A novel technique of three-dimensional reconstruction segmentation and analysis for sliced images of biological tissues

A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.

Research on Cassava Drying, Application and Promotion of the Reversible Airflow Flatbed Dryers for Sliced Cassava

The study was conducted by researchers of the Research Center for Agricultural Energy and Machinery （CAEM） of the Ho Chi Minh City Nong Lam University （NLU） with the objectives of researching on drying ways for cassava and of evaluating the adaptability of the reversible-airflow dryers in drying of cassava. The results obtained were as follows： done with thin-layer drying experiments, deep-layer drying experiments in the lab, and conducted drying experiments at the cassava dryer in actual production scale with two capacity sizes of 8 tons/batch and 16 tons/batch, that operates based on principle of reversible-airflow drying （SRA dryers）. By the means of drying experiments, the performance of the SRA dryers such as optimal drying temperature, drying time, drying airflow reversal timing, moisture content uniformity of the sliced cassava mass after finishing drying process, drying cost, etc. was defined, the optimal drying temperature was 70 ~C, the total actual drying time for finishing one batch was 25-28 hours, applicable time for drying airflow reversal was after drying 16 hours since startup, the deviation in moisture content of the cassava mass after drying was just 2%-3%, the drying costs （per one kg of dried cassava） calculated were in turns VND407/kg at the SRA-8 dryer （8 tons/batch）, and VND351/kg at the SRA-16 dryer （16 tons/batch）. Obviously, comparing with the sale price of dry cassava at present, these levels of drying cost are accounting for 7%-10%, which are suitable and acceptable. Thus, investment of the dryers for sliced cassava would be effective and contribute to bring more income for Vietnamese cassava farmers and dryer end-users.

Measuring Global Warming: Global and Hemisphere Mean Temperature Anomalies Predictions Using Sliced Functional Time Series (SFTS) Model

In this study, the sliced functional time series (SFTS) model is applied to the Global, Northern and Southern temperature anomalies. We obtained the combined land-surface air and sea-surface water temperature from Goddard Institute for Space Studies (GISS), NASA. The data are available for Global mean, Northern Hemisphere mean and Southern Hemisphere means (monthly, quarterly and annual) since 1880 to present (updated through March 2019). We analyze the global surface temperature change, compare alternative analyses, and address the questions about the reality of global warming. We detected the outliers during the last century not only in global temperature series but also in northern and southern hemisphere series. The forecasts for the next twenty years are obtained using SFTS models. These forecasts are compared with ARIMA, Random Walk with drift and Exponential Smoothing State Space (ETS) models. The comparison is made on the basis of root mean square error (RMSE), mean absolute percentage error (MAPE) and the length of prediction intervals.

Bamboo Sliced Mosaic Blocks

Bamboo is a plant favored by Chinese people. Rigid, tall, straight and channing, it is honored along with cymbidium, plum blossom and chrysanthemum. Bamboo has a close relationship with people’s daily life. The poet Su Dongpo wrote the famous poem "Would rather have food without meats than live in a non-bamboo house" in the Song Dynasty. Earth Brand bamboo sliced

The Research on Sliced Boiled Chicken

Sliced boiled chicken is a kind of Chinese food which has a history of more than two hundred years.At the very beginning,it was offered to customers as a kind of fast food.After two centuries’development,it has become a cultural symbol of Guangdong region.In other words,the significance of sliced boiled chicken has transcended the food itself.It is an essential part of Cantonese life.Because it is a dish that is relatively easy to cook,we can see sliced boiled chicken everywhere in Guangdong Province,China.No matter in the city or in the countryside,in upscale restaurants or in fast food restaurants,if you want,you can easily find a place to enjoy the delicacy of sliced boiled chicken.However,most of the people just know to eat sliced boiled chicken.Only a small part of them will notice the history behind this dish.At the same time,though this dish is seen as a cultural symbol,most people just see it as a money making tool which greatly disturbs its development.

