Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of BDNF Val66Met polymorphism with HPA and SAM axis reactivity to psychological and physical stress

Background Decreased expression of brain-derived neurotrophic factor (BDNF) is implicated in enhanced stress responses. The BDNF Val66Met polymorphism is associated with psychological changes; for example, carriers of the Met allele exhibit increased harm avoidance as well as a higher prevalence of depression and anxiety disorder. Methods To analyze the effects of BDNF Val66Met on stress responses, we tested 226 university students (88 women and 138 men) using a social stress procedure (Trier Social Stress Test [TSST]) and an electrical stimulation stress test. Stress indices were derived from repeated measurements of salivary α-amylase, salivary cortisol, heart rate, and psychological testing during the stress tests. All subjects were genotyped for the Val66Met polymorphism (G196A). Results A significant three-way interaction (time [3 levels] × BDNF [Val/Val, Val/Met, Met/Met]; P<0.05) was demonstrated that revealed different salivary cortisol responses in the TSST but not in electrical stimulation. Met/Met women had stronger cortisol responses than Val/Met and Val/Val individuals in the TSST. Met/Met men exhibited stronger salivary cortisol responses than Val/Met and Val/Val individuals in the TSST. Conclusion These results indicate that a common, functionally significant polymorphism in BDNF had different effects on hypothalamic–pituitary–adrenocortical axis reactivity but not on sympathetic adrenomedullary reactivity in TSST and electrical stimulation tests.
MODULAR FORMS IN CHARACTERISTIC ’ ANDSPECIAL VALUES OF THEIR L-FUNCTIONS

In this paper we specialize our results in [A-S] to G GL 2 to obtain information about congruences between classical holomorphic modular forms. In the final section we indicate how the methods can be adapted to prove congruences between special values of L-functions of modular forms of possibly different weights. We begin with a study of the q-expansions in characteristic > 0 of Hecke eigenforms of weight k > 2 and level N prime to '. By a theorem of Eichler and Shimura this is equivalent to a study of the systems of eigenvalues of Hecke operators acting on the group cohomology of FI(N) (see [}2). Using the func-torial properties of cohomology, we show (Theorems 3.4 and 3.5) that the systems of Hecke eigenvalues (mod ') occurring in the space, ,//t' 2(1'1(N)), of modular forms of level N and all weights > 2 coincide, up to twist, with those occurring in the space, ,//t'2(I'(N)), of weight two forms of level N'. In particular, we see that there are only finitely many systems of eigenvalues (mod ') occurring in the infinite dimensional space t'> 2(Ft(N)), a fact proved by Jochnowitz [J] for prime N < 17.
Robot Motion Planning in Dynamic Environments with Moving Obstacles and Target

This paper presents a new sensor-based online method for generating collision-free near-optimal paths for mobile robots pursuing a moving target amidst dynamic and static obstacles. At each iteration, first the set of all collision-free directions are calculated using velocity vectors of the robot relative to each obstacle and target, forming the Directive Circle (DC), which is a novel concept. Then, a direction close to the shortest path to the target is selected from feasible directions in DC. The DC prevents the robot from being trapped in deadlocks or local minima. It is assumed that the target’s velocity is known, while the speeds of dynamic obstacles, as well as the locations of static obstacles, are to be calculated online. Extensive simulations and experimental results demonstrated the efficiency of the proposed method and its success in coping with complex environments and obstacles. Keywords—Dynamic Environment, Moving Target, Robot Motion Planning.
Application of the Ensemble Kalman Filter to Atmosphere-Ocean Coupled Model

We report the first application of the ensemble Kalman filter (EnKF) to an intermediate coupled atmosphere-ocean model by [1], into which the sea surface height (SSH) anomaly observations by TOPEX/POSEIDON (T/P) altimetry are assimilated. Smoothed estimates ofthe 54,403 dimensional state are obtained from 1981 observational points with 2048 ensemble members. While data assimilated are SSH anomalies alone, an ensemble experiment of 2002/03 El Niño event based on the EnKF can predict consistent Niño 3 sea surface temperature (SST) anomalies about 5 months in advance.
New Qualitative Methodologies in Health and Social Care Research

