adipocytes and/or overweight/obesity, the development of T2DM and its clinical and laboratory features; and (2) weight loss effect on glycemic level, endogenous hyperinsulinism (HI), insulin resistance (IR), and T2DM. Methods: We designed a systematic review by searching Web of Science, EBSCO, Scopus/ Science-Direct, Google Scholar, PubMed, Cochrane, and Wolter Kluwer for articles published in 26 years (2000–2026). The study was based on a systematic review of 3853 articles published worldwide. Results: In total, 142 full-text articles were assessed for eligibility. As overweight increases, the size of adipose tissue, adipocytes, and cell radius increase. The increase in cell size overloads intracellular transport and internal organs. The development of IR is a conformational change in cellular receptors caused by an excessive increase in cell size. The increase in cell size with overweight gradually leads to hyperglycemia and HI with the development of IR and T2DM. Any targeted intentional weight loss in patients with T2DM improves metabolic and cardiovascular health, reduces blood pressure and blood sugar, and decreases HI, IR, and T2DM. Conclusions: IR is a protective response of cells that prevents oversaturation and overflow. Overweight is an independent risk factor for the development of HI, IR, and T2DM. Targeted weight loss leads to the cure of HI, IR and T2DM. Full article

With the continuous expansion of building scale and increasingly complex functions, pedestrian congestion within buildings has become increasingly prominent. To identify high-utilization spaces during the architectural design stage, so as to optimize the design at the source and effectively alleviate the risk of oversaturated spatial flow in super high-rise buildings, transportation hubs and other complex buildings, this paper investigates spatial flow estimation methods in the architectural design phase. First, based on detailed data from microscopic pedestrian simulation in buildings, this study conducts an in-depth analysis of the factors influencing spatial flow from the perspectives of spatial structure and pedestrian demand. Then, by incorporating the visual integration degree from space syntax and the proposed Origin-Destination (OD) influence range definition method that accounts for obstacle detours, a spatial utilization intensity index integrating both factors is developed. Furthermore, regression analysis is employed to achieve spatial flow estimation based on the constructed spatial utilization intensity index. Finally, taking the basement 1 floor of the Shenzhen Bay Super Headquarters Base C Tower connected with the metro as an example, the effectiveness of the proposed method is verified. The results show that the MAPE is 26%. This study provides an effective estimation method for the prediction of spatial flow in the architectural design stage. Full article

Methane (CH₄) emissions in urban areas remain a major source of uncertainty in greenhouse gas inventories, particularly in Eastern European cities, where observational studies are limited. This study presents a comprehensive, system-based assessment of CH₄ sources in Cluj-Napoca, Romania, based on high-resolution in situ measurements across five representative urban systems: aquatic environments (AQs), natural gas distribution end-use points (NG), sewer infrastructure (SE), building basements (BSs), and traffic emissions (TEs). Elevated CH₄ concentrations were consistently detected across all investigated systems, confirming the coexistence of both diffuse and point sources within the urban environment. Dissolved methane (dCH₄) in aquatic systems showed strong and persistent oversaturation relative to atmospheric equilibrium, reaching up to 3 × 10⁵% of air–water equilibrium, indicating active microbial methanogenesis enhanced by urban inputs of organic matter and nutrients. Measurements at natural gas end-use points revealed highly localized leaks with concentrations up to 482 ppmv. Sewer infrastructure exhibited extreme variability (up to 1222 ppmv), likely controlled by a combination of microbial production, hydraulic conditions, and potential interactions with adjacent gas distribution networks. Basement environments showed CH₄ accumulation up to 12 ppmv, reflecting the combined effects of gas leakage and limited ventilation. Measurements at vehicle exhausts identified transient CH₄ peaks reaching 162 ppmv during vehicle engine acceleration, with distinct ethane-to-methane ratios, indicative of pyrogenic sources. Overall, these results demonstrate that urban CH₄ emissions are spatially heterogeneous, temporally variable, and derived from multiple coexisting sources. The urban area should, therefore, be understood as a hybrid environment, with natural and anthropogenic CH₄ contributions. Full article