Steamed Sliced Pork with Dried Mustard Cabbage (Meigancai Kourou)

500 grams pork with skin75 grams dried mustard cabbage10 grams Shaoxing wine50 grams sugar100 grams soy sauce2 grams salt5 grams spring onions5 grams ginger500 grams clear stockClean the pork, soak the dried mustard cabbage until soft, and clean and slice the spring onion and ginger.Braise the pork in a wok,

Sliced Average Variance Estimation for Tensor Data

Tensor data have been widely used in many fields,e.g.,modern biomedical imaging,chemometrics,and economics,but often suffer from some common issues as in high dimensional statistics.How to find their low-dimensional latent structure has been of great interest for statisticians.To this end,we develop two efficient tensor sufficient dimension reduction methods based on the sliced average variance estimation(SAVE)to estimate the corresponding dimension reduction subspaces.The first one,entitled tensor sliced average variance estimation(TSAVE),works well when the response is discrete or takes finite values,but is not■consistent for continuous response;the second one,named bias-correction tensor sliced average variance estimation(CTSAVE),is a de-biased version of the TSAVE method.The asymptotic properties of both methods are derived under mild conditions.Simulations and real data examples are also provided to show the superiority of the efficiency of the developed methods.

High Performance Supercapacitors from Hierarchical Porous Carbon Aerogels Based on Sliced Bread

Supercapacitor electrodes with porous structure based on renewable,eco-friendly and cost-effective materials have caused extensive concern in energy storage fields.Sliced bread,the common food ingredient,mainly containing glucose polymers,can be a promising candidate to fabricate porous supercapacitor electrodes.Highly porous carbon aerogels by using sliced bread as the raw material were synthesized through a carefully controlled aerogel carbonization-activation process.Interestingly,the specific surface area and the pore size distribution of the porous carbon were controlled by the activation temperature,which result in the varied performance of the carbon aerogel as a supercapacitor.Electrochemical investigation measurements revealed that the hierarchical porous carbon aerogel shows an excellent capacitor behavior for construction of a symmetric supercapacitor,which demonstrated a high specific capacitance of 229 F·g-1 at discharge current of 0.2 A·g-1.In addition,the fabricated supercapacitor displayed excellent capacitance retention of 95.5% over 5000 cycles.

CLUSTER-BASED REGULARIZED SLICED INVERSE REGRESSION FOR FORECASTING MACROECONOMIC VARIABLES

This paper concerns the dimension reduction in regression for large data set. The authors introduce a new method based on the sliced inverse regression approach, cMled cluster-based regularized sliced inverse regression. The proposed method not only keeps the merit of considering both response and predictors＇ information, but also enhances the capability of handling highly correlated variables. It is justified under certain linearity conditions. An empirical application on a macroeconomic data set shows that the proposed method has outperformed the dynamic factor model and other shrinkage methods.

An Experimental Investigation on the Drying of Sliced Food Products in Centrifugal Fluidized Bed

An experimental investigation on the fluidization and drying characteristics of sliced food products in a centrifugal fluidized bed dryer was carried out. The rotating speed ranges from 300 rpm to 500 rpm.Sliced potato and radish were used as the testing materials. The results show that the sliced materials can be fluidised well in the centrifugal fluidized bed. The fiuidized curve has a maximum value and the critical fiuidised velocities Vary with the type of the test material, its shape and dimension as well as operating parameters. The sliced food materials can be dried very well and fast in the ceotrifugal fiuidised bed with a large productivity. The factors that influence the drying process were examined and discussed. The final shape and inner structure of the dried products were observed.The water recovery characteristics of the dried products were also investigated.

Spectrally sliced heterodyne coherent receiver with halved electrical bandwidth

A spectrally sliced heterodyne coherent receiver(SHCR)employing four balanced photodetectors and analog-to-digital converters with half of the signal bandwidth is proposed to complete the signal reception and field recovery.We first numerically characterize the performance of SHCR compared with an intradyne coherent receiver and then validate the principle of the SHCR in a proof-of-concept single-polarization experiment.A 60 GBaud 16-quadrature amplitude modulation transmission is experimentally demonstrated over 80 km standard single-mode fiber with a bit-error-rate of 8.5×10^(-4) below the 7%hard-decision forward error correction threshold of 3.8×10^(-3).The SHCR offers a low-cost,hybrid-free,and channel-skew-tolerant candidate for data center interconnects.

