Miracle-dz/UniFAR-FTUs huggingface dataset:
Bottom up approach to manage data privacy policy through the front end filter paradigm

An increasing number of business services for private companies and citizens are accomplished trough the web and mobile devices. Such a scenario is characterized by high dynamism and untrustworthiness, as a large number of applications exchange different kinds of data. This poses an urgent need for effective means in preserving data privacy. This paper proposes an approach, inspired to the front-end trust filter paradigm, to manage data privacy in a very flexible way. Preliminary experimentation suggests that the solution could be a promising path to follow for web-based transactions which will be very widespread in the next future.
Animal Models and “Omics” Technologies for Identification of Novel Biomarkers and Drug Targets to Prevent Heart Failure

It is now accepted that heart failure (HF) is a complex multifunctional disease rather than simply a hemodynamic dysfunction. Despite its complexity, stressed cardiomyocytes often follow conserved patterns of structural remodelling in order to adapt, survive, and regenerate. When cardiac adaptations cannot cope with mechanical, ischemic, and metabolic loads efficiently or become chronically activated, as, for example, after infection, then the ongoing structural remodelling and dedifferentiation often lead to compromised pump function and patient death. It is, therefore, of major importance to understand key events in the progression from a compensatory left ventricular (LV) systolic dysfunction to a decompensatory LV systolic dysfunction and HF. To achieve this, various animal models in combination with an “omics” toolbox can be used. These approaches will ultimately lead to the identification of an arsenal of biomarkers and therapeutic targets which have the potential to shape the medicine of the future.
Designing Adaptive Robotic Services

Our research group is designing robotic products and services that will adapt to people’s changing behavior through repeated interactions. Through the process of creating these products and services, we have found that there are many dynamic issues to account for in the design: the behavior of customers, the capabilities of the robot, and what the robot knows about people and their preferences. Current service design blueprints are not sufficient for capturing these dynamic relationships among elements of the service. Therefore, we explored the activity of designing a dynamic robot-assisted snacking service. Based on the results of a contextual inquiry, we created a service design blueprint which incorporated three main components: a delivery robot, a website, and human assistants. Using this blueprint, we mapped out how the snacking service will evolve over time. Our contribution is an addition to the service blueprint process, which can represent services that change over time.
Maternal mental state language is associated with trajectories of Chinese immigrant children’s emotion situation knowledge

We investigated the role of mothers’ references to mental states and behaviors and children’s emotion situation knowledge (ESK) in a prospective, cross-cultural context. European American mothers (n = 71) and Chinese immigrant mothers (n = 60) and their children participated in the study. Maternal references to mental states and behaviors were assessed at Time 1 when children were three years of age. ESK was assessed when children were 3, 3.5, and 4.5 years of age. Multi-group latent growth curve analyses were used to model children’s growth in ESK over time, as well as relations between mental state language and references to behaviors on children’s trajectories. Results indicated that maternal references to mental states were associated with concurrent levels of ESK for European American children, and change over time for the Chinese immigrant children. Maternal references to behaviors were negatively associated with concurrent ESK for both groups.
Directions for research and training in plant omics: Big Questions and Big Data

Abstract A key remit of the NSF‐funded “Arabidopsis Research and Training for the 21st Century” (ART‐21) Research Coordination Network has been to convene a series of workshops with community members to explore issues concerning research and training in plant biology, including the role that research using Arabidopsis thaliana can play in addressing those issues. A first workshop focused on training needs for bioinformatic and computational approaches in plant biology was held in 2016, and recommendations from that workshop have been published (Friesner et al., Plant Physiology, 175, 2017, 1499). In this white paper, we provide a summary of the discussions and insights arising from the second ART‐21 workshop. The second workshop focused on experimental aspects of omics data acquisition and analysis and involved a broad spectrum of participants from academics and industry, ranging from graduate students through post‐doctorates, early career and established investigators. Our hope is that this article will inspire beginning and established scientists, corporations, and funding agencies to pursue directions in research and training identified by this workshop, capitalizing on the reference species Arabidopsis thaliana and other valuable plant systems.
Animal Health Challenges and Veterinary Aspects of Organic Livestock Farming Identified Through a 3 Year EU Network Project

