Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Associated with Substance Use in Older Homeless Adults: Results from the Hope Home Study

Background: The median age of the single adult homeless population is 50 and rising. Although the prevalence of substance use decreases as individuals age, older adults now have a higher prevalence of substance use than older adults did 10 years ago. Homeless individuals have a higher prevalence of substance use disorders than the general population. However, little is known about substance use in older homeless adults. Methods: The objective of the study was to examine prevalence of and factors associated with substance use in a population-based sample (N = 350) of homeless individuals aged 50 and older in Oakland, California. Dependent variables included moderate or greater severity illicit drug symptoms (Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) score >3) and moderate or greater alcohol symptoms (Alcohol Use Disorders Identification Test (AUDIT) score >7). Independent variables included demographics, mental health problems, and negative life course events such as physical and sexual abuse, school expulsion, and onset of homelessness. Results: Almost two thirds of participants, 64.6%, had moderate or greater severity symptoms for at least 1 illicit drug; 25.8% had moderate or greater severity alcohol symptoms. History of psychiatric hospitalization was associated with moderate or greater illicit drug symptoms (adjusted odds ratio [AOR] = 1.9, 1.0–3.6). The presence of major depressive symptoms was associated with moderate or greater severity alcohol symptoms (AOR = 1.8, 1.1–3.0). Conclusions: In this sample of older homeless adults, substance use is common. There is a need for substance use treatment programs, integrated with mental health services, which are targeted towards the needs of older homeless adults.
Preparation of Extracellular Matrix Protein Fibers for Brillouin Spectroscopy

Brillouin spectroscopy is an emerging technique in the biomedical field. It probes the mechanical properties of a sample through the interaction of visible light with thermally induced acoustic waves or phonons propagating at a speed of a few km/sec. Information on the elasticity and structure of the material is obtained in a nondestructive contactless manner, hence opening the way to in vivo applications and potential diagnosis of pathology. This work describes the application of Brillouin spectroscopy to the study of biomechanics in elastin and trypsin-digested type I collagen fibers of the extracellular matrix. Fibrous proteins of the extracellular matrix are the building blocks of biological tissues and investigating their mechanical and physical behavior is key to establishing structure-function relationships in normal tissues and the changes which occur in disease. The procedures of sample preparation followed by measurement of Brillouin spectra using a reflective substrate are presented together with details of the optical system and methods of spectral data analysis.
Modeling the Anisotropic Reflectance of a Surface with Microstructure Engineered to Obtain Visible Contrast After Rotation

Engineering of surface structure to obtain specific anisotropic reflectance properties has interesting applications in large scale production of plastic items. In recent work, surface structure has been engineered to obtain visible reflectance contrast when observing a surface before and after rotating it 90 degrees around its normal axis. We build an analytic anisotropic reflectance model based on the microstructure engineered to obtain such contrast. Using our model to render synthetic images, we predict the above mentioned contrasts and compare our predictions with the measurements reported in previous work. The benefit of an analytical model like the one we provide is its potential to be used in computer vision for estimating the quality of a surface sample. The quality of a sample is indicated by the resemblance of camera-based contrast measurements with contrasts predicted for an idealized surface structure. Our predictive model is also useful in optimization of the microstructure configuration, where the objective for example could be to maximize reflectance contrast.
Exploiting Convolution Filter Patterns for Transfer Learning

In this paper, we introduce a new regularization technique for transfer learning. The aim of the proposed approach is to capture statistical relationships among convolution filters learned from a well-trained network and transfer this knowledge to another network. Since convolution filters of the prevalent deep Convolutional Neural Network (CNN) models share a number of similar patterns, in order to speed up the learning procedure, we capture such correlations by Gaussian Mixture Models (GMMs) and transfer them using a regularization term. We have conducted extensive experiments on the CIFAR10, Places2, and CM-Places datasets to assess generalizability, task transferability, and cross-model transferability of the proposed approach, respectively. The experimental results show that the feature representations have efficiently been learned and transferred through the proposed statistical regularization scheme. Moreover, our method is an architecture independent approach, which is applicable for a variety of CNN architectures.
Needleless electro-spun nanofibers used for filtration of small particles

