Miracle-dz/UniFAR-FTUs huggingface dataset:
A protocol for multi-agent diagnosis with spatially distributed knowledge

In a large distributed system it is often infeasible or even impossible to perform diagnosis using a single model of the whole system. Instead, several spatially distributed local models of the system have to be used to detect possible faults. Traditional diagnostic tools, however, are not suitable to deal with such a set of spatially distributed local models.A Multi-Agent System of diagnostic agents, where each agent has a model\footnote[Here, we focus on Model-Based Diagnosis. ] of a subsystem, may be proposed as a solution for establishing global diagnoses of large distributed systems. Unfortunately, establishing a global minimal diagnosis is NP-Hard, even if every agent is able to determine local minimal diagnoses in polynomial time. Moreover, communication overhead in establishing a global diagnosis will be high: unless Ρ = ΝΡ a super-polynomial number of messages between the agents will be required for establishing a global diagnosis.In this paper we present a protocol that overcomes this complexity issue by exchanging diagnostic precision for enables agents to determine local minimal diagnoses that are consistent with global diagnoses. Moreover, the protocol ensures that no agent acquires knowledge of global diagnoses. The protocol does not guarantee that a combination of the agents' local minimal diagnoses is also a global minimal diagnosis. However, for every global minimal diagnosis, there is a combination of local minimal diagnoses.
Review Perspectives for Multimodal Neurochemical and Imaging Biomarkers in Alzheimer's Disease

The diagnosis of Alzheimer's disease (AD) is presently going through a paradigm shift from disease categories to dimensions and toward the implementation of biomarkers to support identification of predementia and even preclinical asymptomatic stages of the disease. We outline the methodological basis of presently available biomarkers and technological methodologies in AD, including exploratory and hypothesis-based plasma and blood candidates, cerebrospinal fluid markers of amyloid load and axonal destruction, and imaging markers of amyloid deposition, synaptic dysfunction, cortical functional and structural disconnection, and regional atrophy. We integrate biomarker findings into a comprehensive model of AD pathogenesis from healthy aging to cognitive decline, the resilience to cerebral amyloid load (RECAL) matrix. integrates factors of risk and resilience to cerebral amyloid load for individual risk prediction. We show the clinical consequences when the RECAL matrix is operationalized into a diagnostic algorithm both for individual counseling of subjects and for the identification of at risk samples for primary and secondary preventive trials. We discuss the implication of biomarkers for the identification of prodromal AD for the primary care system that seems presently not even prepared to cope with the increasing number of subjects afflicted with late stage AD dementia, let alone future cohorts of subjects searching counseling or treatment of predementia and asymptomatic stages of AD. The paradigm shift in AD diagnosis and its operationalization into a diagnostic framework will have major implications for our understanding of disease pathogenesis. Now, for the first time, we have access to in vivo markers of key events in AD pathogenesis integrated into a heuristic framework that makes strong predictions on pattern of multimodal biomarkers in different stages of AD. Critical testing of these predictions will help us to modify or even falsify the currently hold assumptions on the pathogenesis of AD based on in vivo evidence in humans.
Recognition of facial expressions and measurement of levels of interest from video

This paper presents a spatio-temporal approach in recognizing six universal facial expressions from visual data and using them to compute levels of interest. The classification approach relies on a two-step strategy on the top of projected facial motion vectors obtained from video sequences of facial expressions. First a linear classification bank was applied on projected optical flow vectors and decisions made by the linear classifiers were coalesced to produce a characteristic signature for each universal facial expression. The signatures thus computed from the training data set were used to train discrete hidden Markov models (HMMs) to learn the underlying model for each facial expression. The performances of the proposed facial expressions recognition were computed using five fold cross-validation on Cohn-Kanade facial expressions database consisting of 488 video sequences that includes 97 subjects. The proposed approach achieved an average recognition rate of 90.9% on Cohn-Kanade facial expressions database. Recognized facial expressions were mapped to levels of interest using the affect space and the intensity of motion around apex frame. Computed level of interest was subjectively analyzed and was found to be consistent with "ground truth" information in most of the cases. To further illustrate the efficacy of the proposed approach, and also to better understand the effects of a number of factors that are detrimental to the facial expression recognition, a number of experiments were conducted. The first empirical analysis was conducted on a database consisting of 108 facial expressions collected from TV broadcasts and labeled by human coders for subsequent analysis. The second experiment (emotion elicitation) was conducted on facial expressions obtained from 21 subjects by showing the subjects six different movies clips chosen in a manner to arouse spontaneous emotional reactions that would produce natural facial expressions.
Physiological Background of the Loss of Fractal Heart Rate Dynamics

