Miracle-dz/UniFAR-FTUs huggingface dataset:
Nocardioides houyundeii sp. nov., isolated from Tibetan antelope faeces.

In the present study, we describe two novel Gram-stain-positive, irregular rod-shaped bacterial strains, 78T and 601, that had been isolated from the faeces of Tibetan antelopes at the Hoh Xil Nature Reserve, Qinghai-Tibet Plateau, China. The cells were aerobic, oxidase-negative and catalase-positive. When cultured on brain-heart infusion agar supplemented with 5 % sheep blood, colonies were cream in colour, circular, smooth and convex. Phylogenetic analysis based on the full-length 16S rRNA sequences revealed that type strain 78T and strain 601 belong to the genus Nocardioides, sharing the highest similarity to Nocardioides solisilvae JCM 31492T (98.3 %), Nocardioides gilvus XZ17T (97.4 %) and Nocardioides daejeonensis JCM 16922T (97.4 %). The average nucleotide identity values between the two novel strains and the three closely related type strains of the genus Nocardioides were lower than the 95-96 % threshold. The DNA G+C content of strains 78T and 601 were 71.2 and 71.3 mol% respectively. MK-8 (H4) was the predominant respiratory quinone and ll-2,6-diaminopimelic acid was the diagnostic diamino acid in its cell-wall peptidoglycan. Its polar lipids contained diphosphatidylglycerol, phosphatidylglycerol, phosphatidylinositol, an unidentified phospholipid and an unidentified lipid. The main whole-cell sugars were rhamnose, xylose and galactose and the major fatty acids (>10 %) were C17 : 1ω8c, iso-C16 : 0 and C18 : 1ω9c. These data supported the affiliation of strains 78T and 601 to genus Nocardioides. Based on evidence collected from the phenotypic, genotypic and phylogenetic analyses, we propose a novel species named Nocardioideshouyundeii sp. nov. The type strain is 78T (=CGMCC 4.7461T=DSM 106424T).
Sequence Classification with Human Attention

Learning attention functions requires large volumes of data, but many NLP tasks simulate human behavior, and in this paper, we show that human attention really does provide a good inductive bias on many attention functions in NLP. Specifically, we use estimated human attention derived from eye-tracking corpora to regularize attention functions in recurrent neural networks. We show substantial improvements across a range of tasks, including sentiment analysis, grammatical error detection, and detection of abusive language.
Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training

We focus on the problem of language modeling for code-switched language, in the context of automatic speech recognition (ASR). Language modeling for code-switched language is challenging for (at least) three reasons: (1) lack of available large-scale code-switched data for training; (2) lack of a replicable evaluation setup that is ASR directed yet isolates language modeling performance from the other intricacies of the ASR system; and (3) the reliance on generative modeling. We tackle these three issues: we propose an ASR-motivated evaluation setup which is decoupled from an ASR system and the choice of vocabulary, and provide an evaluation dataset for English-Spanish code-switching. This setup lends itself to a discriminative training approach, which we demonstrate to work better than generative language modeling. Finally, we explore a variety of training protocols and verify the effectiveness of training with large amounts of monolingual data followed by fine-tuning with small amounts of code-switched data, for both the generative and discriminative cases.
PHISHY - A Serious Game to Train Enterprise Users on Phishing Awareness

Game based cyber-security training for enterprise users is a topic which is relatively less researched upon. We intended to conduct an experiment on this topic with Phishy, a game based phishing awareness training, and thus find answers to the following questions: a) Do enterprise, tech-savvy users benefit from having a game based training so that this methodology could be widely used for training important topics on a large scale? b) Will such a game be engaging to the associates and will they come back to play it more than once? c) Will the game be capable of helping them? Phishy game was successfully completed by 8071 associates within a month. From their game data, it was found that the associates who completed the game showed a significant improvement in identifying phishing links. This paper explains the design, development and analysis of Phishy, an online serious game that we developed for providing phishing awareness training to enterprise users.
Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression

Bone age is an essential measure of skeletal maturity in children with growth disorders. It is typically assessed by a trained physician using radiographs of the hand and a reference model. However, it has been described that the reference models leave room for interpretation leading to a large inter-observer and intra-observer variation. In this work, we explore a novel method for automated bone age assessment to assist physicians with their estimation. It consists of a powerful combination of deep learning and Gaussian process regression. Using this combination, sensitivity of the deep learning model to rotations and flips of the input images can be exploited to increase overall predictive performance compared to only using the deep learning network. We validate our approach retrospectively on a set of 12611 radiographs of patients between 0 and 19 years of age.
A Biomechatronic EPP upper-limb prosthesis controller and its performance comparison to other topologies

Historically, Classic Extended Physiological Proprioception (EPP) as an upper-limb prosthesis control topology has been outperforming functionally all other topologies of the past. A novel Biomechatronic EPP controller has been designed to overcome shortcomings of the classic EPP control topology, and has been hypothesized to be functionally equivalent to the classic EPP topology. Using the dSpace realtime hardware platform and other mechanical and electronic components, the following were developed in the lab: (a) A Biomechatronic EPP controller, (b) a classic EPP controller, (c) an “unconnected” controller and (d) an EMG controller. All four topologies were tested in the lab using the target experiments methodology. Initial results of one subject show that performance of (a) is superior or comparable to (b) and superior to (c) and (d).
Lifetime Risks of Valvular Heart Disease and Pacemaker Use in Patients With Ankylosing Spondylitis

Background The likelihoods of valvular heart disease (VHD) and conduction abnormalities in patients with ankylosing spondylitis (ASp) are poorly defined. Knowing their lifetime risks of VHD and pacemaker use would help inform whether cardiac screening should be done. Methods and Results Patients with ASp and a comparison group without ASp were identified among US Medicare beneficiaries in 1999 to 2013. Frequencies of VHD and pacemaker use were compared in 4 age groups: 65 to 69 years, 70 to 74 years, 75 to 79 years, and 80 years or older, as were rates of valve surgeries, a measure of VHD severity, and new pacemaker insertions. Outcomes were compared between 42 327 patients with ASp and 19 211 703 patients without ASp. The prevalence of aortic valve disease in patients with ASp increased with age (2.6%, 6.7%, 10.9%, and 17.1%), as did the prevalence of mitral valve disease. Risks of VHD were slightly but significantly higher in patients with ASp (adjusted odds ratios 1.06–1.51). Rates of aortic valve replacement/repair were also higher in patients with ASp than in the comparison group (125 versus 93; 183 versus 149; 261 versus 208; 279 versus 191 per 100 000 patient‐years in the 4 age groups). Rates of mitral valve surgery did not differ between groups. Among patients with ASp, pacemaker use ranged from 1.0% to 7.6% across age groups, and was slightly higher than in controls (odds ratio range 1.11–1.32). Conclusions Lifetime risks of VHD and pacemaker use in ASp increase markedly with age, but are only slightly higher than in elderly people without ASp.
Basal cortisol levels and the relationship with clinical symptoms in multiple sclerosis: a systematic review

ABSTRACT Multiple sclerosis (MS) is a demyelinating, progressive and neurodegenerative disease. A disturbance on the hypothalamic-pituitary-adrenal axis can be observed in patients with MS, showing altered cortisol levels. We aimed to identify basal cortisol levels and verify the relationship with clinical symptoms in patients with MS. A systematic search was conducted in the databases: Pubmed, Web of Science and SCOPUS. Both higher and lower cortisol levels were associated with MS. Higher cortisol levels were associated with depression and anxiety, while lower levels were associated with depression, fatigue and urinary dysfunction. Higher cortisol levels may be associated with the progression and severity of MS.
Construction and functional characterization of a fully human anti‐CD19 chimeric antigen receptor (huCAR)‐expressing primary human T cells