A composite aerosol filter media was prepared by depositing nanofibers on the non-woven fabrics substrate using needleless electrospinning technique. The polyvinyl alcohol nanofibers with mean diameters of ca. 100 nm were used as top layers. The filtration performance was evaluated by measuring the filtration of sodium chloride nanoparticles (75±20 nm) through the filters. It was found that the filtration efficiency of the composite filter media for nanoparticles was increased along with the thickness of nanofibers mats which was controlled by the collection time during the electrospinning. The multi-layer arrangement for fabrication of the composite filter can achieve high filtration efficiency (up to 99.95%) which was comparable to commercial high efficiency particulate air filters but with higher quality factor and less mass.
Magneto-rheological defects and failures: A review

Magneto-rheological fluid is the colloidal suspension of micron sized magnetic particles in a carrier fluid where defects and failures occur at many circumstances. This paper presents a review on defects and failures of magneto-rheological fluid in engineering applications. The most significant defect is hard cake which developed due to re-dispersion difficulties of remnant particles magnetization, leaving the magneto-rheological fluid ineffective. Clumping effect on the other hand is a separation of carrier fluid from the magnetic particles when magneto-rheological fluid is being exposed to higher magnetic field for an extended period of time. As clumping occurred, it leads to Fluid Particle Separation (FPS) which is believed altering the strength distribution of magneto-rheological fluid and therefore reducing the squeezing force. Another significant failure is magnetic particles oxidation of the magneto-rheological fluid. This paper also will discuss on stability problems which is the most challenged issue in magneto-rheological fluid technology. With the comprehensive review in this paper, researcher can design materials of magneto-rheological fluid for better properties.
Development and validation of empirical indices to assess the insulinaemic potential of diet and lifestyle

Abstract The glycaemic and insulin indices assess postprandial glycaemic and insulin response to foods, respectively, which may not reflect the long-term effects of diet on insulin response. We developed and evaluated the validity of four empirical indices to assess the insulinaemic potential of usual diets and lifestyles, using dietary, lifestyle and biomarker data from the Nurses’ Health Study (NHS, n 5812 for hyperinsulinaemia, n 3929 for insulin resistance). The four indices were as follows: the empirical dietary index for hyperinsulinaemia (EDIH) and the empirical lifestyle index for hyperinsulinaemia (ELIH); the empirical dietary index for insulin resistance (EDIR) and the empirical lifestyle index for insulin resistance (ELIR). We entered thirty-nine FFQ-derived food groups in stepwise linear regression models, and defined indices as patterns most predictive of fasting plasma C-peptide, for the hyperinsulinaemia pathway (EDIH and ELIH), and of theTAG:HDL-cholesterol ratio, for the insulin-resistance pathway (EDIR and ELIR). We evaluated the validity of indices in two independent samples from NHS-II and Health Professionals Follow-up Study (HPFS) using multivariable-adjusted linear regression analyses to calculate relative concentrations of biomarkers. The EDIH is comprised of eighteen food groups; thirteen were positively associated with C-peptide and five were inversely associated. The EDIR is comprised of eighteen food groups; ten were positively associated with TAG:HDL-cholesterol and eight were inversely associated. Lifestyle indices had fewer dietary components, and included BMI and physical activity as components. In the validation samples, all indices significantly predicted biomarker concentrations – for example, the relative concentrations of the corresponding biomarkers comparing extreme index quintiles in the HPFS were EDIH, 1·29 (95 % CI 1·22, 1·37); ELIH, 1·78 (95 % CI 1·68, 1·88); EDIR, 1·44 (95 % CI 1·34, 1·55); and ELIR, 2·03 (95 % CI 1·89, 2·19); all P trend<0·0001. The robust associations of these novel hypothesis-driven indices with insulin response biomarker concentrations suggest their usefulness in assessing the ability of whole diets and lifestyles to stimulate and/or sustain insulin secretion.
Aerobic exercise prior to task‐specific training to improve poststroke motor function: A case series

