Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-Dimensions Vernier Time-to-Digital Converter

A two-dimensions Vernier algorithm applied to a time to digital converter (TDC) is presented. The solution proposed minimizes the length of the delay lines used to perform the digital conversion leading to a better efficiency compared to traditional linear approaches. A 7-bits TDC prototype, targeted for all digital PLL application, was realized in 65 nm CMOS technology with a time resolution of 4.8 ps and a power consumption of 1.65 mW for a conversion rate of 50 Msps. The longest delay line used in such a prototype is one third than what would have been required for a standard Vernier TDC.
Frequent nut consumption and risk of coronary heart disease in women: prospective cohort study

Abstract Objective: To examine the relation between nut consumption and risk of coronary heart disease in a cohort of women from the Nurses' Health Study. Design: Prospective cohort study. Setting: Nurses' Health Study. Subjects: 86 016 women from 34 to 59 years of age without previously diagnosed coronary heart disease, stroke, or cancer at baseline in 1980. Main outcome measures: Major coronary heart disease including non-fatal myocardial infarction and fatal coronary heart disease. Results: 1255 major coronary disease events (861 cases of non-fatal myocardial infarction and 394 cases of fatal coronary heart disease) occurred during 14 years of follow up. After adjusting for age, smoking, and other known risk factors for coronary heart disease, women who ate more than five units of nuts (one unit equivalent to 1 oz of nuts) a week (frequent consumption) had a significantly lower risk of total coronary heart disease (relative risk 0.65, 95% confidence interval 0.47 to 0.89, P for trend=0.0009) than women who never ate nuts or who ate less than one unit a month (rare consumption). The magnitude of risk reduction was similar for both fatal coronary heart disease (0.61, 0.35 to 1.05, P for trend=0.007) and non-fatal myocardial infarction (0.68, 0.47 to 1.00, P for trend=0.04). Further adjustment for intakes of dietary fats, fibre, vegetables, and fruits did not alter these results. The inverse association persisted in subgroups stratified by levels of smoking, use of alcohol, use of multivitamin and vitamin E supplements, body mass index, exercise, and intake of vegetables or fruits. Conclusions: Frequent nut consumption was associated with a reduced risk of both fatal coronary heart disease and non-fatal myocardial infarction. These data, and those from other epidemiological and clinical studies, support a role for nuts in reducing the risk of coronary heart disease.
Human Resources Performance Analysis based on a Hybrid Method

Improving human resources performance (HRP) is the most important task of the century. However, we have few measures or management interventions to make such improvement possible; although we cannot identify the pattern to be followed by human resources because systems and processes in an organization are often regarded as a kiss of death to encouraging creativity. For improving human resource performance, at first, HRP needs to be measured and then the future of HRP needs to be defined. Therefore, in this paper, we seek to present a hybrid method for measuring and predicting the HRP, which can be used in human resources development. A hybrid method is created through a two-phase algorithm for measurement and prediction of HRP as the Human resources performance console (HRPC). HRPC calculates and predicates HRP in any period, thus it has been created to help managers. Nevertheless, the Hybrid method is tested and validated in Alupan company. Key words: Human resources performance (HRP); Time series analysis; human resources performance console (HRPC).
An Easy-To-Use Simulation Program Demonstrates Variations in Bacterial Cell Cycle Parameters Depending on Medium and Temperature

Many studies are performed on chromosome replication and segregation in Escherichia coli and other bacteria capable of complex replication with C phases spanning several generations. For such investigations an understanding of the replication patterns, including copy numbers of origins and replication forks, is crucial for correct interpretation of the results. Flow cytometry is an important tool for generation of experimental DNA distributions of cell populations. Here, a Visual Basic based simulation program was written for the computation of theoretical DNA distributions for different choices of cell cycle parameters (C and D phase durations, doubling time etc). These cell cycle parameters can be iterated until the best fit between the experimental and theoretical DNA histograms is obtained. The Excel file containing the simulation software is attached as supporting information. Cultures of Escherichia coli were grown at twelve different media and temperature conditions, with following measurements by flow cytometry and simulation of the DNA distributions. A good fit was found for each growth condition by use of our simulation program. The resulting cell cycle parameters displayed clear inter-media differences in replication patterns, but indicated a high degree of temperature independence for each medium. The exception was the poorest medium (acetate), where the cells grew with overlapping replication cycles at 42°C, but without at the lower temperatures. We have developed an easy-to-use tool for determination of bacteria's cell cycle parameters, and consequently the cells' chromosome configurations. The procedure only requires DNA distribution measurements by flow cytometry. Use of this simulation program for E. coli cultures shows that even cells growing quite slowly can have overlapping replication cycles. It is therefore always important not only to assume cells' replication patterns, but to actually determine the cell cycle parameters when changing growth conditions.
A similarity-window based background estimation approach

