Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary computation: comments on the history and current state

Evolutionary computation has started to receive significant attention during the last decade, although the origins can be traced back to the late 1950's. This article surveys the history as well as the current state of this rapidly growing field. We describe the purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA) (with links to genetic programming (GP) and classifier systems (CS)), evolution strategies (ES), and evolutionary programming (EP) by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism). Finally, we give a brief overview on the manifold of application domains, although this necessarily must remain incomplete.
Which anthropometric and lower body power variables are predictive of professional and amateur playing status in male rugby union players?

The purpose of this study was to compare anthropometric and lower body power measurements between current professional and amateur male rugby union players. The present study also sought to determine which anthropometric and physical performance variables were predictive of playing standard. Thirty professional and 30 amateur RU players performed Wattbike 6 s maximal effort (WB6S) and countermovement (CMJ) and squat jump (SJ) assessments, anthropometric measures were also taken. Dependant variables recorded and analysed including: body mass, stature, Σ8 site skinfolds, WB6S absolute and relative peak power, CMJ and SJ average concentric force, jump height, peak velocity, time to peak force, rate of force development (RFD) and absolute and relative peak force and power. Professional players were heavier, taller and leaner than their amateur counterparts (p < 0.05). Professional players performed significantly better in all physical performance measures except CMJ and SJ time to peak force, CMJ RFD and SJ relative peak force. Variables which were predictive of playing standard were: Σ8 skinfolds, CMJ peak velocity and WB6S absolute and relative peak power (p < 0.05). These findings indicate that the current body of male professional RU players is anthropometrically and physically superior to their amateur counterparts, although not all variables assessed here were predictive of playing standard. Data presented here indicate that Σ8 skinfolds, WB6S absolute and relative power and CMJ peak velocity are predictive of playing standard, whereas other anthropometric and strength and power variables are not.
Statistical mechanical evaluation of spread spectrum watermarking model with image restoration

In cases in which an original image is blind, a decoding method where both the image and the messages can be estimated simultaneously is desirable. We propose a spread spectrum watermarking model with image restoration based on Bayes estimation. We therefore need to assume some prior probabilities. The probability for estimating the messages is given by the uniform distribution, and the ones for the image are given by the infinite-range model and two-dimensional (2D) Ising model. Any attacks from unauthorized users can be represented by channel models. We can obtain the estimated messages and image by maximizing the posterior probability. We analyzed the performance of the proposed method by the replica method in the case of the infinite-range model. We first calculated the theoretical values of the bit error rate from obtained saddle-point equations and then verified them by computer simulations. For this purpose, we assumed that the image is binary and is generated from a given prior probability. We also assume that attacks can be represented by the Gaussian channel. The computer simulation retults agreed with the theoretical values. In the case of prior probability given by the 2D Ising model, in which each pixel is statically connected with four-neighbors, we evaluated the decoding performance by computer simulations, since the replica theory could not be applied. Results using the 2D Ising model showed that the proposed method with image restoration is as effective as the infinite-range model for decoding messages. We compared the performances in a case in which the image was blind and one in which it was informed. The difference between these cases was small as long as the embedding and attack rates were small. This demonstrates that the proposed method with simultaneous estimation is effective as a watermarking decoder.
Extending Sliding-Window Semantics over Data Streams

Data stream processing is now commonplace in applications such as network monitoring, sensor networks, telecommunications data management, Web personalization, manufacturing and others. The continuous sliding-window query model is used widely in data stream management systems. However, the existing sliding window query models fail to answer some of the queries that qualify a certain condition. In this paper, we extended the existing sliding window to general scenarios by adding a new class of sliding window operator, termed condition-based sliding window. The condition can be defined over any attribute of data stream tuple in an out of order manner. We discuss the semantics of the operator and show that above method performs well for queries that qualify a certain condition.
Windows into Mathematics Teaching Through Data Maps

Although perceptual inference facilitates reasoning, there has been scant attention to the use of icons in visual displays of qualitative data. This paper uses an iconic data map to provide a wholistic representation of two teachers’ mathematics teaching and to establish similarities and differences in their practice. The map had five advantages for data display and analysis related to visual memory, strategic professional development support, the identification of anomalies, differences between espoused and enacted teaching beliefs, and the identification of further research questions. Thus, iconic data maps are a powerful tool in the display and analysis of qualitative data.
A Markerless Augmented Reality Environment for Medical Data Visualization

Augmented Reality (AR) techniques can be applied in medicine to help physicians in diagnosis, treatment planning, surgery simulation, among others. In craniofacial treatments, it can also be used to support prediction in patient’s own body. In this context, AR applications should fill more requirements than usual, like markerless support, tracking deformable objects and volume rendering. This paper presents a markerless AR environment, with support to deformable models, for volumetric medical data visualization based on a simple off-the-shelf hardware.
Implementing K-means Algorithm using Row store and Column store databases : A case study

