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Thick-panel origami has shown great potential in engineering applications. However, the thick-panel origami created by current design methods cannot be readily adopted to structural applications due to the inefficient manufacturing methods. Here, we report a design and manufacturing strategy for creating thick-panel origami structures with excellent foldability and capability of withstanding cyclic loading. We directly print thick-panel origami through a single fused deposition modeling (FDM) multimaterial 3D printer following a wrapping-based fabrication strategy where the rigid panels are wrapped and connected by highly stretchable soft parts. Through stacking two thick-panel origami panels into a predetermined configuration, we develop a 3D self-locking thick-panel origami structure that deforms by following a push-to-pull mode enabling the origami structure to support a load over 11000 times of its own weight and sustain more than 100 cycles of 40% compressive strain. After optimizing geometric parameters through a self-built theoretical model, we demonstrate that the mechanical response of the self-locking thick-panel origami structure is highly programmable, and such multi-layer origami structure can have a substantially improved impact energy absorption for various structural applications.

Regional seismic damage analysis of building clusters based on time history analysis enables damage evolution and distribution to be obtained for structural performance evaluation, seismic loss estimation, and post-earthquake emergency response decision support. Soil–structure cluster interaction (SSCI) effects have been shown to affect significantly seismic damage to buildings due to the influence of neighboring buildings through underlying soils. However, SSCI effects in current regional seismic damage simulations are either ignored or obtained with exceptionally high computation cost due to the common discretization of large scale soil domains using finite elements. To this end, lumped parameter models (LPMs) are presented in this work as a simple effective tool for regional seismic damage simulation of SSCI systems, which is particularly useful for parametric analysis and also enables fast regional damage assessments. The LPMs combine story-based multiple-degree-of-freedom buildings with ‘foundation springs’ that are used to represent soil–foundation interaction and foundation–soil–foundation interaction. Seismic damage analysis of 320 buildings on Wangjiang campus of Sichuan University in China is used as a case study. The results of the specific case study show, that in most cases, SSCI effects result in lower damage to buildings, especially on soft soils. However, the SSCI effects may lead to higher structural damage to buildings in some cases, e.g. those on stiff soils. The results also show that using nominal inter-story drift ratio which includes foundation rocking rotation as the damage index may underestimate story seismic damage to lower stories of tall buildings.

Improving thermal transport between substrate and transistors has become a vital solution to the thermal challenge in nanoelectronics. Recently 2D WTe2 has sparked extensive interest because of heavy atomic mass and low Debye temperature. Here, the thermal transport of supported WTe2 was studied via Raman thermometry with electrical heating. The supported 30 nm WTe2 encased with 70 nm Al2O3 delivered 4.8 W·m−1·K−1 in-plane thermal conductivity along zigzag direction at room temperature, which was almost 1.6 times larger than that along armchair direction (3.0 W·m−1·K−1). Interestingly, the superior and inferior directions for thermal transport are just opposite of those for electrical transport. Hence, a heat manipulation model in WTe2 FET device was proposed. Within the designed configuration, waste heat in WTe2 would be mostly dissipated to metal contacts located along zigzag, relieving the local temperature discrepancy in the channel effectively and preventing degradation or breakdown. Our study provides new insight into thermal transport of anisotropic 2D materials, which might inspire energy-efficient nanodevices in the future.

Groundwater lowering is one of the most important countermeasures to avoid the risk of rainfall-triggered landslides. However, the long-term reliability of many drainage methods is often a matter of concern since the drains may easily get clogged. A new hydraulic-driven self-starting drainage method is presented in this paper. In the proposed Random Forest (RF) based robust design approach for the self-starting drains, the datasets are generated using an automatically controlled numerical modeling technology. The deterministic analysis is carried out based on uncertain soil parameters and the specific designs selected using Uniform Design (UD). The ensemble of RF models is applied in the design process to improve computing efficiency. Safety requirements, design robustness, and cost efficiency are simultaneously considered utilizing multi-objective optimization. A straightforward and efficient framework that focuses on difficulties caused by an enormous design space is established for the robust design of the self-starting drains, and improved computation efficiency is achieved. The effectiveness of the proposed approach is illustrated with a case study, the Qili landslide in Zhejiang Province, China.

