Miracle-dz/UniFAR-FTUs huggingface dataset:
MECHANISMS OF PRECIPITATES FORMATION IN AN Al-Cu-Li-Zr ALLOY USING DSC TECHNIQUE AND ELECTRICAL RESISTANCE MEASUREMENTS

Guinier-Preston (GP) zone formation and precipitation behavior of T1 (Al2CuLi) phase during the ageing of an Al-Cu-Li-Zr alloy was studied by differential scanning calorimetry (DSC) technique and electrical resistance measurement of the samples. Results show that endothermic effects in the thermograms of the alloy between 180°C and 240°C can be related to the enthalpy of GP zones dissolution. Formation of GP zones in the structure increased hardness, tensile strength and electrical resistance of the Al-Cu-Li-Zr alloy. Furthermore, precipitation of T1 phase occurred in temperature range of 250oC to 300oC whereas its dissolution occurred within the temperature of 450530oC. Activation energies for precipitation and dissolution of T1 phase which were determined for the first time in this research, were 122.1(kJ/mol) and 130.3(kJ/mol) respectively. Results of electrical resistance measurements showed that an increase in the aging time resulted in the reduction of electrical resistance of the aged samples.
Peer Influence in Products with Network Externalities : Empirical Evidence from a Large Mobile Network

We study the e↵ect of peer influence for products that exhibit positive network externalities to non-adopters. Users benefit from these products when their friends adopt even if they do not, which reduces their likelihood of adoption. However, using observational data to measure the e↵ect of peer influence in these cases is likely to provide a positive estimate due to unobserved homophily. We suggest using the number of friends that end up adopting the product as a proxy for the unobserved user fixed e↵ects and we show that this method recovers a negative e↵ect of peer influence when expected. We use this method and data from a mobile service provider serving 5.7 million customers to estimate the e↵ect of peer influence across a set of 5 di↵erent products with the feature. In all cases, we obtain negative estimates. Using randomization yields similar results providing robustness to our findings. Finally, we show that even for these products the e↵ect of peer influence associated to the first friend that adopts the product is positive, which arises because these friends convey useful information about the product reducing uncertainty. The negative e↵ect of peer influence arises only for subsequent friends that adopt the product. The latter are unlikely to convey new information about the product but each of them decreases the economic incentives for adoption resulting in a negative e↵ect of peer influence.
Relationships between tumor-infiltrating FoxP 3 + regulatory T cells and overall survival and lymph node metastasis in gastric cancer : a meta-analysis

Objective: Relationships between tumor-Infiltrating FoxP3+ T cells (Tregs) and overall survival (OS) and disease-free survival (DFS) in patients with gastric cancer (GC) remains controversial. Thus, we conducted a metaanalysis to estimate the prognostic value of tumor infiltrating Tregs for OS and DFS in patients with GC. Methods: PubMed, Embase, Web of science and Cochrane library up to July 2017 were used to search relevant literatures. All studies involved with prognostic value of tumor infiltrating Tregs in patients with GC were systematically identified. Results: 22 studies including 2521 patients, 1311 of whom had high Tregs infiltration in GC were included. The OS of high Tregs infiltration patients in 1, 3 and 5-year were significantly lower than low Tregs infiltration patients (OR = 0.61, 95% CI = 0.38-0.97, P = 0.04; OR = 0.54, 95% CI = 0.35-0.81, P = 0.003 and OR = 0.56, 95% CI = 0.35-0.90, P = 0.02, respectively). There is no significant difference in 1, 3 and 5-year DFS between high Tregs infiltration patients and low Tregs infiltration patients (OR = 0.57, 95% CI = 0.27-1.18, P = 0.13; OR = 0.62, 95% CI = 0.33-1.16, P = 0.13 and OR = 0.73, 95% CI = 0.34-1.57, P = 0.41, respectively). When the studies were stratified further by the pathological variables for high Tregs infiltration patients versus low Tregs infiltration patients in GC, finding high Tregs infiltration is prone to lymph node metastasis (OR = 1.73, 95% CI = 1.08-2.77, P = 0.02) and no relationship with T stage (T3+T4), poor histodifferentiation, TNM stage (III+IV), vascular invasion and lymphatic invasion. They also provided some other important clinical prognostic information. Conclusion: Tumor infiltrating Treg, a risk factor of lymph node metastasis, was associated with poor OS, but not with poor DFS, for GC.
Primary health care for South American indigenous peoples : an integrative review of the literature *

1 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 IGO License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited. No modifications or commercial use of this article are permitted. In any reproduction of this article there should not be any suggestion that PAHO or this article endorse any specific organization or products. The use of the PAHO logo is not permitted. This notice should be preserved along with the article’s original URL. Primary health care for South American indigenous peoples: an integrative review of the literature*
Financial Market Dynamics : Implications of Prospect Theory for Asset Prices and Trading Volume