BACKGROUND Aerobic exercise can improve upper limb motor function in both healthy and stroke populations. Research in animals after stroke has shown that aerobic exercise combined with forelimb motor training improved forelimb motor function more than aerobic exercise or motor training alone. There is a lack of knowledge about this combined intervention in humans after stroke. PURPOSE These 2 case reports describe the exploratory implementation of a combined aerobic exercise and task-specific training intervention to improve upper limb motor function in one person in subacute stroke recovery and one person in chronic stroke recovery. METHODS Case descriptions Subacute participant: 45-year-old female, 3 months after ischemic stroke resulting in left-sided hemiparesis affecting her non-dominant upper limb, with a baseline Action Research Arm Test (ARAT) score of 10/57 and Wolf Motor Function Test (WMFT) score of 39/75. Chronic participant: 69-year-old female, 14 years after ischemic stroke resulting in right-sided hemiparesis affecting her non-dominant upper limb, with a baseline ARAT score of 13/57 and WMFT score of 34/75. Intervention Participants performed 30 min of lower limb cycling immediately prior to 30 min of upper limb task-specific training. Sessions were undertaken 3 times a week for 8 weeks in a university rehabilitation laboratory. Results The combined intervention was feasible and perceived as acceptable and beneficial. Participants improved their upper limb motor function on the ARAT (subacute participant = 4 points; chronic participant = 2 points) and WMFT (subacute participant = 5 points; chronic participant = 3 points). Participants improved their aerobic fitness (subacute participant = +4.66 ml O2 /kg/min; chronic participant = +7.34 ml O2 /kg/min) and 6-minute walking distance (subacute participant = +50 m; chronic participant = +37 m). Discussion Combining aerobic exercise with task-specific training may be a worthwhile therapeutic approach to improve upper limb motor function suitable for persons in the subacute or chronic phase after stroke.
Carbon deposition reaction based on heating recycling gas of oxygen blast furnaces

Taking the heating process of recycling-gas for oxygen blast furnaces as a research background,carbon deposition behavior in heating at higher CO and H2volume fractions was investigated under a laboratory condition. The results indicate that temperature and CO2volume fraction are important factors for carbon deposition. In the temperature range of 300 ℃ to 700 ℃,the carbon deposition rate increases with the increase of temperature below 500 ℃,but deceases when above 500 ℃. The carbon deposition includes CO decomposition and carbon deposition reaction by the hybrid of CO and H2,each possible role of which was analyzed through comparing the thermodynamic theory and experimental phenomena in the carbon deposition. The morphology of deposited carbon and the carbon deposition behavior in heating from 500 ℃ to 700 ℃ were investigated by scanning electron microscopy. In addition,the carbon deposition rate decreases gradually with the increasing of CO2volume fraction at 500 ℃ and 600 ℃,and this inhibition effect on the carbon deposition behavior is greater at 500 ℃.
Ginkgo and Warfarin Interaction in a Large Veterans Administration Population

Ginkgo biloba is a widely used herbal product that could potentially have a severe interaction with warfarin, which is the most frequently prescribed anticoagulant agent in North America. Literature, however, provides conflicting evidence on the presence and severity of the interaction. In this study, we developed text processing methods to extract the ginkgo usage and combined it with prescription data on warfarin from a very large clinical data respository. Our statistical analysis suggests that taking concurrently with warfarin, gingko does significantly increase patients' risk of a bleeding adverse event (hazard ratio = 1.38, 95%CI: 1.20 to 1.58, p<.001). This study also is the first attempt of using a large medical record databaseto confirm a suspected herb-drug interaction.
Iron Concentration in Deep Gray Matter Structures is Associated with Worse Visual Memory Performance in Healthy Young Adults

