Miracle-dz/UniFAR-FTUs huggingface dataset:
Using context for supporting users efficiently

A good software is a software that is invisible for the user. This is possible by making context explicit in the software. The increasingly interest for the notion of context appears through the number of approaches based on it. Initially, context was mainly considered in engineering and cognitive science. Now even in engineering, one sees two sub-approaches considering context at the level of the knowledge or the data, namely context-based and context-aware systems. For context-based systems, most of the non formal approaches focus, in one way or another, on context in relationships with the user, aiming at a good computer system that is invisible for the user. Context-aware systems are concerned indirectly with users through a modeling of their dynamic environment. In this paper, we present, first, different viewpoints on context related to human-machine interaction. We then consider why we need to focus on users through two aspects, on the one hand, on planning and plan execution, and, on the other hand, procedures and practice. The lesson learned is that an improvement of user's support needs a consideration of context.
Robust and Hierarchical Stop Discovery in Sparse and Diverse Trajectories

The advance of GPS tracking technique brings a large amount of trajectory data. To better understand such mobility data, semantic models like “stop/move” (or inferring “activity”, “transportation mode”) recently become a hot topic for trajectory data analysis. Stops are important parts of tra- jectories, such as “working at office”, “shopping in a mall”, “waiting for the bus”. There are several methods such as velocity, clustering, density algorithms being designed to discover stops. However, existing works focus on well-defined trajectories like movement of vehicle and taxi, not working well for heterogeneous cases like diverse and sparse trajectories. On the contrary, our paper addresses three main challenges: (1) provide a robust clustering-based method to discover stops; (2) discover both shared stops and personalized stops, where shared stops are the common places where many trajectories pass and stay for a while (e.g. shopping mall), whilst personalized stops are individual places where user stays for his/her own purpose (e.g. home, office); (3) further build stop hierarchy (e.g. a big stop like EPFL campus and a small stop like an office building). We evaluate our approach with several diverse and spare real-life GPS data, compare it with other methods, and show its better data abstraction on trajectory.
Delay in Breast Cancer: Implications for Stage at Diagnosis and Survival

Breast cancer continues to be a disease with tremendous public health significance. Primary prevention of breast cancer is still not available, so efforts to promote early detection continue to be the major focus in fighting breast cancer. Since early detection is associated with decreased mortality, one would think that it is important to minimize delays in detection and diagnosis. There are two major types of delay. Patient delay is delay in seeking medical attention after self-discovering a potential breast cancer symptom. System delay is delay within the health care system in getting appointments, scheduling diagnostic tests, receiving a definitive diagnosis, and initiating therapy. Earlier studies of the consequences of delay on prognosis tended to show that increased delay is associated with more advanced stage cancers at diagnosis, thus resulting in poorer chances for survival. More recent studies have had mixed results, with some studies showing increased survival with longer delays. One hypothesis is that diagnostic difficulties could perhaps account for this survival paradox. A rapidly growing lump may suggest cancer to both doctors and patients, while a slow growing lump or other symptoms could be less obvious to them. If this is the case, then the shorter delays would be seen with the more aggressive tumors for which the prognosis is worse leading to reduced survival. It seems logical that a tumor that is more advanced at diagnosis would lead to shorter survival but the several counter-intuitive studies in this review show that it is dangerous to make assumptions.
Independent maturation of the GABAB receptor subunits GABAB1 and GABAB2 during postnatal development in rodent brain