Background—Altered fractal heart rate (HR) dynamics occur during various disease states, but the physiological background of abnormal fractal HR behavior is not well known. We tested the hypothesis that the fractal organization of human HR dynamics is determined by the balance between sympathetic and vagal outflow. Methods and Results—A short-term fractal scaling exponent (&agr;1) of HR dynamics, analyzed by the detrended fluctuation analysis (DFA) method, and the high-frequency (HF) and low-frequency (LF) spectral components of R-R intervals (0.15 to 0.4 Hz; n=13), along with muscle sympathetic nervous activity (MSNA) from the peroneus nerve (n=11), were assessed at rest and during cold face and cold hand immersion in healthy subjects. During cold face immersion, HF power increased (from 6.9±1.3 to 7.6±1.2 ln ms2, P<0.01), as did MSNA (from 32±17 to 44±14 bursts/100 heartbeats, P<0.001), and LF/HF ratio decreased (P<0.01). Cold hand immersion resulted in a similar increase in MSNA (from 34±17 to 52±19 bursts/100 heartbeats, P<0.001) but a decrease in HF spectral power (from 7.0±1.3 to 6.5±1.1 ln ms2, P<0.05) and an increase in the LF/HF ratio (P<0.05). The fractal scaling index &agr;1 decreased in all subjects (from 0.85±0.27 to 0.67±0.30, P<0.0001) during cold face immersion but increased during cold hand immersion (from 0.77±0.22 to 0.97±0.20, P<0.01). Conclusions—The fractal organization of human HR dynamics is determined by a delicate interplay between sympathetic and vagal outflow, with the breakdown of fractal HR behavior toward more random dynamics occurring during coactivation of sympathetic and vagal outflow.
G protein β3 subunit C825T polymorphism modifies the presentation of temporal lobe epilepsy

Purpose – Experimental studies suggest a role of G protein‐mediated signaling pathways in epileptogenesis. A genetic variation affecting the G protein subunit Gβ3 denoted the C825T polymorphism has been reported to increase the signaling efficiency through Gi proteins and to modify responses to certain drugs. The C825T polymorphism has also been associated with several diseases including hypertension, diabetes type II, obesity, and major depressive disorder. In this study, we have explored whether the G protein polymorphism C825T is associated with or influences temporal lobe epilepsy (TLE).
Experiments on estimating random mapping

The generic function of a feedforward multilayer perceptron (MLP) network is to map patterns from one space to another. This mapping function, determined by the set of examples used to train the network, may be viewed as a hash function. This paper reports the experiments on using a backpropagation MLP network with a dynamic hidden layer to estimate a random mapping from the input to output space and use this estimated mapping as a hash function for a given population of keys. Comparative studies show that the MLP estimated hash functions performs robustly over various population of scarce hash keys which would cause uneven distributions with some traditional hash function.
Gene targeting at the mouse cytokeratin 10 locus: severe skin fragility and changes of cytokeratin expression in the epidermis

