Search Results (139)

Effective water management is a core function of nature-based solutions (NBSs), enabling them to deliver vital ecosystem services and enhance urban resilience. This study examines the hydrological performance of a specific NBS, the Blue-Green Roof (BGR). In contrast to conventional green roofs, the BGR incorporates a subsurface storage layer that retains infiltrated rainfall, thereby sustaining vegetation, boosting evapotranspiration and cooling, and reducing the burden on urban drainage systems. The research evaluates the BGR’s hydrological dynamics over the long term, drawing on data collected between May 2021 and May 2025 at a pilot site in Central Italy. Full article

This paper presents a flipped-voltage-follower low-dropout regulator (FVF-LDO) for power supply rejection enhancement and low-power operation in CMOS transimpedance amplifiers for optical receiver applications. The proposed FVF-LDO ensures high stability and reliable regulation over a wide range of load conditions by employing a flipped-voltage follower for fast local feedback and improved power supply rejection, while a super-source follower enhances the transient response through increased current-driving capability. A bandgap reference with a 3-bit trimming DAC is adopted to compensate process variations and support stable LDO operations, achieving a temperature coefficient of 19.6 ppm/°C over a wide range of −25 °C to 125 °C. The FVF-LDO exhibits a 101 mV undershoot under a 100 µA-to-10 mA load step with a 100 ns edge time. When applied to an optoelectronic inverter-based active-feedback transimpedance amplifier (TIA), the regulated supply improves the power supply rejection ratio (PSRR) from −6 dB to −38.3 dB. The proposed optoelectronic TIA realized in a 180 nm CMOS process achieves 67 dBΩ transimpedance gain, 869 MHz bandwidth, 66 dB dynamic range, 6.68 pA/√Hz input-referred noise current spectral density, and 4.68 mW power consumption from a single 1.8 V supply. The proposed TIA chip occupies a core area of 940 × 162 µm². Full article

Accurate and timely diagnosis of citrus diseases is essential for reducing economic losses in global agriculture. Although deep learning models provide high diagnostic accuracy, their computational demands often hinder deployment on resource-limited edge devices. To overcome this challenge, this study proposes an optimized hybrid framework for phytopathological classification. The methodology combines handcrafted descriptors (Blue-Green-Red “BGR” color statistical moments) with hierarchical spatial abstractions derived from a pre-trained Visual Geometry Group 16-layer (VGG16) deep architecture. An initial high-dimensional feature space was created by concatenating 360 handcrafted statistical descriptors and 12,800 deep textural features. By implementing a Wrapper-Greedy Stepwise selection strategy, this original space was reduced by over 96%. The resulting Elite Model identifies 12 and 18 critical attributes across two independent, transcontinental datasets (Mexico and Pakistan, respectively), effectively capturing both subtle chromatic anomalies and complex structural lesions. Experimental benchmarking confirms that this parsimonious hybrid approach delivers robust classification accuracy ranging from 87.30% to 95.23%, significantly outperforming unimodal architectures. Ultimately, this framework provides a highly efficient, interpretable, and scalable solution for real-time disease monitoring in precision agriculture. Full article

Opalinus Clay (OPA) is a key host rock for the geological disposal of high-level radioactive waste in Switzerland and is also under investigation in Germany. Reliable prediction of the long-term performance of deep geological repositories requires constitutive models capable of capturing the coupled hydro-mechanical (HM) behaviour of the host rock, including mechanical anisotropy, strain-dependent stiffness, suction effects, and stress-dependent failure. This study presents a hydro-mechanically coupled constitutive model incorporating anisotropic yield behaviour, hardening/softening, and strain-dependent permeability. The model is calibrated against laboratory triaxial, Brazilian tensile strength (BTS), and uniaxial compressive strength (UCS) tests on OPA, with bedding orientations between 0° and 90°. Implemented in OpenGeoSys (OGS), the model represents bedding-controlled plastic anisotropy using a microstructure tensor approach. The simulations reproduce key experimental trends relevant to repository-induced perturbations, including bedding-dependent strength and stiffness, suction effects on UCS, and the orientation-dependent tensile strength observed in Brazilian tests. Remaining discrepancies under high confining stress indicate the need for improved regularization and dilatancy formulations. Overall, the proposed framework provides a robust building block for HM process modelling and long-term safety assessments of deep geological repositories. Full article

