Miracle-dz/UniFAR-FTUs huggingface dataset:
Title Cognitive impairment in non-1 demented oldest-old : Prevalence and relationship to cardiovascular risk factors Permalink

Objective—To determine the prevalence and types of cognitive impairment in a sample of nondemented aged 90 and older (the oldest-old) and to examine the relationships between cognitive impairment and cardiovascular risk factors. Participants—420 non-demented participants from The 90+ Study, a study of aging and dementia in the oldest-old. Participants were categorized into four non-overlapping groups: normal cognition, amnestic mild cognitive impairment (aMCI), non-amnestic MCI (naMCI), and other cognitive impairment (OCI). History of cardiovascular risk factors was assessed through self-report. Results—The overall prevalence of cognitive impairment in non-demented was 34.0% (95%CI: 29.5–38.5). The prevalence of OCI was highest (17.4%; 95%CI: 13.9–21.4) followed by aMCI (8.3%; 95%CI: 5.9–11.4) and naMCI (8.3%; 95%CI: 5.9–11.4). Normal cognition was present in 66.0% (95%CI: 61.2–70.5) of participants. History of hypertension and stroke were the only risk factors that varied between the groups, occurring more frequently in participants with naMCI (χ2=3.82; p<0.05) and OCI (χ2=5.51; p<0.05). Conclusions—This study found a high prevalence of cognitive impairment in a sample of nondemented oldest-old. We did not find a strong relationship between cardiovascular risk factors and the cognitive impairment groups other than between hypertension and naMCI and stroke and OCI. Future studies comparing the incidence of dementia in these groups will ultimately determine their predictive utility in the oldest-old.
Photostability Study on Character and Antioxidant Activity of Tomato Extract (Solanum lycopersicum l.) in Nanostructured Lipid Carrier (NLC) and Conventional Creame

The aim of this study was to investigate the ability of NLC in increasing photostability of tomato extract in term of antioxidant activity. Photostability testing on antioxidant activity of samples were conducted by accelerating method using UVB radiation 32.400 joule for 21 hours radiation. Antioxidant activity was measured by DPPH method. NLC was made by High Shear Homogenization (HPH) method at 24000 rpm for 4 cycles, while conventional creame was made by low speed at 400 rpm. The product were characterized include: pH, viscosity, and particle size. There were had difference characters and physical stability. NLC had smaller size, more homogenous and more stable than conventional creame. It was known that stability of antioxidant activity of tomato extract in NLC system higher than in conventional creame. That was showed with k value, as constanta of rate scavenging activity decreasing in antioxidant power between time (Sigma 2-tail < 0.005) of NLC and conventional creame were: 2.03x10 -2 %/hour ±0.08 (3.94) and 4.71x 10-2 %/ hour ±0.23 (4.88) respectively.
Massive Connectivity With Massive MIMO—Part I: Device Activity Detection and Channel Estimation

This two-part paper considers an uplink massive device communication scenario in which a large number of devices are connected to a base station (BS), but user traffic is sporadic so that in any given coherence interval, only a subset of users is active. The objective is to quantify the cost of active user detection and channel estimation and to characterize the overall achievable rate of a grant-free two-phase access scheme in which device activity detection and channel estimation are performed jointly using pilot sequences in the first phase and data is transmitted in the second phase. In order to accommodate a large number of simultaneously transmitting devices, this paper studies an asymptotic regime where the BS is equipped with a massive number of antennas. The main contributions of Part I of this paper are as follows. First, we note that as a consequence of having a large pool of potentially active devices but limited coherence time, the pilot sequences cannot all be orthogonal. However, despite the nonorthogonality, this paper shows that in the asymptotic massive multiple-input multiple-output regime, both the missed device detection and the false alarm probabilities for activity detection can always be made to go to zero by utilizing compressed sensing techniques that exploit sparsity in the user activity pattern. Part II of this paper further characterizes the achievable rates using the proposed scheme and quantifies the cost of using nonorthogonal pilot sequences for channel estimation in achievable rates.
Exacerbations of COPD

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. While COPD is a mainly chronic disease, a substantial number of patients suffer from exacerbations. Severe exacerbations are related to a significantly worse survival outcome. This review summarises the current knowledge on the different aspects of COPD exacerbations. The impact of risk factors and triggers such as smoking, severe airflow limitation, bronchiectasis, bacterial and viral infections and comorbidities is discussed. More severe exacerbations should be treated with β-agonists and anticholinergics as well as systemic corticosteroids. Antibiotic therapy should only be given to patients with presumed bacterial infection. Noninvasive ventilation is indicated in patients with respiratory failure. Smoking cessation is key to prevent further COPD exacerbations. Other aspects include choice of pharmacotherapy, including bronchodilators, inhaled corticosteroids, phosphodiesterase-4 inhibitors, long-term antibiotics and mucolytics. Better education and self-management as well as increased physical activity are important. Influenza and pneumococcal vaccination is recommended. Treatment of hypoxaemia and hypercapnia reduce the rate of COPD exacerbations, while most interventional bronchoscopic therapies increase exacerbation risk within the first months after the procedure. This article highlights the importance of preventing exacerbations of COPD http://ow.ly/ODQp30i5Cel
The association between sedentary behaviors during weekdays and weekend with change in body composition in young adults

