Miracle-dz/UniFAR-FTUs huggingface dataset:
The Emotions of Adults with Diabetes

Abstract Diabetes is a disease with menacing complications and demanding treatment regimes that confront those afflicted throughout their lives. Emotions are common responses to disease and illness. Unfortunately, few studies explore the emotions adults experience while living with diabetes. This qualitative study sought to identify the ordinary (non-pathological) emotions, specify their sources (causes, stimuli), and the effect of race on these experiences. A total of 76 emotions from 38 different sources were described by 34 subjects. Race influenced both the quality and quantity of the emotions. The length of time with diabetes, the number of complications reported, and the subjects' rating for diabetes self-management success also influenced emotion experiences.
Modeling the association between lifecourse socioeconomic disadvantage and systemic inflammation in healthy adults: The role of self-control.

OBJECTIVE We sought to identify pathways connecting lifecourse socioeconomic status (SES) with chronic, low-grade inflammation, focusing on the explanatory roles of self-control, abdominal adiposity, and health practices. METHODS Participants were 360 adults aged 15-55 who were free of chronic medical conditions. They were roughly equally divided between low and high current SES, with each group further divided between low and high early-life SES. Structural equation modeling (SEM) was used to identify direct and indirect pathways linking early-life and current SES with low-grade, chronic inflammation in adulthood, as manifest by serum interleukin-6 and C-reactive protein. Low SES was hypothesized to relate to inflammation by reducing self-control, which in turn was hypothesized to facilitate lifestyle factors that potentiate inflammation (smoking, alcohol use, sedentary behavior, and weight gain). RESULTS Analyses revealed that self-control was pivotal in linking both early-life and current SES to inflammation. Low early-life SES was related to a harsher family climate, and in turn lower adult self-control, over and above the effects of current SES. Controlling for early-life SES, low current SES was associated with perceived stress and, in turn, diminished self-control. Results showed that lower self-control primarily operated through higher abdominal adiposity to associate with greater inflammation. CONCLUSIONS The findings suggest a mechanistic scenario wherein low SES in early life or adulthood depletes self-control and, in turn, fosters adiposity and inflammation. These pathways should be studied longitudinally to elucidate and potentially ameliorate socioeconomic disparities in health.
Deletion 2q37 syndrome: Cognitive‐behavioral trajectories and autistic features related to breakpoint and deletion size

Subtelomeric deletions have been reported in ∼2.5% of individuals with developmental disabilities. Subtelomeric deletion 2q37 has been detected in many individuals diagnosed with intellectual disabilities (ID) and autism spectrum disorders (ASD). Previously, genotype–phenotype correspondences were examined for their relationship to breakpoints 37.1, 37.2, or 37.3. Our purpose was to ascertain whether there were phenotypic differences at these breakpoints, elucidate the cognitive‐behavioral phenotype in del2q37, and examine the genotype–phenotype association in the deletion with respect to cognitive‐behavioral profiles and ASD. We administered a comprehensive cognitive‐behavioral battery to nine children diagnosed with del 2q37, ages 3.9–17.75 years. ID for five tested with the Stanford–Binet (4th Edition) (SBFE) ranged from severe to mild [IQ Range: 36–59]. Adaptive behavior scores from the Vineland Adaptive Behavior Scale (VABS) were much below adequate levels (DQ Range: floor value [“19”] to 55). Autism scores from the Child Autism Rating Scale (CARS) ranged from 22 [non‐autistic] to 56 [extremely autistic]; 5/8 [63%] children received scores on the autism spectrum. Participants with the largest deletions, 10.1 and 9.5 Mb, attained the highest IQ and DQ scores while those with the smallest deletions, 7.9 and 6.6 Mb, made the lowest IQ and DQ scores. No association between deletion breakpoint and phenotype were found. Assessment of the various deleted regions suggested histone deacetylase 4 gene (HDAC4) was a likely candidate gene for ASD in our sample. However, two earlier reports found no association between HDAC4 haploinsufficiency and ASD. © 2016 Wiley Periodicals, Inc.
A New Placement Approach to Minimizing FPGA Reconfiguration Data

Dynamic reconfiguration for fine-grained architectures is still associated with significant reconfiguration costs. In this paper, a new placement algorithm is proposed to reduce the size of FPGA reconfiguration bitstream. The algorithm is modified on the existing placement algorithm within VPR. It introduces the CLBs configuration of the previous circuit into cost function to increase similarity of CLBs configuration for subsequent circuits at the layout level. By using difference-based partial reconfiguration design flow, the proposed approach is validated by experiments on Xilinx Virtex FPGA platform, and experimental results show that the size of reconfiguration bitstream can be reduced.
Monoclonal Antibodies in Gynecological Cancer: A Critical Point of View

