Miracle-dz/UniFAR-FTUs huggingface dataset:
Dental plaque, preventive care, and tooth brushing associated with dental caries in primary teeth in schoolchildren ages 6–9 years of Leon, Nicaragua

Background Our study aimed to evaluate the effect of various risk indicators for dental caries on primary teeth of Nicaraguan children (from Leon, Nicaragua) ages 6 to 9, using the negative binomial regression model. Material/Methods A cross-sectional study was carried out to collect clinical, demographic, socioeconomic, and behavioral data from 794 schoolchildren ages 6 to 9 years, randomly selected from 25 schools in the city of León, Nicaragua. Clinical examinations for dental caries (dmft index) were performed by 2 trained and standardized examiners. Socio-demographic, socioeconomic, and behavioral data were self-reported using questionnaires. Multivariate negative binomial regression (NBR) analysis was used. Results Mean age was 7.49±1.12 years. Boys accounted for 50.1% of the sample. Mean dmft was 3.54±3.13 and caries prevalence (dmft >0) was 77.6%. In the NBR multivariate model (p<0.05), for each year of age, the expected mean dmft decreased by 7.5%. Brushing teeth at least once a day and having received preventive dental care in the last year before data collection were associated with declines in the expected mean dmft by 19.5% and 69.6%, respectively. Presence of dental plaque increased the expected mean dmft by 395.5%. Conclusions The proportion of students with caries in this sample was high. We found associations between dental caries in the primary dentition and dental plaque, brushing teeth at least once a day, and having received preventive dental care. To improve oral health, school programs and/or age-appropriate interventions need to be developed based on the specific profile of caries experience and the associated risk indicators.
Universiteit Leiden Opleiding Informatica A Pushdown System Representation for Unbounded Object Creation

We introduce a block-structured programming language which supports object creation, global variables, static scope and recursive procedures with local variables. Because of the combination of recursion, local variables and object creation, the number of objects stored during a computation is potentially unbounded. However, we show that a program can be viewed as a type of pushdown automata, for which the halting problem as well as LTL and CTL model checking are decidable
Fast Inter Mode Decision Algorithm for H.264/AVC Video Encoding System Based on Correlation of Macroblock

To more effectively reduce temporal and spatial redundancy in the MPEG-4 Part-10 AVC/H.264, motion compensation uses variable block sizes and directional inter prediction investigates all available coding modes to determine the best one. However, these functions are performed for all variable block sizes, high complexity results due to the large number of combinations of coding modes. The researchers propose a fast inter mode decision to reduce the number of combinations of candidate modes using predictive data from macroblock correlations of adjacent frames. An adaptive thresholding scheme using the rate-distortion costs of neighboring blocks is applied for an early decision of the best macroblock in the inter-mode search process.
State space regularization in the nonstationary inverse problem for diffuse optical tomography

In this paper, we present a regularization method in the nonstationary inverse problem for diffuse optical tomography (DOT). The regularization is based on a choosing time evolution process such that in a stationary state it has a covariance function which corresponds to a process with similar smoothness properties as the first-order smoothness Tikhonov regularization. The proposed method is computationally more lightweight than the method where the regularization is augmented as a measurement. The method was tested in the case of the inverse problem of DOT. A solid phantom with optical properties similar to tissue was made, incorporating two moving parts that simulate two different physiological processes: a localized change in absorption and a surrounding rotating two-part shell which simulates slow oscillations in the tissue background physiology. A sequence of measurements of the phantom was made and the reconstruction of the image sequence was computed using this method. It allows the recovery of the full time series of images from relatively slow measurements with one source active at a time. In practice, this allows instruments with a larger dynamic range to be applied to the imaging of functional phenomena using DOT.
The role of N-glycans in colorectal cancer progression: potential biomarkers and therapeutic applications

Changes in glycosylation, which is one of the most common protein post-translational modifications, are considered to be a hallmark of cancer. N-glycans can modulate cell migration, cell-cell adhesion, cell signaling, growth and metastasis. The colorectal cancer (CRC) is a leading cause of cancer-related mortality and the correlation between CRC progression and changes in the pattern of expression of N-glycans is being considered in the search for new biomarkers. Here, we review the role of N-glycans in CRC cell biology. The perspectives on emerging N-glycan-related anticancer therapies, along with new insights and challenges, are also discussed.
How Different Are Malware Collected Actively and Passively ?

