Miracle-dz/UniFAR-FTUs huggingface dataset:
Constitutional alterations of the ATM gene in early onset sporadic breast cancer

Ataxia-telangiectasia (AT) is a recessive disorder caused by mutations in the ATM gene (ataxia-telangiectasia mutated) located on chromosome 11q22-23 (OMIM 208900). AT is characterised by progressive cerebellar ataxia, oculocutaneous telangiectasia, immunodeficiency, radiosensitivity, and cancer predisposition with a predominance of lymphoid tumours and less frequently other tumours including breast cancer. The 13 kb mRNA of ATM is assembled from 66 exons distributed across a genomic region of 150 kb. It codes for a 350 kDa protein with a C-terminus phosphatidylinositol 3-kinase domain involved in the recognition and repair of radiation induced DNA double strand breaks.1–5 Oncoproteins, including the tumour suppressors p53, BRCA1, and CHK2, are regulated by ATM.6 Epidemiological evidence suggests that ATM heterozygotes, representing 0.5-1% of the general population, have a 5 to 8-fold increased risk of developing breast cancer.7,8 These estimations raised the possibility that germline mutations of ATM may account for ∼5% of all breast cancer cases. Furthermore, since breast cancer reported in obligate carriers among AT family members affects predominantly younger women, an age specific relative risk model has been proposed.9 In this model, up to 8% of breast cancer diagnosed in women under the age of 40 may arise in ATM mutation carriers, compared with 2% of cases diagnosed between 40 and 59 years. However, recent data suggest that this model may overestimate the true allele frequency in women with breast cancer.10–12 Moreover, direct molecular examination of ATM in selected breast cancer patients outside AT families has led to conflicting results. Fitzgerald et al 13 showed that ATM mutations were present in only 2/401 (0.5%) women with early onset breast cancer, but they only looked for truncating mutations. In a recent study, Broeks et al 14 identified seven germline ATM truncating mutations among 82 patients who developed breast …
Threat assessment for general road scenes using monte carlo sampling

A stochastic threat assessment algorithm for general road scenes is presented. Vehicles behave in a manner which includes a desire to follow their intended paths comfortably and to avoid colliding with other objects. In particular, this can be used to detect indirect threats from objects that are not on a direct collision course, but may be forced into a collision course by the traffic situation. An example is when a vehicle has to swerve to avoid an obstacle and because of that the vehicle itself becomes a threat to another vehicle. The vehicles are on a direct collision course from the beginning, but the situation still poses a threat because of the obstacle. Control inputs of other vehicles are modelled as stochastic variables and the resulting statistical expressions are solved using Monte Carlo sampling. In any Monte Carlo method there is always a trade-off between accuracy, i.e., number of samples, and computational load. A further contribution of this work is a method to create denser sample sets without increasing computational load
Filochat: handwritten notes provide access to recorded conversations

We present a novel application which integrates handwriting and recorded audio in a semi-portable device. Based on user interviews, it allows people to straightforwardly access particular points in recorded spontaneous speech via handwritten notes, using temporal indexing. Laboratory studies showed objective benefits of combined notes and audio over notes alone. The utility of the access method was shown by improved performance over current audio technolog y such as dictaphones. We also found perceived benefits of higher quality meeting minutes in field trials. An unforeseen benefit was the use of this device as an audio editing tool. We discuss further technical extensions and user issues in relation to the prototype,
A Practical Liquidity-Sensitive Automated Market Maker

Automated market makers are algorithmic agents that enable participation and information elicitation in electronic markets. They have been widely and successfully applied in artificial-money settings, like some Internet prediction markets. Automated market makers from the literature suffer from two problems that contribute to their impracticality and impair their use beyond artificial-money settings: first, they are unable to adapt to liquidity, so that trades cause prices to move the same amount in both heavily and lightly traded markets, and second, in typical circumstances, they run at a deficit. In this article, we construct a market maker that is both sensitive to liquidity and can run at a profit. Our market maker has bounded loss for any initial level of liquidity and, as the initial level of liquidity approaches zero, worst-case loss approaches zero. For any level of initial liquidity we can establish a boundary in market state space such that, if the market terminates within that boundary, the market maker books a profit regardless of the realized outcome.
The effectiveness of conceptual change texts in reducing pre-service physics teachers’ misconceptions in photoelectric effect

There are many misconceptions on the concept of photoelectric effect so it is important to reduce these misconceptions using conceptual change texts. In this study, the effectiveness of conceptual change texts on reducing pre-service physics teachers’ misconceptions of photoelectric effect will be explained. The conceptual change texts (CCT) are enriched by using animation, simulation video, and data from photoelectric effect experiments in modern physics laboratories. Two texts were tried out on two groups, one experimental group (n=31) and one control group (n=31). Experimental group were given CCT, whereas the control group was give text of modern physics book. Data will be collected by four-tier test and questionnaire. The result of this study will compare two texts in reducing pre-service physics teachers’ misconceptions of photoelectric effect.
[Clinical profile and influences on outcomes in patients hospitalized for acute pericarditis].