In view of the axial force produced in the working process of double arc helical gear hydraulic pump, the theory of differential equation of curve and curved surface was utilized so that the calculation formula of axial force was obtained and the relationship between the axial force and structure parameters of gears was clarified. In order to balance the axial force, the pressure oil in the high pressure area was introduced into the end face of the plunger to press the plunger against the gear shaft, and the hydrostatic bearing whose type is plunger at the end of the shaft was designed. In order to verify the balance effect of axial force, the leakage owing to end clearance and volume efficiency of gear hydraulic pump before and after the balancing process was analyzed. This paper provides a new analysis idea and balance scheme for the axial force produced in the working process of the double arc helical gear hydraulic pump, which can reduce the leakage owing to end clearance caused by the axial force and improve the volume efficiency of the gear hydraulic pump.

Maxillofacial space infection (MSI) experience review is beneficial for its management. To identify potential risk factors predisposing to the exacerbation of MSI and a prolonged length of stay (LOS). We performed a comprehensive retrospective review of medical records of 222 MSI patients admitted in Center of Stomatology during 1993–2019. About 63.5% of 222 patients had an odontogenic infection, and submandibular space was the most involved space. Streptococcus spp. was the most common organism isolated (72.4%). Multiple-space cases had more systemic diseases, respiratory difficulty, and life-threatening complications and exhibited worse clinical characteristics (higher white-blood-cell-count, higher body temperature, and restricted mouth opening) than single-space cases (P

Drainage is a cost-effective way to stabilize slopes. However, clogging has always been a factor that decreases the sustainability and efficiency of the drainage method in slope stabilization. A new drainage method utilizing the hydraulic principle is presented in this paper. A deterministic method, which is performed by integrated software, for evaluating the factor of safety (FOS) under the action of a given self-starting drainage design is proposed correspondingly. A framework for the optimized design of self-starting drainage is established, and the following steps are mainly included: The optimal dip angles of the inclined boreholes are determined by a plotting method; the optimal lengths of the permeable section of the inclined boreholes are determined based on uniform design and support vector machine; the concept of Pareto front is introduced to determine the most preferred design in design space considering multiple objectives including safety, cost, and drain effectiveness. The entire process is illustrated with a case study, the Qili landslide in Zhejiang Province, China.

Electrocardiography is a useful diagnostic tool for various cardiovascular diseases, such as myocardial infarction (MI). An electrocardiograph (ECG) records the electrical activity of the heart, which can reflect any abnormal activity. MI recognition by visual examination of an ECG requires an expert’s interpretation and is difficult because of the short duration and small amplitude of the changes in ECG signals associated with MI. Therefore, we propose a new method for the automatic detection of MI using ECG signals. In this study, we used maximal overlap discrete wavelet transform to decompose the data, extracted the variance, inter-quartile range, Pearson correlation coefficient, Hoeffding’s D correlation coefficient and Shannon entropy of the wavelet coefficients and used the k-nearest neighbor model to detect MI. The accuracy, sensitivity and specificity of the model were 99.57%, 99.82% and 98.79%, respectively. Therefore, the system can be used in clinics to help diagnose MI.

Despite the large number of experimental works divulging the use of carbonaceous materials in LIB anodes, there are very few reports modeling the relationships between the characteristics of the electrode active materials and their lithium storage capacity. In this work, it is aimed to model the influence of the size and shape of carbon nano-spheres (carbon dots) on their lithium storage capacity. This study divides lithium storage of carbon nano-spheres into two segregate surface- and bulk-related mechanisms and calculates the capacity as the summation of these two components. Accordingly, a novel model employing a new factor called normalized volume, to accurately add the contribution of the surface lithium storage component to the bulk one, is introduced. The model also considers the size and morphology of the carbonaceous nano-particles simultaneously to estimate the specific capacity of the LIB anodes. The model revealed the fact that the decrease in the size of carbon nano-spheres below 20 nm dramatically results in the enhancement of the lithium storage capacity. The comparison of the estimated values with the experimental data of the literature confirmed the satisfactory consistency of the measured and predicted capacities. More importantly, this model is capable of being utilized as a fundamental tool to predict the specific lithium storage capacity of various carbon nano-structures considering their shape and dimension.

