Miracle-dz/UniFAR-FTUs huggingface dataset:
On the cued activation of situational motivation q

We examined the hypothesis that situational (or state) motivation can generalize from one situation to another via activation by associated cues. In an experimental setting, a neutral cue (a computer tone sequence) was paired repeatedly with controlling feedback. We then assessed the effect of presenting this conditioned cue during a subsequent task on participants motivation for that novel task. In two studies we found evidence that cued activation of controlledness significantly undermined participants self-determined motivation toward this subsequent task. These findings demonstrate that subtle cues, including contextual primes, can influence people s motivational state. 2004 Elsevier Inc. All rights reserved.
Exercise Training at Maximal Fat Oxidation Intensity for Older Women with Type 2 Diabetes

Abstract The purpose of this study was to investigate the pleiotropic effects of 12 weeks of supervised exercise training at maximal fat oxidation (FATmax) intensity on body composition, lipid profile, glycemic control, insulin sensitivity and serum adipokine levels in older women with type 2 diabetes. Thirty-one women with type 2 diabetes, aged 60 to 69 years, were randomly allocated into exercise and control groups. Body composition, lipid profile, blood glucose, insulin resistance and serum leptin and adiponectin concentrations were measured before and after the intervention. Exercise group (n=16) walked at individualized FATmax intensities for 1 h/day for 3 days/week over 12 weeks. No dietary intervention was introduced during the experimental period. Maximal fat oxidation rate was 0.37±0.10 g/min, and occurred at 37.3±7.3% of the estimated VO2max. Within the exercise group, significant improvements were observed for most of the measured variables compared to non-exercising controls; in particular, the FATmax program reduced body fat% (p<0.001), visceral fat% (p<0.001), and insulin resistance (p<0.001). There was no significant change in daily energy intake for all participants during the intervention period. These results suggest that individualized FATmax training is an effective exercise training intensity for managing type 2 diabetes in older women.
Postprocessing of Compressed Images via Sequential Denoising

In this paper, we propose a novel postprocessing technique for compression-artifact reduction. Our approach is based on posing this task as an inverse problem, with a regularization that leverages on existing state-of-the-art image denoising algorithms. We rely on the recently proposed Plug-and-Play Prior framework, suggesting the solution of general inverse problems via alternating direction method of multipliers, leading to a sequence of Gaussian denoising steps. A key feature in our scheme is a linearization of the compression-decompression process, so as to get a formulation that can be optimized. In addition, we supply a thorough analysis of this linear approximation for several basic compression procedures. The proposed method is suitable for diverse compression techniques that rely on transform coding. In particular, we demonstrate impressive gains in image quality for several leading compression methods-JPEG, JPEG2000, and HEVC.
Interpreting beta‐diversity components over time to conserve metacommunities in highly dynamic ecosystems

The concept of metacommunity (i.e., a set of local communities linked by dispersal) has gained great popularity among community ecologists. However, metacommunity research mostly addresses questions on spatial patterns of biodiversity at the regional scale, whereas conservation planning requires quantifying temporal variation in those metacommunities and the contributions that individual (local) sites make to regional dynamics. We propose that recent advances in diversity‐partitioning methods may allow for a better understanding of metacommunity dynamics and the identification of keystone sites. We used time series of the 2 components of beta diversity (richness and replacement) and the contributions of local sites to these components to examine which sites controlled source‐sink dynamics in a highly dynamic model system (an intermittent river). The relative importance of the richness and replacement components of beta diversity fluctuated over time, and sample aggregation led to underestimation of beta diversity by up to 35%. Our literature review revealed that research on intermittent rivers would benefit greatly from examination of beta‐diversity components over time. Adequately appraising spatiotemporal variability in community composition and identifying sites that are pivotal for maintaining biodiversity at the landscape scale are key needs for conservation prioritization and planning. Thus, our framework may be used to guide conservation actions in highly dynamic ecosystems when time‐series data describing biodiversity across sites connected by dispersal are available.
Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging

Significance Complete resection of a tumor is associated with an improved prognosis for most types of solid malignancies. In gastric-cancer surgery, surgical-margin evaluation is commonly performed intraoperatively by histopathologic evaluation of frozen sections. However, frozen-section results are subjective and can be unreliable in up to 30% of patients undergoing resection of gastrointestinal cancers. We used desorption electrospray ionization mass spectrometric imaging (DESI-MSI) and the statistical method of least absolute shrinkage and selection operator (Lasso) to classify tissue as cancer or normal based on molecular information obtained from tissue and also to select those mass-spectra features most indicative of disease state. The results obtained using margin samples from nine gastric-cancer operations suggest that DESI-MSI/Lasso may be a valuable tool for routine intraoperative assessment of surgical margins during gastric-cancer surgery. Surgical resection is the main curative option for gastrointestinal cancers. The extent of cancer resection is commonly assessed during surgery by pathologic evaluation of (frozen sections of) the tissue at the resected specimen margin(s) to verify whether cancer is present. We compare this method to an alternative procedure, desorption electrospray ionization mass spectrometric imaging (DESI-MSI), for 62 banked human cancerous and normal gastric-tissue samples. In DESI-MSI, microdroplets strike the tissue sample, the resulting splash enters a mass spectrometer, and a statistical analysis, here, the Lasso method (which stands for least absolute shrinkage and selection operator and which is a multiclass logistic regression with L1 penalty), is applied to classify tissues based on the molecular information obtained directly from DESI-MSI. The methodology developed with 28 frozen training samples of clear histopathologic diagnosis showed an overall accuracy value of 98% for the 12,480 pixels evaluated in cross-validation (CV), and 97% when a completely independent set of samples was tested. By applying an additional spatial smoothing technique, the accuracy for both CV and the independent set of samples was 99% compared with histological diagnoses. To test our method for clinical use, we applied it to a total of 21 tissue-margin samples prospectively obtained from nine gastric-cancer patients. The results obtained suggest that DESI-MSI/Lasso may be valuable for routine intraoperative assessment of the specimen margins during gastric-cancer surgery.
fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs

In recent years, Convolutional Neural Networks (ConvNets) have become an enabling technology for a wide range of novel embedded Artificial Intelligence systems. Across the range of applications, the performance needs vary significantly, from high-throughput video surveillance to the very low-latency requirements of autonomous cars. In this context, FPGAs can provide a potential platform that can be optimally configured based on the different performance needs. However, the complexity of ConvNet models keeps increasing making their mapping to an FPGA device a challenging task. This work presents fpgaConvNet, an end-to-end framework for mapping ConvNets on FPGAs. The proposed framework employs an automated design methodology based on the Synchronous Dataflow (SDF) paradigm and defines a set of SDF transformations in order to efficiently explore the architectural design space. By selectively optimising for throughput, latency or multiobjective criteria, the presented tool is able to efficiently explore the design space and generate hardware designs from high-level ConvNet specifications, explicitly optimised for the performance metric of interest. Overall, our framework yields designs that improve the performance by up to 6.65x over highly optimised embedded GPU designs for the same power constraints in embedded environments.
3-D Soil Compaction Mapping Through Kriging-Based Exploration With a Mobile Robot

This letter presents an automated method for creating spatial maps of soil condition with an outdoor mobile robot. Effective soil mapping on farms can enhance yields, reduce inputs, and help protect the environment. Traditionally, data are collected manually at an arbitrary set of locations, then soil maps are constructed offline using kriging, a form of Gaussian process regression. This process is laborious and costly, limiting the quality and resolution of the resulting information. Instead, we propose to use an outdoor mobile robot for automatic collection of soil condition data, building soil maps online and also adapting the robot's exploration strategy on-the-fly based on the current quality of the map. We show how using kriging variance as a reward function for robotic exploration allows for both more efficient data collection and better soil models. This letter presents the theoretical foundations for our proposal and an experimental comparison of exploration strategies using soil compaction data from a field generated with a mobile robot.
Moralization and the 2012 U.S. Presidential Election Campaign

People vary in the extent to which they imbue an attitude with moral conviction; however, little is known about what makes an issue transform from a relatively non-moral preference to a moral conviction. In the context of the 2012 U.S. presidential election, we test if affect and beliefs (thoughts about harms and benefits) are antecedents or consequences of participants’ moral conviction about their candidate preferences, or are some combination of both. Using a longitudinal design in the run-up to the election, we find that, overall, affect is both an antecedent and consequence, and beliefs about harms and benefits are only consequences, of changes in moral conviction related to candidate preferences. The affect results were consistent across liberals, conservatives, and moderates; however, the role of beliefs showed some differences between ideologues (liberals and conservatives) and moderates.
A New Algorithm Combining Self Organizing Map with Simulated Annealing Used in Intrusion Detection

The effect of clustering by Self Organizing Map (SOM) is always effective in intrusion detection (IDS). But there are still some limitations in the algorithm of SOM, such as the algorithm is easy to get into the local minimum, detection accuracy is low, the convergence speed is slow and so on. In this paper, to improve the accuracy and convergence rate, we use Simulated Annealing (SA) algorithm to refine the weight of SOM. SA algorithm find the optimal point by a form of probability, and it is proved that if enough time is given, the SA can certainly find the optimal point. The algorithm is divided into two steps: first, use traditional SOM algorithm to train samples; second, adjust the weight of excited neuron and its neighborhoods by SA algorithm. The simulation experiment results illuminate that the application performs fairly more effective.
Two distinct exploratory behaviors in decisions from experience : Comment on Gonzalez & Dutt , 2011 Two Distinct Exploratory Behaviors in Decisions From Experience : Comment on Gonzalez & Dutt

