Miracle-dz/UniFAR-FTUs huggingface dataset:
Near-Field Characterization of Photonic Nanodevices

The increasing density of data transmission, speed of all- optical signal processing, and demand for higher resolution microscopy and spectroscopy stimulate the development of the nanophotonics. Near-field microscopy is not limited by light diffraction and thus it can achieve sufficiently subwavelength resolution. Therefore this approach is perfect for nanophotonic device characterization. Heterodyne detection allows resolution of the optical phase and improves signal-to-noise performance in near-field microscopy. In this thesis we describe a Heterodyne Near-field Scanning Optical Microscope (HNSOM) and apply this approach to characterization of several classes of the photonic nanodevices. First, possible effects of the microscope probe are analyzed and experimentally studied. We show that a metal-coated NSOM probe can introduce loss to the waveguides and change the quality factor and resonant wavelength of the microring resonators. These effects should be taken into account especially for characterization of highly resonant photonic structures. Then various Photonic Crystal (PhC) devices are studied using the HNSOM. The modal structure of the single line defect PhC waveguide is found and the losses between this component and the channel waveguide are estimated. Using near-field characterization the performance of the self- collimating PhC lattice and the PhC polarization beam splitter are demonstrated. Another approach in nanophotonic device design is to directly transfer free- space functionality to a chip using metamaterials with refractive index variation on a deeply subwavelength scale. Such materials can be described using effective medium theory and have an index of refraction which depends on the structure period, filling factor and light polarization. Several photonic nanodevices utilizing this approach including a planar graded index lens are created and characterized using the HNSOM technique. The viability of the concept is confirmed in these measurements, some fabrication imperfections are found as well. The HNSOM setup is further enhanced by adding the low-coherence measurement capability which allows local study of the dispersive properties of the photonic nanodevices. The application of the technique to the characterization of group indices of refraction of silicon waveguides is shown.
Robust image classification by coupling low rank and collaborative representation graphs

A single graph cannot comprehensively describe the true relationship among samples with high dimensionality, especially for the graph-based methods which directly calculate the distances among samples in the Euclidean space. To further improve the performance of the method based on the presentation graph, in this paper we propose a new composite graph, called as low rank representation and collaborative representation (LRRCR) graph. The proposed LRRCR graph can obtain more informative knowledge for robust image classification. The experimental results on three real face image data sets show that the proposed method has better performance when compared to the traditional ones.
Gallic acid attenuates hypertension, cardiac remodeling, and fibrosis in mice with NG-nitro-L-arginine methyl ester-induced hypertension via regulation of histone deacetylase 1 or histone deacetylase 2

Objective: Gallic acid, a natural chemical found in plants, has been reported to show antioxidant, anticancer, and anti-inflammatory effects. We investigated the efficacy of a short-term or long-term treatment with gallic acid in NG-nitro-L-arginine methyl ester (L-NAME)-induced hypertensive mice and the underlying regulatory mechanism. Methods: Hypertension was sufficiently induced after 2 weeks of L-NAME administration. Cardiac remodeling was assessed by echocardiography. Hypertrophic markers, transcription factors, and fibrosis-related gene expression were evaluated by quantitative real-time polymerase chain reaction and western blotting. Results: Gallic acid effectively lowered SBP, regardless of the administration route (intraperitoneal or oral). L-NAME increased the left ventricular (LV) thickness without an increase in the total heart weight. Weekly echocardiography demonstrated that gallic acid significantly reduced LV posterior wall and septum thickness in chronic L-NAME mice from 3 to 7 weeks. The administration of gallic acid to mice showed a dual preventive and therapeutic effect on the L-NAME-induced LV remodeling. The effect was associated with the suppression of the gene expression of hypertrophy markers and the GATA-binding factor 6 (GATA6) transcription factor. Short-term or long-term treatment with gallic acid attenuated cardiac fibrosis and reduced the expression of histone deacetylase 1 and 2 in H9c2 cells and in rat primary cardiac fibroblasts, as well as in vivo. Small interfering RNA knockdown confirmed the association of these enzymes with L-NAME-induced cardiac remodeling and fibrosis. Conclusion: These results suggested that gallic acid may be a potential therapeutic agent for the treatment of cardiovascular diseases with hypertension and cardiac fibrosis.
Clinical Significance of Serum Adiponectin and Resistin Levels in Liver Cirrhosis.

