Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Bandpass Filter Shape and Interference Cancellation Control Utilizing Bandpass–Bandstop Filter Cascade

A tunable highly integrated bandpass-bandstop filter (BSF) cascade that is capable of dynamically relocating its transmission zeros arbitrarily close to its passband without causing parasitic resonances and additional mismatch loss is demonstrated in this paper. An arbitrary phase BSF that enables a compact cascade topology and an extension of the classical coupling matrix synthesis for filters terminated with a complex impedance are the key advantages of the proposed bandpass-BSF cascade. Independent and simultaneous tuning of the passband center frequency, bandwidth, and transmission zeros are possible in this topology. The proposed cascade synthesis approach is experimentally validated using commercially available lumped elements. In these implementations the transmission zeros can be placed on the skirt of the bandpass filter and can be used to create high isolation (50-dB notch 4.7% away from the passband edge), increase the selectivity of the passband, and tune the fractional bandwidth from 3% to 9% without additional mismatch loss.
Processing and domain selection: Quantificational variability effects

Three studies investigated how readers interpret sentences with variable quantificational domains, for example, The army was mostly in the capital, where mostly may quantify over individuals or parts (Most of the army was in the capital) or over times (The army was in the capital most of the time). It is proposed that a general conceptual economy principle, No Extra Times, discourages the postulation of potentially unnecessary times, and thus favours the interpretation quantifying over parts. Disambiguating an ambiguously quantified sentence to a quantification over times interpretation was rated as less natural than disambiguating it to a quantification over parts interpretation (Experiment 1). In an interpretation questionnaire, sentences with similar quantificational variability were constructed so that both interpretations of the sentence would require postulating multiple times; this resulted in the elimination of the preference for a quantification over parts interpretation, suggesting the parts preference observed in Experiment 1 is not reducible to a lexical bias of the adverb mostly (Experiment 2). An eye movement recording study showed that, in the absence of prior evidence for multiple times, readers exhibit greater difficulty when reading material that forces a quantification over times interpretation than when reading material that allows a quantification over parts interpretation (Experiment 3). These experiments contribute to understanding readers' default assumptions about the temporal properties of sentences, which is essential for understanding the selection of a domain for adverbial quantifiers and, more generally, for understanding how situational constraints influence sentence processing.
Automating Composite SLA Management Tasks by Exploiting Service Dependency Information

According to the Internet of Services vision, composite services are created by composing services to complex business processes. The relationships between services in a composition are defined by Service Level Agreements (SLAs). Managing composite SLAs is a complex task which is currently performed manually. In this paper we present an approach for automating the management of composite SLAs by exploiting the explicit knowledge about dependencies between composed services. We define a formal model for representing a set of dependencies. A set of algorithms exploits this information to automate tasks of composite SLA management. These tasks are the validation of SLAs during negotiation, the evaluation of SLA renegotiation requests and the evaluation of SLA violations with regard to their effects on other services. We have validated our approach based on a logistics scenario. We present results with respect to performance and a set of test cases demonstrating the added value of dependency information based automated SLA management.
Feature Learning from Spectrograms for Assessment of Personality Traits

Several methods have recently been proposed to analyze speech and automatically infer the personality of the speaker. These methods often rely on prosodic and other hand crafted speech processing features extracted with off-the-shelf toolboxes. To achieve high accuracy, numerous features are typically extracted using complex and highly parameterized algorithms. In this paper, a new method based on feature learning and spectrogram analysis is proposed to simplify the feature extraction process while maintaining a high level of accuracy. The proposed method learns a dictionary of discriminant features from patches extracted in the spectrogram representations of training speech segments. Each speech segment is then encoded using the dictionary, and the resulting feature set is used to perform classification of personality traits. Experiments indicate that the proposed method achieves state-of-the-art results with an important reduction in complexity when compared to the most recent reference methods. The number of features, and difficulties linked to the feature extraction process are greatly reduced as only one type of descriptors is used, for which the 7 parameters can be tuned automatically. In contrast, the simplest reference method uses 4 types of descriptors to which 6 functionals are applied, resulting in over 20 parameters to be tuned.
Localization in a wide range of industrial environments using relative 3D ceiling features