Bullous congenital ichthyosiform erythroderma (BCIE) is a dominantly inherited blistering skin disorder caused by point mutations in the suprabasal cytokeratins 1 or 10. Targeting the murine cytokeratin 10 gene in ES cells resulted in mice with different phenotypes in the homozygotes and heterozygotes; both of which exhibit similarities to specific clinical characteristics of BCIE. Homozygotes suffered from severe skin fragility and died shortly after birth. Heterozygotes were apparently unaffected at birth, but developed hyperkeratosis with age. In both genotypes, aggregation of cytokeratin intermediate filaments, changes in cytokeratin expression, and alterations in the program of epidermal differentiation were observed. In addition we demonstrate, for the first time, the existence of the murine equivalent of human cytokeratin 16.
Programming abstractions for integrating autonomous and reactive behaviors: an agent-oriented approach

The integration of autonomous and reactive behavior is a relevant problem in the context of concurrent programming, related to the integration of thread-based and event-driven programming. From a programming paradigm perspective, the problem can not be easily solved by approaches based on object-oriented concurrent programming or by the actor model, being them natively based on the reactivity principle only. In this paper we tackle the problem with agent-oriented programming, using an agent-oriented programming language called simpAL.
Longevity of Cane Corso Italiano dog breed and its relationship with hair colour

The Cane Corso Italiano belongs among the new dog breeds that were fully recognised by Federation Cynologique Internationale (FCI) in 2007. For the first time, this study describes a median lifespan using the data of 232 dogs of the Cane Corso Italiano breed collected from kennels and individual owners from 25 countries. The median lifespan of the whole examined group is 9.29 years (IQR 6.98-11.12, IQR = Interquartile Range). This paper is the first to describe the possible relationship between median lifespan and hair colour within one breed. The longest living group is formed by black brindle coloured dogs, with a median of 10.30 years (IQR 8.33-13.00), and brindle coloured dogs, with a median of 10.13 years (IQR 7.12-11.25). The median lifespan of black brindle dogs exceeded the overall median lifespan of all dogs by 1.01 year and the median lifespan of other colour dogs by 2.21 years. Our results suggest a possible way for a prolongation of age at death of the Cane Corso Italiano breed using appropriate breeding. The median lifespan of male Cane Corso Italiano dogs is 9.25 years (IQR 6.97-11.00) and female Cane Corso Italiano dogs 9.33 years (IQR 7.00-11.31). The statistical analysis using the Independent Samples Student’s t test confirmed that the lifespan of female dogs did not exceed the median lifespan of male dogs (P>0.01).
Is the Crowd's Wisdom Biased? A Quantitative Analysis of Three Online Communities

Abstract—We present a study of user voting on three websites: Imdb, Amazon and BookCrossings. Here we report on an expert evaluation of the voting mechanisms of each website and a quantitative data analysis of users’ aggregate voting behavior. Our results suggest that the websites with higher barrier to vote introduce a relatively high number of one-off voters, and they appear to attract mostly experts. We also find that one-off voters tend to vote on popular items, while experts mostly vote for obscure, low-rated items. We conclude with design suggestions to address the “wisdom of the crowd” bias.
Glomerular formation in the developing rat olfactory bulb

Using the confocal microscope together with markers for the cellular components of glomeruli, we examined the spatiotemporal cellular interactions that occur between the axons of olfactory receptor cells, their dendritic targets, and glial cells during the critical period of glomerular formation. We have employed markers of immature and mature olfactory receptor cell axons, mitral/tufted cell dendrites, and glial cells as well as a synapse‐associated protein for double‐ and triple‐label immunocytochemistry. Axons of olfactory receptor cells grew into a dense dendritic zone of the olfactory bulb (comprising the dendrites of both mitral and tufted cells) between E17 and E18. At E19, these axons coalesced into protoglomeruli, which continued to develop until birth, when the basic anatomical structure of adult glomeruli emerged. Neither mitral/tufted cell dendrites nor olfactory bulb astrocytes became specifically associated with these protoglomeruli until E21. Ensheathing cells remained restricted to the outer nerve fiber layer and did not appear to contribute to glomerular formation. Finally, the synaptophysin staining has shown that synaptic constituents are expressed as early as E17, prior to the appearance of mature olfactory receptor cell axons. Based on these data, we have established a time line detailing the temporal and spatial interactions that occur between cell types during late embryonic rat olfactory bulb development. We conclude that the initial event in the formation of glomeruli is the penetration of the mitral/tufted cell dendritic zone by olfactory receptor cell axons. The coalescence of dendritic and glial processes into glomerular structures appears secondary to the arrival of the olfactory receptor cell axons. J. Comp. Neurol. 413:289–304, 1999. © 1999 Wiley‐Liss, Inc.
Turkish Ministry of Health, 2nd Turkish Medical General Assembly Clinical Oncology Study Group Report.

