Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison Between Bare-metal, Container and VM using Tensorflow Image Classification Benchmarks for Deep Learning Cloud Platform

The recent success of AI is contributed by the adaptation of u sing deep learning in decision making process. To harness the power of deep learning, developers must not only rely on a computing framework, but a cloud platform to ensure resource utilization and computin g performance to ease the burden on users as well. Hence, ”how cloud resources should be orchestrated for deep learnin g? ” becomes a fundamental question for cloud providers. In this work, we built an in-house OpenS tack cloud platform to enable various resource orchestrations, including virtual machine, container and bare-metal. Then we systematically evaluate the performance of different orchestration choices using Tensorfl ow image classification benchmarks to quantify the performance impact and discuss the challenges of addressin g these performance issues.
HiPPAI: High Performance Portable Accelerator Interface for SoCs

Specialized hardware accelerators are enabling today's System on Chip (SoC) platforms to target various applications. In this paper we show that as these SoCs evolve in complexity and usage, the programming models for such platforms need to evolve beyond the traditional driver oriented architecture. Using a test set up that employs a programmable FPGA based accelerator to implement one of the critical computation functions of a Mobile Augmented Reality based workload, we describe the performance drawbacks that a conventional programming model brings to compute environments employing hardware accelerators. We show that these performance issues become more critical as the interface latencies continue to improve over time with better hardware integration and efficient interconnect technologies. Under these usage scenarios, we show with measurements that the software overheads enforced by the current programming model, like those associated with system calls, memory copy and memory address translations account for a major part of the performance overheads. We then propose a novel High Performance Portable Accelerator Interface (HiPPAI) for SoC platforms using hardware accelerators to reduce the software overheads mentioned above. In addition, we position the new programming interface to allow for function portability between software and hardware function accelerators to reduce the application development effort. Our proposed model relies on two major building blocks for performance improvement. A uniform virtual memory addressing model based on hardware IOMMU support and direct user mode access to accelerators. We demonstrate how these enhancements reduce the overheads of system calls and address translations at the user/kernel boundary in traditional software stacks and enable function portability.
Optimizing Landmark-Based Routing and Preprocessing

Many acceleration techniques exist for the single-pair shortest path problem on road networks. Most of them have been significantly improved over the years to achieve faster preprocessing times and superior performance. In this spirit, our current work significantly improves the classic ALT (A* + Landmarks + Triangle equality) algorithm. By carefully optimizing both preprocessing and query phases, we managed to effectively minimize preprocessing time to a few seconds, making the ALT algorithm also suitable for dynamic scenarios, i.e., road networks with changing edge weights due to traffic updates. We also accelerated the query phase for both unidirectional and bidirectional versions of the ALT algorithm, providing fast enough query times (including full-path unpacking) suitable for real-time services and continental road networks.
Developmental mechanism of the periodic membrane skeleton in axons

Actin, spectrin, and associated molecules form a periodic sub-membrane lattice structure in axons. How this membrane skeleton is developed and why it preferentially forms in axons are unknown. Here, we studied the developmental mechanism of this lattice structure. We found that this structure emerged early during axon development and propagated from proximal regions to distal ends of axons. Components of the axon initial segment were recruited to the lattice late during development. Formation of the lattice was regulated by the local concentration of βII spectrin, which is higher in axons than in dendrites. Increasing the dendritic concentration of βII spectrin by overexpression or by knocking out ankyrin B induced the formation of the periodic structure in dendrites, demonstrating that the spectrin concentration is a key determinant in the preferential development of this structure in axons and that ankyrin B is critical for the polarized distribution of βII spectrin in neurites. DOI: http://dx.doi. org/10.7554/eLife.04581. 001
Autonomous optimization of fine motions for robotic assembly