Background—The clinical profile with regard to sex and the influences on outcomes in patients who have been hospitalized for acute pericarditis is largely uncharacterized. Methods and Results—We studied all patients aged ≥16 years admitted to the hospital because of acute pericarditis (postpericardiotomy and myocardial infarction associated pericarditis were excluded). Data were collected from a Finnish national registry that included data on all cardiovascular admissions (670 409) during 9.5 years in 29 hospitals nationwide. During the study period, there were 1361 admissions for acute pericarditis. Pericarditis patients were more likely to be male (64.9% of patients) than female (35.1%), with an age-adjusted likelihood ratio of 1.85 (95% confidence interval [CI], 1.65–2.06; P<0.0001) for male sex. The standardized incidence rate of hospitalizations for acute pericarditis was 3.32 per 100 000 person-years. Men 16 to 65 years of age were at higher risk for pericarditis (relative risk, 2.02; 95% CI, 1.81–2.
rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks

Abstract Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element–target gene pairs (E–G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies.
Differential effects of PARP inhibition on vascular cell survival and ACAT-1 expression favouring atherosclerotic plaque stability.

AIMS The aim of this study was to take a combination of animal and cell culture approaches to examine the individual responses of vascular cells to varying inflammatory factors in order to gain insights on the mechanism(s) by which poly(ADP-ribose) polymerase (PARP) inhibition promotes factors of plaque stability. METHODS AND RESULTS Apolipoprotein (ApoE(-/-)) mice fed a high-fat diet were used as a model of atherosclerosis. Primary endothelial cells, smooth muscle cells (SMCs), and ex-vivo generated foam cells (FCs) were used in our in vitro studies. PARP inhibition significantly decreased the markers of oxidative stress and caspase-3 activation and increased smooth muscle actin within plaques from ApoE(-/-) mice fed a high-fat diet. PARP inhibition protected against apoptosis and/or necrosis in SMCs and endothelial cells in response to H(2)O(2) or tumour necrosis factor (TNF). Remarkably, PARP inhibition in FCs resulted in significant sensitization to 7-ketocholesterol (7-KC) by increasing cellular-toxic-free cholesterol, potentially through a down-regulation of acyl-CoA:cholesterol acyltransferase-1 (ACAT-1) expression. 7-KC induced necrosis exclusively in endothelial cells, which was, surprisingly, unaffected by PARP inhibition indicating that PARP inhibition does not prevent all forms of necrotic cell death. In SMCs, PARP-1 inhibition by gene deletion conferred protection against 7-KC or TNF, potentially by reducing caspase-3-like activation, preventing induction of c-Jun N-terminal protein kinase phosphorylation, and inducing extracellular signal-regulated kinase phosphorylation independently of PARP classical enzymatic activity. CONCLUSIONS These data present PARP-1 as an important player in the death of cells constituting atherosclerotic plaques contributing to plaque dynamics. PARP inhibition may be a protective, a neutral, or a sensitizing factor. Additionally, PARP-1 may be a novel factor that can alter lipid metabolism. These novel functions of PARP not only challenge the current understanding of the role of the enzyme in cell death but also provide insights on the intricate contribution of PARP in cellular responses to predominant inflammatory factors within atherosclerotic plaques, presenting additional evidence for the viability of PARP inhibition as a therapeutic strategy for atherosclerosis.
Performance analysis of Reinforcement Learning for achieving context-awareness and intelligence in Cognitive Radio networks

Cognitive Radio (CR) is a novel and promising paradigm for next-generation wireless communication. It is able to sense and change its transmission and reception parameters adaptively according to spectrum availability at different channels. The Cognition Cycle (CC) is a state machine that is embodied in each CR that defines the mechanisms related to achieving context-awareness and intelligence including observation, orientation, learning, planning, decision making, and action selection. The CC is the key element in the design of various schemes in CR networks such as Dynamic Channel Selection (DCS), scheduling and congestion control. Hence, a good implementation of the CC is of paramount importance. In this paper, Reinforcement Learning (RL) is employed to implement the CC. The main focus is to analyze the performance of RL as an approach to achieving context-awareness and intelligence in regard to DCS. The contributions of this paper are twofold. Firstly, we seek to justify whether RL is an appropriate tool to implement the CC. Secondly, we seek to understand the effects of changes on RL parameters on network performance. In addition, we propose solutions for the problems associated with the application of RL in DCS. The results presented in this paper show that RL is a promising approach.
How does partitioning matter for 3D floorplanning?