Gonzalez and Dutt (2011) recently reported that trends during sampling, prior to a consequential risky decision, reveal a gradual movement from exploration to exploitation. That is, even when search imposes no immediate costs, people adopt the same pattern manifest in costly search: early exploration followed by later exploitation. From this isomorphism the authors conclude that the same cognitive mechanisms underlie the control of sampling in two experimental paradigms employed to investigate decisions from experience—the sampling paradigm implementing costless search and the repeated choice paradigm implementing costly search. We show that this is a misinterpretation of the data resulting from drawing inferences about cognitive processes from data aggregated across individuals. Because of an inverse relationship between sample size and the propensity to explore, aggregating across individuals produces a pattern where exploration is gradually replaced by exploitation. On an individual level, however, there is no general reduction in exploration during the sampling in the sampling paradigm. We list ensuing problems for the instance-based learning model Gonzalez and Dutt present to explain the similarities between sampling and repeated decisions from experience.
triple hop for distance

Introduction H school, university, and professional sports teams often devote considerable resources (human and capital) to quantify an athlete’s sport potential and to train individuals to improve athletic performance. Athleticism is computed not simply by the points scored or tackles achieved, but also through metrics that eliminate the need to compensate for different levels of competition and support from teammates. Performance on screening tests such as the vertical jump, 10-yard sprint, or pro-agility shuttle run are used to help differentiate those athletes most likely to excel in a given sport from a larger cohort of skillful recruits [1]. These same performance measures can also be used to track an athlete’s response to training over short and long periods of time [2]. Lower extremity strength and power can heavily factor into overall athletic performance. For example, the results of performance tests involving jumping height and running speed are largely dependent on the individual’s lower extremity strength and power production capabilities [1, 3]. When taking into account Abstract Introduction. Triple hop for distance (THD) is an inexpensive test used clinically to evaluate lower extremity functional performance. Given known relationships between THD and lower extremity strength and power, THD could be used as a time efficient approach for assessing athleticism. Aim of Study. The aim of this study was to detect the extent to which THD of the dominant and non-dominant legs predict performance of vertical jump (VJ), pro-agility shuttle run, and 10-yard sprint in a large cohort of male and female collegiate athletes. Material and Methods. One hundred sixty athletes (80 men) performed VJ, 10-yard sprint, pro-agility shuttle run, and THD. Separate stepwise linear regression analyses were used to determine how THD of dominant and non-dominant legs predicted athletic performance of each test. Results. For male athletes, nondominant leg was the best and only predictor for VJ, pro-agility shuttle run, and 10-yard sprint, explaining 42.4%, 56.6%, and 46.9% of the variance, respectively. For female athletes, the dominant leg was the best and only predictor for VJ, pro-agility shuttle run, and 10-yard sprint, explaining 42.9%, 41.5%, and 27.0% of the variance, respectively. Conclusions. THD could serve as efficient tool to predict performance on athletic tasks including jumping and sprinting. Moreover, THD could guide subsequent training interventions aimed at improving athletes’ jumping and sprinting abilities.
Compatibilization of Linear PPS/PET Blends with SEBS Copolymers

The effect of styrene-ethylene/butylene-styrene (SEBS) on the blend of polyphenylene sulfide (PPS) and polyethylene terephthalate (PET) was investigated. The blends were extruded by a single screw extruder equipped with a Maddock mixing screw, and their molded properties were examined. After the binary blends were prepared on the whole compositions of PPS/PET (80/20, 60/40, 40/60, 20/80), the thermal, rheological, mechanical properties and morphology of the blends were analyzed. The results showed the significant decline in the properties of the blends owing to the incompatibility between PPS and PET phases. As a basic blend composition, the PPS/PET (40/60) blend was selected by considering cost efficiency. To this basic blend, SEBS was added as a compatibilizer. With increasing SEBS addition, the mechanical properties were improved. From the domain size reduction observed in morphology, it might be due to the enhancement of compatibility between linear PPS and PET phases by addition of SEBS.
Determination of Optimal Process Flowrates and Reactor Design for Autothermal Hydrogen Production in a Heat-Integrated Ceramic Microchannel Network