In the past, robotic assembly has required rigid fixturing and special purpose robotic tools for every assembly component. Unfortunately, rigid fixtures and special purpose robotic tools often have to be customized for varying geometries. Alternatively, it is possible to operate in a semi-structured environment, defined by the use of softer fixtures (e.g. pickup bin) and softer robotic tools (e.g. suction cups or compliant pads) that can be used for many assembly applications without modification, but they demand specific motion plans that can tolerate greater positional uncertainty. We have developed a system that supports autonomous generation of parameterized fine motion plans for assembly that are robust under positional uncertainty and compliance introduced by the use of a suction cup instead of a gripper. To accomplish this a classifier is trained, implemented and tested for performance in the semi-structured environment for distinguishing between a failed or successful assembly. The trained classifier is then integrated with the entire system and many robot-attended experiments are performed that vary the fine motion parameters, and optimize them for successful outcomes using an Interval Estimation optimization algorithm. An approach to machine learning based on Support Vector Machines and Principal Component Analysis is used to make the optimization autonomous. We achieved a 99.7% classification accuracy with the trained classifier and by running repeated robot-attended experiments with artificial positional uncertainty and optimizing fine motion parameters, we were able to achieve a 38% improvement compared to fine motion plans with initial best guess parameters.
Resilience and acculturation among unaccompanied refugee minors

The present study was designed to understand differences between unaccompanied refugees who retained or achieved good mental health (healthy or resilient) and those who maintained or developed poor mental health (clinical and vulnerable). Using person-based analyses, the role of pre-migration traumatic exposure and acculturation-related factors in long-term trajectories of psychological adjustment among unaccompanied refugees was explored. This study included three waves of data collection in a population-based sample. The participants were 918 unaccompanied refugees who had received asylum and residence status in Norway. The pattern of change in depression symptoms over time was used to characterize subgroups displaying resilient, vulnerable, clinical or healthy trajectories. Results indicated that the extent of post-migration acculturation hassles and heritage culture competence, as well as pre-migration traumatic events and gender, distinguished the refugee groups in terms of mental health trajectories. The implications for clinical practice and immigration policy are discussed.
Genome Analysis of Small-Ruminant Lentivirus Genotype E: a Caprine Lentivirus with Natural Deletions of the dUTPase Subunit, vpr-Like Accessory Gene, and 70-Base-Pair Repeat of the U3 Region

ABSTRACT The nucleotide sequence of the highly divergent small-ruminant lentivirus genotype E has been determined. The full genome consists of 8,418 nucleotides and lacks two large portions corresponding nearly to the entire dUTPase subunit of the pol and vpr-like accessory genes. Moreover, the 70-bp repeat of the U3 region of the long terminal repeat was observed to be deleted. Interestingly, this lentivirus genotype is able to persist in a local breed population, and retrospective analysis revealed its presence in milk samples collected in 1999. gag sequences obtained from a flock coinfected with the B1 and E genotypes revealed that the evolutionary rates of the two viruses were quite similar. Since a reduced viral load and/or disease progression was observed for viruses with artificially deleted dUTPase and vpr-like genes, it is proposed that this viral cluster be designated a low-pathogenicity caprine lentivirus.
α5β1 Integrin-Mediated Adhesion to Fibronectin Is Required for Axis Elongation and Somitogenesis in Mice

