Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsupervised segmentation based on Von Mises circular distributions for orientation estimation in textured images

This paper deals with textured images and more particularly with directional textures. We propose a new parametric technique to estimate the orientation field of textures. It consists in partitioning the image into regions with homogeneous orientations, and then to estimate the orientation inside each of these regions, which allows us to maximize the size of the samples used to estimate the orientation without being corrupted by the presence of frontiers between regions. Once estimated the local - hence noisy - orientations of the texture using small filters (3×3 pixels), image partitioning is based on the minimization of the stochastic complexity (Minimum Description Length principle) of the orientation field. The orientation fluctuations are modeled with Von Mises probability density functions, leading to a fast and unsupervised partitioning algorithm. The accuracy of the orientations estimated with the proposed method is then compared with other approaches on synthetic images. An application to the processing of real images is finally addressed.
Using Higher Order DCT Difference to Effective Improve Markov Process Based JPEG Steganalysis Detection Rate

In recent, A Markov Process based approach has been proposed to effective attacking JPEG Steganography, and the experimental works had demonstrated that scheme has outperformed the existing steganalyzers in attacking JPEG steganography. To improve that original Markov Process based approach, several variants based that scheme has been proposed and experimented including using JPEG 1-D array, using higher order difference of JPEG DCT coefficients, using inter-block 1-D array and separating the DCT coefficients to several groups. Support vector machines (SVM) are utilized as classifier. The experimental works are presented to demonstrate that using intra-block JPEG 2-D array and second order difference can significantly improve detection rate.
Feature-Based Matrix Factorization

Recommender system has been more and more popular and widely used in many applications recently. The increasing information available, not only in quantities but also in types, leads to a big challenge for recommender system that how to leverage these rich information to get a better performance. Most traditional approaches try to design a specic
MIROS: A Hybrid Real-Time Energy-Efficient Operating System for the Resource-Constrained Wireless Sensor Nodes

Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant.
Pharmaceutical drugs supporting regeneration of small-intestinal mucosa severely damaged by ionizing radiation in mice

Accidental exposure of the abdomen to high-dose radiation leads to severe consequences initiated by disruption of the mucosa in the small intestine. Therapeutic options are limited, even though various treatments have been investigated, particularly in the field of regenerative therapy. In order to identify readily available treatment methods, we included several current pharmaceutical drugs, for which the clinical trials have already been completed, in tests on mice that had undergone severe mucosal damage by radiation. The drugs were injected into mice 24 h after exposure to 15.7 Gy X-rays. The effects of the drugs on the damaged mucosa of the small intestine were evaluated using early regeneration indices [the expression of c-myb mRNA, and proliferation of epithelial cells in the form of microcolonies (MCs) by Days 4 and 5 post-irradiation] and the survival rate of the mice. Enhancement of mucosal regeneration at Day 4 (c-myb: P < 0.01, MC: P < 0.05) and improvement of the survival rate (P < 0.05) were observed when a clinical dose of gonadotropin, a stimulator of androgen, was injected. Similarly, a clinical dose of thiamazole (which prevents secretion of thyroid hormone) stimulated mucosal growth by Day 5 (c-myb: P < 0.01, MC: P < 0.05) and also improved the survival rate (P < 0.05). The nonclinical drugs histamine and high-dose octreotide (a growth hormone antagonist) also gave significant survival-enhancing benefits (P < 0.01 and P < 0.05, respectively). These results can be used to construct therapeutic programs and applied in various experimental studies to control the regeneration of damaged mucosa.
Respiratory motion correction for 2D cine cardiac MR images using probabilistic edge maps

2D short axis (SA) cine MR images are of crucial importance for the accurate assessment of cardiac anatomy and function. Since SA cine stacks are routinely acquired during multiple breath-holds, different breath-hold positions can cause a misalignment of the heart between different slices, with potential detrimental effects on a variety of clinically relevant measurements (e.g. volume or shape of the left ventricle). In this study, we propose a novel approach to spatially align motion corrupted SA slices in MR image stacks using 3D probabilistic edge maps (PEMs) generated with structured decision forests. In our technique, each 2D SA slice is associated with a 3D PEM outlining the myocardial contours in the same slice as well as in the adjacent one. In-plane spatial misalignment between adjacent slices is then corrected using a registration algorithm applied to the associated PEMs. This approach was tested against a conventional intensity-based registration method on SA cine stacks acquired from 26 healthy subjects, for whom anatomical 3D cardiac images were also available as reference. End-diastolic left ventricular volumes are estimated using a 3D multi-atlas segmentation technique and used to quantify alignment accuracy. The results show that the proposed technique successfully reduces the misalignment between slices and that the registered stacks allow a more accurate volumetric estimation than both the original and the intensity-corrected ones.
Cross-cultural professional communication in the context of globalization

