Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Control in Overweight and Obese Individuals: The Relationship of Dispositional Self-Control and Blood Glucose

Currently, the etiology of obesity is conceptualized as a confluence of environmental, socioeconomic, behavioral, biological and genetic factors. With regard to behavioral factors, some have suggested that a failure of self-control may contribute to the difficulty of an overweight/obese individual because of their inability to resist food or maintain physical activity. Recent research proposed that self-control could be described as similar to a muscle that can be fatigued. Thus, if an individual engages in a self-control task they have lessened ability to utilize self-control on a subsequent task. Theory also suggests self-control may be fueled by a finite resource, identified as blood glucose. The role blood glucose plays is important to understand, especially in overweight and obese populations, as they may be more likely to be insulin resistant. In effect overweight and obese individuals are less likely to adequately process glucose. Therefore overweight/obese individuals might react to self-control tasks differently than normal weight individuals. Participants who were considered normal weight, overweight, and obese were recruited from the UNT research pool. They answered questions about their trait self-control in daily life and engaged in either a task that required them to exert self-control (e.g., resist crossing out a letter unless criteria is met) or a control task (e.g., cross out a letter without restriction). All participants then engaged in a subsequent self-control task to assess if engaging in the initial self-control task reduced performance on the subsequent self-control task compared to the control task. The current research findings were not in line with previous research, in that a depletion effect in self-control was not observed; in neither the normal weight individuals nor the overweight and obese groups. There were several limitations that may have contributed to these findings including; higher DSC than observed in the general population and a possible adaptation effect due to the duration of the self-control tasks, which is in keeping with subsequently published research.
Speech Emotion Recognition Using Fourier Parameters

Recently, studies have been performed on harmony features for speech emotion recognition. It is found in our study that the first- and second-order differences of harmony features also play an important role in speech emotion recognition. Therefore, we propose a new Fourier parameter model using the perceptual content of voice quality and the first- and second-order differences for speaker-independent speech emotion recognition. Experimental results show that the proposed Fourier parameter (FP) features are effective in identifying various emotional states in speech signals. They improve the recognition rates over the methods using Mel frequency cepstral coefficient (MFCC) features by 16.2, 6.8 and 16.6 points on the German database (EMODB), Chinese language database (CASIA) and Chinese elderly emotion database (EESDB). In particular, when combining FP with MFCC, the recognition rates can be further improved on the aforementioned databases by 17.5, 10 and 10.5 points, respectively.
On the Linear Algebraic Structure of Distributed Word Representations

In this work, we leverage the linear algebraic structure of distributed word representations to automatically extend knowledge bases and allow a machine to learn new facts about the world. Our goal is to extract structured facts from corpora in a simpler manner, without applying classifiers or patterns, and using only the co-occurrence statistics of words. We demonstrate that the linear algebraic structure of word embeddings can be used to reduce data requirements for methods of learning facts. In particular, we demonstrate that words belonging to a common category, or pairs of words satisfying a certain relation, form a low-rank subspace in the projected space. We compute a basis for this low-rank subspace using singular value decomposition (SVD), then use this basis to discover new facts and to fit vectors for less frequent words which we do not yet have vectors for.
The complexity of perception of image distortion: an initial study

Image retargeting methods adapt an image for displays with different sizes and aspect ratios. Methods are based on the assumption that some kinds of distortions are preferable to others. While a rich variety of literature exists on retargeting methods, there is little codified understanding of how these distortions are perceived. This paper shows that people's perception of image distortions is complex. We report an initial study exploring the phenomenon that shows that even in a simple form of distortion, perception depends on a myriad of factors including amount of distortion, image content, and the viewer's cultural background. These initial findings have ramifications for the design and evaluation of image retargeting, and suggest that a more thorough study is necessary.
Paracoccidioides spp. ferrous and ferric iron assimilation pathways