The arginine-glycine-aspartate (RGD) motif in fibronectin (FN) represents the major binding site for α5β1 and αvβ3 integrins. Mice lacking a functional RGD motif in FN (FNRGE/RGE) or α5 integrin develop identical phenotypes characterized by embryonic lethality and a severely shortened posterior trunk with kinked neural tubes. Here we show that the FNRGE/RGE embryos arrest both segmentation and axis elongation. The arrest is evident at about E9.0, corresponding to a stage when gastrulation ceases and the tail bud-derived presomitic mesoderm (PSM) induces α5 integrin expression and assumes axis elongation. At this stage cells of the posterior part of the PSM in wild type embryos are tightly coordinated, express somitic oscillator and cyclic genes required for segmentation, and form a tapered tail bud that extends caudally. In contrast, the posterior PSM cells in FNRGE/RGE embryos lost their tight associations, formed a blunt tail bud unable to extend the body axis, failed to induce the synchronised expression of Notch1 and cyclic genes and cease the formation of new somites. Mechanistically, the interaction of PSM cells with the RGD motif of FN is required for dynamic formation of lamellipodia allowing motility and cell-cell contact formation, as these processes fail when wild type PSM cells are seeded into a FN matrix derived from FNRGE/RGE fibroblasts. Thus, α5β1-mediated adhesion to FN in the PSM regulates the dynamics of membrane protrusions and cell-to-cell communication essential for elongation and segmentation of the body axis.
Design and Implementation of Baseband Digital Modulator for CDMA Communication System

Code Division Multiple Access (CDMA) technique provides anti jamming capability, carrier frequency reuse and most importantly, avoids unauthorized access to the systems. aft. The paper presents the design and implementation of base band digital modulator for a CDMA communication system. It describes the selection criteria for spreading code along with their implementation. To achieve more hardware efficiency and good phase resolution, Coordinate Rotation Digital Computer (CORDIC) is used in realizing the base band BPSK modulator. The paper also presents the comparison of CORDIC based and look up table based modulator. The application of developed system in satellite communication is explored. The system is implemented on XILINX FPGA platform and tested in real time for its performance.
Modeling the Spectral Signatures of Accretion Disk Winds: A New Monte Carlo Approach

Bipolar outflows are present in many disk-accreting astrophysical systems. In disk-accreting cataclysmic variables (CVs), these outflows are responsible for most of the strong features in the ultraviolet spectra of these systems. However, there have been few attempts to model these features quantitatively. Here we describe a new, hybrid Monte Carlo/Sobolev code, which allows us to synthesize the complete spectrum of a disk-dominated, mass-losing CV. The line profiles that we calculate for C IV resemble those calculated by previous workers when an identical geometry is assumed. However, our synthetic spectra exhibit not only the well-known resonance lines of O VI, N V, Si IV, and C IV but, with an appropriate choice of mass-loss rate and wind geometry, also many lines originating from excited lower states. Many of these lines have already been seen in the far-ultraviolet spectra of CVs obtained with the Hopkins Ultraviolet Telescope, the Far Ultraviolet Spectroscopic Explorer, and the Hubble Space Telescope. In order to illustrate the degree to which we are currently able to reproduce observed spectra, we finally present a preliminary fit to the Hopkins Ultraviolet Telescope spectrum of the dwarf nova Z Cam in outburst.
SENESCENCE AND REJUVENATION IN INTACT COTYLEDONS OF CUCURBITA PEPO L. (ZUCCHINI)

Summary. Growth parameters and total pigment content (chlorophyll a+b and carotenoids) were investigated through postgermination, greening, natural senescence and subsequent rejuvenation of intact cotyledons of Cucurbita pepo L. (zucchini). Dark-induced senescence and recovery of the cotyledons after 2-day darkening of a whole plant were also studied. Results showed significant increase in the fresh weight of cotyledons accompanied by a reciprocal decrease in dry matter during the first two weeks of their postgerminative growth. During the period of greening cotyledons rapidly accumulated chlorophylls and carotenoids in a synchronous manner. Maximum pigment contents were reached by days 7-8 after the onset of germination, followed by a steady state by day 14-15, and a gradual decline thereafter during the period of natural senescence. Cotyledons intensively yellowed, lost their turgor and died about 25 days after seed germination. Epicotyl decapitation at the stage of visible yellowing resulted in a recovery of both chlorophyll and carotenoids amounts during the next 15 days of rejuvenation period. When 8-day-old seedlings were transferred to the dark for 2 days, a progressive reduction in fresh and dry weight as well as in the chlorophyll and carotenoids content and net photosynthetic rate was registered. The pigment losses and CO 2 assimilation as well as the growth reduction of darktreated cotyledons were completely reversed after the return of the plants to normal light regime. Eleven days after ceasing the dark treatment chlorophyll content of the recovering plants was even increased. In contrast, fiveday dark treatment of entire plants could not be overcome by returning to the light.
Beyond ℓ1 norm minimization — High quality recovery of non-sparse compressible signals

