Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Evolutionary Computation Approaches to Feature Selection

Feature selection is an important task in data mining and machine learning to reduce the dimensionality of the data and increase the performance of an algorithm, such as a classification algorithm. However, feature selection is a challenging task due mainly to the large search space. A variety of methods have been applied to solve feature selection problems, where evolutionary computation (EC) techniques have recently gained much attention and shown some success. However, there are no comprehensive guidelines on the strengths and weaknesses of alternative approaches. This leads to a disjointed and fragmented field with ultimately lost opportunities for improving performance and successful applications. This paper presents a comprehensive survey of the state-of-the-art work on EC for feature selection, which identifies the contributions of these different algorithms. In addition, current issues and challenges are also discussed to identify promising areas for future research.
The Impact of Computer Self-Efficacy and Technology Dependence on Computer-Related Technostress: A Social Cognitive Theory Perspective

Professionals and end users of computers often experience being constantly surrounded by modern technology. One side effect of modern technology is termed technostress, which refers to the “negative impact on attitudes, thoughts, behaviors, or body physiology that is caused either directly or indirectly by technology” (Well and Rosen, 1997). Based on social cognitive theory, this study developed a conceptual model in which computer-related technostress was studied as consequences of computer self-efficacy and technology dependence. Results show that (a) employees with higher level of computer self-efficacy have lower level of computer-related technostress, (b) employees with higher level of technology dependence have higher level of computer-related technostress, and (c) employees under different individual situations may perceive different levels of technostress. Contributions of this research and implications for theory and managerial practice are also discussed.
Effect of Carrier Frequency Offset on Offset QAM Multicarrier Filter Bank Systems over Frequency-Selective Channels

This paper presents an analysis of the effect of carrier frequency offset (CFO) on offset QAM (OQAM) multicarrier filter bank (MCFB) systems, also known as staggered modulated multitone (SMT), over frequency-selective channels. This effect may be quantified by signal-to-interference ratio (SIR). We drive an accurate expression for the interference power and the desired signal power. Then SIR of SMT systems is calculated. Next, we drive an approximated SIR when the maximum delay of the channel is small in comparison with symbol spacing. The approximated SIR show that the SIR over frequency-selective channels converges to that over additive white Gaussian noise (AWGN) channels. Numerical results show that with increasing number of subcarriers, both of accurate and approximated forms of SIR as a function of CFO over frequency-selective channels converge to that over AWGN channels. Also, we compare SMT and orthogonal frequency division multiplexing (OFDM). It is shown that OFDM has better SIR in small CFO over frequency-selective channels. But with large number of subcarriers or high CFO, SMT outperforms OFDM.
From plant surface to plant metabolism: the uncertain fate of foliar-applied nutrients

The application of agrochemical sprays to the aerial parts of crop plants is an important agricultural practice world-wide. While variable effectiveness is often seen in response to foliar treatments, there is abundant evidence showing the beneficial effect of foliar fertilizers in terms of improving the metabolism, quality, and yields of crops. This mini-review is focused on the major bottlenecks associated with the uptake and translocation of foliar-applied nutrient solutions. A better understanding of the complex scenario surrounding the ultimate delivery of foliar-applied nutrients to sink cells and organs is essential for improving the effectiveness and performance of foliar fertilizers.
Muscle Mass Scaling in Primates: An Energetic and Ecological Perspective

Body composition is known to vary dramatically among mammals, even in closely related species, yet this issue has never been systematically investigated. Here, we examine differences in muscle mass scaling among mammals, and explore how primate body composition compares to that of nonprimate mammals. We use a literature‐based sample of eutherian and metatherian mammals, and combine this with new dissection‐based data on muscularity in a variety of strepsirrhine primates and the haplorhine, Tarsius syrichta. Our results indicate an isometric scaling relationship between total muscle mass and total body mass across mammals. However, we documented substantial variation in muscularity in mammals (21–61% of total body mass), which can be seen both within and between taxonomic groups. We also found that primates are under‐muscled when compared to other mammals. This difference in body composition may in part reflect the functional consequences of arboreality, as arboreal species have significantly lower levels of muscularity than terrestrial species. Am. J. Primatol. 74:395‐407, 2012. © 2012 Wiley Periodicals, Inc.
Potential drivers of microbial community structure and function in Arctic spring snow