Full-duplex (FD) technology holds great promise for enhancing the spectral efficiency of Mobile Ad Hoc Networks (MANETs) and Wireless Sensor Networks (WSNs). However, the practical performance gain of FD over Half-Duplex (HD) is highly sensitive to the dynamic nature of traffic loads and residual self-interference. Existing Optimal Dynamic Selection Strategies (ODSS) often rely on static workload assumptions within a single time window, failing to capture long-term traffic fluctuations. Consequently, applying instantaneous switching strategies in highly bursty environments necessitates excessively frequent mode switching (e.g., the switching frequency can approach the total number of time windows), incurring prohibitive signaling overhead and unignorable MAC-layer adaptation delays. To overcome these concrete bottlenecks, this paper proposes a comprehensive traffic-aware adaptive duplex mode selection framework. First, we model the multi-scale dynamic workload using Dynamic Activated Probability in Short-term (DAPS) and Long-term (DAPL), effectively characterizing both bursty traffic (via Beta distribution) and Markov-modulated stable traffic. Second, by integrating physical layer performance analysis, we define the Break-even Workload Point (BWP) to partition traffic into Oversaturated (OZ) and Unsaturated (UZ) Workload Zones (WZs). Furthermore, to handle unknown future traffic with low complexity, we propose the Pre-scheduling Duplex selection based on the Workload zone Estimation (PDWE) algorithm. PDWE leverages a Hidden Markov Model (HMM) combined with a Rollout algorithm to estimate hidden traffic states and adaptively pre-schedule duplex modes. Simulation results demonstrate that the proposed strategy achieves near-optimal throughput (approximately 91% of the ideal ODSS) while reducing the duplex switching frequency by two orders of magnitude compared to instantaneous switching strategies. This approach offers a robust cross-layer solution for next-generation self-organizing networks. Full article

This study evaluates the role of groundwater in the dynamics of the Slano blato landslide using hydrogeochemical and stable isotope data. Results show that deep groundwater inflow significantly affected the landslide behavior, as demonstrated by pronounced hydrogeochemical and isotopic differences among springs. Springs within the landslide differ markedly from those in similar geological settings of the Vipava Valley, indicating a distinct local groundwater system. Groundwater is present within the landslide body even during dry periods. Waters originate mainly from a higher karstic recharge area and flow through deep flysch strata, particularly fractured sandstones, where they become enriched in dissolved ions, especially K⁺ and SO₄²⁻, and show increased mineralization in the lower parts of the landslide. Saturation indices indicate slight oversaturation with calcite and dolomite and equilibrium with quartz for most samples, reflecting interaction with carbonates and flysch sandstones. Elevated sulphate concentrations and near-equilibrium conditions for mirabilite and thenardite suggest salt-related deterioration of landslide material, enhanced by evaporation. Stable isotope data (δ¹³C_DIC, δ¹⁸O, δ²H) indicate dominant carbonate recharge, meteoric origin, evaporation effects, and long-term water–rock interaction. This study highlights the need for additional isotope tracers, groundwater age indicators, seasonal monitoring, and on-site meteorological measurements to improve interpretation. Full article

Mealworm farming is gaining interest as a possible solution to the oversaturated meat supply chain, as an alternative source of protein. This is a more environmentally friendly activity that requires fewer inputs for production compared to meat. This review discusses the feasibility of mealworms as an ingredient for the production of novel foods, investigating crucial aspects, such as nutrition, technological capability, food safety, and consumer acceptance, among others. Tenebrio molitor larvae can be nutritionally comparable to meat, as they provide high-quality protein and other essential nutrients. Although the omega-6/omega-3 ratio exceeds the recommended limit (<5), certain strategies during larval breeding, including feeding, and cooking, may significantly reduce this gap. The use of mealworm flour in the food industry can provide apparently healthy, safe matrices with high protein content. However, inclusions above 10% often lead to technological and sensory deficiencies. Further experimentation is required to overcome these issues, which negatively impact consumer acceptance, and to promote social behavioral strategies to attract consumers toward insects. On the other hand, regulatory policies might play a crucial role in supporting this business, which is predicted to grow as technology develops and this activity aligns with a circular economy. Full article

Accurate traffic modeling is essential for effective urban mobility planning within Smart Cities. Conventional capacity assessment methods assume rule-based driver behavior and therefore neglect psychological priority, an informal interaction in which drivers negotiate right-of-way contrary to traffic regulations. This study investigates how the absence of this behavioral factor affects the accuracy of delay and capacity evaluation at unsignalized intersections. A 12 h field observation was conducted at an intersection in Prešov, Slovakia, and 28 driver interactions were analyzed using linear regression modeling. The derived model (R² = 0.83, p < 0.05) demonstrates that incorporating psychological priority significantly improves the agreement between calculated and observed waiting times. Unrealistic results occurring under oversaturated conditions in standard methodologies were eliminated. The findings confirm that behavioral variability has a measurable impact on traffic performance and should be reflected in analytical and simulation models. Integrating these behavioral parameters into Smart City traffic modeling contributes to more realistic and human-centered decision-making in intersection design and capacity management, supporting the development of safer and more efficient urban mobility systems. Full article