OBJECTIVE There is an increase in the incidence of cancer, and consequently in mortality rates, both in the world and in Turkey. The increase in the incidence and mortality rate of cancer are more prominent in our country as well as in other developing countries. The aim of this workshop was to determine the current status on prevention, screening, early diagnosis and treatment of cancer in our country, to identify related shortcomings, specify solutions and to share these with health system operators, and to aid in implementation of these systems. Developments on palliative care were also evaluated. MATERIALS AND METHODS The current situation in the practice of clinical oncology, related drawbacks, problems encountered during multidisciplinary approach and their solutions were discussed under several sub-headings during a 3-day meeting organized by the Turkish Ministry of Health (Türkiye Cumhuriyeti Sağlık Bakanlığı-TCSB) with participation of 16 scientists from Turkey and 6 from abroad, and the conclusions were reported. RESULTS It is expected that the newly established Turkish Health Institutes Association (Türkiye Sağlık Enstitüleri Başkanlığı-TÜSEB) and the National Cancer Institute (Ulusal Kanser Enstitüsü) will provide a new framework in the field of oncology. The current positive findings include the increase in the number of scientists who carry out successful trials in oncology both in Turkey and abroad, the implementation of the national cancer registry program by the Cancer Control Department and the breast cancer registry program by the Turkish Federation of Breast Diseases Societies (Türkiye Meme Hastalıkları Dernekleri Federasyonu-TMHDF), and introduction of Cancer Early Diagnosis, Screening, and Training Centers (Kanser Erken Tanı, Tarama ve Eğitim Merkezi-KETEM) for the application of community-based cancer screening programs. In addition to these, obvious shortcomings related to education, implementation, management and research issues were also determined, and policy and project proposals to address these issues were presented. Collaboration with relevant organizations in the implementation of these studies was supported. CONCLUSION Both the incidence and mortality rates of cancer are increasing in Turkey. The widespread deficiencies in population-based screening and in effective treatment lead to an increase in delay in diagnosis and mortality. Despite improvements in data recording, screening and treatment over the last 10 years, extensive, organized, population-based screening programs and fully equipped early diagnosis and treatment centers are required. Enhancement of basic cancer epidemiologic, translational, genetic and molecular research studies is essential in our country. Improvements on pain treatment and palliative care of patients with chronic and terminal cancer are also required.
Creating Networking Adaptive Interactive Hybrid Systems: A Methodic Approach

Advances in network technologies enable distributed systems, operating in complex physical environments, to co-ordinate their activities over larger areas within shorter time intervals. Some envisioned application domains for such systems are defense, crisis management, traffic management, public safety and security, defense and smart infrastructures. In these systems, humans and intelligent machines will, in close interaction, be able to adapt their behavior under changing conditions and situations to reach their goals. Various architecture models are proposed for such systems from different research areas such as sensor web technology, data fusion, command and control, cognitive systems, multi agent systems, complex adaptive systems and cyber physical systems. However, most of these models only cover part of the system, are too much focused on specific research areas and use different design principles. In this papers the latest developments of a method for designing these Networking Adaptive Interactive Hybrid (human-machine) Systems is presented, paving the way to efficient and effective design and operation.
PIntron: A fast method for gene structure prediction via maximal pairings of a pattern and a text

