Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal Profiles of Axon Terminals, Synapses and Spines in the Ischemic Penumbra of the Cerebral Cortex: Ultrastructure of Neuronal Remodeling

Background and Purpose— Because the recovery process of axon terminals, synapses, and spine-dendrites in the ischemic penumbra of the cerebral cortex is obscure, we studied the temporal profile of these structures up to 12 weeks after the ischemic insult, using a gerbil model. Methods— Stroke-positive animals were selected according to their stroke index score during the first 10-minute left carotid occlusion done twice with 5-hour interval. The animals were euthanized at various times after the second ischemic insult. Ultra-thin sections including the 2nd to 4th cortical layers were obtained from the neocortex coronally sectioned at the infundibular level, in which the penumbra appeared. We counted the number of synapses, spines and multiple synapse boutons, measured neurite thickness, and determined the percent volume of the axon terminals and spines by Weibel point counting method. Results— The number of synapses, synaptic vesicles and spines and the total percent volume of the axon terminals and spines decreased until the 4th day. From 1 to 12 weeks after the ischemic insult, these values increased to or exceeded the control ones, and neuritic thickening and increase in number of multiple synapse boutons occurred. Conclusions— In the ischemic penumbra, the above structures degenerated, with a reduction in their number and size, until 4 days and then recovered from 1 to 12 weeks after the ischemic insult.
Energetic efficient synthesis of general mutual intensity distribution

The mutual intensity distribution of a light beam may contain available information. The task of encoding a given mutual intensity distribution is addressed in this paper. Various approaches for encoding the mutual intensity function have been previously proposed. However, all of them provide low energetic efficiency and commonly require sophisticated production methods. The idea of using a phase-only filter for performing this synthesis is hereby investigated. The proposed method is numerically examined for the case of placing the mutual intensity generating filter in the fractional Fourier domain.
Analytical modeling of a Minimally Invasive Surgery grasper actuated by shape memory alloy wires

Minimally Invasive Surgery (MIS) is getting common these days. MIS robots using special tools can perform surgery precisely as humans. This is only possible with dexterous end-effectors and a well-controlled system. Local, lightweight and powerful actuators positioned at end-effectors provide the ability to decrease the degrees of freedom and simplify the design. This paper discusses a grasper design actuated by Shape Memory Alloy (SMA) wires that can be used in MIS robotics. The properties of a commercially available shape memory alloy are explored and analytical formulations for the actuation procedure are developed. The grasper actuated by SMA wires is studied and the procedure of grasping is discussed. It is shown that this grasper can perform well in robotic surgery.
Towards a General Framework for Modeling, Simulating and Building Sensor/Actuator Systems and Robots for the Web of Things

The Web of Things (WoT) refers to those parts of the web consisting of special web application systems connected to the real world via sensors or actuators. These WoT systems include robots connected to the web as a special case. We propose a general framework for modeling, simulating, designing and building WoT systems. We propose a core ontology for WoT systems, which is the basis for our modeling and simulation approach. The modeling and simulation part of our framework is independent of the WoT and could also be employed in the engineering of other forms of embedded systems and robots. As a test case and a proof of concept we present an example of a green house WoT system.
The UCube: a child-friendly device for introductory three-dimensional design

Currently there is a burgeoning interest in three-dimensional construction and design: 3D printing and fabrication devices have--with almost shocking swiftness--become available to students and home hobbyists, allowing a vastly expanded audience to imagine, and then print out, their own tangible designs. Still, while the fabrication devices themselves are becoming available to younger children, the task of 3D design itself remains difficult for youngsters. The difficulty lies in the "2D screen bottleneck": three-dimensional objects for printing must generally be designed in complex software that works exclusively with, and through, a flat two-dimensional screen. This paper introduces the UCube, a spatial input device designed specifically with children and "3D novices" in mind. The basic idea behind the UCube is that it provides a spatial, volumetric array of light switches that can be turned on and off individually by the user; the pattern of lights is then input to a desktop computer, where it can be employed to specify a collection of 3D points in space. The result is that 3D design--at least for simple shapes--becomes a matter of moving one's hands in space to (e.g.) select the boundary points of the desired shape. We describe the design of the UCube, the influences behind it, and some early encouraging pilot tests of the device with middle-school-age children.
A simple hand posture recognition for e ffi cient single handed pointing and selection

