Miracle-dz/UniFAR-FTUs huggingface dataset:
Epigram prime: a demonstration

It would not be too much of a stretch to imagine that dependent types will be the next big thing in programming language research. The key benefit is that by allowing types to be indexed by data, it is possible to expose more and more of the structure that lies behind the programs we write. This leads to many pay-offs, especially in refined program control and in program verification. The appearance of GADTs in Haskell has shown that there is an appetite for this kind of type discipline in the functional programming community; we believe, however, that the full benefits will only be seen with a language that is designed from the ground up around the idea of dependent types. The Epigram project has been at the fore-front of research in to dependently typed functional programming since 2004 [4]. While its initial prototype implementation proved to be as notorious as it was influential - It nonetheless provided inspiration for many features in the latest version of the Agda programming language [5], and beyond. After a long period of development hell, the Epigram team [2] are well on the way to being able to release a system that will finally put the toys that we've been working on in the hands of people who are impatient to have them, including ourselves. We hope that the real impact of Epigram 2 will, once again, be its influence on other, more mature, languages. The key motivation to Epigram remains that the solution to many of the challenges to writing programs in dependently typed languages lies with the types themselves. By explaining, using the type system, what the problem is, we can then use the system to help us find the solution - this is the power of dependent types at work. In this demonstration, I will introduce the current state of the system and will show off some of the new features, which we hope will be of interest the MSFP audience. Of the new elements, the most fundamental change is in the underlying Type Theory, which is based on Observational Type Theory (OTT) [1]. Thanks to OTT, Epigram 2 provides the ability to reason extensionally about programs, while for the first time maintaining decidable type checking. I will also demonstrate how it has been possible to extended the equality to allow certain algebraic properties, for instance the functor laws, to hold definitionally. Our Type Theory also implements a reflective approach to data types [3], we will see how we can use this to write generic programs inductively over the structure of data types.
Verifying information flow goals in Security-Enhanced Linux

In this paper, we present a systematic way to determine the information flow security goals achieved by systems running a secure O/S, specifically systems running Security-Enhanced Linux. A formalization of the access control mechanism of the SELinux security server, together with a labeled transition system representing an SELinux configuration, provides our framework. Information flow security goal statements expressed in linear temporal logic provide a clear description of the objectives that SELinux is intended to achieve. We use model checking to determine whether security goals hold in a given system. These formal models combined with appropriate algorithms have led to automated tools for the verification of security properties in an SELinux system. Our approach has been used in other security management contexts over the past decade, under the name rigorous automated security management.
Scalable Data Dissemination for Inter-Vehicle-Communication: Aggregation versus Peer-to-Peer (Skalierbare Informationsverbreitung für die Fahrzeug-Fahrzeug-Kommunikation: Aggregation versus Peer-to-Peer)

Summary This paper investigates the scalable dissemination of data between vehicles. The application context of this work is traffic information systems where cars are not only consumers but also producers of information. The key challenge in those systems is to ensure scalability in an environment where data is provided and requested by all participating vehicles in a large area. We discuss two fundamentally different approaches to this problem: using direct communication between cars and compressing the data via aggregation versus relying on infrastructure. The latter approach can further be divided into client-server and peer-to-peer systems. We outline all three approaches and highlight their advantages and disadvantages. Zusammenfassung Im Rahmen dieses Beitrages wird die Verbreitung von Informationen zwischen Fahrzeugen untersucht. Im Vordergrund stehen dabei Verkehrsinformationssysteme, bei denen Fahrzeuge sowohl Produzenten als auch Konsumenten von Informationen sind. Die zentrale Herausforderung solcher Systeme ist ihre Skalierbarkeit. Wir stellen hier zwei fundamental verschiedene Herangehensweisen vor: Einerseits die direkte Kommunikation zwischen Fahrzeugen, andererseits den Einsatz von Infrastruktur für den Nachrichtenaustausch zwischen Fahrzeugen. Letzeres kann weiter in Client-Server- und Peer-to-Peer-Ansätze unterteilt werden. In diesem Artikel geben wir Beispiele für alle drei Ansätze und untersuchen diese hinsichtlich ihrer Vor- und Nachteile.
Small patches get in!

