Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-Based Testing for Embedded Systems

What the experts have to say about Model-Based Testing for Embedded Systems: "This book is exactly what is needed at the exact right time in this fast-growing area. From its beginnings over 10 years ago of deriving tests from UML statecharts, model-based testing has matured into a topic with both breadth and depth. Testing embedded systems is a natural application of MBT, and this book hits the nail exactly on the head. Numerous topics are presented clearly, thoroughly, and concisely in this cutting-edge book. The authors are world-class leading experts in this area and teach us well-used and validated techniques, along with new ideas for solving hard problems. "It is rare that a book can take recent research advances and present them in a form ready for practical use, but this book accomplishes that and more. I am anxious to recommend this in my consulting and to teach a new class to my students. " Dr. Jeff Offutt, professor of software engineering, George Mason University, Fairfax, Virginia, USA "This handbook is the best resource I am aware of on the automated testing of embedded systems. It is thorough, comprehensive, and authoritative. It covers all important technical and scientific aspects but also provides highly interesting insights into the state of practice of model-based testing for embedded systems. " Dr. Lionel C. Briand, IEEE Fellow, Simula Research Laboratory, Lysaker, Norway, and professor at the University of Oslo, Norway "As model-based testing is entering the mainstream, such a comprehensive and intelligible book is a must-read for anyone looking for more information about improved testing methods for embedded systems. Illustrated with numerous aspects of these techniques from many contributors, it gives a clear picture of what the state of the art is today. " Dr. Bruno Legeard, CTO of Smartesting, professor of Software Engineering at the University of Franche-Comt, Besanon, France, and co-author of Practical Model-Based Testing
Effects of Spirulina platensis on Growth Performance, Carcass Characteristics, Egg Traits and Immunity Response of Japanese Quails

In present study, two trials had been conducted to evaluate the effects of Spirulina platensis (SP) on growth performance, carcass characteristics, egg quantity and quality traits, and immunity response of Japanese quails. In trial 1, a total number of 180 one-day-old Japanese quails were randomly assigned into 6 groups, 3 replicates with 10 quail chicks per replicate. Experimental diets including basal diet (with no additive), diet contained probiotic, and diets contained 4 levels of SP (2.5, 5, 10, 20 g/kg diet). In trial 2, a total number of 250 Japanese laying quails were randomly assigned into 5 groups, 5 replicates with 10 laying quails per replicate. Experimental diets included of basal diet (no additive) and diets supplemented with three levels of SP (1, 3 or 5 g/kg diet). In experiment 1, using 5 g SP/kg diet caused higher body weight gain and European production efficiency factor during 1-35 d of age (P<0.05). Using SP at the levels of 2.5 or 5 g/kg diet increased breast percentage (P<0.05). In experiment 2, using different levels of SP decreased shell thickness, albumen height, haugh unit and yolk height in laying quails (P<0.05). However, Feeding different levels of SP increased (P< 0.05) egg yolk color compared to control group linearly. Dietary supplementation of SP at levels of 3 and 5 g/kg diet decreased cholesterol level per g yolk (P<0.05). Different levels of SP caused higher levels of total antibody against sheep red blood cells (SRBC) and IgG titers (P<0.05). Laying quails fed with 3 or 5 g SP/kg showed higher cutaneous basophil hypersensitivity after 12 or 24 h of phytohemagglutinin injection (P<0.05). In conclusion, we recommend using SP at the levels of 5 and 3 g/kg diet during growth and laying period of Japanese quails, respectively.
A neural algorithm for a fundamental computing problem