Background/Objectives: Speech and language delay (SLD) is one of the most prevalent developmental conditions in childhood, with post-pandemic data indicating a notable increase in identified cases. Within this group, expressive language disorder (ELD) frequently appears alongside neurodevelopmental disorders such as autism spectrum disorder (ASD), epilepsy, and intellectual disability. Although awareness of ELD has grown, the role of genetic testing in its evaluation remains unclear, as such testing is not routinely pursued for isolated expressive language concerns. This gap highlights the need to better define the diagnostic value of genetic analysis and to examine the interval between an ELD diagnosis and the return of genetic testing results. Methods: This study investigated genetic contributions to ELD using the National Brain Gene Registry (BGR), a multisite database of rare neurodevelopmental disorders. Participants with ICD-10 code F80.1 were identified through electronic health records; demographic data, comorbidities, genetic variants, inheritance patterns, age at diagnosis, and timing of interventions were analyzed. Results: Of 687 BGR participants, 32 (4.7%) had documented ELD. The cohort, aged 3–19 years, presented with common comorbidities like developmental delays, ASD, epilepsy, and hypotonia. Across 42 genes, 49 unique variants were identified: 26 pathogenic or likely pathogenic, 22 variants of uncertain significance, and one benign variant. Seventeen variants were de novo, and 10 participants carried multiple variants. Most children (80%) received an expressive language diagnosis prior to genetic testing, with reports returned an average of 1.5 years following the diagnosis. Conclusions: Overall, children with ELD commonly carry genetic variants and neurodevelopmental comorbidities, yet genetic testing is typically pursued well after diagnosis and does not currently alter early management. These findings underscore the need for clearer, evidence-based guidelines to define when genetic testing adds diagnostic or prognostic value in the evaluation of ELD. Full article

This paper introduces an enhanced bandgap reference (BGR) design, addressing the shortcomings of traditional circuits, such as significant temperature drift, limited power-supply rejection, and inadequate load-driving capacity. The proposed design incorporates a symmetric folded common-emitter–common-base BJT amplifier with MOS-assisted biasing, employed in the proposed BGR, enforcing branch voltage symmetry to effectively suppress intrinsic offset caused by structural mismatch. By reducing the amplifier input offset, the circuit achieves improved reference voltage stability, a lower temperature coefficient (TC), and an enhanced power-supply rejection ratio (PSRR). Additionally, a negative-feedback adaptive current-adjustment driver is implemented to dynamically adjust the output current in response to real-time load changes. This method bolsters the load-driving capability and maintains a stable reference output across varying load conditions. The circuit was simulated using a 0.18 μm BCD process, revealing that with a 3.3 V supply voltage, the BGR produces a stable output voltage of 2.5 V, with a TC of $2.372\times {10}^{-6}$ °C⁻¹. The simulated PSRR is −114.2 dB at DC and −62.07 dB at 1 kHz. Moreover, under a 3.3 V supply, sweeping the load capacitance from 0.1 μF to 100 μF demonstrates that the reference voltage remains consistently regulated at 2.5 V, confirming its excellent load tolerance and output stability. Full article

A 3.0 V bandgap reference (BGR) for battery management integrated circuit (BMIC) is presented, achieving a low temperature coefficient (TC) and a high power supply rejection ratio (PSRR). Precision is enhanced through two techniques: (1) a base current correction technique eliminates errors from the bipolar junction transistor (BJT) base current, and (2) a high-order temperature compensation circuit counteracts the inherent nonlinearity of the BJT’s base-emitter voltage (V_BE). Furthermore, an improved flipped voltage follower (FVF) pre-regulation structure is integrated for efficient power supply noise suppression. The circuit is designed based on a 180 nm BiCMOS process, occupying a layout area of 0.0459 mm². Post-layout simulation results demonstrate that the BGR achieves a temperature coefficient of 1.59 ppm/°C over the −40 °C to 125 °C temperature range. Within a supply voltage range of 4.7 V to 5.3 V, the line regulation is 0.00058 mV/V. At a 5.0 V supply voltage, the quiescent current is 23 μA, and the PSRR is −128.89 dB@1 Hz and −102.9 dB@1 kHz. Full article

