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Hydrologic models such as the USEPA Stormwater Management Model (SWMM) are commonly used to assess the design and performance of green infrastructure (GI). To accurately represent GI performance models used in design need to be able to address both the hydrology/hydraulics of the catchment and the GI unsaturated (vadose) zone hydrology. While hydrologic models, such as SWMM, address the need for catchment hydrology/hydraulics, they often simplify the unsaturated zone hydrology. This paper presents a methodology utilizing existing components of SWMM to represent unsaturated zone hydrology in an accessible format that does not require adjustments to the SWMM source code. The methodology simulated the unsaturated soil water movement by considering flow caused by differences of soil matric head and flow caused by gravity between soil layers with finite depth/length. The flow flux related to the soil matric head is a function of soil water diffusivity (D) and the soil moisture gradient, where D can be represented by a pump curve in SWMM. The flow flux related to gravity was controlled by unsaturated hydraulic conductivity (K) only and was also simulated by a pump. The methodology was compared to another variably saturated model, HYDRUS, with theoretical soils (with single layers of sand, loam, silt, and clay, as well as dual-layer scenarios). Field data was used to compare the methodology to HYDRUS and the SWMM LID (Low Impact Development) module. In all comparisons the presented methodology and HYDRUS delivered similar results for the vadose zone response to a storm event, while the LID module of SWMM exhibited slower water movement. The results showed that under natural conditions, the approximation of the presented methodology yielded satisfactory results to simulate flow through the unsaturated vadose zone.

SWMM (Storm Water Management Model) has been widely used in urban water resources management. Despite its popularity, no commonly accepted pollutant buildup and washoff parameters are available for urban areas in semi-arid or arid climate, which covers 30% of global land area and is sustaining fast growth. This study provides a method to determine these parameters using inverse modeling and apply it in a semi-arid Texan urban watershed. Because GIS land use data is not available for early 1980s, it was determined from aerial photography from 1984 to 2006, and GIS land use data from 2006. Calibration using Shuffled Complex Evolution – University of Arizona (SCEUA) was used for hydraulic parameters followed by pollutant parameters. Confidence intervals of pollutant parameters were calculated by GLD (Generalized Lambda Distribution). Buildup parameters are clustered in narrow numerical ranges, indicating that spatially uniform factors are responsible for pollutant buildup. Washoff parameters do not cluster and are distributed more evenly, indicating strong influence of local factors such as topography. The results also imply that the commonly used parameter values need major revision.

Background Core fucosylation (addition of fucose in α-1,6-linkage to core N-acetylglucosamine of N-glycans) catalyzed by fucosyltransferase 8 (FUT8) is critical for signaling receptors involved in many physiological and pathological processes such as cell growth, adhesion, and tumor metastasis. Transforming growth factor-β (TGF-β)-induced epithelial–mesenchymal transition (EMT) regulates the invasion and metastasis of breast tumors. However, whether receptor core fucosylation affects TGF-β signaling during breast cancer progression remains largely unknown. Method In this study, gene expression profiling and western blot were used to validate the EMT-associated expression of FUT8. Lentivirus-mediated gain-of-function study, short hairpin RNA (shRNA) or CRISPR/Cas9-mediated loss-of-function studies and pharmacological inhibition of FUT8 were used to elucidate the molecular function of FUT8 during TGF-β-induced EMT in breast carcinoma cells. In addition, lectin blot, luciferase assay, and in vitro ligand binding assay were employed to demonstrate the involvement of FUT8 in the TGF-β1 signaling pathway. The role of FUT8 in breast cancer migration, invasion, and metastasis was confirmed using an in vitro transwell assay and mammary fat pad xenograft in vivo tumor model. Results Gene expression profiling analysis revealed that FUT8 is upregulated in TGF-β-induced EMT; the process was associated with the migratory and invasive abilities of several breast carcinoma cell lines. Gain-of-function and loss-of-function studies demonstrated that FUT8 overexpression stimulated the EMT process, whereas FUT8 knockdown suppressed the invasiveness of highly aggressive breast carcinoma cells. Furthermore, TGF-β receptor complexes might be core fucosylated by FUT8 to facilitate TGF-β binding and enhance downstream signaling. Importantly, FUT8 inhibition suppressed the invasive ability of highly metastatic breast cancer cells and impaired their lung metastasis. Conclusions Our results reveal a positive feedback mechanism of FUT8-mediated receptor core fucosylation that promotes TGF-β signaling and EMT, thus stimulating breast cancer cell invasion and metastasis.