Iron is an essential micronutrient for almost all organisms, including fungi. Usually, fungi can uptake iron through receptor-mediated internalization of a siderophore or heme, and/or reductive iron assimilation (RIA). Traditionally, the RIA pathway consists of ferric reductases (Fres), ferroxidase (Fet3) and a high-affinity iron permease (Ftr1). Paracoccidioides spp. genomes do not present an Ftr1 homolog. However, this fungus expresses zinc regulated transporter homologs (Zrts), members of the ZIP family of membrane transporters that are able in some organisms to transport zinc and iron. A 2,3,5-triphenyltetrazolium chloride (TTC)-overlay assay indicates that both Pb01 and Pb18 express a ferric reductase activity; however, 59Fe uptake assays indicate that only in Pb18 is this activity coupled to a reductase-dependent iron uptake pathway. In addition, Zrts are up-regulated in iron deprivation, as indicated by RNAseq and qRT-PCR using Pb01 transcripts. RNAseq strategy also demonstrated that transcripts related to siderophore uptake and biosynthesis are up-regulated in iron-deprived condition. The data suggest that the fungus could use both a non-classical RIA, comprising ferric reductases and Fe/Zn permeases (Zrts), and siderophore uptake pathways under iron-limited conditions. The study of iron metabolism reveals novel surface molecules that could function as accessible targets for drugs to block iron uptake and, consequently, inhibit pathogen's proliferation.
Human Nature: Duality or Triality?

According to eighteenth-century theory and the argument of this article, more science, not less, is the key to human survival. By applying the scientific method in the social sciences.society can target the findings of the physical sciences on ends that are mutually beneficial. [Thereby] humans can deliberately construct? and attach their passions to? institutions that promote peace and prosperity.If institutions can be rationally designed, then irrational motivations can bring rational outcomes. (Miller, 1993:231)
Enzyme Reaction Annotation Using Cloud Techniques

An understanding of the activities of enzymes could help to elucidate the metabolic pathways of thousands of chemical reactions that are catalyzed by enzymes in living systems. Sophisticated applications such as drug design and metabolic reconstruction could be developed using accurate enzyme reaction annotation. Because accurate enzyme reaction annotation methods create potential for enhanced production capacity in these applications, they have received greater attention in the global market. We propose the enzyme reaction prediction (ERP) method as a novel tool to deduce enzyme reactions from domain architecture. We used several frequency relationships between architectures and reactions to enhance the annotation rates for single and multiple catalyzed reactions. The deluge of information which arose from high-throughput techniques in the postgenomic era has improved our understanding of biological data, although it presents obstacles in the data-processing stage. The high computational capacity provided by cloud computing has resulted in an exponential growth in the volume of incoming data. Cloud services also relieve the requirement for large-scale memory space required by this approach to analyze enzyme kinetic data. Our tool is designed as a single execution file; thus, it could be applied to any cloud platform in which multiple queries are supported.
Progression and adherence to an individually prescribed and supervised resistance training intervention in older adults recovering in hospital from lower limb fragility fracture

This study evaluated adherence and progression with a 12-week resistance training program amongst a sample of older adults recovering in hospital from lower limb fragility fracture. Forty-nine participants (mean age 84 years) commenced the resistance training program seven days after the injury. The exercise prescription involved training of the hip and knee extensors, hip abductors, and ankle plantar- and dorsi flexors using resistive bands. Exercise sessions were completed tri-weekly for six weeks under supervision by a physiotherapist and tri-weekly for an additional six weeks independently. Adherence was assessed as the proportion of exercise sessions completed of those prescribed and any progression in resistance was documented. Level of adherence was not found to be influenced by age, gender, cognition or strength but was greater amongst those admitted from the community setting and for the first six weeks when supervision was present. Participants were able to obtain similar levels of resistance for the injured side compared to the noninjured side for all exercises excluding hip abduction and those admitted from the community setting achieved higher levels of resistance compared to those admitted from the residential care setting. These findings suggest that an early resistance training program is feasible and well tolerated amongst older adults recovering from lower limb fragility fracture. Further work is necessary to determine how this level of resistance training translates into functional improvements and how to improve adherence levels in clinical rehabilitation settings.
Head-to-head comparison of 11C-PiB and 18F-FC119S for Aβ imaging in healthy subjects, mild cognitive impairment patients, and Alzheimer's disease patients

