Miracle-dz/UniFAR-FTUs huggingface dataset:
Constraint Games: Framework and Local Search Solver

Game theory is a highly successful paradigm for strategic decision making between multiple agents having conflicting objectives. Since a few years, games have been studied in a computational perspective, raising new issues like complexity of equilibria or succinctness of representation. Indeed, the main representation for general games is still a n-dimensional matrix of exponential size called normal form. In this paper, we introduce the framework of Constraint Games to model strategic interaction between players. A Constraint Game is composed of a set of variables shared by all the players. Among these variables, each player owns a set of decision variables she can control and a Constraint Optimization Problem defining her preferences. Since the preferences of a player depend on the decisions taken by the other players, each player may try to improve her position by choosing an assignment that optimizes her preferences. Pure Nash equilibria are situations in which no player may improve her preferences unilaterally. Constraint Games are thus a generic tool to model general games and can be exponentially more succinct than their normal form. We show the practical utility of the framework by modelling a few realistic problems and we propose an algorithm based on tabu search to compute pure Nash equilibria in Constraint games that outperforms the algorithms based on normal form. In addition, Constraint Games raise some interesting research issues that deserve further attention.
IMMIX-intrusion detection and prevention system

Computer security has become a major problem in our society. Specifically, computer network security is concerned with preventing the intrusion of an unauthorized person into a network of computers. An intrusion detection system (IDS) is a tool to monitor the network traffic and users activity with the aim of distinguishing between hostile and non-hostile traffic. Most of current networks implement Misuse detection or Anomaly detection techniques for Intrusion detection. By deploying misuse based IDS it cannot detect unknown intrusions and anomaly based IDS have high false positive rate for detection. To overcome this, proposed system uses combination of both network based and host based IDPS as Hybrid Intrusion Detection and Prevention System which will be helpful for detecting maximum attacks on networks.
Using LTAG Based Features in Parse Reranking

We propose the use of Lexicalized Tree Adjoining Grammar (LTAG) as a source of features that are useful for reranking the output of a statistical parser. In this paper, we extend the notion of a tree kernel over arbitrary sub-trees of the parse to the derivation trees and derived trees provided by the LTAG formalism, and in addition, we extend the original definition of the tree kernel, making it more lexicalized and more compact. We use LTAG based features for the parse reranking task and obtain labeled recall and precision of 89.7%/90.0% on WSJ section 23 of Penn Treebank for sentences of length ≤ 100 words. Our results show that the use of LTAG based tree kernel gives rise to a 17% relative difference in f-score improvement over the use of a linear kernel without LTAG based features.
On Quantifying Semantic Information

The purpose of this paper is to look at some existing methods of semantic information quantification and suggest some alternatives. It begins with an outline of Bar-Hillel and Carnap’s theory of semantic information before going on to look at Floridi’s theory of strongly semantic information. The latter then serves to initiate an in-depth investigation into the idea of utilising the notion of truthlikeness to quantify semantic information. Firstly, a couple of approaches to measure truthlikeness are drawn from the literature and explored, with a focus on their applicability to semantic information quantification. Secondly, a similar but new approach to measure truthlikeness/information is presented and some supplementary points are made.
Impedance Estimation of Soft Tissue Using Ultrasound Signal

This paper proposes a new impedance estimation method for soft tissue using ultrasound. This method estimates the impedance distribution inside an object. An ultrasound probe, which is attached to a force sensor, compresses soft tissue and observes the deformation process of tissue while measuring reaction force. The impedance parameters are then estimated based on this information. Experiments were conducted under two conditions, a static analysis and a dynamic analysis. In the static analysis, the ultrasound probe compressed the soft tissue slowly while keeping a balance of the power. In the dynamic analysis, the probe compressed tissue dynamically, and the deformation process of the soft tissue was observed. Experimental results demonstrated that our method can estimate the impedance of a soft object.
Animating the adelino robot with ERIK: the expressive robotics inverse kinematics

This paper presents ERIK, an inverse kinematics technique for robot animation that is able to control a real expressive manipulator-like robot in real-time, by simultaneously solving for both the robot's full body expressive posture, and orientation of the end-effector (head). Our solution, meant for generic autonomous social robots, was designed to work out of the box on any kinematic chain, and achieved by blending forward kinematics (for posture control) and inverse kinematics (for the gaze-tracking/orientation constraint). Results from a user study show that the resulting expressive motion is still able to convey an expressive intention to the users.
Native code execution control for attack mitigation on android

