Miracle-dz/UniFAR-FTUs huggingface dataset:
iCub Whole-Body Control through Force Regulation on Rigid Non-Coplanar Contacts

This paper details the implementation on the humanoid robot iCub of state-of-the-art algorithms for whole-body control. We regulate the forces between the robot and its surrounding environment to stabilize a desired robot posture. We assume that the forces and torques are exerted on rigid contacts. The validity of this assumption is guaranteed by constraining the contact forces and torques, e.g. the contact forces must belong to the associated friction cones. The implementation of this control strategy requires to estimate the external forces acting on the robot, and the internal joint torques. We then detail algorithms to obtain these estimations when using a robot with an iCub-like sensor set, i.e. distributed six-axis force-torque sensors and whole-body tactile sensors. A general theory for identifying the robot inertial parameters is also presented. From an actuation standpoint, we show how to implement a joint torque control in the case of DC brushless motors. In addition, the coupling mechanism of the iCub torso is investigated. The soundness of the entire control architecture is validated in a real scenario involving the robot iCub balancing and making contacts at both arms.
A Semi-supervised Approach for Generating a Table-of-Contents

This paper presents a semi-supervised model for generating a table-of-contents as an indicative summarization. We mainly focus on using word cluster-based information derived from a large amount of unannotated data by an unsupervised algorithm. We integrate word cluster-based features into a discriminative structured learning model, and show that our approach not only increases the quality of the resulting table-of-contents, but also reduces the number of iterations in the training process. In the experiments, our model shows better results than the baseline model in generating a table-of-contents, about 6.5% improvement in terms of averaged ROUGE-L score.
The roles of the temporal lobe in creative insight: an integrated review

ABSTRACT Recent studies have revealed that the temporal lobe, a cortical region thought to be in charge of episodic and semantic memory, is involved in creative insight. This work examines the contributions of discrete temporal regions to insight. Activity in the medial temporal regions is indicative of novelty recognition and detection, which is necessary for the formation of novel associations and the “Aha! ” experience. The fusiform gyrus mainly affects the formation of gestalt-like representation and perspective taking. The anterior and posterior middle temporal gyri (MTG) are individually associated with extensive semantic processing and inhibiting salient or routine word associations, which are necessary to form non-salient, novel and remote associations. The anterior and posterior superior temporal gyri (STG) are individually responsible for integrating/binding and accessing various types of available conceptual representations. Based on the current knowledge, an integrated model of the temporal lobe's role in insight and some future directions are proposed.
Evaluation of feature-based object identification for augmented reality applications on mobile devices

With the technological advancement in mobile computing industry the field of electronic commerce has gone through a paradigm shift. Today's customers are more inclined towards using sophisticated mobile assistants, to help them in shopping, indoor navigation etc. rather than struggling on their own. In the literature it can be found that several attempts have been taken to address this cause. Majority of those attempts are based on marker based object identification. But current scale and the trends of the electronic commerce industry demand shopping assistants who are following markerless object identification methods due to limitations like the limited number of objects that can be identified. In order to support more usable electronic commerce applications, this paper focuses on the feasibility of deploying common and readily available feature tracking algorithms which can provide the object identification capability without having fiducial markers.
Medial forebrain bundle axotomy during development induces apoptosis in dopamine neurons of the substantia nigra and activation of caspases in their degenerating axons

There is growing evidence that programmed cell death may play a role in degenerative neurologic disease. The caspases are a family of cell death proteins that mediate proteolytic cascades in the death process. Although there is clear evidence that caspases play a role in the destruction of the components of the neuronal soma, it has been controversial whether they play a role in the degeneration of axons that accompanies the death of the cell body. It is important to define the molecular mechanisms of axonal degeneration, because terminal degeneration may occur early in neurodegenerative disease. We have therefore investigated whether caspases play a role in axonal degeneration in the dopaminergic nigrostriatal system following axotomy of the median forebrain bundle during development. We find that this lesion induces apoptosis in midbrain dopaminergic neurons at the level of the cell soma. Concomitantly with this induction of apoptosis, degeneration of dopaminergic axons occurs and is characterized by the formation of axonal swellings and spheroids. Immunohistochemical analysis reveals that the activated form of caspase‐3 and a caspase cleavage product of β‐actin are abundantly expressed in these degenerating fibers. We conclude that caspases are activated in degenerating dopaminergic axons as the somata undergo programmed cell death in this model. These results raise the possibility that caspase activation may occur in other programmed cell death contexts for these neurons, and, if this is so, then their inhibition may be a useful therapeutic target. J. Comp. Neurol. 452:65–79, 2002. © 2002 Wiley‐Liss, Inc.
Complete characterization of the spectrum of the Kitaev model on spin ladders