Fly brain inspires computing algorithm Flies use an algorithmic neuronal strategy to sense and categorize odors. Dasgupta et al. applied insights from the fly system to come up with a solution to a computer science problem. On the basis of the algorithm that flies use to tag an odor and categorize similar ones, the authors generated a new solution to the nearest-neighbor search problem that underlies tasks such as searching for similar images on the web. Science, this issue p. 793 Smell circuitry in the fly brain reveals a superior strategy for a common computer science task. Similarity search—for example, identifying similar images in a database or similar documents on the web—is a fundamental computing problem faced by large-scale information retrieval systems. We discovered that the fruit fly olfactory circuit solves this problem with a variant of a computer science algorithm (called locality-sensitive hashing). The fly circuit assigns similar neural activity patterns to similar odors, so that behaviors learned from one odor can be applied when a similar odor is experienced. The fly algorithm, however, uses three computational strategies that depart from traditional approaches. These strategies can be translated to improve the performance of computational similarity searches. This perspective helps illuminate the logic supporting an important sensory function and provides a conceptually new algorithm for solving a fundamental computational problem.
Cardiac contraction velocity has evolved to match heart rate with body size through variation in β-cardiac myosin sequence

Heart rate and the maximum velocity of contraction of striated muscle are inversely related to species size. As mammals evolve to different sizes, adaptations are required such as slower contracting heart and skeletal muscles. Analysis of the motor domain of β-myosin from 67 mammals from two clades identifies 14 sites, out of 800, strongly associated with body mass (p<0.01) but not with the clade (p>0.05). Nine of these sites were mutated in the human β-myosin to make it resemble the rat sequence. Biochemical analysis revealed that the rat-human β-myosin chimera functioned like the native rat myosin with a two fold increase in both motility and in the rate of ADP release from the actin.myosin cross-bridge (the step that limits contraction velocity). Both clades use the same small set of amino acids to adjust contraction velocity, suggesting a limited number of ways in which velocity can be manipulated.
Program and interface slicing for reverse engineering

A case is presented for the use of conventional and interface slicing as enabling mechanisms for numerous reverse engineering and reengineering tasks. The authors first discuss the applicability of conventional slicing to algorithm extraction and design recovery at statement-level granularity. They then present interface slicing and show how it provides similar capabilities at module-level granularity. Module is a general term for a collection of subprograms, possibly with information hiding mechanisms: It includes but is not limited to Ada packages. Component refers to a module in a reuse repository. A component is thus a code asset of a repository, possibly also incorporated into a program. Ada is used for the example, as Ada's features facilitate the types of transformations which are invoked. <<ETX>>
Band-notched UWB Printed Log-Periodic Dipole Antenna Fed by Half Mode Substrate Integrated Waveguide

Ultra-wideband (UWB) systems approved by U.S. Federal Communications Commission (FCC) [1] utilize spectrum resource ranging from 3.1 to 10.6 GHz, a valuable bandwidth for highspeed indoor data-communication application. As a key component of UWB systems, UWB antenna has drawn more and more attention worldwide to be designed for the purpose of transmitting very short and low power pulses. However, interferences from other narrowband communication systems will be inevitably introduced into UWB systems. For instance, Wireless Local Area Network (WLAN), operated at the bands of 2400-2484MHz, 5150-5350MHz, 57255825MHz, will cause interferences in UWB frequency band. Therefore, it is necessary to design antennas with band notched function in specified frequency bands. Recently, various band-notched antennas have been proposed for UWB communication systems [2]-[4]. Directional antenna can gain a great concentration of radiated power in a specified direction and is necessary for UWB application, but only a few researches have focused on such category of antennas. Printed log-periodic dipole antenna (PLPDA) [5][6] has sparked a great deal of research interest and is becoming an attractive candidate in this area, due to its elegant merits, such as low profile, light weight, low cost, and easy integration. However, the feeding system of PLPDA needs to be further developed. It is too complex and costly to use stripline as feeding system on the grounds that stripline is of a two layer structure [7], while using coaxial cable will result in strict requirements on structure in high frequency band [6]. In present study, a band-notched UWB printed log-periodic dipole antenna fed by half mode substrate integrated waveguide (HMSIW) is proposed. The natural balance structure of HMSIW [8]-[10] makes it suitable for the feeding system of PLPDA. Moreover, this property is independent of frequency in a wide bandwidth. HMSIW inherently cannot support the TE(2m)n modes and TM modes, and it will gain a broad dominant mode bandwidth. This antenna was fabricated with a standard printed circuit board (PCB) process. The measured results of the proposed antenna are consistent with simulated results, obtained by using Ansoft High Frequency Structure Simulator (HFSS) 11.0.
Enhanced DC estimation via sequence-specific frequency offset