The Arctic seasonal snowpack can extend at times over a third of the Earth’s land surface. This chemically dynamic environment interacts constantly with different environmental compartments such as atmosphere, soil and meltwater, and thus, strongly influences the entire biosphere. However, the microbial community associated with this habitat remains poorly understood. Our objective was to investigate the functional capacities, diversity and dynamics of the microorganisms in snow and to test the hypothesis that their functional signature reflects the snow environment. We applied a metagenomic approach to nine snow samples taken over 2 months during the spring season. Fungi, Bacteroidetes, and Proteobacteria were predominant in metagenomic datasets and changes in community structure were apparent throughout the field season. Functional data that strongly correlated with chemical parameters like mercury or nitrogen species supported that this variation could be explained by fluctuations in environmental conditions. Through inter-environmental comparisons we examined potential drivers of snowpack microbial community functioning. Known cold adaptations were detected in all compared environments without any apparent differences in their relative abundance, implying that adaptive mechanisms related to environmental factors other than temperature may play a role in defining the snow microbial community. Photochemical reactions and oxidative stress seem to be decisive parameters in structuring microbial communities inside Arctic snowpacks.
Inter Causal Biasing Characteristics—Defining Confounding

In the October issue editorial readers were provided with a series of factors that are important to consider when embarking on or interpreting results from an observational study. For example, outpatient cardiac or pulmonary rehabilitation participants are ambulatory enough to leave the house and get to the facility, they are willing to participate, they have a physician provider that referred them to rehabilitation, or they somehow knew to request that their physician provider refer them to rehabilitation. All of these characteristics can confound and influence our ability to make inferences to a larger population from a sample. Confounding is not necessarily something that statistical inference (confidence intervals or P-values) helps us address. The easiest approach to consider whether a confounder is present is to consider a graph of the proposed cause and effect claim. For example, if “participate in rehabilitation” then “improved outcome” is the underlying causal claim; we must consider whether anything is a potential cause of both participation in rehabilitation and an improved outcome. For example, being ambulatory is necessary to participate and it is also possibly a cause of an improved outcome. Having health insurance, a physician provider that refers or knowing to ask your physician provider to refer are all causes of participation in rehabilitation and all are also possibly a cause for an improved outcome. In a directed acyclic graph this is referred to as a biasing path: X causes Y, but Z causes both X and Y. Therefore, Z is a confounder. There is a great free tool online that can be used to help draw and alert observational researchers, observational research consumers or observational research reviewers to the presence of confounding (http://www.dagitty.net/). Once it is determined that there are confounders, the question is what can we do about it? In observational designs there are less options which is why researcher, reviewer and reader vigilance is critical. In an upcoming editorial we will discuss possible approaches for researchers to address confounding. At the very least, researcher, reviewer and reader should all keep the STROBE checklist in mind (www.strobestatement.org), which is a requirement when submitting an observational study to CPTJ, and in which “Not Applicable” is not an acceptable answer to questions about addressing bias and confounding. IN THIS ISSUE
Rankings and Social Tournaments: Evidence from a Crowd-Sourcing Experiment

There is a growing interest in behavioral incentive schemes exploiting people preference about how they rank compared to others as a non-monetary mechanism to shape effort. In this paper we present evidence from a crowd-sourcing experiment where employees were given feedback about how they rank in terms of performance compared to others doing the same task. The context is such that rank had no implication for current or future compensation. Compared to a control group with no rank feedback, employees who received feedback about their rank were less likely to return to work and also less productive on the job.
The Supportive School: Wellbeing and the Young Adolescent

The Supportive School tackles some important contemporary issues of interest to teachers, parents and policy-makers alike. There is a widespread perception across the developed world that the social and emotional wellbeing of young people has been in decline in recent years and that various problem behaviours are on the rise. Because children spend so much of their time in educational institutions, schools are assumed to be part of the problem. But how precisely do schools affect young adolescents’ wellbeing? This book aims to answer that question. The book brings together for the first time the results of over 300 research studies, both from the UK and further afield. It identifies the key factors related to schooling which impact upon young people’s development and affect their wellbeing. These include: the extent to which they feel ‘connected’ with school, their relationships with teachers and with their peers, their sense of the school as a learning community, and the ways in which they respond to the pressures of academic work. What matters is how schools bring these elements together to create a strong ‘culture of support’. The Supportive School documents how schools handle young people, particularly at the key transition point from primary to secondary school, as well as the ways in which they respond to their pastoral and other concerns. It also places the UK’s much-criticised ‘performance’ on wellbeing issues in an international context and asks challenging questions about how far the UK is lagging behind. Schools are currently under considerable pressure to give greater attention to issues of wellbeing. The overriding message from The Supportive School is that how schools approach these issues can make a difference to young people’s lives and emotional wellbeing.
A Threefold User-Based Software Evaluation Framework