While there is a considerable amount of research on analyzing the change information stored in software repositories, only few researcher have looked at software changes contained in email archives in form of patches. In this paper we look at the email archives of two open source projects and answer questions like the following: How many emails contain patches? How long does it take for a patch to be accepted? Does the size of the patch influence its chances to be accepted or the duration until it gets accepted? Obviously, the answers to these questions can be helpful for the authors of patches, in particular because some of the answers are surprising.
Energy Aware Zone-based Clustering Algorithm in WSNs

Recent advances in the wireless sensor network introduction many protocols specially designed for sensor networks, different traffic models and energy efficiency techniques in Wireless Sensor Networks (WSN) so far. Most of the clustering protocols planned for the nodes are stationary. But, in applications like habitat monitoring those clustering mechanisms are invalid, so the static environment of sensors is not real. This paper proposes an effective clustering based on 'Energy Aware Zone-based with Splitting and Merging Clustering Algorithm in WSNs EZSMCA' protocol for WSN aiming at energy consumption, reduced traffic. Simulation results also show that EZSMCA outperforms existing LEACH and HEED protocols in terms of network lifetime and energy consumptions.
Formal Speciﬁcation and Veriﬁcation of Trust in Multi-Agent Systems

Trust remains one fundamental challenge that is holding back the success of mas . Although the available literature is rich with trust mechanisms and strategies, the notion of trust remains a vague notion. In this paper we try to bring these trust theories to a concrete level. We present a mechanism for specifying and verifying the various trust strategies and mechanisms of the available literature. We show how a dynamic model checker, along with the interaction and deontic models of multi-agent systems, may be used to achieve this.
Fast Schedulability Analysis Using Commodity Graphics Hardware

In this paper we explore the possibility of using commodity graphics processing units (GPUs) to speedup standard schedulability analysis algorithms. Our long-term goal is to exploit GPUs to accelerate common electronic design automation algorithms, most of which tend to be computationally expensive. Our main contribution in this paper is a reformulation of a standard demand bound criteria-based schedulability analysis algorithm as a streaming algorithm expressed in terms of computer graphics primitives. This allows the algorithm to be efficiently implemented on a GPU, thereby resulting in very attractive speedups.
ChaLearn looking at people: A review of events and resources

This paper reviews the historic of ChaLearn Looking at People (LAP) events. We started in 2011 (with the release of the first Kinect device) to run challenges related to human action/activity and gesture recognition. Since then we have regularly organized events in a series of competitions covering all aspects of visual analysis of humans. So far we have organized more than 10 international challenges and events in this field. This paper reviews associated events, and introduces the ChaLearn LAP platform where public resources (including code, data and preprints of papers) related to the organized events are available. We also provide a discussion on our main findings and perspectives of ChaLearn LAP activities.
Visual Analysis of Online Interactions through Social Network Patterns

In this article we present a system capable of graphically representing the interactions between students and teachers in hierarchical online forums. By defining the a'reply-to' relation between the users the system builds a graph. During forum posts mining, the system computes metrics taken from social network analysis which are then applied to the graph drawing process. This system brings up new possibilities to e-learning as a tool capable of helping the teacher assorting and illustrating the degree of participation of students; to identify key students in information passing, and to find the implicit relations between forums participants. Preliminary tests lead to the conclusions that the system is able to rapidly help in identifying situations like outliers, sources and sinks of information. It also depicts rapidly sub communities formed from forum participants.
Beneficial effects of local profound hypothermia and the possible mechanism after experimental spinal cord injury in rats