Background estimation is one of the most challenging phases in extracting foreground objects from video sequences. In this paper we present a background modeling approach that uses the similarity of frames to extract background areas from the video sequence. We use a window over the frames history and compute the similarity between the selected frames of this window as a similarity window. The properties of similarity window depend on the characteristics of the scene and can be adjusted parametrically. Our primary results show that if proper parameters are chosen, this method can give a good approximation of the background model.
Reverse-link macrodiversity in CDMa distributed antenna systems with imperfect channel estimation

The performance of reverse-link macrodiversity in CDMA distributed antenna (DA) systems with imperfect channel estimation is analyzed by taking the effect of multi-path fading environment into account. A detailed multi-access model with MRC-based multi-path micro diversity and multi-antenna macrodiversity is presented and exact reverse-link E b/I0 expression is derived. The investigation shows that when multipath fading and channel estimation errors occur, for the reverse-link of CDMA DA systems, the Eb/I0 performance degrades and the macrodiversity gains diminish more rapidly in comparison with the results obtained based on the ideal assumption. Furthermore, it is shown that, on the reverse-link, the conventional solution recommended in most of previous studies that the number of remote antennas per "virtual cell" set to four is no longer cost-effective in such an imperfect environment
Amyloidosis of the head and neck: a clinicopathological study of cases with long-term follow-up

Extracellular deposits of insoluble proteinaceous material giving a starch-like reaction when treated with iodine and sulphuric acid and accumulating in tissue was for the first time described by Rokitansky in 1842 [1]. It was not until 1851 that Virchow applied the term “amyloidosis” to describe this deposition [2]. An amorphous substance called amyloid (insoluble fibril-forming protein) is deposited in extracellular spaces of organs and tissues. Amyloid deposits, under the electron microscope, appear as non-branching fibrils with a cross-linked, β-pleated sheet conformation. They are eosinophilic after haematoxylin–eosin staining and display apple-green birefringence with polarized light when stained with Congo red. Chronic inflammations of bacterial or non-bacterial origin and immunological immune-competent neoplasm cells are examples of factors that induce amyloid fibril biosynthesis. The organs and tissues where amyloid deposits occur become stiff and plastic, having a hyaline-like appearance that leads to a loss of previous function [3].
Mismatch Detection and Compensation Method for the LINC System Using a Closed-Form Expression

This paper proposes a simple and straightforward path mismatch detection method with a closed-form expression for linear amplification with nonlinear components (LINC) system implementation. In this work, a test vector signal set with three phase differences and one amplitude difference is employed to detect the amplitude and phase mismatches at the same time. The proposed method can predict the exact mismatch value without any iterations, because the mismatch value has a unique solution with a closed-form expression with the proposed test signal set. Moreover, the sensitivity of the proposed method to the measurement noise is also analyzed for practical implementation of LINC system. The LINC system is realized with the proposed mismatch detection method and the performance is evaluated with a IEEE 802.16 WiMAX signal, which has 7 MHz channel bandwidth and 16-QAM. The error vector magnitude (EVM) of -37.4 dB is obtained through performance testing, which meets the performance requirement of -24 dB EVM. The proposed mismatch detection method is validated to improve the LINC system performance.
Specification of rewriting strategies

User-definable strategies for the application of rewrite rules provide a means to construct transformation systems that apply rewrite rules in a controlled way. This paper describes a strategy language and its interpretation. The language is used to control the rewriting of terms using labeled rewrite rules. Rule labels are atomic strategies. Compound strategies are formed by means of sequential composition, nondeterministic choice, left choice, fixed point recursion, and two primitives for expressing term traversal. Several complex strategies such as bottom-up and top-down application and (parallel) innermost and (parallel) outermost reduction can be defined in terms of these primitives. The paper contains two case studies of the application of strategies.
Self-destructing Instant Messages by Employing KAD DHT Network

Privacy protection is becoming more and more important due to the ubiquitous access to information. Distributed Hash Tables (DHTs) are widely used by peer-to-peer networks with more than one million concurrently active users. This paper proposes and designs a web based self-Destructing Instant Messenger (DIM) on eMule KAD DHT network in China without any involvement of users and trusted systems, thus protecting the privacy of instant messages. Comprehensive experiments are performed to evaluate the features of eMule KAD DHT network and analyze the impacts of the features on the DIM. Experimental results reveal that the lifespan of data objects in the eMule KAD network in China is much shorter than that defined by the KAD protocol, and the pattern of eMule peers in China has a significant impact on the behavior of DIM. Furthermore, an approach of prstoring subkeys is designed to eliminate the overhead involved in the distribution and retrieving of subkeys, thus optimizing the performance of DIM.
Causal commutative arrows