Sophisticated malware targeting the Android mobile operating system increasingly utilizes local root exploits. These allow for the escalation of privileges and subsequent automatic, unnoticed, and permanent infection of a target device. Poor vendor patch policy leaves customer devices vulnerable for many months. All current local root exploits are exclusively implemented as native code and can be dynamically downloaded and run by any app. Hence, the lack of control mechanisms for the execution of native code poses a major threat to the security of Android devices. In this paper, we present different approaches to prevent local root exploits by means of gradually controlling native code execution. The proposed alterations to the Android operating system protect against all current local root exploits, while limiting the user experience as little as possible. Thus, the approaches we present help to avert automatic privilege escalation and to reduce exploitability and malware infection of Android devices.
Automatic image description by using word-level features

Automatic image description is one of the challenging tasks of image recognitions. However, there are image descriptions that contain some too specific phrases that cannot be judged only from appearance of images. In this paper, we propose a novel approach to collect general phrases for generating image descriptions. On the assumption that there are high frequency phrases related to an query image in the image descriptions of similar images, we select nouns and their attribute phrases from the image descriptions of similar images based on their frequency. In order to evaluate the relevance of our image description, we conduct comparative experiments with existing approaches. Our experimental results show that our image descriptions are short, concise and visually relevant to query images.
Siemens, Ferdinand von: Bargaining under Incomplete Information, Fairness, and the Hold-Up Problem

In the hold-up problem incomplete contracts cause the proceeds of relation-speciﬁc investments to be allocated by ex-post bargaining. The present paper investigates the eﬃciency of incomplete contracts if individuals have heterogeneous preferences implying heterogeneous bargaining behavior and - equally important - preferences are private information. As the sunk investment costs can thus potentially signal preferences, they can inﬂuence beliefs and consequently bargaining outcomes. The necessities of signalling are shown to generate very strong investment incentives. These incentives are based on the desire not to reveal information that is unfavorable in the ensuing bargaining. After ﬁnding all perfect Bayesian equilibria in pure strategies, the paper derives the necessary and suﬃcient conditions under which it is optimal to invest and trade eﬃciently.
Coordinated repression and activation of two transcriptional programs stabilizes cell fate during myogenesis

Molecular models of cell fate specification typically focus on the activation of specific lineage programs. However, the concurrent repression of unwanted transcriptional networks is also essential to stabilize certain cellular identities, as shown in a number of diverse systems and phyla. Here, we demonstrate that this dual requirement also holds true in the context of Drosophila myogenesis. By integrating genetics and genomics, we identified a new role for the pleiotropic transcriptional repressor Tramtrack69 in myoblast specification. Drosophila muscles are formed through the fusion of two discrete cell types: founder cells (FCs) and fusion-competent myoblasts (FCMs). When tramtrack69 is removed, FCMs appear to adopt an alternative muscle FC-like fate. Conversely, ectopic expression of this repressor phenocopies muscle defects seen in loss-of-function lame duck mutants, a transcription factor specific to FCMs. This occurs through Tramtrack69-mediated repression in FCMs, whereas Lame duck activates a largely distinct transcriptional program in the same cells. Lineage-specific factors are therefore not sufficient to maintain FCM identity. Instead, their identity appears more plastic, requiring the combination of instructive repressive and activating programs to stabilize cell fate.
WHO calls for better living conditions to reduce health gap

Improving daily living conditions is the key to reducing the health inequalities between rich and poor countries, says a report published by the World Health Organization, which aims to close the gap within the next generation. The report summarises the findings of a three year investigation by WHO’s commission on the social determinants of health, whose members include leading policy makers, academics, former heads of state, and former ministers of health. Children have dramatically different life chances, depending on where they were born, the report confirms. Life expectancy of children is …
Attention for speaking: domain-general control from the anterior cingulate cortex in spoken word production

Accumulating evidence suggests that some degree of attentional control is required to regulate and monitor processes underlying speaking. Although progress has been made in delineating the neural substrates of the core language processes involved in speaking, substrates associated with regulatory and monitoring processes have remained relatively underspecified. We report the results of an fMRI study examining the neural substrates related to performance in three attention-demanding tasks varying in the amount of linguistic processing: vocal picture naming while ignoring distractors (picture-word interference, PWI); vocal color naming while ignoring distractors (Stroop); and manual object discrimination while ignoring spatial position (Simon task). All three tasks had congruent and incongruent stimuli, while PWI and Stroop also had neutral stimuli. Analyses focusing on common activation across tasks identified a portion of the dorsal anterior cingulate cortex (ACC) that was active in incongruent trials for all three tasks, suggesting that this region subserves a domain-general attentional control function. In the language tasks, this area showed increased activity for incongruent relative to congruent stimuli, consistent with the involvement of domain-general mechanisms of attentional control in word production. The two language tasks also showed activity in anterior-superior temporal gyrus (STG). Activity increased for neutral PWI stimuli (picture and word did not share the same semantic category) relative to incongruent (categorically related) and congruent stimuli. This finding is consistent with the involvement of language-specific areas in word production, possibly related to retrieval of lexical-semantic information from memory. The current results thus suggest that in addition to engaging language-specific areas for core linguistic processes, speaking also engages the ACC, a region that is likely implementing domain-general attentional control.
Choosing Wisely Overnight? Residents’ Approach to Fever