We study the Kitaev model on a ladder network and find the complete spectrum of the Hamiltonian in closed form. Closed and manageable forms for all eigenvalues and eigenvectors, allow us to calculate the partition function and averages of non-local operators in addition to the reduced density matrices of different subsystems at arbitrary temperatures. It is also briefly discussed how these considerations can be generalized to more general lattices, including three-leg ladders and two dimensional square lattices.
Insecure Context Switching: Inoculating Regular Expressions for Survivability

For most computer end-users, web browsers and Internet services act as the providers and protectors of their personal information, from bank accounts to personal correspondence. These systems are critical to users' continued lifestyles but often show no evidence of survivability [45], or robustness against present and future attacks. Software defects, considered the largest risk to survivability [45], are quite prevalent in consumer products and Web service software components [12]. Recent widespread security issues [20] [19] serve to emphasize this fact and show a lack investment in survivability engineering practices [22] [23] [50] [53] that may have mitigated the risk. Common software components that comprise industry software, commercial or free, were authored and deployed with functional isolation in mind. Despite original intent, many of these components are migrating in to Internet-connected systems. The context switch from functional isolation to extreme connectivity changes the threat environment of these components dramatically [10] [53]. Most software that has undergone this sort of insecure context switch has received very little security attention. This paper briefly surveys recent examples of these sorts of context switches. In particular, we focus on the survivability and inoculation [31] of regular expression engine implementations in connected environments. Through the course of this research, a number of critical vulnerabilities were uncovered that traverse operating systems and applications including Adobe Flash, Apple Safari, Perl, GnuPG, and ICU.
Helicobacter pylori vacuolating cytotoxin inhibits duodenal bicarbonate secretion by a histamine-dependent mechanism in mice.

BACKGROUND The pathogenic mechanisms involved in Helicobacter pylori-induced duodenal mucosal injury are incompletely understood. In the present study, we sought to investigate the effect of H. pylori vacuolating cytotoxin (VacA) on duodenal mucosal bicarbonate (HCO3-) secretion. METHODS Concentrated bacterial culture supernatants from an H. pylori wild-type strain producing VacA with s1/m1 genotypes (P12) and from an isogenic mutant lacking VacA (P12DeltavacA) were used. HCO3- secretion by murine duodenal mucosa was examined in vitro in Ussing chambers. Duodenal mucosal histamine release was measured using enzyme-linked immunosorbent assay. The expression of histamine H2 receptor was examined by immunohistochemical analysis. RESULTS In a dose-dependent manner, the VacA-positive supernatant P12 reduced prostaglandin E2 (PGE2)-stimulated duodenal mucosal HCO3- secretion to a maximum of 49% (P<.0001), whereas P12DeltavacA did not result in significant inhibition (P>.05). Purified VacA had a similar effect. Histamine H2 receptor antagonists attenuated the effect of P12 on PGE2-induced HCO3- secretion. P12 stimulated duodenal histamine release in a dose-dependent manner, and exogenous histamine inhibited PGE2-stimulated duodenal HCO3- secretion. H2 receptor expression was found in duodenal epithelial cells, the enteric nerve plexus, and lymphocytes in Peyer's patch. CONCLUSIONS H. pylori VacA inhibits PGE2-stimulated duodenal epithelial HCO3- secretion by a histamine-dependent mechanism. This effect likely contributes to the damaging effect of H. pylori in the duodenal mucosa.
Association between Vitamin D and Circulating Lipids in Early Childhood

Vitamin D is associated with established cardiovascular risk factors such as low density lipoprotein (LDL) in adults. It is unknown whether these associations are present in early childhood. To determine whether serum 25-hydroxyvitamin D (25(OH)D) is associated with serum non-high density lipoprotein (non-HDL) cholesterol during early childhood we conducted a cross-sectional study of children aged 1 to 5 years. Healthy children were recruited through the TARGet Kids! practice based research network from 2008-2011 (n=1,961). The associations between 25(OH)D and non-fasting non-HDL cholesterol (the primary endpoint), total cholesterol, triglycerides, HDL, and low density lipoprotein (LDL) cholesterol, were evaluated using multiple linear regression adjusted for age, sex, skin pigmentation, milk intake, vitamin D supplementation, season, body mass index, outdoor play, and screen time. Each 10 nmol/L increase in 25(OH)D was associated with a decrease in non-HDL cholesterol concentration of -0.89 mg/dl (95% CI: -1.16,-0.50), total cholesterol of -1.08 mg/dl (95%CI: -1.49,-0.70), and triglycerides of -2.34 mg/dl (95%CI: -3.23,-1.45). The associations between 25(OH)D and LDL and HDL were not statistically significant. 25(OH)D concentrations were inversely associated with circulating lipids in early childhood, suggesting that vitamin D exposure in early life may be an early modifiable risk factor for cardiovascular disease.
Concurrent Validity and Test-retest Reliability of the OPTOGait Photoelectric Cell System for the Assessment of Spatio-temporal Parameters of the Gait of Young Adults

