Miracle-dz/UniFAR-FTUs huggingface dataset:
TSI Finders for Estimation of the Location of an Interference Source Using an Ariborne Array

An algorithm based on space fast time adaptive processing to estimate the physical location of an interference source closely associated with a physical object and enhancing the detection performance against that object using a phased array radar is presented. Conventional direction finding techniques can estimate all the signals and their associated multipaths usually in a single spectrum. However, none of the techniques are currently able to identify direct path (source direction of interest) and its associated multipath individually. Without this knowledge, we are not in a position to achieve an estimation of the physical location of the interference source via ray tracing. The identification of the physical location of an interference source has become an important issue for some radar applications. The proposed technique identifies all the terrain bounced interference paths associated with the source of interest only (main lobe interferer). This is achieved via the introduction of a postprocessor known as the terrain scattered interference (TSI) finder.
Harmony search algorithm for the container storage problem

Recently a new metaheuristic called harmony search was developed. It mimics the behaviors of musicians improvising to find the better state harmony. In this paper, this algorithm is described and applied to solve the container storage problem in the harbor. The objective of this problem is to determine a valid containers arrangement, which meets customers delivery deadlines, reduces the number of container rehandlings and minimizes the ship idle time. In this paper, an adaptation of the harmony search algorithm to the container storage problem is detailed and some experimental results are presented and discussed. The proposed approach was compared to a genetic algorithm previously applied to the same problem and recorded a good results.
Two novel frame shift, recurrent and de novo mutations in the ITGB2 (CD18) gene causing leukocyte adhesion deficiency in a highly inbred North African population

We have identified four different mutations causing leukocyte adhesion deficiency (LAD) in the ITGB2 gene of patients from a highly inbred population. Two were novel single-bp deletions (1497delG and 1920delG) causing frame shift and the two others were the missense mutations G284S and R593C. In our study, the G284S was a recurrent mutation while the R593C occurred de novo. We have also characterized a novel Xba1 polymorphic site located at the 5′ end of the ITGB2 locus. Family studies showed that the 1497delG mutation segregated with this marker and the intragenic AvaII polymorphic marker, suggesting the presence of a founder effect. The observation of a heterogeneous spectrum including de novo and recurrent mutations causing LAD in a highly inbred population is rather unexpected. In view of the literature published on the molecular genetics of LAD and considering the ethnic origin of the patients studied, our findings confirm the heterogeneity of the mutations causing LAD and point out potential mutational hot spots in the ITGB2 gene.
Supporting Non-membership Proofs with Bilinear-map Accumulators

In this short note, we present an extension of Nguyen’s bilinear-map based accumulator scheme [8] to support non-membership witnesses and corresponding non-membership proofs, i.e., cryptographic proofs that an element has not been accumulated to a given set. This complements the non-membership proofs developed by Li et al. [7] for the RSA accumulator [2, 3, 5], making the functionality of the bilinear-map accumulator equivalent to that of the RSA accumulator. Our non-membership extension of Nguyen’s scheme [8] makes use of the q-Strong Diffie-Hellman assumption the security of the original scheme is based on.
Factorial Structure of the Hospital Anxiety and Depression Scale in Outpatients with Somatic Disease

Objective: To examine the factorial structure of the Hospital Anxiety and Depression Scale(HADS) in a sample of Outpatients with somatic disease.Methods: Exploratory and confirmatory factor analytic approaches were used to evaluate the factor structure of this measure in a sample of Outpatients with somatic disease(n=244). Results: Both factor analysis methods indicated that two-factor(anxiety and depression) models provided a better fit to the data compared to three-factor and single-factor models for Outpatients with somatic disease.Conclusion: These results suggest that the Chinese version of the HADS may be two-factor(anxiety and depression) models in Outpatients with somatic disease or,more likely,that different factor models may be needed for different populations.
Pseudo-Newtonian gravitational potential for Schwarzschild-de Sitter spacetimes

Pseudo-Newtonian gravitational potential describing the gravitational field of static and spherically symmetric black holes in the universe with a repulsive cosmological constant is introduced. In order to demonstrate the accuracy of the pseudo-Newtonian approach, the related effective potential for test-particle motion is constructed and compared with its general relativistic counterpart given by the Schwarzschild-de Sitter geometry. The results indicate that such an approach could be useful in applications of developed Newtonian theories of accretion discs in astrophysically interesting situations in large galactic structures for the Schwarzschild-de Sitter spacetimes with the cosmological parameter y=(1/3)\Lambda M^2<10^{-6}.
Function-Theoretic Explanation and Neural Mechanisms