Regeneration of jawbone defects poses major challenges. The combination of dental pulp stem cells (DPSCs) or DPSC-derived extracellular vesicles (EVs) with bone substitute materials shows promising potential for bone tissue engineering in vitro. This study evaluated the in vivo bone regeneration potential of DPSCs and EVs with bone graft substitutes in a novel intrabony defect model. DPSCs were isolated from 35 male Sprague–Dawley rat incisors, and EVs were collected from the cell culture medium. DPSCs were seeded onto alloplastic and xenogeneic bone graft materials and implanted into bone defects. Control groups received bone substitutes without DPSCs or EVs. Micro-computed tomography (µCT) was performed at 12 and 24 weeks post-implantation to assess bone volume (BV), bone density (BD), trabecular thickness (Tr.Th), bone growth rate (BGR), and bone-to-mineral ratio (BMR). Both graft types increased BV and BD, with no significant differences between them. Tr.Th increased across all treatments after 24 weeks, indicating ongoing bone remodeling. Notably, xenogeneic grafts combined with DPSCs and EVs significantly improved BGR (p = 0.034) and BMR (p = 0.021) compared to alloplastic grafts with DPSCs. Xenogeneic bone grafts combined with DPSCs and EVs appear to be a promising approach for bone regeneration of alveolar bone defects. Full article

Groundwater resources in Jordan are under severe stress due to rapidly increasing water demand and over-abstraction that far exceeds natural replenishment. In addition, water quality is threatened by pollution from the misuse of fertilizers and pesticides, leakage from septic tanks, and illegal waste disposal. This study focuses on the Aqeb, Corridor, and Special Economic Zone wellfields, where hydrological and hydrochemical investigations were carried out. A total of 36 groundwater samples were collected and analyzed for hydrochemical composition, stable isotopes of oxygen (δ¹⁸O) and hydrogen (δ²H), and trace elements. In addition, two exploration 2D seismic profiles crossing the study area were interpreted, providing critical insights into the activity of the subsurface Fuluk Fault zone and its relationship with the wellfields. The hydrochemical results reveal elevated total dissolved solids and nitrate concentrations, accompanied by more depleted δ¹⁸O and δ²H values in wells located in the central part of the study area. Three distinct hydrochemical groups were identified within the same aquifer, indicating heterogeneity in groundwater chemistry that reflects variations in recharge conditions, flow paths, and geochemical processes. The first group (high Na/Cl with low salinity) likely represents recently recharged waters with limited rock–water interaction. The second group (intermediate Na/Cl and moderate salinity) may be influenced by evaporation, irrigation return flow, or cation exchange. The third group (low Na/Cl with high salinity) suggests the dissolution of sulfate minerals or mixing with deeper mineralized groundwater, possibly facilitated by structural features such as the Fuluk Fault. Seismic interpretation indicates several active near-surface fault systems that are likely to serve as preferential pathways for salinity and nitrate enrichment, linked to intensive agricultural activities and wastewater leakage from nearby septic tanks. The findings emphasize the combined influence of geochemical processes, excessive groundwater abstraction, and structural features in controlling water quality in the region. Full article