Background High sedentary time has been considered an important chronic disease risk factor but there is only limited information on the association of specific sedentary behaviors on weekdays and weekend-days with body composition. The present study examines the prospective association of total sedentary time and specific sedentary behaviors during weekdays and the weekend with body composition in young adults. Methods A total of 332 adults (50% male; 27.7 ± 3.7 years) were followed over a period of 1 year. Time spent sedentary, excluding sleep (SED), and in physical activity (PA) during weekdays and weekend-days was objectively assessed every 3 months with a multi-sensor device over a period of at least 8 days. In addition, participants reported sitting time, TV time and non-work related time spent at the computer separately for weekdays and the weekend. Fat mass and fat free mass were assessed via dual x-ray absorptiometry and used to calculate percent body fat (%BF). Energy intake was estimated based on TDEE and change in body composition. Results Cross-sectional analyses showed a significant correlation between SED and body composition (0.18 ≤ r ≤ 0.34). Associations between body weight and specific sedentary behaviors were less pronounced and significant during weekdays only (r ≤ 0.16). Nevertheless, decrease in SED during weekends, rather than during weekdays, was significantly associated with subsequent decrease in %BF (β = 0.06, p <0.01). After adjusting for PA and energy intake, results for SED were no longer significant. Only the association between change in sitting time during weekends and subsequent %BF was independent from change in PA or energy intake (β%BF = 0.04, p = 0.01), while there was no significant association between TV or computer time and subsequent body composition. Conclusions The stronger prospective association between sedentary behavior during weekends with subsequent body composition emphasizes the importance of leisure time behavior in weight management.
Multiscale modelling in immunology: a review

One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases.
Adaptive learning to speed-up control of prosthetic hands: A few things everybody should know

Domain adaptation methods have been proposed to reduce the training efforts needed to control an upper-limb prosthesis by adapting well performing models from previous subjects to the new subject. These studies generally reported impressive reductions in the required number of training samples to achieve a certain level of accuracy for intact subjects. We further investigate two popular methods in this field to verify whether this result also applies to amputees. Our findings show instead that this improvement can largely be attributed to a suboptimal hyperparameter configuration. When hyperparameters are appropriately tuned, the standard approach that does not exploit prior information performs on par with the more complicated transfer learning algorithms. Additionally, earlier studies erroneously assumed that the number of training samples relates proportionally to the efforts required from the subject. However, a repetition of a movement is the atomic unit for subjects and the total number of repetitions should therefore be used as reliable measure for training efforts. Also when correcting for this mistake, we do not find any performance increase due to the use of prior models.
Network Flows That Solve Linear Equations

We study distributed network flows as solvers in continuous time for the linear algebraic equation <inline-formula> <tex-math notation="LaTeX">$\mathbf{z}=\mathbf{H}\mathbf{y}$</tex-math></inline-formula>. Each node <inline-formula> <tex-math notation="LaTeX">$i$</tex-math></inline-formula> has access to a row <inline-formula> <tex-math notation="LaTeX">${\mathbf{h}}_{i}^{\mathrm{T}}$</tex-math></inline-formula> of the matrix <inline-formula> <tex-math notation="LaTeX">$\mathbf{H}$</tex-math></inline-formula> and the corresponding entry <inline-formula> <tex-math notation="LaTeX">$z_i$</tex-math></inline-formula> in the vector <inline-formula><tex-math notation="LaTeX"> $\mathbf{z}$</tex-math></inline-formula>. The first “consensus + projection” flow under investigation consists of two terms, one from standard consensus dynamics and the other contributing to projection onto each affine subspace specified by the <inline-formula><tex-math notation="LaTeX">$\mathbf{h}_{i}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$z_i$</tex-math></inline-formula>. The second “projection consensus” flow on the other hand simply replaces the relative state feedback in consensus dynamics with projected relative state feedback. Without dwell-time assumption on switching graphs, we prove that all node states converge to a common solution of the linear algebraic equation, if there is any. The convergence is global for the “consensus + projection” flow while local for the “projection consensus” flow in the sense that the initial values must lie on the affine subspaces. If the linear equation has no exact solutions, we show that the node states can converge to a ball around the least-squares solution whose radius can be made arbitrarily small through selecting a sufficiently large gain for the “consensus + projection” flow for a fixed bidirectional graph. Semi-global convergence to approximate least-squares solutions is also demonstrated for switching balanced directed graphs under suitable conditions. It is also shown that the “projection consensus” flow drives the average of the node states to the least-squares solution with a complete graph. Numerical examples are provided as illustrations of the established results.
Optical coherence tomography angiography in the management of age-related macular degeneration