[Purpose] The purpose of this study was to investigate the concurrent validity and test-retest reliability of the recently introduced OPTOGait Photoelectric Cell System for the assessment of spatio-temporal parameters of gait. [Subjects] Twenty healthy young adults (mean age = 27.35, SD = 7.4) were asked to walk 3 times on walkway at a comfortable speed. [Methods] Concurrent validity was assessed by comparing data obtained using the OPTOGait and GAITRite systems, and reliability was assessed by comparing data from the first and third OPTOGait sessions. [Results] Concurrent validity, as identified by intra-class correlation coefficients (ICC (2, 1) = 0.929–0.998), coefficients of variation (CVME = 0.32–11.30%), and 95% limits of agreement, showed high levels of correlation. In addition, the test-retest reliability of the OPTOGait Photoelectric Cell System was demonstrated as showing a high level of correlation with all spatio-temporal parameters by intra-class correlation coefficients (ICC (3, 1) = 0.785–0.952), coefficients of variation (CVME = 1.66–4.06%), 95% limits of agreement, standard error of measurement (SEM = 2.17–5.96%), and minimum detectable change (MDC95% = 6.01–16.52%). [Conclusion] The OPTOGait Photoelectric Cell System has strong concurrent validity along with relative and absolute test-retest reliabilities. This portable system with easy-to-use features can be used for clinical assessments or research purposes as an objective means of assessing gait.
Clustering of Mycobacterium tuberculosis Cases in Acapulco: Spoligotyping and Risk Factors

Recurrence and reinfection of tuberculosis have quite different implications for prevention. We identified 267 spoligotypes of Mycobacterium tuberculosis from consecutive tuberculosis patients in Acapulco, Mexico, to assess the level of clustering and risk factors for clustered strains. Point cluster analysis examined spatial clustering. Risk analysis relied on the Mantel Haenszel procedure to examine bivariate associations, then to develop risk profiles of combinations of risk factors. Supplementary analysis of the spoligotyping data used SpolTools. Spoligotyping identified 85 types, 50 of them previously unreported. The five most common spoligotypes accounted for 55% of tuberculosis cases. One cluster of 70 patients (26% of the series) produced a single spoligotype from the Manila Family (Clade EAI2). The high proportion (78%) of patients infected with cluster strains is compatible with recent transmission of TB in Acapulco. Geomatic analysis showed no spatial clustering; clustering was associated with a risk profile of uneducated cases who lived in single-room dwellings. The Manila emerging strain accounted for one in every four cases, confirming that one strain can predominate in a hyperendemic area.
Building the Enterprise Fabric for Big Data with Vertica and Spark Integration

Enterprise customers increasingly require greater flexibility in the way they access and process their Big Data while at the same time they continue to request advanced analytics and access to diverse data sources. Yet customers also still require the robustness of enterprise class analytics for their mission-critical data. In this paper, we present our initial efforts toward a solution that satisfies the above requirements by integrating the HPE Vertica enterprise database with Apache Spark's open source big data computation engine. In particular, it enables fast, reliable transferring of data between Vertica and Spark; and deploying Machine Learning models created by Spark into Vertica for predictive analytics on Vertica data. This integration provides a fabric on which our customers get the best of both worlds: it extends Vertica's extensive SQL analytics capabilities with Spark's machine learning library (MLlib), giving Vertica users access to a wide range of ML functions; it also enables customers to leverage Spark as an advanced ETL engine for all data that require the guarantees offered by Vertica.
A Survey of Techniques for Intrusion Detection System

In this paper we will discuss the various kinds of anomalous and malicious activities, which can be a symptoms of Intrusion. The term Intrusion detection was coined in 1980. Since then many Frameworks for Intrusion Detection were proposed and executed successfully. But, day by day attackers come-up with new ideas, and with them, the field of Intrusion detection should also update in the technologies and methods of detecting Intrusions in the network. So, in this paper we will discuss about various frameworks or methods which were proposed by researchers, and their use and effectiveness in the field of Intrusion Detection. To detect Intrusion in the network we required a distributed approach which is a kind of using small independent entities, called as Agents, to detect these anomalous or malicious behaviors. Along with this the different data mining methods and algorithms are also used in Intrusion Detection.
Kwestionariuszowy pomiar pięciu cech osobowości dzieci i dorastających. Polska adaptacja Big Five Questionnaire-Children (BFQ-C)

