Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the base of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution route with and without carbon emissions cost are constructed, and fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, the path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit

Dexmedetomidine alleviates high glucose-induced podocyte damage by inhibiting EDA2R

Purpose: To investigate the effect and mechanism of action of dexmedetomidine (Dex) on podocyte injury. Methods: Cells were incubated with high glucose (50 mM) to induce a podocyte injury model in vitro. Cell viability, apoptosis, the expression of related protein related in podocyte injury and albumin permeability were evaluated by 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl tetrazolium bromide (MTT), flow cytometry, western blot and Transwell assays. Results: Dex administration enhanced HG-induced cell viability and the relative protein expression of Bcl-2, but reduced the HG-induced relative protein level of Bax and apoptosisrate in podocytes (p < 0.05). Besides, Dex incubation compensated HG-induced relative protein expressions of nephrin and podocin in podocytes but did the reverse with regard to relative protein expression of desmin and albumin permeability (p < 0.05). Moreover, Dex treatment resulted in a decrease in ectodysplasin A2 receptor (EDA2R) expression in HG-induced podocytes. The level of EDA2R was upregulated by the transfection of overexpression plasmid containing the EDA2R sequences. Overexpression of EDA2R reversed Dex-induced increase in cell viability, apoptosis, expression of nephrin, podocin and desmin, as well as albumin permeability in HG-stimulated podocytes (p < 0.05). Conclusion: Dex ameliorates HG-induced podocyte injury via inhibition of EDA2R, indicating that Dex is a potential alternative drug for the treatment of podocyte injury

Constrained Maximum Cross-Domain Likelihood for Domain Generalization

As a recent noticeable topic, domain generalization aims to learn a generalizable model on multiple source domains, which is expected to perform well on unseen test domains. Great efforts have been made to learn domain-invariant features by aligning distributions across domains. However, existing works are often designed based on some relaxed conditions which are generally hard to satisfy and fail to realize the desired joint distribution alignment. In this paper, we propose a novel domain generalization method, which originates from an intuitive idea that a domain-invariant classifier can be learned by minimizing the KL-divergence between posterior distributions from different domains. To enhance the generalizability of the learned classifier, we formalize the optimization objective as an expectation computed on the ground-truth marginal distribution. Nevertheless, it also presents two obvious deficiencies, one of which is the side-effect of entropy increase in KL-divergence and the other is the unavailability of ground-truth marginal distributions. For the former, we introduce a term named maximum in-domain likelihood to maintain the discrimination of the learned domain-invariant representation space. For the latter, we approximate the ground-truth marginal distribution with source domains under a reasonable convex hull assumption. Finally, a Constrained Maximum Cross-domain Likelihood (CMCL) optimization problem is deduced, by solving which the joint distributions are naturally aligned. An alternating optimization strategy is carefully designed to approximately solve this optimization problem. Extensive experiments on four standard benchmark datasets, i.e., Digits-DG, PACS, Office-Home and miniDomainNet, highlight the superior performance of our method

Mitigating Both Covariate and Conditional Shift for Domain Generalization

Domain generalization (DG) aims to learn a model on several source domains, hoping that the model can generalize well to unseen target domains. The distribution shift between domains contains the covariate shift and conditional shift, both of which the model must be able to handle for better generalizability. In this paper, a novel DG method is proposed to deal with the distribution shift via Visual Alignment and Uncertainty-guided belief Ensemble (VAUE). Specifically, for the covariate shift, a visual alignment module is designed to align the distribution of image style to a common empirical Gaussian distribution so that the covariate shift can be eliminated in the visual space. For the conditional shift, we adopt an uncertainty-guided belief ensemble strategy based on the subjective logic and Dempster-Shafer theory. The conditional distribution given a test sample is estimated by the dynamic combination of that of source domains. Comprehensive experiments are conducted to demonstrate the superior performance of the proposed method on four widely used datasets, i.e., Office-Home, VLCS, TerraIncognita, and PACS

Empirical Research on the Impact of Personalized Recommendation Diversity

Personalized recommendation has important implications in raising online shopping efficiency and increasing product sales. There has been wide interest in finding ways to provide more efficient personalized recommendations. Most existing studies focus on how to improve the accuracy of the recommendation algorithms, or are more concerned on ways to increase consumer satisfaction. Unlike these studies, our study focuses on the process of decision-making, using long tail theory as a basis, to reveal the mechanisms involved in consumers’ adoption of recommendations. This paper analyzes the effect of personalized recommendations from two angles: product sales and ratings, and tries to point out differences in consumer preferences between mainstream products and niche products, high rating products and low rating products, search products and experience products. The study verifies that consumers demand diversity in the recommended content, and also provides suggestions on how to better plan and operate a personalized recommendation system

