Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of the properties of different surfaces used in evaporation systems

This paper presents a study of the properties of surfaces with nanocoatingsof two types:NOA 81 photoresist with silanizationand NOA 65 photoresist. These surfaces are resistant to thermal and mechanical loads. The structure of the surfaces was investigated by scanning electron microscopy. The contact angle hysteresis for these surfaces wasdeterminedby the standard DSA-100 KRUSSprocedure, in which theadvancing and receding contact angles are measured, and also by a second method - measuring the contact angle under isothermal droplet evaporation. The contact angle hysteresis values measured by the two different methods are in satisfactory agreement. The contact angle hysteresis was about 20° for the NOA 81 substrateand about 50° for NOA 65.
C-Type Lectin Receptors in Antiviral Immunity and Viral Escape

C-type lectin receptors (CLRs) are important pattern recognition receptors involved in recognition and induction of adaptive immunity to pathogens. Certain CLRs play an important role in viral infections as they efficiently interact with viruses. However, it has become clear that deadly viruses subvert the function of CLRs to escape antiviral immunity and promote infection. In particular, viruses target CLRs to suppress or modulate type I interferons that play a central role in the innate and adaptive defense against viruses. In this review, we discuss the function of CLRs in binding to enveloped viruses like HIV-1 and Dengue virus, and how uptake and signaling cascades have decisive effects on the outcome of infection.
Ileal Transposition Surgery Decreases Fat Mass and Improves Glucose Metabolism in Diabetic GK Rats: Possible Involvement of FGF21

Objective: Ileal transposition (IT) surgery has been reported to improve glucose and lipid metabolism, and fibroblast growth factor 21 (FGF21) is a powerful metabolic regulator. In the present study, we aimed to investigate the effects of IT surgery on metabolism and its possible relationship with the FGF21 signaling pathway in diabetic Goto-Kakizaki (GK) rats. Methods: Ten-week-old male GK rats were subjected to IT surgery with translocation of a 10 cm ileal segment to the proximal jejunum (IT group) or sham surgery without the ileum transposition (Sham-IT group). Rats in the no surgery group did not receive any surgical intervention. Six weeks later, body weight, fat mass, fasting blood glucose (FBG), and serum levels of FGF21 and leptin were measured. The expression of the FGF21 signaling pathway and white adipose tissue (WAT) browning-related genes in the WAT and liver were evaluated by real-time reverse transcription polymerase chain reaction (RT-qPCR) and western blot. Results: IT surgery significantly decreased the body weights and FBG levels and increased the insulin sensitivity of GK rats. The total WAT mass of the IT rats showed a 41.5% reduction compared with the Sham-IT rats, and serum levels of FGF21 and leptin of the IT rats decreased by 26.3 and 61.7%, respectively (all P < 0.05). The mRNA levels of fibroblast growth factor receptor 1 (FGFR1) and its co-receptor β klotho (KLB) in the perirenal WAT (pWAT) of the IT rats were 1.4- and 2.4-fold that of the Sham-IT rats, respectively, and the FGFR1 protein levels were 1.7-fold of the Sham-IT rats (all P < 0.05). In accordance with the pWAT, the protein levels of FGFR1 and KLB in the epididymal WAT (eWAT) of the IT rats notably increased to 3.0- and 3.9-fold of the Sham-IT rats (P < 0.05). Furthermore, uncoupling protein 1 (UCP1) protein levels in the eWAT and pWAT of the IT rats also increased to 2.2- and 2.3-fold of the Sham-IT rats (P < 0.05). However, the protein levels of FGFR1 and KLB in the subcutaneous WAT (sWAT) of the IT rats decreased by 34.4 and 72.1%, respectively, compared with the Sham-IT rats (P < 0.05). In addition, the protein levels of FGF21 and KLB in the livers of IT rats were 3.9- and 2.3-fold of the Sham-IT rats (all P < 0.05). Conclusions: IT surgery significantly decreased fat mass and improved glucose metabolism in diabetic GK rats. These beneficial roles of IT surgery were probably associated with its stimulatory action on the expression of FGFR1 and KLB in both the eWAT and the pWAT, thereby promoting UCP1 expression in these tissues.
Capacity analysis based on channel measurements of massive MU-MIMO System at 3.5 GHz