A method for improving DC estimation over any particular training sequence is presented for use in direct conversion receivers. It is known that direct-conversion receivers suffer from a large DC-offset, which often cannot be adequately removed by a simple average of the received signal. To alleviate this problem, the DC offset can be jointly estimated with the channel over the training sequence in baseband. However, training sequences designed to facilitate channel estimation are not necessarily good for the estimation of DC offset. In the proposed method, an intentional frequency offset tailored to each training sequence is imposed at the radio front-end in order to improve the ability of estimating DC over that training sequence in digital baseband. We analyze the resulting DC estimation error and show analytically how the optimal frequency offset can be derived for each training sequence. Using the EDGE air interface, we demonstrate that significant gains can be achieved with this new method.
Ultraviolet radiation exposure and melanoma: evidence for gene-environment interaction in a large prospective cohort

Melanoma develops as the result of complex interactions between sun exposure and genetic factors. Data on the relationship between sunlight and melanoma from prospective studies are scant, and the combination of ultraviolet exposure data collected before melanoma diagnosis and genetic information is rarer still. We aimed to quantify the association between ambient and personal UV exposure in relation to risk of incident melanoma (invasive; invasive+in situ) in a large population-based prospective study of men and women (n=38,833) residing in a high ambient UV setting, and to examine potential gene-environment interactions. During a median follow-up time of 4.4 years, 782 (1.5%) participants developed cutaneous melanoma (316 invasive, 466 in situ). Country of birth, age at migration and sunburns during all periods of life were significantly associated with melanoma risk. Histories of keratinocyte cancer and of other actinic lesions were both strongly associated with melanoma risk. An interaction with polygenic risk is possible; among people at low risk, markers of cumulative sun exposure were associated with melanoma. In contrast, among people at high polygenic risk, markers of high-level early life ambient exposure were associated with melanoma. Polygenic risk scores can assist in identifying individuals for whom sunlight exposure is most relevant.
Multiresolution terrain modeling based on triangulated irregular networks

Multiresolution modeling provides an abstraction for representing, manipulating, and visualizing large volumes of spatial dafa at multiple levels of detail and accuracy. In geographic information systems (GIS), a coarse representation can be used to describe less relevant areas of a terrain, while high resolution can be focused on specific parts of interest. This work presents a method for constructing a sequence of triangular meshes in the context of terrain modeling, where meshes are created through a set of simplification and refinement operations, while preserving relevant terrain features. The method has been tested on several terrain data sets.
Repurposing protein degradation for optogenetic modulation of protein activities

Non-neuronal optogenetic approaches empower precise regulation of protein dynamics in live cells but often require target-specific protein engineering. To address this challenge, we developed a generalizable light modulated protein stabilization system (GLIMPSe) to control intracellular protein level independent of its functionality. We applied GLIMPSe to control two distinct classes of proteins: mitogen-activated protein kinase phosphatase 3 (MKP3), a negative regulator of the extracellular signal-regulated kinase (ERK) pathway, as well as a constitutively active form of MEK (CA MEK), a positive regulator of the same pathway. Kinetics study showed that light-induced protein stabilization could be achieved within 1 minute of blue light stimulation. GLIMPSe enables target-independent optogenetic control of protein activities and therefore minimizes the systematic variation embedded within different photoactivatable proteins. Overall, GLIMPSe promises to achieve light-mediated post-translational stabilization of a wide array of target proteins in live cells.
Haptics Aided Kinematic Assembly Modeling and Efficient Determination of Joint Ranges of Motion