Urban areas face increasing flood risks due to climate change, intensified rainfall events, and high impervious surface coverage. Blue-Green Roofs (BGR) have emerged as a nature-based solution to retain stormwater, while Smart BGR systems integrate active control functions to enhance performance under varying rainfall conditions. This study evaluated the rooftop-scale runoff reduction efficiency of conventional roofs, BGR, and Smart BGR using 31 monitored rainfall events in 2024, while eight years of historical rainfall data (2017–2024) were used only to characterize long-term rainfall patterns in the study area. A multiple-linear regression analysis was performed for exploratory trend identification between rainfall characteristics and runoff reduction; variables unrelated to short-term storm responses such as evapotranspiration or initial storage were beyond the study scope. Results showed that the annual runoff per unit area was 1.115 m³/m² for conventional roofs, 0.547 m³/m² for BGR, and 0.128 m³/m² for Smart BGR, corresponding to reduction rates of 50.98% and 88.53% for BGR and Smart BGR, respectively. In higher rainfall classes, Smart BGR maintained significantly higher performance: for Class 3 (average 53.00 mm), BGR reduced runoff by 54.89% while Smart BGR achieved 86.71%; for Class 4 (average 121.21 mm), the rates were 54.68% and 90.00%, respectively. These findings indicate that Smart BGR’s storage optimization and controlled discharge enable superior effectiveness during intense and prolonged events. The study highlights Smart BGR’s potential as an advanced stormwater management technology, offering clear advantages over both conventional roofs and passive BGR designs. Limitations include the need for testing under more extreme rainfall scenarios, optimization of operational strategies, and economic feasibility assessments. Nevertheless, Smart BGR represents a promising approach for enhancing urban flood resilience in the context of climate change. Full article

A precision bandgap reference (BGR) is an essential building block in modern analog and mixed-signal systems, as it provides stable and predictable current and voltage references required for reliable operation across process, voltage, and temperature variations. However, one of the key challenges in conventional BGR circuits is their sensitivity to resistance variations, which directly impacts the accuracy of bias currents. Even small changes in resistance can lead to significant current mismatch between the core branches of the circuit, thereby degrading output stability and limiting the precision of the overall system. This degradation is particularly problematic in high-performance applications such as data converters, oscillators, and low-power biasing networks, where robust current matching is critical. To address this limitation, this work proposes a resistance-compensated BGR architecture that incorporates an auxiliary trimming network and a compensation branch. The trimming network senses variations in resistance and generates a control bias proportional to the deviation, while the compensation branch injects a corrective current into the output stage. By dynamically balancing the mismatch introduced by resistor spread, the proposed architecture effectively restores current stability across process corners. This method achieves reduction in the current variation across resistance corners from 21% to 3% in worst-case corners (±3%). This approach offers enhancement of current mismatches in analog systems in which robust current is essential. Full article

The Gadouras Reservoir, Rhodes Island’s primary water source, experiences recurrent whiting events—milky turbidity from calcium carbonate precipitation—that challenge treatment operations, with impacts compounded by a major 2023 wildfire in this fire-prone Mediterranean setting. To elucidate these dynamics, a pragmatic, multi-source monitoring framework integrates archived Sentinel-2 and Landsat imagery with treatment-plant records (2017–mid-2025). Unitless spectral indices (e.g., AreaBGR) for whiting detection and chlorophyll-a proxies are combined with laboratory measurements of turbidity, pH, total organic carbon, manganese, and hydrological metrics, analyzed via spatiotemporal Hovmöller diagrams, Pearson correlations, and interrupted time-series models. Two seasonal whiting regimes are identified: a biogenic summer mode (southern origin; elevated chlorophyll-a; water temperature > 15 °C; pH > 8.5) and a non-biogenic winter mode (northern inflows). Following the wildfire, the system exhibits characteristics that could be related to possible hypolimnetic anoxia, prolonged whiting, a ~50% rise in organic carbon, and a manganese excursion to ~0.4 mg L⁻¹ at the deeper intake. Crucially, the post-fire period shows a decoupling of AreaBGR from turbidity (r ≈ 0.233 versus ≈ 0.859 pre-fire)—a key diagnostic finding that confirms a fundamental shift in the composition and optical properties of suspended particulates. The manganese spike is best explained by the confluence of a wildfire-induced biogeochemical predisposition (anoxia and Mn mobilization) and a consequential operational decision (relocation to a deeper, Mn-rich intake). This framework establishes diagnostic baselines and thresholds for managing fire-impacted reservoirs, supports the use of remote sensing in data-scarce systems, and informs adaptive operations under increasing climate pressures. Full article

