Optimal design of sand blown wind tunnel

This work investigates the airflow driven by dual axial-flow fans in an atmospheric boundary layer (ABL) wind tunnel and the expected entrainment of sand movement together. The present study is conducted via 3D numerical simulation based on modelling the entire wind tunnel, including the power fan sections. Three configurations of dual fans in the tunnel are proposed. Simulation results show that the airflow in the tunnel with dual-fan configuration can satisfy the logarithmic distribution law for ABL flows. The airflow driven by the dual fans placed together at the tunnel outlet is highly similar to that in the tunnel with single fans. Although the boundary layer thickness is reduced, the maximum airflow velocity (53.393 m/s) and turbulence intensity (12.02%), which are respectively 1.75 and 1.49 times higher than those under the single-fan configuration, can be reached when dual fans are separately placed at the tunnel inlet and outlet. The simulation and experiment manifest that the separated arrangement of dual fans in the tunnel should be suitable for the experimental study of aeolian sand transport. Some measures, such as wind tunnel construction adjustment and optimal roughness element arrangement, are necessary to guarantee the required boundary layer thickness in the wind tunnel

Quantum algorithms for optimal effective theory of many-body systems

A common situation in quantum many-body physics is that the underlying theories are known but too complicated to solve efficiently. In such cases, one usually builds simpler effective theories as low-energy or large-scale alternatives to the original theories. Here the central tasks are finding the optimal effective theories among a large number of candidates and proving their equivalence to the original theories. Recently quantum computing has shown the potential of solving quantum many-body systems by exploiting its inherent parallelism. It is thus an interesting topic to discuss the emergence of effective theories and design efficient tools for finding them based on the results from quantum computing. As the first step towards this direction, in this paper, we propose two approaches that apply quantum computing to find the optimal effective theory of a quantum many-body system given its full Hamiltonian. The first algorithm searches the space of effective Hamiltonians by quantum phase estimation and amplitude amplification. The second algorithm is based on a variational approach that is promising for near-future applications.Comment: 8 pages, 4 figure

The Effects of Benefit Timing and Income Fungibility on Food Purchasing Decisions among SNAP Households

The Supplemental Nutrition Assistance Program (SNAP) is the largest nutritional safety net in the United States. Prior research has found that participants have higher consumption shortly after receiving their benefits, followed by lower consumption towards the end of the benefit month. This “SNAP benefit cycle” has been found to have negative effects on beneficiaries. We examine two behavioral responses of SNAP participants that may work in tandem to drive much of the cycle: short-run impatience – a higher preference to consume today; and fungibility of income – the degree of substitutability between a SNAP dollar and a cash dollar. Using data from the National Food Acquisition and Purchase Survey (FoodAPS), we find evidence of both behavioral responses. The degree of short-run impatience and fungibility of income is found to differ significantly across poverty levels and use of grocery lists to plan food purchases. Food purchase planning education could be used to counter the observed benefit cycle. Deeper analysis of the purchase data suggests that the benefit cycle is primarily associated with a decrease in the purchase of healthful and perishable foods—which could lead to lower dietary quality. We also find evidence that suggests households compensate for the effects of the SNAP benefit cycle by acquiring free food, primarily from schools. This highlights the importance of programs like the National School Lunch Program for SNAP households

The link between diabetic retinal and renal microvasculopathy is associated with dyslipidemia and upregulated circulating level of cytokines

PurposeTo investigate the mechanisms underlying the correlations between diabetic retinopathy (DR) and diabetic nephropathy (DKD) and examine whether circulating cytokines and dyslipidemia contribute to both DR and DKD in patients with 2 diabetes mellitus (T2DM).MethodsA total of 122 patients with T2DM were enrolled and categorized into the DM group (without no DR and DKD), DR group [non-proliferative DR (NPDR), and proliferative DR (PDR)] with no DKD), DR complicated with DKD groups (DR+DKD group). The biochemical profile, including fasting blood glucose (FBG), glycated hemoglobin (HbA1c), and lipid profile were estimated, and plasma inflammatory and angiogenic cytokines [monocyte chemoattractant protein-1 (MCP-1), interleukin (IL)-6, IL-8, vascular endothelial growth factor (VEGF)-A, C, D, and placental growth factor (PlGF)] were analyzed by protein microarrays. The atherogenic plasma index (API) was defined as low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein-cholesterol (HDL-C); atherogenic index (AI) was calculated as [(total cholesterol (TC) -HDL-C)/HDL-C], and atherogenic index of plasma (AIP) was defined as log (TG/HDL-C).ResultsBy multivariable disordered regression analysis, after controlling for duration of DM and hypertension, LDL-C (p = 0.019) and VEGF-D (p = 0.029) resulted as independent risk factors for DR. Albumin-to-creatinine ratio (uACR) (p = 0.003) was an independent risk factor for DR with DKD. In DR, NPDR, and PDR groups, grades of A1, A2, and A3 of albuminuria increased with the severity of DR. In A1, A2, and A3 grade groups, the severity of DR (DM, NPDR, and PDR) increased with higher albuminuria grades. Kendall's tau-b correlation coefficient analysis revealed that FBG (p = 0.019), circulating level of PlGF (p = 0.002), and VEGF-D (p = 0.008) were significantly positively correlated with the grades of uACR (p < 0.001), and uACR grades were significantly correlated with DR severity (p < 0.001).ConclusionsThe occurrence and severity of DR are closely correlated with kidney dysfunction. Among the three kidney functional parameters, uACR resulted as the better indicator of DR severity and progression than glomerular filtration (eGFR) and serum creatinine (Scr). Impaired FBG was associated with microalbuminuria, emphasizing that well-controlled FBG is important for both DR and DKD. The link between diabetic retinal and renal microvasculopathy was associated with dyslipidemia and upregulated circulating level of angiogenic cytokines