Introduction: Shifting Sands in Qualitative Methodology 1. Discourse Analysis: Addressing the Communication Strategies of Healthcare Professionals 2. The Turn to a Narrative Knowing of Persons: Minimalist Passive Interviewing Technique and Team Analysis of Narrative Qualitative Data 3. Hermeneutics and Nursing Research 4. Descriptive Phenomenology: Lifeworld as Evidence 5. From the Porter's Point of View: Participant-Observation by the Interpretive Anthropologist in the Hospital 6. Imagework Method and Potential Applications in Health 7. Post Modern Literary Poetics of Experience: A New Form of Aesthetic Enquiry 8. Historiography, Illness and the Interpretation of Fiction 9. Methodology and Practical Application of the Social Action Research Model
Learning Bounded Rationality Models of the Adversary in Repeated Stackelberg Security Games

Several competing human behavior models have been proposed to model and protect against boundedly rational adversaries in repeated Stackelberg security games (SSGs). However, these existing models fail to address three main issues which are extremely detrimental to defender performance. First, while they attempt to learn adversary behavior models from adversaries’ past actions (“attacks on targets”), they fail to take into account adversaries’ future adaptation based on successes or failures of these past actions. Second, they assume that sufficient data in the initial rounds will lead to a reliable model of the adversary. However, our analysis reveals that the issue is not the amount of data, but that there just is not enough of the attack surface exposed to the adversary to learn a reliable model. Third, current leading approaches have failed to include probability weighting functions, even though it is well known that human beings’ weighting of probability is typically nonlinear. Moreover, the performances of these models may be critically dependent on the learning algorithm used to learn the parameters of these models. The first contribution of this paper is a new human behavior model, SHARP, which mitigates these three limitations as follows: (i) SHARP reasons based on success or failure of the adversary’s past actions on exposed portions of the attack surface to model adversary adaptiveness; (ii) SHARP reasons about similarity between exposed and unexposed areas of the attack surface, and also incorporates a discounting parameter to mitigate adversary’s lack of exposure to enough of the attack surface; and (iii) SHARP integrates a non-linear probability weighting function to capture the adversary’s true weighting of probability. Our second contribution is a comparison of two different approaches for learning the parameters of the bounded rationality models. Our third contribution is a first “longitudinal study” – at least in the context of SSGs – of competing models in settings involving repeated interaction between the attacker and the defender. This study, where each experiment lasted a period of multiple weeks with individual sets of human subjects, illustrates the strengths and weaknesses of different models and shows the advantages of SHARP.
Comparison of lung proteome profiles in two rodent models of pulmonary arterial hypertension

We studied the lung proteome changes in two widely used models of pulmonary arterial hypertension (PAH): monocrotaline (MCT) injection and chronic hypoxia (CH); untreated rats were used as controls (n = 6/group). After 28 days, invasive right ventricular systolic pressure (RVSP) was measured. Lungs were immunostained for α‐smooth muscle actin (αSMA). 2‐DE (n = 4/group) followed by nano‐LC‐MS/MS was applied for protein identification. Western blotting was used additionally if possible. RVSP was significantly increased in MCT‐ and CH‐rats (MCT 62.5 ± 4.4 mmHg, CH 62.2 ± 4.1 mmHg, control 25.0 ± 1.7 mmHg, p<0.001). This was associated with an increase of αSMA positive vessels. In both groups, there was a significantly increased expression of proteins associated with the contractile apparatus (diphosphoHsp27 (p<0.001), Septin2 (p<0.001), F‐actin capping protein (p<0.01), and tropomyosin β (p<0.02)). In CH, proteins of the nitric oxide (Hsc70; p = 0.002), carbon monoxide (biliverdin reductase; p = 0.005), and vascular endothelial growth factor (VEGF) pathway (annexin 3; p<0.001) were significantly increased. In MCT, proteins involved in serotonin synthesis (14‐3‐3; p = 0.02), the enhanced unfolded protein response (ERp57; p = 0.02), and intracellular chloride channels (CLIC 1; p = 0.002) were significantly elevated. Therefore, MCT‐ and CH‐induced vasoconstriction and remodeling seemed to be mediated via different signaling pathways. These differences should be considered in future studies using either PAH model.
Evolutionary design of polymorphic gates using ambipolar transistors