Does prospect theory produce price momentum and return-volume co-movement via the disposition effect? The answer to this question requires a general equilibrium analysis. This paper provides a general equilibrium model and finds that different components of prospect theory play different roles. Diminishing sensitivity drives a disposition effect that, in turn, leads to price momentum and a positive return-volume correlation; loss aversion predicts exactly the opposite. In a calibrated economy with prospect theory preference parameters set at the values estimated by earlier studies, our model can generate price momentum ranging from 1% to 7% on an annual basis.
Product shape feature recognition based on entity model

Based on the characteristics of entity model, the simple shape features are searched in the model feature space by starting with feature tier in it. According to the characteristics of the model, the geometric topologic relation on parts model of single feature is obtained, and the automatic shap feature recognition is realized. After further investigation on feature-based entity model, an approach about shape feature recognition of product is proposed. And a module of feature parameter extraction for microwave part is developed to implement automatic recognition and extraction for shape feature on complex part model. The method provides a way to quickly create part warehouse for enterprises, and lays the foundation for collaborative design and data sharing under network environment.
Modeling Relationships between Objects for Referring Expression Comprehension

The Referring Expression Comprehension (REC) task is to correctly identify an object in an image that corresponds to a given natural language expression (i.e., referring expression). In this thesis, we improve a previous REC model by explicitly aligning relations between mentions in a language expression to pairs of objects placed in specific relative positions in an image. Evaluation using the Google Refexp dataset [1] demonstrates that the proposed model outperforms the baseline method. In addition, we found that in stead of the image features extracted from a pretrained convolution neural network and popularly used by previous research, one can simply boost performance by using automatically recognized category labels.
Clinical role of serum expression of miR-222 as a novel non-invasive predictor for bladder cancer

In this study, we aimed to characterize miR-222 expression in serum as a non-invasive biomarker for diagnosis of bladder cancer (BC) and differentiation of muscle invasive bladder cancer (MIBC) from non-muscle invasive bladder cancer (NMIBC). Serum samples were obtained from 98 BC patients and 100 healthy individuals. Serum levels of miR-222 were detected by qRT-PCR analysis and further associated with the clinicopathological characteristics and prognosis of BC patients, and also compared between patients with MIBC and NMIBC. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic value of serum miR-222 in BC screening and differentiation of MIBC from NMIBC. We found that serum miR-222 levels in BC patients were significantly higher in comparison with that in healthy controls, and the levels of serum miR-222 in patients with MIBC were significantly higher than that in patients with NMIBC. Upregulation of serum miR-222 was greatly associated with aggressive clinicopathological features and poor prognosis in BC patients. According to ROC curve analysis, between BC patients and healthy controls, the area under the curve (AUC) of serum miR-222 was 0.857, and its specificity and sensitivity were 0.745 and 0.920 at a diagnostic threshold of 2.035. Between patients with MIBC and NMIBC, the AUC of ROC curve of serum miR-222 was 0.799, and its specificity and sensitivity were 0.743 and 0.841 at a diagnostic threshold of 3.705. Serum miR-222 can be utilized as a promising non-invasive molecular marker for BC screening and prognosis, as well as differentiation of MIBC from NMIBC.
Guidance And Control Of Ocean Vehicles

By searching the title, publisher, or authors of guide you in reality want, you can discover them rapidly. In the house, workplace, or perhaps in your method can be all best place within net connections. If you objective to download and install the guidance and control of ocean vehicles, it is utterly easy then, past currently we extend the colleague to buy and make bargains to download and install guidance and control of ocean vehicles therefore simple!
MODIFIED K-MEANS ALGORITHM FOR FINDING SIFT CLUSTERS IN AN IMAGE

This paper explores the ways to represent images as bags of SIFT feature clusters. SIFT features themselves are widely used in image analysis because of their properties of scale and rotation invariance. The usual way to group them is to segment the image into regions and then assign features to the corresponding image parts. When images themselves are not available for privacy reasons, this is not possible. We created a hybrid clustering algorithm which offers more flexibility than simple spatial k-means clustering. The algorithm parameters were optimized by a stochastic procedure. The impact of different elements of local representation on final clustering quality is discussed.
Karakterizacija sadržaja izoflavona u hrvatskoj kolekciji crvene djeteline