Objective: The primary focus of this study was to investigate the effects of local profound hypothermia and to explore the possible mechanism in adult rats with spinal cord injury. Study Design and Methods: Spinal cord injury models were established by placing aneurysm clips on T10. An epidural perfusion device was applied to maintain a steady temperature (18 °C) for 120 min with gradual rewarming to 37 °C Total hypothermic duration lasted up to about 170 min. The expression of axon regeneration inhibitors was tested by Western blot and real-time PCR. Luxol Fast Blue (LFB) stain and Bielschowsky silver stain were used to observe spinal cord morphology. Motor function of the hind limbs (BBB score) was monitored for 21 days. Results: The expressions of RhoA, ROCK-II, NG2, Neurocan, Brevican, and Nogo-A were downregulated by regional hypothermia (RH) after spinal cord injury. Subsequent observation showed that rats that had received RH had an alleviated demyelinating condition and a greater number of nerve fibers. Furthermore, the RH group achieved higher BBB scores than the spinal cord injury (SCI) group. Conclusions: Recovery of hind limb function in rats can be promoted by local profound hypothermia; this may be caused by the suppression of axon regeneration inhibitors.
Measuring the Hierarchy of Molecular Events During Clathrin‐Mediated Endocytosis

A well‐orchestrated hierarchy of molecular events is required for successful initiation and maturation of clathrin‐coated pits (CCPs). Nevertheless, CCPs display a broad range of lifetimes. This dynamic heterogeneity could either reflect differences in the temporal hierarchy of molecular events, or similar CCP maturation processes with variable kinetics. To address this question, we have used multi‐channel image acquisition and automated analysis of CCP dynamics in combination with a new method to quantify the time courses of recruitment of endocytic factors to CCPs of different lifetimes. Using this approach we have extracted the kinetics of recruitment and disassembly of fluorescently labeled clathrin and/or AP‐2 throughout the entire lifetime of temporally defined CCP cohorts. On the basis of these analyses, we can (i) directly correlate recruitment profiles of these two proteins; (ii) define five distinct CCP maturation phases, i.e. initiation, growth, maturation, separation and departure; (iii) distinguish events with absolute versus fractional timing and (iv) provide information on the spatial distribution of fluorophores during CCP maturation. Emerging from these analyses is a more clearly defined role for AP‐2 in determining the temporal hierarchy for clathrin recruitment and CCP maturation. This method provides a new means to identify other such hierarchies during CCP maturation.
Real-time Algorithms for Sparse Neuronal System Identification

We consider the problem of sparse adaptive neuronal system identification, where the goal is to estimate the sparse time-varying neuronal model parameters in an online fashion from neural spiking observations. We develop two adaptive filters based on greedy estimation techniques and regularized log-likelihood maximization. We apply the proposed algorithms to simulated spiking data as well as experimentally recorded data from the ferret's primary auditory cortex during performance of auditory tasks. Our results reveal significant performance gains achieved by the proposed algorithms in terms of sparse identification and trackability, compared to existing algorithms.
Thrombin-activatable fibrinolysis inhibitor and cardiovascular risk factors in polycystic ovary syndrome.

OBJECTIVE We aimed to assess circulating thrombin activatable fibrinolysis inhibitor (TAFI) levels and carotid intima-media thickness (CIMT) in PCOS patients and control subjects. In this study we aimed to evaluate the relation between the levels of TAFI and homocysteine, high sensitive CRP (hsCRP), fibrinogen and CIMT in PCOS patients carrying a potential risk for developing CVD and diabetes and compared with age- and body mass index-matched controls. RESEARCH DESIGN AND METHODS We studied 68 PCOS patients and 26 healthy controls. We conducted an observational study examining noninvasive markers of early CV disease in women with PCOS including structural CIMT. Noninvasive markers of early CVD, CIMT were measured in PCOS patients and control subjects. Metabolic parameters included fasting insulin and glucose levels, lipid and androgen levels, TAFI levels, hsCRP. RESULTS Fasting glucose levels, prolactin, TSH, Total-cholesterol, LDL-cholesterol, triglyceride, estradiol, DHEA-S and age were similar in the two groups, whereas serum insulin, fibrinogen, hs-CRP, 17-OHP, free-testosterone, total testosterone, HOMA-IR, HDL were significantly elevated in PCOS patients in comparison to control subjects (p<0.05). Plasma TAFI levels were similarly in PCOS patients compared with healthy controls. No difference was observed in the combined IMT among the studied groups. CONCLUSIONS In our study, no significant difference in lipid parameters was determined between patients with PCOS and healthy controls. In our study, we did not observed any difference in CIMT measurements and TAFI levels between patients with PCOS and healthy controls that can be explained by their low ages and short duration of PCOS.
Qualité, Fouille et Gestion des Connaissances