Although remarkable results have been attained by adoptively transferring T cells expressing fully murine and/or humanized anti‐CD19 chimeric antigen receptors (CARs) to treat B cell malignancies, evidence of human anti‐mouse immune responses against CARs provides a rationale for the development of less immunogenic CARs. By developing a fully human CAR (huCAR), these human anti‐mouse immune responses are likely eliminated. This, perhaps, not only increases the persistence of anti‐CD19 CAR T cells—thereby reducing the risk of tumor relapse—but also facilitates administration of multiple, temporally separated doses of CAR T cells to the same recipient. To these ends, we have designed and constructed a second‐generation fully human anti‐CD19 CAR (or huCAR19) containing a fully human single‐chain variable fragment (ScFv) fused with a CD8a hinge, a 4‐1BB transmembrane domain and intracellular T cell signaling domains of 4‐1BB and CD3z. T cells expressing this CAR specifically recognized and lysed CD19+ target cells produced cytokines and proliferated in vitro. Moreover, cell volume data revealed that our huCAR construct cannot induce antigen‐independent tonic signaling in the absence of cognate antigen. Considering our results, our anti‐CD19 huCAR may overcome issues of transgene immunogenicity that plague trials utilizing CARs containing mouse‐derived ScFvs. These results suggest that this huCAR19 be safely and effectively applied for adaptive T cell immunotherapy in clinical practice.
Variants at the APOE/C1/C2/C4 Locus Modulate Cholesterol Efflux Capacity Independently of High‐Density Lipoprotein Cholesterol

Background Macrophage cholesterol efflux to high‐density lipoproteins (HDLs) is the first step of reverse cholesterol transport. The cholesterol efflux capacity (CEC) of HDL particles is a protective risk factor for coronary artery disease independent of HDL cholesterol levels. Using a genome‐wide association study approach, we aimed to identify pathways that regulate CEC in humans. Methods and Results We measured CEC in 5293 French Canadians. We tested the genetic association between 4 CEC measures and genotypes at >9 million common autosomal DNA sequence variants. These analyses yielded 10 genome‐wide significant signals (P<6.25×10−9) representing 7 loci. Five of these loci harbor genes with important roles in lipid biology (CETP,LIPC,LPL,APOA1/C3/A4/A5, and APOE /C1/C2/C4). Except for the APOE/C1/C2/C4 variant (rs141622900, P nonadjusted=1.0×10−11; P adjusted=8.8×10−9), the association signals disappear when correcting for HDL cholesterol and triglyceride levels. The additional 2 significant signals were near the PPP1CB/PLB1 and RBFOX3/ENPP7 genes. In secondary analyses, we considered candidate functional variants for 58 genes implicated in HDL biology, as well as 239 variants associated with blood lipid levels and/or coronary artery disease risk by genome‐wide association study. These analyses identified 27 significant CEC associations, implicating 5 additional loci (GCKR,LIPG,PLTP,PPARA, and TRIB1). Conclusions Our genome‐wide association study identified common genetic variation at the APOE/C1/C2/C4 locus as a major determinant of CEC that acts largely independently of HDL cholesterol. We predict that HDL‐based therapies aiming at increasing CEC will be modulated by changes in the expression of apolipoproteins in this gene cluster.
VTM: Vehicular Traffic Monitor via Images Processing of GoogleMaps

A realistic simulation scenario is instrumental for the study of transportation problems and the possible solutions that Intelligent Transportation Systems (ITS) can provide such as smart traffic lights, warning notification. In this paper we focus on providing a automatic traffic flow monitor, named Vehicular Traffic Monitor~(VTM), to extract information from GoogleMaps traffic layer. Our monitor bases on image processing and the relationship between geographical coordinates to pixel position and does not needs any interface to process vehicular flow information. VTM can be used to obtain traffic flow logs, which are the base to generate realistic, synthetic vehicular traffic traces, specially for areas where those traces are not available. Moreover, we show the traffic flow evolution along a specific day (Father's day) can vary from usual behavior, and therefore our tool is useful to obtain information of such cases.
VRmove: Design Framework for Balancing Enjoyment, Movement and Exertion in VR Games

