Miracle-dz/UniFAR-FTUs huggingface dataset:
Coherent Optical OFDM Transmitter Design Employing Predistortion

In this letter, we analyze the transmitter design for coherent optical orthogonal frequency-division multiplexing (CO-OFDM) employing predistortion. Digital clipping and digital predistortion processes are introduced to the radio frequency OFDM transmitter to compensate the nonlinearity effect introduced by the optical in-phase/quadrature modulator. We first provide a detailed description of signal processing involved in digital clipping and predistortion. We then carry out a numerical simulation to identify the performance dependence on clipping ratio, digital-to-analog converter (DAC) resolution, and modulation index. We find that for quadrature phase-shift keying modulation, 4-bit DAC resolution is sufficient for the CO-OFDM transmitter to incur only 0.3-dB penalty while maintaining the excess modulation insertion loss less than 6.0 dB. The performance improvement of the predistorted transmitter over nonpredistorted one is also discussed.
Multi-Perspective Study of Novice Learners Adopting the Visual Algorithm Simulation Exercise System TRAKLA2

This paper presents results from three interrelated studies focusing on introducing TRAKLA2 to students taking courses on data structures and algorithms at the University of Turku and Abo Akademi University in 2004. Using TRAKLA2 they got acquainted with a completely new system for solving exercises that provided them with automatic feedback and the possibility to resubmit their solutions. Besides comparing the students' learning results, a survey was made with 100 students on the changes in their attitudes towards web-based learning environments. In addition, a usability evaluation was conducted in a human-computer interaction laboratory. Our results show that TRAKLA2 considerably increased the positive attitudes towards web- based learning. According to students' self-evaluations, the best learning results are achieved by combining traditional exercises with web-based ones. In addition, the numerical course statistics were clearly better than in 2003 when only pen-and-paper exercises in class were used. The results from the usability test were also very positive: no severe usability problems were revealed; in fact, the results indicate that the system is very easy to learn and user-friendly as a whole.
On LP Solvable Models for Portfolio Selection

The Markowitz model for single period portfolio optimization quantifies the problem by means of only two criteria: the mean, representing the expected outcome, and the risk, a scalar measure of the variability of outcomes. The classical Markowitz model uses the variance as the risk measure, thus resulting in a quadratic optimization problem. Following Sharpe's work on linear approximation to the mean-variance model, many attempts have been made to linearize the portfolio optimization problem. There were introduced several alternative risk measures which are computationally attractive as (for discrete random variables) they result in solving Linear Programming (LP) problems. The LP solvability is very important for applications to real-life financial decisions where the constructed portfolios have to meet numerous side constraints and take into account transaction costs. This paper provides a systematic overview of the LP solvable models with a wide discussion of their properties.
Smoking and Quitting Beliefs, Attitudes, and Behaviors Among Smokers With Severe Mental Illness From Three Race/Ethnicity Groups

Objective: Most people with severe mental illness do not use evidence-based smoking cessation treatments. Ethnic and racial identification among people with severe mental illness may add complexity to their participation in smoking cessation interventions. The purpose of this qualitative study was to explore smoking and smoking cessation attitudes, beliefs, and behaviors among three race/ethnicity groups of smokers with severe mental illness. Methods: Researchers inquired into day-to-day smoking activities and quit attempts in six focus groups with 36 randomly selected African American, Latino, and White smokers with severe mental illness. Transcripts were reviewed to identify prominent themes, and first-person perspectives were selected to provide a description of smoking norms, motivation to quit, and sources of quit information. Results: Participants of all three race/ethnicity groups reported that multiple facets of their lives contributed to smoking initiation and maintenance, including the belief that smoking was a key strategy for coping with mental illness symptoms, reinforcement within institutional living situations and treatment environments, and lack of resources to obtain effective treatments. African Americans and Latinos with severe mental illnesses tended to seek advice about smoking from a broad social network of family and friends and expressed misinformation about and mistrust of medical cessation treatments. Conclusions: Smoking cessation policies and interventions for smokers with severe mental illness should be tailored to address the smoking culture in mental health settings and the variation in health-seeking attitudes and behaviors across race/ethnicity groups.
The Power of Musical Play: The Value of Play-Based, Child-Centered Curriculum in Early Childhood Music Education

Young children learn through play.This has long been acknowledged in the writings of educational theorists dating back as far as Rousseau, Pestalozzi, and Froebel and is strongly supported by current early childhood research. Play is at the heart of contemporary early childhood pedagogy, and this has led to a strong belief in the importance of an emergent, child-centered approach to curriculum. Although music educators commonly recognize the importance of making music enjoyable, music education pedagogy for young children is often teacher led and structured toward specific behavioral outcomes. Research has shown, however, that child-centered musical play can be a powerful medium for young children’s exploration of many musical elements and concepts.
Altered Network Topologies and Hub Organization in Adults with Autism: A Resting-State fMRI Study