The article provides evidence that business communication and especially at the industrial enterprise depends on a lot of factors. One of such factors, cross-cultural communication, is focused on as a central notion. The author attracts examples and considers exogenous and endogenous factors for effective industrial business communication. One of the widely covered aspects of communication is the role of the individual, his personality and personal traits of behavior in establishing and maintaining mutual understanding. The concept of culture in corporate or business ethics is proven to be an inseparable factor of communication which should guide the communicators in treating contracts and employees.
Examination Of Gender And Age Differences In Disgust Sensitivity

Disgust sensitivity (DS) is the strength of response an individual has to a disgust-eliciting stimulus, such as feces or a bloody injury. It is believed that DS evolved as a way to prevent illness and to protect an individual from potentially harmful substances. Previous research suggests a relationship between gender and DS, as women tend to be higher in DS than men. The purpose of this study was to replicate this finding using a larger, representative sample, and to investigate levels of DS across the lifespan. Additionally, we hypothesized that younger women would have higher levels of DS than older women, particularly for the contamination and core DS subscales. Participants in this study included US citizens who were online Amazon MTurk workers. There were 1,339 participants, 804 women and 535 men, ages 18 to 83 years old. Participants completed the Disgust Scale, which included the Core Disgust, Animal-Reminder, and Contamination subscales. Multiple regression analysis demonstrated that gender more than age reliably predicted several different types of disgust sensitivity. In addition to several main effects, there was one interaction demonstrating that younger women were more likely to report higher levels the Contamination component of DS.
Effects of resveratrol on apoptosis in a rat model of vascular dementia

Resveratrol is a natural polyphenol widely present in plants, particularly in the skin of red grapes and in wine. It possesses a wide range of biological effects and exhibits neuroprotective effects in numerous diseases. However, data evaluating the effects of resveratrol in vascular dementia (VaD) are lacking. In the present study, the permanent, bilateral common carotid artery occlusion rat model was used to study the effects of resveratrol on VaD. The Morris water maze was used to test the spatial learning and memory performance of the rats. The expression levels of Bax, Bcl-2, cleaved caspase-3 and cleaved poly(ADP-ribose) polymerase (PARP) in the hippocampus were measured. The results showed that resveratrol inhibited memory impairment in the VaD rat model, and attenuated the increases in the expression levels of Bax, cleaved caspase-3 and cleaved PARP and the reductions in the expression levels of Bcl-2 that were induced by VaD. These results provide a novel insight into the neuroprotective effects of resveratrol and its possible therapeutic role in VaD.
Span Ef fi ciencies of Wings at Low Reynolds Numbers

Elegant and inviscid analytical theory can predict the induced drag on lifting wings of finite span. The theoretical prediction is then often modified by multiplication with a dimensionless coefficient for which the departure from a value of 1 is used as a way to incorporate realistic and necessary departures from the idealizedmodel. Unfortunately, there are conflicting definitions of these dimensionless coefficients, often known as span efficiencies, so that even if numerical values are assigned in a clear and transparent fashion, their application andvalidity remain unclear.Here, the differences between two commonly used definitions of span efficiency are identified and it is shown that for the case of airfoil sections and finite wings at chordwise Reynolds numbers less than 10, neither one has values close to those commonly assumed in the aeronautics literature. The cause of these significant viscousmodifications to inviscid theory is traced to themovement of separation points from the trailing edge of real airfoils. Amodified nomenclature is suggested to reduce the likelihood of confusion, and appropriate formulations for the drag of streamlined bodies in viscous flows at moderate Reynolds number are considered, with application to small-scale flying devices, both natural and engineered.
Morphine disinhibits glutamatergic input to VTA dopamine neurons and promotes dopamine neuron excitation

One reported mechanism for morphine activation of dopamine (DA) neurons of the ventral tegmental area (VTA) is the disinhibition model of VTA-DA neurons. Morphine inhibits GABA inhibitory neurons, which shifts the balance between inhibitory and excitatory input to VTA-DA neurons in favor of excitation and then leads to VTA-DA neuron excitation. However, it is not known whether morphine has an additional strengthening effect on excitatory input. Our results suggest that glutamatergic input to VTA-DA neurons is inhibited by GABAergic interneurons via GABAB receptors and that morphine promotes presynaptic glutamate release by removing this inhibition. We also studied the contribution of the morphine-induced disinhibitory effect on the presynaptic glutamate release to the overall excitatory effect of morphine on VTA-DA neurons and related behavior. Our results suggest that the disinhibitory action of morphine on presynaptic glutamate release might be the main mechanism for morphine-induced increase in VTA-DA neuron firing and related behaviors. DOI: http://dx.doi. org/10.7554/eLife.09275. 001
Improving the Design Process by Predicting Downstream Values of Design Attributes

