Miracle-dz/UniFAR-FTUs huggingface dataset:
Oxidative Stress-Related Biomarkers in Postmenopausal Osteoporosis: A Systematic Review and Meta-Analyses

Numerous studies suggested that oxidative stress (OS) played a central role in the onset and development of postmenopausal osteoporosis (PO); however, conflicting results were obtained as to the association of OS-related biomarkers and PO. This meta-analysis aimed to identify the association between these markers and PO, and explore factors that may explain the inconsistencies in these results. A systematic literature search was conducted in relevant database. Search terms and selection criteria were priorly determined to identify and include all studies that detected markers of OS in PO patients. We pooled data with a random effects meta-analysis with standardized mean differences and 95% confidence interval. Total 17 studies including 12 OS markers were adopted. The results showed that superoxide dismutase (SOD) in erythrocytes, catalase (CAT), total antioxidant status (TAS), hydroperoxides (HY), advanced oxidation protein products (AOPP), malondialdehyde (MDA), and vitamin B12 (VB12) in plasma/serum were not statistically different between the PO and control group, whereas significantly increased level of homocysteine (Hcy) and nitric oxide (NO), along with decreased SOD, glutathione peroxidase (GPx), folate, and total antioxidant power (TAP) in plasma/serum were obtained in the PO group. In summary, OS might serve as potential biomarkers in the etiopathophysiology and clinical course of PO.
On managing visibility of resources in social networking sites

The social network sites has been very popular these days. In these systems, resources are associated with each user (i.e., network node) in the network, and these resources include both soft and physical resources, such as pictures, videos, books, etc. Users would like to control who can see their resources, e.g., any one, only friends, friends and families, friends of friends, etc. The rules defining who can see the resources are called visibility views, and in our system they are identified by the owner nodes and regular path expressions. The users can issue queries for discovering resources, e.g., “Find all lawnmowers in my three degree network that are visible to me”. The evaluation process needs to check all candidate resources to see if they are visible to the query issuer, and this requires computing the visibility views associated with every candidate resources. The visibility views are expensive to evaluate. In order to facilitate the visibility query answering, it is necessary to pre-compute and materialize the views in the so called “cache”. But because of the tremendous volume of the whole view data, we have to select only a portion of them to materialize, based on metrics such as the views’ sizes, the costs to evaluate them, the popularity of references, the temporal locality of requested views, and the correlation relationships among them. The problem of trying to select the views in a static way is called the static view selection problem, and it has been studied extensively by the database community, mostly for answering OLAP queries in data warehouses. We call it “static” because it pre-computes and materializes the views in one lump-sum, based on statistics accumulated before the query sequence starts. This problem has a deep root from the caching problem studied in the theory and system communities. The researches done on caching policies solve the problem in an ad-hoc dynamic way by making decisions at each request, which
Citizen emotion analysis in Smart City

Applications in Smart City context are improving the quality of life of citizens through several technological interactions. These interactions can be also used to relate the citizens' emotions to city's areas. Thus, the main objective of this work is to present a smart phone application that analyzes the citizens' emotions and the relations between these parameters and different city's areas. Daily the citizens deal with a variety of emotions due a set of factors such as, violence, street illumination or car noises, trash and pollution, for instance. The techniques used to do the acquisition of the citizens' emotions involve, heart rate (HR), heart rate variability (HRV) and galvanic skin response (GSR), measured by Shimmer3 sensors. Additionally the citizens fill an on-line questionnaire using a smart phone application. The acquired signals are also processed by a smart phone application that includes signal acquisition control, citizens' emotions analysis, emotion mapping, and data storage. Once identified and stored these citizens' emotions reported to a city's area, it can be represented by green, yellow or red color, circular icons that are plotted over the city's map, using the Google Maps API on the mobile application. Several tests for ten are presented.
The impact of oil prices, real effective exchange rate and inflation on economic activity: Novel evidence for Vietnam

The goal of this paper is to examine the impact of oil prices on Vietnam's economic activity using vector autoregressive (VAR) modeling and cointegration techniques. We use monthly data for the period 1995-2009 and include inflation and the real effective exchange rate as additional determinants of economic activity. We find evidence of a long-run relationship between oil prices, inflation, exchange rate, and economic activity. The results suggest that both oil prices and the real effective exchange rates have strongly significant impact on economic activity. An increase in oil price or depreciation may enhance economic activity. Vietnamese economic activity is influenced more by changes of value of Vietnamese currency than the fluctuations of oil prices. Inflation has a positive impact on economic activity however its impact is not highly significant. This suggests that moderate inflation is helpful rather than harmful to economic activity.
ON FINITE ELEMENT METHODS FOR NONLINEAR DYNAMIC RESPONSE