In the description of object shapes, humans usually perform iconic gestures that coincide with speech (are coverbal). Marked by a similarity between the gestural sign and the described object, iconic gestures may easily depict content difficult to describe using words alone. Though the expressive potential of iconic gestures in human-computer communication is generally acknowledged, the development of application systems that take non-verbal modalities of natural communication into account has in most cases focused much more on pointing and symbolic gestures. In this paper, we describe how Imagistic Description Tree representations can be used in an application system for generating virtual objects with particular spatial features by way of verbal descriptions and iconic gestures. 1 Defining Shape through Iconic Gestures Based on a comprehensive corpus of speech-gesture shape descriptions acquired from an empirical study [4], the Imagistic Tree (IDT) was proposed as a representation for the semantics of multimodal shape-related expressions, to the end of algorithmically interpretive operational shape descriptions from gesture and speech input modalities. It extends an earlier approach [3], which models the two factors of extent and (partly) profile information in gestures, but which has not included structured spatial organization of gesture and accompanying speech reflecting this factor. The IDT models object extent, profile, and structure, as the salient semantic elements contained in gesture and speech. The basic level of IDT reprepresentations are object schemata, in which each object is described by a collection of up to three axes which represent the objects extents in one, two, or three spatial dimensions. Using different combinations of axes in an object schema, several basic objects can be represented, such as cubes, cylinders, etc. Structural aspects of an object are represented in an imagistic description which can recursively embed further imagistic descriptions for object parts, to result in a tree-like structure similar to the hierarchical structure used in the Marr and Nishihara [1] model. The complete tree describing an object including
Reaction times as an index of visual conspicuity when driving at night

Abstract Conspicuity refers to the visibility of objects that are either close to threshold or viewed in a cluttered environment. Conventional, threshold‐based tests of vision are unlikely to be related to target visibility, because visual systems behave differently under supra‐threshold and close‐to‐threshold conditions, or when low luminance levels are used. In these experiments, Reaction Times (RTs) are tested under a wide range of contrasts, luminances and spatial frequencies commonly encountered in the real world. We show that RTs are closely related to sensitivity and can therefore provide a method of measuring supra‐threshold visual performance. The data are interpreted in terms of visual performance when driving, where a reduction in target visibility leads to increases in processing time.
Hyperspectral Images Terrain Classification in Combination Spectrum DLDA Subspace

Hyperspectral images face the problem of high dimensionality and lowsamples number, which results in unsatisfied recognition efficiency, thus dimensionalityreduction is needed before terrain classification. A novel hyperspectral imagesfeature extraction method is presented for dimensionality reduction. Firstly,take discrete Fourier transformation (DFT) of each pixel spectral curve, andcombine the amplitude spectrum and corresponding phase spectrum; then directlinear discriminant analysis (DLDA) is performed in the combination spectrumspace to extract features. Minimum distance classifier is used to evaluate thefeature extraction performance in the achievedcombination spectrum DLDA subspace. The experimental results for airbornevisible/infrared imaging spectrometer (AVIRIS) hyperspectral image show that,comparing with the spectral DLDA subspace method, the present method canimprove the terrain classification efficiency.
Cellular Immune Reactions of the Sunn Pest, Eurygaster integriceps, to the Entomopathogenic Fungus, Beauveria bassiana and Its Secondary Metabolites

Abstract In this study, five morphological types of circulating hemocytes were recognized in the hemolymph of the adult sunn pest, Eurygaster integriceps Puton (Hemiptera: Scutelleridae), namely prohemocytes, plasmatocytes, granulocytes, adipohemocytes, and oenocytoids. The effects of the secondary metabolites of the entomopathogenic fungus Beauveria bassiana on cellular immune defenses of Eurygaster integriceps were investigated. The results showed that the fungal secondary metabolites inhibited phagocytic activity of E. integriceps hemocytes and hampered nodule formation. A reduction of phenoloxidase activity was also observed. The data suggest that B. bassiana produce secondary metabolites that disable several immune mechanisms allowing the fungus to overcome and then kill its host. This characteristic makes B. bassiana a promising model for biological control of insect pests such as E. integriceps.
Hierarchical Encoded Path Views for Path Query Processing: An Optimal Model and Its Performance Evaluation