Purpose of review Optical coherence tomography angiography (OCT-A) provides rapid, flow-based imaging of the retinal and choroidal vasculature in a noninvasive manner. This review contrasts this novel technique with conventional angiography and discusses its current uses and limitations in the management of age-related macular degeneration (AMD). Recent findings Initial work with OCT-A has focused on its ability to identify choriocapillaris flow alterations in dry AMD and to sensitively detect choroidal neovascular membranes (CNVs) in neovascular AMD. Reduced choriocapillaris flow beyond the borders of geographic atrophy seen on OCT-A suggests a primary vascular cause in geographic atrophy. Longitudinal OCT-A analysis of CNV morphology has demonstrated the transition from an immature to mature CNV phenotype following treatment. Current clinical applications of OCT-A include identification of asymptomatic CNV and monitoring for CNV development in the setting of an acquired vitelliform lesion. Summary OCT-A remains a promising diagnostic tool but one still very much in evolution. Larger studies will be needed to more accurately describe its sensitivity and specificity for CNV detection and to better characterize longitudinal CNV morphologic changes. Anticipated hardware and software updates including swept-source light sources, automated montaging, and manual adjustment of interscan timing should enhance the capabilities of OCT-A in the management of AMD.
The inter-sensor radiometric comparison of SNPP VIIRS reflective solar bands with Aqua MODIS updated through June 2017

We update the effort in the radiometric evaluation of the two different versions of the calibrated sensor data records (SDRs) for the SNPP VIIRS reflective solar bands (RSBs) through direct comparison analysis with Aqua MODIS. The two SDR versions of interest are the official version generated by the Interface Data Process Segment (IDPS) system and the independent version calibrated by the NOAA Ocean Color (OC) Team. The key finding is the continual drift in the IDPS-generated radiance data for five short-wavelength RSBs (443 nm to 1238 nm), contrasting the multi-year stable result for the OC version. SNPP VIIRS M1 (410 nm) versus Aqua MODIS B8 (412 nm) continues to show drift for the IDPS-based and the OC-based comparison time series, pointing to the continual and worsening inaccuracy in Aqua MODIS B8 radiometric data that had been established by preceding studies in the previous year. The SNPP VIIRS M7 (862 nm) versus Aqua MODIS B2 (859 nm) comparison exhibits recent discontinuity in both IDPS-based and OC-based time series - the discontinuity for IDPS-generated SNPP VIIRS M7 is estimated at 0.5% upward near early October 2016, and for Aqua MODIS B2 it is 1.7% upward near mid-July 2016. The other important first-time result is the SNPP VIIRS M11 (2257 nm) versus Aqua MODIS B7 (2130 nm) comparison time series using the land-based snowy scenes of Antarctica, which demonstrates multi-year stability of SNPP VIIRS M11 and the agreement between the IDPS and the OC version of the VIIRS SDRs at this spectral range.
Challenges for Managing Candidatus Liberibacter spp. (Huanglongbing Disease Pathogen): Current Control Measures and Future Directions.

Huanglongbing (HLB; "citrus greening" disease) has caused significant damages to the global citrus industry as it has become well established in leading citrus-producing regions and continues to spread worldwide. Insecticidal control has been a critical component of HLB disease management, as there is a direct relationship between vector control and Candidatus Liberibacter spp. (i.e., the HLB pathogen) titer in HLB-infected citrus trees. In recent years, there have been substantial efforts to develop practical strategies for specifically managing Ca. Liberibacter spp. ; however, a literature review on the outcomes of such attempts is still lacking. This work summarizes the greenhouse and field studies that have documented the effects and implications of chemical-based treatments (i.e., applications of broad-spectrum antibiotics, small molecule compounds) and nonchemical measures (i.e., applications of plant-beneficial compounds, applications of inorganic fertilizers, biological control, thermotherapy) for phytopathogen control. The ongoing challenges associated with mitigating Ca. Liberibacter spp. populations at the field-scale, such as the seasonality of the phytopathogen and associated HLB disease symptoms, limitations for therapeutics to contact the phytopathogen in planta, adverse impacts of broad-spectrum treatments on plant-beneficial microbiota, and potential implications on public and ecosystem health, are also discussed.
Designer epigenome modifiers enable robust and sustained gene silencing in clinically relevant human cells