Frances Egan A common kind of explanation in cognitive neuroscience might be called functiontheoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function contributes to the exercise of the cognitive capacity. Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it reveals the causal structure of the mechanism underlying the capacity. If they are right, then a cognitive model that resists a transparent mapping to known neural mechanisms fails to be explanatory. I argue that a function-theoretic characterization of a cognitive capacity can be genuinely explanatory even absent an account of how the capacity is realized in neural hardware.
Neural network based extended Kalman filter for localization of mobile robots

This paper studies the localization of a mobile robot based on neural network based extended Kalman filter (NNEKF) algorithm. Extended Kalman filter (EKF) is used to fuse the information acquired from both the robot optical encoders and ultrasonic sensors in order to estimate the current robot position and orientation. Then the error covariance of the EKF is tracked by the covariance matching technique. When the output of the matching technique does not meet the certain condition, a neural network is employed to modify the system noise covariance matrix. Simulation results demonstrate that, with the comparison to the odometry and the standard EKF method under the same error divergence condition, the proposed algorithm effectively improves the accuracy of the localization of the mobile robot system and prevents the filter divergence.
Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases

The function of genes is often evolutionarily conserved, and comparing the annotation of ortholog genes in different model organisms has proved to be a powerful predictive tool to identify the function of human genes. Here, we describe Manteia, a resource available online at http://manteia.igbmc. fr. Manteia allows the comparison of embryological, expression, molecular and etiological data from human, mouse, chicken and zebrafish simultaneously to identify new functional and structural correlations and gene-disease associations. Manteia is particularly useful for the analysis of gene lists produced by high-throughput techniques such as microarrays or proteomics. Data can be easily analyzed statistically to characterize the function of groups of genes and to correlate the different aspects of their annotation. Sophisticated querying tools provide unlimited ways to merge the information contained in Manteia along with the possibility of introducing custom user-designed biological questions into the system. This allows for example to connect all the animal experimental results and annotations to the human genome, and take advantage of data not available for human to look for candidate genes responsible for genetic disorders. Here, we demonstrate the predictive and analytical power of the system to predict candidate genes responsible for human genetic diseases.
A Computer-Aided Distinction Method of Borderline Grades of Oral Cancer

We have developed a new computer-aided diagnostic system for differentiating oral borderline malignancies in hematoxylin-eosin stained microscopic images. Epithelial dysplasia and carcinoma in-situ (CIS) of oral mucosa are two different borderline grades similar to each other, and it is difficult to distinguish between them. A new image processing and analysis method has been applied to a variety of histopathological features and shows the possibility for differentiating the oral cancer borderline grades automatically. The method is based on comparing the drop-shape similarity level in a particular manually selected pair of neighboring rete ridges. It was found that the considered similarity level in dysplasia was higher than those in epithelial CIS, of which pathological diagnoses were conventionally made by pathologists. The developed image processing method showed a good promise for the computer-aided pathological assessment of oral borderline malignancy differentiation in clinical practice.
Restricting the spread of Firestorms in Social Networks

We investigate the social-media phenomenon defined as “online firestorms”: sudden discharges of large quantities of negative word-of-mouth that spreads rapidly through online social networks. Firestorms can start due to various reasons, such as online marketing campaigns that backfired or dissatisfaction of customers, and are a consequence of opening social media channels to the crowds. Firestorms have affective and viral nature and therefore posing severe threats, such as harming brand reputation and causing customer losses. Our motivation in this paper is the development of optimized forms of counteraction to firestorms, which engage individuals to act as supporters and initiate the spread of positive word-of-mouth, helping to constrain the firestorm as much as possible. We describe the required optimization as a seed-selection problem in the context of firestorms by explaining the differences it has compared to its examination in other existing contexts. We propose a new seed-selection method that is based on the concept of local centrality, which unlike existing social network analytics, selects supporters based not on the global structure of the social network, but locally, i.e., by taking into account the areas of a social network that have been affected by the negative word-of-mouth. Experimental evaluation with data from a real social network demonstrates that the proposed method presents several advantages compared to seed-selection based on commonly used global centrality scores.
Eicosanoid production, thrombogenic ratio, and serum and LDL peroxides in normo- and hypercholesterolaemic post-menopausal women consuming two oleic acid-rich diets with different content of minor components