Efficient path computation is essential for applications such as intelligent transportation systems (ITS) and network routing. In ITS navigation systems, many path requests can be submitted over the same, typically huge, transportation network within a small time window. While path precomputation (path view) would provide an efficient path query response, it raises three problems which must be addressed: 1) precomputed paths exceed the current computer main memory capacity for large networks; 2) disk-based solutions are too inefficient to meet the stringent requirements of these target applications; and 3) path views become too costly to update for large graphs (resulting in out-of-date query results). We propose a hierarchical encoded path view (HEPV) model that addresses all three problems. By hierarchically encoding partial paths, HEPV reduces the view encoding time, updating time and storage requirements beyond previously known path precomputation techniques, while significantly minimizing path retrieval time. We prove that paths retrieved over HEPV are optimal. We present complete solutions for all phases of the HEPV approach, including graph partitioning, hierarchy generation, path view encoding and updating, and path retrieval. In this paper, we also present an in-depth experimental evaluation of HEPV based on both synthetic and real GIS networks. Our results confirm that HEPV offers advantages over alternative path finding approaches in terms of performance and space efficiency.
Challenges in projecting clustering results across gene expression-profiling datasets.

BACKGROUND Gene expression microarray studies for several types of cancer have been reported to identify previously unknown subtypes of tumors. For breast cancer, a molecular classification consisting of five subtypes based on gene expression microarray data has been proposed. These subtypes have been reported to exist across several breast cancer microarray studies, and they have demonstrated some association with clinical outcome. A classification rule based on the method of centroids has been proposed for identifying the subtypes in new collections of breast cancer samples; the method is based on the similarity of the new profiles to the mean expression profile of the previously identified subtypes. METHODS Previously identified centroids of five breast cancer subtypes were used to assign 99 breast cancer samples, including a subset of 65 estrogen receptor-positive (ER+) samples, to five breast cancer subtypes based on microarray data for the samples. The effect of mean centering the genes (i.e., transforming the expression of each gene so that its mean expression is equal to 0) on subtype assignment by method of centroids was assessed. Further studies of the effect of mean centering and of class prevalence in the test set on the accuracy of method of centroids classifications of ER status were carried out using training and test sets for which ER status had been independently determined by ligand-binding assay and for which the proportion of ER+ and ER- samples were systematically varied. RESULTS When all 99 samples were considered, mean centering before application of the method of centroids appeared to be helpful for correctly assigning samples to subtypes, as evidenced by the expression of genes that had previously been used as markers to identify the subtypes. However, when only the 65 ER+ samples were considered for classification, many samples appeared to be misclassified, as evidenced by an unexpected distribution of ER+ samples among the resultant subtypes. When genes were mean centered before classification of samples for ER status, the accuracy of the ER subgroup assignments was highly dependent on the proportion of ER+ samples in the test set; this effect of subtype prevalence was not seen when gene expression data were not mean centered. CONCLUSIONS Simple corrections such as mean centering of genes aimed at microarray platform or batch effect correction can have undesirable consequences because patient population effects can easily be confused with these assay-related effects. Careful thought should be given to the comparability of the patient populations before attempting to force data comparability for purposes of assigning subtypes to independent subjects.
Rate-distortion optimized multipass video encoding with application to MPEG-4

In this paper we propose a rate-distortion optimized multipass algorithm for video encoding. The problem of dependent quantization in a hybrid coding framework is addressed by constructing a trellis from the exponentially growing search tree which is then searched using a Lagrangian cost function. To avoid exponential growth, states with similarly distorted reference frames are merged based on the assumption that similar rate-distortion behavior results for future frames. The goal is to select an optimal quantizer for each frame such that the overall R-D performance is optimized. The algorithm is applied to MPEG-4 SP and typical average PSNR gains of 0.3 dB are achieved. A comparison with the DivX 5.2 codec shows PSNR gains of up to 2 dB.
Distributed Image compression in wireless sensor networks using intelligent methods

The availability of low cost hardware like microphone and CMOS cameras has led to spread in multimedia wireless sensor network. Data transfer is considered one of the high cost tasks in wireless sensor network consuming more than 80 percent of dedicated energy. The most appropriate way to reduce energy consumption is to use an appropriate compression image technique. Designing a compression method requires balance and careful estimation among compression ratio factors, quality, complexity, and time. The present article presents a new method, unlike previous ones, focusing only on the structure of the network. In addition, it tries to deal with low compression rate along with high quality of recovered images and reduction in energy consumption. Hence, the method used here is Distributed Vector Quantization (DVQ) whose codebook, being real-time and dynamic, was created by applying neural network of adaptive resonance theory. The results from tests on primary images demonstrate the accuracy and efficacy of proposed method.
A Block Cipher Circuit Design against Power Analysis