The objective of the paper is to introduce a new approach to the evolutionary design of polymorphic digital circuits conducted directly at transistor level. A discrete event-driven simulator was utilized to achieve reasonable trade-off between performance and precision. The proposed approach was evaluated on a set of polymorphic logic circuits controlled by switching the power rails. It was demonstrated that the proposed method is able to produce valid solutions. A lot of polymorphic gates based on ambipolar transistors were designed, which provide transistor savings compared to existing circuits. A new class of polymorphic gates was discovered thanks to the proposed system - gates based on conventional MOS transistors whose functions are changed by switching the power rails. They seem to have the best parameters among currently known polymorphic gates based on conventional transistors.
Enabling Mobile Networks through secure naming

Mobile Networks are increasingly important in land-, sea-and air-based military scenarios. The interest in supporting network mobility for Internet Protocol (IP) networks has led to the Network Mobility (NEMO) protocol extensions being proposed for IP within the IETF. These extensions are based on the work already completed on host mobility for Mobile IP (MIP). The current work is based on the use of software agents: a Home Agent (HA) intercepts packets destined for the addresses in the mobile network and uses an IP-in-IP tunnel to send the packets to the Mobile Router (MR) located at a Care of Address (CoA), which terminates the tunnel. As the mobile network moves to new IP networks, the MR updates the HA with its new CoA. While this tunnelling approach represents a sound engineering solution for backwards compatibility, and is the only one that has been pursued within the IETF, it has seen little deployment, either in support of mobile hosts or mobile networks. We make the case for an alternative approach based on secure naming. We make a comparison in operation with the current tunnelling-based approach, both in architecture and by analysis of protocol operation. Our initial analyses indicate that a naming-based approach shows promise as a viable alternative to a tunnelling-based approach, and could offer other architectural benefits.
Identification of cardio-pulmonary resuscitation (CPR) scenes in medical simulation videos using spatio-temporal gradient orientations

In this work, we present the application of spatio-temporal three dimensional gradients to detect and classify scenes that involve localized actions like CPR in medical simulation videos. Medical simulations provide a more feasible and comprehensive training to avoid human errors during uncommon clinical situations. Life-like mannequins that can simulate emergency patient conditions are used for this purpose. The physician responsible for these simulations, records each session after which, he manually reviews and annotates the recordings, and then debriefs the trainees. With the increasing number of video recordings, automatic retrieval of specific video segments became necessary. Here we propose an automatic scene retrieval system which can detect and classify scenes into CPR and non-CPR scenes. We use a simple linear SVM classifier for the classification. It provides answers to queries that are of interest to the physician supervising the training sessions such as: "show me all the scenes that have a CPR action from a given video simulation training", or "retrieve time specific data about such critical events as elapsed time between failure of circulation and the initiation of CPR, a measure clearly associated with patient outcome". Our system has the following two main advantages over other existing systems: (1) It does not require video shot segmentation (2) It uses one algorithm and need not be coupled with any other algorithms like image segmentation, skin detection etc. The proposed approach was evaluated and validated using ~30 min video simulation sessions. We show that the proposed approach out performs the state of the art by being able to correctly classify the CPR scenes with an error rate of only 10%.
Schizophrenia‐like topological changes in the structural connectome of individuals with subclinical psychotic experiences