A Comprehensive Model for Real Gas Transport in Shale Formations with Complex Non-planar Fracture Networks

A complex fracture network is generally generated during the hydraulic fracturing treatment in shale gas reservoirs. Numerous efforts have been made to model the flow behavior of such fracture networks. However, it is still challenging to predict the impacts of various gas transport mechanisms on well performance with arbitrary fracture geometry in a computationally efficient manner. We develop a robust and comprehensive model for real gas transport in shales with complex non-planar fracture network. Contributions of gas transport mechanisms and fracture complexity to well productivity and rate transient behavior are systematically analyzed. The major findings are: simple planar fracture can overestimate gas production than non-planar fracture due to less fracture interference. A “hump” that occurs in the transition period and formation linear flow with a slope less than 1/2 can infer the appearance of natural fractures. The sharpness of the “hump” can indicate the complexity and irregularity of the fracture networks. Gas flow mechanisms can extend the transition flow period. The gas desorption could make the “hump” more profound. The Knudsen diffusion and slippage effect play a dominant role in the later production time. Maximizing the fracture complexity through generating large connected networks is an effective way to increase shale gas production

Raising ABV Levels, Alcohol Consumption and Alcohol-Related Motor Vehicle Fatalities in the United States

Over the past 10 years, five states have proposed to raise the alcohol by volume (ABV) limit on beer being sold to promote the beer brewery industry in their states. An increase in ABV limits increases the variety of beer being sold and may change people’s consumption behavior. Such changes could subsequently influence drinking behaviors as well as driving safety in those states. This paper investigates the relationship between the increase in ABV limits and individual alcohol consumption and alcohol-related fatal crashes. We use difference-in-difference model to analyze the alcohol consumption before and after the rising ABV limit. Our panel data allows us to control for state and time fixed effects, state level economic conditions and beer consumption. We find higher ABV limits lead to a slight increase in alcohol consumption as well as a negative effect on alcohol-related fatality rate

A numerical investigation on the unidirectional unsteady oscillatory wind flow over a fixed isolated downsized barchan dune

Turbulent wind patterns over a two-dimensional isolated downsized barchan dune under the influence of sinusoidal inflow with different amplitudes and periods are simulated. The evolution rules of wind velocity over time at different positions are revealed. The flow reattachment distance and turbulence intensity distribution are also compared. The results show that wind velocities at different positions of the dune whose similar evolvement process of going from short-term fast adjustment transition to long-term stable sinusoidal fluctuation, can be reasonably estimated by the present simulation. It is found that, for the leeward toe of a dune with complex reversed flow, the balance position value of the sinusoidal wind velocity fluctuation is no longer close to the value of the steady wind velocity but shows a velocity deviation of about 0.40m/s. The flow reattachment distances under different unsteady inflows ultimately show a sinusoidal fluctuation with time, and their values are all larger than that of the steady flow. These synthetically predict that the unsteady flow has a stronger shaping effect on the leeward side of the dune body by enhancing sand transport. In addition, the predicted distribution comparison between unsteady wind velocity and turbulence intensity indicates that the unsteady wind velocity has a dominant effect on the turbulence intensity

A Numerical Study of Aeolian Sand Particle Flow Incorporating Granular Pseudofluid Optimization and Large Eddy Simulation

A numerical investigation of aeolian sand particle flow in atmospheric boundary layer is performed with a Eulerian–Eulerian granular pseudofluid model. In this model, the air turbulence is modelled with a large eddy simulation, and a kinetic–frictional constitutive model incorporating frictional stress and the kinetic theory of granular flow is applied to describe the interparticle movement. The simulated profiles of streamwise sand velocity and sand mass flux agree well with the reported experiments. The quantitative discrepancy between them occurs near the sand bed surface, which is due to the difference in sand sample, but also highlights the potential of the present model in addressing near-surface mass transport. The simulated profiles of turbulent root mean square (RMS) particle velocity suggest that the interparticle collision mainly account for the fluctuation of sand particle movement

Yet Another Effective Dendritic Neuron Model Based on the Activity of Excitation and Inhibition

Neuronal models have remained an important area of research in computer science. The dendritic neuron model (DNM) is a novel neuronal model in recent years. Previous studies have focused on training DNM using more appropriate algorithms. This paper proposes an improvement to DNM based on the activity of excitation and proposes three new models. Each of the three improved models are designed to mimic the excitation and inhibition activity of neurons. The improved model proposed in this paper is shown to be effective in the experimental part. All three models and original DNM have their own strengths, so it can be considered that the new model proposed in this paper well enriches the diversity of neuronal models and contributes to future research on networks models

Arsenic Adsorption and Desorption in Various Aqueous Media in the Nearshore Zone and Influencing Factors

A profound understanding of the adsorption and desorption characteristics of arsenic on various media in aqueous solutions is helpful for evaluating the behavior of arsenic in groundwater. In this study, the characteristics of arsenic adsorption and desorption on aqueous media including silty clay, fine sand, medium sand, and coarse sand with gravel from Shenyang Huangjia water source, China were investigated by batch experiments. The results showed that the aqueous media in the study area had a strong fixation ability for arsenic, and both physical and chemical adsorption of arsenic occurred. Among them, silty clay had the strongest adsorption capacity and the largest buffer capacity for arsenic. As the specific surface area (SSA) of the medium decreased, the adsorption capacity decreased, and the desorption capacity increased. There was an obvious positive correlation between the desorption capacity and adsorption capacity of arsenic, and the force of the adsorption process was larger than that of the desorption process. The pH, temperature, carbonate, and ionic strength all affected the arsenic adsorption and desorption, and adsorption of arsenic occurred mainly by obligate adsorption in the study area