Recent functional magnetic resonance imaging (fMRI) studies on autism spectrum condition (ASC) have identified dysfunctions in specific brain networks involved in social and non-social cognition that persist into adulthood. Although increasing numbers of fMRI studies have revealed atypical functional connectivity in the adult ASC brain, such functional alterations at the network level have not yet been fully characterized within the recently developed graph-theoretical framework. Here, we applied a graph-theoretical analysis to resting-state fMRI data acquired from 46 adults with ASC and 46 age- and gender-matched controls, to investigate the topological properties and organization of autistic brain network. Analyses of global metrics revealed that, relative to the controls, participants with ASC exhibited significant decreases in clustering coefficient and characteristic path length, indicating a shift towards randomized organization. Furthermore, analyses of local metrics revealed a significantly altered organization of the hub nodes in ASC, as shown by analyses of hub disruption indices using multiple local metrics and by a loss of “hubness” in several nodes (e.g., the bilateral superior temporal sulcus, right dorsolateral prefrontal cortex, and precuneus) that are critical for social and non-social cognitive functions. In particular, local metrics of the anterior cingulate cortex consistently showed significant negative correlations with the Autism-Spectrum Quotient score. Our results demonstrate altered patterns of global and local topological properties that may underlie impaired social and non-social cognition in ASC.
Visual Psychophysics and Physiological Optics Visual Contrast Detection Cannot Be Predicted From Surrogate Measures of Retinal Ganglion Cell Number and Sampling Density in Healthy Young Adults

Citation: Denniss J, Turpin A, McKendrick AM. Visual contrast detection cannot be predicted from surrogate measures of retinal ganglion cell number and sampling density in healthy young adults. Invest Ophthalmol Vis Sci. 2014;55:7804–7813. DOI:10.1167/iovs.14-15339 PURPOSE. To establish whether a clinically exploitable relationship exists between surrogate measures of retinal ganglion cell number and functional sampling density and visual contrast sensitivity in healthy young eyes.
Dynamically Filtering Thread-Local Variables in Lazy-Lazy Hardware Transactional Memory

Transactional Memory (TM) is an emerging technology which promises to make parallel programming easier. However, to be efficient, underlying TM system should protect only true shared data and leave thread-local data out of the transaction. This speed-up the commit phase of the transaction which is a bottleneck for a lazily versioned HTM. This paper proposes a scheme in the context of a lazy-lazy(lazy conflict detection and lazy data versioning) Hardware Transactional Memory (HTM) system to identify dynamically variables which are local to a thread and exclude them from the commitset of the transaction. Our proposal covers sharing of both stack and heap but also filters out local accesses to both of them. We also propose, in the same scheme, to identify local variables for which versioning need not be maintained.For evaluation, we have implemented a lazy-lazy model of HTM in line with the conventional and the scalable version of the TCC in a full system simulator. For operating system, we have modified the Linux kernel. We got an average speed-up of 31% for the conventional TCC, on applications from the STAMP benchmark suite. For the scalable TCC we got an average speedup of 16%. Also, we found that on average 99% of the local variables can be safely omitted when recording their old values to handle aborts.
Microwave chemistry in silicon carbide reaction vials: separating thermal from nonthermal effects.

tool for most organic chemists working in both academic and industrial laboratories. However, there is an ongoing debate in the scientific community on whether the observed dramatic accelerations of reaction rate are mainly a consequence of the high bulk temperatures attained in microwave chemistry, or whether there is a significant contribution of "nonthermal" effects (e.g. a decrease in transition state energies by direct molecule-field interactions not related to a macroscopic temperature-effect), or "specific " microwave effects (e.g. selective heating of catalyst particles).
Adaptive scan-on-receive based on spatial spectral estimation for high-resolution, wide-swath Synthetic Aperture Radar

Intensive research is currently ongoing in the field of Smart Multi-Aperture Radar Techniques (SMART) for high-resolution wide-swath Synthetic Aperture Radar (SAR) imaging. This work investigates the possibility of applying direction of arrival estimation methods to spaceborne SMART SAR systems, that employ receive beam steering. In particular, a new algorithm based on the actual spatial distribution of the received signal power is proposed. The performance of the algorithm is evaluated by Monte Carlo simulations and compared with that of the conventional scan-on-receive approach, in different operational scenarios. The Cramér Rao Lower Bound is also reported as a benchmark on the performance.
Minimising post-operative risk using a Post-Anaesthetic Care Tool (PACT): protocol for a prospective observational study and cost-effectiveness analysis