Forcing pathways between urban surfaces (impervious and pervious pavers) and near-surface air temperature were measured and investigated with a network of multiple sensors. Utilizing field data measured between April 2021 and May 2022, and assuming that the influential variables follow the basic heat-transfer energy-balance equations, multiple regression-based statistical models were built to predict the surface temperature and near-surface air temperature (0.05 m, 0.5 m, 1 m, 2 m, and 3 m) of one impervious paver site and one pervious paver site in Taipei City, Taiwan. Evaporative cooling was found to be more influential on the pervious paver with a statistically significant influence on the microclimate up to 1.8 m (and up to 0.7 m for the impervious paver), using in situ data with an ambient air temperature higher than 24 °C. The surface temperature is mainly affected by solar shortwave radiation and ambient air temperature. As for near-surface air temperature, ambient air temperature is the most influential factor, followed by surface temperature. The importance of surface temperature indicates the influence of upwelling longwave radiation on the microclimate. The predictive equations show that pervious surfaces can help cities with hot and humid climates fight the changing climate in the future.

In this paper, we propose a novel structure with Control Source and Control Gate structured tunnel field-effect transistor (CSCG‑iTFET), which achieves an unprecedentedly steep subthreshold swing (SS) while maintaining high ON-state current ( ). In addition, using Schottky contacts at the source without doping reduces leakage current and thermal budget. We compared the performance of four different device structures, including conventional Double Gate TFET with Control Gate, iTFET with Control Gate, iTFET with Charge Enhancement Layer and Control Gate, and our structure. The accumulation layer can be enhanced by using the characteristic of Control Source to modulate the voltage. We performed simulation studies using Sentaurus TCAD. Utilize calibrated models for accurate simulations, exploiting the same referenced processes, demonstrate that the Control Source iTFET exhibits an average subthreshold swing S.S AVG of 9.69 mV/Dec and a minimum subthreshold swing S.S MIN of 1.72 mV/Dec, respectively. At V D = 0.2 V, the I ON current is 2.95 × 10 − 7 A/µm, and the I ON / I OFF ratio is 3.84 × 10 9 . It is believed that the performance can be further improved if the fabrication processes are optimized.

The Newtonian gravitational constant, G , is one of the most fundamental constants of nature, but we still do not have an accurate value for it. Despite two centuries of experimental effort, the value of G remains the least precisely known of the fundamental constants. A discrepancy of up to 0.05 per cent in recent determinations of G suggests that there may be undiscovered systematic errors in the various existing methods. One way to resolve this issue is to measure G using a number of methods that are unlikely to involve the same systematic effects. Here we report two independent determinations of G using torsion pendulum experiments with the time-of-swing method and the angular-acceleration-feedback method. We obtain G values of 6.674184 × 10 −11 and 6.674484 × 10 −11 cubic metres per kilogram per second squared, with relative standard uncertainties of 11.64 and 11.61 parts per million, respectively. These values have the smallest uncertainties reported until now, and both agree with the latest recommended value within two standard deviations. The Newtonian gravitational constant is measured with two independent methods, yielding results with relative standard uncertainties of 11.6 parts per million—the lowest uncertainty reported until now.

A simple approach to enable water-management agencies employing free data to create a single set of water quality predictive equations with satisfactory accuracy is proposed. Multiple regression-derived equations based on surface reflectance, band ratios, and environmental factors as predictor variables for concentrations of Total Suspended Solids (TSS) and Total Nitrogen (TN) were derived using a hybrid forward-selection method that considers both p-value and Variance Inflation Factor (VIF) in the forward-selection process. Landsat TM, ETM+, and OLI/TIRS images were jointly utilized with environmental factors, such as wind speed and water surface temperature, to derive the single set of equations. Through splitting data into calibration and validation groups, the coefficients of determination are 0.73 for TSS calibration and 0.70 for TSS validation, respectively. The coefficients of determination for TN calibration and validation are 0.64 and 0.37, respectively. Among all chosen predictor variables, ratio of reflectance of visible red (Band 3 for Landsat TM and ETM+, or Band 4 for Landsat OLI/TIRS) to visible blue (Band 1 for Landsat TM and ETM+, or Band 2 for Landsat OLI/TIRS) has a strong influence on the predictive power for TSS retrieval. Environmental factors including wind speed, remote sensing-derived water surface temperature, and time difference (in days) between the image acquisition and water sampling were found to be important in water-quality quantity estimation. The hybrid forward-selection method consistently yielded higher validation accuracy than that of the conventional forward-selection approach.