INTRODUCTION Adiponectin and resistin levels are increased in patients with cirrhosis, but it prognostic significance is unknown. We sought to investigate the factors associated with adiponectin and resistin levels and its clinical significance in patients with cirrhosis. MATERIALS AND METHODS This was a prospective cohort study that included 122 subjects with cirrhosis who attended an outpatient clinic and were initially evaluated in 2012. Serum adiponectin and resistin levels were measured in samples collected in 2012 (adiponectin and resistin) and 2014 (adiponectin). Thirty healthy subjects served as a control group. RESULTS Higher adiponectin (21.59 μ g/mL vs. 12.52 μg/mL, P < 0.001) and resistin levels (3.83 ng/mL vs. 2.66 ng/mL, P < 0.001) were observed among patients with cirrhosis compared to controls. Patients classified as Child-Pugh B/C had higher adiponectin levels in relation to Child-Pugh A patients. At second measurement, adiponectin levels increased significantly in non-transplant patients and decreased in liver transplant recipients. Univariate Cox analysis showed that among patients with alcoholic liver disease, adiponectin levels were associated with lower transplant-free survival (HR = 1.034, 95% CI 1.006 - 1.062, P = 0.016). The transplant-free survival was significantly lower among patients with alcoholic liver disease and adiponectin ≥ 17 μg/mL (26.55 months, 95% CI 21.40-31.70) as compared to those with levels < 17 μg/mL (33.76 months, 95% CI 30.70-36.82) (P = 0.045). No relationship was found between the levels of resistin and survival. CONCLUSION Adiponectin but not resistin levels were associated with intensity of liver dysfunction and worse prognosis in patients with alcoholic liver disease, suggesting a potential as a prognostic biomarker.
Influence Maximization in Online Social Networks

Starting with the earliest studies showing that the spread of new trends, information, and innovations is closely related to the social influence exerted on people by their social networks, the research on social influence theory took off, providing remarkable evidence on social influence induced viral phenomena. Fueled by the extreme popularity of online social networks and social media, computational social influence has emerged as a subfield of data mining whose goal is to analyze and optimize social influence using computational frameworks such as algorithm design and theoretical modeling. One of the fundamental problems in this field is the problem of influence maximization, primarily motivated by the application of viral marketing. The objective is to identify a small set of users in a social network who, when convinced to adopt a product, shall influence others in the network in a manner that leads to a large number of adoptions. In this tutorial, we extensively survey the research on social influence propagation and maximization, with a focus on the recent algorithmic and theoretical advances. To this end, we provide detailed reviews of the latest research effort devoted to (i) improving the efficiency and scalability of the influence maximization algorithms; (ii) context-aware modeling of the influence maximization problem to better capture real-world marketing scenarios; (iii) modeling and learning of real-world social influence; (iv) bridging the gap between social advertising and viral marketing.
Integrated Text Mining and Chemoinformatics Analysis Associates Diet to Health Benefit at Molecular Level

Awareness that disease susceptibility is not only dependent on genetic make up, but can be affected by lifestyle decisions, has brought more attention to the role of diet. However, food is often treated as a black box, or the focus is limited to few, well-studied compounds, such as polyphenols, lipids and nutrients. In this work, we applied text mining and Naïve Bayes classification to assemble the knowledge space of food-phytochemical and food-disease associations, where we distinguish between disease prevention/amelioration and disease progression. We subsequently searched for frequently occurring phytochemical-disease pairs and we identified 20,654 phytochemicals from 16,102 plants associated to 1,592 human disease phenotypes. We selected colon cancer as a case study and analyzed our results in three directions; i) one stop legacy knowledge-shop for the effect of food on disease, ii) discovery of novel bioactive compounds with drug-like properties, and iii) discovery of novel health benefits from foods. This works represents a systematized approach to the association of food with health effect, and provides the phytochemical layer of information for nutritional systems biology research.
Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network

Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA.
Accuracy of a step counter during treadmill and daily life walking by healthy adults and patients with cardiac disease