Introduction While the risk of adverse events following surgery has been identified, the impact of nursing care on early detection of these events is not well established. A systematic review of the evidence and an expert consensus study in post-anaesthetic care identified essential criteria for nursing assessment of patient readiness for discharge from the post-anaesthetic care unit (PACU). These criteria were included in a new nursing assessment tool, the Post-Anaesthetic Care Tool (PACT), and incorporated into the post-anaesthetic documentation at a large health service. The aim of this study is to test the clinical reliability of the PACT and evaluate whether the use of PACT will (1) enhance the recognition and response to patients at risk of deterioration in PACU; (2) improve documentation for handover from PACU nurse to ward nurse; (3) result in improved patient outcomes and (4) reduce healthcare costs. Methods and analysis A prospective, non-randomised, pre-implementation and post-implementation design comparing: (1) patients (n=750) who have surgery prior to the implementation of the PACT and (2) patients (n=750) who have surgery after PACT. The study will examine the use of the tool through the observation of patient care and nursing handover. Patient outcomes and cost-effectiveness will be determined from health service data and medical record audit. Descriptive statistics will be used to describe the sample and compare the two patient groups (pre-intervention and post-intervention). Differences in patient outcomes between the two groups will be compared using the Cochran-Mantel-Haenszel test and regression analyses and reported as ORs with the corresponding 95% CIs. Conclusions This study will test the clinical reliability and cost-effectiveness of the PACT. It is hypothesised that the PACT will enable nurses to recognise and respond to patients at risk of deterioration, improve handover to ward nurses, improve patient outcomes, and reduce healthcare costs.
Blast: A Tool for Error Analysis of Machine Translation Output

We present Blast, an open source tool for error analysis of machine translation (MT) output. We believe that error analysis, i.e., to identify and classify MT errors, should be an integral part of MT development, since it gives a qualitative view, which is not obtained by standard evaluation methods. Blast can aid MT researchers and users in this process, by providing an easy-to-use graphical user interface. It is designed to be flexible, and can be used with any MT system, language pair, and error typology. The annotation task can be aided by highlighting similarities with a reference translation.
Towards a parameterizable cycle-accurate ISS in ArchC

With the increase in the design complexity of MP-SoC architectures, flexible and accurate processor simulators became a necessity for exploring the vast design space solutions. In this paper, we present a flexible cycle-accurate ISS model based on ArchC 2.0 language. The model can have a variable pipeline depth and can be integrated easily in any SoC design based on SystemC. Its performance and capabilities are demonstrated by running MiBench embedded benchmark suite, while extracting pipeline statistics for each application.
The Way Forward — Positive Discrimination or Positive Action?

The focus of this article is an evaluation of the Race Relations (Amendment) Act 2000, which imposes duties on public authorities, and the Sex Discrimination (Election Candidates) Act 2002, which gives opportunities to political parties over the selection of candidates. Both of these Acts help to move anti-discrimination law in the United Kingdom away from a concentration on remedies for inconsistent treatment towards the acceptance of the need for positive measures aimed at both protecting and also advancing the position of an under-represented group. The article suggests that the positive measures these Acts exemplify may lead to conflict with the background principle that individuals should be treated with equal concern and respect. The article suggests that this principle underlies the limits to positive action in employment schemes under European Union law (the article includes a consideration of whether such limits apply to election candidacy); it goes on to consider the principle in respect of the limits to positive action authorised by these two Acts that may follow from the Human Rights Act 1998. The article concludes by considering whether the new legislation provides acceptable models for the future.
Hyperspectral Image Spectral-Spatial Feature Extraction via Tensor Principal Component Analysis

We consider the tensor-based spectral-spatial feature extraction problem for hyperspectral image classification. First, a tensor framework based on circular convolution is proposed. Based on this framework, we extend the traditional principal component analysis (PCA) to its tensorial version tensor PCA (TPCA), which is applied to the spectral-spatial features of hyperspectral image data. The experiments show that the classification accuracy obtained using TPCA features is significantly higher than the accuracies obtained by its rivals.
An Intelligent System to Avoid Collision in Vehicle based on Can Protocol