The recent hierarchical design framework[8] for 3D floorplan-ning suggests a better performance than previous flat design framework. Under this framework, the layer assignment of the blocks is accomplished by some partitioning algorithms which are assumed to be critical[8]. In this paper, we provide an empirical study on the impact of such partitioning algorithms on the total wire length. By generating various partitions and running our floorplanner based on these partitions, we obtain the statistic of the resultant wire length. We observe that when the design instance has a large number of blocks which are uniformly sized, different partitions with the same cut size lead to roughly the same wire length. By another experiment, we find out that the cut size of the partition has the major influence on the wire length. Therefore, we argue that cut size is a metric good enough for the wire length optimization of 3D floorplanning and suggest that future research focus on other problems such as thermal effect, signal delay, etc.
What Are Lightness Illusions and Why Do We See Them?

Lightness illusions are fundamental to human perception, and yet why we see them is still the focus of much research. Here we address the question by modelling not human physiology or perception directly as is typically the case but our natural visual world and the need for robust behaviour. Artificial neural networks were trained to predict the reflectance of surfaces in a synthetic ecology consisting of 3-D “dead-leaves” scenes under non-uniform illumination. The networks learned to solve this task accurately and robustly given only ambiguous sense data. In addition—and as a direct consequence of their experience—the networks also made systematic “errors” in their behaviour commensurate with human illusions, which includes brightness contrast and assimilation—although assimilation (specifically White's illusion) only emerged when the virtual ecology included 3-D, as opposed to 2-D scenes. Subtle variations in these illusions, also found in human perception, were observed, such as the asymmetry of brightness contrast. These data suggest that “illusions” arise in humans because (i) natural stimuli are ambiguous, and (ii) this ambiguity is resolved empirically by encoding the statistical relationship between images and scenes in past visual experience. Since resolving stimulus ambiguity is a challenge faced by all visual systems, a corollary of these findings is that human illusions must be experienced by all visual animals regardless of their particular neural machinery. The data also provide a more formal definition of illusion: the condition in which the true source of a stimulus differs from what is its most likely (and thus perceived) source. As such, illusions are not fundamentally different from non-illusory percepts, all being direct manifestations of the statistical relationship between images and scenes.
Altered sleep composition after traumatic brain injury does not affect declarative sleep-dependent memory consolidation

Individuals with a history of traumatic brain injury (TBI) often report sleep disturbances, which may be caused by changes in sleep architecture or reduced sleep quality (greater time awake after sleep onset, poorer sleep efficiency, and sleep stage proportion alterations). Sleep is beneficial for memory formation, and herein we examine whether altered sleep physiology following TBI has deleterious effects on sleep-dependent declarative memory consolidation. Participants learned a list of word pairs in the morning or evening, and recall was assessed 12-h later, following an interval awake or with overnight sleep. Young adult participants (18–22 years) were assigned to one of four experimental groups: TBI Sleep (n = 14), TBI Wake (n = 12), non-TBI Sleep (n = 15), non-TBI Wake (n = 15). Each TBI participant was >1 year post-injury. Sleep physiology was measured with polysomnography. Memory consolidation was assessed by comparing change in word-pair recall over 12-h intersession intervals. The TBI group spent a significantly greater proportion of the night in SWS than the non-TBI group at the expense of NREM1. The TBI group also had marginally lower EEG delta power during SWS in the central region. Intersession changes in recall were greater for intervals with sleep than without sleep in both groups. However, despite abnormal sleep stage proportions for individuals with a TBI history, there was no difference in the intersession change in recall following sleep for the TBI and non-TBI groups. In both Sleep groups combined, there was a positive correlation between Intersession Change and the proportion of the night in NREM2 + SWS. Overall, sleep composition is altered following TBI but such deficits do not yield insufficiencies in sleep-dependent memory consolidation.
The fluorescent pentameric oligothiophene pFTAA identifies filamentous tau in live neurons cultured from adult P301S tau mice