This paper presents a computational approach to developing design space models that are utilized to improve the design process by predicting values of downstream design attributes based on information available at early stages, such as preliminary design specifications. The predictive models are similar in function, though not in form, to the internal (mental) models created by experienced designers; however, the advantages of these models are that it may be possible to construct them in the absence of a designer’s internal models, and that they can be passed on to and used by less experienced designers. Once created, the computational models aid designers in exploration of design alternatives and to reduce design costs and product development time.
Towards a single-photon energy-sensitive pixel readout chip: pixel level ADCs and digital readout circuitry

Unlike conventional CMOS imaging, a single photon imager detects each individual photon impinging on a detector, accumulating the number of photons during a certain time window and not the charge generated by the all the photons hitting the detector during said time window. The latest developments in the semiconductor industry are allowing faster and more complex chips to be designed and manufactured. With these developments in mind we are working towards the next step in single photon X-ray imaging: energy sensitive pixel readout chips. The goal is not only to detect and count individual photons, but also to measure the charge deposited in the detector by each photon, and consequently determine its energy. Basically, we are aiming at a spectrometer-in-a-pixel, or a “color X-ray camera”. The approach we have followed towards this goal is the design of small analog-to-digital-converters at the pixel level, together with a very fast digital readout from the pixels to the periphery of the chip, where the data will be transmitted off-chip. We will present here the design and measurement on prototype chips of two different 4-bit pixel level ADCs. The ADCs are optimized for very small area and low power, with a resolution of 4-bits and a sample rate of 1 Msample/s. The readout architecture is based around current-mode sense amplifiers and asynchronous token-passing between the pixels. This is done in order to achieve event-by-event readout and, consequently, on-line imaging. We need to read eventby- event (photon-by-photon), because we cannot have memory on the pixels due to obvious size constraints. We use current-mode sense amplifiers because they perform very well in similar applications as very fast static-RAM readout.
Relying on Safe Distance to Ensure Consistent Group Membership in Ad Hoc Networks

The design of ad hoc mobile applications often requires the availability of a consistent view of the application state among the participating hosts. Such views are important because they simplify both the programming and verification tasks. Essential to constructing a consistent view is the ability to know what hosts are within proximity of each other, i.e., form a group in support of the particular application. In this paper we propose a protocol that allows hosts within communication range to maintain a consistent view of the group membership despite movement and frequent disconnections. The novel features of this protocol are its reliance on location information and a conservative notion of logical connectivity that creates the illusion of announced disconnection. Movement patterns and delays are factored in the policy that determines which physical connections are susceptible to disconnection. An implementation of the protocol in Java is available for testing.
AVPpred: collection and prediction of highly effective antiviral peptides

In the battle against viruses, antiviral peptides (AVPs) had demonstrated the immense potential. Presently, more than 15 peptide-based drugs are in various stages of clinical trials. Emerging and re-emerging viruses further emphasize the efforts to accelerate antiviral drug discovery efforts. Despite, huge importance of the field, no dedicated AVP resource is available. In the present study, we have collected 1245 peptides which were experimentally checked for antiviral activity targeting important human viruses like influenza, HIV, HCV and SARS, etc. After removing redundant peptides, 1056 peptides were divided into 951 training and 105 validation data sets. We have exploited various peptides sequence features, i.e. motifs and alignment followed by amino acid composition and physicochemical properties during 5-fold cross validation using Support Vector Machine. Physiochemical properties-based model achieved maximum 85% accuracy and 0.70 Matthew’s Correlation Coefficient (MCC). Performance of this model on the experimental validation data set showed 86% accuracy and 0.71 MCC which is far better than the general antimicrobial peptides prediction methods. Therefore, AVPpred—the first web server for predicting the highly effective AVPs would certainly be helpful to researchers working on peptide-based antiviral development. The web server is freely available at http://crdd.osdd. net/servers/avppred.
Characterization of Pythium Transcriptome and Gene Expression Analysis at Different Stages of Fermentation

