Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations of smoking and alcohol consumption with healthy ageing: a systematic review and meta-analysis of longitudinal studies

Objectives The number of older people is growing across the world; however, quantitative synthesis of studies examining the impact of lifestyle factors on the ageing process is rare. We conducted a systematic review and meta-analysis of longitudinal studies to synthesise the associations of smoking and alcohol consumption with healthy ageing (HA). Methods Major electronic databases were searched from inception to March 2017 (prospectively registered systematic reviews registration number CRD42016038130). Studies were assessed for methodological quality. Random-effect meta-analysis was performed to calculate pooled ORs and 95% CI. Results In total, we identified 28 studies (n=184 543); 27 studies reported results on smoking, 22 on alcohol consumption. 23 studies reported a significant positive association of never or former smoking with HA and 4 non-significant. 12 studies reported a significant positive association of alcohol consumption with HA, 9 no association and 1 negative. Meta-analysis revealed increased pooled OR of HA for never smokers compared with current smokers (2.36, 95% CI 2.03 to 2.75), never smokers compared with former smokers (1.32, 95% CI 1.23 to 1.41), former or never smokers compared with current smokers (1.72, 95% CI 1.20 to 2.47), never smokers compared with past or current smokers (1.29, 95% CI 1.16 to 1.43); drinkers compared with non-drinkers (1.28, 95% CI 1.08 to 1.52), light drinkers compared with non-drinkers (1.12, 95% CI 1.03 to 1.22), moderate drinkers compared with non-drinkers (1.35, 95% CI 0.93 to 1.97) and high drinkers compared with non-drinkers (1.25, 95% CI 1.09 to 1.44). There was considerable heterogeneity in the definition and measurement of HA and alcohol consumption. Conclusions There is consistent evidence from longitudinal studies that smoking is negatively associated with HA. The associations of alcohol consumption with HA are equivocal. Future research should focus on the implementation of a single metric of HA, on the use of consistent drinking assessment among studies and on a full-range of confounding adjustment. Our research also highlighted the limited research on ageing in low-and-middle-income countries.
Traffic Remapping Attacks in Ad Hoc Networks

Ad hoc networks rely on the mutual cooperation of stations. As such, they are susceptible to selfish attacks that abuse network mechanisms. Class-based QoS provisioning mechanisms, such as the EDCA function of IEEE 802.11, are particularly prone to traffic remapping attacks, which may bring an attacker better QoS without exposing it to easy detection. Such attacks have been studied in wireless LANs, whereas their impact in multihop settings is less known. We provide a definition of traffic remapping attacks, highlighting their ease of execution, and analyze their impact in multihop networks. Suitable detection methods and defense measures are also discussed and evaluated.
Graphene-Assisted Integrated Nonlinear Optics

The unique linear and massless band structure of graphene in a purely two-dimensional Dirac fermionic structure has ignited intense research since the first monolayer graphene was isolated in the laboratory. Not only does it offer new inroads into low-dimensional physics; graphene exhibits several peculiar properties that promise to widen the realm of opportunities for integrated optics and photonics. This thesis is an attempt to shed light on the exceptional nonlinear optical properties of graphene and their potential applications in integrated photonics. Following a theoretical exploration of light-graphene interaction, disruptive new insight into the nonlinear optics of graphene was generated. It now appears that graphene can efficiently enable photon-photon interaction in a fully integrated fashion. This property, taken together with ultrawideband tunability and ultrafast carrier dynamics could be fully exploited within integrated photonics for a variety of applications including harmonic generation and all-optical signal processing. The multidisciplinary work described herein combines theoretical modeling and experimentation to proceed one step further toward this goal. This thesis begins by presenting a semiclassical theory of light-graphene interaction. The emphasis is placed on the nonlinear optical response of graphene from the standpoint of its underlying chiral symmetry. The peculiar energymomentum dispersion of the quasiparticles in graphene entails a diverging field-induced interband coupling. Following a many-body study of the carrier relaxations dynamics in graphene, it will be shown that the charged carriers in the vicinity of the Dirac point undergo an unconventional saturation effect that can be induced by an arbitrarily weak electromagnetic field. The perturbative treatment of the optical response of graphene is revisited and a theoretical model is developed to estimate the nonlinear optical coefficients including the Kerr coefficient of graphene. The theoretical models are complimented by the experimental results. The peculiar nonlinear optical properties of graphene together with its ablity to being integrated with optical platforms would render it possible to perform nonlinear optics in graphene integrated nanophotonic structures. Here, the suitability of graphene for nonlinear optical applications is investigated both theoretically and experimentally. The emphasis is placed on an on-chip platform for ultrafast all-optical amplitude modulation. The experimental results indicate strong all-optical modulation in a graphene-cladded planar photonic crystal nanocavity. This development relies heavily on the unique properties of graphene, including its fast carrier dynamics and the special phonon induced relaxation mechanism. Finally, the potential application of graphene based all-optical modulation in time resolved nonlinear spectroscopy is also discussed.
Action recognition from mutually incoherent pose bases in static image

