Miracle-dz/UniFAR-FTUs huggingface dataset:
Microwave filter and antenna for wireless communication systems

This paper presents the investigation and characterization of integrated microwave filter and antenna to reduce the overall physical volume for RF/ microwave front-end subsystems. This study focuses on the integrating of rectangular Substrate Integrated Waveguide (SIW) filter with rectangular microstrip patch antenna to produce filtering and radiating element in a single device. To proof the concept, the integrated microwave filter and antenna at center frequency of 2 GHz is demonstrated and validated through simulation and analysis. This class of microwave filters and antenna integration would be useful in microwave systems where the reduction of size and weight as well as cost is very important such as in base stations and multiplexer in any communication systems.
Opposing Effects of Acute Stress in a Rodent Model of Gambling Behaviour

Impulsive decision-making is characteristic of both pathological gambling and depression. It remains unclear why some individuals are prone to make risky decisions and develop gambling behaviours. Stress is known to increase the risk for addiction, depression, and disrupt optimal decision-making. The goal of this study is to explore the effects of stress-induced depressive behaviours on gambling-like decision-making in rodents. We hypothesized that stress will increase impulsive decision-making in rats. Rodents were exposed to acute stress using a stress paradigm known to induce depressive-like behaviours and the animal’s decision-making was assessed using a rodent model of gambling-like behaviour. As expected, we found that inescapable footshocks increased impulsive decision-making. Surprisingly, we found that escapable footshocks improved decision-making. Furthermore, high levels of baseline impulsivity in addition to inescapable footshocks increased impulsive decision-making. Our findings suggest that the observed effects of both types of shocks on decision-making could be modulated by baseline levels of impulsivity.
Coupon Incentive-Based Demand Response: Theory and Case Study

This paper presents the formulation and critical assessment of a novel type of demand response (DR) program targeting retail customers (such as small/medium size commercial, industrial, and residential customers) who are equipped with smart meters yet still face a flat rate. Enabled by pervasive mobile communication capabilities and smart grid technologies, load serving entities (LSEs) could offer retail customers coupon incentives via near-real-time information networks to induce demand response for a future period of time in anticipation of intermittent generation ramping and/or price spikes. This scheme is referred to as coupon incentive-based demand response (CIDR). In contrast to the real-time pricing or peak load pricing DR programs, CIDR continues to offer a flat rate to retail customers and also provides them with voluntary incentives to induce demand response. Theoretical analysis shows the benefits of the proposed scheme in terms of social welfare, consumer surplus, LSE profit, the robustness of the retail electricity rate, and readiness for implementation. The pros and cons are discussed in comparison with existing DR programs. Numerical illustration is performed based on realistic supply and demand data obtained from the Electric Reliability Council of Texas (ERCOT).
Learning in the presence of noise

We investigate the emergence of rationality in repeated games where, at each iteration, the players' payoffs are randombly perturbed (to account e.g. for the effects of fading or errors in the reading of one's throughput). We see that even if players start out completely uneducated about the game, there is a simple learning scheme that enables them to eventually weed out the noise and identify suboptimal choices, regardless of the noise level. More precisely, we show that strategies that are strictly dominated (even iteratively) become extinct in the long run, i.e. players exhibit rational behavior. As an application, we model a number of users that are able to switch dynamically between multiple wireless nodes and see that they are able to pick up which node works best for them, even in the presence of high performance fluctuations.
Mortality and Incidence of Hospital Admissions for Stroke among Brazilians Aged 15 to 49 Years between 2008 and 2012

Introduction The objective was to analyze rates of stroke-related mortality and incidence of hospital admissions in Brazilians aged 15 to 49 years according to region and age group between 2008 and 2012. Methods Secondary analysis was performed in 2014 using data from the Hospital and Mortality Information Systems and the Brazilian Institute of Geography and Statistics. Stroke was defined by ICD, 10th revision (I60–I64). Crude and standardized mortality (WHO reference) and incidence of hospital admissions per 100,000 inhabitants, stratified by region and age group, were estimated. Absolute and relative frequencies; and linear regression were also used. The software used was Stata 11.0. Results There were 35,005 deaths and 131,344 hospital admissions for stroke in Brazilians aged 15–49 years old between 2008 and 2012. Mortality decreased from 7.54 (95% CI 7.53; 7.54) in 2008 to 6.32 (95% CI 6.31; 6.32) in 2012 (β = -0.27, p = 0.013, r2 = 0.90). During the same time, incidence of hospital admissions stabilized: 24.67 (95% CI 24.66; 24.67) in 2008 and 25.11 (95% CI 25.10; 25.11) in 2012 (β = 0.09, p = 0.692, r2 = 0.05). There was a reduction in mortality in all Brazilian regions and in the age group between 30 and 49 years. Incidence of hospitalizations decreased in the South, but no significant decrease was observed in any age group. Conclusion We observed a decrease in stroke-related mortality, particularly in individuals over 30 years old, and stability of the incidence of hospitalizations; and also regional variation in stroke-related hospital admission incidence and mortality among Brazilian young adults.
Using TS fuzzy models in anytime control systems