This paper presents the development of a tool for the assembly and kinematic modeling of the tessellated objects. The tool addresses the issue of reducing the effort required to generate the kinematic models. The tool is capable of automatically ascertaining the type of kinematic pairing between two part models represented in STL format by detecting the compatible combination of features and determining the joint range of motion (ROM). The haptic interface is used to realistically simulate the assembly process and to determine the range of motion in 3D. The feature extraction algorithm uses a mix of curvature and surface normal based segmentation of the tessellated surfaces. The computation necessary for the geometry extraction and joint recognition has been decoupled from the complexity of the models by “Region of Interest” identification. A novel method for the determination of the ROM is proposed, wherein the recognized joint type information is used to restrict the computation necessary to the physically allowed degrees of freedom (DOF), unlike in the methods like configuration space, where, the computation needs to be done in 6-DOF space. Also, an efficient haptic rendering scheme for the simulation of the ROM has been proposed, which eliminates the need for the computationally intensive collision detection between the two parts.
Pyramidal contextual classification of SAR images

Pyramid-based classification techniques have shown great performance when compared to global classification methods. However, the accuracy becomes very low when spectral parameters only are considered. A new classification method is proposed which deals with integration of two algorithms: the hierarchical image segmentation by step-wise optimization to take into account the spatial context, and the Iterative Conditional Mode algorithm to classify the segmented image. After a comprehensive description of the new algorithm, its performance is analysed with SAR agricultural data.
Cooperative Robot Structures Modeled After Whale Behavior and Social Structure

This paper analyses the communications and social structure of whale pods and tries to apply their principles on cooperative robot structures which can be guided to perform a certain task. The communication patterns and social structure are presented at first in order to define real, natural phenomena which can then be translated through cooperative robotic structures. Whale communication has suffered modifications in the latter years mostly because of the increase of noise in the ocean. Problems regarding communications between the cooperative structures chosen for modelling whale behavior are solved by data fusion techniques. In the last part of the paper the problem of dynamic compensation of disturbances is studied with regard to cooperative structures.
Adaptive compensation for imbalance and offset losses in direct conversion transceivers

It is pointed out that analog implementations of quadrature modulators and demodulators have deficiencies-primarily amplitude and phase imbalances and DC offset-that result in several troublesome problems for digital transceivers. An analysis and quantitative assessment of the losses due to analog implementations are presented. They include spurious tones and intermodulation products at the transmitter and a degraded BER (bit error rate) due to distortion of the signal constellation. The asymptotic degradation in BER performance in 16 QAM (quadrature amplitude modulation) for example is shown to be 1.1 dB for a 5 degrees phase imbalance and 0.65 dB for 5% gain imbalance. An adaptive procedure at the receiver for minimization of the imbalance and offset errors is developed. It is demonstrated that the LMS (least mean square) algorithm can be used to adapt the compensator in a manner similar to an equalizer, and that the computational load is the same as that of a three-tap equalizer. <<ETX>>
Identification of Key Genes and Pathways in First Acute Myocardial Infarction Based on Gene Expression Profiling by Bioinformatics Analysis

Patients with acute myocardial infarction (AMI) have high morbidity and mortality. This study explored the molecular mechanisms of first acute myocardial infarction (FAMI) with integrated bioinformatic analyses of the feature genes and the correlative gene functions. The expression profile of GSE24519 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between FAMI and normal specimens were identified. Gene ontology (GO) enrichment analysis on gene functions and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed by using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Cytoscape was used to visualize the protein-protein interaction (PPI) of these DEGs. GO analysis revealed that the “transcription”, “DNA binding” and “cilium” were the enriched GO terms belonging to BP, MF and CC, respectively. The KEGG pathway analysis showed that the aberrant expression of long-term potentiation, amphetamine addiction and calcium signaling pathway were closely associated with FAMI occurrence. Importantly, JUN, PRKACB, GNB4, MTOR, HDAC2, PPP3CB, PPP3R1 and, FGFR3 were predicted to be significantly related to FAMI. Our discovery provides a registry of genes and pathways that are disrupted in FAMI, which has the potential to be used in the clinic for diagnosis and targeted therapy of FAMI in future.
Oct4-mediated inhibition of Lsd1 activity promotes the active and primed state of pluripotency enhancers