GABAB receptors mediate slow inhibitory GABAergic neurotransmission. They are encoded by two distinct subunits, GABAB1 (GBR1) and GABAB2 (GBR2), with two major isoforms of GBR1, GBR1a and GBR1b, arising from differential promoter usage. Heterodimerization of GBR1 and GBR2 is essential for GABAB receptor function, as shown in recombinant expression systems and in GBR1−/− mice. GABAB receptors are highly expressed during ontogeny, prior to synaptogenesis, but their developmental function remains elusive. Here we investigated the postnatal development of GABAB receptors in rodent brain, focusing on potential differences in the spatial and temporal expression pattern of GBR1 and GBR2. Immunohistochemistry with subunit‐specific antibodies revealed a widespread staining for GBR1a and GBR2 in neonatal rodent brain. During the first 2 weeks, these two subunits exhibited largely overlapping regional distribution, but with profound distinctions in cellular and subcellular localization. The adult‐like pattern was established during the third week, with a prominent up‐regulation of GBR1b, extensively codistributed with GBR2. Several unexpected features were noted at early stages, notably, a selective GBR2 staining of axonal tracts, such as the corticothalamic projection, and a prominent GBR1 expression in astrocytes. The specificity of the antibody labeling was verified in GBR1‐ and GBR2‐knockout mice. In addition, the analysis of these mutants revealed a partial preservation of GBR2 staining in GBR1−/− mice and vice versa. Altogether, the results suggest a functional role for GBR1 and GBR2 proteins in immature brain in addition to their contribution to dimeric GABAB receptor complexes. J. Comp. Neurol. 477:235–252, 2004. © 2004 Wiley‐Liss, Inc.
A functional consideration of anatomical connections between the basal ganglia and the thalamus suggests that antipsychotic drugs inhibit the initiation of movement

of the original article: Ncurolcptic drugs disrupt the learning and performance of operant habits motivated by a variety of positive reinforcers, including food, water, brain stimulation, intravenous opiates, stimulants, and barbiturates. This disruption has been demonstrated in several kinds of experiments with doses that do not significantly limit normal response capacity. With continuous reinforcement neuroleptics gradually cause responding to cease, as in extinction or satiation. This pattern is not due to satiation, however, because it also occurs with nonsatiating reinforcement (such as saccharin or brain stimulation). Repeated tests with neuroleptics result in earlier and earlier response cessation reminiscent of the kind of decreased resistance to extinction caused by repeated tests without the expected reward. Indeed, withholding reward can have the same effect on responding under later neuroleptic treatment as prior experience with neuroleptics themselves, this suggests that there is a transfer of learning (really unlearning) from nonreward to neuroleptic conditions. These tests under continuous reinforcement schedules suggest that neuroleptics blunt the ability of reinforcers to sustain responding at doses which largely spare the ability of the animal to initiate responding. Animals trained under partial reinforcement, however, do not respond as well during neuroleptic testing as animals trained under continuous reinforcement. Thus, neuroleptics can also impair responding (though not response capacity) that is normally sustained by environmental stimuli (and associated expectancies) in the absence of the primary reinforcer. Ncuroleptics also blunt the euphoric impact of amphetamine in humans. These data suggest that the most subtle and interesting effect of neuroleptics is a selective attenuation of motivational arousal which is: (a) critical for goal-directed behavior, (b) normally induced by reinforcers and associated environmental stimuli, and (c) normally accompanied by the subjective experience of pleasure. Because these drugs are used to treat schizophrenia and because they cause parkinsonian-like side effects, this action has implications for a better understanding of human pathology as well as normal motivational processes. A functional consideration of anatomical connections between the basal ganglia and the thalamus suggests that antipsychotic drugs inhibit the initiation of movement
Transforming growth factor β: A potential biomarker and therapeutic target of ventricular remodeling

Transforming growth factor β (TGF-β) is a multifunctional cytokine that is synthesized by many types of cells and regulates the cell cycle. Increasing evidence has led to TGF-β receiving increased and deserved attention in recent years because it may play a potentially novel and critical role in the development and progression of myocardial fibrosis and the subsequent progress of ventricular remodeling (VR). Numerous studies have highlighted a crucial role of TGF-β in VR and suggest potential therapeutic targets of the TGF-β signaling pathways for VR. Changes in TGF-β activity may elicit anti-VR activity and may serve as a novel therapeutic target for VR therapy. This review we discusses the smad-dependent signaling pathway, such as TGF-β/Smads, TGF-β/Sirtuins, TGF-β/BMP, TGF-β/miRNAs, TGF-β/MAPK, and Smad-independent signaling pathway of TGF-β, such as TGF-β/PI3K/Akt, TGF-β/Rho/ROCK,TGF-β/Wnt/β-catenin in the cardiac fibrosis and subsequent progression of VR. Furthermore, agonists and antagonists of TGF-β as potential therapeutic targets in VR are also described.
Contextual representations for enterprise model application (C.R.E.M.A.)