We propose a novel algorithm for the recovery of non-sparse, but compressible signals from linear undersampled measurements. The algorithm proposed in this paper consists of two steps. The first step recovers the signal by the ℓ1 minimization. Then, the second step decomposes the ℓ1 reconstruction into major and minor components. By using the major components, measurements for the minor components of the target signal are estimated. Error evaluation of the estimate leads to the standard ridge regression for the recovery of the minor components with the regularization parameter determined using the error bound. After a slight modification to the major components, the final estimate is obtained by combining the two estimates. Computational cost of the proposed algorithm is mostly the same as the ℓ1 minimization. Simulation results show the effectiveness of the proposed algorithm over not only ℓ1 minimization but also the Lasso estimator.
Wireless system for detecting human temperature

To help keep seniors in their homes while maximizing the goal of remote monitoring relentlessly, we opted for a remote monitoring system based around a so-called smart camera and a wireless transmission system between the patient's residence and a center for medical expertise. We know that the rise in body temperature is a convincing and reliable indicator of most viral infections in humans. To address this issue we have used the thermal photography whose ability to capture the moving heat. We know that the human body emits infrared radiation whose mean wavelength is approximately 10 microns. Thermal photography is used in this project because it allows developing real-time infrared images of the face or the body of the targeted person to detect whether or not its temperature exceeds a certain threshold value. Infrared (IR) detectors used in this work, with proper calibration, are able to monitor remotely and without contact with the human body temperature and even discriminate between radiations emitted by human body in two different situations.
A versatile electrophoresis system for the analysis of high‐ and low‐molecular‐weight proteins

A new, versatile, multiphasic buffer system for high‐resolution sodium dodecyl sulfate‐polyacrylamide gel electrophoresis of proteins in the relative molecular weight range of 300 000–3000 Da is described. The system, based on the theory of multiphasic zone electrophoresis, allows complete stacking and destacking of proteins in the above Mr range. The buffer system uses taurine and chloride as trailing and leading ion, respectively, and Tris, at a pH close to its pKa, as the buffering counterion. Coupled with limited variation in the acrylamide concentration, this electrophoresis system allows to tailor the resolution in the 6–200 kDa Mr range, with minimal difficulties in the post electrophoretic identification processes.
Extractive Summarization Of Farsi Documents Based On PSO Clustering

As there is an ever-increasing number of textual resources, users nowadays enjoy access to a wider range of data; hence, accessing accurate and reliable ones has become a problematic issue. Automated summarization systems can play a principal role in covering the main ideas of the texts and removing time limitations. The present study presents a textual summarization system based on sentence clustering. There are some methods proposed to solve clustering problems so that for reaching a desirable clustering, collective intelligence algorithms are used for optimizing the methods. These methods rely on semantic aspect of words based on their relations in the text. Ultimately, appropriate sentences are selected from each cluster after clustering the sentences on the basis of the aforementioned criteria. A collection of Persian sports news articles are selected for the assessment. The findings reveal that the presented method yields more accurate results than others.
Numerical Study for the Three-Dimensional Rayleigh-Taylor Instability through the TVD/AC Scheme and Parallel Computation

The Rayleigh? Taylor instability is a gravity driven instability of a contact surface between fluids of different densities. The growth of this instability is sensitive to numerical or physical mass diffusion. For this reason, high resolution of the contact discontinuity is particularly important. In this paper, we address this problem using a second-order TVD finite difference scheme with artificial compression. We describe our numerical simulations of the 3D Rayleigh? Taylor instability using this scheme. The numerical solutions are compared to (a) the exact 2D solution in the linear regime and (b) numerical solutions using the TVD scheme and the front tracking method. The computational program is used to study the evolution of a single bubble and 3D bubble merger, i.e., the nonlinear evolution of a single mode and the process of nonlinear mode? mode interaction.
Revenue Management Without Forecasting or Optimization: An Adaptive Algorithm for Determining Airline Seat Protection Levels