This paper presents a localization system for mobile robots that are able to navigate autonomously in industrial environments like factory and exhibition halls. Previous approaches show that ceiling structures like beams, pipes and lighting installation are well-suited for self-localization in large halls. With this paper we describe how to use ceiling structures, measured with a 3D laser range sensor, as natural landmarks. Due to the novel relative representation of 3D ceiling features this method can be used in a wide range of industrial halls with sloped, stepped and even curved ceiling structures. In addition to this new algorithm the paper presents experimental results with an autonomous fork lift working without the need for artificial landmarks or extra infrastructure.
A low-voltage OP amp with digitally controlled algorithmic approximation

This paper presents a new architecture of digitally controlled algorithmic OP amp suitable for scaled CMOS technologies. With inverter-based gain stages and digitally-assisted damping control, the amplifier achieves high-gain and wide input/output ranges even at the minimally allowable supply voltage by digital circuits. The amplifier, implemented in a standard 0.18 mum CMOS, shows a DC gain of 73 dB and 95% settling time of 41 ns at 0.5 V step input.
Projection matrix optimization for block-sparse compressive sensing

Traditionally, the projection matrix in compressive sensing (CS) is chosen as a random matrix. In recent years, we have seen that the performance of CS systems can be improved by using a carefully designed projection matrix rather than a random one. In particular, we can reduce the coherence between the columns of the equivalent dictionary thanks to a well-designed projection matrix. Then, we can get a lower reconstruction error and a higher successful reconstruction rate. In some applications, the signals of interest have nonzero entries occurring in clusters - i.e., block-sparse signals. In this paper, we use the equiangular tight frame (ETF) to approach the Gram matrix of equivalent dictionary rather than the identity matrix used in [1]. Then, we minimize a weighted sum of the subblock coherence and the interblock coherence of the equivalent dictionary. The simulation results show that our novel method for projection matrix optimization significantly improves the ability of block-sparse approximation techniques to reconstruct and classify signals than the method proposed by Lihi Zelnik-Manor (LZM) [1].
Symbiotic-Autonomous Service Robots for User-Requested Tasks in a Multi-Floor Building

Although since the days of the Shakey robot, there have been a rich variety of mobile robots, we realize that there were still no general autonomous, unsupervised mobile robots servicing users in our buildings. In this paper, we contribute the algorithms and results of our successful deployment of a service mobile robot agent, CoBot, in our multi-floor office environment. CoBot accepts requests from users, autonomously navigates between floors of the building, and asks for help when needed in a symbiotic relationship with the humans in its environment. We present the details of such challenging deployment, in particular the effective real-time depth-camera based localization and navigation algorithms, the symbiotic human-robot interaction approach, and the multitask dynamic planning and scheduling algorithm. We conclude with a comprehensive analysis of the extensive results of the last two weeks of daily CoBot runs for a total of more than 8.7 km, performing a large varied set of user requests.
Influence of the Component Excipients on the Quality and Functionality of a Transdermal Film Formulation

The influence of formulation variables, i.e., a hydrophilic polymer (Methocel® E15) and a film-forming polymer (Eudragit® RL 100 and Eudragit® RS 100), on the physicochemical and functional properties of a transdermal film formulation was assessed. Several terpenes were initially evaluated for their drug permeation enhancement effects on the transdermal film formulations. d-Limonene was found to be the most efficient permeation enhancer among the tested terpenes. Transdermal film formulations containing granisetron (GRN) as a model drug, d-limonene as a permeation enhancer, and different ratios of a hydrophilic polymer (Methocel® E15) and a film-forming polymer (Eudragit® RL 100 or Eudragit® RS 100) were prepared. The prepared films were evaluated for their physicochemical properties such as weight variation, thickness, tensile strength, folding endurance, elongation (%), flatness, moisture content, moisture uptake, and the drug content uniformity. The films were also evaluated for the in vitro drug release and ex vivo drug permeation. The increasing ratios of Methocel®:Eudragit® polymers in the formulation linearly and significantly increased the moisture content, moisture uptake, water vapor transmission rate (WVTR), and the transdermal flux of GRN from the film formulations. Increasing levels of Methocel® in the formulations also increased the rate and extent of the GRN release and the GRN permeation from the prepared films.
Interframe-Space (IFS)-Based Distributed Fair Queuing for Proportional Fairness in IEEE 802.11 WLANs