Since the release of the HTC Vive and Oculus Rift tracking has improved, leading to virtual reality (VR) games that allow players to stand and physically move around virtual environments. Consequently, these VR games can provide players with beneficial levels of exercise. In this paper we provide a design framework for using activity sensor data within VR games called VRmove. This framework was derived from an analyses of data from studies of 18 players over 4 diverse commercial VR games to identify key elements for exertion and enjoyment: actual and perceived exertion being key for representing the gain from the fun disguising the effort and the multi-factorial element of movement involved. The rationale of this work is to demonstrate the use of the VRmove framework to inform the design of a new game. This work's core contribution is the VRmove framework, which informs the design of future VR games so they are exerting while still being enjoyable.
Developing Vicarious Calibration for Microwave Sounding Instruments Using Lunar Radiation

Accurate global observations from space are critical for global climate change study. However, atmospheric temperature trend derived from spaceborne microwave instruments remains a subject of debate, due mainly to the uncertainty in characterizing the long-term drift of instrument calibration. Thus, a highly stable target with a well-known microwave radiation is required to evaluate the long-term calibration stability. This paper develops a new model to simulate the lunar emission at microwave frequencies, and the model is then used for monitoring the stability of the Advanced Technology Microwave Sounder (ATMS) onboard Suomi NPP satellite. It is shown that the ATMS cold space view of lunar radiation agrees well with the model simulation during the past five years and this instrument is capable of serving the reference instrument for atmospheric temperature trending studies, and connecting the previous generation of microwave sounders from NOAA-15 to the future Joint Polar Satellite System Microwave Sounder onboard NOAA-20 satellite.
No Chattering and Adaptive Sliding Mode Control of a Fractional-Order Phase Converter with Disturbances and Parameter Uncertainties

Discussing the dynamical properties of various power system models is of significant importance in order to understand its complete behavior. Even though there are many literatures discussing about the chaotic behavior shown by phase converter circuits, none of them have reported the hazardous phenomenon of multistability. In this paper, we derive the fractional-order model of a phase converter circuit and investigate its dynamics. Bifurcation of the system with the parameters and fractional order are investigated. A forward and backward continuation scheme is adopted to display various coexisting attractors; the property of multistability is also discussed. Using forward and backward continuation, various coexisting attractors and the property of multistability are discussed. Two different sliding mode controllers for controlling chaotic oscillations with model disturbances and parameter uncertainties are derived, and the effectiveness of the controllers is discussed with numerical simulations.
Multispectral camera fusion increases robustness of ROI detection for biosignal estimation with nearables in real-world scenarios

Thermal cameras enable non-contact estimation of the respiratory rate (RR). Accurate estimation of RR is highly dependent on the reliable detection of the region of interest (ROI), especially when using cameras with low pixel resolution. We present a novel approach for the automatic detection of the human nose ROI, based on facial landmark detection from an RGB camera that is fused with the thermal image after tracking. We evaluated the detection rate and spatial accuracy of the novel algorithm on recordings obtained from 16 subjects under challenging detection scenarios. Results show a high detection rate (median: 100%, 5th–95th percentile: 92%– 100%) and very good spatial accuracy with an average root mean square error of 2 pixels in the detected ROI center when compared to manual labeling. Therefore, the implementation of a multispectral camera fusion algorithm is a valid strategy to improve the reliability of non-contact RR estimation with nearable devices featuring thermal cameras.
User Verification Based On Customized Sentence Reading