Single-image nonparametric blind super-resolution is a fundamental image restoration problem yet largely ignored in the past decades among the computational photography and computer vision communities. An interesting phenomenon is observed that learning-based single-image super-resolution (SR) has been experiencing a rapid development since the boom of the sparse representation in 2005s and especially the representation learning in 2010s, wherein the high-res image is generally blurred by a supposed bicubic or Gaussian blur kernel. However, the parametric assumption on the form of blur kernels does not hold in most practical applications because in real low-res imaging a high-res image can undergo complex blur processes, e.g., Gaussian-shaped kernels of varying sizes, ellipse-shaped kernels of varying orientations, curvilinear kernels of varying trajectories. The paper is mainly motivated by one of our previous works: Shao and Elad (in: Zhang (ed) ICIG 2015, Part III, Lecture notes in computer science, Springer, Cham, 2015). Specifically, we take one step further in this paper and present a type of adaptive heavy-tailed image priors, which result in a new regularized formulation for nonparametric blind super-resolution. The new image priors can be expressed and understood as a generalized integration of the normalized sparsity measure and relative total variation. Although it seems that the proposed priors are simple, the core merit of the priors is their practical capability for the challenging task of nonparametric blur kernel estimation for both super-resolution and deblurring. Harnessing the priors, a higher-quality intermediate high-res image becomes possible and therefore more accurate blur kernel estimation can be accomplished. A great many experiments are performed on both synthetic and real-world blurred low-res images, demonstrating the comparative or even superior performance of the proposed algorithm convincingly. Meanwhile, the proposed priors are demonstrated quite applicable to blind image deblurring which is a degenerated problem of nonparametric blind SR.

In this paper we use the fixed point index and nonnegative matrices to study the existence of positive solutions for a class of fractional difference systems with coupled boundary conditions.

In this paper, we present an active contour model for image segmentation based on a nonparametric distribution metric without any intensity a priori of the image. A novel nonparametric distance metric, which is called joint probability classification, is established to drive the active contour avoiding the instability induced by multimodal intensity distribution. Considering an image as a Riemannian manifold with spatial and intensity information, the contour evolution is performed on the image manifold by embedding geometric image feature into the active contour model. The experimental results on medical and texture images demonstrate the advantages of the proposed method.

The nonparametric blur-kernel estimation, using either single image or multi-observation, has been intensively studied since Fergus et al.'s influential work (ACM Trans Graph 25:787---794, 2006). However, in the current literature there is always a gap between the two highly relevant problems; that is, single- and multi-shot blind deconvolutions are modeled and solved independently, lacking a unified optimization perspective. In this paper, we attempt to bridge the gap between the two problems and propose a rigorous and unified minimization function for single/multi-shot blur-kernel estimation by coupling the maximum-a-posteriori (MAP) and variational Bayesian (VB) principles. The new function is depicted using a directed graphical model, where the sharp image and the inverse noise variance associated with each shot are treated as random variables, while each blur-kernel, in difference from existing VB methods, is just modeled as a deterministic parameter. Utilizing a universal, three-level hierarchical prior on the latent sharp image and a Gamma hyper-prior on each inverse noise variance, single/multi-shot blur-kernel estimation is uniformly formulated as an $${\varvec{\fancyscript{l}}}_{{0.5}}$$l0.5-norm-regularized negative log-marginal-likelihood minimization problem. By borrowing ideas of expectation-maximization, majorization-minimization, and mean field approximation, as well as iteratively reweighted least squares, all the unknowns of interest, including the sharp image, the blur-kernels, the inverse noise variances, as well as other relevant parameters are estimated automatically. Compared with most single/multi-shot blur-kernel estimation methods, the proposed approach is not only more flexible in processing multiple observations under distinct imaging scenarios due to its independence of the commutative property of convolution but also more adaptive in sparse image modeling while in the meanwhile with much less implementational heuristics. Finally, the proposed blur-kernel estimation method is naturally applied to two low-level vision problems, i.e., camera-shake deblurring and nonparametric blind super-resolution. Experiments on benchmark real-world motion blurred images, simulated multiple-blurred images, as well as both synthetic and realistic low-resolution blurred images are conducted, demonstrating the superiority of the proposed approach to state-of-the-art single/multi-shot camera-shake deblurring and nonparametric blind super-resolution methods.