Abnormally high deposition of iron can contribute to neurodegenerative disorders with cognitive impairment. Since previous studies investigating cognition-brain iron accumulation relationships focused on elderly people, our aim was to explore the association between iron concentration in subcortical nuclei and two types of memory performances in a healthy young population. Gender difference was found only in the globus pallidus. Our results showed that iron load characterized by R2* value on the MRI in the caudate and putamen was related to visual memory, while verbal memory was unrelated to iron concentration.
Ultrastructure of Shewanella oneidensis MR-1 nanowires revealed by electron cryotomography

Significance Recent findings from in vivo fluorescence and immunolabeling measurements hinted at the possible role of outer membrane (OM) extensions as Shewanella oneidensis MR-1 nanowires. However, a detailed understanding of the architecture and electron transport mechanism along OM extensions was lacking. In this work, we report a unique setup for correlative light and electron microscopy of Shewanella OM extensions and demonstrate that they are chains of interconnected outer membrane vesicles with densities, consistent with periplasmic and OM cytochromes, distributed along their length. We propose, based on the packing density of cytochromes measured from electron cryotomograms, that the electron transport mechanism involves a combination of direct electron hopping and diffusion of electron carriers. Bacterial nanowires have garnered recent interest as a proposed extracellular electron transfer (EET) pathway that links the bacterial electron transport chain to solid-phase electron acceptors away from the cell. Recent studies showed that Shewanella oneidensis MR-1 produces outer membrane (OM) and periplasmic extensions that contain EET components and hinted at their possible role as bacterial nanowires. However, their fine structure and distribution of cytochrome electron carriers under native conditions remained unclear, making it difficult to evaluate the potential electron transport (ET) mechanism along OM extensions. Here, we report high-resolution images of S. oneidensis OM extensions, using electron cryotomography (ECT). We developed a robust method for fluorescence light microscopy imaging of OM extension growth on electron microscopy grids and used correlative light and electron microscopy to identify and image the same structures by ECT. Our results reveal that S. oneidensis OM extensions are dynamic chains of interconnected outer membrane vesicles (OMVs) with variable dimensions, curvature, and extent of tubulation. Junction densities that potentially stabilize OMV chains are seen between neighboring vesicles in cryotomograms. By comparing wild type and a cytochrome gene deletion mutant, our ECT results provide the likely positions and packing of periplasmic and outer membrane proteins consistent with cytochromes. Based on the observed cytochrome packing density, we propose a plausible ET path along the OM extensions involving a combination of direct hopping and cytochrome diffusion. A mean-field calculation, informed by the observed ECT cytochrome density, supports this proposal by revealing ET rates on par with a fully packed cytochrome network.
Efficient Convolutional Network Learning Using Parametric Log Based Dual-Tree Wavelet ScatterNet

We propose a DTCWT ScatterNet Convolutional Neural Network (DTSCNN) formed by replacing the first few layers of a CNN network with a parametric log based DTCWT ScatterNet. The ScatterNet extracts edge based invariant representations that are used by the later layers of the CNN to learn high-level features. This improves the training of the network as the later layers can learn more complex patterns from the start of learning because the edge representations are already present. The efficient learning of the DTSCNN network is demonstrated on CIFAR-10 and Caltech-101 datasets. The generic nature of the ScatterNet front-end is shown by an equivalent performance to pretrained CNN front-ends. A comparison with the state-of-the-art on CIFAR-10 and Caltech-101 datasets is also presented.
Chance of surgery in adult congenital heart disease