Nowadays practical solutions of engineering problems involve model-integrated computing. Model based approaches offer a very challenging way to integrate a priori knowledge into the procedure. Due to their flexibility, robustness, and easy interpretability, the application of soft computing based models, may have an exceptional role. Nevertheless, ever so advantageous their usage can be, it can still be limited by their high computational complexity. Although, a possible solution can be, if we combine soft computing and anytime techniques, because the anytime mode of operation is able to adaptively cope with the available, usually imperfect or even missing information, the dynamically changing, possibly insufficient amount of resources and reaction time. In this paper, possibilities offered by the combination of TS fuzzy models and anytime techniques are presented.
Cooperative coding scheme using polar codes

Cooperative coding technique combines the channel coding technique to cooperative communications, and guarantees the high performance. Polar codes, proposed by Arikan in 2007, have been proven to be capacity-achieving codes with low encoding and decoding complexity. In the paper, we propose a cooperative coding scheme using polar codes. We present the cooperative coding schemes with amplify-forward (AF) mode and decode-forward (DF) mode, respectively. By numerical simulations, we compare the performance of the proposed schemes using polar codes with those schemes using low density parity check (LDPC) codes under the same conditions. The simulation results show that the performance of the proposed schemes with AF and DF modes has been improved significantly compared with those using LDPC codes. We also study the distance factor on the performance of the cooperative communication system. The results show the smaller the distance between R and S, the better the performance of the system is.
e-Publications@Marquette e-Publications@Marquette

: It is, by now, well known that McIntyre's localized carrier-multiplication theory cannot explain the suppression of excess noise factor observed in avalanche photodiodes (APDs) that make use of thin multiplication regions. We demonstrate that a carrier multiplication model that incorporates the effects of dead space, as developed earlier by Hayat et al. provides excellent agreement with the impact-ionization and noise characteristics of thin InP, In/sub 0.52/Al/sub 0.48/As, GaAs, and Al/sub 0.2/Ga/sub 0.8/As APDs, with multiplication regions of different widths. We outline a general technique that facilitates the calculation of ionization coefficients for carriers that have traveled a distance exceeding the dead space (enabled carriers), directly from experimental excess-noise-factor data. These coefficients depend on the electric field in exponential fashion and are independent of multiplication width, as expected on physical grounds. The procedure for obtaining the ionization coefficients is used in conjunction with the dead-space-multiplication theory (DSMT) to predict excess noise factor versus mean-gain curves that are in excellent accord with experimental data for thin III-V APDs, for all multiplication-region widths.
A Survey on Product Operators in Abstract Interpretation

interpretation (6) has been widely applied as a general technique for the sound approximation of the semantics of computer programs. In particular, abstract domains (to represent data) and semantics (to represent data operations) approximate the concrete computation. When analyzing a program and trying to prove some property on it, the quality of the result is determined by the abstract domain choice. There is always a trade-off between accuracy and efficiency of the analysis. During the years, various abstract domains have been developed. An interesting feature of the abstract interpretation theory is the possibility to combine different domains in the same analysis. In fact, the abstract interpretation framework offers some standard ways to compose abstract domains, ensuring the preservation of the theoretical properties needed to guarantee the soundness of the analysis. These compositional methods are called domain refinements. A systematic treatment of abstract domain refinements has been given in (12, 14), where a generic refinement is defined to be a lower closure operator on the lattice of abstract interpretations of a given concrete domain. These kinds of operators on abstract domains provide high- level facilities to tune a program analysis in terms of accuracy and cost. Two of the most well-known domain refinements are the disjunctive completion (6, 9, 13, 15, 18) and the reduced product (6), but they are not the only ones. The reduced product can be seen as the most precise refinement of the simple Cartesian product. Moreover, the reduced cardinal power is introduced by (6). While the other domain refinements have been, since their introduction, widely used and explored, the reduced cardinal power has seen definitely less further developments since 1979, with the exception of (16). To verify our assertion, we looked for the number of scientific citations (in the abstract interpretation context) to some domain refinements in Google Scholar. We depicted the results of this search in Figure 1. In particular, we focused on the Cartesian product, the reduced product and the reduced cardinal power. Throughout the years, the number of citations increases in all three cases, but the absolute numbers are very different: just consider that the total citations of "Cartesian product" are 964, while the ones to "reduced cardinal power" are only 38.
A Computational Model of Craving and Obsession