This paper reports the effect of temperature on the bending properties and failure mechanism of 3D MWK (Multiaxial warp knitted) composites. Three-point bending experiments on composites with three fiber architectures were performed at four different temperatures. Then the effect of temperature on the load/deflection curves, bending strength and stiffness were analyzed. Macroscopic fracture morphology and SEM micrographs were also examined to understand the deformation and failure mechanism. The results show that the temperature has great impact on the bending properties of 3D MWK composites and the performance decreases significantly with the increase of the temperature. Meanwhile, the bending properties can be affected greatly by the fiber architecture and these decrease significantly with the increase of fiber orientation angle at room and elevated temperatures. Moreover, the damage and failure patterns of composites vary with the test temperature and fiber architecture. At room temperature, the composite exhibits brittle fracture feature and damages in the breakage and tearing of fibers. But at the higher temperature, the composite becomes more softened, cracked and plastic. It damages in fiber layer delaminating, matrix cracking and fiber/matrix interface debonding.

Elastic heat transfer tube bundles are widely used in the field of flow-induced vibration heat transfer enhancement. Two types of mainly used tube bundles, the planar elastic tube bundle and the conical spiral tube bundle were comprehensively compared in the condition of the same shell side diameter. The natural mode characteristics, the effect of fluid-structure interaction, the stress distribution, the comprehensive heat transfer performance and the secondary fluid flow of the two elastic tube bundles were all concluded and compared. The results show that the natural frequency and the critical velocity of vibration buckling of the planar elastic tube bundle are larger than those of the conical spiral tube bundle, while the stress distribution and the comprehensive heat transfer performance of the conical spiral tube bundle are relatively better.

At 8:02 am on April 20, 2013, an earthquake with a magnitude of seven on the Richter scale occurred in Lushan County, Sichuan Province, China. This paper describes the investigation of the damage to buildings in quake-hit areas. By comparison with “5.12” Wenchuan earthquake that occurred in the same region 5 years ago, the damage modes of the buildings have been analyzed. Public buildings, most of which were reconstructed after the Wenchuan earthquake, exhibited a good performance in regard to the main structures. However, severe damages were identified from non-structural elements. The performance of frame structures supported on rubber isolators was examined, and very few cracks from the infilled walls were observed, unlike the other frame structures. Rural housing suffered extensive damage during this earthquake, due to inadequate structural systems for horizontal-force resistance, lack of construction supervision, and insufficient ground treatment, all of which lead to the tragic destruction. Conclusions were given by presenting several suggestions to enhance the seismic behavior of rural housing.

It is well-known that shaken cameras or mobile phones during exposure usually lead to motion blurry photographs. Therefore, camera shake deblurring or motion deblurring is required and requested in many practical scenarios. The contribution of this paper is the proposal of a simple yet effective approach for motion blur kernel estimation, i.e., blind motion deblurring. Though there have been proposed several methods for motion blur kernel estimation in the literature, we impose a type of non-stationary Gaussian prior on the gradient fields of sharp images, in order to automatically detect and purse the salient edges of images as the important clues to blur kernel estimation. On one hand, the prior is able to promote sparsity inherited in the non-stationarity of the precision parameters (inverse of variances). On the other hand, since the prior is in a Gaussian form, there exists a great possibility of deducing a conceptually simple and computationally tractable inference scheme. Specifically, the well-known expectation---maximization algorithm is used to alternatingly estimate the motion blur kernels, the salient edges of images as well as the precision parameters in the image prior. In difference from many existing methods, no hyperpriors are imposed on any parameters in this paper; there are not any pre-processing steps involved in the proposed method, either, such as explicit suppression of random noise or prediction of salient edge structures. With estimated motion blur kernels, the deblurred images are finally generated using an off-the-shelf non-blind deconvolution method proposed by Krishnan and Fergus (Adv Neural Inf Process Syst 22:1033---1041, 2009). The rationality and effectiveness of our proposed method have been well demonstrated by the experimental results on both synthetic and realistic motion blurry images, showing state-of-the-art blind motion deblurring performance of the proposed approach in the term of quantitative metric as well as visual perception.