Enterprise models help to make enterprise processes and services more transparent while also improving stockholders' abilities to analyze, optimize and control them. These models include every relevant element as well as enterprise processes, including their relationships with one another. the growing complexity of these models reduces their usability as well as user friendliness. the different stakeholders have different expectations towards the visualization and the relevant information being displayed to them. Therefore contextual representations of enterprise models allow the provision of the relevant information in a user oriented perspective by applying different visualization methods. This helps to manage the complexity and facilitates a sustainable application of enterprise models for various enterprise aspects such as quality management, strategic planning, reporting and operational control.
Unsupervised Structure Detection in Biomedical Data

A major challenge in computational biology is to find simple representations of high-dimensional data that best reveal the underlying structure. In this work, we present an intuitive and easy-to-implement method based on ranked neighborhood comparisons that detects structure in unsupervised data. The method is based on ordering objects in terms of similarity and on the mutual overlap of nearest neighbors. This basic framework was originally introduced in the field of social network analysis to detect actor communities. We demonstrate that the same ideas can successfully be applied to biomedical data sets in order to reveal complex underlying structure. The algorithm is very efficient and works on distance data directly without requiring a vectorial embedding of data. Comprehensive experiments demonstrate the validity of this approach. Comparisons with state-of-the-art clustering methods show that the presented method outperforms hierarchical methods as well as density based clustering methods and model-based clustering. A further advantage of the method is that it simultaneously provides a visualization of the data. Especially in biomedical applications, the visualization of data can be used as a first pre-processing step when analyzing real world data sets to get an intuition of the underlying data structure. We apply this model to synthetic data as well as to various biomedical data sets which demonstrate the high quality and usefulness of the inferred structure.
Managing Highly Complex Product Families with Multi-Level Feature Trees

Feature trees are a well-established instrument for domain analysis and modeling. But for highly complex product families like a vehicle manufacturer's product range comprising well-above a thousand technical features - they become very large, and thus cumbersome and inflexible, especially when managing changes to the tree's structure over a long time. Furthermore, a conflict of aims arises when using feature trees in large organizations: while a single global feature tree for the entire company is desirable, local amendments for individual units or projects are indispensable in practice. In this paper, we present a detailed description of this problem and show its great relevance to the automotive domain. We then provide a detailed definition of multi-level feature trees as a possible solution to the above problem. Finally, we describe scenarios how such multi-level feature trees can be put into practice and introduce a prototypical tool implementation of this concept
On the probability of independent sets in random graphs

Let k be the asymptotic value of the independence number of the random graph G(n, p). We prove that if the edge probability p(n) satisfies p(n) ≫ n−2/5ln6/5n then the probability that G(n, p) does not contain an independent set of size k − c, for some absolute constant c > 0, is at most exp{−cn2/(k4p)}. We also show that the obtained exponent is tight up to logarithmic factors, and apply our result to obtain new bounds on the choice number of random graphs. We also discuss a general setting where our approach can be applied to provide an exponential bound on the probability of certain events in product probability spaces. © 2002 Wiley Periodicals, Inc. Random Struct. Alg. , 22: 1–14, 2003
COmplete GENome Tracking (COGENT): A Flexible Data Environment for Computational Genomics