Determination of Optimal Process Flowrates and Reactor Design for Autothermal Hydrogen Production in a Heat-Integrated Ceramic Microchannel Network. (May 2012) Shalini Damodharan, B.Tech., Anna University Chair of Advisory Committee: Dr. Benjamin Wilhite The present work aimed at designing a thermally efficient microreactor system coupling methanol steam reforming with methanol combustion for autothermal hydrogen production. A preliminary study was performed by analyzing three prototype reactor configurations to identify the optimal radial distribution pattern upon enhancing the reactor self-insulation. The annular heat integration pattern of Architecture C showed superior performance in providing efficient heat retention to the system with a 50 – 150 o C decrease in maximum external-surface temperature. Detailed work was performed using Architecture C configuration to optimize the catalyst placement in the microreactor network, and optimize reforming and combustion flows, using no third coolant line. The optimized combustion and reforming catalyst configuration prevented the hot-spot migration from the reactor midpoint and enabled stable reactor operation at all process flowrates studied. Best results were obtained at high reforming flowrates (1800 sccm) with an increase in combustion flowrate (300 sccm) with the net H2 yield of 53% and
Industrial Cyberphysical Systems: Realizing Cloud-Based Big Data Infrastructures

Future industrial systems and applications are expected to be complex constellations of cyberphysical systems (CPSs) where intel l igent networked embedded devices play a pivotal role toward the realization of new sophisticated industrial scenarios. The prevalence of multifaceted devices enables new avenues for monitoring at large scale via Internet of Things (IoT) technologies, and, when coupled with the real-time analysis of massive amounts of data, it results in new insights that can enhance decision-making processes and provide a competitive business advantage. How to collect, process, analyze, and interpret big data is a challenge that affects all industries, and, if effectively addressed, it would offer numerous operational benefits. This article discusses some of the main architectural issues related to collecting and handling big data for analysis linked to IoT and cloud technologies in the industrial context. The aim is to provide a high-level introductory view of this topic, underpinned with examples from popular frameworks, and discuss open research questions and future directions.
Buckling analysis of the functionally graded sandwich rectangular plates integrated with piezoelectric layers under bi-axial loads

Mechanical stability of the functionally graded rectangular plates bonded with functionally graded piezoelectric layers is studied in the present research. Classical plate theory is employed in the description of three components of the plate displacement. Geometric nonlinearity is considered in the strain–displacement relations using the von Karman equation. The constitutive relations are developed for the functionally graded material core and functionally graded plate material layers in the general state. The top and bottom of the piezoelectric layers is assumed to be short-circuited. Three equilibrium equations as well as Maxwell equation are constituted of four governing differential equations of the problem. Some important nondimensional parameters representing the geometries of the sandwich plate incorporated with nonhomogeneous index of the material properties are considered for this analysis. The results indicate that these parameters have important effects on the buckling loads.
SNP Discovery in European Anchovy (Engraulis encrasicolus, L) by High-Throughput Transcriptome and Genome Sequencing

Increased throughput in sequencing technologies has facilitated the acquisition of detailed genomic information in non-model species. The focus of this research was to discover and validate SNPs derived from the European anchovy (Engraulis encrasicolus) transcriptome, a species with no available reference genome, using next generation sequencing technologies. A cDNA library was constructed from four tissues of ten fish individuals corresponding to three populations of E. encrasicolus, and Roche 454 GS FLX Titanium sequencing yielded 19,367 contigs. Additionally, the European anchovy genome was sequenced for the same ten individuals using an Illumina HiSeq2000. Using a computational pipeline for combining transcriptome and genome information, a total of 18,994 SNPs met the necessary minor allele frequency and depth filters. A series of further stringent filters were applied to identify those SNPs likely to succeed in genotyping assays, and for filtering of those in potential duplicated genome regions. A novel method for detecting potential intron-exon boundaries in areas of putative SNPs has also been applied in silico to improve genotyping success. In all, 2,317 filtered putative transcriptome SNPs suitable for genotyping primer design were identified. From those, a subset of 530 were selected, with the genotyping results showing the highest reported conversion and validation rates (91.3% and 83.2%, respectively) reported to date for a non-model species. This study represents a promising strategy to discover genotypable SNPs in the exome of non-model organisms. The genomic resource generated for E. encrasicolus, both in terms of sequences and novel markers, will be informative for research into this species with applications including traceability studies, population genetic analyses and aquaculture.
Identifying Single-Event Transient Location Based on Compressed Sensing

Single-event transients (SETs) have seriously deteriorated the reliability of integrated circuits (ICs), especially for those in mission- or security-critical applications. Detecting and locating SETs can be useful for fault analysis and design enhancement. Traditional methods of location identification of SETs usually require special sensors embedded into the circuits, or radiation scanning with fine resolutions over the surface for inspection. In this paper, we propose a method of location identification of SETs without sensors or image processing. We formulate location identification of SETs as a compressed sensing problem due to the sparsity and noncoherence observation. The simulation result on a cryptographic IC is demonstrated. The results illustrate that the proposed method has three advantages, compared to traditional SETs test methods: 1) the SETs sensitive area can be accurately identified; 2) the sampling rate is reduced by 64%; therefore, the test efficiency is largely enhanced with negligible hardware overhead; and 3) the method of location identification of SETs is robust to noise interference.