Abstract We surveyed internal medicine residents regarding how they approach febrile patients in cross-cover settings. Residents frequently use the term “full fever work-up,” and rely on this for sign-out. Despite this, residents felt fever work-ups were not evidenced-based, and definitions of when and how to respond to a fever varied.
Consistency of Markov chain quasi-Monte Carlo on continuous state spaces

The random numbers driving Markov chain Monte Carlo (MCMC) simulation are usually modeled as independent U(0, 1) random variables. Tribble [Markov chain Monte Carlo algorithms using completely uniformly distributed driving sequences (2007) Stanford Univ.] reports substantial improvements when those random numbers are replaced by carefully balanced inputs from completely uniformly distributed sequences. The previous theoretical justification for using anything other than i.i. d. U(0, 1) points shows consistency for estimated means, but only applies for discrete stationary distributions. We extend those results to some MCMC algorithms for continuous stationary distributions. The main motivation is the search for quasi-Monte Carlo versions of MCMC. As a side benefit, the results also establish consistency for the usual method of using pseudo-random numbers in place of random ones.
Simultaneous registration of multiple range views for use in reverse engineering

When reverse engineering a CAD model, it is necessary to integrate information from several views of an object into a common reference frame. Given a rough initial alignment, further pose refinement here uses an improved version of the interactive closes point algorithm. Incremental adjustments are computed simultaneously for all data sets, resulting in a more globally optimal set of transformations. Also, thresholds for removing outlier correspondences are not needed, as the merging data sets are considered as a whole. Motion updates are computed through force-based optimization, using implied springs between data sets. Experiments indicate that even for very rough initial positionings, registration accuracy approaches 25% of the interpoint sampling resolution of the images.
Effect of powder compaction on radiation-thermal synthesis of lithium-titanium ferrites

Effect of powder compaction on the efficiency of thermal and radiation-thermal synthesis of lithium-substituted ferrites was investigated by X-Ray diffraction and specific magnetization analysis. It was shown that the radiation-thermal heating of compacted powder reagents mixture leads to an increase in efficiency of lithium-titanium ferrites synthesis.
A Three-day Course of Dexamethasone Therapy to Prevent Chronic Lung Disease in Ventilated Neonates: A Randomized Trial

Background. Although several trials of early dexamethasone therapy have been completed to determine if such therapy would reduce mortality and chronic lung disease (CLD) in infants with respiratory distress, optimal duration and side effects of such therapy remain unknown. Purpose. The purpose of this study was: 1) to determine if a 3-day course of early dexamethasone therapy would reduce CLD and increase survival without CLD in neonates who received surfactant therapy for respiratory distress syndrome and 2) to determine adverse effects associated with such therapy. Design. This was a prospective multicenter randomized trial comparing a 3-day course of dexamethasone therapy beginning at 24 to 48 hours of life to placebo therapy. Two hundred forty-one neonates (dexamethasone n = 118, placebon = 123), who weighed between 500 g and 1500 g, received surfactant therapy, and were at significant risk for CLD or death using a model to predict CLD or death at 24 hours of life, were enrolled in the trial. Infants randomized to receive early dexamethasone were given 6 doses of dexamethasone at 12-hour intervals beginning at 24 to 48 hours of life. The primary outcomes compared were survival without CLD and CLD. CLD was defined by the need for supplemental oxygen at the gestational age of 36 weeks. Complication rates and adverse effects of study drug therapy were also compared. Results. Neonates randomized to early dexamethasone treatment were more likely to survive without CLD (RR: 1.3; 95% CI: 1.03, 1.7) and were less likely to develop CLD (RR: 0.6; CI: 0.3, 0.98). Mortality rates were not significantly different. Subsequent dexamethasone therapy use was less in early dexamethasone-treated neonates (RR: 0.8; CI: 0.7, 0.96). Very early (≤7 days of life) intestinal perforations were more common among dexamethasone-treated neonates (8% vs 1%). Conclusion. We conclude that an early 3-day course of dexamethasone therapy increases survival without CLD, reduces CLD, and reduces late dexamethasone therapy in high-risk, low birth weight infants who receive surfactant therapy for respiratory distress syndrome. Potential benefits of early dexamethasone therapy at the dosing schedule used in this trial need to be weighed against the risk for early intestinal perforation.
Food Image Recognition by Using Bag-of-SURF Features and HOG Features