While pressured to release new software to market, software development organization often find themselves choosing between quality and timeliness. From a business perspective, success is determined to a significant extent by the perceptions of quality exhibited by consumers with respect to the software product being offered. In this context, we propose taxonomy of software users and design a user-centered software evaluation framework to support software quality assessment processes. An online survey is conducted for exploring software users’ perceptions of quality and the results are used to define three categories of software users. The findings of this study shed new light on the way software development organizations should perceive the relationship with their consumers and, consequently, on the way they should manage development projects. The contributions to both research and practice stem from the proposing of a new and more detailed approach to defining and measuring software system quality and its associated assessment processes.
Helicity Evolution in Emerging Active Regions

We study the evolution of twist and magnetic helicity in the coronal fields of active regions as they emerge. We use multiday sequences of Solar and Heliospheric Observatory Michelson Doppler Interferometer magnetograms to characterize the region's emergence. We quantify the overall twist in the coronal field, α, by matching a linear force-free field to bright coronal structures in EUV images. At the beginning of emergence, all regions studied have α ≃ 0. As the active region grows, α increases and reaches a plateau within approximately 1 day of emergence. The inferred helicity transport rate is larger than differential rotation could produce. Following the 2000 work of Longcope & Welsch, we develop a model for the injection of helicity into the corona by the emergence of a twisted flux tube. This model predicts a ramp-up period of approximately 1 day. The observed time history α(t) is fitted by this model assuming reasonable values for the subphotospheric Alfvén speed. The implication is that helicity is carried by twisted flux tubes rising from the convection zone and transported across the photosphere by spinning of the poles driven by magnetic torque.
Demo: CogMAC+ - a decentralized multichannel MAC protocol for cognitive wireless networks

Cognitive MAC schemes are emerging as a prospective solution to efficiently utilize the wireless medium. In order to enable opportunistic access to unused licensed band, a node has to monitor the frequency spectrum and carry out its transmission without causing harmful interference to the primary user. In this work, we demonstrate a decentralized multichannel MAC protocol CogMAC+ which uses a multichannel preamble reservation scheme to achieve parallel transmissions for multiple secondary users. Moreover, CogMAC+ uses an adaptive energy detection scheme to dynamically set the frame detection threshold based on the false positive detection ratio. Our table-top demonstration shows that CogMAC+ enables spectral coexistence and allows nodes to utilize spectrum opportunities efficiently in a dynamic fashion.
Risks in software development with imperfect testing

This study analytically assesses the risk of releasing defective software that cannot be exhaustively tested and of needlessly testing defect-free software. Specifically, it quantifies the probability of committing a Type II error (s) in software development when one may release software that still is faulty while the test methods themselves may not be perfect. The study uses truncated Poisson and geometric distributed path lengths and Bernoulli-type inspection errors to link s to software design features, the development philosophies employed and certain aspects that include code quality, cyclomatic complexity and the average length of basis paths. For risk reduction, this study finds quantitative justification for raising test coverage, perfecting the test methods, the adoption of recent innovations and programming methods such as component-based design, SOA and XP as ways to raise the likelihood that the product developed will be fault-free. Results are relatively robust with respect to the probability distributions assumed.
Real Time Closed Loop Control of Full Penetration Keyhole Welding with Cellular Neural Network Cameras

Camera based in-process control for laser welding enables flexible image processing which allows the adaption of the system to different processes and quality features. A closed loop control system with a Cellular Neural Network Camera was implemented into a laser welding machine. The system is surveying the contour of the full penetration hole with a frame rate of over 10 kHz for both, acquisition and evaluation of area images. As a result the system reaches and holds the full penetration state automatically. This paper shows the latest experimental results including the extension to direction independent weldings.
Climate and vegetation water use efficiency at catchment scales

Peter A. Troch1,2* Guillermo F. Martinez1 Valentijn R. N. Pauwels3 Matej Durcik4 Murugesu Sivapalan5,6 Ciaran Harman6 Paul D. Brooks1,4 Hoshin Gupta1,4 and Travis Huxman7,2 1 Department of Hydrology and Water Resources, University of Arizona, USA 2 Biosphere 2 Earthscience, University of Arizona, USA 3 Laboratory of Hydrology and Water Management, Ghent University, Belgium 4 SAHRA (Sustainability of semi-arid hydrology and riparian areas), University of Arizona, USA 5 Department of Geography, University of Illinois at Urbana-Champaign, USA 6 Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, USA 7 Department of Ecology and Evolutionary Biology, University of Arizona, USA
Exploring the Moderating Effects of Absorptive Capacity on the Relationship between Social Networks and Innovation