Background Step counters have been used to observe activity and support physical activity, but there is limited evidence on their accuracy. Objective The purpose was to investigate the step accuracy of the Fitbit Zip (Zip) in healthy adults during treadmill walking and in patients with cardiac disease while hospitalised at home. Methods Twenty healthy adults aged 39±13.79 (mean ±SD) wore four Zips while walking on a treadmill at different speeds (1.7–6.1 km/hour), and 24 patients with cardiac disease (age 67±10.03) wore a Zip for 24 hours during hospitalisation and for 4 weeks thereafter at home. A Shimmer3 device was used as a criterion standard. Results At a treadmill speed of 3.6 km/hour, the relative error (±SD) for the Zips on the upper body was −0.02±0.67 on the right side and −0.09 (0.67) on the left side. For the Zips on the waist, this was 0.08±0.71 for the right side and -0.08 (0.47) on the left side. At a treadmill speed of 3.6 km/hour and higher, the average per cent of relative error was <3%. The 24-hour test for the hospitalised patients showed a relative error of −47.15±24.11 (interclass correlation coefficient (ICC): 0.60), and for the 24-hour test at home, the relative error was −27.51±28.78 (ICC: 0.87). Thus, none of the 24-hour tests had less than the expected 20% error. In time periods of evident walking during the 24 h test, the Zip had an average per cent relative error of <3% at 3.6 km/hour and higher speeds. Conclusions A speed of 3.6 km/hour or higher is required to expect acceptable accuracy in step measurement using a Zip, on a treadmill and in real life. Inaccuracies are directly related to slow speeds, which might be a problem for patients with cardiac disease who walk at a slow pace.
1 Aptamers Selected for Recognizing Amyloid 2 β-protein — A Case for Cautious Optimism 3

Aptamers are versatile oligonucleotide ligands used for molecular recognition of diverse 8 targets. However, application of aptamers to the field of amyloid β-protein (Aβ) has been limited 9 so far. Aβ is an intrinsically disordered protein that exists in a dynamic conformational 10 equilibrium, presenting time-dependent ensembles of short-lived, metastable structures and 11 assemblies that have been generally difficult to isolate and characterize. Moreover, despite 12 understanding of potential physiological roles of Aβ, this peptide has been linked to the 13 pathogenesis of Alzheimer disease, and its pathogenic roles remain controversial. Accumulated 14 scientific evidence thus far highlights undesirable or nonspecific interactions between selected 15 aptamers and different Aβ assemblies likely due to metastable nature of Aβ or inherent affinity of 16 RNA oligonucleotides to β-sheet-rich fibrillar structures of amyloidogenic proteins. Accordingly, 17 lessons drawn from Aβ–aptamer studies emphasize that purity and uniformity of the protein 18 target and rigorous characterization of aptamers’ specificity are important for realizing and 19 garnering the full potential of aptamers selected for recongizing Aβ or other intrinsically 20 disordered proteins. This review summarizes studies of aptamers selected for recognizing different 21 Aβ assemblies and highlights controversies, difficulties, and limitations of such studies. 22
Pilot Feasibility Study of a Digital Storytelling Intervention for Immigrant and Refugee Adults With Diabetes

Purpose The purpose of this pilot feasibility project was to examine the potential effectiveness of a digital storytelling intervention designed through a community-based participatory research (CBPR) approach for immigrants and refugees with type 2 diabetes mellitus (T2DM). Methods The intervention was a 12-minute culturally and linguistically tailored video consisting of an introduction, 4 stories, and a concluding educational message. A structured interview was used to assess the intervention for acceptability, interest level, and usefulness among 25 participants with T2DM (15 Latino, 10 Somali) across 5 primary care clinical sites. After watching the video, participants rated their confidence and motivation about managing T2DM as a result of the intervention. Baseline A1C and follow-up values (up to 6 months) were abstracted from medical records. Results All participants reported that the intervention got their attention, was interesting, and was useful; 96% reported that they were more confident about managing their T2DM than before they watched the video, and 92% reported that the video motivated them to change a specific behavior related to T2DM self-management. The mean baseline A1C level for the intervention participants was 9.3% (78 mmol/mol). The change from baseline to first follow-up A1C level was −0.8% (−10 mmol/mol) (P < .05). Conclusions Implementation of a digital storytelling intervention for T2DM among immigrant populations in primary care settings is feasible and resulted in self-rated improvement in psychosocial constructs that are associated with healthy T2DM self-management behaviors, and there was some evidence of improvement in glycemic control. A large-scale efficacy trial of the intervention is warranted.
Paper as Active Layer in Inkjet-Printed Capacitive Humidity Sensors

An inkjet-printed relative humidity sensor based on capacitive changes which responds to different humidity levels in the environment is presented in this work. The inkjet-printed silver interdigitated electrodes configuration on the paper substrate allowed for the fabrication of a functional proof-of-concept of the relative humidity sensor, by using the paper itself as a sensing material. The sensor sensitivity in terms of relative humidity changes was calculated to be around 2 pF/RH %. The response time against different temperature steps from 3 to 85 °C was fairly constant (about 4–5 min), and it was considered fast for the aimed application, a smart label.
Aalborg Universitet Thermal Tracking of Sports Players

We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920× 480 pixels.
Implicit discourse relation identification based on tree structure neural network