Background The Pythium splendens is a potentially useful organism for the synthesis of large amounts of eicosapentaenoic acid. Peak biomass and lipid accumulation do not occur at the same time and growth temperature has an effect on the fatty acid composition. Little is known about the pathway or the genes involved in growth, lipid synthesis or temperature resistance in P. splendens. Analysis of the transcriptome and expression profile data for P.splendensRBB-5 were used to extend genetic information for this strain and to contribute to a comprehensive understanding of the molecular mechanisms involved in specific biological processes. Methodology/Principal Findings This study used transcriptome assembly and gene expression analysis with short-read sequencing technology combined with a tag-based digital gene expression (DGE) system. Assembled sequences were annotated with gene descriptions, such as gene ontology (GO), clusters of orthologous group (COG) terms and KEGG orthology (KO) to generate 23,796 unigenes. In addition, we obtained a larger number of genes at different stages of fermentation (48, 100 and 148 h). The genes related to growth characteristics and lipid biosynthesis were analyzed in detail. Some genes associated with lipid and fatty acid biosynthesis were selected to confirm the digital gene expression (DGE) results by quantitative real-time PCR (qRT-PCR). Conclusion/Significance The transcriptome improves our genetic understanding of P.splendensRBB-5 greatly and makes a large number of gene sequences available for further study. Notably, the transcriptome and DGE profiling data of P.splendensRBB-5 provide a comprehensive insight into gene expression profiles at different stages of fermentation and lay the foundation for the study of optimizing lipid content and growth speed at the molecular level.
Opaque: An Oblivious and Encrypted Distributed Analytics Platform

Many systems run rich analytics on sensitive data in the cloud, but are prone to data breaches. Hardware enclaves promise data confidentiality and secure execution of arbitrary computation, yet still suffer from access pattern leakage. We propose Opaque, a distributed data analytics platform supporting a wide range of queries while providing strong security guarantees. Opaque introduces new distributed oblivious relational operators that hide access patterns, and new query planning techniques to optimize these new operators. Opaque is implemented on Spark SQL with few changes to the underlying system. Opaque provides data encryption, authentication and computation verification with a performance ranging from 52% faster to 3.3x slower as compared to vanilla Spark SQL; obliviousness comes with a 1.6-46x overhead. Opaque provides an improvement of three orders of magnitude over state-of-the-art oblivious protocols, and our query optimization techniques improve performance by 2-5x.
Matching and blending human motions temporal scaleable dynamic programming

This paper presents a method for matching the frames of the human motions acquired by a motion capture system, and then creating blended (interpolated) motions according to the matching result. This matching method is basically a variation of a dynamic programming (DP) matching but we enhanced it to enable it to detect the timescale parameters. This scaleable dynamic programming (scaleable-DP) can match and evaluate the same class of motions such as walking, running, stepping and their timescale parameters. This approach is adaptable for differences in individuals, such as body sizes and timing of the stop-frames. On the blending pipeline, we first generate the keyframes according to the matching result. The keyframes are generated by considering the spatial and temporal difference of individual motions. After that, transition motions are synthesized between the keyframes. We experimented with our approach by using 15 gait motions and 5 dance motions. The results of these demonstrations show the validity of the proposed algorithm.
Task Scheduling Algorithm based on Greedy Strategy in Cloud Computing

In view of Min-Min algorithm prefers scheduling small tasks and Max-Min algorithm prefers scheduling big tasks led to the problem of load imbalance in cloud computing, a new algorithm named Min-Max is proposed. Min-Max makes good use of time of greedy strategy, small tasks and big tasks are put together for scheduling in order to solve the problem of load imbalance. Experimental results show that the Min-Max improves the utilization rate of the entire system and saves 9% of the overall execution time compared with Min-Min. As compared to Max-Min, Min-Max improves the utilization rate of the entire system and the total completion time and average response time are saved by 7% and 9%, re- spectively.
DP5: A Private Presence Service

Abstract Users of social applications like to be notified when their friends are online. Typically, this is done by a central server keeping track of who is online and offline, as well as of all of the users’ “buddy lists”, which contain sensitive information. We present DP5, a cryptographic service that implements online presence indication in a privacy-friendly way. DP5 allows clients to register their online presence and query the presence of their list of friends while keeping this list secret. Besides presence, high-integrity status updates are supported, to facilitate key update and rendezvous protocols. While infrastructure services are required for DP5 to operate, they are designed to not require any long-term secrets and provide perfect forward secrecy in case of compromise. We provide security arguments for the indistinguishability properties of the protocol, as well as an evaluation of its scalability and performance.