The article presents the psychometric properties of the Polish version of the Big Five Questionnaire – Children (BFQ-C; Barbaranelli, Caprara, Rabasca & Pastorelli, 2003). BFQ-C is a questionnaire measuring five personality traits (energy/extraversion, agreeableness, conscientiousness, emotional instability and intellect/openness) in late childhood and adolescence. Two versions of BFQ-C were used in the study: in the first one children and adolescents describe themselves, and in the second one other informants (parents and teachers) provide information about children and adolescents. The participants in the study were 1,241 children and adolescents (aged from 7 to 15 years), 226 parents, and 475 teachers. The reliability was assessed by Cronbach’s alpha. The structural validity was assessed in a set of factor analyses. Convergent and discriminant validity were assessed using a multitrait–multimethod matrix (five traits and two versions of BFQ--C) and analyzed in structural equation modeling. The external validity was assessed by inspecting the relations between the personality traits measured by BFQ-C and temperamental traits in the model proposed by Oakland, Glutting, and Horton (1996), as well as temperamental traits in the model by Buss and Plomin (Oniszczenko, 1997). Both reliability and all kinds of validity were at acceptable levels, which leads to the conclusion that BFQ-C can be used in scientific research
Team: towards a software engineering semantic web

Large software development projects are complex endeavours that involve numerous participants which can work across several sites and act in various roles. Each participant produces and consumes information relevant for the success of the project. In such settings, an effective and efficient allocation of knowledge is a hard challenge, especially if there is no central authority, which enforces standards for the whole ecosystem. We consider semantic technologies as an important enabler to improve information and knowledge sharing in such scenarios, by helping to exchange and interconnect software engineering knowledge across the web. In this paper, we describe the corresponding vision of a Software Engineering Semantic Web and the role of intelligent IDEs in order to benefit from and contribute to it.
In Vivo Imaging Reveals a Pioneer Wave of Monocyte Recruitment into Mouse Skin Wounds

The cells of the mononuclear phagocyte system are essential for the correct healing of adult skin wounds, but their specific functions remain ill-defined. The absence of granulation tissue immediately after skin injury makes it challenging to study the role of mononuclear phagocytes at the initiation of this inflammatory stage. To study their recruitment and migratory behavior within the wound bed, we developed a new model for real-time in vivo imaging of the wound, using transgenic mice that express green and cyan fluorescent proteins and specifically target monocytes. Within hours after the scalp injury, monocytes invaded the wound bed. The complete abrogation of this infiltration in monocyte-deficient CCR2−/− mice argues for the involvement of classical monocytes in this process. Monocyte infiltration unexpectedly occurred as early as neutrophil recruitment did and resulted from active release from the bloodstream toward the matrix through microhemorrhages rather than transendothelial migration. Monocytes randomly scouted around the wound bed, progressively slowed down, and stopped. Our approach identified and characterized a rapid and earlier than expected wave of monocyte infiltration and provides a novel framework for investigating the role of these cells during early stages of wound healing.
Empirical Evaluation of Secure Two-Party Computation Models

Secure multi-party protocols make the computation of answers and decisions that depend on multiple parties’ private data possible, without revealing anything about the private inputs (other than what unavoidably can be deduced from the outputs). There are general results showing that any probabilistic polynomial time function can be computed in this framework in an asymptotically efficient manner, using circuit-simulation techniques. There is a frequent belief that these general circuit-simulation techniques are not practical compared to custom-built (i.e., problem-specific) solutions, unless the function being computed has a naturally circuit-like formulation. This paper carries out a quantitative empirical evaluation of this belief, for a problem that would apparently benefit from a custom-built protocol (forecasting using time series techniques). Our findings are somewhat surprising in the following aspects. First, the custom-built solution does not overcome the general circuit-simulation solution on a local network until the problem size becomes quite large. Second, relaxing (even slightly) the requirement that, instead of “nothing”, the protocols reveal “little” makes possible dramatic performance improvements over the solutions for the more strict requirement (whether they are custom-built or based on general circuit simulations). Third, other aspects (such as, e.g., system resources available) play a significant role in evaluation of a computational model. This paper describes the subtle implementation issues involved with this evaluation, presents its results, and talks about the lessons learned that should be valuable in future deployments of this kind of technology.
Development of the RWTH transcription system for slovenian

In this paper we describe the RWTH automatic speech recognition system for Slovenian developed within the transLectures project. The project aims at supporting the transcription and translation of video lectures freely available on the web. Difficulties arise on all levels of modeling: Slovenian is a morphologically rich language with a high level of inflection (pronunciation model), and a large variety of dialects and recording conditions brings uncertainty into the audio signal (acoustic model). Moreover, the video lectures cover a wide spectrum of topics with a high share of spontaneous speech and technical terms (language model). These issues require application of robust and adaptive methods. Besides the system description, this study mainly focuses on robust acoustic modeling. Building acoustic models from various resources, we also compare the influence of speaker adaptation to different neural network based acoustic features. Systematic application of these methods allows us to reduce the word error rate on the evaluation corpus from 59.2% to 43.4%. We also give a motivation for Slovenian open vocabulary recognition and perform some first steps.