-A new open-source tool chain with malware collection, detection, and analysis is presented, evaluated, and open sourced. It actively collects malware through two channels: web-links and peer-to-peer. Then it detects malware with multiple anti-virus scanners and analyzes their host and network activities on virtual machines. The evaluation shows the differences between the malware collected by the traditional passive honeypot approach and this active approach, in the aspects of distribution, timeliness, and degree of network and host activity, i.e., activeness. These two collections are quite distinct and disjoint. Among the 800 and 354 malware programs collected in one month actively and passively, respectively, 79% of the passively captured malware are active bots and 59% of the actively captured malware are passive Trojans. 16% of actively captured are zero-day malware, but no zero-day malware had been captured by the passive approach. Moreover, the passive approach receives mostly, 98%, malware with network behavior while the active approach collects both, i.e., 77% with network behavior and 23% with only host behavior or no action.
The $S$-Transform From a Wavelet Point of View

The S-transform is becoming popular for time-frequency analysis and data-adaptive filtering thanks to its simplicity. While this transform works well in the continuous domain, its discrete version may fail to achieve accurate results. This paper compares and contrasts this transform with the better known continuous wavelet transform, and defines a relation between both. This connection allows a better understanding of the S-transform, and makes it possible to employ the wavelet reconstruction formula as a new inverse S-transform and to propose several methods to solve some of the main limitations of the discrete S-transform, such as its restriction to linear frequency sampling.
Optimal Monetary Policy in a Model with Agency Costs

This paper integrates a fully explicit model of agency costs into an otherwise standard Dynamic New Keynesian model in a particularly transparent way. A principal result is the characterization of agency costs as endogenous markup shocks in an output-gap version of the Phillips curve. The model's utility-based welfare criterion is derived explicitly and includes a measure of credit market tightness that we interpret as a risk premium. The paper also fully characterizes optimal monetary policy and provides conditions under which zero inflation is the optimal policy. Finally, optimal policy can be expressed as an inflation targeting criterion that (depending upon parameter values) can be either forward or backward looking. Copyright (c) 2010 The Ohio State University.
Clustering sequences of categorical values

Conceptual clustering is a discovery process that groups a set of data in the way that the intra-cluster similarity is maximized and the inter-cluster similarity is minimized. Traditional clustering algorithms employ some measure of distance between data points in n-dimensional space. However, not all data types can be represented in a metric space, therefore no natural distance function is available for them. We address the problem of clustering sequences of categorical values. We present a measure of similarity for the sequences and an agglomerative hierarchical algorithm that uses frequent sequential patterns found in the database to efficiently generate the resulting clusters. The algorithm iteratively merges smaller, similar clusters into bigger ones until the requested number of clusters is reached.
The Design of the Microarchitecture of UltraSPARCTM-I

The realization of a high pe@ormance modem microprocessor involves hundreds of person-years of conception, logic design, circuit design, layout drawing, etc. In order to leverage effectively the 5-10 millions of transistors available, careful microarchitecture tradeoff analysis must be pe@ormed. This paper describes not only the microarchitecture of UltraSPARC-I, a 167 MHz 64-b fourway superscalar processor, but more importantly it presents the analysis and tradeoffs that were made “en route” to the$nal chip. Among several issues, the in-order execution model is compared with alternatives, variations of the issue-width of the machine as well as the number of functional units are described, subtle features that are part of the memory hierarchy are explained, and the advantages of the packet-switched interconnect are exposed.
Software-Defined Radio design based on GALS architecture for FPGAs

The design, implementation and comparison of Software-Defined Radio (SDR) based on GALS architectures were focused on. GALS port controllers, previously proposed for implementation in ASIC, have been redesigned for use in conventional FPGAs, eliminating the need for hard macros. A GALS architecture for SDR was proposed and validated, comprising a wrapper described in VHDL. In addition, some guidelines for its implementation in synchronous designs are shown. Whereas asynchronous wrappers were designed to be robust and to dispense timing verification, the verification effort is negligible, since the same test benches can be used for both designs. When compared with a synchronous design, a reduction of 39% in the dynamic consumption was obtained, what may be even greater if the idle clock periods are considered. We saw that for the same device, it is possible to earn 53% in the data flow (throughput), signifying that the radio is able to process a broader band, or that the cost of equipment can be reduced, once it is possible to adopt a cheaper FPGA version with lower performance.
Evaluation of the Vocabulary Tree Object Recognition Method For a Mobile Robotic Platform

This paper addresses object perception applied to mobile robotics. Being able to perceive semantically meaningful objects in unstructured environments is a key capability in order to make robots suitable to perform high-level tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. Here we extensively evaluate the vocabulary tree object recognition method in a very challenging dataset of 30 objects captured while navigating with a mobile robot in a typical indoor setting. In order to make the method suitable for this detection task, a sliding windows method as well as two segmentation methods, based in intensity and depth information, are evaluated. The obtained results are compared with those obtained in the same dataset by two other popular state of the art object recognition methods: SIFT object detection method and the Boosted Cascade of Weak Classifiers.
Assessment of educational divide and computer literacy among primary school students in Selangor, Malaysia