From 2003-2006, an EU network project 'Sustaining Animal Health and Food Safety in Organic Farming' (SAFO), was carried out with 26 partners from 20 EU-countries and 4 related partners from 4 candidate or new member states. The focus was the integration of animal health and welfare issues in organic farming with food safety aspects. Four very consistent conclusions became apparent: 1) The climatic, physical and socio-economic conditions vary considerably throughout Europe, leading to different livestock farming systems. This limits the possibility for technology transfer be- tween regions, and creates several challenges for a harmonised regulation, 2) Implementing organic standards at farm level does not always ensure that animal health and welfare reach the high ideals of the organic principles, 3) To over- come these deficiencies, organic farmers and farmer organisations need to take ownership of organic values and, 4) In all participating countries, a strong need for training of farmers and in particular veterinarians in animal health promotion and organic principles was identified. The article presents a summary of papers presented at the five SAFO workshops.
Aprataxin Tumor Levels Predict Response of Colorectal Cancer Patients to Irinotecan-based Treatment

Purpose: Irinotecan (CPT11) treatment significantly improves the survival of colorectal cancer patients and is routinely used for the treatment of these patients, alone or in combination with other agents. However, only 20% to 30% of patients show an objective response to irinotecan, and there is great need for new molecular markers capable of identifying the subset of patients who are unlikely to respond. Experimental Design: Here we used microarray analysis of a panel of 30 colorectal cancer cell lines and immunohistochemistry to identify and validate a new biomarker of response to irinotecan. Results: A good correlation was observed between irinotecan sensitivity and the expression of aprataxin (APTX), a histidine triad domain superfamily protein involved in DNA repair. Moreover, using an isogenic in vitro system deficient in APTX, we show that aprataxin directly regulates the cellular sensitivity to camptothecin, suggesting that it could be used to predict patient response to irinotecan. We constructed a tissue microarray containing duplicate tumor samples from 135 patients that received irinotecan for the treatment of advanced colorectal cancer. Immunohistochemical assessment of the tumor levels of aprataxin showed a significant association with treatment response and patient survival. Patients with low aprataxin had longer progression-free (9.2 versus 5.5 months; P = 0.03) and overall survival (36.7 versus 19.0 months; P = 0.008) than patients with high tumor aprataxin. No associations were found between coding APTX variants and aprataxin levels or camptothecin sensitivity. Conclusions: These results show that aprataxin tumor levels can be used to identify patients with low probability of response to irinotecan-based therapy who are ideal candidates to receive treatment with alternative agents in an attempt to improve patient survival. Clin Cancer Res; 16(8); 2375–82. ©2010 AACR.
Efficient HEX-Program Evaluation Based on Unfounded Sets

HEX-programs extend logic programs under the answer set semantics with external computations through external atoms. As reasoning from ground Horn programs with nonmonotonic external atoms of polynomial complexity is already on the second level of the polynomial hierarchy, minimality checking of answer set candidates needs special attention. To this end, we present an approach based on unfounded sets as a generalization of related techniques for ASP programs. The unfounded set detection is expressed as a propositional SAT problem, for which we provide two different encodings and optimizations to them. We then integrate our approach into a previously developed evaluation framework for HEX-programs, which is enriched by additional learning techniques that aim at avoiding the reconstruction of the same or related unfounded sets. Furthermore, we provide a syntactic criterion that allows one to skip the minimality check in many cases. An experimental evaluation shows that the new approach significantly decreases runtime.
A middleware-based approach to supporting trust-based service selection

Trust plays an important role in decision making especially in cases of uncertainty and incomplete information. There are many challenges to trust calculation. In this paper, we identify the challenges and offer a middleware solution. Our solution consists of a SCOUT middleware and a SCOUT client (Trust Calculator) that can be used by an application to facilitate trust calculation. As validation, a scenario is implemented. The scenario consists of service selection based on trust calculated by our proposed solution.
WebCORE : A Web application for Collaborative Ontology Reuse and Evaluation

In this work we present WebCORE: a Web application for collaborative ontology reuse and evaluation. The system receives an informal description of a specific semantic domain and determines which ontologies from a repository are the most appropriate to describe the given domain. For this task, the environment is divided into three modules. The first component receives the problem description as a set of terms, and allows the user to refine and enlarge it using WordNet. The second module applies multiple automatic criteria to evaluate the ontologies of the repository, and determines which ones fit best the problem description. A ranked list of ontologies is returned for each criterion, and the lists are combined by means of rank fusion techniques. Finally, the third component uses manual user evaluations in order to incorporate a human, collaborative assessment of the ontologies. The new version of the system incorporates several novelties, such as its implementation as a web application; the incorporation of a NLP module to manage the problem definitions; modifications on the automatic ontology retrieval strategies; and a collaborative framework to find potential relevant terms according to previous user queries. Finally, we present some early experiments on ontology retrieval and evaluation, showing the benefits of our system.
Determination of Broadening Functions using the Singular Value Decomposition (SVD) Technique