Due to food culture, religion, allergy and food intolerance we have to find a good system to help us recognize our food. In this paper, we propose methods to recognize food and to show the ingredients using a bag-of-features (BoF) based on SURF detection features. We also propose bag of SURF features and bag-of HOG Features at the same time with the SURF feature detection to recognize the food items. In the experiment, we have achieved up to 72% of accuracy rate on a small food image dataset of 10 categories. Our experiments show that the proposed representation is significantly accurate at identifying food in the existing methods. Moreover, the enhancement of the visual dataset with more images will improve the accuracy rates, especially for the classes with high diversity.
REORDERING EXPERIMENTS FOR N-GRAM-BASED SMT

This paper addresses the problem of reordering in statistical machine translation (SMT). We describe an elegant and efficient approach to couple reordering (word order monotonization) and decoding, which does not need for any additional model. We use linguistically motivated reordering rules to extend a monotonic search graph (with reordering hypotheses). The extended graph is traversed in decoding when a fully- informed decision can be taken (no preprocessing decision about reordering is taken). We also show how the N-gram translation model can be successfully used as reordering model when estimated with reordered source words (to harmonize the source and target word order). Experiments are reported on the Euparl task (Spanish- to-English and English-to-Spanish). Results are presented regarding translation accuracy and computational efficiency, showing significant improvements in translation quality for both translation directions at a very low computational cost.
Methylprednisolone reduces adhesion molecules in blood and cerebrospinal fluid in patients with MS

Objective: To analyze the expression of adhesion molecules on mononuclear cells from blood and CSF of patients with exacerbations of MS before and after megadose IV methylprednisolone (MP). Background: Adhesion molecules regulate transmigration of lymphocytes and monocytes/macrophages to the CNS and have an important role in the pathogenesis of MS. Methods: The expression of very late activation antigen 4 (VLA-4) and vascular cell adhesion molecule 1, lymphocyte function-associated antigen 1 (LFA-1), and intercellular adhesion molecule 1 (ICAM-1) was analyzed immunocytologically on lymphocytes and monocytes from blood and CSF of 23 patients and 11 healthy control subjects. The results were correlated with the Expanded Disability Status Scale and in half of the patients with the number of T2-weighted MS plaques and brain atrophy analyzed by MRI. Results: After treatment, the mean proportions of VLA-4, LFA-1, and ICAM-1 on blood lymphocytes (p < 0.0003, p < 0.00001, p < 0.01) and monocytes (p < 0.0001, p < 0.0002, p < 0.007) of 23 patients decreased. The expression of these adhesion proteins was also diminished on CSF leukocytes. However, even after treatment, the levels of VLA-4 and LFA-1 on lymphocytes from blood of MS patients remained higher than in the control subjects. The levels of VLA-4 and LFA-1 on blood lymphocytes (r = 0.67, p = 0.023) and VLA-4 on monocytes (r = 0.61, p = 0.047) correlated with the number of T2-weighted lesions. Conclusions: Megadose MP may suppress brain inflammation by reducing the expression of adhesion molecules on mononuclear cells from blood and CSF of MS patients. The inhibition of cellular trafficking in MS by MP offers an important means of altering the autoimmune response in MS.
The Tera computer system

The Tera architecture was designed with several major goals in mind. First, it needed to be suitable for very high speed implementations, i. e. , admit a short clock period and be scalable to many processors. This goal will be achieved; a maximum con guration of the rst implementation of the architecture will have 256 processors, 512 memory units, 256 I/O cache units, 256 I/O processors, and 4096 interconnection network nodes and a clock period less than 3 nanoseconds. The abstract architecture is scalable essentially without limit (although a particular implementation is not, of course). The only requirement is that the number of instruction streams increase more rapidly than the number of physical processors. Although this means that speedup is sublinear in the number of instruction streams, it can still increase linearly with the number of physical processors. The price/performance ratio of the system is unmatched, and puts Tera's high performance within economic reach. Second, it was important that the architecture be applicable to a wide spectrum of problems. Programs that do not vectorize well, perhaps because of a preponderance of scalar operations or too-frequent conditional branches, will execute e ciently as long as there is su cient parallelism to keep the processors busy. Virtually any parallelism available in the total computational workload can be turned into speed, from operation level parallelism within program basic blocks to multiuser timeand space-sharing. The architecture
Performance assessment and analysis of DNS tunneling tools

DNS Tunnels are built by proper tools that allow embedding data on DNS queries and responses. Each tool has its own strategies that affect the network performance in a unique way. In this paper, we propose an architectural analysis of the current state-of-the-art of DNS Tunneling tools. Then, we provide a comparative evaluation of such tools in term of performance, as a first step towards the possibility to relate each tool with a specific pattern of the DNS traffic. To this aim, we define an assessment of the tools in three different network configurations based on three performance metrics. We finally analyze the testing results and provide a first characterization of the performance of each tool.