Experimental research on mechanical properties of desert sand steel-PVA fiber engineered cementitious composites

An orthogonal experimental design method involving five-factor and four-level is adopted for the mix design of Desert Sand Steel-PVA fiber ECC. The effect of each level on Mechanical properties of ECC and the difference of Mechanical properties between each level is analyzed. The influence of different experimental factors is discussed, which includes water-binder ratio, fly ash substitution rate, desert sand substitution rate, proportion of PVA fiber and proportion of steel fiber. The experimental results indicate that water-binder ratio and fly ash substitution rate are the most principal and significant influencing factors on the compressive strength of ECC, regardless of age. Steel fiber is conducive to development of splitting tensile strength; PVA fiber is conducive to the development of flexural strength. High strength ECC can be prepared when the desert sand substitution rate is high. As the raw material of ECC, river sand can be 90% replaced by desert sand

Robust Hybrid Algorithm of PSO and SOCP for Grating Lobe Suppression and against Array Manifold Mismatch

Based on Particle Swarm Optimization (PSO) and Second-Order Cone Programming (SOCP) algorithm, this paper proposes a hybrid optimization method to suppress the grating lobes of sparse arrays and improve the robustness of array layout. With the peak side-lobe level (PSLL) as the objective function, the paper adopts the particle swarm optimization as a global optimization algorithm to optimize the elements’ positions, the convex optimization as a local optimization algorithm to optimize the elements’ weights. The effectiveness of the grating lobes suppression (as low as -32.13 dB) by this method is illustrated through its application to the sparse linear array when the actual steering vector is known. To enhance the robustness of the optimized array, a rebuilt robust convex optimization model is adopted in the optimization of both array excitations and layout. When the array manifold mismatch error is 1cm, the PSLL by the robust algorithm can be compressed to -27dB, compared to that of -24dB by the ordinary optimization. Results of a set of representative numerical experiments show that the algorithm proposed in this paper can obtain a more robust array layout and matched elements’ weight coefficients to avoid the huge degradation of the array pattern performance in the presence of array manifold mismatch errors. The good performance of pattern synthesis demonstrates the effectiveness of the proposed robust algorithm

Didymin improves UV irradiation resistance in C. elegans

Didymin, a type of flavono-o-glycoside compound naturally present in citrus fruits, has been reported to be an effective anticancer agent. However, its effects on stress resistance are unclear. In this study, we treated Caenorhabditis elegans with didymin at several concentrations. We found that didymin reduced the effects of UV stressor on nematodes by decreasing reactive oxygen species levels and increasing superoxide dismutase (SOD) activity. Furthermore, we found that specific didymin-treated mutant nematodes daf-16(mu86) & daf-2(e1370), daf-16(mu86), akt-1(ok525), akt-2(ok393), and age-1(hx546) were susceptible to UV irradiation, whereas daf-2(e1371) was resistant to UV irradiation. In addition, we found that didymin not only promoted DAF-16 to transfer from cytoplasm to nucleus, but also increased both protein and mRNA expression levels of SOD-3 and HSP-16.2 after UV irradiation. Our results show that didymin affects UV irradiation resistance and it may act on daf-2 to regulate downstream genes through the insulin/IGF-1-like signaling pathway

Network analysis of cold cognition and depression in middle-aged and elder population: the moderation of grandparenting

BackgroundCognitive decline and negative emotions are common in aging, especially decline in cold cognition which often co-occurred with depression in middle-aged and older adults. This study analyzed the interactions between cold cognition and depression in the middle-aged and elder populations using network analysis and explored the effects of grandparenting on the cold cognition-depression network.MethodsThe data of 6,900 individuals (≥ 45 years) from the China Health and Retirement Longitudinal Study (CHARLS) were used. The Minimum Mental State Examination (MMSE) and the Epidemiology Research Center Depression Scale-10 (CESD-10) were used to assess cold cognition and depressive symptoms, respectively. Centrality indices and bridge centrality indices were used to identify central nodes and bridge nodes, respectively.ResultsNetwork analysis showed that nodes “language ability” and “depressed mood” were more central nodes in the network of cold cognition and depression in all participants. Meantime, nodes “attention,” “language ability” and “hopeless” were three key bridge nodes connecting cold cognition and depressive symptoms. Additionally, the global connectivity of the cold cognition and depression network was stronger in the non-grandparenting than the grandparenting.ConclusionThe findings shed a light on the complex interactions between cold cognition and depression in the middle-aged and elder populations. Decline in language ability and depressed mood can serve as predictors for the emergence of cold cognitive dysfunction and depression in individuals during aging. Attention, language ability and hopelessness are potential targets for psychosocial interventions. Furthermore, grandparenting is effective in alleviating cold cognitive dysfunction and depression that occur during individual aging

The Market for Organic Canned Corn in Germany and the United States

This market research paper has been prepared under the supervision of Prof. Dr. Wolfgang Veit of TH Köln and Prof. Dr. Carol Scovotti of University of Wisconsin-Whitewater in the course of the inter-university cross-border collaboration student research project “Export Opportunity Surveys (EOS)”. This study explores organic canned corn export opportunities to the German and US markets

Graphene/silicon heterojunction for reconfigurable phase-relevant activation function in coherent optical neural networks

Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network performances and on-chip AF devices are still in development. Here, we first demonstrate on-chip reconfigurable AF devices with phase activation fulfilled by dual-functional graphene/silicon (Gra/Si) heterojunctions. With optical modulation and detection in one device, time delays are shorter, energy consumption is lower, reconfigurability is higher and the device footprint is smaller than other on-chip AF strategies. The experimental modulation voltage (power) of our Gra/Si heterojunction achieves as low as 1 V (0.5 mW), superior to many pure silicon counterparts. In the photodetection aspect, a high responsivity of over 200 mA/W is realized. Special nonlinear functions generated are fed into a complex-valued ONN to challenge handwritten letters and image recognition tasks, showing improved accuracy and potential of high-efficient, all-component-integration on-chip ONN. Our results offer new insights for on-chip ONN devices and pave the way to high-performance integrated optoelectronic computing circuits