Abstract As a new beta amyloid (A&bgr;) positron emission tomography (PET) tracer, 18F-FC119S has shown higher cortical uptake in patients with Alzheimer's disease (AD) than that in healthy control subjects without adverse effects in a previous preliminary study. The aim of this study was to compare 18F-FC119S PET and 11C-PiB PET in healthy control (HC) subjects, mild cognitive impairment (MCI) patients, and AD patients. A total of 48 subjects, including 28 HC subjects, 10 MCI patients, and 10 AD patients, underwent static 18F-FC119S PET (30 minutes after intravenous [i.v.] injection) and 11C-PiB PET (40 minutes after i.v. injection) on the same day. Both PET images were visually and quantitatively assessed. Standardized uptake value ratios (SUVRs) were calculated for each brain region using the cerebellar cortex as a reference region. None (0%) of the 28 HC subjects and 4 (40%) of 10 MCI patients had positive scans on both PET images. Of the 10 AD patients, 7 (70%) had positive scans on 11C-PiB PET while 6 (60%) had positive scans on 18F-FC119S PET. Overall, 47 (98%) of 48 participants showed identical results based on visual analysis. Cortical SUVR of 18F-FC119S was higher in AD patients (1.38 ± 0.16), followed by that in MCI patients (1.24 ± 0.10) and in HC subjects (1.14 ± 0.05). Compared with 11C-PiB PET, 18F-FC119S PET yielded a higher effect size (d = 2.02 vs. 1.67) in AD patients and a slightly lower effect size (d = 1.26 vs. 1.38) in MCI patients. In HC subjects, the nonspecific binding of 18F-FC119S to white matter (with the frontal cortex-to-white matter SUV ratio of 0.76) was slightly lower than that of 11C-PiB (ratio of 0.73). There was a significant linear correlation (slope = 0.41, r = 0.78, P < 0.001) between 11C-PiB and 18F-FC119S cortical SUVR. We could safely obtain images similar to 11C-PiB PET imaging A&bgr; in the brain using 18F-FC119S PET. Therefore, 18F-FC119S might be suitable for imaging A&bgr; deposition.
A Min-Min Max-Min Selective Algorithm for Grid Task Scheduling

Today, the high cost of supercomputers in the one hand and the need for large-scale computational resources on the other hand, has led to use network of computational resources known as Grid. Numerous research groups in universities, research labs, and industries around the world are now working on a type of Grid called Computational Grids that enable aggregation of distributed resources for solving large-scale data intensive problems in science, engineering, and commerce. Several institutions and universities have started research and teaching programs on Grid computing as part of their parallel and distributed computing curriculum. To better use tremendous capabilities of this distributed system, effective and efficient scheduling algorithms are needed. In this paper, we introduce a new scheduling algorithm based on two conventional scheduling algorithms, Min-Min and Max-Min, to use their cons and at the same time, cover their pros. It selects between the two algorithms based on standard deviation of the expected completion time of tasks on resources. We evaluate our scheduling heuristic, the Selective algorithm, within a grid simulator called GridSim. We also compared our approach to its two basic heuristics. The experimental results show that the new heuristic can lead to significant performance gain for a variety of scenarios.
Raptor is Phosphorylated by cdc2 during Mitosis