Action recognition in static image is challenging. The authors propose mutually incoherent pose bases which are implicit poselet co-occurrences and are learned by dictionary training to describe body pose. Poselets in a pose basis are not constrained in space and quantity, thus pose basis can describe body pose more flexibly than k-poselet. In their method, body pose in an image is represented by a sparse linear combination of pose bases because pose in an action varies while each image only captures a snapshot from a single viewpoint. In dictionary training, the challenge is how to stabilise the sparse representation which is the input of Support Vector Machine (SVM) for action recognition, because the original pose signal is ambiguous while dictionary is an over complete matrix. Their solution is to add cumulative coherence as penalty in objective function and induce pose bases become mutually incoherent. They evaluate the method on two popular datasets and experiment results show the pose representation has encouraging performance in action recognition. Furthermore, they empirically exploit the complementary role of the local pose feature with deep convolutional neural network features from holistic image. Experiment results demonstrate aggressive performance improvement by concatenating the two features.
Fall detection algorithm for the elderly using acceleration sensors on the shoes

The rate of increase in the number of aging population in Korea is very rapid among OECD-member countries. And fall accident is one of the most common factors that threaten the health of the elderly. Therefore, it is needed to develop a fall detection system for the elderly. Most fall detection systems use accelerometers attached on the torso. And in various studies, it was verified that these systems have high sensitivity and high specificity. However, the elderly would feel uncomfortable when banding a sensor on the chest every day. Therefore, in this study, we attached an accelerometer on the shoes to detect fall in the elderly. This prototype system would be improved as a smaller, low-power system in the next study. Also, applying energy harvesting device to this shoe system is being developed to reduce the weight of battery.
Interactions between Anandamide & Corticotropin-Releasing Hormone Signaling Modulate Human Amygdala Function & Risk for Anxiety Disorders : An Imaging Genetics Strategy for Modeling Molecular Interactions

Background—Preclinical models reveal that stress-induced amygdala activity and impairment in fear extinction reflects reductions in anandamide driven by corticotropin-releasing hormone receptor type 1 (CRHR1) potentiation of the anandamide catabolic enzyme fatty acid amide hydrolase (FAAH). Methods—Here we provide clinical translation for the importance of these molecular interactions using an imaging genetics strategy to examine whether interactions between genetic polymorphisms associated with differential anandamide (FAAH rs324420) and CRHR1 (CRHR1 rs110402) signaling modulate amygdala function and anxiety disorder diagnosis. Results—Analyses revealed that individuals with a genetic background predicting relatively high anandamide and CRHR1 signaling exhibited blunted basolateral amygdala habituation, which further mediated increased risk for anxiety disorders amongst these same individuals. Conclusions—The convergence of preclinical and clinical data suggests that interactions between anandamide and CRHR1 represent a fundamental molecular mechanism regulating amygdala function and anxiety. Our results further highlight the potential of imaging genetics to powerfully translate complex preclinical findings to clinically meaningful human phenotypes. Corresponding Author: Ryan Bogdan, Ph.D., Campus Box 1125, Psychology Bldg. Washington University in St. Louis, One Brookings Dr., St. Louis, MO 63130, USA, rbogdan@wustl.edu. FINANCIAL DISCLOSURES All authors report no biomedical financial interests or potential conflict of interest. The authors declare no competing financial interests. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. HHS Public Access Author manuscript Biol Psychiatry. Author manuscript; available in PMC 2017 September 01. Published in final edited form as: Biol Psychiatry. 2016 September 1; 80(5): 356–362. doi:10.1016/j.biopsych. 2015.12. 021. A uhor M anscript
GTZAN-Rhythm: Extending the GTZAN Test-Set with Beat, Downbeat and Swing Annotations

We present here the GTZAN-Rhythm test-set which is an extension of the GTZAN test-set with rhythm annotations. While there is a controversy related to the use of the GTZAN test-set for music genre classification, its audio content is however representative of real commercial music of various music genre and its audio is also already widely shared. Also, considering the various genres included in it, it provides a good balance between various types of rhythm including tracks with and without swing. We manually annotated the 1000 audio excerpts into beat, downbeat and swing annotations. We describe here this new test-set, as well as the validation of the annotations and the various uses one can make out of it (swing analysis , beat and downbeat tracking).
Bio-physical closure criteria without reference sites: realistic targets in modified rivers.