On spline approximation of sliced inverse regression

The dimension reduction is helpful and often necessary in exploring the nonparametric regression structure.In this area,Sliced inverse regression (SIR) is a promising tool to estimate the central dimension reduction (CDR) space.To estimate the kernel matrix of the SIR,we herein suggest the spline approximation using the least squares regression.The heteroscedasticity can be incorporated well by introducing an appropriate weight function.The root-n asymptotic normality can be achieved for a wide range choice of knots.This is essentially analogous to the kernel estimation.Moreover, we also propose a modified Bayes information criterion (BIC) based on the eigenvalues of the SIR matrix.This modified BIC can be applied to any form of the SIR and other related methods.The methodology and some of the practical issues are illustrated through the horse mussel data.Empirical studies evidence the performance of our proposed spline approximation by comparison of the existing estimators.

Surface micromorphology and nanostructures evolution in hybrid laser processes of slicing and polishing single crystal 4H-SiC

Slicing and post-treatment of SiC crystals have been a significant challenge in the integrated circuit and microelectronics industry.To compete with wire-sawing and mechanical grinding technology,a promis-ing approach combining laser slicing and laser polishing technologies has been innovatively applied to increase utilization and decrease damage defects for single crystal 4H-SiC.Significant material utiliza-tion has been achieved in the hybrid laser processes,where material loss is reduced by 75%compared to that of conventional machining technologies.Without any special process control or additional treat-ment,an internally modified layer formed by laser slicing can easily separate the 4H-SiC crystals using an external force of about∼3.6 MPa.The modified layer has been characterized using a micro-Raman method to determine residual stress.The sliced surface exhibits a combination of smooth and coarse appearances around the fluvial morphology,with an average surface roughness of over S_(a) 0.89μm.An amorphous phase surrounds the SiC substrate,with two dimensions of lattice spacing,d=0.261 nm and d=0.265 nm,confirmed by high-resolution transmission electron microscopy(HRTEM).The creation of laser-induced periodic surface nanostructures in the laser-polished surface results in a flatter surface with an average roughness of less than S_(a) 0.22μm.Due to the extreme cooling rates and multiple thermal cy-cles,dissociation of Si-C bonding,and phase separation are identified on the laser-polished surface,which is much better than that of the machining surface.We anticipate that this approach will be applicable to other high-value crystals and will have promising viability in the aerospace and semiconductor industries.

Stability analysis of tunnel face reinforced with face bolts

Face bolting has been widely utilized to enhance the stability of tunnel face,particularly in soft soil tunnels.However,the influence of bolt reinforcement and its layout on tunnel face stability has not been systematically studied.Based on the theory of linear elastic mechanics,this study delved into the specific mechanisms of bolt reinforcement on the tunnel face in both horizontal and vertical dimensions.It also identified the primary failure types of bolts.Additionally,a design approach for tunnel face bolts that incorporates spatial layout was established using the limit equilibrium method to enhance the conventional wedge-prism model.The proposed model was subsequently validated through various means,and the specific influence of relevant bolt design parameters on tunnel face stability was analyzed.Furthermore,design principles for tunnel face bolts under different geological conditions were presented.The findings indicate that bolt failure can be categorized into three stages:tensile failure,pullout failure,and comprehensive failure.Increasing cohesion,internal friction angle,bolt density,and overlap length can effectively enhance tunnel face stability.Due to significant variations in stratum conditions,tailored design approaches based on specific failure stages are necessary for bolt design.

Resource Allocation for Cognitive Network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning

In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.

Extraction of fractures in shale CT images using improved U-Net

Accurate extraction of pores and fractures is a prerequisite for constructing digital rocks for physical property simulation and microstructural response analysis.However,fractures in CT images are similar in grayscale to the rock matrix,and traditional algorithms have difficulty to achieve accurate segmentation results.In this study,a dataset containing multiscale fracture information was constructed,and a U-Net semantic segmentation model with a scSE attention mechanism was used to classify shale CT images at the pixel level and compare the results with traditional methods.The results showed that the CLAHE algorithm effectively removed noise and enhanced the fracture information in the dark parts,which is beneficial for further fracture extraction.The Canny edge detection algorithm had significant false positives and failed to recognize the internal information of the fractures.The Otsu algorithm only extracted fractures with a significant difference from the background and was not sensitive enough for fine fractures.The MEF algorithm enhanced the edge information of the fractures and was also sensitive to fine fractures,but it overestimated the aperture of the fractures.The U-Net was able to identify almost all fractures with good continuity,with an MIou and Recall of 0.80 and 0.82,respectively.As the image resolution increases,more fine fracture information can be extracted.