Red clover is a perennial forage crop rich in isoflavones, the bioactive compounds with a positive effect on human and animal health. The aim of the research was to determine a variation in the isoflavone contents in the Croatian red clover collection and to identify the most promising materials to be used in the breeding program for the development of new cultivars for specific purposes. Leaf samples of 29 red clover cultivars/populations (two cultivars, twenty breeding populations, and seven local populations) were collected in a full flowering stage, and the identification and quantification of isoflavones was performed using the HPLC analysis. The most common isoflavones in the red clover cultivars/populations were formononetin and biochanin A. A significant variation among the cultivars/populations in the total and individual isoflavone content was determined. The populations with very high and low contents of both the total and of the individual isoflavones were identified to be used for the breeding purposes in order to develop new forage cultivars, or for specific goals in the pharmaceutical industry.
The Effect of Interactive Media on Elementary School Childrens ’ Story Memory

An experimental study examined the influence of interactive media on primary graders memory. A sample of 40 first graders from an Elementary School in the Philippines were randomly assigned to experience a computer-based story in 1 of 4 presentation modes (audio narration of the story, similar to radio; audiovisual presentation, similar to television; interactive viewing, and interactive observation). They were asked to listen, watch, interactively participate or observe during a storytelling activity and were asked later to answer a (a) narration-based questions; (b) visually-dependent questions; and (c) inference questions. The results showed that among students who had the storytelling activity, the ones under the condition of audio only remembered the story poorly, including the story facts and ability to make inferences. However, the effect of interactive media for this present study was identified to be non-contributing factor of facilitation of memory retrieval. Participants in the Audio-visual condition (M= 2.65, SD=.03) performed better than those in the Audio condition (M=2.02, SD=.15); t(9) = -3.720, p=. 005. Likewise, participants in the Audio-visual condition (M= 2.65, SD=.03) performed better than those in the interactive (M= 2.19, SD=.11); t (9) = 3.743, p=. 005. Lastly, Audio-visual participants performed better than those in the interactive observer (M= 2.04, SD=.11); t(9) =4.788, p=. 001.
Effect of Room Temperature Ionic Liquids for Electroless Nickel Plating on Acrylonitrile Butadiene Styrene Plastic

In this study, electroless nickel (EN) plating on acrylonitrile butadiene styrene (ABS) engineering plastic using room temperature ionic liquids (RTIL) was studied. Electroless plating is a fundamental step in metal plating on plastic. This step makes the plastic conductive and makes it possible to a homogeneous and hard plating without using any hazardous and unfriendly chemical such as palladium, tin, etc. In the industry there are many distinct chemical materials both catalysts and activation solutions for the electroless bath which is one of the most important parts of the process. In this study the effects of the ionic liquid, plating time, and sand paper size were investigated on electroless nickel plating. The etching and the plating processes were performed with environmentally friendly chemicals instead of the chromic and sulphuric acids used in the traditional processes. Experiments were carried out with and without ionic liquid, EMIC, 1-ethyl-3-methyl imidazolium chloride (C6H11N2Cl), and with 400, 500 and 800 grit sandpaper with the application of the sand attrition process and 70, 80, and 90 °C bath temperatures with 30, 60, and 90 minutes of deposition time. The surface morphology and the thickness of deposit analysis were performed using the Fischer scope X-Ray XDL-B System, X-ray Diffraction (XRD), and Scanning Electron Microscopy (SEM). Due to the results of the experiments and analysis, the electroless nickel plating on ABS plastic was a success. The best plating was obtained at 5.010 μm as the maximum plating thickness, at 90 min of plating time and 80 °C as the plating bath temperature for electroless nickel plating on ABS plastic whit the surface activated with 800 grit sandpaper using EMIC ionic liquid. DOI: http://dx.doi. org/10.5755/j01.ms.25.3. 20116
Regions Step 2 Step 3 Step 4 Step 5 Divide Conquer Best Models Leaf-wise Weights Computations Code changes in Software repositories Bug fix patches

Issue tracking systems are commonly used in modern software development for collecting feedback from users and developers. An ultimate automation target of software maintenance is then the systematization of patch generation for user-reported bugs. Although this ambition is aligned with the momentum of automated program repair, the literature has, so far, mostly focused on generate-andvalidate setups where fault localization and patch generation are driven by a well-defined test suite. On the one hand, however, the common (yet strong) assumption on the existence of relevant test cases does not hold in practice for most development settings: many bugs are reported without the available test suite being able to reveal them. On the other hand, for many projects, the number of bug reports generally outstrips the resources available to triage them. Towards increasing the adoption of patch generation tools by practitioners, we investigate a new repair pipeline, iFixR, driven by bug reports: (1) bug reports are fed to an IR-based fault localizer; (2) patches are generated from fix patterns and validated via regression testing; (3) a prioritized list of generated patches is proposed to developers. We evaluate iFixR on the Defects4J dataset, which we enriched (i.e., faults are linked to bug reports) and carefullyreorganized (i.e., the timeline of test-cases is naturally split). iFixR generates genuine/plausible patches for 21/44 Defects4J faults with its IR-based fault localizer. iFixR accurately places a genuine/plausible patch among its top-5 recommendation for 8/13 of these faults (without using future test cases in generation-and-validation).
Understanding Security Vulnerabilities in File Systems