Abstract Targeted modulation of gene expression represents a valuable approach to understand the mechanisms governing gene regulation. In a therapeutic context, it can be exploited to selectively modify the aberrant expression of a disease-causing gene or to provide the target cells with a new function. Here, we have established a novel platform for achieving precision epigenome editing using designer epigenome modifiers (DEMs). DEMs combine in a single molecule a DNA binding domain based on highly specific transcription activator-like effectors (TALEs) and several effector domains capable of inducing DNA methylation and locally altering the chromatin structure to silence target gene expression. We designed DEMs to target two human genes, CCR5 and CXCR4, with the aim of epigenetically silencing their expression in primary human T lymphocytes. We observed robust and sustained target gene silencing associated with reduced chromatin accessibility, increased promoter methylation at the target sites and undetectable changes in global gene expression. Our results demonstrate that DEMs can be successfully used to silence target gene expression in primary human cells with remarkably high specificity, paving the way for the establishment of a potential new class of therapeutics.
A graph-based approach for local and global panorama imaging in cystoscopy

Inspection of the urinary bladder with an endoscope (cystoscope) is the usual procedure for early detection of bladder cancer. The very limited field of view provided by the endoscope makes it challenging to ensure, that the interior bladder wall has been examined completely. Panorama imaging techniques can be used to assist the surgeon and provide a larger view field. Different approaches have been proposed, but generating a panorama image of the entire bladder from real patient data is still a challenging research topic. We propose a graph-based and hierarchical approach to assess this problem to first generate several local panorama images, followed by a global textured three-dimensional reconstruction of the organ. In this contribution, we address details of the first level of the approach including a graph-based algorithm to deal with the challenging condition of in-vivo data. This graph strategy gives rise to a robust relocalization strategy in case of tracking failure, an effective keyframe selection process as well as the concept of building locally optimized sub-maps, which lay the ground for a global optimization process. Our results show the successful application of the method to four in-vivo data sets.
Compensating drift of mono-visual odometry using road direction sign database

Mono-Visual odometry(Mono VO) is a widely implemented method to locate the ego-motion of a camera on a mobile platform. Since it is based on concatenating relative motions between image frames, it has a weakness of error accumulation that results erroneous drift for a long-range navigation. In this paper, we propose a drift compensation method for Mono VO by leveraging publicly available road sign database. In the first process of the proposed algorithm, it estimates the relative position of the camera on a vehicle with respect to the road sign using an online database that provides the positions and dimensions of the corresponding road signs. Then, the estimated positions are integrated in the Mono VO pipeline to update the current positions to compensate the accumulated drift. Unlike the previous research, the proposed solution neither uses a post-processing of optimization nor requires a loop closure, not to mention that the required database are easily available on online. Experiments are conducted to compare the proposed method with a Mono VO algorithm and results showed that the relative position drift is bounded within 0.5% for a 3km trajectory.
Morphine Interaction with Aspirin: a Double-Blind, Crossover Trial in Healthy Volunteers

Aspirin is a cornerstone in the antiplatelet therapy for acute coronary syndromes. Coadministration of morphine may potentially influence the intestinal absorption, pharmacokinetics, and pharmacodynamics, as seen with P2Y12 inhibitors. In this trial, healthy volunteers were randomized to receive morphine (5 mg, i.v. bolus injection) at one of seven different time points before, after, or with aspirin (162 mg, p.o.) in a double-blind, placebo-controlled fashion. After a 14-day washout, subjects received placebo instead of morphine. Pharmacokinetics were determined by liquid chromatography, and aspirin’s effects were measured by platelet function tests (whole-blood platelet aggregation: multiplate, platelet plug formation: PFA-100). Morphine increased the total acetylsalicylic acid exposure by 20% compared with placebo when given simultaneously with aspirin, whereas Cmax and tmax were not altered. Morphine had no significant effect on aspirin-induced platelet inhibition. In contrast to coadministration with P2Y12 inhibitors, morphine appears to have negligible interaction with aspirin.
Semi-Supervised Image Classification With Self-Paced Cross-Task Networks

In a semi-supervised setting, direct training of a deep discriminative model on partially labeled images often suffers from overfitting and poor performance, because only a small number of labeled images are available, and errors in label propagation are, in many cases, inevitable. In this paper, we introduce an auxiliary clustering task to explore the structure of the image data, and judiciously weigh unlabeled data to alleviate the influence of ambiguous data on model training. For this purpose, we propose a cross-task network composed of two streams to jointly learn two tasks: classification and clustering. Based on the model predictions, a large number of pairwise constraints can be generated from unlabeled images, and are fed to the clustering stream. Since pairwise constraints encode weak supervision information, the clustering is tolerant of errors in labeling. Unlabeled images are weighted according to the distances to the clusters discovered, and a better discriminative model is trained on the classification stream associated with a weighted softmax loss. Furthermore, a self-paced learning paradigm is adopted to gradually train our deep model from easy examples to difficult ones. Experimental results on widely used image classification datasets confirm the effectiveness and superiority of the proposed approach.