The present paper compares the effects of two monounsaturated oils, extra virgin olive oil (EVOO) and high-oleic acid sunflower oil (HOSO), on serum and LDL peroxides, eicosanoid production and the thrombogenic ratio (thromboxane (TX) B2:6-keto-prostaglandin F1α) in fourteen non-obese post-menopausal women. The subjects, mean age 63 (SD 11) years, were assigned to two consecutive oleic acid-rich 28 d dietary periods. EVOO and HOSO represented 62 % of the total lipid intake and were used as the only culinary fat during the first and second dietary periods respectively. Serum peroxides, plasma α-tocopherol and TXB2 levels in stimulated platelet-rich plasma (PRP-TXB2) were significantly higher (P<0.01, P<0.001, and P<0.05 respectively) after the HOSO diet than after the EVOO diet. The relationship between the serum cholesterol level (<6.21 mmol/l or ≥6.21 mmol/l) and the type of dietary oil on eicosanoids, peroxides and α-tocopherol were evaluated by two-way ANOVA. Dietary oil significantly affected (P<0.05) the PRP-TXB2 level, whereas serum and LDL peroxides were significantly affected (P<0.001 and P<0.01 respectively) by the serum cholesterol level. The plasma α-tocopherol level was significantly affected by the serum cholesterol level and the type of dietary oil (both P<0.001). No significant relationships were found between serum cholesterol levels, serum peroxide or LDL peroxide levels, plasma α-tocopherol concentrations or α-tocopherol intakes with eicosanoid production or the thrombogenic ratio due to dietary changes. However, in spite of their higher α-tocopherol levels, hypercholesterolaemic subjects showed increased peroxidation in serum and LDL in comparison with normocholesterolaemic subjects on the HOSO diet in comparison with the EVOO diet. These findings suggest that differences in the type of minor compounds, as well as in the concentration of linoleic acid, in both these monounsaturated oils may play an important role in modulating eicosanoid production and lipoprotein peroxidation when they constitute a large proportion of the diet of post-menopausal women.
Temporary employment and health: a review.

OBJECTIVES We aimed to review evidence on the relationship between temporary employment and health, and to see whether the association is dependent on outcome measure, instability of employment, and contextual factors. METHOD We systematically searched for studies of temporary employment and various health outcomes and critically appraised 27 studies. RESULTS The review suggests higher psychological morbidity among temporary workers compared with permanent employees. According to some studies, temporary workers also have a higher risk of occupational injuries but their sickness absence is lower. Morbidity may be higher in temporary jobs with high employment instability and in countries with a lower number of temporary workers and unemployed workers. CONCLUSIONS The evidence indicates an association between temporary employment and psychological morbidity. The health risk may depend on instability of temporary employment and the context. Confounding by occupation may have biased some of the studies. Additional research to clarify the role of employment instability, hazard accumulation, and selection is recommended.
Memsherlock: an automated debugger for unknown memory corruption vulnerabilities

Software vulnerabilities have been the main contributing factor to the Internet security problems such as fast spreading worms. Among these software vulnerabilities, memory corruption vulnerabilities such as buffer overflow and format string bugs have been the most common ones exploited by network-based attacks. Many security countermeasures (e.g., patching, automatic signature generation for intrusion detection systems) require vulnerability information to function correctly. However, despite many years of research, automatically identifying unknown software vulnerabilities still remains an open problem. In this paper, we present the development of a security debugging tool named MemSherlock, which can automatically identify unknown memory corruption vulnerabilities upon the detection of malicious payloads that exploit such vulnerabilities. MemSherlock provides critical information for unknown memory corruption vulnerabilities, including (1) the corruption point in the source code (i.e., the statement that allows the exploitation of memory corruption vulnerability), (2) the slice of source code that helps the malicious input to reach the corruption point, and (3) the description of how the malicious input exploits the unknown vulnerability. We evaluate MemSherlock with a set of 11 real-world applications that have buffer overflow, heap overflow, and format string vulnerabilities. The evaluation results indicate that MemSherlock is a useful tool to facilitate the automatic vulnerability analysis process.
Security Analysis of Gagne et al.'s Threshold Attribute-Based Signcryption Scheme

In SCN2010, Gagne, Narayan, and Safavi-Naini proposed attribute-based signcryption with threshold structure. As in cipher text-policy attribute-based encryption, a sender can specify the access structure of recipients, and as in attribute-based signature, each recipient can verify the sender's attributes. In contrast to the access structure of recipients, the access structure of the sender needs to be fixed in the setup phase. In this paper, we show that Gagne et al.'s threshold attribute-based signcryption is not secure and give a concrete forgery attack. The attack can make use some keys to construct any other legal keys and at last totally break the scheme. We also show that the attack is effective on other attribute-based cryptographic schemes with the same key structure.
Boosting English-Chinese Machine Transliteration via High Quality Alignment and Multilingual Resources