In this paper we briefly focus on the nonlinear analysis of solids and structures when these undergo large deformations, possibly over long time durations, and perhaps subjected to fluidstructure interactions. The analysis should be conducted with finite element methods, including the time integration, that are reliable and effective. The requirement of reliability is particularly important in nonlinear finite element analysis because physical test data are frequently not available.
Design and implementation of Linux firewall based on the frame of Netfilter/IPtable

With the constant development of network technology today, network not only brings us a convenient and efficient life, and is accompanied by a variety of network security problems. Firewall, as a main way to prevent network attacks, is often used to prevent illegal connection and separates the internal network from the insecure networks, to protect the safety of the Linux systems which used in small and medium-sized enterprise. In this paper, the main content is to complete the function of firewall which is based on the Linux operating system, using Netfliter as firewall architecture, and the IPtable as a user space module tool. Firstly, this paper briefly analyzes the Netfilter/IPtable architecture and princIPle and working process of state detection technology, then, configure the firewall. At the last, the firewall experiment verified the effectiveness and safety of the design of the firewall.
Forecasting Seasonally Cointegrated Systems: Supply Response in Austrian Agriculture

This paper examines the relevance of incorporating seasonality in agricultural supply models. Former studies have eliminated the problem of seasonality by using seasonally adjusted data. Recent developments in cointegration techniques allow the comprehensive modelling of error-correcting structures in the presence of seasonality. We consider a four-variables model for Austrian agriculture. Series on the producer price for soy beans, bulls and pigs, as well as the stock of breeding sows are included. A vector autoregression incorporating seasonal cointegration is estimated. A tentative interpretation of long-run and seasonal features is considered. The model is also used to generate forecasts for the supply of pigs in Austria.
Supporting Development of Context-aware Applications Using Semantic Space Toolkit

In order to facilitate rapid development of context-aware applications, there is a need for architectural support in the entire context processing flow, and improved programming abstractions that ease the prototyping. In this paper, a toolkit called Semantic Space, is proposed to support rapid prototyping of context-aware applications via a set of programming abstractions on context processing. The functionality encapsulated in the toolkit handles the common, time-consuming and low-level details in context acquisition, aggregation, storage and inference. Architectural design and implementation issues of the Semantic Space toolkit are discussed in detail. Finally, a case study on building a mobile situation aware phone is described to illustrate the validity of our approach and usability of the toolkit.
ASSESSING THE RELIABILITY OF THE COR ADVANTAGE by VINCENT CAHALAN

SSESSING THE RELIABILITY OF THE COR ADVANTAGE by VINCENT CAHALAN May 2015 Advisor: Dr. Shlomo Sawilowsky Major: Educational Evaluation and Research Degree: Master of Education The purpose of this study is to first assess the internal consistency reliability of the COR Advantage with Cronbach’s alpha for the entire scale and the SpearmanBrown prophecy formula for the subscales. The second is to examine the internal factor structure of the eight developmental domains by exploratory factor analysis. Results of the analyses yielded relatively high alpha coefficients ranging from . 659 to . 963. The exploratory factor analysis produced a two-factor solution that accounted for 47.22% of the variance. These results, with the exception of the Physical Development & Health developmental area having an alpha coefficient of . 659, are indicative of a fairly reliable assessment. With an average alpha coefficient of . 768, George and Mallery (2003), would classify this assessment as at least “acceptable” (p. 231).
Rapid shifts in dominant taxa among microbial eukaryotes in estuarine ecosystems

Studies in several estuarine ecosystems along the mid-Atlantic coast of the USA were carried out to examine short-term (every 1 to 3 wk) to long-term (seasonal-annual) shifts in the phylotypic composition of the planktonic microbial eukaryotic assemblage using terminal restriction fragment length polymorphism (T-RFLP) analyses. Fragment patterns revealed relatively rapid and striking shifts in the dominant phylotypes observed. Although the presence of some phylotypes was persistent or repetitive, dramatic changes in the overall composition of the microbial eukaryotic assemblage were observed for samples collected from a single environment at 1 to 2 wk intervals, samples collected on the same day from neighboring locales, and samples collected from different seasons. Bray-Curtis similarity values rarely indicated ≥70% similarity for any 2 sample pairs. Non-metric multi-dimensional scaling and detrended correspondence analysis revealed a weak degree of relatedness among samples by location and season. Putative identifications of taxa comprising fragments of specific lengths were determined for 63 of the observed 162 fragment sizes from in silico restriction digests of partial 18S gene sequences obtained from the samples. This approach identified a wide phylogenetic diversity of protistan taxa, despite the presence of significant 'brown tides' caused by the pelagophyte Aureococcus anophagefferens at some sampling times and locations. The regularity and rapidity with which the protistan assemblage restructured itself to yield unique combinations of dominant taxa indicates the existence of a highly dynamic and resilient microbial community that responded swiftly to changing environmental conditions in these estuaries.
A new algorithm for detecting corners in digital images

