Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear Parameter Varying Control for Sampled-data Multi-rate Systems

Abstract A new methodology for the design and implementation of linear parameter varying (LVP) controllers for multi-rate sampled-data systems is presented and its stability properties are analyzed. A controller structure is first proposed for the regulation of multi-rate systems with more measured outputs than inputs. This structure is specially suited for a gain-scheduling implementation that verifies an important property known as the linearization property. The proposed solution guarantees local stability of the feedback interconnection of the nonlinear multi-rate system and the LPV controller about individual equilibria, and ultimate boundedness of a conveniently defined closed-loop error in response to slowly varying exogenous inputs. An example is presented that illustrates the applicability of the proposed solution.
Amplifying Matrix Design for Cooperative Relay Networks under Channel Uncertainty and Power Constraint

This paper presents an optimum amplifying relay matrix based on minimum mean square error (MMSE) criteria for the cooperative distributed wireless relay networks under channel uncertainty and total power constraint at the relay nodes. A one-source-one-destination pair node and �� relay nodes are considered, which can be extended for a general case. All relays are assumed to exchange their received signals with no errors for full cooperation. With the derived optimum amplifying relay matrix, bit error rate (BER) of the relay network under channel uncertainty is simulated and compared with that of the network under a certain channel condition to observe the degradation. Index Terms—AF, MMSE, channel-uncertainty, power-const- raint.
Exploring the Test of Covariate Moderation Effects in Multilevel MIMIC Models

In multilevel multiple-indicator multiple-cause (MIMIC) models, covariates can interact at the within level, at the between level, or across levels. This study examines the performance of multilevel MIMIC models in estimating and detecting the interaction effect of two covariates through a simulation and provides an empirical demonstration of modeling the interaction in multilevel MIMIC models. The design factors include the location of the interaction effect (i.e., between, within, or across levels), cluster number, cluster size, intraclass correlation (ICC) level, magnitude of the interaction effect, and cross-level measurement invariance status. Type I error, power, relative bias, and root mean square of error of the interaction effects are examined. The results showed that multilevel MIMIC models performed well in detecting the interaction effect at the within or across levels. However, when the interaction effect was at the between level, the performance of multilevel MIMIC models depended on the magnitude of the interaction effect, ICC, and sample size, especially cluster number. Overall, cross-level measurement noninvariance did not make a notable impact on the estimation of interaction in the structural part of multilevel MIMIC models when factor loadings were allowed to be different across levels.
Wind Turbine Structural Health Monitoring: A Short Investigation Based on SCADA Data

The use of offshore wind farms has been growing in recent years, as steadier and higher wind speeds can be generally found over water compared to land. Moreover, as human activities tend to complicate the construction of land wind farms, offshore locations, which can be found more easily near densely populated areas, can be seen as an attractive choice. However, the cost of an offshore wind farm is relatively high, and therefore their reliability is crucial if they ever need to be fully integrated into the energy arena. As wind turbines have become more complex, efficient, and expensive structures, they require more sophisticated monitoring systems, especially in offshore sites where the financial losses due to failure could be substantial. This paper presents the preliminary analysis of supervisor control and data acquisition (SCADA) extracts from the Lillgrund wind farm for the purposes of structural health monitoring. A machine learning approach is applied in order to produce individual power curves, and then predict measurements of the power produced of each wind turbine from the measurements of the other wind turbines in the farm. A comparison between neural network and Gaussian process regression is also made.
Lecture notes on Knowledge-Based and Learning Systems by Maciej Lískiewicz Lecture 8 : Decision Tree Learning 1 Introduction

We continue with a short motivation. Nowadays, across a wide variety of fields, data are being collected and accumulated at a dramatic pace. For example, within the human genome project there are now billions of data available. But researchers in this field are not mainly interested in the data themselves. Instead, they want to find out, for example, which genes may cause a particular kind of cancer. So, there is an urgent need for a new generation of computational techniques and tools to assist humans in extracting useful information (knowledge) from the rapidly growing volumes of data.
Invasiveness of plants is predicted by size and fecundity in the native range