K-means Clustering is an important algorithm for identifying the structure in data. K-means is the simplest clustering algorithm [8]. This algorithm uses as input a predefined number of clusters i.e., the K from its name. Mean stands for an average, an average location of all the members of a particular cluster. In this work, a novel approach to seeding the clusters with a latent data structure is proposed. This is expected to minimize the need for number of clusters apriory, Time for convergence by providing near optimal cluster centers. Also these algorithms are tested on the latest standards for data warehouse – the column store databases.
On the accuracy of passive multipath-aided underwater range estimation

We consider a range estimation algorithm based on the time-of-arrival differences between multipath replicas of a signal transmitted by an anchor node of known location to a silent node that needs to localize itself. We consider the geometry of the problem in the simplified case of a constant sound speed profile (SSP), and argue that the more realistic case of a non-constant SSP can be still tackled as if the SSP were constant, provided that an “effective” sound speed value is computed based on the geometry of the signal propagation. We finally evaluate the accuracy of the latter approach in the presence of errors affecting different quantities required for the range estimation process, including the TDoA values and the bottom depth. Our results show that our approach offers improved accuracy with respect to a baseline LSE estimator.
Provider Adherence to National Guidelines for Managing Hypertension in African Americans

Purpose. To evaluate provider adherence to national guidelines for the treatment of hypertension in African Americans. Design. A descriptive, preexperimental, quantitative method. Methods. Electronic medical records were reviewed and data were obtained from 62 charts. Clinical data collected included blood pressure readings, medications prescribed, laboratory studies, lifestyle modification, referral to hypertension specialist, and follow-up care. Findings. Overall provider adherence was 75%. Weight loss, sodium restriction, and physical activity recommendations were documented on 82.3% of patients. DASH diet and alcohol consumption were documented in 6.5% of participants. Follow-up was documented in 96.6% of the patients with controlled blood pressure and 9.1% in patients with uncontrolled blood pressure. Adherence in prescribing ACEIs in patients with a comorbidity of DM was documented in 70% of participants. Microalbumin levels were ordered in 15.2% of participants. Laboratory adherence prior to prescribing medications was documented in 0% of the patients and biannual routine labs were documented in 65% of participants. Conclusion. Provider adherence overall was moderate. Despite moderate provider adherence, BP outcomes and provider adherence were not related. Contributing factors that may explain this lack of correlation include patient barriers such as nonadherence to medication and lifestyle modification recommendations and lack of adequate follow-up. Further research is warranted.
A Proximal Approach for Sparse Multiclass SVM

Sparsity-inducing penalties are useful tools to design multiclass support vector machines (SVMs). In this paper, we propose a convex optimization approach for efficiently and exactly solving the multiclass SVM learning problem involving a sparse regularization and the multiclass hinge loss formulated by Crammer and Singer. We provide two algorithms: the first one dealing with the hinge loss as a penalty term, and the other one addressing the case when the hinge loss is enforced through a constraint. The related convex optimization problems can be efficiently solved thanks to the flexibility offered by recent primal-dual proximal algorithms and epigraphical splitting techniques. Experiments carried out on several datasets demonstrate the interest of considering the exact expression of the hinge loss rather than a smooth approximation. The efficiency of the proposed algorithms w.r. t. several state-of-the-art methods is also assessed through comparisons of execution times.
Automatic Identification of Rhetorical Roles using Conditional Random Fields for Legal Document Summarization

In this paper, we propose a machine learning approach to rhetorical role identification from legal documents. In our approach, we annotate roles in sample documents with the help of legal experts and take them as training data. Conditional random field model has been trained with the data to perform rhetorical role identification with reinforcement of rich feature sets. The understanding of structure of a legal document and the application of mathematical model can brings out an effective summary in the final stage. Other important new findings in this work include that the training of a model for one sub-domain can be extended to another sub-domains with very limited augmentation of feature sets. Moreover, we can significantly improve extraction-based summarization results by modifying the ranking of sentences with the importance of specific roles.
LineLens : Automatic Data Extraction from Line Charts

INTRODUCTION Charts and Diagrams are used extensively in newspapers, scientific publications, and visualization websites to communicate data to the audience succinctly and compactly. These charts often contain useful and valuable information and cover a wide variety of topics. It would be advantageous for users to be able to directly search for and query on these charts, instead of sifting through pages of information among websites. For example, the user can query “What is the population of United States in 1960’s”, and a line chart containing the population trend of U.S. during 1960’s can be returned to the user, as opposed to links to websites. This arguably helps the user gain an overall understanding of the subject matter much more efficiently and effectively.
PROAKTİF KİŞİLİK İLE PROAKTİF ÇALIŞMA DAVRANIŞI ARASINDAKİ İLİŞKİDE İŞE GÖNÜLDEN ADANMANIN ARACI ETKİSİ

