Pseudo-solidification of dredged marine soils with cement - fly ash for reuse in coastal development

The dislodged and removed sediments from the seabed, termed dredged marine soils, are generally classified as a waste material requiring special disposal procedures. This is due to the potential contamination risks of transporting and disposing the dredged soils, and the fact that the material is of poor engineering quality, unsuitable for usage as a conventional good soil in construction. Also, taking into account the incurred costs and risk exposure in transferring the material to the dump site, whether on land or offshore, it is intuitive to examine the possibilities of reusing the dredged soils, especially in coastal development where the transportation route would be of shorter distance between the dredged site and the construction location. Pseudo-solidification of soils is not a novel idea though, where hydraulic binders are injected and mixed with soils to improve the inherent engineering properties for better load bearing capacity. It is commonly used on land in areas with vast and deep deposits of soft, weak soils. However, to implement the technique on the displaced then replaced dredged soil would require careful study, as the material is far more poorly than their land counterparts, and that the deployment of equipment and workforce in a coastal environment is understandably more challenging. The paper illustrates the laboratory investigation of the improved engineering performance of dredged marine soil sample with cement and fly ash blend. Some key findings include optimum dosage of cement and fly ash mix to produce up to 30 times of small strain stiffness improvement, pre-yield settlement reduction of the treated soil unaffected by prolonged curing period, and damage of the cementitious bonds formed by the rather small dosage of admixtures in the soil post-yield. In short, the test results show a promising reuse potential of the otherwise discarded dredged marine soils

Three-step Formation of Diamonds in Shock-compressed Hydrocarbons: Decomposition, Species Separation, and Nucleation

The accumulation and circulation of carbon-hydrogen dictate the chemical evolution of ice giant planets. Species separation and diamond precipitation have been reported in carbon-hydrogen systems, verified by static and shock-compression experiments. Nevertheless, the dynamic formation processes for the above-mentioned phenomena are still insufficiently understood. Here, combing deep learning model, we demonstrate that diamonds form through a three-step process involving decomposition, species separation and nucleation procedures. Under shock condition of 125 GPa and 4590 K, hydrocarbons are decomposed to give hydrogen and low-molecular-weight alkanes (CH4 and C2H6), which escape from the carbon chains resulting in C/H species separation. The remaining carbon atoms without C-H bonds accumulate and nucleate to form diamond crystals. The process of diamond growth is found to associated with a critical nucleus size where dynamic energy barrier plays a key role. These dynamic processes for diamonds formation are insightful in establishing the model for ice giant planet evolution.Comment: 5 figure

The Synergistic Effect of Valsartan and LAF237 [(S)-1-[(3-Hydroxy-1-Adamantyl)Ammo]acetyl-2-Cyanopyrrolidine] on Vascular Oxidative Stress and Inflammation in Type 2 Diabetic Mice

Aim. To investigate the combination effects and mechanisms of valsartan (angiotensin II type 1 receptor blocker) and LAF237 (DPP-IV inhibitor) on prevention against oxidative stress and inflammation injury in db/db mice aorta. Methods. Db/db mice (n = 40) were randomized to receive valsartan, LAF237, valsartan plus LAF237, or saline. Oxidative stress and inflammatory reaction in diabetic mice aorta were examined. Results. Valsartan or LAF237 pretreatment significantly increased plasma GLP-1 expression, reduced apoptosis of endothelial cells isolated from diabetic mice aorta. The expression of NAD(P)H oxidase subunits also significantly decreased resulting in decreased superoxide production and ICAM-1 (fold change: valsartan : 7.5 ± 0.7, P < 0.05; LAF237: 10.2 ± 1.7, P < 0.05), VCAM-1 (fold change: valsartan : 5.2 ± 1.2, P < 0.05; LAF237: 4.8 ± 0.6, P < 0.05), and MCP-1 (fold change: valsartan: 3.2 ± 0.6, LAF237: 4.7 ± 0.8; P < 0.05) expression. Moreover, the combination treatment with valsartan and LAF237 resulted in a more significant increase of GLP-1 expression. The decrease of the vascular oxidative stress and inflammation reaction was also higher than monotherapy with valsartan or LAF237. Conclusion. These data indicated that combination treatment with LAF237 and valsartan acts in a synergistic manner on vascular oxidative stress and inflammation in type 2 diabetic mice

Исследование прочности концевых фрез методом конечных элементов

В процессе исследования проводились: обзор и анализ научно-технической литературы по теме магистерской работы, формулирование цели и задач исследования прочности режущих пластин концевой фрезы, проведение экспериментов для измерений технологических и физических составляющих силы резании, исследование распределения контактных напряжений на передней и задней поверхностях острозаточенного и изношенного инструмента, анализ полученных эпюр, вывод эмпирических формул для расчёта эпюр контактных напряжений, исследование НДС режущей пластины фрезы, определение оптимальной геометрии режущей пластины при обработке разных материалов.In the course of probe were spent: the review and the assaying of the scientific and technical literature on a theme of master Diploma Thesis, a formulation of the purpose and research problems of strength of cutting inserts of an end mill, carry out experiments for measurements of technological and physical components of force cutting, research of distribution of contact stresses on a rake both flank surfaces of new and the worn out cutting tool, the assaying received epures, an output empirical formulas for calculation of contact stresses, probe of the SDC of a cutting plate of a mill, definition of optimum geometry of a cutting plate in machining of different materials

Efficient Structure Slimming for Spiking Neural Networks

Spiking neural networks (SNNs) are deeply inspired by biological neural information systems. Compared to convolutional neural networks (CNNs), SNNs are low power consumption because of their spike based information processing mechanism. However, most of the current structures of SNNs are fully-connected or converted from deep CNNs which poses redundancy connections. While the structure and topology in human brain systems are sparse and efficient. This paper aims at taking full advantage of sparse structure and low power consumption which lie in human brain and proposed efficient structure slimming methods. Inspired by the development of biological neural network structures, this paper designed types of structure slimming methods including neuron pruning and channel pruning. In addition to pruning, this paper also considers the growth and development of the nervous system. Through iterative application of the proposed neural pruning and rewiring algorithms, experimental evaluations on CIFAR-10, CIFAR-100, and DVS-Gesture datasets demonstrate the effectiveness of the structure slimming methods. When the parameter count is reduced to only about 10% of the original, the performance decreases by less than 1%

A hybrid SDS and WPT-IBBO-DNM based model for ultra-short term photovoltaic prediction

Accurate photovoltaic (PV) power prediction has been a subject of ongoing study in order to address grid stability concerns caused by PV output unpredictability and intermittency. This paper proposes an ultra-short-term hybrid photovoltaic power forecasting method based on a dendritic neural model (DNM) in this paper. This model is trained using improved biogeography-based optimization (IBBO), a technique that incor�porates a domestication operation to increase the performance of classical biogeography-based optimization (BBO). To be more precise, a similar day selection (SDS) technique is presented for selecting the training set, and wavelet packet transform (WPT) is used to divide the input data into many components. IBBO is then used to train DNM weights and thresholds for each component prediction. Finally, each component’s prediction results are stacked and reassembled. The suggested hybrid model is used to forecast PV power under various weather conditions using data from the Desert Knowledge Australia Solar Centre (DKASC) in Alice Springs. The simulation results indicate that the proposed hybrid SDS and WPT-IBBO-DNM model has the lowest error of any of the benchmark models and hence has the potential to considerably enhance the accuracy of solar power forecasting (PVPF)