Corners and vertices are important features in images, which are frequently used for scene analysis, stereo matching and object tracking. Many algorithms for detecting the corners have been reported up to now. In this paper, a new algorithm is presented. The algorithm is based on measuring the variance of the directions of the gradient of brightness. The probability of the event that a point belongs to the approximation of a straight segment of the isoline of brightness passing through the point being tested is computed using the technique of Bayesian estimations and used as a weight. The algorithm is presented both from the theoretical and from the practical point of view. The results of tests show that the algorithm is better than other known algorithms that are usually used for solving the problem.
Recapitulation of endochondral bone formation using human adult mesenchymal stem cells as a paradigm for developmental engineering

Mesenchymal stem/stromal cells (MSC) are typically used to generate bone tissue by a process resembling intramembranous ossification, i.e., by direct osteoblastic differentiation. However, most bones develop by endochondral ossification, i.e., via remodeling of hypertrophic cartilaginous templates. To date, endochondral bone formation has not been reproduced using human, clinically compliant cell sources. Here, we aimed at engineering tissues from bone marrow-derived, adult human MSC with an intrinsic capacity to undergo endochondral ossification. By analogy to embryonic limb development, we hypothesized that successful execution of the endochondral program depends on the initial formation of hypertrophic cartilaginous templates. Human MSC, subcutaneously implanted into nude mice at various stages of chondrogenic differentiation, formed bone trabeculae only when they had developed in vitro hypertrophic tissue structures. Advanced maturation in vitro resulted in accelerated formation of larger bony tissues. The underlying morphogenetic process was structurally and molecularly similar to the temporal and spatial progression of limb bone development in embryos. In particular, Indian hedgehog signaling was activated at early stages and required for the in vitro formation of hypertrophic cartilage. Subsequent development of a bony collar in vivo was followed by vascularization, osteoclastic resorption of the cartilage template, and appearance of hematopoietic foci. This study reveals the capacity of human MSC to generate bone tissue via an endochondral program and provides a valid model to study mechanisms governing bone development. Most importantly, this process could generate advanced grafts for bone regeneration by invoking a “developmental engineering” paradigm.
Mobile devices as infotainment user interfaces in the car: contextual study and design implications

The spreading of mobile devices to all areas of everyday life impacts many contexts of use, including cars. Even though driving itself has remained relatively unchanged, there are now a wide variety of new in-car tasks, which people perform with both integrated infotainment systems and their mobile devices. To gain insights into this new task context and how it could be improved, we conducted a qualitative, contextual study in which we observed real-life car journeys with eight participants. The focus was on user interaction with touchscreen mobile devices, due to their wide range of functions and services. The findings show that the car is an extension of other contexts and it contains a rich set of infotainment tasks, including use of social media. Drivers emphasized gesture interaction and the use of non-visual modalities, for replacing visual information and notifying of changes in the driving context. Based on the findings, we present design implications for future in-car infotainment systems.
Programmers' build errors: a case study (at google)

Building is an integral part of the software development process. However, little is known about the compiler errors that occur in this process. In this paper, we present an empirical study of 26.6 million builds produced during a period of nine months by thousands of developers. We describe the workflow through which those builds are generated, and we analyze failure frequency, compiler error types, and resolution efforts to fix those compiler errors. The results provide insights on how a large organization build process works, and pinpoints errors for which further developer support would be most effective.
A Line Model based approach for monkey intrusion detection

Animal intrusion detection is a major application in human habitats like institutions and agricultural fields to ensure safety and security to the life and assets of human. In this paper, a new image processing method is proposed to detect the presence of animals using Line Model Approach based on their skeletons. In this new frame work, the simple Background subtraction followed by a fast Star Skeletonization algorithm is performed to obtain the skeleton of the object. A novel Line Model is derived from the skeleton of the object. Based on the Line Model, the object is classified into animals and human. Since, the proposed method works on the low quality images and performs faster on intermittent frames, it finds application in real time animal intrusion detection scenario.
Autophosphorylation of Phosphoglucosamine Mutase from Escherichia coli