The purpose of this study was to assess the educational divide and computer literacy among primary school students located in a rural school as well as an urban one Specifically the places are in Sabak Bernam and Shah Alam, Selangor. Demographic profiles play an important part in determining the education divide between the schools such as family background, income, parents' educational qualification and other socio-economic factors These in turn would affect the computer literacy of the units of analysis A total of 120 Year 6 students in the two primary schools in Sabak Bernam and Shah Alam participated in this study. Questionnaires were distributed to students in the presence of the respective class teachers, hence, the returned survey for ms was 100%. Using SPSS to analyze the data, the results indicated that the educational divide and computer literacy are significantly low. This evidence brooks well for the government and continuous support for primary schools is recommended in line with the Prime Minister's agenda of "People first, performance now".
VLSI Implementation of a Fixed-Complexity Soft-Output MIMO Detector for High-Speed Wireless

This paper presents a low-complexity MIMO symbol detector with close-Maximum a posteriori performance for the emerging multiantenna enhanced high-speed wireless communications. The VLSI implementation is based on a novel MIMO detection algorithm called Modified Fixed-Complexity Soft-Output (MFCSO) detection, which achieves a good trade-off between performance and implementation cost compared to the referenced prior art. By including a microcode-controlled channel preprocessing unit and a pipelined detection unit, it is flexible enough to cover several different standards and transmission schemes. The flexibility allows adaptive detection to minimize power consumption without degradation in throughput. The VLSI implementation of the detector is presented to show that real-time MIMO symbol detection of 20 MHz bandwidth 3GPP LTE and 10 MHz WiMAX downlink physical channel is achievable at reasonable silicon cost.
A new hybrid collective classification method based on random walk and link pattern

Collective classification, which is represented to classify unobserved nodes simultaneously in networked data is becoming an important research area with applications in several domains, such as the classification of documents, image processing. Most algorithms are based on the hypothesis that nearby nodes tend to have the same label. However, there are many networks that do not necessarily satisfy this hypothesis. In this paper, we present a new method based on random walk and link pattern of the network. It adopts the pseudoinverse laplacian matrix of the graph as similarity measure to identify nearby nodes and assigns an initial label for each unlabeled node, then iteratively update the label of unlabeled nodes based on the link pattern. The experimental results on two real world datasets demonstrate that the proposed method outperforms the other state-of-art approaches for this problem.
The off-Season is ‘No Season’: The Case of the Danish Island of Bornholm

For all cold water resorts in peripheral areas, it is the ‘dream’ of the marketing department to expand the season but very few have succeeded. The purpose of this paper is to analyse the possibilities using the Danish Baltic Island of Bornholm as a case example. For the past three years, departing visitors have been surveyed as part of a research programme, ‘Tourism in the peripheral areas of Europe’, with the purpose of analysing tourism demand. Particular attention was given to visitors in the off-season. The sad conclusion is that the findings indicate no realistic possibilities for increasing the off-season market. The visitors in the off-season to Bornholm are mostly visiting friends and relatives, and repeat visitors with a special love for the island. The Bornholm tourism product is the nature, the atmosphere and the landscape. Even though the product is still there in autumn, winter and spring, the holidaymakers prefer to enjoy it in sunshine. Consequently, the tourism businesses, with hotels as an important exception, have adjusted to the short season. A strategy for broadening the season would imply dramatic changes in the operation of the tourist product out of season. Even then, it would be a very uncertain goal.
Explicit Isoperimetric Constants and Phase Transitions in the Random-Cluster Model

The random-cluster model is a dependent percolation model that has applications in the study of Ising and Potts models. In this paper, several new results are obtained for the random-cluster model on nonamenable graphs with cluster parameter q > 1. Among these, the main ones are the absence of percolation for the free random-cluster measure at the critical value and examples of planar regular graphs with regular dual where p free c (q) > p wired u (q) for q large enough. The latter follows from considerations of isoperimetric constants, and we give the first nontrivial explicit calculations of such constants. Such considerations are also used to prove nonrobust phase transition for the Potts model on nonamenable regular graphs.
A 1.2V, 0.1-6.0 GHz, Two-Stage Differential LNA Using Gain Compensation Scheme

A broadband low-noise amplifier (LNA) in a 0.13 mum CMOS is presented. The LNA consists of two cascaded gain stages. The first stage is a resistive feedback amplifier for an input impedance matching, and the second stage is an inductive peaking amplifier for gain compensation. Measurement results exhibit a voltage gain of 14 dB and a gain variation less than 1.7 dB over the frequency range of 0.1 to 6.0 GHz. Its input return loss is below -8.3 dB and the noise figure is 4.0 to 4.7 dB across the bandwidth. The LNA consumes 16 mW from a 1.2 V supply and occupies 0.13 mm2.
An Algorithm for Critical Nodes Problem in Social Networks Based on Owen Value