An important goal for invasive species research is to find key traits of species that predispose them to being invasive outside their native range. Comparative studies have revealed phenotypic and demographic traits that correlate with invasiveness among plants. However, all but a few previous studies have been performed in the invaded range, an approach which potentially conflates predictors of invasiveness with changes that happen during the invasion process itself. Here, we focus on wild plants in their native range to compare life-history traits of species known to be invasive elsewhere, with their exported but noninvasive relatives. Specifically, we test four hypotheses: that invasive plant species (1) are larger; (2) are more fecund; (3) exhibit higher fecundity for a given size; and (4) attempt to make seed more frequently, than their noninvasive relatives in the native range. We control for the effects of environment and phylogeny using sympatric congeneric or confamilial pairs in the native range. We find that invasive species are larger than noninvasive relatives. Greater size yields greater fecundity, but we also find that invasives are more fecund per-unit-size. Synthesis: We provide the first multispecies, taxonomically controlled comparison of size, and fecundity of invasive versus noninvasive plants in their native range. We find that invasive species are bigger, and produce more seeds, even when we account for their differences in size. Our findings demonstrate that invasive plant species are likely to be invasive as a result of both greater size and constitutively higher fecundity. This suggests that size and fecundity, relative to related species, could be used to predict which plants should be quarantined.
Convex analysis approach to d.c. programming: Theory, Algorithm and Applications

Dedicated to Hoang Tuy on the occasion of his seventieth birthday Abstract. This paper is devoted to a thorough study on convex analysis approach to d.c. (difierence of convex functions) programming and gives the State of the Art. Main results about d.c. duality, local and global opti- malities in d.c. programming are presented. These materials constitute the basis of the DCA (d.c. algorithms). Its convergence properties have been tackled in detail, especially in d.c. polyhedral programming where it has flnite convergence. Exact penalty, Lagrangian duality without gap, and regularization techniques have beeen studied to flnd appropriate d.c. de- compositions and to improve consequently the DCA. Finally we present the application of the DCA to solving a lot of important real-life d.c. pro- grams.
Hierarchical Multi-Species Modeling of Carnivore Responses to Hunting, Habitat and Prey in a West African Protected Area

Protected areas (PAs) are a cornerstone of global efforts to shield wildlife from anthropogenic impacts, yet their effectiveness at protecting wide-ranging species prone to human conflict – notably mammalian carnivores – is increasingly in question. An understanding of carnivore responses to human-induced and natural changes in and around PAs is critical not only to the conservation of threatened carnivore populations, but also to the effective protection of ecosystems in which they play key functional roles. However, an important challenge to assessing carnivore communities is the often infrequent and imperfect nature of survey detections. We applied a novel hierarchical multi-species occupancy model that accounted for detectability and spatial autocorrelation to data from 224 camera trap stations (sampled between October 2006 and January 2009) in order to test hypotheses about extrinsic influences on carnivore community dynamics in a West African protected area (Mole National Park, Ghana). We developed spatially explicit indices of illegal hunting activity, law enforcement patrol effort, prey biomass, and habitat productivity across the park, and used a Bayesian model selection framework to identify predictors of site occurrence for individual species and the entire carnivore community. Contrary to our expectation, hunting pressure and edge proximity did not have consistent, negative effects on occurrence across the nine carnivore species detected. Occurrence patterns for most species were positively associated with small prey biomass, and several species had either positive or negative associations with riverine forest (but not with other habitat descriptors). Influences of sampling design on carnivore detectability were also identified and addressed within our modeling framework (e.g., road and observer effects), and the multi-species approach facilitated inference on even the rarest carnivore species in the park. Our study provides insight for the conservation of these regionally significant carnivore populations, and our approach is broadly applicable to the robust assessment of communities of rare and elusive species subject to environmental change.
Genetic Diversity of Tick-Borne Rickettsial Pathogens; Insights Gained from Distant Strains

The ability to capture genetic variation with unprecedented resolution improves our understanding of bacterial populations and their ability to cause disease. The goal of the pathogenomics era is to define genetic diversity that results in disease. Despite the economic losses caused by vector-borne bacteria in the Order Rickettsiales, little is known about the genetic variants responsible for observed phenotypes. The tick-transmitted rickettsial pathogen Anaplasma marginale infects cattle in tropical and subtropical regions worldwide, including Australia. Genomic analysis of North American A. marginale strains reveals a closed core genome defined by high levels of Single Nucleotide Polymorphisms (SNPs). Here we report the first genome sequences and comparative analysis for Australian strains that differ in virulence and transmissibility. A list of genetic differences that segregate with phenotype was evaluated for the ability to distinguish the attenuated strain from virulent field strains. Phylogenetic analyses of the Australian strains revealed a marked evolutionary distance from all previously sequenced strains. SNP analysis showed a strikingly reduced genetic diversity between these strains, with the smallest number of SNPs detected between any two A. marginale strains. The low diversity between these phenotypically distinct bacteria presents a unique opportunity to identify the genetic determinants of virulence and transmission.
Communication challenges in high-density deployments of wearable wireless devices