This paper presents our machine transliteration systems developed for the NEWS 2015 machine transliteration shared task. Our systems are applied to two tasks: English to Chinese and Chinese to English. For standard runs, in which only official data sets are used, we build phrase-based transliteration models with refined alignments provided by the M2M-aligner. For non-standard runs, we add multilingual resources to the systems designed for the standard runs and build different language specific transliteration systems. Linear regression is adopted to rerank the outputs afterwards, which significantly improves the overall transliteration performance.
Widespread Use of Non-productive Alternative Splice Sites in Saccharomyces cerevisiae

Saccharomyces cerevisiae has been used as a model system to investigate the mechanisms of pre-mRNA splicing but only a few examples of alternative splice site usage have been described in this organism. Using RNA-Seq analysis of nonsense-mediated mRNA decay (NMD) mutant strains, we show that many S. cerevisiae intron-containing genes exhibit usage of alternative splice sites, but many transcripts generated by splicing at these sites are non-functional because they introduce premature termination codons, leading to degradation by NMD. Analysis of splicing mutants combined with NMD inactivation revealed the role of specific splicing factors in governing the use of these alternative splice sites and identified novel functions for Prp17p in enhancing the use of branchpoint-proximal upstream 3′ splice sites and for Prp18p in suppressing the usage of a non-canonical AUG 3′-splice site in GCR1. The use of non-productive alternative splice sites can be increased in stress conditions in a promoter-dependent manner, contributing to the down-regulation of genes during stress. These results show that alternative splicing is frequent in S. cerevisiae but masked by RNA degradation and that the use of alternative splice sites in this organism is mostly aimed at controlling transcript levels rather than increasing proteome diversity.
The Smart environment for retrieval system evaluation — advantages and problem areas

The Smart environment provides a test-bed for implementing and evaluating a large number of different automatic search and retrieval processes. In this chapter, the basic parameters underlying the Smart system design are briefly outlined, and a comparison is made with the characteristics of more conventional retrieval systems. The principal lessons learned from the Smart experiments are described, and some of the methodological problems raised by the system design are outlined. Finally, some comments are included about the disadvantages inherent in working in the laboratory, and the insights that can be gained in such a situation.
Project TEAL : Add Adaptive e-Learning to your Workflows

Workflowor taskembedded e-learning is an actual trend in enterprise and office environments. Having been integrated into enterprise workflow or task management systems, e-learning turns into a powerful tool for enterprise knowledge management: the seamless integration into the working environment allows getting actual information about potential learning goals of the user; using up-to-date e-learning technologies enables just-in-time delivery of goal-oriented, user-tailored learning curricula, helping employees to solve problems autonomously and competently. This paper reports about the results of the project TEAL (Task-embedded adaptive e-Learning) taking place at German Research Center for Artificial Intelligence (DFKI). The aim of the project was to prove the concepts and feasibility of task-embedded e-learning by designing a reference architecture and realizing prototypical implementation based on the existing components built at DFKI: WFMS Taskman, LCMS DaMiT and ActiveMath.
A 0535+26: back in business

In 2005 May/June, after 10 yr of inactivity, the Be/X-ray binary system A 0535+26 underwent a major X-ray outburst. In this paper, data are presented from 10 yr of optical, infrared and X-ray monitoring showing the behaviour of the system during the quiescent epoch and the lead up to the new outburst. The results show the system going through a period when the Be star in the system had a minimal circumstellar disc and then a dramatic disc recovery leading, presumably, to the latest flare up of X-ray emission. The data are interpreted in terms of the state of the disc and its interaction with the neutron star companion.
Detection of hazardous driving behavior using fuzzy logic

We propose a system that can record driving events and detect unsafe driving behaviors. Three sensors, an engine control unit (ECU) reader, a 3-axis accelerometer, and a camera are used, in which they represent the car, the passenger, and the driverpsilas perspective. Our system combines data from these three sensors with a fuzzy inference system to identify an event of hazardous driving. The output of the system is the driving risk level ranging from 1 to 3, where 1 is the safest. The output of the system was verified by comparison with a questionnaire from three passengers in a test run experiment.
Interaction modelling for wearable assistive devices

An exoskeleton may help healthy older adults stay independent for a longer time by augmenting their torque at weakened joints. Predictive models are useful to develop exoskeletons and assess the effect of exoskeletons on the user. Existing models that predict the effect of exoskeletons on the user use pre-defined motions which do not change when the forces applied by the exoskeleton changes. In this work we have developed and tested a simulation architecture that incorporates the dynamic interaction between the user and the exoskeleton. This allows to predict modified motions due to the influence of the exoskeleton