Schizophrenia is often regarded as a “dysconnectivity” disorder and recent work using graph theory has been used to better characterize dysconnectivity of the structural connectome in schizophrenia. However, there are still little data on the topology of connectomes in less severe forms of the condition. Such analysis will identify topological markers of less severe disease states and provide potential predictors of further disease development. Individuals with psychotic experiences (PEs) were identified from a population‐based cohort without relying on participants presenting to clinical services. Such individuals have an increased risk of developing clinically significant psychosis. 123 individuals with PEs and 125 controls were scanned with diffusion‐weighted MRI. Whole‐brain structural connectomes were derived and a range of global and local GT‐metrics were computed. Global efficiency and density were significantly reduced in individuals with PEs. Local efficiency was reduced in a number of regions, including critical network hubs. Further analysis of functional subnetworks showed differential impairment of the default mode network. An additional analysis of pair‐wise connections showed no evidence of differences in individuals with PEs. These results are consistent with previous findings in schizophrenia. Reduced efficiency in critical core hubs suggests the brains of individuals with PEs may be particularly predisposed to dysfunction. The absence of any detectable effects in pair‐wise connections illustrates that, at less severe stages of psychosis, white‐matter alterations are subtle and only manifest when examining network topology. This study indicates that topology could be a sensitive biomarker for early stages of psychotic illness. Hum Brain Mapp 36:2629–2643, 2015. © 2015 TheAuthors Human Brain Mapping Published by Wiley Periodicals, Inc.
A Simple Ductal Mammary Papilloma in a Male Maned Wolf (Chrysocyon Brachyurus)

A 1-cm-diameter nodule was identified in the left inguinal mammary gland of a 9-year-old male maned wolf (Chrysocyon brachyurus). The mass was surgically excised and examined histologically. Microscopically, the neoplasm consisted of papillary proliferations of epithelial cells on well-defined fibrovascular stalks. A myoepithelial layer was located between the single layer of epithelial cells and the fibrovascular stalk. This histologic appearance was compatible with a diagnosis of simple ductal mammary papilloma. Immunohistochemical staining was positive for p63, cytokeratins AE1/AE3, and estrogen receptors. The clinical and histologic observations in the present case indicate that male maned wolves may develop mammary tumors that are similar to those observed in domestic dogs and humans.
Magnetic Field Analysis of Lorentz Motors Using a Novel Segmented Magnetic Equivalent Circuit Method

A simple and accurate method based on the magnetic equivalent circuit (MEC) model is proposed in this paper to predict magnetic flux density (MFD) distribution of the air-gap in a Lorentz motor (LM). In conventional MEC methods, the permanent magnet (PM) is treated as one common source and all branches of MEC are coupled together to become a MEC network. In our proposed method, every PM flux source is divided into three sub-sections (the outer, the middle and the inner). Thus, the MEC of LM is divided correspondingly into three independent sub-loops. As the size of the middle sub-MEC is small enough, it can be treated as an ideal MEC and solved accurately. Combining with decoupled analysis of outer and inner MECs, MFD distribution in the air-gap can be approximated by a quadratic curve, and the complex calculation of reluctances in MECs can be avoided. The segmented magnetic equivalent circuit (SMEC) method is used to analyze a LM, and its effectiveness is demonstrated by comparison with FEA, conventional MEC and experimental results.
Multi-task deep neural network acoustic models with model adaptation using discriminative speaker identity for whisper recognition

This paper presents a study on large vocabulary continuous whisper automatic recognition (wLVCSR). wLVCSR provides the ability to use ASR equipment in public places without concern for disturbing others or leaking private information. However the task of wLVCSR is much more challenging than normal LVCSR due to the absence of pitch which not only causes the signal to noise ratio (SNR) of whispers to be much lower than normal speech but also leads to flatness and formant shifts in whisper spectra. Furthermore, the amount of whisper data available for training is much less than for normal speech. In this paper, multi-task deep neural network (DNN) acoustic models are deployed to solve these problems. Moreover, model adaptation is performed on the multi-task DNN to normalize speaker and environmental variability in whispers based on discriminative speaker identity information. On a Mandarin whisper dictation task, with 55 hours of whisper data, the proposed SI multi-task DNN model can achieve 56.7% character error rate (CER) improvement over a baseline Gaussian Mixture Model (GMM), discriminatively trained only using the whisper data. Besides, the CER of the proposed model for normal speech can reach 15.2%, which is close to the performance of a state-of-the-art DNN trained with one thousand hours of speech data. From this baseline, the model-adapted DNN gains a further 10.9% CER reduction over the generic model.
Macrophage Migration Inhibitory Factor Deficiency Augments Doxorubicin‐Induced Cardiomyopathy