Abstract: If addictions and problematic behaviors arise from interactions between drugs, reward sequences, and natural learning sytems, then an explanation of clinically problematic conditions (such as the self‐administration of drugs or problem gambling) requires an understanding of the neural systems that have evolved to allow an agent to make decisions. We hypothesize a unified decision‐making system consisting of three components—a situation recognition system, a flexible, planning‐capable system, and an inflexible, habit‐like system. In this article, we present a model of the planning‐capable system based on a planning process arising from experimentally observed look‐ahead dynamics in the hippocampus enabling a forward search of possibilities and an evaluation process in the nucleus accumbens. Based on evidence that opioid signaling can provide hedonic evalutation of an achieved outcome, we hypothesize that similar opioid‐signaling processes evaluate the value of expected outcomes. This leads to a model of craving, based on the recognition of a path to a high‐value outcome, and obsession, based on a value‐induced limitation of the search process. This theory can explain why opioid antagonists reduce both hedonic responses and craving.
Does Hospital Competition Save Lives? Evidence from the English NHS Patient Choice Reforms

Recent substantive reforms to the English National Health Service expanded patient choice and encouraged hospitals to compete within a market with fixed prices. This study investigates whether these reforms led to improvements in hospital quality. We use a difference-in-difference-style estimator to test whether hospital quality (measured using mortality from acute myocardial infarction) improved more quickly in more competitive markets after these reforms came into force in 2006. We find that after the reforms were implemented, mortality fell (i.e. quality improved) for patients living in more competitive markets. Our results suggest that hospital competition can lead to improvements in hospital quality.
Pose and motion estimation of a moving rigid body with few features

This paper proposes a reliable solution to the problem of estimating the motion of a rigid object moving freely in 3D space, through the use of a passive vision system. The feature-based tracking technique builds upon the selection of a consistent set of features and their tracking on a frame-by-frame basis. A thorough investigation is conducted to determine a proper vision system setup, which results in a configuration that ensures the coverage of the complete patterns of motion that the object may exhibit. While the system relies on low resolution cameras, the proposed algorithm provides subpixel accuracy on the pose estimation of the rigid body and its associated motion. The algorithm is experimentally validated and operates within an execution timeframe that makes it suitable for real-time processing applications.
Restricted-Verifier Precise Bounded-Concurrent Zero-Knowledge

We present a stronger notion of precise bounded-concurrent zero-knowledge. Our notion captures the idea that view of any verifier in a bounded-concurrent interaction can be reconstructed in the almost same time. Precise zero-knowledge in stand-alone setting was introduced by Micali and Pass in STOC'06 and they constructed some precise stand-alone zero-knowledge protocols for NP using at least omega(1) rounds. Via providing a precise simulator for the known O(1)-round bounded-concurrent non-black-box zero-knowledge argument, we show the existence of O(1)- round bounded-concurrent zero-knowledge arguments with polynomial precision for NP. Our result assumes that the ratio of running-time of any adversarial verifier on any two different views in bounded-concurrent execution of the protocol is bounded by na, where a is any predeterminate constant. Such verifiers are called restricted verifiers.
OF K OWLEDGE-BASED SYSTEMS THROUGH COMMO KADS

This paper defines a method that can be used for validating knowledge-based systems (KBS) throughout their entire lifecycle. Method’s name is MAVERICK. It stands for Method for Automated Validation Embedded into the Reusable and Incremental CommonKADS. The lack of suitable, rigorous and general validation methods has become a serious obstacle to user acceptance of KBS for critical applications. In spite of recent significant advances in validation of KBS, it still remains an open problem. The ideas presented in this paper are based on the concept that validation should be performed in a structured and guided manner, integrated within a knowledge-based systems’ lifecycle development method. We define an incremental validation method for KBS based on extracting test cases from CommonKADS. Furthermore, we introduce our method for reducing the number of test cases and thus reducing validation’s effort and cost. Index Terms Validation, CommonKADS, Knowledge-based systems, Test case.
Improving functional verification of embedded systems using hierarchical composition and set theory

During functional verification, complex interactions between multiple modules that compose a digital circuit design can reveal hard-to-find bugs. Functional coverage specifications must be precise to assure these interactions occur during the simulation. We are proposing a technique for improving the functional verification specification of individual modules, preserving the occurrence of these interactions scenarios in the composition phase. We obtain these new specifications in a deductive way, by means of set theory. Using experimental results, we show how our work can contribute to error detection and save functional verification time.
Combined Sum of Squares Penalties for Molecular Divergence Time Estimation