Conical spiral tube bundles are widely used in enhancing the heat transfer via the flow-induced vibration in heat exchangers. The shell side flow-induced vibration of the conical spiral tube bundle is experimentally investigated in this paper. The experiment table was built and the operational modes, the vibration parameters of the tube bundle were analyzed. The results show that, the operational mode frequencies of the conical spiral tube are decreased as the shell-side fluid flow velocity increases, especially for the first order frequency. Within the parameter range of this experiment, the real working frequency of the conical spiral tube is between the 1st and the 2nd operational modes, and the free end vibration amplitude of the tube bundle increases greatly when the shell side fluid flow velocity exceeds a critical value.

A modified least square finite difference (LSFD) method is proposed to solve the gas film lubrication equation in the head/disk interface in hard disk drives (HDDs). In the modified LSFD scheme, around a reference node there are 24 regular distribution supporting points, and a new scaling matrix is used to replace the one used in the general LSFD method. A least square technique is used to smooth the first-order derivative of flying height where discontinuities occur. Numerical examples show that the modified LSFD method can overcome divergence problem of the general LSFD method in complicated cases and has higher computational efficiency.

An adaptive grid generation technique including three kinds of weight functions related to the maximum pressure gradient is proposed to simulate the pressure distribution of a sub-5 nm flying height air bearing slider with clearance discontinuities in the interface of the head and the disk in hard disk drives. Considering the clearance discontinuities of a slider with complex geometrical shape, we have defined a discontinuous factor to describe the mass flux crossing the discontinuous boundaries. The effect of different parameters in the weight functions on the node distribution of a typical slider is investigated. The pressure profile of a slider with sub-5 nm flying height is obtained based on the grid distribution calculated from the weight functions. The computational efficiency for simulating the pressure distributions is compared for different kinds of weight functions.

We investigate the complexity of counting Eulerian tours ({\sc #ET}) and its variations from two perspectives---the complexity of exact counting and the complexity w.r.t. approximation-preserving reductions (AP-reductions \cite{MR2044886}). We prove that {\sc #ET} is #P-complete even for planar 4-regular graphs. A closely related problem is that of counting A-trails ({\sc #A-trails}) in graphs with rotational embedding schemes (so called maps). Kotzig \cite{MR0248043} showed that {\sc #A-trails} can be computed in polynomial time for 4-regular plane graphs (embedding in the plane is equivalent to giving a rotational embedding scheme). We show that for 4-regular maps the problem is #P-hard. Moreover, we show that from the approximation viewpoint {\sc #A-trails} in 4-regular maps captures the essence of {\sc #ET}, that is, we give an AP-reduction from {\sc #ET} in general graphs to {\sc #A-trails} in 4-regular maps. The reduction uses a fast mixing result for a card shuffling problem \cite{MR2023023}. In order to understand whether #{\sc A-trails} in 4-regular maps can AP-reduce to #{\sc ET} in 4-regular graphs, we investigate a problem in which transitions in vertices are weighted (this generalizes both #{\sc A-trails} and #{\sc ET}). In the 4-regular case we show that {\sc A-trails} can be used to simulate any vertex weights and provide evidence that {\sc ET} can simulate only a limited set of vertex weights.