Abstract Arrows are a popular form of abstract computation. Being more general than monads, they are more broadly applicable, and, in particular, are a good abstraction for signal processing and dataflow computations. Most notably, arrows form the basis for a domain-specific language called Yampa, which has been used in a variety of concrete applications, including animation, robotics, sound synthesis, control systems, and graphical user interfaces. Our primary interest is in better understanding the class of abstract computations captured by Yampa. Unfortunately, arrows are not concrete enough to do this with precision. To remedy this situation, we introduce the concept of commutative arrows that capture a noninterference property of concurrent computations. We also add an init operator that captures the causal nature of arrow effects, and identify its associated law. To study this class of computations in more detail, we define an extension to arrows called causal commutative arrows (CCA), and study its properties. Our key contribution is the identification of a normal form for CCA called causal commutative normal form (CCNF). By defining a normalization procedure, we have developed an optimization strategy that yields dramatic improvements in performance over conventional implementations of arrows. We have implemented this technique in Haskell, and conducted benchmarks that validate the effectiveness of our approach. When compiled with the Glasgow Haskell Compiler (GHC), the overall methodology can result in significant speedups.
Developing the evidence base for community-governed health promotion and prevention

The community governance or management of health promotion together with evidence about the health of a community is essential to the success of community health collaborations and to community empowerment and change. This paper offers an introductory review of the literature on evidence based public health and health promotion and provides a rationale and method for developing an evidence-based resource to support the community governance of health promotion. The review outlines the origin of and current debate around evidence-based health promotion; and presents a model that describes the use of two major forms of evidence referred to as guiding and evaluative evidence. While two forms of evidence are described (guiding and evaluative) the importance of guiding evidence for community-based and community-governed collaborations is emphasised and is the primary focus of this paper. The Australian national health priority areas are introduced, and a second model, which draws attention to determinants of health, inequalities in health and health status is offered. The model will be used to guide data collection and analysis in the first stage of an ongoing research thesis and subsequent health promotion activities with community members in the second stage of the research.
Doing critical IS research: the question of methodology

INTRODUCTION Critical information systems (IS) research denotes a critical process of inquiry that seeks to achieve emancipatory social change by going beyond the apparent to reveal hidden agendas, concealed inequalities and tacit manipulation involved in a complex relationship between IS and their social, political and organisational contexts. It has its philosophical and theoretical roots in critical social theory (Held, 1980; Fay, 1987; Morrow and Brown, 1994). As a critical social researcher studies the social life of people in order to help them change conditions and improve their lives, so too does a critical IS researcher. By demystifying technological imperatives and managerial rationalism justifying a particular information system design, the critical IS researcher helps both IS practitioners and users understand its social consequences, envisage desirable alternatives and take action. Like interpretive approaches to IS research, critical theory-informed approaches came along as a reaction to positivism. While interpretive researchers aim to understand and describe “the context of the information system, and the process whereby the information system influences and is influenced by its context” (Walsham, 1993),
Joint kernel collaborative representation on Tensor manifold for face recognition

Gabor-based region covariance matrix (GRCM) is an emerging face feature descriptor, which has been shown promising for face recognition. The GRCM lies on Tensor manifold is inherently non-Euclidean, hence a disconnect exists between GRCM descriptor and vector-based classifiers, such as collaborative representation-based classifier (CRC). CRC is a strong alternative to sparse representation-based classifier yet enjoys high efficiency. In this paper, we bridge GRCM and CRC with kernel learning method. We investigate several geodesic distances on Tensor manifold that satisfy the Mercer's condition for kernel CRC construction as well as for speedy computation. Apart from that, we also devise two strategies to jointly combine the regionalized GRCMs with Tensor kernel CRC. Extensive experiments on the ORL and FERET datasets are conducted to verify the efficacy of the proposed method.
Convergent Smoothing and Segmentation of Noisy Range Data in Multiscale Space

With few exceptions, most of the existing noise reduction and data segmentation algorithms are only suited to image data. Therefore, an adaptive smoothing algorithm, with model-based masks, within a scale space framework is proposed for range data in this paper. This algorithm smoothes range data that conform to predefined, geometric models, while leaving other data points unaffected. The convergence of the algorithm in yielding dominant features is shown based on its compliance with the anisotropic diffusion concept. The weights of the smoothing masks are adaptively calculated according to the Mahalanobis distances between range data and model-based predictions. These behave as the diffusion coefficient in the anisotropic diffusion equation, thus satisfying the requirements of the causality criterion that no new features are introduced from fine to coarse scales. The computational complexity of this algorithm is examined and compared to that of the well-known RANSAC feature extraction algorithm. Unlike RANSAC, it has the advantage that the computational complexity is less affected by increasing the order of the model, and is independent of the number of model outliers. The proposed algorithm can be used to smooth range data in multiscale space by increasing the number of smoothing iterations. Robust, robot-occlusion-invariant features are then easily extracted from the smoothed data by least squares fitting algorithms.
Growth Condition and Degradation Dynamics of p-Chloroaniline Degrading Strain