Background Young patients with congenital heart disease reaching adulthood face mandatory transition to adult cardiology. Their new cardiologist needs to assess the chances of major future events such as surgery. Using a large national registry, we assessed if patient characteristics at the age of 18 years could predict the chance of congenital heart surgery in adulthood. Design and methods Of 10,300 patients from the CONCOR national registry, we used general patient characteristics at age 18 years, underlying congenital heart defect, history of complications, and interventions in childhood as potential predictors of congenital heart surgery occurring from age 18 years up to age 40 and 60 years. Cox regression was used to calculate hazard ratios with 95% confidence intervals. Analyses were performed separately for all congenital heart surgery and for valvular surgery alone. Results Altogether 2427 patients underwent congenital heart surgery after age 18 years, 1389 of whom underwent valvular surgery. Underlying heart defect, male sex, multiple defects, childhood endocarditis, supraventricular arrhythmia, aortic complications and paediatric cardiovascular surgery, independently predicted adult congenital heart surgery. The mean chance of congenital heart surgery was 22% up to age 40 and 43% up to age 60 years; individual chances spanned from 9–68% up to age 40 and from 19–93% up to age 60 years. Conclusion At the time of transition from paediatric to adult cardiology, an easily obtainable set of characteristics of patients with congenital heart disease can meaningfully inform cardiologists about the patient's individual chance of surgery in adulthood. Our findings warrant validation in other cohorts.
Is the current level of training in the use of equipment for prehospital radio communication sufficient? A cross-sectional study among prehospital physicians in Denmark

Background Physicians working in prehospital care are expected to handle radio communication both within their own sector as well as with other divisions of the National Emergency Services. To date, no study has been conducted on the level of training received by physicians in the use of the equipment provided or on the level of competency acquired by physicians. Methods In order to investigate the self-assessed skill level acquired in the use of the TETRA (TErrestrial Trunked RAdio) authority radio for communication in a prehospital setting, a cross-sectional study was conducted by questionnaire circulated to all 454 physicians working in the Danish Emergency Medical Services. Results A lack of training was found among physicians working in prehospital care in Denmark in relation to the proper use of essential communication equipment. Prior to starting their first shift in a prehospital setting 38% of physicians reported having received no training in the use of the equipment, while 80% of physicians reported having received one1 hour of training or less. Among the majority of physicians their current level of training was sufficient for their everyday needs for prehospital communication but for 28% of physicians their current level of training was insufficient as they were unable to handle communication at this level. Conclusion As the first study in its field, this study investigated the training received in the use of essential communication equipment among physicians working in prehospital care in Denmark. The study found that competency does not appear to have been prioritised as highly as other technical skills needed to function in these settings. For the majority of physicians their current level of training was sufficient for everyday use but for a substantial minority further training is required, especially if the redundancy of the prehospital system is to be preserved.
Monitoring impact damaging of thermoplastic composites

Thermoplastic composites are becoming ever more attractive also to the aeronautical sector. The main advantage lies in the possibility to modify the interface strength of polypropylene based laminates by adjusting the composition of the matrix. Understanding these aspects is of great importance to establish a possible link between the material toughness and the matrix ingredients. The aim of the present work is to ascertain the ability of an infrared imaging device to visualize any change, in the material behaviour to low energy impact, induced by changes in the matrix composition. Attention is given to image processing algorithms; in particular, an original procedure to measure the extension of the impact-affected area is proposed.
Particle Filter Based Probabilistic Forced Alignment for Continuous Gesture Recognition

In this paper, we propose a novel particle filter based probabilistic forced alignment approach for training spatiotemporal deep neural networks using weak border level annotations. The proposed method jointly learns to localize and recognize isolated instances in continuous streams. This is done by drawing training volumes from a prior distribution of likely regions and training a discriminative 3D-CNN from this data. The classifier is then used to calculate the posterior distribution by scoring the training examples and using this as the prior for the next sampling stage. We apply the proposed approach to the challenging task of large-scale user-independent continuous gesture recognition. We evaluate the performance on the popular ChaLearn 2016 Continuous Gesture Recognition (ConGD) dataset. Our method surpasses state-of-the-art results by obtaining 0.3646 and 0.3744 Mean Jaccard Index Score on the validation and test sets of ConGD, respectively. Furthermore, we participated in the ChaLearn 2017 Continuous Gesture Recognition Challenge and was ranked 3rd. It should be noted that our method is learner independent, it can be easily combined with other approaches.