We investigate a simple adaptive approach to optimizing seat protection levels in airline revenue management systems. The approach uses only historical observations of the relative frequencies of certain seat-filling events to guide direct adjustments of the seat protection levels in accordance with the optimality conditions of Brumelle and McGill (1993). Stochastic approximation theory is used to prove the convergence of this adaptive algorithm to the optimal protection levels. In a simulation study, we compare the revenue performance of this adaptive approach to a more traditional method that combines a censored forecasting method with a common seat allocation heuristic (EMSR-b).
Simple Algorithms for Graph Partition Problems

Based on the Belief Propagation Method, we propose simple and deterministic algorithms for some NP-hard graph partitioning problems, such as the Most Likely Partition problem and the Graph Bisection problem. These algorithms run in O(n+m) or O((n+m) log n) time on graphs with n vertices and m edges. For their average case analysis, we consider the planted solution model and prove that they yield an correct answer with high probability for large range of probabilistic parameters.
A Genetic-Based Design of Auto-Tuning Fuzzy PID Controllers

This paper presents genetic algorithms (GAs) to perform the optimal design of an auto-tuning fuzzy proportional-integral-derivative (PID) controller and to determine the minimal number of fuzzy rules simultaneously. Different from PID controllers with fixed gains, the fuzzy PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivatives, while the output variables are the PID gains. Based on the proposed GAs, the centers and the widths of the Gaussian membership functions, the fuzzy control rules corresponding to every possible combination of input linguistic variables, and the PID gains are chosen as parameters to be determined. When defining the fitness function of the GA, the concept of multi-objective optimization is used such that the fitness function can be defined in a systematic way. To show the effectiveness and validity of the designed fuzzy PID controller, a typical benchmark, a multivariable seesaw system, is used for illustration.
Hapticat: exploration of affective touch

This paper describes the Hapticat, a device we developed to study affect through touch. Though intentionally not highly zoomorphic, the device borrows behaviors from pets and the rich manner in which they haptically communicate with humans. The Hapticat has four degrees of freedom to express itself: a pair of ear-like appendages, a breathing mechanism, a purring mechanism, and a warming element. Combinations of levels for these controls are used to define the five active haptic responses: playing dead, asleep, content, happy, and upset,. In the paper we present the design considerations and implementation details of the device. We also detail a preliminary observational study where participants interacted with the Hapticat through touch. To compare the effects of haptic feedback, the device presented either active haptic renderings or none at all. Participants reported which of the five responses they believed the Hapticat rendered, as well as their degree of affect to the device. We observed that participants' expectations of the device's response to various haptic stimuli correlated with our mappings. We also observed that participants were able to reasonably recognize three of the five response renderings, while having difficulty discriminating between happy and content states. Finally, we found that participants registered a broader range of affect when active haptic renderings were applied as compared to when none were presented.
Chapter 14 GRAPHICAL REPRESENTATION OF FINGERPRINT IMAGES

Fingerprint recognition is very important in automatic personal identification. In conventional fingerprint recognition algorithms, fingerprints are represented graphically with a simple set of minutiae and singular points, but the information in this kind of representation is not adequate for large-scale applications or where fingerprint quality is poor. A complete and compact representation of fingerprints is thus highly desirable. In this chapter, we focus on research issues in the graphical representation of fingerprints. We first introduce minutiae-based representation and provide some models for the graphical representation of orientation fields. Latterly, we deal with the generation of synthetic fingerprint images and conclude with a discussion of how to establish a complete fingerprint representation.