In this study, the effects of proactive personality traits on the proactive work behavior and work engagement are examined. The study aims to examine whether proactive personality structure of employees working for Development Agencies in Turkey has any effect on proactive work behavior, work engagement of people. In line with this aim, data from 151 people working in Development Agencies were collected by the questionnaire method and these data were analyzed by hierarchical regression method in order to determine the direct and regulatory effects of the variables included in the model. As result, it is reviled that proactive personality and proactive work behavior has a positive relationship, moreover, work engagement has a mediating effect on this relationship.
Another Look at Sex Offender Treatment Efficacy : A Within-Treatment Design

The purpose of this study was to fill an existing hole in the literature on sex offender treatment efficacy by measuring within-treatment changes in psychological and interpersonal adjustment in a sample of convicted sexual offenders. The sample consisted of 30 adult males convicted of sexual offences who were in group treatment for approximately 2 years. Results revealed statistically significant improvement in the offenders’ emotional and cognitive maturity, ability to identify and process personal thoughts and emotions, and improved self-esteem and interpersonal interactions. Significant decreases were also observed in the offender’s tendencies to distort reality in order to fit their wants and needs. Results also reveal a considerable reduction in the number of elevated personality scales from pre-test to follow-up. Implications of these findings and recommendations for treatment and further research are provided.
A Low-Power CMOS Antenna-Switch Driver Using Shared-Charge Recycling Charge Pump

A technique to reduce power consumption of charge-pump-based antenna-switch drivers by recycling wasted charges in clock buffers of charge pumps is presented. The proposed shared-charge recycling technique allows discharging current of capacitors in the clock buffers to be shared and recycled to charge other capacitors. The clock buffers only need to charge the capacitors half way, and the current consumption can be cut in half. Furthermore, because the burden of the clock buffers is lessened, the driving capability of the clock buffers can be reduced. This advantage can result in the benefits of a reduced size of a chip area and lowered manufacturing cost. Furthermore, the relationship between the charge-recycling time and the current saving by the charge recycling is analyzed and incorporated in the driver design. The proposed antenna-switch driver using the shared-charge recycling technique has been fabricated using a standard 0.35-μ m CMOS technology. The fabricated chip saves over 30% of current over conventional drivers. The details on measurement results and comparisons with conventional charge pumps are also presented.
Physical and chemical properties of pollution aerosol particles transported from North America to Greenland as measured during the POLARCAT summer campaign

Abstract. Within the framework of the POLARCAT-France campaign, aerosol physical, chemical and optical properties over Greenland were measured onboard the French ATR-42 research aircraft. The origins of CO excess peaks detected in the aircraft measurements then have been identified through FLEXPART simulations. The study presented here focuses particularly on the characterization of air masses transported from the North American continent to Greenland. Air masses that picked up emissions from Canadian boreal forest fires as well as from the cities on the American east coast were identified and selected for a detailed study. Measurements of CO concentrations, aerosol chemical composition, aerosol number size distributions, aerosol volume volatile fractions and aerosol light absorption (mainly from black carbon) are used in order to study the relationship between CO enhancement (ΔCO), aerosol particle concentrations and number size distributions. Aerosol number size distributions (normalised with their respective ΔCO) are in good agreement with previous studies. Nonetheless, wet scavenging may have occurred along the pathway between the emission sources and Greenland leading to a less pronounced accumulation mode in the POLARCAT data. Chemical analyses from mass spectrometry show that submicrometer aerosol particles are mainly composed of sulphate and organics. The observed bimodal (Aitken and accumulation) aerosol number size distributions show a significant enhancement in Aitken mode particles. Furthermore, results from the thermodenuder analysis demonstrate the external mixture of boreal fire (BF) air masses from North America (NA). This is particularly observed in the accumulation mode, containing a volume fraction of up to 25–30% of refractory material at the applied temperature of 280 °C. NA anthropogenic air masses with only 6% refractory material in the accumulation mode can be clearly distinguished from BF air masses. Overall, during the campaign rather small amounts of black carbon from the North American continent were transported towards Greenland during the summer POLARCAT observation period, which also is a valuable finding with respect to potential climate impacts of black carbon in the Arctic.
The Anatomy-An Instrument for Managing Software Evolution and Evolvability