Qualite, Fouille et Gestion des Connaissances Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Sed non risus. Suspendisse lectus tortor, dignissim sit amet, adipiscing nec, ultricies sed, dolor. Cras elementum ultrices diam. Maecenas ligula massa, varius a, semper congue, euismod non, mi. Proin porttitor, orci nec nonummy molestie, enim est eleifend mi, non fermentum diam nisl sit amet erat. Duis semper. Duis arcu massa, scelerisque vitae, consequat in, pretium a, enim. Pellentesque congue. Ut in risus volutpat libero pharetra tempor. Cras vestibulum bibendum augue. Praesent egestas leo in pede. Praesent blandit odio eu enim. Pellentesque sed dui ut augue blandit sodales
Ensemble of Diverse Sparsifications for Link Prediction in Large-Scale Networks

Previous research has aimed to lower the cost of handling large networks by reducing the network size via sparsification. However, when many edges are removed from the network, the information that can be used for link prediction becomes rather limited, and the prediction accuracy thereby drops significantly. To address this issue, we propose a framework called Diverse Ensemble of Drastic Sparsification (DEDS), which constructs ensemble classifiers with good accuracy while keeping the prediction time short. DEDS includes various sparsification methods that are designed to preserve different measures of a network. Therefore, DEDS can generate sparsified networks with significant structural differences and increase the diversity of the ensemble classifier, which is key to improving prediction performance. When a network is drastically sparsified to 0.1% of the original one, DEDS effectively relieves the drop in prediction accuracy and raises the AUC value from 0.52 to 0.70. With a larger sparsification ratio, DEDS is even able to outperform the classifier trained from the original network. As for the efficiency, more than 95% prediction cost can be saved when the network is sparsified to 1% of the original one. If the original network is disk-resident but can fit into main memory after being sparsified, as much as 99.94% of the prediction cost can be saved.
Withania somnifera: a pre-clinical study on neuroregenerative therapy for stroke

Stroke management exerts insurmountable societal and economic burden on the patient as well as their caregivers. In the year 2010 alone, the direct and indirect costs of stroke care amounted to 36.5 billion dollars (Go et al., 2014). Despite concentrated efforts to develop a safe, effective drug for stroke, we have not discovered one since the introduction of recombinant tissue plasminogen activator (rtPA)—the standalone FDA-approved therapy for stroke. While rtPA is highly effective, it needs to be given within 3–4.5 hours of the onset of stroke symptoms (Zivin, 2009). This is often complicated by the delay in the commencement of treatment due to preliminary inclusion parameters that are required to be ascertained before rtPA administration.
Organochlorine pesticide levels and risk of Alzheimer’s disease in north Indian population