Cross-correlation function (CCF) has become the standard tool for extraction of radial-velocity and broadening information from high resolution spectra. It permits integration of information which is common to many spectral lines into one function which is easy to calculate, visualize and interpret. However, CCF is not the best tool for many applications where it should be replaced by the proper broadening function (BF). Typical applications requiring use of the BF’s rather than CCF’s involve finding locations of star spots, studies of projected shapes of highly distorted stars such as contact binaries (as no assumptions can be made about BF symmetry or even continuity) and [Fe/H] metallicity determinations (good baselines and avoidance of negative lobes are essential). It is stressed that the CCF’s are not broadening functions. The note concentrates on the advantages of determining the BF’s through the process of linear inversion, preferably accomplished using the Singular Value Decomposition (SVD). Some basic examples of numerical operations are given in the IDL programming language. 1. Convolution and cross-correlation Convolution is an operation that the nature does for us. We seldom see “naked” functions. These could be a convolution of a spectrum with the spectrograph’s instrumental profile or with the radial component of the micro-turbulence velocity field in the stellar atmosphere or with a broadening function due to rapid rotation of a star. Thus, instead of a function f(u), we observe a function h(x) which is a convolution with some other broadening function (BF), g(x):
Policyholder Exercise Behavior in Life Insurance: The State of Affairs

ABSTRACT The article presents a review of structural models of policyholder behavior in life insurance. We first discuss underlying drivers of policyholder behavior in theory and survey the implications of different models. We then turn to empirical behavior and appraise how well different drivers explain observations. The key contributions lie in the synthesis and the systematic categorization of different approaches. The article should provide a foundation for future studies, and we describe some important directions for future research in the conclusion.
A Study on Natural Interaction for Human Body Motion Using Depth Image Data

This paper explains a study on natural interaction (NI) in human body motion using depth image data. It involves about overview of NI and depth image data. Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. Furthermore, interaction with computer or machine can be more realistic as real world and becoming more important to academic researchers, game industries, and can be adapt to other field like mechanical engineering for robotics movement and surgery purpose in medical area. Functional taxonomies will show step-by-step how human body motion were detected and created a skeleton joint. Also, we discuss about technologies behind Kinect for Xbox 360 (Kinect). Recent research in this area also included.
Efficient Saliency-Model-Guided Visual Co-Saliency Detection

This letter proposes a novel framework to detect common salient objects in a group of images automatically and efficiently. Different from most existing co-saliency models which directly redesign algorithms for multiple images, the saliency model for a single image is fully exploited under the proposed framework to guide the co-saliency detection. Given single image saliency maps, a two-stage guided detection pipeline led by queries is proposed to obtain the guided saliency maps of the image set through a ranking scheme. Then the guided saliency maps generated by different queries are fused in a way that takes advantages of both averaging and multiplication. The proposed model makes existing saliency models work well in co-saliency scenarios. Experimental results on two benchmark databases demonstrate that the proposed framework outperforms the state-of-the-art models in terms of both accuracy and efficiency.
Cyclic Storage for Fault-Tolerant Distributed Executions

Given a set V of active components in charge of a distributed execution, a storage scheme is a sequence B0, B1,. , Bb-1 of subsets of V, where successive global states are recorded. The subsets, also called blocks, have the same size and are scheduled according to some fixed and cyclic calendar of b steps. During the ith step, block Bi is selected. Each component takes a copy of its local state and sends it to one of the components in Bi, in such a way that each component stores (approximately) the same number of local states. Afterward, if a component of Bi crashes, all of its stored data is lost and the computation cannot continue. If there exists a block with no failed components in it, then a recent global state can be retrieved and the computation does not need to start over from the very beginning. The goal is to design storage schemes that tolerate as many crashes as possible, while trying to have each component participating in as few blocks as possible and, at the same time, working with large blocks (so that a component in a block stores a small number of local states). In this paper, several such schemes are described and compared in terms of these measures
Approximating L2‐invariants and the Atiyah conjecture

Let G be a torsion‐free discrete group, and let ℚ denote the field of algebraic numbers in ℂ. We prove that ℚG fulfills the Atiyah conjecture if G lies in a certain class of groups D, which contains in particular all groups that are residually torsion‐free elementary amenable or are residually free. This result implies that there are no nontrivial zero divisors in ℂG. The statement relies on new approximation results for L2‐Betti numbers over ℚG, which are the core of the work done in this paper. Another set of results in the paper is concerned with certain number‐theoretic properties of eigenvalues for the combinatorial Laplacian on L2‐cochains on any normal covering space of a finite CW complex. We establish the absence of eigenvalues that are transcendental numbers whenever the covering transformation group is either amenable or in the Linnell class 𝒞. We also establish the absence of eigenvalues that are Liouville transcendental numbers whenever the covering transformation group is either residually finite or more generally in a certain large bootstrap class 𝒢. © 2003 Wiley Periodicals, Inc.
Active malware analysis using stochastic games