The use of reference sites for establishing closure criteria in areas disturbed by mining activities is common practice. ‘Reference’ sites are those considered to be largely unimpacted by anthropogenic activity (retaining desirable natural characteristics), and occurring near disturbed sites. Sites are considered rehabilitated when their biophysical condition approximates that of the reference site. However, this approach often creates impossible or unrealistic targets for miners seeking to close rehabilitated lands. For example, reference sites are often limited in availability (or non-existent) due to impacts by other land uses. Further, any available reference sites might not be realistic matches for the rehabilitated sites – in many rivers (for example) it is questionable whether sites which superficially appear similar are actually ecologically similar. We propose a more achievable approach to mine closure by comparing the bio-physical characteristics of rehabilitated sites to overall ecosystem variability, rather than specific target reference sites. Using multivariate ordination a classic data clustering technique in ecology as an applied management tool allows managers to measure how different their rehabilitated sites are from co-occurring sites, and how the rehabilitated sites are tracking over time. Our approach also identifies the key biological, physical, and chemical parameters that potentially differentiate a rehabilitated site and, therefore, the necessary actions to bring a rehabilitation site within range of normal river variability. Further, this conceptual paper introduces two unique case studies used to develop the model, involving microbes as indicators of rehabilitation progress and mine water impact in Australian rivers. The challenges and benefits associated with implementation of this approach from the practitioners’ perspectives are discussed. The outcome of this new approach to closure will allow miners to create realistic and definable targets for relinquishing rehabilitation land in already modified landscapes, potentially simplifying closure and project approvals.
USING AIR TRAFFIC CONTROL TASKLOAD MEASURES AND COMMUNICATION EVENTS TO PREDICT SUBJECTIVE WORKLOAD

Abstract : A study was conducted to determine whether air traffic control (ATC) communication events would predict subjective estimates of controller workload as well as measures of controller taskload. We compared different regression models' predictions of subjective workload estimates made by 16 subject matter experts on 5 occasions during 8 samples of air traffic activity. The predictors were different combinations of four taskload principal components computed from routinely recorded ATC data, two principal components representing the number and duration of voice communication events, and two principal components representing the content of voice communications. Several regression model comparisons were computed to identify 'reduced' regression models containing fewer predictors that would predict the workload ratings as well as a full model containing all predictors. Several reduced models predicted ATWIT (Air Traffic Workload Input Technique) ratings as well as the full model but all of these contained the Activity component. These reduced models were a model containing only the Activity component, a model containing the Activity and Instructional Clearances components, and a model containing the Activity, Instructional Clearances, and All Communications Number and Duration components. The results suggest that routinely recorded ATC data provide a good estimate of subjective workload. However, if recordings of voice communications are available and researchers want to invest the time required to analyze the transcripts, they may be able to improve slightly their estimate of subjective workload. The researcher must consider whether the information gained is worth the additional time investment required for analysis.
Test and analysis on anti-seismic property of frp-reinforced non-ductile reinforced concrete frame structures

The research is conducted for experimental analysis on anti-seismic property of FRP-reinforced non-ductile reinforced concrete frame structures. Research and analysis on the anti-seismic property of the structural model are conducted with the shaking table experiment and the simulation analysis. Based on the research findings, the experimental results of the FRP-reinforced non-ductile reinforced concrete frame structure in this research are in accordance with design requirements, contributing to reducing structural frame failures and displacements. Further researches by professionals are still needed for the anti-seismic property of the FRPreinforced non-ductile reinforced concrete frame structure model in the future.
Secondary Bacterial Pneumonia by Staphylococcus aureus Following Influenza A Infection Is SaeR/S Dependent

Staphylococcus aureus is a predominant cause of fatal pneumonia following influenza A virus (IAV) infection. Herein we investigate the influence of antecedent IAV infection on S. aureus virulence gene expression. Using a murine model, comparing the USA300 and USA300ΔsaeR/S strains, we demonstrate that S. aureus pathogenesis following IAV infection is SaeR/S dependent. Furthermore, we show that IAV modulates the lung environment to rapidly up-regulate S. aureus virulence factors containing the SaeR-binding domain. Data demonstrate that the pathogen response to IAV infection impacts host outcome and provides evidence that the ability of S. aureus to sense and respond to the lung environment determines severity of pneumonia.
Efficient lattice representation and generation