Alzheimer’s disease (AD) could result from a multifactorial process involving both genetic predisposition and exposure to environmental factors like pesticides. A case control study of 70 patients of AD and 75 controls was done to examine the association between organochlorine pesticides (OCPs) and risk of AD. OCPs (hexachlorocyclohexane (HCH), aldrin, dieldrin, endosulfan, pp′-dichlorodiphenyldichloroethylene (pp′-DDE), op′-DDE, pp′-dichlorodiphenyltrichloroethane (pp′-DDT), op′-DDT, pp′-dichlorodiphenyldichloroethane (pp′-DDD) and op′-DDD) were extracted from blood and quantitatively estimated using gas chromatography. A Mann–Whitney U test revealed significant difference in β-HCH levels (U = 1237.00, W = 4087.00, z = −6.296, p = 0.000, r = −0.71), dieldrin levels (U = 1449.00, W = 4299.00, z = −5.809, p = 0.000, r = −0.68) and pp′-DDE levels (U = 2062.00, W = 4912.00, z = −2.698, p = 0.007, r = −0.59) between AD patients and controls. In conclusion, this study supports epidemiological studies that associate exposure to pesticides with increased risk of AD, and we identified the specific pesticides β-HCH, dieldrin and pp′-DDE that are associated with the risk of AD in the north Indian population. However, further research is needed to establish the potential role of these OCPs as an etiologic agent for AD case.
Attacking image classification based on bag-of-visual-words

Nowadays, with the widespread diffusion of online image databases, the possibility of easily searching, browsing and filtering image content is more than an urge. Typically, this operation is made possible thanks to the use of tags, i.e., textual representations of semantic concepts associated to the images. The tagging process is either performed by users, who manually label the images, or by automatic image classifiers, so as to reach a broader coverage. Typically, these methods rely on the extraction of local descriptors (e.g., SIFT, SURF, HOG, etc.), the construction of a suitable feature-based representation (e.g., bag-of-visual words), and the use of supervised classifiers (e.g., SVM). In this paper, we show that such a classification procedure can be attacked by a malicious user, who might be interested in altering the tags automatically suggested by the classifier. This might be used, for example, by an attacker who is willing to avoid the automatic detection of improper material in a parental control system. More specifically, we show that it is possible to modify an image in order to have it associated to the wrong class, without perceptually affecting the image visual quality. The proposed method is validated against a well known image dataset, and results prove to be promising, highlighting the need to jointly study the problem from the standpoint of both the analyst and the attacker.
Haptic Interaction with Complex Models Based on Precomputations

There have been several approaches proposed so far to address the issue of coupling the heavy computations with high refresh rate of the haptic loop. Basically, two main classes of solutions can be identified: either simplified models based on linearization or reduction are used, or some precomputation is employed before the real-time interaction takes place. In the first part of this chapter, an overview of the methods proposed in last decade is presented. Some of them are described in more detail to emphasize the key concepts which are used frequently in haptic soft-tissue modeling nowadays. In the second part of the chapter, an approach based on precomputation and interpolation of precomputed data is presented. The technique consists of two procedures: first, it is a construction of a discrete set of data, which can be performed in reasonable time on today's computers. Second, it is a fast approximation of an arbitrary deformation which is needed during the real-time interaction using only the data from the discrete set constructed by the first procedure.
Ambiguous collision outcomes and sliding with infinite friction in models of legged systems

This work explores the collision process at foot contact in models of legged robots. In particular, we highlight that for legged systems the widely used assumption of no sliding of the contact points can yield inconsistent outcomes. For certain contact configurations and system parameters, neither the assumption of lift-off of the trailing foot nor the assumption that it stays fixed on the ground yield valid solutions. The foot will slide, even if an infinite coefficient of friction is assumed. In a related effect, we present configurations in which the solution of the collision process is ambiguous. These behaviors are examined for the models of a minimalistic biped, a passive dynamic walker, and the five-link bipedal robot RAMone. The paper provides background for these non-intuitive behaviors and investigates the influence of system parameters onto the collision behavior of a passive dynamic walker. By studying bipedal models that range from minimalistic to physically accurate, this paper establishes a bridge between the theoretical study of unilateral contact in multibody dynamic simulations and the application of these simulation methods in the modeling of ground contact in actual legged systems.