In this paper, we propose an interframe-space (IFS)-based distributed-fair-queuing (IDFQ) mechanism to provide proportional fairness service for IEEE 802.11 wireless local-area networks (WLANs). IDFQ is designed to emulate self-clocked fair queuing in a distributed manner. It eliminates the backoff process as implemented in existing work and introduces a new mechanism to assign the IFS value to each station. IDFQ is immune from the implementation problem suffered by existing IFS-based mechanisms and is adaptive to the collision state in the system. Moreover, it can be used to eliminate the performance-anomaly problem of 802.11 medium-access control. The performance of IDFQ is validated by ns-2 simulations. The simulation results show that IDFQ supports fairness service for flows in proportion to their weights and outperforms existing mechanisms in terms of fairness and stability, rendering IDFQ an excellent candidate to provide weighted fairness in IEEE 802.11 WLANs
A Multi-source Message Passing Model to Improve the Parallelism Efficiency of Graph Mining on MapReduce

The MapReduce framework has been employed in many papers to process the large-scale graph. In this paper, we propose a multi-source message passing model to achieve multi-source traversal of graph in one iterative progress, which largely improve the parallelism efficiency of graph algorithm involving multi-source traversal which occurs in many complex graph algorithms. As the model can traverse the graph from different sources in one iterative progress, the multi-source traversal will finish in much less iteration than before. In this way, the total runtime of the algorithm involves multi-source traversal will be reduced in a large scale. Besides, the message passing model is flexible enough to express a broad set of algorithms. Hence, we design the interface of message passing to facilitate using our model to develop algorithms. Finally, the experiment shows the efficiency and scalability of the model.
Lipid profile frequency and the prevalence of dyslipidaemia from biochemical tests at Saint Louis University Hospital in Senegal

Introduction The aim of this study was to evaluate the frequency of lipid profile requests and the prevalence of dyslipidemia in patients at the biochemistry laboratory of St. Louis University Hospital, as well as their correlation with sex and age. Methods This was a retrospective study reviewing 14,116 laboratory results of patients of both sexes, over a period of six months (January-June 2013) regardless of the indication for the request. The lipid parameters included were: Total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides with normal values defined as follows: Total cholesterol (<2g/l), HDL- cholesterol (>0,40g/l), LDL- cholesterol (<1,30g/l) and Triglycerides (<1,50g/l). Results The average age of our study population was 55.15 years with a female predorminance (M/F = 0.60). The age group most represented was that between 55-64 years. The frequency of lipid profile request in our sample was 9.41% (or 1,329). The overall prevalence of isolated hypercholesterolemia, hyperLDLaemia, hypoHDLaemia, hypertriglyceridaemia, and mixed hyperlipidemia were respectively 60.91%, 66.27%, 26.58%, 4.57% and 2.75%. Hypercholesterolemia, hyperLDLaemia, hypertriglyceridaemia and mixed hyperlipidaemia were higher in women with respectively 66.22%, 67.98%, 4.58%, 2.89% than in men (52.01%, 62.81%, 4.44% and 2.40% respectively). On the other hand, the prevalence of hypoHDLaemia was higher in males (32.19%) compared to females (23.76%). Hypercholesterolemia correlated significantly with age and sex. Conclusion Our study showed a relatively low request rate for lipid profile and a high prevalence of dyslipidaemia hence the importance of conducting a major study on the prevalence of dyslipidaemia and associated factors in the Senegalese population.
Simple and effective image quality assessment based on edge enhanced mean square error