Massive multiple-input multiple-output (MIMO) is considered as one of the promising fifth Generation (5G) technologies, one of its key properties is the favorable propagation condition which describes mutual orthogonality among channels to different users. In this paper, we investigate to what extent the favorable condition can be realized by increasing the number of transmitting antennas (Tx) to 256 in a practical Urban Macro (UMa) scenario based on channel measurements at 3.5 GHz. Multi-user MIMO (MU-MIMO) capacity based on the zero forcing block diagonalized (ZFBD) scheme is evaluated, and the results are compared to the independent identically distributed (i.i.d.) channel. The performance improvements are found to decelerate at 64 Tx and certain gap from i.i. d. channel remains for all cases. The eigenvalue distributions of the composed two users' channel matrix are then checked, and very limited decorrelation of the users' sub-channels is observed. Finally, we consider number growths of receiving antennas (Rx) and numerical results indicate that the capacity gain is dependent on the scenario conditions and the antenna configurations at both Rx and Tx sides, although sustained growths are observed. Therefore, the full gain of favorable propagation is not entirely achieved in our measured practical channel environment.
Multi-view stereo via geometric expansion and depth refinement

Multi-view stereo, which aims at reconstructing 3D models from series of images, has always been one of the important subjects in the field of robot vision. In this paper, we propose a novel framework to recover a 3D point cloud from calibrated images. Firstly, we construct a sparse point cloud from images by feature matching and triangulation. Then, the sparse point cloud is geometrically expanded to a dense point cloud model by using a shape prior patch library. Finally, we employ a depth refinement procedure so as to recover the details of the surface. Hence, in this work, the most difficult task, dense matching construction across the images, can be avoided as much as possible. Experimental results demonstrate the effectiveness of our method. On the reconstructed 3D model, the elaborate details are recovered, and the noise can also be suppressed as well.
Fabrication and Evaluation of Solid Dispersion Containing Simvastatin

Hyperlipidemia or hyper lipoproteinemia or dyslipidemia is the presence of elevated or abnormal levels of lipids or lipoproteins in the blood. Lipid and lipoprotein abnormalities are extremely common in general population and are regarded as a highly modifiable risk factor for cardiovascular diseases due to influence of cholesterol and its more common in elderly patients. Simvastatin is a selective competitive inhibitor of HMG CoA reductase. However its absolute bioavailability is 5%. To increase the solubility of drug solid dispersion was prepared. The objective of the present study was to enhance the dissolution rate of Simvastatin by making a molecular dispersion of drug in the polymeric matrix of Pluronic F-127. These solid dispersions were analyzed for the percent yield, drug content, solubility, SEM, XRD, DSC and in vitro dissolution profile. Dissolution study of the solid dispersions shows the enhancement of dissolution rate of Simvastatin. The stability study of the formulations as per ICH guideline Q1A in stability chamber both at intermediate and accelerated conditions ascertained that the formulations are stable at wide range of storage conditions.
Exploring multiple clusterings in attributed graphs

Many graph clustering algorithms aim at generating a single partitioning (clustering) of the data. However, there can be many ways a dataset can be clustered. From a exploratory analisys perspective, given a dataset, the availability of many different and non-redundant clusterings is important for data understanding. Each one of these clusterings could provide a different insight about the data. In this paper, we propose M-CRAG, a novel algorithm that generates multiple non-redundant clusterings from an attributed graph. We focus on attributed graphs, in which each vertex is associated to a n-tuple of attributes (e.g., in a social network, users have interests, gender, age, etc.). M-CRAG adds Artificial edges between similar vertices of the attributed graph, which results in an augmented attributed graph. This new graph is then given as input to our clustering algorithm (CRAG). Experimental results indicate that M-CRAG is effective in providing multiple clusterings from an attributed graph.
Association between famine exposure in early life and type 2 diabetes mellitus and hyperglycemia in adulthood: Results from the China Health And Retirement Longitudinal Study (CHARLS)

Studies have revealed the association between famine in early life and type 2 diabetes mellitus (T2DM) in adulthood. However, studies on the Great Chinese Famine were not conducted nationwide. Because of regional variations in the severity of this famine, the results of regional studies are limited. This study explored associations between famine and T2DM in adulthood in a nationwide study.
Platelet Distribution Width on Admission Predicts In-Stent Restenosis in Patients with Coronary Artery Disease and Type 2 Diabetes Mellitus Treated with Percutaneous Coronary Intervention