Wearable wireless devices are very likely to soon move into the mainstream of our society, led by the rapidly expanding multibillion dollar health and fitness markets. Should wearable technology sales follow the same pattern as those of smartphones and tablets, these new devices (a.k.a. wearables) will see explosive growth and high adoption rates over the next five years. It also means that wearables will need to become more sophisticated, capturing what the user sees, hears, or even feels. However, with an avalanche of new wearables, we will need to find ways to supply them with low-latency highspeed data connections to enable truly demanding use cases such as augmented reality. This is particularly true for high-density wearable computing scenarios, such as public transportation, where existing wireless technology may have difficulty supporting stringent application requirements. In this article, we summarize our recent progress in this area with a comprehensive review of current and emerging connectivity solutions for high-density wearable deployments, their relative performance, and open communication challenges.
Preamble-Based Estimation of Highly Frequency Selective Channels in FBMC/OQAM Systems

Channel estimation in multicarrier systems employing filter banks with offset quadrature amplitude modulation (FBMC/OQAM) is far less easy compared to orthogonal frequency division multiplexing (OFDM). Challenges come from the interference effect, inherent in this type of FBMC systems, and the (generally) nonnegligible frequency selectivity of their subchannels, due to the nature of this modulation and the cyclic prefix (CP)-free transmission. Most of the FBMC/OQAM channel estimation methods rely on the assumption of a low frequency selective channel (thus implying (almost) flat subchannels) in order to more easily (i.e., in a manner analogous to CP-OFDM) tackle this problem. However, they perform quite poorly when applied in more demanding propagation conditions. Others, more recent ones, relax the assumption of low frequency selectivity but they either depend on a parametric model for the channel or they concentrate on persubchannel estimation and often require long training sequences. This paper revisits this problem through a formulation that does not rely on any simplifying assumption about the channel. This gives rise to a new estimation method, applicable to channels of any frequency selectivity, which relies on a very short preamble for training. The latter is optimized with respect to the channel estimation mean squared error and is shown to result in a very significant simplification of the estimation procedure. Both full (block-type) and sparse (comb-type) preambles are considered. Applying these results in low-dispersion channels yields, as special cases, existing and new preamble-based estimation schemes for such scenarios. The superiority of the proposed method over classical ones is demonstrated via simulation results for both mildly and highly frequency selective channels.
Molecular dynamics of neuronal information transfer

Abstract A detailed analysis of synapses as connecting elements between neurons is of central importance to understand the brain’s cognitive performance and its constraints. Nowadays, state-of-the-art optical methods make possible to localize individual molecules in a living cell. In particular, the dynamics of molecular composition can be evaluated in smallest neuronal compartments, such as pre- and postsynaptic membrane. The monitoring of the distribution of receptors, ion channels, and adhesion molecules over time revealed their continuous stochastic motion. This is surprising, since the synapses are considered as accumulation sites anchoring these molecules. The direct manipulation of the lateral dynamics of glutamate receptors, in combination with classical electrophysiological approaches, demonstrated that such molecular dynamics is necessary for the induction of synaptic plasticity and, in turn, is influenced by synaptic activity. Therefore, the molecular dynamics requires further studies in the context of the brain function in health and disease.
Cancer treatment decision-making with/ for older adults with dementia: the intersections of autonomy, capital, and power

ABSTRACT In healthcare, health risk assessments are influenced by technical ‘objective’ measurements of the physical body and disease; the values that underlie professional practices (such as beneficence, non-maleficence, and autonomy); the organisations healthcare professionals work for; and subjective belief systems of individual healthcare professionals. As a result, cancer treatments prescribed for older adults can be tempered by personal views about a patient’s age, and other age-associated health conditions or comorbidities that they may have. Drawing from interviews undertaken with nine key staff members in a large cancer service, we examine how treatment recommendations and decisions are determined when older adults with cancer also have dementia; two health conditions more common in older age. Our analysis reveals two themes that underlie the complicated processes of risk-benefit assessment in treatment decision-making: the unequal distribution of capital and power between health workers; and whether older adults with cancer and dementia are assessed as solely individuals or embedded in supportive social networks (individual versus relational autonomy). This analysis exposes capital and personal beliefs about dementia are implicit in health risk assessments for older adults who have cancer and dementia which, in conjunction with organisational constraints, significantly influence how treatment recommendations and decisions are reached.
Quality of a family medicine preceptorship is significantly associated with matching into family practice.