Background Recent evidence has depicted a role of macrophage migration inhibitory factor (MIF) in cardiac homeostasis under pathological conditions. This study was designed to evaluate the role of MIF in doxorubicin‐induced cardiomyopathy and the underlying mechanism involved with a focus on autophagy. Methods and Results Wild‐type (WT) and MIF knockout (MIF−/−) mice were given saline or doxorubicin (20 mg/kg cumulative, i.p.). A cohort of WT and MIF−/− mice was given rapamycin (6 mg/kg, i.p.) with or without bafilomycin A1 (BafA1, 3 μmol/kg per day, i.p.) for 1 week prior to doxorubicin challenge. To consolidate a role for MIF in the maintenance of cardiac homeostasis following doxorubicin challenge, recombinant mouse MIF (rmMIF) was given to MIF−/− mice challenged with or without doxorubicin. Echocardiographic, cardiomyocyte function, and intracellular Ca2+ handling were evaluated. Autophagy and apoptosis were examined. Mitochondrial morphology and function were examined using transmission electron microscopy, JC‐1 staining, MitoSOX Red fluorescence, and mitochondrial respiration complex assay. DHE staining was used to evaluate reactive oxygen species (ROS) generation. MIF knockout exacerbated doxorubicin‐induced mortality and cardiomyopathy (compromised fractional shortening, cardiomyocyte and mitochondrial function, apoptosis, and ROS generation). These detrimental effects of doxorubicin were accompanied by defective autophagolysosome formation, the effect of which was exacerbated by MIF knockout. Rapamycin pretreatment rescued doxorubicin‐induced cardiomyopathy in WT and MIF−/− mice. Blocking autophagolysosome formation using BafA1 negated the cardioprotective effect of rapamycin and rmMIF. Conclusions Our data suggest that MIF serves as an indispensable cardioprotective factor against doxorubicin‐induced cardiomyopathy with an underlying mechanism through facilitating autophagolysosome formation.
Development of new psychometric instruments to measure appearance distress during adolescence: The adolescent appearance distress scales

Measures of adolescent appearance distress have focused on weight and body shape, excluding other aspects of appearance. The absence of a psychometrically sound, general measure of appearance distress has limited evaluation of interventions and curtailed investigation of psychological processes in adolescent appearance adjustment. This paper describes the development of scales assessing adolescent appearance distress to address this dearth of appropriate measures, validated through cross-sectional design involving 617 adolescents. Two scales were developed, comprising 13 items for younger adolescents and 17 items for older adolescents. Two similar factors were generated for each scale, “fear of negative appearance evaluation” and “salience and investment in appearance. ” A third factor was identified for older adolescents, “social appearance comparison. ” Sound psychometric properties were demonstrated
Anomaly detection in cyber-physical systems: A formal methods approach

As the complexity of cyber-physical systems increases, so does the number of ways an adversary can disrupt them. This necessitates automated anomaly detection methods to detect possible threats. In this paper, we extend our recent results in the field of inference via formal methods to develop an unsupervised learning algorithm. Our procedure constructs from data a signal temporal logic (STL) formula that describes normal system behavior. Trajectories that do not satisfy the learned formula are flagged as anomalous. STL can be used to formulate properties such as “If the train brakes within 500 m of the platform at a speed of 50 km/hr, then it will stop in at least 30 s and at most 50 s. ” STL gives a more human-readable representation of behavior than classifiers represented as surfaces in high-dimensional feature spaces. STL formulae can also be used for early detection via online monitoring and for anomaly mitigation via formal synthesis. We demonstrate the power of our method with a physical model of a train's brake system. To our knowledge, this paper is the first instance of formal methods being applied to anomaly detection.