Background: Lymphangiogenesis plays a significant role in metastasis and recurrence of gastric cancer. There is no report yet focusing on the modulation of VEGF pathway and lymphangiogenesis of gastric cancer by targeting Akt/mTOR pathway. This study aims to demonstrate the relationship between Akt/mTOR pathway and VEGF-C/-D in gastric cancer. Methods: We collected surgically resected gastric adenocarcinoma specimens from 55 consented patients. Immunohistochemistry staining of p-Akt, p-mTOR, VEGF-C, VEGF-D were performed and scored by two independent pathologists. The results were presented as staining intensity and positive staining cell rate. We also measured lymphatic vessel density (LVD) by D2-40 staining. Different dosages of p-Akt inhibitor LY294002 (12.5 μM, 25 μM, 50 μM) and p-mTOR inhibitor Rapamycin (25 nM, 50 nM, 100 nM) were given to gastric cancer cell line SGC-7901 in vitro. The inhibition rate of cell growth was tested by MTT at 24 h, 48 h and 72 h, respectively and protein expressions of Akt, p-Akt, mTOR, p-mTOR, VEGF-C and VEGF-D were examined by Western blot. Results: The positive staining rates of p-Akt, p-mTOR, VEGF-C and VEGF-D in 55 gastric cancer clinical specimens were 74.54%, 85.45%, 72.73% and 58.18%. p-Akt and p-mTOR were positively correlated with VEGF-C and VEGF-D (p < 0.01). The LVD increased with incremental tendency of staining intensity of p-Akt, p-mTOR, VEGF-C and VEGF-D. LY294002 or Rapamycin significantly suppressed SGC-7901 cell growth and the inhibition rate was dose and time dependent (p < 0.001). In addition, the protein expression of p-Akt and p-mTOR were positively correlated with that of VEGF-C and VEGF-D (p < 0.05). Conclusions: The level of LVD in gastric cancer specimens was significant higher than that of normal gastric tissue and was positively correlated with p-Akt, p-mTOR, VEGF-C and VEGF-D. Inhibition of p-Akt and p-mTOR, in vitro, decreased tumor cell VEGF-C and VEGF-D significantly. Therefore, we concluded that lymphangiogenesis of gastric cancer might be related to Akt/mTOR-VEGF-C/VEGF-D axis.

As early as in 1975, Shamos and Hoey first gave an O(n lg n)-time divide-and-conquer algorithm (SH algorithm in short) for the problem of finding the closest pair of points. In one process of combination, the Euclidean distances between 3n pairs of points need to be computed, so the overall complexity of computing distance is then 3n lg n. Since the computation of distance is more costly compared with other basic operation, how to improve SH algorithm from the aspect of complexity of computing distance is considered. In 1998, Zhou, Xiong and Zhu improved SH algorithm by reducing this complexity to 2n lg n. In this paper, we make further improvement. The overall complexity of computing distances is reduced to (3n lg n)/2, which is only half that of SH algorithm.

Shape memory polymers are at the forefront of recent materials research. Although the basic concept has been known for decades, recent advances in the research of shape memory polymers demand a unified approach to predict the shape memory performance under different thermo-temporal conditions. Here we report such an approach to predict the shape fixity and free recovery of thermo-rheologically simple shape memory polymers. The results show that the influence of programming conditions to free recovery can be unified by a reduced programming time that uniquely determines shape fixity, which consequently uniquely determines the shape recovery with a reduced recovery time. Furthermore, using the time-temperature superposition principle, shape recoveries under different thermo-temporal conditions can be extracted from the shape recovery under the reduced recovery time. Finally, a shape memory performance map is constructed based on a few simple standard polymer rheology tests to characterize the shape memory performance of the polymer.

This special issue of Algorithmica contains the journal version of selected papers from the ninth Latin American Theoretical Informatics Symposium (LATIN), which was held in the city of Oaxaca, Mexico in April 2010. LATIN was launched in 1992 to foster the interaction between the Latin-American theoretical computer science community and computer scientists around the world. The conference, which is international in scope, is now held every other year, and LATIN’10 was the ninth of a series, after Sao Paulo, Brazil (1992); Valparaiso, Chile (1995); Campinas, Brazil (1998); Punta del Este, Uruguay (2000); Cancun, Mexico (2002); Buenos Aires, Argentina (2004); Valdivia, Chile (2006); and Buzios, Brazil (2008). The conference proceedings were published by Springer in the Lecture Notes in Computer Science series, as they have been since inception. There were fifty-six papers presented in LATIN’10, and Volume 6034 of LNCS is devoted to them. A set of papers were selected from those presented in LATIN’10 and invited to submit an extended version for this issue. Each of these papers went through a careful selection and refereeing process. They provide a wide view of the different subfields of theoretical computer science within the scope of LATIN. We are grateful to the authors for their valuable contributions, as well as the reviewers for their effort and dedication. The papers in this issue are: • Pairs of Complementary Unary Languages with “Balanced” Nondeterministic Automata. Viliam Geffert, Giovanni Pighizzini. • The Complexity of Counting Eulerian Tours in 4-Regular Graphs. Qi Ge, Daniel Stefankovic. • Minimum-perimeter Intersecting Polygons. Adrian Dumitrescu, Minghui Jiang.