Characterization and modeling of a noncollinearly phase-matchedfemtosecond optical parametric oscillator based on KTA and operating tobeyond 4 μm

We describe the design and operation of a critically phase-matched femtosecond optical parametric oscillator based on KTA. By employing a small pump-signal noncollinear angle, tuning of the idler to beyond 4 μm is achieved using a Ti:sapphire pump laser. A Gaussian-beam model is described which can be used to identify the optimal noncollinear phase-matching geometry. Idler and signal pulses are characterized fully both temporally and spectrally and interferometric autocorrelation data at 3.5 μm showing idler pulses of only eight optical cycles duration are presented     

不去健身房 锻炼随时随地

现代医学定义了一个健康的边缘状态,称之为"亚健康",所谓亚健康可以简单地理解为:各个生理指标虽然正常,但却有病症感觉,有潜在的发病倾向。而作为城市中快节奏生活的白领一族,拼命工作,熬夜加班,缺少锻炼,正是被亚健康状态深深困扰的一群人。     

Alpha Fusion Adversarial Attack Analysis Using Deep Learning

The deep learning model encompasses a powerful learning ability that integrates the feature extraction, and classification method to improve accuracy. Convolutional Neural Networks (CNN) perform well in machine learning and image processing tasks like segmentation, classification, detection, identification, etc. The CNN models are still sensitive to noise and attack. The smallest change in training images as in an adversarial attack can greatly decrease the accuracy of the CNN model. This paper presents an alpha fusion attack analysis and generates defense against adversarial attacks. The proposed work is divided into three phases: firstly, an MLSTM-based CNN classification model is developed for classifying COVID-CT images. Secondly, an alpha fusion attack is generated to fool the classification model. The alpha fusion attack is tested in the last phase on a modified LSTM-based CNN (CNN-MLSTM) model and other pre-trained models. The results of CNN models show that the accuracy of these models dropped greatly after the alpha-fusion attack. The highest F1 score before the attack was achieved is 97.45 And after the attack lowest F1 score recorded is 22%. Results elucidate the performance in terms of accuracy, precision, F1 score and Recall.     

A dynamic bibliometric model for identifying online communities

Predictive modelling of online dynamic user-interaction recordings and community identification from such data becomes more and more important with the widespread use of online communication technologies. Despite of the time-dependent nature of the problem, existing approaches of community identification are based on static or fully observed network connections. Here we present a new, dynamic generative model for the inference of communities from a sequence of temporal events produced through online computer- mediated interactions. The distinctive feature of our approach is that it tries to model the process in a more realistic manner, including an account for possible random temporal delays between the intended connections. The inference of these delays from the data then forms an integral part of our state-clustering methodology, so that the most likely communities are found on the basis of the likely intended connections rather than just the observed ones. We derive a maximum likelihood estimation algorithm for the identification of our model, which turns out to be computationally efficient for the analysis of historical data and it scales linearly with the number of non-zero observed (L + 1)-grams, where L is the Markov memory length. In addition, we also derive an incremental version of the algorithm, which could be used for real-time analysis. Results obtained on both synthetic and real-world data sets demonstrate the approach is flexible and able to reveal novel and insightful structural aspects of online interactions. In particular, the analysis of a full day worth synchronous Internet relay chat participation sequence, reveals the formation of an extremely clear community structure.     

Effects of humidity changes on damping and stress relaxation in wood

Mechanical damping (tan ) and stress relaxation on pine veneer samples under stepwise humidity changes were investigated. The loss factor shows a transient peak every time the relative humidity (RH) of the surrounding atmosphere is changed. The effect appears to be associated with the diffusion of water molecules into or out of the material, the peaks being observed both when the sample is humidified (5%–85% RH) or subjected to drying. The results are supplemented by stress relaxation data obtained on similar specimens. Also in this case a higher relaxation rate is observed when the RH level around the sample is changed, the total stress decrease after several cycles being significantly larger than the corresponding value observed after the same period at the higher RH level.     

Modeling industrial thickener using computational fluid dynamics (CFD), a case study: Tailing thickener in the Sarcheshmeh copper mine

Separation of particles from liquid in the large gravitational tanks is widely used in mining and industrial wastewater treatment process. Thickener is key unit in the operational processes of hydrometallurgy and is used to separate solid from liquid. In this study, population balance models were combined with computational fluid dynamics (CFD) for modeling the tailing thickener. Parameters such as feed flow rate, flocculant dosage, inlet solid percent and feedwell were investigated. CFD was used to simulate the industrial tailing thickener with settled bed of 120 m diameter which is located in the Sarcheshmeh copper mine. Important factor of drag force that defines the rake torque of rotating paddles on the bed was also determined. Two phases turbulence model of Eulerian/Eulerian in accordance with turbulence model of k-ε was used in the steady-state. Also population balance model consists of 15 groups of particle sizes with Luo and Lehr kernel was used for aggregation/breakage kernel. The simulation results showed good agreement with the operational data.     