An aberrant increase in pluripotency gene (PpG) expression due to enhancer reactivation could induce stemness and enhance tumorigenicity of cancer stem cells. Silencing of PpG enhancers (PpGe) during embryonic stem cell differentiation involves Lsd1–mediated H3K4me1 demethylation and DNA methylation. Here, we observed retention of H3K4me1 and DNA hypomethylation at PpGe associated with a partial repression of PpGs in F9 embryonal carcinoma cells (ECCs) post-differentiation. H3K4me1 demethylation in F9 ECCs could not be rescued by Lsd1 overexpression. Given our observation that H3K4me1 demethylation is accompanied by strong Oct4 repression in P19 ECCs, we tested if Oct4 interaction with Lsd1 affects its catalytic activity. Our data show a dose-dependent inhibition of Lsd1 activity by Oct4 and retention of H3K4me1 at PpGe in Oct4 overexpressing P19 ECCs. These data suggest that Lsd1-Oct4 interaction in cancer stem cells could establish a primed enhancer state that is susceptible to reactivation leading to aberrant PpG expression.
Statistics of Epidemics in Networks by Passing Messages

Epidemic processes are common out-of-equilibrium phenomena of broad interdisciplinary interest. In this thesis, we show how message-passing approach can be a helpful tool for simulating epidemic models in disordered medium like networks, and in particular for estimating the probability that a given node will become infectious at a particular time. The sort of dynamics we consider are stochastic, where randomness can arise from the stochastic events or from the randomness of network structures. As in belief propagation, variables or messages in message-passing approach are defined on the directed edges of a network. However, unlike belief propagation, where the posterior distributions are updated according to Bayes’ rule, in messagepassing approach we write di↵erential equations for the messages over time. It takes correlations between neighboring nodes into account while preventing causal signals from backtracking to their immediate source, and thus avoids “echo chamber effects” where a pair of adjacent nodes each amplify the probability that the other is infectious. v In our first results, we develop a message-passing approach to threshold models of behavior popular in sociology. These are models, first proposed by Granovetter, where individuals have to hear about a trend or behavior from some number of neighbors before adopting it themselves. In thermodynamic limit of large random networks, we provide an exact analytic scheme while calculating the time dependence of the probabilities and thus learning about the whole dynamics of bootstrap percolation, which is a simple model known in statistical physics for exhibiting discontinuous phase transition. As an application, we apply a similar model to financial networks, studying when bankruptcies spread due to the sudden devaluation of shared assets in overlapping portfolios. We predict that although diversification may be good for individual institutions, it can create dangerous systemic e↵ects, and as a result financial contagion gets worse with too much diversification. We also predict that financial system exhibits “robust yet fragile” behavior, with regions of the parameter space where contagion is rare but catastrophic whenever it occurs. In further results, we develop a message-passing approach to recurrent state epidemics like susceptible-infectious-susceptible and susceptible-infectious-recoveredsusceptible where nodes can return to previously inhabited states and multiple waves of infection can pass through the population. Given that message-passing has been applied exclusively to models with one-way state changes like susceptible-infectious and susceptible-infectious-recovered, we develop message-passing for recurrent epidemics based on a new class of di↵erential equations and demonstrate that our approach is simple and e ciently approximates results obtained from Monte Carlo simulation, and that the accuracy of message-passing is often superior to the pair approximation (which also takes second-order correlations into account). vi