This paper presents a tree structure neural network to predict the sense of implicit discourse relation in English. Tree structure neural network, also called recursive neural network, has been proved to be powerful in modeling compositionality in natural language using parse tree based structural representations. By integrating the semantic information along the parse trees, the tree structure neural network shows its superiority in capturing the structure information and composition semantics, which is meaningful for the deep semantic problems, such as sentiment analysis and discourse structure understanding. Experimental results obtained on Penn Discourse Tree Bank show that the tree structure neural network is more effective to predict the logical semantic relations between discourse texts when compared with the traditional shallow feature classifiers and sequential deep semantic models.
Investigation of CAV1/CAV2 rs4236601 and CDKN2B-AS1 rs2157719 in primary open-angle glaucoma patients from Brazil

ABSTRACT Large-scale genome-wide association studies have identified several susceptibility variants associated with the risk of primary open-angle glaucoma (POAG), among which rs4236601 (CAV1/CAV2) at chromosome 7q31 and rs2157719 at chromosome 9p21 (CDKN2B-AS1). The purpose of this study was to investigate whether these variants contribute to the incidence of POAG in a sample of the Brazilian Southeastern population and to determine the best-fitted genetic model for these single nucleotide polymorphisms (SNPs). A case-control study with 557 individuals, 310 with POAG, and 247 controls was conducted through PCR and direct sequencing. We observed a significant effect of the heterozygous genotype (G/A) of rs2157719 that occurred more frequently in the control group (p = 0.0004; OR: 0.517, CI 95%: 0.357–0.745). Allele frequencies also differed between cases and controls (p = 0.006; OR: 0.694, CI 95%: 0.522–0.922) with the best-fitted genetic model for rs2157719 being the codominant model. No differences were observed for genotype and allele distributions in relation to rs4236601 in the CAV1/CAV2 region. The association of rs2157719 (CDKN2B-AS1) with the POAG phenotype corroborates previously published results, reinforcing the importance of this variant in POAG etiology.
Friction and Wear Properties of Si3N4/Carbon Fiber Composites with Aligned Microstructure

The friction and wear properties of silicon nitride/carbon fiber composites have been assessed and compared with monolithic Si3N4. Three different types of composites have been produced; one in which both the Si3N4 grains and the carbon fibers were aligned, one in which only the fibers had alignment, and a third where both the grains and fibers had random orientation. The friction coefficients of all of the composites, following running in, were around 0.2–0.3, typically less than one-third of that of the monolithic material. However there was no significant difference in friction coefficient between the three different types of composite. The specific wear rates of all the materials decreased with sliding distance and those of the composites were lower than the monolithic material. Among the composites, the wear rate of the one with aligned fibers in a randomly oriented Si3N4 matrix showed no dependence on sliding direction relative to the fiber alignment, and the specific wear rates of these samples were similar to that of the randomly oriented fiber composite, indicating little effect of fiber alignment alone on the wear properties under the present testing conditions. However, the specific wear rate of the composite with both fiber and grain alignment showed directional dependence. Grain cracking was observed perpendicular to the sliding direction, and the Spara specimen, in which the sliding direction was parallel to the Si3N4 grain alignment, showed higher wear rates than the Sperp and N samples of this composite. Such cracks are perpendicular to the major axis of the grains in the Spara sample and are thought to lead to easier removal of grains following their cracking under the tensile stresses induced particularly during the running in period.
Phenotypic screening reveals TNFR2 as a promising target for cancer immunotherapy

Antibodies that target cell-surface molecules on T cells can enhance anti-tumor immune responses, resulting in sustained immune-mediated control of cancer. We set out to find new cancer immunotherapy targets by phenotypic screening on human regulatory T (Treg) cells and report the discovery of novel activators of tumor necrosis factor receptor 2 (TNFR2) and a potential role for this target in immunotherapy. A diverse phage display library was screened to find antibody mimetics with preferential binding to Treg cells, the most Treg-selective of which were all, without exception, found to bind specifically to TNFR2. A subset of these TNFR2 binders were found to agonise the receptor, inducing iκ-B degradation and NF-κB pathway signalling in vitro. TNFR2 was found to be expressed by tumor-infiltrating Treg cells, and to a lesser extent Teff cells, from three lung cancer patients, and a similar pattern was also observed in mice implanted with CT26 syngeneic tumors. In such animals, TNFR2-specific agonists inhibited tumor growth, enhanced tumor infiltration by CD8+ T cells and increased CD8+ T cell IFN-γ synthesis. Together, these data indicate a novel mechanism for TNF-α-independent TNFR2 agonism in cancer immunotherapy, and demonstrate the utility of target-agnostic screening in highlighting important targets during drug discovery.