This paper addresses the optimization of traffic signal timing at urban intersections by introducing a dynamic green ratio allocation framework based on cycle-based delay classification. Conventional methods such as the Webster delay model often fail to capture the asymmetric delay characteristics and the impact of fluctuating flows across multiple cycles. We propose a novel approach that classifies cycles into undersaturated and oversaturated states and develops dedicated optimization models for each type. For undersaturated cycles, a new delay function is derived to accurately capture the interaction between queue dissipation and green time allocation, enabling multi-period minimization of total vehicle delay. For oversaturated cycles, queue minimization at the end of each phase is adopted to accelerate congestion dissipation. The framework is validated through simulation and compared with existing methods, demonstrating superior performance in congestion clearance and delay minimization. The results show improved adaptability to changing traffic conditions and enhanced practicality for real-time signal control in smart transportation systems. Full article

This paper reports a novel effort to estimate and evaluate the coefficients of Hg transfer across the water/air interface in lakes such as Cane Creek Lake (CCL, Cookeville, TN, USA). This was accomplished by calculating the coefficients (k_w) using the Two-Thin Film (TTF) Model for Hg transfer together with the field-measured data of Hg emission flux (F), dissolved gaseous mercury concentration (DGM), air Hg concentration (C_a), and water temperature for Henry’s coefficient (K_H) obtained from a separate field study at the CCL. The daily mean k_w values range from 0.045 to 0.21 m h⁻¹, with the min. at 0.0025–0.14 and the max. at 0.079–0.41 m h⁻¹, generally higher for the summer, and from 0.0092 to 0.15, with the min. at 0.0032–0.033 and the max. at 0.017–0.31 m h⁻¹, generally lower for the fall and winter, exhibiting an apparent seasonal trend. The highest k_w values occur in August (mean: 0.21, max.: 0.41 m h⁻¹). Our k_w results add to and enrich the aquatic interfacial Hg transfer coefficient database and provide an alternative avenue to evaluate and select the coefficients for the TTF Model’s application. The k_w results are of value in gaining insights into the Hg transfer actually occurring across the water/air interface under environmental influences (e.g., wind/wave, solar radiation). Our k_w results do not show a clear, consistent correlation of k_w with wind/wave effect, nor sunlight effect, in spite of some correlations in sporadic cases. Generally, the k_w values do not exbibit the trends prescribed by the model sensitivity study. The comparisons of our k_w results with those obtained using wind-based transfer models (the Liss/Merlivat Model, the Wanninkhof Model, and the modified linear model) show that they depart from each other. The findings of this study indicate that the TTF Model has limitations and weaknesses. One major assumption of the TTF Model is the equilibrium of the Hg distribution between the air and water films across the water/air interface. The predominant oversaturation of DGM shown by our DGM data evidently challenges this assumption. This study suggests that aquatic interfacial Hg transfer is considerably more complicated, involving a group of factors, more than just wind and wave. Full article

At present, the ductility of engineered cementitious composites (ECC) is not sufficient to achieve compatibility with steel, which limits the application of ECC in composite structures. To prepare ECC with ultra-high tensile strain, tensile tests on eighteen types of ECC with different mix ratios were carried out. The effect of cementitious material composition, sand/binder ratio, and fiber hybridization on tensile properties was analyzed. Meanwhile, three types of ECC were developed and defined as ultra-high tensile property cementitious composites (UHTCC). UHTCC exhibits the characteristic of oversaturated cracking and obvious strain hardening during the tensile process. The tensile strain of UHTCC was up to 18.3% with an average tensile strength of 9.9 MPa. Meanwhile, UHTCC shows ultra-high flexural toughness and high compressive strength. In addition, the hybridization of PE fibers and macro-PP fibers has been proved to be beneficial to improve tensile strain capacity, with the cost of fibers decreased by 24.3%. To explore the causes of UHTCC’s ultra-high tensile strain, the state of the matrix and fibers after the tensile test was observed by scanning electron microscope. In addition, the cracking process of UHTCC was analyzed by comparing average crack spacing with the theoretical value. Further, a four-stage tensile constitutive model was proposed. And the new constitutive model has been verified to be applicable to three different types of UHTCC. Full article