File systems have been developed for decades with the security-critical foundation provided by operating systems. However, they are still vulnerable to malware attacks and software defects. In this paper, we undertake the first attempt to systematically understand the security vulnerabilities in various file systems. We conduct an empirical study of 157 real cases reported in Common Vulnerabilities and Exposures (CVE). We characterize the file system vulnerabilities in different dimensions that include the common vulnerabilities leveraged by adversaries to initiate their attacks, their exploitation procedures, root causes, consequences, and mitigation approaches. We believe the insights derived from this study have broad implications related to the further enhancement of the security aspect of file systems, and the associated vulnerability detection tools.
3D-Trail-Making Test: A Touch-Tablet Cognitive Test to Support Intelligent Behavioral Recognition

The decades-old Trail-Making Test has established itself as an effective and versatile cognitive testing tool. However, its reliance on a paper-and-pencil method of administration severely limits its capabilities for quantitative evaluation. We evaluate input data via sketch recognition algorithms on a digitized version of the Trail-Making Test, as well as exploring the viability of a novel touch-based version designed around the basic concepts of the traditional paper-and-pencil exam. Two quantitative studies helped evaluate the viability of these digital examinations: the first builds a normative data set that shows a stable increase in test completion times with a lower overall skewness, while the second indicates the new examination’s capability to perform behavioral classification based on participant nationality by correctly classifying input behavior with up to 96% accuracy.
Learning scikit-learn: Machine Learning in Python

Experience the benefits of machine learning techniques by applying them to real-world problems using Python and the open source scikit-learn library Overview Use Python and scikit-learn to create intelligent applications Apply regression techniques to predict future behaviour and learn to cluster items in groups by their similarities Make use of classification techniques to perform image recognition and document classification In Detail Machine learning, the art of creating applications that learn from experience and data, has been around for many years. However, in the era of big data, huge amounts of information is being generated. This makes machine learning an unavoidable source of new data-based approximations for problem solving. With Learning scikit-learn: Machine Learning in Python, you will learn to incorporate machine learning in your applications. The book combines an introduction to some of the main concepts and methods in machine learning with practical, hands-on examples of real-world problems. Ranging from handwritten digit recognition to document classification, examples are solved step by step using Scikit-learn and Python. The book starts with a brief introduction to the core concepts of machine learning with a simple example. Then, using real-world applications and advanced features, it takes a deep dive into the various machine learning techniques. You will learn to evaluate your results and apply advanced techniques for preprocessing data. You will also be able to select the best set of features and the best methods for each problem. With Learning scikit-learn: Machine Learning in Python you will learn how to use the Python programming language and the scikit-learn library to build applications that learn from experience, applying the main concepts and techniques of machine learning. What you will learn from this book Set up scikit-learn inside your Python environment Classify objects (from documents to human faces and flower species) based on some of their features, using a variety of methods from Support Vector Machines to Nave Bayes Use Decision Trees to explain the main causes of certain phenomenon such as the Titanic passengers survival Predict house prices using regression techniques Display and analyse groups in your data using dimensionality reduction Make use of different tools to preprocess, extract, and select the learning features Select the best parameters for your models using model selection Improve the way you build your models using parallelization techniques Approach The book adopts a tutorial-based approach to introduce the user to Scikit-learn. Who this book is written for If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this the book for you. No previous experience with machine-learning algorithms is required.
Increased risk of hip fracture related to cardiovascular disease : a meta-analysis

Cardiovascular diseases (CVDs) might have a relationship to hip fracture risk. Many studies have investigated this hypothesis but provided conflicting and inconclusive findings. In this study, we aim to validate the potential association between CVD and hip fracture risk by pooling all available publications. After a comprehensive literature search in PubMed, Embase, Wanfang and CNKI databases from their inception up to June 20, 2017, a total of 13 independent studies were identified and included in our study. The pooled relative risks (RRs) with 95% confidence intervals (95% CIs) were calculated to assess the strength of the association. The results from this metaanalysis showed that CVD is positively associated with the risk of hip fracture, suggesting a risk role of CVD in the development of hip fracture (RR = 1.67, 95% CI 1.39-1.99, P < 0.001). Stratified analyses by study design further confirmed the pooled findings. CVD is related to increased risk of hip fracture among Caucasians but not Asians. Our pioneering findings provide strong evidence for a risk effect of CVD on hip fracture, particularly in the Caucasian population.