Inhibition of miR-665 alleviates neuropathic pain by targeting SOCS1

Purpose: To investigate the effect of miR-665 in neuropathic pain and the possible molecular mechanism involved.Methods: A neuropathic pain model was established using chronic constriction injury (CCI) methods in Sprague Dawley (SD) rats. Mechanical and thermal hyperalgesia were measured using paw withdrawal threshold (PWT) and paw withdrawal latency (PWL), respectively. The inflammation response was determined by assessing the production of inflammation factors. The target relationship of miR-665 and suppressor of cytokine signaling 1 (SOCS1) was verified by luciferase assay.Results: In the CCI rat model, PWT and PWL decreased following treatment with miR-665 (p < 0.01). MiR-665 was elevated in the spinal cord and microglia of CCI rats at different time points (p < 0.01). Down-regulation of miR-665 increased PWT and PWL and inhibited the production of interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α in CCI rats (p < 0.01). Luciferase assay results indicate that SOCS1 was the target of miR-665 (p < 0.01). SOCS1 decreased in CCI rats (p < 0.01) after treatment with miR-665. MiR-665 negatively regulated the expression of SOCS1 (p < 0.01). Down-regulation of SOCS1 reversed the alleviating effect of decreased miR-665 on pain sensitivity and inflammationresponse (p < 0.01).Conclusion: Down-regulation of miR-665 alleviates neuropathic pain by targeting SOCS1, and hence making miR-665 a promising therapeutic target for neuropathic pain. Keywords: MiR-665, SOCS1, Neuropathic pain, CCI, Spinal cor

Mechanical Property of Al Alloy Joints by Friction Stir Blind Riveting

AbstractDissimilar lap-shear joints were fabricated by the friction stir blind riveting process using AA6111 (0.9mm) as the top-sheet and AA6022 (2.0mm) as the bottom-sheet in a 2-sheet stack-up. Tensile testing of the friction stir blind riveting joints exhibited a combined fracture mode of initial shear followed by tearing. The maximum tensile load of the friction stir blind riveting joints increases slightly with increasing feed rate and shows little dependence on the spindle speed. The microhardness of the material at different layers along with the rivet penetration are analyzed and discussed

Slag Blended Cement Paste Carbonation under Different CO(2)Concentrations: Controls on Mineralogy and Morphology of Products

To investigate the effect of different CO(2)concentrations on the carbonation results of slag blended cement pastes, carbonation experiments under natural (0.03% CO2) and accelerated conditions (3, 20, and 100% CO2) were investigated with various microscopic testing methods, including X-ray diffraction (XRD),Si-29 magic angle spinning nuclear magnetic resonance (Si-29 MAS NMR) and scanning electron microscopy (SEM). The XRD results indicated that the major polymorphs of CaCO(3)after carbonation were calcite and vaterite. The values of the calcite/(aragonite + vaterite) (c/(a + v)) ratios were almost the same in all carbonation conditions. Additionally, NMR results showed that the decalcification degree of C-S-H gel exposed to 0.03% CO(2)was less than that exposed to accelerated carbonation; under accelerated conditions, it increased from 83.1 to 84.2% when the CO(2)concentration improved from 3% to 100%. In SEM observations, the microstructures after accelerated carbonation were denser than those under natural carbonation but showed minor differences between different CO(2)concentrations. In conclusion, for cement pastes blended with 20% slag, a higher CO(2)concentration (above 3%) led to products different from those produced under natural carbonation. A further increase in CO(2)concentration showed limited variation in generated carbonation products

Many-Body Chiral Edge Currents and Sliding Phases of Atomic Spin Waves in Momentum-Space Lattice

Collective excitations (spinwaves) of long-lived atomic hyperfine states can be synthesized into a Bose-Hubbard model in momentum space. We explore many-body ground states and dynamics of a two-leg momentum-space lattice formed by two coupled hyperfine states. Essential ingredients of this setting are a staggered artificial magnetic field engineered by lasers that couple the spinwave states, and a state-dependent long-range interaction, which is induced by laser-dressing a hyperfine state to a Rydberg state. The Rydberg dressed two-body interaction gives rise to a state-dependent blockade in momentum space, and can amplify staggered flux induced anti-chiral edge currents in the many-body ground state in the presence of magnetic flux. When the Rydberg dressing is applied to both hyperfine states, exotic sliding insulating and superfluid/supersolid phases emerge. Due to the Rydberg dressed long-range interaction, spinwaves slide along a leg of the momentum-space lattice without costing energy. Our study paves a route to the quantum simulation of topological phases and exotic dynamics with interacting spinwaves of atomic hyperfine states in momentum-space lattice. Introduction-Chiral edge states have played an important role in understanding quantum Hall effects [1-3] in solid state materials [4-6]. Ultracold atoms exposed to artificial gauge fields provide an ideal platform to simulate chiral edge currents in and out of equilibrium. This is driven by the ability to precisely control and in-situ monitor [7, 8] internal and external degrees of freedom, and atom-atom interactions [9]. Chiral dynamics [10-13] has been examined in the continuum space [14, 15], ladders [16-20], and optical lattices [21-28]. However, chiral states realized in the coordinate space require extremely low temperatures (typical in the order of a few kilo Hz) to protect the topological states from being destroyed by motional fluctuations [13]. Up to now, experimental observations of chiral phenomena in ultracold gases are largely at a single-particle level, due to unavoidable dis-sipations (e.g. spontaneous emission and heating) [9, 29-33], while the realization of many-body chiral edge currents in ultracold atoms is still elusive