Identification of fluorescent dyes that label the filamentous protein aggregates characteristic of neurodegenerative disease, such as β-amyloid and tau in Alzheimer's disease, in a live cell culture system has previously been a major hurdle. Here we show that pentameric formyl thiophene acetic acid (pFTAA) fulfills this function in living neurons cultured from adult P301S tau transgenic mice. Injection of pFTAA into 5-month-old P301S tau mice detected cortical and DRG neurons immunoreactive for AT100, an antibody that identifies solely filamentous tau, or MC1, an antibody that identifies a conformational change in tau that is commensurate with neurofibrillary tangle formation in Alzheimer's disease brains. In fixed cultures of dorsal root ganglion (DRG) neurons, pFTAA binding, which also identified AT100 or MC1+ve neurons, followed a single, saturable binding curve with a half saturation constant of 0.14 μM, the first reported measurement of a binding affinity of a beta-sheet reactive dye to primary neurons harboring filamentous tau. Treatment with formic acid, which solubilizes filamentous tau, extracted pFTAA, and prevented the re-binding of pFTAA and MC1 without perturbing expression of soluble tau, detected using an anti-human tau (HT7) antibody. In live cultures, pFTAA only identified DRG neurons that, after fixation, were AT100/MC1+ve, confirming that these forms of tau pre-exist in live neurons. The utility of pFTAA to discriminate between living neurons containing filamentous tau from other neurons is demonstrated by showing that more pFTAA+ve neurons die than pFTAA-ve neurons over 25 days. Since pFTAA identifies fibrillar tau and other misfolded proteins in living neurons in culture and in animal models of several neurodegenerative diseases, as well as in human brains, it will have considerable application in sorting out disease mechanisms and in identifying disease-modifying drugs that will ultimately help establish the mechanisms of neurodegeneration in human neurodegenerative diseases.
Biometric Evidence that Sexual Selection Has Shaped the Hominin Face

We consider sex differences in human facial morphology in the context of developmental change. We show that at puberty, the height of the upper face, between the lip and the brow, develops differently in males and females, and that these differences are not explicable in terms of sex differences in body size. We find the same dimorphism in the faces of human ancestors. We propose that the relative shortening in men and lengthening in women of the anterior upper face at puberty is the mechanistic consequence of extreme maxillary rotation during ontogeny. A link between this developmental model and sexual dimorphism is made for the first time, and provides a new set of morphological criteria to sex human crania. This finding has important implications for the role of sexual selection in the evolution of anthropoid faces and for theories of human facial attractiveness.
Design on Power-Rail ESD Clamp Circuit for 3.3-V I/O Interface by Using Only 1-V/2.5-V Low-Voltage Devices in a 130-nm CMOS Process

A new power-rail electrostatic discharge (ESD) clamp circuit for application in 3.3-V mixed-voltage input-output (I/O) interface is proposed and verified in a 130-nm 1-V/2.5-V CMOS process. The devices in this power-rail ESD clamp circuit are all 1-V or 2.5-V low-voltage nMOS/pMOS devices, which are specially designed without suffering the gate-oxide reliability issue under 3.3-V I/O interface applications. A special ESD detection circuit realized with the low-voltage devices is designed and added in the power-rail ESD clamp circuit to improve ESD robustness of ESD clamp devices by substrate-triggered technique. The experimental results verified in a 130-nm CMOS process have proven the excellent effectiveness of this new proposed power-rail ESD clamp circuit
MaTrEx: The DCU MT System for WMT 2008

In this paper, we give a description of the machine translation system developed at DCU that was used for our participation in the evaluation campaign of the Third Workshop on Statistical Machine Translation at ACL 2008. We describe the modular design of our data-driven MT system with particular focus on the components used in this participation. We also describe some of the significant modules which were unused in this task. We participated in the EuroParl task for the following translation directions: Spanish-English and French-English, in which we employed our hybrid EBMT-SMT architecture to translate. We also participated in the Czech-English News and News Commentary tasks which represented a previously untested language pair for our system. We report results on the provided development and test sets.
JTF-based high-resolution radar imaging of micromotion targets from corrupted data

Effective radar imaging based on the joint time-frequency (JTF) distribution has played significant roles in recognition, measurement, and cataloguing of micromotion targets in space. Sometimes, however, the radar returns are incomplete due to strong interference and occlusion, and the phase of the available samples is corrupted as a result of inaccurate motion compensation or atmospheric turbulence. To tackle this problem, this paper constructs the data-adaptive, nonparametric dictionary in the JTF domain. Then, it solves the optimal and sparse JTF distribution by iterative optimization using the theory of sparse signal representation and the least-square-error criterion. Particularly, this method applies the modified augmented Lagrangian method to reduce the computational complexity. The validity of the method has been proved by simulated data.
Reinforcement learning: Computational theory and biological mechanisms

Reinforcement learning is a computational framework for an active agent to learn behaviors on the basis of a scalar reward signal. The agent can be an animal, a human, or an artificial system such as a robot or a computer program. The reward can be food, water, money, or whatever measure of the performance of the agent. The theory of reinforcement learning, which was developed in an artificial intelligence community with intuitions from animal learning theory, is now giving a coherent account on the function of the basal ganglia. It now serves as the “common language” in which biologists, engineers, and social scientists can exchange their problems and findings. This article reviews the basic theoretical framework of reinforcement learning and discusses its recent and future contributions toward the understanding of animal behaviors and human decision making.