Driver and passenger safety are one of the prime concerns in a modern day vehicle. Alarming statistics of accidents and increased number of vehicles on road demands for an intelligent safety mechanism that helps the driver in handling immediate precarious situations like sudden probability of a collision. The work proposes a mechanism that not only computes the deceleration of vehicle due to braking and displays the braking intensity through an array of LED but also involves an emergency braking system and communicate it to the vehicles that are following it in lambertian [1] range of IR transmitter module to avoid any collision pre-hand, due to any situation that may arise and cause immediate deceleration of the vehicle ahead. An Arduino UNO microcontroller will be interfaced with an accelerometer and ultrasonic sensor that senses the deceleration levels, a LED array to display the braking intensity and an IR transceiver module for inter-vehicle communication that would transmit pulses whose frequency is modulated proportional to the braking intensity level. To take decision and automatically control the motion of the following vehicle, a collision avoidance system consisting of Arduino UNO microcontroller is implemented that actuates the brake control system in case of drastic
Local density based similarity criterion for clustering of remote-sensing images

Unsupervised clustering is a powerful method for land cover identification using remote-sensing images. Due to increasing spatial resolution and improved satellite capabilities, these images have had large sizes, which in turn makes pixel-based clustering often infeasible and necessitates prototype-based clustering. The use of prototypes comes with advantages such as robustness to noise and outliers, but more importantly, new types of information for similarity definition in addition to distance-based approaches. A recently proposed local density based similarity (CONN) is shown powerful for hierarchical and spectral clustering. This study shows its success in clustering of remote-sensing images for agricultural monitoring.
Aggregation Bias in Deterrence Research: an Empirical Analysis

A theoretical treatment is given of the sources of bias that might be expected in deterrence research when estimation is carried out with spatially aggregated data. In addition, aggregation is studied empirically by comparing estimates obtained from city data for the reciprocal effects of arrest clearance rates and index crime rates on one another with those obtained from state data. Some evidence for bias in the state estimates is found.
Advanced grid filters for AC-DC converters — Analysis and design methodology

The paper presents advanced grid filters used for AC-DC converters supported distributed generation systems. Analyzed filters are based on the LCL filter and extended by additional frequency traps for attenuation of the harmonics related to switching frequency. For each presented filter methodology of the parameters selection is proposed. Finally, the properties of the discussed filters are verified by simulation analysis and compared to the classical LCL filter.
Selling with Evidence

We study the informed‐principal problem in a bilateral asymmetric information trading setting with interdependent values and quasi‐linear utilities. The informed seller proposes a mechanism and voluntarily certifies information about the good's characteristics. When the set of certifiable statements is sufficiently rich, we show that there is an ex ante profit‐maximizing selling procedure that is an equilibrium of the mechanism proposal game. In contrast to posted price settings, the allocation obtained when product characteristics are commonly known (the unravelling outcome) may not be an equilibrium allocation, even when all buyer types agree on the ranking of product quality. Our analysis relies on the concept of strong Pareto optimal allocation, which was originally introduced by Maskin and Tirole (1990) in private value environments.
Entropy-based measures for clustering and SOM topology preservation applied to content-based image indexing and retrieval

Content-based image retrieval (CBIR) addresses the problem of finding images relevant to the users' information needs, based principally on low-level visual features for which automatic extraction methods are available. For the development of CBIR applications, an important issue is to have efficient and objective performance assessment methods for different features and techniques. In this paper, we study the efficiency of clustering methods for image indexing with entropy-based measures. Furthermore, the self-organizing map (SOM) as an indexing method is discussed further and an analysis method that takes into account also the spatial configuration of the data on the SOM is presented. The proposed methods enable computationally light measurement of indexing and retrieval performance for individual image features.
An Exploration of Social Circles and Prescription Drug Abuse Through Twitter

Background Prescription drug abuse has become a major public health problem. Relationships and social context are important contributing factors. Social media provides online channels for people to build relationships that may influence attitudes and behaviors. Objective To determine whether people who show signs of prescription drug abuse connect online with others who reinforce this behavior, and to observe the conversation and engagement of these networks with regard to prescription drug abuse. Methods Twitter statuses mentioning prescription drugs were collected from November 2011 to November 2012. From this set, 25 Twitter users were selected who discussed topics indicative of prescription drug abuse. Social circles of 100 people were discovered around each of these Twitter users; the tweets of the Twitter users in these networks were collected and analyzed according to prescription drug abuse discussion and interaction with other users about the topic. Results From November 2011 to November 2012, 3,389,771 mentions of prescription drug terms were observed. For the 25 social circles (n=100 for each circle), on average 53.96% (SD 24.3) of the Twitter users used prescription drug terms at least once in their posts, and 37.76% (SD 20.8) mentioned another Twitter user by name in a post with a prescription drug term. Strong correlation was found between the kinds of drugs mentioned by the index user and his or her network (mean r=0.73), and between the amount of interaction about prescription drugs and a level of abusiveness shown by the network (r=0.85, P<.001). Conclusions Twitter users who discuss prescription drug abuse online are surrounded by others who also discuss it—potentially reinforcing a negative behavior and social norm.