Simple and effective image quality assessment (IQA) method is very desirable in many image and video processing applications, such as coding, transmission, restoration and enhancement. Classic pixel absolute error based objective IQA metrics such as mean square error (MSE) and corresponding peak signal to noise ratio (PSNR) are widely used for various applications due to low computation and clear physical meanings, but have also been criticized for poorly correlated with subjective evaluation. Inspired by that human visual system (HVS) is more sensitive to image local edge distortion than flat or texture areas, in this paper, we propose a novel edge enhanced MSE (EE-MSE) to emphasize edge distortion effects on IQA. Experimental results on LIVE database release 2 show that the proposed EE-MSE IQA metric is competitive with state-of-the-art HVS-based IQA metrics, while has lower computational complexity and is more suitable for optimization task.
A contribution to modification of PART clustering algorithm for text processing

The paper presents one of the possible modifications of the Projective Adaptive Resonance Theory (PART) clustering algorithm and its application in the processing of text documents. Clustering on the basis of PART can be applied, for example, to generate a dictionary of keywords from a text. The principle of this method is based on clustering of words with the same root word. In order to demonstrate the increased clustering accuracy, the achieved clustering results with modified algorithm are compared with the results based on the standard PART algorithm.
Psychological sequelae resulting from the 2004 Florida hurricanes: implications for postdisaster intervention.

OBJECTIVES Data are limited regarding mental health effects of disasters such as hurricanes. We sought to determine the prevalence of and major risk factors associated with posttraumatic stress disorder (PTSD), generalized anxiety disorder, and major depressive episode 6 to 9 months after the 2004 Florida hurricanes. METHODS Random-digit dialing was used to recruit a representative population sample of 1452 hurricane-affected adults. RESULTS Posthurricane prevalence for PTSD was 3.6%, for generalized anxiety disorder was 5.5%, and for major depressive episode was 6.1%. Risk factors varied somewhat across disorders, with the exception of previous exposure to traumatic events, which increased risk of all negative outcomes. CONCLUSIONS Storm exposure variables and displacement were associated primarily with PTSD. Notably, high social support in the 6 months preceding the hurricanes protected against all types of disorders.
Visualization of Big High Dimensional Data in a Three Dimensional Space

This paper studies feasibility and scalable computing processes for visualizing big high dimensional data in a 3 dimensional space by using dimension reduction techniques. More specifically, we propose an unsupervised approach to compute a measure that is called visualizability in a 3 dimensional space for a high dimensional data. This measure of visualizability is computed based on the comparison of the clustering structures of the data before and after dimension reduction. The computation of visualizability requires finding an optimal clustering structure for the given data sets. Therefore, we further implement a scalable approach based on K-Means algorithm for finding an optimal clustering structure for the given big data. Then we can reduce the volume of a given big data for dimension reduction and visualization by sampling the big data based on the discovered clustering structure of the data.
Pharmacological Prevention of Peri-, and Post-Procedural Myocardial Injury in Percutaneous Coronary Intervention

In recent years, percutaneous coronary intervention (PCI) has become a well-established technique for the treatment of coronary artery disease. PCI improves symptoms in patients with coronary artery disease and it has been increasing safety of procedures. However, peri- and post-procedural myocardial injury, including angiographical slow coronary flow, microvascular embolization, and elevated levels of cardiac enzyme, such as creatine kinase and troponin-T and -I, has also been reported even in elective cases. Furthermore, myocardial reperfusion injury at the beginning of myocardial reperfusion, which causes tissue damage and cardiac dysfunction, may occur in cases of acute coronary syndrome. Because patients with myocardial injury is related to larger myocardial infarction and have a worse long-term prognosis than those without myocardial injury, it is important to prevent myocardial injury during and/or after PCI in patients with coronary artery disease. To date, many studies have demonstrated that adjunctive pharmacological treatment suppresses myocardial injury and increases coronary blood flow during PCI procedures. In this review, we highlight the usefulness of pharmacological treatment in combination with PCI in attenuating myocardial injury in patients with coronary artery disease.
Development of a camera model and calibration procedure for oblique-viewing endoscopes