Discovering critical nodes in social networks has many important applications. For finding out the critical nodes and considering the widespread community structure in social networks, we obtain each node's marginal contribution by Owen value. And then we can give a method for the solution of the critical node problem. We validate the feasibility and effectiveness of our method on two synthetic datasets and six real datasets. At the same time, the result obtained by using our method to analyze the terrorist network is in line with the actual situation.
Modulation of Adipocytokines Production and Serum NEFA Level by Metformin, Glimepiride, and Sitagliptin in HFD/STZ Diabetic Rats

Type 2 diabetes mellitus (T2DM) is a group of metabolic disorders characterized by hyperglycemia owing to insulin resistance and/or insulin deficiency. Current theories of T2DM pathophysiology include a decline in β-cells function, a defect in insulin signaling pathways, and a dysregulation of secretory function of adipocytes. This study aimed to investigate the effect of different antidiabetic drugs on serum levels of certain adipocytokines and nonesterified fatty acids (NEFA) in high-fat diet (HFD)/streptozotocin- (STZ-) induced diabetic rats. All treatments significantly decreased serum NEFA level. Metformin and sitagliptin increased serum adiponectin level, whereas they decreased serum leptin level. Glimepiride showed significant decline in serum levels of both adiponectin and leptin. All treatments remarkably ameliorated insulin resistance, suggested by an improvement of glycemic control, a significant reduction in homeostasis model assessment of insulin resistance (HOMA-IR), and a correction in lipid profile. Modulation of adipocytokines production (i.e., increased serum adiponectin and decreased serum leptin) may also underlie the improvement of insulin resistance and could be a possible mechanism for the beneficial cardiovascular effects of metformin and sitagliptin.
Development of topology and power electronic devices for solid-state circuit breakers

With the development of power electronic devices, solid-state circuit breakers (SSCBs) are likely to replace traditional mechanical breakers and applied to the power system. This paper firstly points out the disadvantages of traditional mechanical breakers. Then, the history of SSCBs has been introduced. The classification, characteristics and working principles of the SSCBs are summarized and shortcomings of different SSCBs are pointed out. This paper introduces the domestic and foreign researches on solid-state circuit breakers, which indicates that studies tend to focus on hybrid solid-state DC circuit breakers in recent years. Based on the applications of SSCBs, different power electronic devices have been compared and the result shows the IGBT-based SSCBs are suitable for a low-current branch while the IGCT-based SSCBs are a good choice for a medium-current branch. Finally, this paper points out SSCBs will develop along a high-power direction and accordingly series-parallel problems of power electronic devices must be overcome.
Pressure overload induces cardiac hypertrophy in angiotensin II type 1A receptor knockout mice.

BACKGROUND Many studies have suggested that the renin-angiotensin system plays an important role in the development of pressure overload-induced cardiac hypertrophy. Moreover, it has been reported that pressure overload-induced cardiac hypertrophy is completely prevented by ACE inhibitors in vivo and that the stored angiotensin II (Ang II) is released from cardiac myocytes in response to mechanical stretch and induces cardiomyocyte hypertrophy through the Ang II type 1 receptor (AT1) in vitro. These results suggest that the AT1-mediated signaling is critical for the development of mechanical stress-induced cardiac hypertrophy. METHODS AND RESULTS To determine whether AT1-mediated signaling is indispensable for the development of pressure overload-induced cardiac hypertrophy, pressure overload was produced by constricting the abdominal aorta of AT1A knockout (KO) mice. Quantitative reverse transcriptase-polymerase chain reaction revealed that the cardiac AT1 (probably AT1B) mRNA levels in AT1A KO mice were <10% of those of wild-type (WT) mice and were not affected by pressure overload. Chronic treatment with subpressor doses of Ang II increased left ventricular mass in WT mice but not in KO mice. Pressure overload, however, fully induced cardiac hypertrophy in KO as well as WT mice. There were no significant differences between WT and KO mice in expression levels of fetal-type cardiac genes, in the left ventricular wall thickness and systolic function as revealed by the transthoracic echocardiogram, or in the histological changes such as myocyte hypertrophy and fibrosis. CONCLUSIONS AT1-mediated Ang II signaling is not essential for the development of pressure overload-induced cardiac hypertrophy.
Search queries based sales forecasting on Taobao

In recent years, rapid development E-commerce has occurred in China. E-commerce and longtail economy are playing an increasingly important role in the national economy. How to accurately forecast the sales of E-commerce website is valuable. On the basis of building theoretical frame of keywords search queries and online shopping transaction volume, this paper took Taobao.com - the largest E-commerce retail website in China-as an example, composed the keywords into composite index by stepwise synthesis, then analyzed the relationship between the sales of different categories of goods and the corresponding composite index through the regression model, made a prediction test, and finally got the forecast results of daily sales for different categories goods. Compared the forecast results to the actual data, the Mean Absolute Percentage Error is fewer than nine percent.