Strengthening network slicing for Industrial Internet with deep reinforcement learning

Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value chain.Its highly heterogeneous network structure and diversified application requirements call for the applying of network slicing technology.Guaranteeing robust network slicing is essential for Industrial Internet,but it faces the challenge of complex slice topologies caused by the intricate interaction relationships among Network Functions(NFs)composing the slice.Existing works have not concerned the strengthening problem of industrial network slicing regarding its complex network properties.Towards this end,we aim to study this issue by intelligently selecting a subset of most valuable NFs with the minimum cost to satisfy the strengthening requirements.State-of-the-art AlphaGo series of algorithms and the advanced graph neural network technology are combined to build the solution.Simulation results demonstrate the superior performance of our scheme compared to the benchmark schemes.

Lightweight Malicious Code Classification Method Based on Improved Squeeze Net

With the growth of the Internet,more and more business is being done online,for example,online offices,online education and so on.While this makes people’s lives more convenient,it also increases the risk of the network being attacked by malicious code.Therefore,it is important to identify malicious codes on computer systems efficiently.However,most of the existing malicious code detection methods have two problems:(1)The ability of the model to extract features is weak,resulting in poor model performance.(2)The large scale of model data leads to difficulties deploying on devices with limited resources.Therefore,this paper proposes a lightweight malicious code identification model Lightweight Malicious Code Classification Method Based on Improved SqueezeNet(LCMISNet).In this paper,the MFire lightweight feature extraction module is constructed by proposing a feature slicing module and a multi-size depthwise separable convolution module.The feature slicing module reduces the number of parameters by grouping features.The multi-size depthwise separable convolution module reduces the number of parameters and enhances the feature extraction capability by replacing the standard convolution with depthwise separable convolution with different convolution kernel sizes.In addition,this paper also proposes a feature splicing module to connect the MFire lightweight feature extraction module based on the feature reuse and constructs the lightweight model LCMISNet.The malicious code recognition accuracy of LCMISNet on the BIG 2015 dataset and the Malimg dataset reaches 98.90% and 99.58%,respectively.It proves that LCMISNet has a powerful malicious code recognition performance.In addition,compared with other network models,LCMISNet has better performance,and a lower number of parameters and computations.

3D Printing with a 5-Axis FDM Printer Using Bézier Techniques

In the last decade,3D printing,especially fused deposition modeling(FDM),has revolutionized manufacturing with intricate designs.Traditional 3-axis FDM printers face challenges with complex geometries,but 5-axis versions offer more design freedom.However,it requires specialized strategies.This research presents a model for 5-axis FDM printers using Bézier curves with an algorithm to enhance print quality.The result shows significant accuracy improvements,especially for curve-based tasks.In addition,this study deepens the understanding of 5-axis FDM technology,setting a solid basis for further research and potentially refining manufacturing methods.

基于SLICE模型的东台“三医”协同发展和治理实践分析

医疗、医保、医药协同发展和治理是实现卫生健康事业高质量发展和深化医药卫生体制改革的关键。剖析总结了江苏省东台市医疗、医保、医药协同发展和治理改革在战略设计(导航仪)、组织领导(引擎机)、资源统合(燃料箱)、协同工具(润滑剂)和评估反馈(晴雨表)全闭环方面的经验举措,提炼为“三医”协同发展和治理的SLICE模型,并提出在坚持以改革创新激发“三医”协同发展和治理活力的基础上,充分发挥各级党委、政府的主导作用,建立“三医”协同发展和治理跨部门议事协调机制,吸纳多元主体参与协同治理并强化协同治理措施的系统性,以确保“三医”协同发展和治理改革行稳致远。