This paper describes ongoing research concerning support for evolution and evolvability of software systems at a development unit of Ericsson AB, Sweden. At Ericsson, there is currently a shift towards shorter and swifter development projects, which requires greater attention to evolution aspects. The paper presents the concept of anatomy, which is a view of the functional evolution of a software system, and how it acts as an instrument for dealing with software evolution and evolvability. The anatomy concept brings together release planning, scoping and incremental development to form a holistic evolution view. Both a multi-release evolution and a within-release evolution are addressed. The former is shown in a product anatomy driven by strategic and business goals, whereas the latter is shown in a project anatomy which adds time and resource constraints to a subset of the product anatomy. The anatomy is argued to lead to a greater organisational focus on both evolution and evolvability, in part due to being a tool for spreading knowledge about the evolution of the system it depicts. The paper presents the so far defined anatomy infrastructure, and a desired way of working. It also points to open research issues for the continuation of the research at hand
Kinematical structure of the circumstellar environments of galactic B[e]-type stars

High resolution line profiles are presented for selected forbidden and permitted emission lines of a sample of galactic B(e)-type stars. The spectral resolution corresponds to 5− 7k m s −1 with the exception of some line profiles which were observed with a resolution of 9−13 km s −1 . All Hα profiles are characterized by a narrow split or single emission component with a width of ∼150−250 km s −1 (FWHM) and broad wings with a full width of ∼1000−2000 km s −1 . The Hα profiles can be classified into three groups: double-peaked profiles representing the majority, single-peaked emission-line profiles, and normal P Cygni-type profiles. Likewise, the forbidden lines exhibit in most cases double-peaked profiles. In particular, the majority of stars shows split (O )λ6300 A. Double-peaked profiles are also found in several stars for (N )λ6583 A and (Fe )λ7155 A although these lines in many stars exhibit single-peaked emission profiles. The split forbidden line profiles have peak separations of as little as ∼10 km s −1 , and were therefore only discernible for the first time in the high-resolution spectra. The ratio of violet to red emission peak intensities, V/R, is predominantly smaller or equal to 1. Theoretical profiles were calculated for the optically thin case. A latitude-dependent stellar wind with a radial expansion and a velocity decreasing from the pole to the equator was adopted. This configuration can produce split line profiles if viewed under some angle with respect to the line of sight. In addition an equatorial dust ring with various optical depths was assumed. It can explain line asymmetries observed in some stars. Moreover, the V/R ratios can be understood in terms of this model. The comparison of the observed line profiles with the models thus confirms the assumption of disk-like line-formation regions as commonly adopted for B(e)-type stars.
Identification and Comparative Analysis of MicroRNAs Associated with Low-N Tolerance in Rice Genotypes

Background Nitrogen [N] is a critical limiting nutrient for plants and has to be exogenously supplied to many crops, to achieve high yield with significant economic and environmental costs, specifically for rice. Development of low-input nitrogen sustainable crop is necessary for sustainable agriculture. Identification of regulatory elements associated with low-N tolerance is imperative for formulating innovative approaches for developing low-N tolerant crop plants, using gene manipulation. MicroRNAs (miRNAs) are known to play crucial roles in the modulation of gene expression in plants under various environmental conditions. Methodology/Principal Findings MiRNAs associated with low-N tolerance have not been identified so far. In this study, we investigated microarray-based miRNA expression in low-N tolerant and low-N sensitive rice genotypes under low N condition. Expressions of 32 miRNAs differed significantly in the two genotypes. Of these 32 miRNAs, expressions of nine miRNAs were further validated experimentally in leaves as well as in roots. Of these differentially expressed miRNAs, six miRNAs (miR156, miR164, miR528, miR820, miR821 and miR1318) were reported in leaves and four (miR164, miR167, miR168 and miR528) in roots. Target genes of all the 32 miRNAs were predicted, which encode transcription factors, and proteins associated with metabolic processes or stress responses. Expression levels of some of the corresponding miRNA targets were analysed and found to be significantly higher in low N-tolerant genotype than low-N sensitive genotype. These findings suggested that miRNAs played an important role in low-N tolerance in rice. Conclusions/Significance Genome-wide differences in expression of miRNA in low N-tolerant and low N-sensitive rice genotypes were reported. This provides a platform for selection as well as manipulation of genotypes for better N utilization efficiency.
Diabetic mice exhibited a peculiar alteration in body composition with exaggerated ectopic fat deposition after muscle injury due to anomalous cell differentiation

Sarcopenic obesity, age‐related muscle loss, which is compensated by an increase in fat mass, impairs quality of life in elderly people. Although the increase in intramuscular fat is associated with decreased insulin sensitivity and increased metabolic risk factors, the origin of diabetes‐associated intramuscular fat has not been elucidated. Here, we investigated intramuscular fat deposition using a muscle injury model in type 2 diabetic mice.