Although networks in prior research have been highlighted as a remedy to resource constraints experienced by smaller firms, little attention has been paid to understanding mechanisms through which smaller firms benefit from networks for effective innovation performance. In this paper we develop a conceptual model of direct and moderated network effects on a firm’s innovation. We test this model on a large sample of small and medium-sized firms from a post-transitional and developed economy. We show that absorptive capacity moderates the relationship between networks and innovation outcomes, but with some country level variations. The implications of these results in relation to entrepreneurship theory and practice are discussed.
Faith - an empirical study of expectations of unconditional other-regarding preferences

Expectations of unconditional other-regarding preferences have shown to be important for trust game behavior and can be seen as expectations of generosity or fairness. In this thesis these expectations are captured in the variable faith. A plausible mechanism between faith and trust is developed in line with the findings of Holm and Danielson (2005). An experiment revealing faith and a standard set of survey questions regarding trust is then examined in order to study the predictive power of surveys for faith. The results show that people who donate money expect others to be generous and individuals who engage in several risky activities have higher faith. The result suggests that questions related to these findings should be incorporated with standard questions when combining trust experiments and surveys. The result also shows that faith is better predicted by variables measuring behavior rather than attitudes.
Agency Attribution in Infancy: Evidence for a Negativity Bias

Adults tend to attribute agency and intention to the causes of negative outcomes, even if those causes are obviously mechanical. Is this over-attribution of negative agency the result of years of practice with attributing agency to actual conspecifics, or is it a foundational aspect of our agency-detection system, present in the first year of life? Here we present two experiments with 6-month-old infants, in which they attribute agency to a mechanical claw that causes a bad outcome, but not to a claw that causes a good outcome. Control experiments suggest that the attribution stems directly from the negativity of the outcome, rather than from physical cues present in the stimuli. Together, these results provide evidence for striking developmental continuity in the attribution of agency to the causes of negative outcomes.
A Case Study of the Lived Experiences of Individuals: How Experiential Exercises Aid Entrepreneurship Teachers to Understand Intrapreneurship and the Art of Entrepreneurial Thinking

This research addressed a gap in our knowledge and understanding of if, how, and why experiential exercises might aid teachers to introduce to Entrepreneurship 30 an expanded understanding of the phenomena of entrepreneurship and the “art” of entrepreneurial thinking. A group of five Entrepreneurship 30 teachers attended a 2-day workshop where they were introduced by modelling to a series of experiential exercises. This was followed by a 6-week observation period with interviews. The case study represents the discovery, insight, and understanding of the lived experiences of the research participants as they rejected, adopted, or adapted the material into the curriculum. My research confirms that entrepreneurial thinking can be activated through experiential exercises, but it is not a simple matter to provide teachers with a toolkit of exercises and preliminary training and expect them to teach in this manner. Even experienced teachers with facilitation skills require the resource of expanded class time and administration support to teach the “art” processes of entrepreneurial thinking that require unique pedagogies and a teacher style that encourages students to progress from being passive attendees in classrooms to being participative in terms of discussion, deriving options for decision making and creativity.
Employee participation and company performance: A review of the literature

The Joseph Rowntree Foundation has supported this project as part of its programme of research and innovative development projects, which it hopes will be of value to policy makers, practitioners and service users. The facts presented and views expressed in this report are, however, those of the authors and not necessarily those of the Foundation. Further copies of this report, or any other JRF publication, can be obtained either from the JRF website
Identifying Cause and Effect on Discrete Data using Additive Noise Models

Inferring the causal structure of a set of random variables from a finite sample of the joint distribution is an important problem in science. Recently, methods using additive noise models have been suggested to approach the case of continuous variables. In many situations, however, the variables of interest are discrete or even have only finitely many states. In this work we extend the notion of additive noise models to these cases. Whenever the joint distribution P ) admits such a model in one direction, e.g. Y = f(X) + N, N ⊥ X, it does not admit the reversed model X = g(Y ) + N , N ⊥ Y as long as the model is chosen in a generic way. Based on these deliberations we propose an efficient new algorithm that is able to distinguish between cause and effect for a finite sample of discrete variables. We show that this algorithm works both on synthetic and real data sets.