Background The appropriate control of mitotic entry and exit is reliant on a series of interlocking signaling events that coordinately drive the biological processes required for accurate cell division. Overlaid onto these signals that promote orchestrated cell division are checkpoints that ensure appropriate mitotic spindle formation, a lack of DNA damage, kinetochore attachment, and that each daughter cell has the appropriate complement of DNA. We recently discovered that AMP-activated protein kinase (AMPK) modulates the G2/M phase of cell cycle progression in part through its suppression of mammalian target of rapamycin (mTOR) signaling. AMPK directly phosphorylates the critical mTOR binding partner raptor inhibiting mTORC1 (mTOR-raptor rapamycin sensitive mTOR kinase complex 1). As mTOR has been previously tied to mitotic control, we examined further how raptor may contribute to this process. Methodology/Principal Findings We have discovered that raptor becomes highly phosphorylated in cells in mitosis. Utilizing tandem mass spectrometry, we identified a number of novel phosphorylation sites in raptor, and using phospho-specific antibodies demonstrated that raptor becomes phosphorylated on phospho-serine/threonine-proline sites in mitosis. A combination of site-directed mutagenesis in a tagged raptor cDNA and analysis with a series of new phospho-specific antibodies generated against different sites in raptor revealed that Serine 696 and Threonine 706 represent two key sites in raptor phosphorylated in mitosis. We demonstrate that the mitotic cyclin-dependent kinase cdc2/CDK1 is the kinase responsible for phosphorylating these sites, and its mitotic partner Cyclin B efficiently coimmunoprecipitates with raptor in mitotic cells. Conclusions/Significance This study demonstrates that the key mTOR binding partner raptor is directly phosphorylated during mitosis by cdc2. This reinforces previous studies suggesting that mTOR activity is highly regulated and important for mitotic progression, and points to a direct modulation of the mTORC1 complex during mitosis.
“Now We Have Equality”: A Feminist Political Ecology Analysis of Carbon Markets in Oaxaca, Mexico

Abstract:Carbon projects follow a neoliberal logic that stresses that nature is best conserved via market mechanisms. Studies and experiences of the impacts of development projects on communities and feminist political ecologies suggest that women, the elderly, the young, the poor, and the indigenous often perceive projects differently, benefit and lose in different ways, or shape the projects on the ground to fit their needs. Carbon projects have differentiated impacts within a community especially on the poor, women, and ecology; however, these differences do not tend to be the main focus of scholarship. The research presented here focuses on the effects of a wind project and a small scale reforestation project and the convergence of environment, gender and development as these are introduced into communities in Oaxaca, Mexico. This paper expands on carbon offset literature in Mexico by looking at the differential impacts of technologies on geographies and people with specific attention to gender. I find that there are important gendered differences between the wind and the forest projects, and suggest that a Feminist Political Ecology perspective is a necessary, though infrequently employed, lens through which to understand the impacts of carbon markets.Resumen:Los proyectos de carbono siguen una lógica neoliberal que mantiene que la mejor manera de conservar a la naturaleza es a través de mecanismos de mercado. Estudios y experiencias de los impactos de proyectos de desarrollo en las comunidades y ecologías políticas feministas sugieren que las mujeres, los ancianos, los jóvenes, los pobres y los indígenas a menudo perciben los proyectos de manera diferente, ganan ó pierden de manera diferente, o adaptan los proyectos para satisfacer a sus necesidades. Se ha documentado que los proyectos de carbono tienen impactos diferenciados dentro de comunidades, especialmente sobre los pobres, las mujeres, y la ecología; Sin embargo, estas diferencias no tienden a ser el foco principal. La investigación que se presenta aquí se centra en un mega proyecto eólico y dos proyectos de reforestación de pequeña escala y se enfoca en la convergencia del medio ambiente, de género y desarrollo, al ser introducidos en las comunidades de Oaxaca, México. Este trabajo busca expandir la literatura sobre los mercados de carbono en México con un enfoque en los impactos diferenciales de las tecnologías, la geografía y en las personas con atención especial al género. Encuentro que hay diferencias de género importantes entre: los proyectos forestales y el de viento y, si están bajo un esquema de Mecanismo de Desarrollo Limpio o un mecanismo voluntario, la escala del proyecto y el grado en el que está involucrada la comunidad.
ZT Optimization: An Application Focus

Significant research has been performed on the challenge of improving thermoelectric materials, with maximum peak figure of merit, ZT, the most common target. We use an approximate thermoelectric material model, matched to real materials, to demonstrate that when an application is known, average ZT is a significantly better optimization target. We quantify this difference with some examples, with one scenario showing that changing the doping to increase peak ZT by 19% can lead to a performance drop of 16%. The importance of average ZT means that the temperature at which the ZT peak occurs should be given similar weight to the value of the peak. An ideal material for an application operates across the maximum peak ZT, otherwise maximum performance occurs when the peak value is reduced in order to improve the peak position.
The fast affine projection algorithm