Cyber security is increasingly important for defending computer systems from loss of privacy or unauthorised use. One important aspect is threat analysis --- how does an attacker infiltrate a system and what do they want once they are inside. This paper considers the problem of Active Malware Analysis, where we learn about the human or software intruder by actively interacting with it with the goal of learning about its behaviours and intentions, whilst at the same time that intruder may be trying to avoid detection or showing those behaviours and intentions. This game-theoretic active learning is then used to obtain a behavioural clustering of malware, an important contribution for both understanding malware at a high level and more crucially, for the deployment of effective anti-malware defences. This paper makes the following contributions: (i) A formal definition of the game-theoretic active malware analysis problem; (ii) A fast algorithm for learning about a malware in the active analysis problem which utilises the concept of reducing entropy in the beliefs about the malware; (iii) A virtual machine based agent architecture for the implementation of the active malware analysis problem and (iv) A behaviour based clustering of malware behaviour which is shown to be more accurate than a similar clustering using only passive information about the malware.
Prevalence, determinants, and effect on quality of life of freezing of gait in Parkinson disease.

IMPORTANCE Freezing of gait (FOG) is a common axial symptom of Parkinson disease (PD). OBJECTIVE To determine the prevalence of FOG in a large group of PD patients, assess its relationship with quality of life and clinical and pharmacological factors, and explore its changes from the off to on conditions in patients with motor fluctuations. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional survey of 683 patients with idiopathic PD. Scores for FOG were missing in 11 patients who were not included in the analysis. Patients were recruited from referral centers and general neurology clinics in public or private institutions in France. EXPOSURE Patients with FOG were identified as those with a score of 1 or greater on item 14 of the Unified Parkinson's Disease Rating Scale (UPDRS) in the on condition. Item 14 scores for FOG in the off condition were also collected in patients with fluctuating motor symptoms. MAIN OUTCOMES AND MEASURES Quality of life (measured by the 39-item Parkinson's Disease Questionnaire and 36-Item Short Form Health Survey), anxiety and depression (Hospital Anxiety and Depression Scale), clinical features (UPDRS), and drug consumption. RESULTS Of 672 PD patients, 257 reported FOG during the onstate (38.2%), which was significantly related to lower quality of life scores (P < .01). Freezing of gait was also correlated with longer PD duration (odds ratio, 1.92 [95% CI, 1.28-2.86]), higher UPDRS parts II and III scores (4.67 [3.21-6.78]), the presence of apathy (UPDRS item 4) (1.94 [1.33-2.82]), a higher levodopa equivalent daily dose (1.63 [1.09-2.43]), and more frequent exposure to antimuscarinics (3.07 [1.35-6.97]) (logistic regression). The FOG score improved from the off to on states in 148 of 174 patients with motor fluctuations (85.1%) and showed no change in 13.8%. The FOG score improved by more than 50% in 43.7% of patients. Greater improvement in the on state was observed in younger patients (r = -0.25; P < .01) with lower UPDRS II and III scores (r = -0.50; P < .01) and no antimuscarinic use (r = -0.21; P < .01). CONCLUSIONS AND RELEVANCE Freezing of gait in PD patients correlates with poor quality of life, disease severity, apathy, and exposure to antimuscarinics. Dopaminergic therapy improved FOG in most patients with motor fluctuations, especially younger ones with less severe disease and no antimuscarinic use. This finding suggests that quality of life is impaired in PD patients with FOG and that optimizing dopaminergic therapy and avoiding antimuscarinics should be considered.
A Primer on Molecular Similarity in QSAR and Virtual Screening Part III – Connecting descriptors and experimental measurements – model generation

The generation of models relating structure and some form of measurement of structural properties, be it bioactivity or any physicochemical property, consists of the description of the problem, the choice of a dataset of experimental endpoints, and the construction of the actual mathematical model. The descriptor generation was discussed in the first part of this primer, with the conclusion to choose descriptors relevant to the problem and of not overly complex nature. In the second part we were discussing experimental endpoints that can be used as “output variables” of models. Here the conclusion was that also experimental data are not without fault – data measured in a single laboratory may show significant differences (e.g. in high-throughput screenings), and combining results from different labs might be even more error-prone. Therefore, a clean dataset, measured by a single, well-defined experimental procedure should be used in the ideal case. In the current, concluding part of the primer I would like to discuss the basics of constructing a useful mathematical model that connects molecular descriptors as an independent variable, and outputs (predicted) properties as the dependent variable. The focus of this part of the primer will be on two steps commonly performed in the generation of QSAR/QSPR models, namely feature selection and model validation.