Oblique-viewing endoscopes (oblique scopes) are widely used in medical practice. They are essential for certain procedures such as laparoscopy, arthroscopy and sinus endoscopy. In an oblique scope the viewing directions are changeable by rotating the scope cylinder. Although a camera calibration method is necessary to apply augmented reality technologies to oblique endoscopic procedures, no method for oblique scope calibration has yet been developed. In the present paper, we formulate a camera model and a calibration procedure for oblique scopes. In the calibration procedure, Tsai's calibration is performed at zero rotation of the scope cylinder, then the variation of the external camera parameters corresponding to the rotation of the scope cylinder is modeled and estimated as a function of the rotation angle. Accurate estimation of the rotational axis is included in the procedure. The accuracy of this estimation was demonstrated to have a significant effect on overall calibration accuracy in the experimental evaluation, especially with large rotation angles. The projection error in the image plane was approximately two pixels. The proposed method was shown to be clinically applicable.
Internationalizing a Community College: A View From the Top

ABSTRACT Using definitions of the American Council on Education (2012) and Knight (2015) as guides, this article explores the internationalization of one urban community college. Twelve interviews–the president, board, and administrators–were held. While all acknowledged that the college had made progress toward the goal of internationalization, they identified various issues that may affect all community colleges in their quest to internationalize. We discuss these issues and provide recommendation for practitioners.
Interactive Effect of the Serotonin Transporter 5-HTTLPR Genotype and Chronic Stress on Depressive Symptoms in Postmenopausal Women

ii Acknowledgments.iii Vita. iiv List of Tables . vii List of Figures . viii Background & Significance. 1 The Present Study . 29 Results. 38 Discussion. 44 Tables and Figures . 57 References. 65 Appendix A: Abbreviations . 97 Appendix B: Measures. 99
Age and Gender Differences in the Social Patterning of Cardiovascular Risk Factors in Switzerland: The CoLaus Study

Objectives We examined the social distribution of a comprehensive range of cardiovascular risk factors (CVRF) in a Swiss population and assessed whether socioeconomic differences varied by age and gender. Methods Participants were 2960 men and 3343 women aged 35–75 years from a population-based survey conducted in Lausanne, Switzerland (CoLaus study). Educational level was the indicator of socioeconomic status used in this study. Analyses were stratified by gender and age group (35–54 years; 55–75 years). Results There were large educational differences in the prevalence of CVRF such as current smoking (Δ = absolute difference in prevalence between highest and lowest educational group:15.1%/12.6% in men/women aged 35–54 years), physical inactivity (Δ = 25.3%/22.7% in men/women aged 35–54 years), overweight and obesity (Δ = 14.6%/14.8% in men/women aged 55–75 years for obesity), hypertension (Δ = 16.7%/11.4% in men/women aged 55–75 years), dyslipidemia (Δ = 2.8%/6.2% in men/women aged 35–54 years for high LDL-cholesterol) and diabetes (Δ = 6.0%/2.6% in men/women aged 55–75 years). Educational inequalities in the distribution of CVRF were larger in women than in men for alcohol consumption, obesity, hypertension and dyslipidemia (p<0.05). Relative educational inequalities in CVRF tended to be greater among the younger (35–54 years) than among the older age group (55–75 years), particularly for behavioral CVRF and abdominal obesity among men and for physiological CVRF among women (p<0.05). Conclusion Large absolute differences in the prevalence of CVRF according to education categories were observed in this Swiss population. The socioeconomic gradient in CVRF tended to be larger in women and in younger persons.