SUMMARY We present a database of fully sequenced and published genomes to facilitate the re-distribution of data and ensure reproducibility of results in the field of computational genomics. For its design we have implemented an extremely simple yet powerful schema to allow linking of genome sequence data to other resources. AVAILABILITY http://maine.ebi. ac.uk:8000/services/cogent/
Predicting treatment drop-out in sex offenders

This study identifies risk factors associated with recidivism for sexual offences against children to determine the efficacy in using such variables in analysing drop-out in a sample of 96 sex offenders who had attended a community treatment programme in the West Midlands area. The study considered 30 risk factors; 12 concerned with current offences and criminal history, 9 looking at the current situation and background history and 9 addressing current psychological problems and the treatment process. The study found that 60 offenders were observed to stay in treatment and thirty six offenders dropped out. Overall, nine risk factors were found to have a positive association with treatment drop-out. The nine significant risk factors, when considered together, were shown to distinguish those offenders who stayed in treatment from those who dropped out with a 78% accuracy. These findings were used to develop a weighted risk factor checklist. It was observed that those offenders who dropped out of treatment scored significantly higher on this “resistance to treatment” scale. The implications for practice work with sex offenders are discussed. Copyright © 1998 John Wiley & Sons, Ltd.
Interval Tracker: Tracking by Interval Analysis

This paper proposes a robust tracking method that uses interval analysis. Any single posterior model necessarily includes a modeling uncertainty (error), and thus, the posterior should be represented as an interval of probability. Then, the objective of visual tracking becomes to find the best state that maximizes the posterior and minimizes its interval simultaneously. By minimizing the interval of the posterior, our method can reduce the modeling uncertainty in the posterior. In this paper, the aforementioned objective is achieved by using the M4 estimation, which combines the Maximum a Posterior (MAP) estimation with Minimum Mean-Square Error (MMSE), Maximum Likelihood (ML), and Minimum Interval Length (MIL) estimations. In the M4 estimation, our method maximizes the posterior over the state obtained by the MMSE estimation. The method also minimizes interval of the posterior by reducing the gap between the lower and upper bounds of the posterior. The gap is reduced when the likelihood is maximized by the ML estimation and the interval length of the state is minimized by the MIL estimation. The experimental results demonstrate that M4 estimation can be easily integrated into conventional tracking methods and can greatly enhance their tracking accuracy. In several challenging datasets, our method outperforms state-of-the-art tracking methods.
Information perception, wishes, and satisfaction in ambulatory cancer patients under active treatment: patient-reported outcomes with QLQ-INFO25

Background Information is vital to cancer patients. Physician–patient communication in oncology presents specific challenges. The aim of this study was to evaluate self-reported information of cancer patients in ambulatory care at a comprehensive cancer centre and examine its possible association with patients’ demographic and clinical characteristics. Patients and methods This study included adult patients with solid tumours undergoing chemotherapy at the Institute Jules Bordet’s Day Hospital over a ten-day period. EORTC QLQ-C30 and QLQ-INFO25 questionnaires were administered. Demographic and clinical data were collected. Descriptive and inferential statistics were used. Results 101 (99%) fully completed the questionnaires. They were mostly Belgian (74.3%), female (78.2%), with a mean age of 56.9 ± 12.8 years. The most frequent tumour was breast cancer (58.4%). Patients were well-informed about the disease and treatments, but presented unmet information domains. The Jules Bordet patients desired more information on treatment side effects, long-term outcome, nutrition, and recurrence symptoms. Patients on clinical trials reported having received less information about their disease and less written information than patients outside clinical trials. Higher information levels were associated with higher quality of life (QoL) scores and higher patient satisfaction. Conclusion Patients were satisfied with the information they received and this correlated with higher QoL, but they still expressed unmet information wishes. Additional studies are required to investigate the quality of the information received by patients enrolled in clinical trials.
Reversibility of lipoatrophy in HIV-infected patients 2 years after switching from a thymidine analogue to abacavir: the MITOX Extension Study