Speaker verification systems have been one of the most important means for user authentication on modern devices and systems such as smartphones, smart buildings, etc. Existing speaker verification systems are prone to replay attacks due to the acoustic nature of human voices. In this paper, we aim at designing a novel speaker verification system which is immune to replay attacks while achieving accurate verification results. We propose a sentence-level customization scheme, which generates different types of sentences for speaker training. The training and testing voice data is different but within the same category, which naturally avoids replay attacks and reserves the ability to identify speakers. Experiments will be conducted on both RSR2015 and NIST SRE10 databases in our future work.
A State-Space Approach for Detecting Stress from Electrodermal Activity

The human body responds to neurocognitive stress in multiple ways through its autonomic nervous system. Increases in heart rate, salivary cortisol and skin conductance level are often observed accompanying high levels of stress. Stress can also take on different forms including emotional, cognitive and motivational. While a precise definition for stress is lacking, a pertinent issue is to quantify the state of psychological stress manifested in the nervous system. State-space models have previously been applied to estimate an unobserved neural state (e.g. learning, consciousness) from physiological signal measurements and data collected during behavioral experiments. In this paper, we relate stress to the probability that a phasic driver impulse occurs in skin conductance signals. We apply state-space modeling to extracted binary measures to continuously track a stress level across episodes of cognitive and emotional stress as well as relaxation. Results demonstrate a promising approach for tracking stress through wearable devices.
Impact of Ideal Cardiovascular Health in Childhood on the Retinal Microvasculature in Midadulthood: Cardiovascular Risk in Young Finns Study

Background This study examined the association between ideal cardiovascular health (CVH) and the retinal microvasculature in midadulthood. Methods and Results The Cardiovascular Risk in Young Finns Study included children from 5 Finnish University cities, who were chosen randomly from the national population register. Participants ranged from 12 to 18 years in childhood (1986) and from 37 to 43 years in midadulthood (2011). Ideal CVH was defined according to the American Heart Association criteria. Retinal microvascular measures included diameters, lengths, length:diameter ratio, and tortuosity. From childhood to adulthood, fasting plasma glucose and blood pressure were significantly higher in those with impaired fasting glucose or diabetes mellitus. Childhood ideal CVH was negatively associated with adult arteriolar tortuosity (β=−0.008; 95% confidence interval [CI], −0.01 to −0.003; P=0.001). Improved ideal CVH from childhood to adulthood was positively associated with adult arteriolar diameter (β=0.122; 95% CI, 0.01–0.24; P=0.033) and negatively associated with adult length:diameter ratio (β=−0.666; 95% CI, −1.25 to −0.08; P=0.026). When stratified by glucose metabolism, among those with diabetes mellitus and impaired fasting glucose, there was a negative association between childhood ideal CVH and adult venular diameter (diabetes mellitus: β=−2.75; 95% CI, −5.46 to −0.04; P=0.047; impaired fasting glucose: β=−2.13; 95% CI, −4.18 to −0.08; P=0.042). Conclusions This study is the first to comprehensively examine the impact of CVH from childhood to midadulthood on quantitative measures of the retinal microvasculature. Ideal CVH in childhood and improvement in CVH from childhood to adulthood appears to have a protective effect on the retinal microvasculature in those with, without, and at risk of diabetes mellitus.
Epsilon Voting: Mechanism Design for Parameter Selection in Differential Privacy

The behavior of a differentially private system is governed by a parameter epsilon which sets a balance between protecting the privacy of individuals and returning accurate results. While a system owner may use a number of heuristics to select epsilon, existing techniques may be unresponsive to the needs of the users who's data is at risk. A promising alternative is to allow users to express their preferences for epsilon. In a system we call epsilon voting, users report the parameter values they want to a chooser mechanism, which aggregates them into a single value. We apply techniques from mechanism design to ask whether such a chooser mechanism can itself be truthful, private, anonymous, and also responsive to users. Without imposing restrictions on user preferences, the only feasible mechanisms belong to a class we call randomized dictatorships with phantoms. This is a restrictive class in which at most one user has any effect on the chosen epsilon. On the other hand, when users exhibit single-peaked preferences, a broader class of mechanisms - ones that generalize the median and other order statistics - becomes possible.