Background: It is known that there is a definite association between platelet distribution width (PDW) and poor prognosis in patients with coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM). However, there are no data available regarding the prognostic significance of PDW for in-stent restenosis (ISR) in patients with CAD and T2DM. We aimed to determine the value of PDW on admission that predicted ISR in patients with CAD and T2DM. Methods: Between January 2012 and December 2013, a total of 5232 consecutive patients diagnosed with CAD and T2DM undergoing percutaneous coronary intervention were admitted. Three years of retrospective follow-up was undertaken. A total of 438 patients with second angiography operations were included. ISR was defined as ≥50% luminal stenosis of the stent or peri-stent segments. Continuous data were presented as the mean ± standard deviation or median (P25, P75) and were compared by one-way analysis of variance or Kruskal-Wallis H-test. Categorical variables were presented as percentages and were compared by Chi-square test or Fisher's exact test. The association between PDW and ISR was calculated by logistic regression analysis. A two-sided value of P < 0.05 was considered statistically significant. Statistical analyses were performed by SPSS version 22.0 for windows. Results: Fifty-nine patients with ISR, accounting for 13.5% of the total, were included. ISR was significantly more frequent in patients with higher PDW quartiles compared with lower quartiles. We observed that PDW had a strong relationship with mean platelet volume (r = 0.647, 95% confidence interval [CI]: 0.535–0.750, P < 0.0001). The receiver-operating characteristic curves showed that the PDW cutoff value for predicting ISR rate was 13.65 fl with sensitivity of 59.3% and specificity of 72.4% (area under curve [AUC] = 0.701, 95% CI: 0.625–0.777, P < 0.001). Multivariate analysis showed that the risk of ISR increased approximately 30% when PDW increased one unit (odds ratio [OR]: 1.289, 95% CI: 1.110–1.498, P = 0.001). Patients with higher PDW, defined as more than 13.65 fl, had a 4-fold higher risk of ISR compared with lower PDW (OR: 4.241, 95% CI: 1.879–9.572, P = 0.001). Furthermore, when patients were divided by PDW quartiles values, PDW was able to predict ISR (Q2: OR = 0.762, 95% CI: 0.189–3.062, P = 0.762; Q3: OR = 2.782, 95% CI: 0.865–8.954, P = 0.086; and Q4: OR = 3.849, 95% CI: 1.225–12.097, P = 0.021, respectively; P for trend <0.0001). Conclusion: PDW is an independent predictor of ISR in patients with CAD and T2DM.
Evidence for panmixia despite barriers to gene flow in the hooked mussel, Ischadium recurvum (Mytilidae; Brachidontinae) along the North American coastline

Abstract The discovery of phylogeographic patterns within broadly distributed marine species can be particularly challenging because absolute physical barriers to dispersal can be inconspicuous. Genetic boundaries often lie where ocean currents meet, forming sharp physical and ecological gradients, which may act as barriers to successful migrants. In eastern North America, coastal species often show phylogeographic differentiation associated with two recognized genetic barriers: the Gulf/Atlantic and the Virginia/Carolina discontinuities. We examined 185 specimens of the intertidal hooked mussel Ischadium recurvum collected from 15 locations along the eastern coastline of North America to examine phylogeographic, migration and historical demographic patterns associated climate change associated with Pleistocene glacial patterns. Hypothesis testing using Bayes factors in Migrate-n rejected the presence of phylogeographic breaks consistent with either maritime discontinuity and favoured a panmictic population model. The migration rate from the Gulf to the Atlantic was approximately three times higher than the migration from the Atlantic to the Gulf whereas the Carolina–Virginia migration rates were nearly equal. The summary statistics (Tajima’s D, Fu’s Fs) were significant and the demographic analyses (mismatch distributions, Bayesian skyline plot) were consistent with patterns of population expansion following glacial retreat during the Pleistocene epoch.
Evaluating cross domain sentiment analysis using supervised machine learning techniques

Sentiment Analysis is the process of computationally identifying and categorizing opinion expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic is negative, positive or neutral. Many researchers have proposed novel methods for sentiment classification especially using supervised machine learning (ML) techniques. However, there is still limited research with successful results in Cross-Domain Sentiment Analysis. Therefore, previous experiments were replicated by using different ML techniques with several enhancements in order to better understand the sentiment classification process and to compare results with cross-domain analysis. Limitations of the proposed approach are discussed and a new automated model is suggested for future work.
A quantitative approach for determining pilot affective patterns during soaring flight simulation

The development of affective computing system for soaring flight simulation training requires a mechanism for determining pilot affective patterns. These patterns may be comprised of multiple elements, including emotion, pilot performance level, and physiological responses. This article proposes an approach to quantify these elements during the performance of flight training maneuvers. To validate this, a sample population of pilots performed flight tasks in a soaring flight simulator while wearing physiological sensors. Pilots reported subjective emotional stress using a 10-point numeric scale. A 5-point numeric scale was developed to transform flight task performance criteria into a unified scale. The use of common quantitative units for emotion and performance provides a simple mechanism for computational analysis and comparison of values that would otherwise be either qualitative (i.e. emotion) or measured in different units (i.e. flight tasks). The research provides a foundation and initial data set for the development of affective flight training systems that adapt to operator affect and performance in real-time. During analysis, asymmetric EDA responses were observed (left vs. right side sensors).
Employing deep learning and sparse representation for data classification

Selecting a proper set of features with the best discrimination is always a challenge in classification. In this paper we propose a method, named GLLC (General Locally Linear Combination), to extract features using a deep autoencoder and reconstruct a sample based on other samples in a low dimensional space, then the class with minimum reconstruction error is selected as the winner. Extracting features along with the discrimination characteristic of the sparse model can create a robust classifier that shows simultaneous reduction of samples and features. Although the main application of GLLC is in the visual classification and face recognition, it can be used in other applications. We conduct extensive experiments to demonstrate that the proposed algorithm gain high accuracy on various datasets and outperforms the state-of-the-art methods.
A Concept Learning Tool Based On Calculating Version Space Cardinality