Background: Chagas disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), remains a major public health concern in Latin America. No licensed vaccine exists to prevent or treat T. cruzi infection. Identifying correlates of protection (CoPs) could provide substitute endpoints to guide and accelerate vaccine development. Although most CoPs established to date are antibody-based, their utility has not been demonstrated in T. cruzi vaccine reports. Thus, this study aimed to explore alternative strategies considering the use of immune cells as potential CoPs. Methods: Mice were immunized with a vaccine candidate based on the T. cruzi trans-sialidase protein (TSf) and potentiated with 5-fluorouracil (5FU) to deplete myeloid-derived suppressor cells (MDSCs). Percentages of CD4⁺, CD8⁺, and CD11b⁺Gr-1⁺ cellular biomarkers were assessed by flow cytometry from the peripheral blood of immunized mice, which were subsequently challenged with a high dose of T. cruzi. A machine-learning (ML) model based on decision trees was applied to identify potential CoPs to predict survival by day 25 post-infection. Results: Individual biomarkers obtained from flow cytometry did not show strong predictive performance. In contrast, biomarker engineering led to a combination that integrated biomarkers rationally: summing the percentages of CD8⁺ and CD4⁺ cells and subtracting the percentage of CD11b⁺Gr-1⁺ MDSC-like cells (REB), enhanced the predictive capacity. Subsequent computational analysis and ML application led to the identification of a better and even improved potential Integrative CoP: $2 \ast \%CD{8}^{+}+ {\%CD4}^{+} - {\%CD11b}^{+}{ Gr1}^{+}$(pICoP), which significantly improved the performance of a simple one-level decision-tree model, achieving an average accuracy of 0.86 and an average AUC-ROC of 0.87 for predicting survival in immunized and infected mice. Conclusions: Results presented herein provide evidence that integrating cellular immune biomarkers through rational biomarker engineering, together with ML analysis, could lead to the identification of potential CoPs for a T. cruzi vaccine. Full article

The diffusion effect of river cooling is critical for mitigating the urban heat island effect in riverside areas and for establishing an urban cooling network. River cooling effect diffusion is influenced by the two-dimensional (2D) and three-dimensional (3D) urban morphology of surrounding areas. However, the characteristics of 2D/3D urban morphology that facilitate efficient river cooling effect diffusion remain unclear. This study establishes a technical framework to analyze river cooling effect diffusion resistance (RCDR) across different urban morphologies, using the Huangpu River waterside area in Shanghai as a case study. Seven urban morphology indicators, derived from both 2D and 3D dimensions, were developed to characterize the river cooling effect diffusion resistance. The relative contributions and marginal effects were analyzed using the Boosted Regression Tree (BRT) model. The study found that (1) river cooling effect diffusion was heterogeneous, with four typical patterns; (2) the Landscape Shape Index (LSI) and Blue-green Space Ratio (BGR) significantly impacted cooling effect diffusion; and (3) optimal cooling effect diffusion occurred when the blue-green space occupancy ratio exceeded 20% and building density ranged from 0.1 to 0.3. This study’s technical framework offers a new perspective on river cooling effect diffusion and heat island mitigation in riverside spaces, with significant practical value and potential for broader application. Full article

The recycling of lithium-ion batteries is picking up rather slowly, although recent rapid growth in consumption and increasing prevalence of battery electric vehicles have increased the quantity of recoverable material from past years of production. Yet, the diversity of different product types i.e., chemistries and product life spans complicates the recovery of raw materials. At present, large-scale industrial recycling of lithium-ion batteries employs (1) pyrometallurgy, with downstream hydrometallurgy for recovery of refined metals/salts; and (2) hydrometallurgy, requiring upstream mechanical shredding of cells and/or modules. Regulatory requirements, especially in Europe, and the high industry concentration along the lithium-ion battery value chain drive recycling efforts forward. The present study aims to quantify the potential contribution of 2nd lithium from recycling to battery production on a global and European scale up to 2050. The overall recycling output of lithium in any given year depends on the interactions between several different factors, including past production, battery lifetime distributions, and recovery rates, all of which are uncertain. The simplest way to propagate input uncertainties to the final results is to use Monte Carlo-type simulations. Calculations were done separately for EVs and portable batteries. The overall supply of lithium from recycling is the sum of the contributions from EVs and portable electronics from both the EU and the RoW in each battery production scenario. Results show a total global supply of recycled lithium below 20% in each scenario until 2050. On the EU level, the contribution of recycled lithium may reach up to 50% due to the high collection and recovery rate targets. Full article