Growth condition of p-chloroaniline (p-CA) degrading Bacillus licheniformis named strain ycsd02 which was isolated from rhizosphere soil in phragmites wetland and stored in our labrary was studied. The result showed that the optimal culture temperature, culture pH value and dissolved oxygen for satisfactory cells growth were about 37¿, pH7.2 and 4 mg•L-1 in LB liquid medium. Growth of strain ycsd02 cells was inhibited by p-CA at the concentration up to 200 mg•L-1. The biodegradation of p-CA by ycsd02 cells had a cutty lag phase at initial concentrations more than 40 mg•L-1 while no lag phase at concentrations less than 40 mg•L-1. Results could offer useful information for the application of strain ycsd02 in bioremediation.
Triple H-shaped multiple band frequency reconfigurable patch antenna

In this paper "Triple H-Shaped Multiple Band Frequency Reconfigurable Patch Antenna" is presented. The purpose of this research is to make such antenna which can cover multiple applications by using electronic switches. This presented antenna has 8 different modes and each mode cover at least triple bands which cover applications like GSM, ISM, GPS and many other wireless applications. The substrate used for this antenna is FR-4 having epsilon 4.4 and modeling and simulations done in CST MWS. All main parameters of antenna results like its Sil parameter, directivity and gain discussed in this paper briefly.
Improved histogram-based feature compensation for robust speech recognition and unsupervised speaker adaptation

Feature compensation for noise robust speech recognition becomes more effective if normalization of time-derivative parameters is taken into account. This paper describes an implementation of Delta-Cepstrum Normalization (DCN) that runs with only minimum response time. The proposed algorithm, referred to as Recursive DCN, provides word error rate improvements comparable to conventional DCN. Since DCN includes the procedure that adjusts the mismatch between the cepstrum part and the delta-cepstrum part, it works effectively even if only small amount of data can be used. We also investigate the possibility of applying DCN to unsupervised speaker adaptation. It is shown that DCN adaptation improves the recognition accuracy even without reference transcription of the adaptation data. Finally, DCN adaptation is combined with Feature-space Maximum Likelihood Linear Regression (FMLLR). It shows promising results in the batch mode experiments, although the improvement is rather small in the recursive mode.
Racial Income Inequality, Perceptions of Competition, and Negative Interracial Outcomes

There exists a racial income gap in America: Blacks earn ∼38% less than Whites, but little is known about its relation to interracial psychological outcomes. Toward this end, the present research examined associations between the Black–White income gap and perceptions of interracial competition and, subsequently, negative intergroup outcomes. Study 1 extracted data from a large, preexisting data set (N = 2,543) and provided initial support for the hypothesis that higher levels of racial income inequality are associated with increased perceptions of competition. Study 2 then recruited approximately equal numbers of White and Black participants (N = 1,731) and demonstrated that increases in racial income inequality predict increased perceptions of competition, discrimination, behavioral avoidance, and intergroup anxiety. Implications for theory development and public policy are discussed.
POTENTIAL OF THE ADS40 AERIAL SCANNER FOR ARCHAEOLOGICAL PROSPECTION IN RHEINAU, SWITZERLAND

A sizing catheter and method of measuring a preselected internal opening within a patient to provide a rapid and precise determination of a stretched diameter of the preselected internal opening. The sizing catheter includes a dilation balloon constructed of a thin expandable plastic which is inflatable and is utilized to determine a size of the preselected opening. The dilation balloon is inflated to an inflation threshold, wherein the dilation balloon deforms about the preselected opening and the size of the dilation balloon adjacent the preselected opening approximates a stretched diameter of the preselected opening. The sizing catheter and method may be utilized to determine an appropriate sized occluding device to thereby occlude the preselected opening.
Democracy and Economic Growth: A Meta-Analysis

Despite a sizeable theoretical and empirical literature, no firm conclusions have been drawn regarding the impact of political democracy on economic growth. This article challenges the consensus of an inconclusive relationship through a quantitative assessment of the democracy-growth literature. It applies meta-regression analysis to the population of 483 estimates derived from 84 studies on democracy and growth. Using traditional meta-analysis estimators, the bootstrap, and Fixed and Random Effects meta-regression models, it derives several robust conclusions. Taking all the available published evidence together, it concludes that democracy does not have a direct impact on economic growth. However, democracy has robust, significant, and positive indirect effects through higher human capital, lower inflation, lower political instability, and higher levels of economic freedom. Democracies may also be associated with larger governments and less free international trade. There also appear to be country- and region-specific democracy-growth effects. Overall, democracy's net effect on the economy does not seem to be detrimental.