A challenging issue in designing computational methods for predicting the gene structure into exons and introns from a cluster of transcript (EST, mRNA) sequences, is guaranteeing both accuracy and efficiency in time and space, when large clusters of over than 20,000 ESTs and genes longer than 1Mb are processed. Traditionally, the problem has been faced by combining different tools, not specifically designed for this task. We propose a fast method based on ad hoc procedures for solving the problem. Our method combines two ideas: a novel algorithm of proved small time complexity for computing spliced alignments of a transcript against a genome, and an efficient algorithm that exploits the inherent redundancy of information in a cluster of transcripts to select, among all possible factorizations of EST sequences, those allowing to infer splice site junctions that are largely confirmed by the input data. The EST alignment procedure is based on the construction of maximal embeddings, that are sequences obtained from paths of a graph structure, called embedding graph, whose vertices are the maximal pairings of a genomic sequence T and an EST P. The procedure runs in time linear in the length of P and T and in the size of the output. PIntron, the software tool implementing our methodology, is available at http://www.algolab. eu/PIntron and it is able to process in a few seconds some critical genes that are not manageable by other gene structure prediction tools. At the same time, PIntron exhibits high accuracy (sensitivity and specificity) when compared with ENCODE data.
Regulatory effects of intermittent noxious stimulation on spinal cord injury-sensitive microRNAs and their presumptive targets following spinal cord contusion

Uncontrollable nociceptive stimulation adversely affects recovery in spinally contused rats. Spinal cord injury (SCI) results in altered microRNA (miRNA) expression both at, and distal to the lesion site. We hypothesized that uncontrollable nociception further influences SCI-sensitive miRNAs and associated gene targets, potentially explaining the progression of maladaptive plasticity. Our data validated previously described sensitivity of miRNAs to SCI alone. Moreover, following SCI, intermittent noxious stimulation decreased expression of miR124 in dorsal spinal cord 24 h after stimulation and increased expression of miR129-2 in dorsal, and miR1 in ventral spinal cord at 7 days. We also found that brain-derived neurotrophic factor (BDNF) mRNA expression was significantly down-regulated 1 day after SCI alone, and significantly more so, after SCI followed by tailshock. Insulin-like growth factor-1 (IGF-1) mRNA expression was significantly increased at both 1 and 7 days post-SCI, and significantly more so, 7 days post-SCI with shock. MiR1 expression was positively and significantly correlated with IGF-1, but not BDNF mRNA expression. Further, stepwise linear regression analysis indicated that a significant proportion of the changes in BDNF and IGF-1 mRNA expression were explained by variance in two groups of miRNAs, implying co-regulation. Collectively, these data show that uncontrollable nociception which activates sensorimotor circuits distal to the injury site, influences SCI-miRNAs and target mRNAs within the lesion site. SCI-sensitive miRNAs may well mediate adverse consequences of uncontrolled sensorimotor activation on functional recovery. However, their sensitivity to distal sensory input also implicates these miRNAs as candidate targets for the management of SCI and neuropathic pain.
Does language affect personality perception? A functional approach to testing the Whorfian hypothesis.

Whether language shapes cognition has long been a controversial issue. The present research adopts a functional approach to examining the effects of language use on personality perception and dialectical thinking. We propose that language use activates corresponding cultural mindsets, which in turn influence social perception, thinking, and behavior. Four studies recruited Chinese-English bilinguals (N = 129 in Study 1, 229 in Study 2, 68 in Study 3, 106 in Study 4) and used within-subjects and between-subjects design, written and behavioral reports, and self- and other perceptions. The four studies converged to show that Chinese-English bilinguals exhibit higher dialectical thinking and more variations in self- and observer ratings of personality when using the Chinese language than when using English. Furthermore, dialectical thinking predicted more self- and other-perceived variations in personality and behavior across bilingual contexts. These results highlight the important role of culture in understanding the relations between language and cognition, and attest to the malleability of personality perception and dialectical thinking within and across individuals in response to culture-related linguistic cues.