Multi-product multi-chance-constraint stochastic inventory control problem with dynamic demand and partial back-ordering: A harmony search algorithm

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms.     

Topic Identification in Dynamical Text by Complexity Pursuit

The problem of analysing dynamically evolving textual data has arisen within the last few years. An example of such data is the discussion appearing in Internet chat lines. In this Letter a recently introduced source separation method, termed as complexity pursuit, is applied to the problem of finding topics in dynamical text and is compared against several blind separation algorithms for the problem considered. Complexity pursuit is a generalisation of projection pursuit to time series and it is able to use both higher-order statistical measures and temporal dependency information in separating the topics. Experimental results on chat line and newsgroup data demonstrate that the minimum complexity time series indeed do correspond to meaningful topics inherent in the dynamical text data, and also suggest the applicability of the method to query-based retrieval from a temporally changing text stream. This revised version was published online in June 2006 with corrections to the Cover Date.     

High molecular weight plasticizers in thermoplastic starch/polyethylene blends

In this study thermoplastic starch (TPS) was prepared with four different molecular weight polyol plasticizers: glycerol, sorbitol, diglycerol and polyglycerol. Diglycerol-TPS (DTPS) and polyglycerol-TPS (PTPS) show significantly lower moisture uptake and a higher temperature stability when compared to conventional glycerol-TPS (GTPS). TPS formulations were blended with HDPE at a concentration of 20 TPS/80 HDPE wt% and a range of interfacial modifier contents via a one-step extrusion process. The emulsification curves of the blends, which track the volume and number average diameter of the dispersed TPS domains with per cent interfacial modifier, show significantly different profiles and a non-correspondence between the d _n and d _v values at the critical concentration for interfacial saturation. The addition of small amounts of interfacial modifier to the blends prepared with diglycerol and polyglycerol results in TPS dispersed phases of wide polydispersity with droplets in the order of 200–300 nm coexisting with droplets of 5–7 µm. This wide polydispersity of TPS phase size can give insight into the mechanism of droplet formation in these systems with interfacial modifier and is indicative of an erosion-type mechanism, where small portions of the TPS droplet break off at the outer part of the droplet. Blends prepared with GTPS and sorbitol-TPS do not display this behaviour and show a more classic correspondence of d _n and d _v at the critical concentration. Dynamic mechanical analysis shows miscible behaviour for DTPS and PTPS and partially miscible behaviour for GTPS. This phenomenon was attributed to the presence of ether bonds in the chemical structure of diglycerol and polyglycerol. The increased chain flexibility and lower cohesive energy forces of diglycerol and polyglycerol lead to a more homogeneous TPS phase and consequently an erosion-type compatibilization at the interface. The mechanical properties of blends prepared with polyglycerol and diglycerol show a similar overall behaviour to glycerol.     

Investigation of Freeze Lining in Copper-Containing Slag Systems: Part III. High-Temperature Experimental Investigation of the Effect of Bath Agitation

Freeze-lining technologies have been employed to protect the cooling walls of reactors from chemically aggressive molten reactants. To date, the designs of freeze linings for pyrometallurgical reactors have been based on the basic assumption that the interface between the deposit and the bath remains at the liquidus temperature of the bulk liquid. There is, however, increasing evidence that interface temperature between stagnant deposit and bath is less than the liquidus of the bulk liquid. A previous study also demonstrated that the effects of bath chemistry need to be taken into account in freeze-lining designs. To investigate the fundamental processes involved in the formation and stability of the deposit, experimental laboratory studies have been undertaken in the Cu-Fe-Si-Al-O slag system in equilibrium with metallic copper using an air-cooled probe technique. In the current study, the effects of bath agitation on the microstructure, morphologies of the phases, and formation of various layers across the freeze-lining deposit were studied at steady-state conditions. It appears that the changes in the fluid flow pattern through changes in shear intensities result in corresponding changes in the deposit microstructure, formation of the sealing primary phase layer, thus influencing the interface temperature between freeze-lining deposit and the liquid bath.