To investigate the association of bilateral high-frequency hearing loss (BHFHL) with blood pressure and hypertension among occupational noise exposed workers. Occupational noise exposed workers were enrolled in 2017 from the occupational diseases survey of Chengdu. BHFHL was classified as normal, mild, or high by the bilateral high-frequency tone average. Linear regression model was used to assess the effects of occupational noise exposure time and BHFHL on blood pressure. Logistic regression model was performed to estimate hypertension risk odds ratios (ORs) associated to occupational noise exposure time and BHFHL. Increasing years of occupational noise exposure and BHFHL were significantly associated with systolic and diastolic blood pressure increase (all P<0.001). The lineal trend was only significant in males, with adjusted ORs for hypertension gradually increasing with increasing years of occupational noise exposure (P<0.001). Furthermore, subjects having mild and high BHFHL had a higher hypertension risk of 34% and 281%, respectively (both P<0.001). Dose-response relationship between BHFHL and hypertension was found in both males and females. Occupational noise exposure was positively associated with blood pressure levels and hypertension risk.

Telemedicine interventions may be associated with reductions in hospital admission rate and mortality in patients with heart failure (HF). The present study is an updated analysis (as of June 30, 2016) of randomized controlled trials, where patients with HF underwent telemedicine care or the usual standard care. Data were extracted from 39 eligible studies for all-cause and HF-related hospital admission rate, length of stay, and mortality. The overall all-cause mortality (pooled OR=0.80, 95% CI 0.71 to 0.91, p<0.001), HF-related admission rate (pooled OR=0.63, 95% CI 0.53 to 0.76, p<0.001), and HF-related length of stay (pooled standardized difference in means=−0.37, 95% CI −0.72 to −0.02, p=0.041) were significantly lower in the telemedicine group (teletransmission and telephone-supported care), as compared with the control group. In subgroup analysis, all-cause mortality (pooled OR=0.69, 95% CI 0.56 to 0.86, p=0.001), HF-related admission rate (OR=0.61, 95% CI 0.42 to 0.88, p=0.008), HF-related length of stay (pooled standardized difference in means=−0.96, 95% CI −1.88 to −0.05, p=0.039) and HF-related mortality (OR=0.68, 95% CI 0.54 to 0.85, p=0.001) were significantly lower in the teletransmission group, as opposed to the standard care group, whereas only HF-related admission rate (OR=0.64, 95% CI 0.52 to 0.79, p<0.001) was lower in the telephone-supported care group. Overall, telemedicine was shown to be beneficial, with home-based teletransmission effectively reducing all-cause mortality and HF-related hospital admission, length of stay and mortality in patients with HF.

The unrivaled computing capabilities of modern GPUs meet the demand of processing massive amounts of data seen in many application domains. While traditional HPC systems support applications as standalone entities that occupy entire GPUs, there are GPU-based DBMSs where multiple tasks are meant to be run at the same time in the same device. To that end, system-level resource management mechanisms are needed to fully unleash the computing power of GPUs in large data processing, and there were some researches focusing on it. In our previous work, we explored the single compute-bound kernel modeling on GPUs under NVidia's CUDA framework and provided an in-depth anatomy of the NVidia's concurrent kernel execution mechanism (CUDA stream). This paper focuses on resource allocation of multiple GPU applications towards optimization of system throughput in the context of systems. Comparing to earlier studies of enabling concurrent tasks support on GPU such as MultiQx-GPU, we use a different approach that is to control the launching parameters of multiple GPU kernels as provided by compile-time performance modeling as a kernel-level optimization and also a more general pre-processing model with batch-level control to enhance performance. Specifically, we construct a variation of multi-dimensional knapsack model to maximize concurrency in a multi-kernel environment. We present an in-depth analysis of our model and develop an algorithm based on dynamic programming technique to solve the model. We prove the algorithm can find optimal solutions (in terms of thread concurrency) to the problem and bears pseudopolynomial complexity on both time and space. Such results are verified by extensive experiments running on our microbenchmark that consists of real-world GPU queries. Furthermore, solutions identified by our method also significantly reduce the total running time of the workload, as compared to sequential and MultiQx-GPU executions.