In this paper, we will present a block cipher circuit design against Power Analysis. This design consists of usual masking and hiding method. For XOR, permutation and other linear layer, masking method of protection is used, but for S-box and other non-linear layer, hiding method is used in the reason that masking requires a lot of hardware consumption. We accomplished hardware implementation and Power Analysis in our research, whose test results proved that the design had strong capacity against Power Analysis. 200, 000 curves were extracted in our attack simulation, and the key successfully resisted complete recovery.
An optimized scheduling algorithm on a cloud workflow using a discrete particle swarm

Abstract In order to solve the problems of security threats on workflow scheduling in cloud computing environments, the security of tasks and virtual machine resources are quantified using a cloud model, and the users’ satisfaction degree with the security of tasks assigned to the virtual resources is measured through the similarity of the security cloud. On this basis, combined with security, completion time and cost constraints, an optimized cloud workflow scheduling algorithm is proposed using a discrete particle swarm. The particle in the particle swarm indicates a different cloud workflow scheduling scheme. The particle changes its velocity and position using the evolution equation of the standard particle swarm algorithm, which ensures that it is a feasible solution through the feasible solution adjustment strategies. The simulation experiment results show that the algorithm has better comprehensive performance with respect to the security utility, completion time, cost and load balance compared to other similar algorithms.
A new mortar formulation for modeling elastically bedded structures in vibro-acoustics in 3D

Background: It is a well-known fact that cross-laminated timber structures are prone to rumbling noises. These transmissions are best captured by a fully resolved three-dimensional model. As it is algorithmically highly complex to discretize such models with hexahedral elements in a conforming manner, we chose the mortar method to reduce the algorithmic complexity for the mesh generation. We also utilize high-order finite elements in order to cope with the high aspect ratios in three-dimensionally resolved, cross-laminated walls and slabs. The geometric models and necessary material information was derived from a building information model.
Combination of turbo equalization and turbo TCM for mobile communication system

A novel low-complexity scheme of turbo trellis-coded modulation (TCM) iterative equalization and decoding is presented, which serially concatenates a soft-input-soft-output (SISO) equalizer and symbol-by-symbol turbo TCM (TTCM) decoder through an iterative process in order to realize iterative equalization and decoding process. This scheme can not only improve the bandwidth efficiency, but also reduce the intersymbol interference (ISI). The equalizer with maximum a posteriori (MAP) is replaced with linear one based on minimum mean-square error (MMSE) at the receiver so that the complexity of the system can be reduced greatly. Computer simulation results show that the novel low-complexity receiver on fading channel can achieve comparable performance with TTCM on Gaussian channel with coding.
genius bodybuilder a tool to create avatars by genetic modelling

GENIUS Bodybuilder is a tool for the evolutionary design of arbitrary closed surfaces that integrates seamlessly into the 3D-modelling process. In contrast to prevailing evolutionary tools it is not built on a proprietary object representation, but makes use of a deformative approach that can be applied to commonly used surface representations such as polygon meshes or NURBS faces. The current implementation – GENIUS Sculptor – is used to create individual avatars out of prototypes by shape blending and free form deformation. The next step – Genius Creator – will be concerned with the creation of arbitrary forms using embryology, L-Systems and Cellular Automata.
Clinico-anesthetic changes following administration of propofol alone and in combination of meperidine and pentazocine lactate in dogs

Aim: The aim of this study is to find out the effect of propofol and its combination with meperidine and pentazocine lactate on certain clinico-anesthetic profiles in dogs. Materials and Methods: 15 apparently healthy mongrel dogs of either sex of about 1 year of age were randomly divided into three groups of five dogs each. The animals of Group I were administered propofol intravenously alone “to effect,” whereas meperidine at 2 mg/kgb.wt. and pentazocine lactate at 2 mg/kg b.wt. were injected intramuscularly 15 min before propofol “to effect” in Groups II and III, respectively. Atropine sulfate at 0.04 mg/kgb.wt. was injected intramuscularly 20 min before each treatment. Rectal temperature, heart rate, respiration rate, and anesthetic indices were recorded before and at 5, 10, 20, 30, and 60 min of induction. Results: As compared to Group I, the animals of Groups II and III exhibited a significant decrease (p<0.05) in the level of rectal temperature, respiration rate, and heart rate. Duration of recumbency, time of standing, time of recovery as well as the duration of analgesia were longer in pentazocine lactate (Group III) followed by meperidine (Group II) as compared to propofol alone (Group I). Meperidine treated dogs showed defecation and muscle twitching during anesthesia. Conclusion: Meperidine and pentazocine are suitable opioids used in combination with propofol for achieving surgical anesthesia and helpful in reduction of propofol dose.