ABSTRACT Phosphoglucosamine mutase (GlmM) catalyzes the formation of glucosamine-1-phosphate from glucosamine-6-phosphate, an essential step in the pathway for UDP-N-acetylglucosamine biosynthesis in bacteria. This enzyme must be phosphorylated to be active and acts according to a ping-pong mechanism involving glucosamine-1,6-diphosphate as an intermediate (L. Jolly, P. Ferrari, D. Blanot, J. van Heijenoort, F. Fassy, and D. Mengin-Lecreulx, Eur. J. Biochem. 262:202–210, 1999). However, the process by which the initial phosphorylation of the enzyme is achieved in vivo remains unknown. Here we show that the phosphoglucosamine mutase fromEscherichia coli autophosphorylates in vitro in the presence of [32P]ATP. The same is observed with phosphoglucosamine mutases from other bacterial species, yeastN-acetylglucosamine-phosphate mutase, and rabbit muscle phosphoglucomutase. Labeling of the E. coli GlmM enzyme with [32P]ATP requires the presence of a divalent cation, and the label is subsequently lost when the enzyme is incubated with either of its substrates. Analysis of enzyme phosphorylation by high-pressure liquid chromatography and coupled mass spectrometry confirms that only one phosphate has been covalently linked to the enzyme. Only phosphoserine could be detected after acid hydrolysis of the labeled protein, and site-directed mutagenesis of serine residues located in or near the active site identifies the serine residue at position 102 as the site of autophosphorylation of E. coliGlmM.
Enhanced Customer Relationship Management Using Fuzzy Clustering Gayathri . A , Mohanavalli

Data mining is the process of extracting patterns from data. Data mining is becoming an increasingly important tool to transform this data into knowledgeable information. Clustering is a popular mining strategy that separates those data into subsets called clusters. The two main approaches of clustering is soft clustering and hard clustering. This project aims to implement soft clustering and hard clustering to enhance CRM (Customer Relationship Management). CRM is the process of managing a good relationship with customer and improve their profitability of their interactions with the customer. Data mining is an efficiently used tool in CRM. The telecom industry specifically handles the large data being generated by applying various data mining techniques. This project primarily focuses on applying apt clustering algorithm to identify the soft partitions of the customers namely the fuzzy c means (FCM) clustering algorithm to determine the churn ratio
Training Set Properties and Decision-Tree Taggers : A Closer Look

This paper examines three ways to improve part-of-speech tagging accuracy: by increasing the number of training examples presented to the tree learner, by increasing the number of word-specific subtrees grown, and by increasing the number of ngrams (preceding parts of speech) per training example. Though experimental results indicate that additional training data generally leads to the greatest amount improved accuracy, they also demonstrate that including word-specific subtrees can be useful and that trees considering two or more previous parts of speech in their classification decision are superior to those examining just one.
A Study On Designing Effective Introductory Materials for Information Visualization

Designing introductory materials is extremely important when developing new information visualization techniques. All users, regardless of their domain knowledge, first must learn how to interpret the visually encoded information in order to infer knowledge from visualizations. Yet, despite its significance, there has been little research on how to design effective introductory materials for information visualization. This paper presents a study on the design of online guides that educate new users on how to utilize information visualizations, particularly focusing on the employment of exercise questions in the guides. We use two concepts from educational psychology, learning type (or learning style) and teaching method, to design four unique types of online guides. The effects of the guides are measured by comprehension tests of a large group of crowdsourced participants. The tests covered four visualization types (graph, scatter plot, storyline, and tree map) and a complete range of visual analytics tasks. Our statistical analyses indicate that online guides which employ active learning and the top‐down teaching method are the most effective. Our study provides quantitative insight into the use of exercise questions in online guides for information visualizations and will inspire further research on design considerations for other elements in introductory materials.
Communication adaptive multi-robot simultaneous localization and tracking via hybrid measurement and belief sharing

Existing multi-robot cooperative perception solutions can be mainly classified into two categories, measurement-based and belief-based, according to the information shared among robots. With well-controlled communication, measurement-based approaches are expected to achieve theoretically optimal estimates while belief-based approaches are not because the cross-correlations between beliefs are hard to be perfectly estimated in practice. Nevertheless, belief-based approaches perform relatively stable under unstable communication as a belief contains the information of multiple previous measurements. Motivated by the observation that measurement sharing and belief sharing are respectively superior in different conditions, in this paper a hybrid algorithm, communication adaptive multi-robot simultaneous localization and tracking (ComAd MR-SLAT), is proposed to combine the advantages of both. To tackle the unknown or unstable communication conditions, the information to share is decided by maximizing the expected uncertainty reduction online, based on which the algorithm dynamically alternates between measurement-sharing and belief-sharing without information loss or reuse. The proposed ComAd MR-SLAT is evaluated in communication conditions with different packet loss rates and bursty loss lengths. In our experiments, ComAd MR-SLAT outperforms measurement-based and belief-based MR-SLAT in accuracy. The experimental results demonstrate the effectiveness of the proposed hybrid algorithm and exhibit that ComAd MR-SLAT is robust under different communication conditions.