Objective: To determine if long-term improvement in HIV lipoatrophy can be attained by substitution of thymidine analogues zidovudine (ZDV) or stavudine (d4T) with abacavir (ABC). Design: Long-term follow-up (104 weeks) of a randomized, open-label study. Setting: Seventeen ambulatory HIV clinics in Australia and London. Subjects: Patients with HIV lipodystrophy were randomized to switch from a thymidine analogue to ABC, while continuing all other antiretroviral therapy (ABC arm) (n = 42) or continue current therapy (ZDV/d4T arm) (n = 43). Intervention: At week 24, all control patients could switch to ABC. Of the original 111 patients randomized, 85 had long-term follow-up data, with 77 having imaging data available at 104 weeks. Main outcome measure: The primary endpoint was time-weighted change in limb fat mass, measured by dual-energy X-ray absorptiometry (DEXA). Results: At week 104, the mean increase in limb fat for the ABC and ZDV/d4T group was 1.26 ± 2.02 kg and 0.49 ± 1.38 kg, respectively. The time-weighted change for limb fat was significantly different between the two arms (0.43 kg; P = 0.008). On-treatment analysis demonstrated a trend for increased limb fat in patients in the ABC arm. Visceral fat accumulation, buffalo hump, self-assessed lipodystrophy or the lipodystrophy case definition score (LCDS) did not improve. Conclusions: In patients with moderate-to-severe lipodystrophy, significant improvements in subcutaneous fat continued over 104 weeks after switching from a thymidine analogue to ABC. Nevertheless, the lipodystrophy syndrome was still evident, indicating additional strategies need evaluating.
Paradoxical Facilitation of a Free Recall of Nonwords in Persons with Traumatic Brain Injury

Brain damage is usually associated with behavioral deficits. However, there is an increasing amount of evidence that lesions of some brain regions are associated with improvements instead of impairments of certain behaviors. We report the results of a study of free recall performance in subjects with traumatic brain injury. One-fourth of the subjects displayed above-normal performance in recall of nonwords. No such facilitation was found with nine lists of words.
Optimized low-power synchronizer design for the IEEE 802.11a standard

The authors propose a low-power synchronizer design for the IEEE 802.11a standard capable to estimate frequency offsets in the range /spl plusmn/468 kHz (80 ppm @ 5.8 GHz) with very simple and effective frame detection and timing synchronization. The core area of the design after layout is 13 mm/sup 2/, including the CORDIC and FFT processors, with a total estimated power consumption of 140 mW.
Enterohemorrhagic E. coli (EHEC) pathogenesis

Enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7 is a human pathogen responsible for outbreaks of bloody diarrhea and hemolytic uremic syndrome (HUS) worldwide. Conventional antimicrobials trigger an SOS response in EHEC that promotes the release of the potent Shiga toxin that is responsible for much of the morbidity and mortality associated with EHEC infection. Cattle are a natural reservoir of EHEC, and approximately 75% of EHEC outbreaks are linked to the consumption of contaminated bovine-derived products. This review will discuss how EHEC causes disease in humans but is asymptomatic in adult ruminants. It will also analyze factors utilized by EHEC as it travels through the bovine gastrointestinal (GI) tract that allow for its survival through the acidic environment of the distal stomachs, and for its ultimate colonization in the recto-anal junction (RAJ). Understanding the factors crucial for EHEC survival and colonization in cattle will aid in the development of alternative strategies to prevent EHEC shedding into the environment and consequent human infection.
Incremental Delta-Sigma Modulators for Temperature Sensing Applications

This paper presents a comparison of incremental delta-sigma analog-to-digital converters for integrated temperature sensing applications. The characteristics of bipolar transistor based temperature sensing front-ends place specific requirements on the modulator loop architecture. Single loop delta-sigma architectures that removes the input signal from the internal loop by the addition of a feed-forward path to the quantiser, has been investigated thoroughly. It is found that the noise transfer function (NTF) implemented by the modulator can be optimised for either accuracy or integrator signal excursion, based on the requirements of the target application.