Estimates of molecular divergence times when rates of evolution vary require the assumption of a model of rate change. Brownian motion is one such model, and since rates cannot become negative, a log Brownian model seems appropriate. Divergence time estimates can then be made using weighted least squares penalties. As sequences become long, this approach effectively becomes equivalent to penalized likelihood or Bayesian approaches. Different forms of the least squares penalty are considered to take into account correlation due to shared ancestors. It is shown that a scale parameter is also needed since the sum of squares changes with the scale of time. Errors or uncertainty on fossil calibrations, may be folded in with errors due to the stochastic nature of Brownian motion and ancestral polymorphism, giving a total sum of squares to be minimized. Applying these methods to placental mammal data the estimated age of the root decreases from 125 to about 94 mybp. However, multiple fossil calibration points and relative molecular divergence times inflate the sum of squares more than expected. If fossil data are also bootstrapped, then the confidence interval for the root of placental mammals varies widely from ~70 to 130 mybp. Such a wide interval suggests that more and better fossil calibration data is needed and/or better models of rate evolution are needed and/or better molecular data are needed. Until these issues are thoroughly investigated, it is premature to declare either the old molecular dates frequently obtained (e.g. > 110 mybp) or the lack of identified placental fossils in the Cretaceous, more indicative of when crown-group placental mammals evolved.
Book review: Aditi Bathia, Discursive Illusions in Public Discourse: Theory and Practice

The study also contains interdisciplinary reflections on the close relation between Lakoff’s ideas and Hunter’s (1991) well-known and extremely influential theory of ‘culture war’, pointing to the interconnections between them. Hunter postulates a values divide among American citizens and describes the repercussions of cultural oppositions on political behaviour. Degani suggests that Lakoff appears to adapt and translate Hunter’s theory into his own linguistic framework, thus emphasising the connection between Hunter’s culturally relevant theory and the linguistic analysis presented in the book. Necessarily complex, Framing the Rhetoric of a Leader skilfully melds together perspectives from the areas of political discourse, rhetoric, public speaking and public address. Written by a passionate scholar in the field of political discourse, this work should rightly be seen as a significant contribution to a growing literature in the publicspeaking domain both in Europe and in the United States.
Low visual difference virtual high dynamic range image synthesizer from a single legacy image

New generations of display technologies provide signicantly improved dynamic range over conventional display devices. Current inverse tone mapping schemes require multiple exposure low dynamic range (LDR) images to generate high dynamic range (HDR) images. In this work, we propose an exposure dependent S curve to convert one optimized LDR image to multiple images with different brightness, which are then fused into a virtual real scene HDR image with wide dynamic range. According to our implementation results, the dynamic range can reach about 105. The synthesizer is robust and temporally coherent, and does not require image specific parameter adjustment. This paper also presents the image quality assessment with HDR visual difference predictor (HDR-VDP) and relative entropy contrast, and our work has better performance than other inverse tone mapping operators (iTMOs) for the both image quality assessments.
About Noneigenvector Source LocalizationMethods

Previous studies dedicated to source localization are based on the spectral matrix algebraic properties. In particular, two noneigenvector methods, namely, propagator and Ermolaev and Gershman (EG) algorithms, exhibit a low computational load. Both methods are based on spectral matrix structure. The first method is based on the spectral matrix partitioning. The second one obtains directly an approximation of noise subspace using an adjustable power parameter of the spectral matrix and choosing a threshold value. It has been shown that these algorithms are efficient in nonnoisy or high signal to noise ratio (SNR) environments. However, both algorithms will be improved. Firstly, propagator is not robust to noise. Secondly, EG algorithm that requires the knowledge of a threshold value between largest and smallest eigenvalues, which are not available as eigendecomposition, is not performed. In this paper, we aim firstly at demonstrating the usefulness of QR and LU factorizations of the spectral matrix for these methods and secondly we propose a new way to reduce the computational load of a high resolution algorithm by estimating only the needed eigenvectors. For this, we adapt fixed-point algorithm to compute only the leading eigenvectors. We evaluate the performance of the proposed methods by a comparative study.
The fake news game: actively inoculating against the risk of misinformation

Abstract The rapid spread of online misinformation poses an increasing risk to societies worldwide. To help counter this, we developed a ‘fake news game’ in which participants are actively tasked with creating a news article about a strongly politicized issue (the European refugee crisis) using misleading tactics, from the perspective of different types of fake news producers. To pilot test the efficacy of the game, we conducted a randomized field study (N = 95) in a public high school setting. Results provide some preliminary evidence that playing the fake news game reduced the perceived reliability and persuasiveness of fake news articles. Overall, these findings suggest that educational games may be a promising vehicle to inoculate the public against fake news.