In large-vocabulary, multi-pass speech recognition systems, it is desirable to generate word lattices incorporating a large number of hypotheses while keeping the lattice sizes small. We describe two new techniques for reducing word lattice sizes without eliminating hypotheses. The first technique is an algorithm to reduce the size of non-deterministic bigram word lattices. The algorithm iteratively combines lattice nodes and transitions if local properties show that this does not change the set of allowed hypotheses. On bigram word lattices generated from Hub4 Broadcast News speech, it reduces lattice sizes by half on average. It was also found to produce smaller lattices than the standard finite state automaton determinization and minimization algorithms. The second technique is an improved algorithm for expanding lattices with trigram language models. Instead of giving all nodes a unique trigram context, this algorithm only creates unique contexts for trigrams that are explicitly represented in the model. Backed-off trigram probabilities are encoded without node duplication by factoring the probabilities into bigram probabilities and backoff weights. Experiments on Broadcast News show that this method reduces trigram lattice sizes by a factor of 6, and reduces expansion time by more than a factor of 10. Compared to conventionally expanded lattices, recognition with the compactly expanded lattices was also found to be 40% faster, without affecting recognition accuracy.1
Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World

We introduce a method to disentangle controllable and uncontrollable factors of variation by interacting with the world. Disentanglement leads to good representations and is important when applying deep neural networks (DNNs) in fields where explanations are required. This study attempts to improve an existing reinforcement learning (RL) approach to disentangle controllable and uncontrollable factors of variation, because the method lacks a mechanism to represent uncontrollable obstacles. To address this problem, we train two DNNs simultaneously: one that represents the controllable object and another that represents uncontrollable obstacles. For stable training, we applied a pretraining approach using a model robust against uncontrollable obstacles. Simulation experiments demonstrate that the proposed model can disentangle independently controllable and uncontrollable factors without annotated data.
From Sequence to Trajectory and Vice Versa: Solving the Inverse QTC Problem and Coping with Real-World Trajectories

Spatial interactions between agents carry information of high value to human observers, as exemplified by the high-level interpretations that humans make when watching the Heider and Simmel movie, or other such videos which just contain motions of simple objects, such as points, lines and triangles. However, not all the information contained in a pair of continuous trajectories is important; and thus the need for qualitative descriptions of interaction trajectories arises. Towards that purpose, Qualitative Trajectory Calculus (QTC) has been proposed in (Van de Weghe, 2004). However, the original definition of QTC handles uncorrupted continuous-time trajectories, while real-world signals are noisy and sampled in discrete-time. Also, although QTC presents a method for transforming trajectories to qualitative descriptions, the inverse problem has not yet been studied. Thus, in this paper, after discussing several aspects of the transition from ideal QTC to discrete-time noisy QTC, we introduce a novel algorithm for solving the QTC inverse problem; i.e. transforming qualitative descriptions to archetypal trajectories that satisfy them. Both of these problems are particularly important for the successful application of qualitative trajectory calculus to Human-Robot Interaction.
Rubber Additions into Concrete and Gamma Radiation Effects on Mechanical Properties and Microwave Absorption Capacity

Rubber is the indispensable raw material for the manufacture of tires; it is obtained from plants, trees and currently can be produced synthetically. The tire rubber is mixed with compounds such as carbon black, sulfur, cement, paints, antioxidants, oils and fats, steel wire, almost etc., making impossible to recycle the tires itself. In this work, we investigate, the effects of the incorporation of ground rubber in concrete, mixture designed to establish the possibility of being used in the construction industry. The samples of concrete were addition with, 5 vol. %. , 15 vol. % and 25 vol. % of rubber. Samples with different rubber addition were irradiated by a cobalt 60 gamma source to study the effect on their mechanical compression properties and microwave absorption capacity. Likewise, the microwave absorption capacity was studied for both irradiated and the non-irradiated. It was found that between 5 vol. % and 15 vol. % of rubber addition change the mechanical properties approximately 25 %, higher rubber additions result in a decrease in a 75 % of its mechanical properties. The fracture behavior is not the expected one due to as the curves of stress vs. strain show a double slope, which is associated with the concrete porosity and rubber content. The aging with the gamma rays generates loss of mechanical properties, especially at lower rubber addition, since at content greater than 15 Vol % the radiation effect is less. These rubber additions allow moderate deformations in compression, thus contributing to the care and preservation of the environment.