This paper discusses a new adaptive filtering algorithm called fast affine projections (FAP). FAP's key features include LMS like complexity and memory requirements (low), and RLS like convergence (fast) for the important case where the excitation signal is speech. Another of FAP's important features is that it causes no delay in the input or output signals. In addition, the algorithm is easily regularized resulting in robust performance even for highly colored excitation signals. The combination of these features make FAP an excellent candidate for the adaptive filter in the acoustic echo cancellation problem. A simple, low complexity numerical stabilization method for the algorithm is also introduced.
5-MHz 11-bit delay-based self-oscillating ΣΔ modulator in 0.025mm2

In this paper a self-oscillating ΣΔ modulator is presented. By introducing this self-oscillation in the system, the loop filter operates at a speed significantly lower than dictated by the clock frequency. This allows for a simple and power efficient design of the opamps used in the loop filter. The self-oscillation is induced here by introducing a controlled delay in the feedback loop of the modulator. A second order CMOS prototype was constructed in a 0.18 µm technology. A clock frequency of 850MHz generates a self-oscillation mode at 106.25 MHz. The modulator achieves a dynamic range (DR) of 66 dB for a signal bandwidth of 5 MHz. The power consumption is only 6mW and the chip area of the modulator core is 0.025mm2.
A Language Detection System for Short Chats in Mobile Games

Machine Translation system accuracies are often brought down due to inaccurate Language Detection (LD) of input phrases. The Language detection accuracy is further affected when the inputs are short and contain ungrammatical phrases, especially in a multilingual mobile game setting. Chat messages in mobile games are often short as they are typed on mobile devices and contain slang as a common communication preference. Previous work has shown that LD systems have a drop in accuracy when the inputs are short messages instead of long ones. This paper targets LD for short chat messages in mobile games. We propose a novel LD system which integrates text-based and user-based methods to achieve significantly better performance over current state-of-the-art LD systems.
Improved decision tree induction: Prioritized Height Balanced tree with entropy to find hidden rules

Classification is widely used technique in the data mining domain, where scalability and efficiency are the immediate problems in classification algorithms for large databases. We suggest improvements to the existing C4.5 decision tree algorithm. In this paper attribute oriented induction (AOI) and relevance analysis are incorporated with concept hierarchy's knowledge and HeightBalancePriority algorithm for construction of decision tree along with Multi level mining. The assignment of priorities to attributes is done by evaluating information entropy, at different levels of abstraction for building decision tree using HeightBalancePriority algorithm. Modified DMQL queries are used to understand and explore the shortcomings of the decision trees generated by C4.5 classifier for education dataset and the results are compared with the proposed approach.
SNPAnalyzer: Web-Based Workbench for the SNPs Analysis

There are many number of computer programs freely available for studying genetic variation of human. Computer programs like EH program [7] and Haplotyper [6] reconstruct haplotypes from unphased genotype data, and QTL Cartographer [2] is a qtl mapping software. However, these programs have many limitations such as time complexity problem for the analysis of large amount of alleles or SNPs, difficult manipulation for installation, data import, and usage, and low quality visual output. SNPAnalyzer is a new workbench program for the SNP analysis, which consists of 4 main modules: 1) Hardy-Weinberg Equilibrium, 2) Haplotype Estimation, 3) Linkage Disequilibrium, and 4) QTL Mapping. It can handle large amount of alleles and SNPs in rather manageable time with at least two different algorithms, and the data import and format are quite convenient and simple. One outstanding feature of SNPAnalyzer is that it can also deal with qtl (quantitative trait locus) analysis as well as linkage study. All the analysis results are displayed in user-friendly format of tables, graphs, or maps. SNPAnalyzer is developed using C and C++ and can be executed through web-interface.