In this paper, we proposed VeSC-CoL (Version Space Cardinality based Concept Learning) to deal with concept learning on extremely imbalanced datasets, especially when cross-validation is not a viable option. VeSC-CoL uses version space cardinality as a measure for model quality to replace cross-validation. Instead of naive enumeration of the version space, Ordered Binary Decision Diagram and Boolean Satisfiability are used to compute the version space. Experiments show that VeSC-CoL can accurately learn the target concept when computational resource is allowed.
Fast and Accurate Exploration of Multi-level Caches Using Hierarchical Reuse Distance

Exploring the design space of the memory hierarchy requires the use of effective methodologies, tools, and models to evaluate different parameter values. Reuse distance is of one of the locality models used in the design exploration and permits analytical cache miss estimation, program characterization, and synthetic trace generation. Unfortunately, the reuse distance is limited to a single locality granularity. Hence, it is not a suitable model for caches with hybrid line sizes, such as sectored caches, an increasingly popular choice forlarge caches. In this work, we introduce a generalization to the reuse distance, which is able to capture locality seen at multiple granularities. We refer to it as Hierarchical Reuse Distance (HRD). The proposed model has same profiling and synthesis complexity as the traditional reuse distance, and our results show that HRD reduces the average miss rate error on sectored caches by more than three times. In addition, it has superior characteristics in exploring multi-level caches with conventional single line size. For instance, our method increases the accuracy on L2 and L3 by a factor of 4 and converges three orders of magnitude faster.
WarpMap: Accurate and Efficient Indoor Location by Dynamic Warping in Sequence-Type Radio-Map

Radio-map based method has been widely used for indoor location and navigation, but remaining key challenges are: 1) laborious efforts to calibrate a fine-grained radio-map, and 2) the locating result inaccuracy and not robust problems due to random signal strength (RSS) noises. An efficient way to overcome these problems is to collect RSS signatures along indoor paths and utilize sequence matching to enhance the location robustness. But, due to problems of indoor path combinational explosion, random RSS loss during movement, and moving speed disparity during online and offline phases, how to exploit sequence matching in radio-map remains difficult. This paper proposes WarpMap, an efficient sequence-type radio-map model and an accurate indoor location method by dynamic warping. Its distinct features include: 1) an undirected graph model (Trace-graph) for efficiently calibrating and storing sequence-type radio-map, which overcomes the path combinational explosion and RSS miss-of-detection problems; 2) an efficient sub-sequence dynamic time warping (SDTW) algorithm for accurate and efficient on-line locating. We show SDTW can tolerate random RSS disparities at discrete points and handle the moving speed differences in on-line and offline phases. The impacts of different warping distance functions, RSS preprocessing techniques were also investigated. Extensive experiments in office environments verified the efficiency and accuracy of WarpMap, which can calibrated within ten minutes by one person for 1100m2 area and provides overall nearly 20% accuracy improvements than the state-of-the-art of radio-map method.
Knowledge extraction from software engineering repositories

Software engineering processes are hard to understand, and related tasks frequently produce lot of information which can be used for development of strategy for future Projects. In the last decade, a large number of software data sets have been created for different purposes, however as the challenges in the development and maintenance of software are increased the need for novel approaches to make use of the collected data is also increased. The demands for reduced development time and increased reliability of software also necessitated the need for knowledge extraction from the previously collected data sets. In this paper a detailed survey is conducted on the available methods for the knowledge extraction from the software engineering data bases to forecast and aid in improved development and maintenance phases of software.
Revalorisation of Posidonia Oceanica as Reinforcement in Polyethylene/Maleic Anhydride Grafted Polyethylene Composites

Posidonia Oceanica waste was used as reinforcement in a polyethylene matrix and the obtained composites were characterised by a tensile test and morphological analysis. The fi brous material derived from P. Oceanica wastes was characterised by morphological, thermal and chemical analysis, and a subsequent treatment with sodium hydroxide (NaOH) at different weight content (2, 5 and 10 wt%) was considered as an optimised method for surface modifi cation of pristine fi bres (PO). The TGA analysis and morphological investigation of the treated fi bres selected the 5 wt% of NaOH as the best treatment. Matrix compatibilisation with maleic anhydride grafted polyethylene was also considered and the effect on both grafting procedure and alkali treatment was studied for composites containing 20 wt% of fi bres. The results confi rmed that it is possible to aim for a revalorisation of coastal algae and seaweed wastes as raw material for polyolefi n matrix composites, even without applying a strong chemical treatment to the waste.