OBJECTIVES This study tested whether clinical experiences in family practice are associated with matching into family practice. METHODS We conducted a prospective cohort study of 913 medical students who completed the Family Practice Preceptorship (FPP) at the University of Iowa from 1990-1996. Using univariate techniques and logistic regression, we compared the background and experiences of those who matched into family practice with those who chose other specialties. RESULTS Twenty-nine percent (n=267) matched into family practice. Positive independent predictors of family practice match were hometown size less than 10,000 (odds ratio [OR] 1.8), anticipating choosing family practice at matriculation (OR 4.2), and liking to help others (OR 4.1). Negative independent predictors included parental income of at least $120,000 (OR .61), desiring to perform technical procedures (OR .51), and liking the scientific method and research (OR .54). The effect of an early summer clinical experience at a community hospital varied depending on the level of student interest in family practice at matriculation. Students who rated the educational value of the FPP as high or very high were significantly more likely to go into family practice (OR 2.9), even after adjusting for all other student characteristics. CONCLUSIONS A number of student characteristics and preferences, early clinical experiences, and the perceived quality of a required family medicine preceptorship were significantly and independently associated with students matching into family practice.
Author ' s response to reviews Title : Evaluation of the potential pleotropic role of angiotensinogen gene polymorphism in atherosclerosis

Critique: The title reads: Evaluation of the potential pleiotropic role of angiotensinogen gene polymorphism in atherosclerosis. My earlier point (which the authors misunderstood) points to the fact that the study does not address the role of the AGT variants, but rather their association with CAD and related traits. I suggest that the title be changed to: Association of the functional angiotensinogen gene polymorphism in coronary artery disease and related traits among Saudi subjects.
Ideology in the schools: Developing the teacher’s Civic Education Ideology Scale within the United States

What ideological views toward citizenship education do teachers possess? Does a teacher’s Civic Education Ideology relate to how and what they teach? This study addresses these questions by developing a psychometric scale measuring teachers’ level of conservative, liberal, and critical Civic Education Ideology in one Midwestern state in the United States. After establishing the Civic Education Ideology scale, these views are compared to teachers’ reported practices inside of school and curriculum emphasized in the classroom. The findings indicate that both conservative- and liberal-oriented teachers were more likely to support curriculum based on civic institutions. In contrast, teachers with a critical orientation were less supportive of civic institutions and more likely to endorse curriculum based on social institutions and an open classroom climate. These findings indicate that a teacher’s ideology relates to their reports of how and what they teach. In addition to these findings, the goal is for the Civic Education Ideology scale to be adapted and applied in future studies to uncover important connections.
The Discovery of Cepheids and a New Distance to NGC 2841 Using the Hubble Space Telescope

We report on the discovery of Cepheids in the spiral galaxy NGC 2841, based on observations made with the Wide Field Planetary Camera 2 on board the Hubble Space Telescope. NGC 2841 was observed over 12 epochs using the F555W filter and over five epochs using the F814W filter. Photometry was performed using the DAOPHOT/ALLFRAME package. We discovered a total of 29 variables, including 18 high-quality Cepheids with periods ranging from 15 to 40 days. Period-luminosity relations in the V and I bands, based on the high-quality Cepheids, yield a reddening-corrected distance modulus of 30.74 ± 0.23 mag, which corresponds to a distance of 14.1 ± 1.5 Mpc. Our distance is based on an assumed LMC distance modulus of μ0 = 18.50 ± 0.10 mag (D = 50 ± 2.5 kpc) and a metallicity dependence of the Cepheid P-L relation of γVI = -0.2 ± 0.2 mag dex-1.
MTJ-Based Nonvolatile 9 T SRAM Cell

This paper presents a spin-transfer torquemagnetic tunnel junction (STT-MTJ) based non-volatile 9-transistor (9T) SRAM cell. The cell achieves low power dissipation due to its series connected MTJ elements and read buffer which offer stacking effect. The paper studies the impact of PVT (process, voltage, and temperature) variations on the design metric of the SRAM cell such as write delay and compares the results with non-volatile 8T SRAM cell (NV8T). The proposed design consumes lower leakage power and exhibits narrower spread in write delay compared with NV8T.
Evaluating Touch-Based Interactions in an Image Search Task

Current technologies provide users different ways to interact with digital content, nevertheless, a physical gap between these two interaction components exists. In particular, touch-based interfaces enable users to use their own fingers to manipulate and interact with digital objects in a more direct fashion than mouse-based interactions. However, it is not clear yet to what extent, if any, this type of interaction could help bridge the gap between users and the digital world in particular information-related contexts such as information search. In this paper we report preliminary results of a user study designed to compare mouse and touch-based interactions in the context of an image search task. This study is part of a larger research project focused on immersive interaction with digital information objects. Our results show that in spite of the novelty, high adoption rates, and tangible nature of touch-based interfaces, no significant differences exist with prevalent technology (i.e., mouse) in terms of performance; nevertheless, user experience was found to better in touch-based interactions.