During the last decades, several improvements in treating gynecological malignancies have been achieved. In particular, target therapies, mostly monoclonal antibodies, have emerged as an attractive option for the treatment of these malignancies. In fact, various molecular-targeted agents have been developed for a variety of malignancies with the objective to interfere with a precise tumor associated receptor, essential for cancer cell survival or proliferation, blocking its function, of the cancer cells. Alternatively, monoclonal antibodies have been developed to block immune suppression or enhance functions of immune effector cells. So far, several monoclonal antibodies have been tested for clinical efficacy for the treatment of gynecological cancers. Antibodies against Vascular Endothelial Growth Factor (VEGF) and Epidermal Growth Factor Receptor (EGFR) have been used in different neoplasms such as ovarian and cervical cancer. Catumazumab, a bivalent antibody against CD3 and EpCAM, is effective in the treatment of neoplastic ascites. Other antibodies are peculiar for specific cancer-associated antigen such as Oregovomab against CA125 or Farletuzumab against the folate receptor. Here we describe the preclinical and clinical experience gained up to now with monoclonal antibodies in tumors of the female genital tract and trace future therapeutic and research venues.
Colliding interfaces in old and new diffuse-interface approximations of Willmore-flow

This paper is concerned with diffuse-interface approximations of the Willmore flow. We first present numerical results of standard diffuse-interface models for colliding one dimensional interfaces. In such a scenario evolutions towards interfaces with corners can occur that do not necessarily describe the adequate sharp-interface dynamics. We therefore propose and investigate alternative diffuse-interface approximations that lead to a different and more regular behavior if interfaces collide. These dynamics are derived from approximate energies that converge to the $L^1$-lower-semicontinuous envelope of the Willmore energy, which is in general not true for the more standard Willmore approximation.
An Experiment on Ultra-resolution Video Transmission with Tiled Display Wall in Wide-Area Network

In order to realize high-realistic sensation tele-communication over wide-area network, we consider that non-verbal communication play an important role, and displaying the existence of participant by high-quality video streaming on large-scale screen system in each remote site is effective. However, the display specification of these systems such as commercial projector and wide-area monitor is low-resolution, and displaying of real video streaming with sufficient quality is difficult. Moreover, displaying video streaming with realistic high-resolution is serious, because there is a limit in the display resolution of video image captured by a single camera. We have constructed the tele-communication environment to display ultra resolution video streaming by multi-transmitting each video image which captured by four cameras with tiled display wall which is a technology to display various high-resolution contents by configuring the large-scale display with two or more LCD panels. In this paper, we have conducted an experiment on ultra-resolution video transmission between remote sites via wide-area network by using this tiled display wall environment in order to examine the feasibility of high-realistic sensation tele-communication, and have reported the experimental results.
Optimized Parallel Coding of Second-Order Stimulus Features by Heterogeneous Neural Populations

Efficient processing of sensory input is essential to ensure an organism's survival in its natural environment. Growing evidence suggests that sensory neurons can optimally encode natural stimuli by ensuring that their tuning opposes stimulus statistics, such that the resulting neuronal response contains equal power at all frequencies (i.e., is “white”). Such temporal decorrelation or whitening has been observed across modalities, but the effects of neural heterogeneities on determining tuning and thus responses to natural stimuli have not been investigated. Here, we investigate how heterogeneities in sensory pyramidal neurons organized in three parallel maps representing the body surface determine responses to second-order electrosensory stimulus features in the weakly electric fish Apteronotus leptorhynchus. While some sources of heterogeneities such as ON- and OFF-type responses to first-order did not affect responses to second-order electrosensory stimulus features, other sources of heterogeneity within and across the maps strongly determined responses. We found that these cells effectively performed a fractional differentiation operation on their input with exponents ranging from zero (no differentiation) to 0.4 (strong differentiation). Varying adaptation in a simple model explained these heterogeneities and predicted a strong correlation between fractional differentiation and adaptation. Using natural stimuli, we found that only a small fraction of neurons implemented temporal whitening. Rather, a large fraction of neurons did not perform any significant whitening and thus preserved natural input statistics in their responses. We propose that this information is needed to properly decode optimized information sent in parallel through temporally whitened responses based on context. SIGNIFICANCE STATEMENT We demonstrate that heterogeneities in the same sensory neuron type can either have no or significant influence on their responses to second-order stimulus features. While an ON- or OFF-type response to first-order stimulus attributes has no significant influence on responses to second-order stimulus features, we found that only a small fraction of sensory neurons optimally encoded natural stimuli through high-pass filtering, thereby implementing temporal whitening. Surprisingly, a large fraction of sensory neurons performed little if no filtering of stimuli, thereby preserving natural stimulus statistics. We hypothesize that this pathway is necessary to properly decode optimized information contained in temporally whitened responses based on context.
Breakdown of the brain’s functional network modularity with awareness

Significance How the brain begets conscious awareness has been one of the most fundamental and elusive problems in neuroscience, psychology, and philosophy. Correspondingly, this problem has spawned a remarkably large number of theories that differ by the proposed extent of cortical and subcortical changes associated with awareness, ranging from local to global changes in functional connectivity. Graph theoretical techniques, in combination with functional magnetic resonance imaging, provide a well-suited tool to adjudicate between these disparate theories by characterizing whole-brain patterns of communication. In this paper, we demonstrate large-scale differences in functional connections with awareness of a visual target, consistent with global models of awareness. Neurobiological theories of awareness propose divergent accounts of the spatial extent of brain changes that support conscious perception. Whereas focal theories posit mostly local regional changes, global theories propose that awareness emerges from the propagation of neural signals across a broad extent of sensory and association cortex. Here we tested the scalar extent of brain changes associated with awareness using graph theoretical analysis applied to functional connectivity data acquired at ultra-high field while subjects performed a simple masked target detection task. We found that awareness of a visual target is associated with a degradation of the modularity of the brain’s functional networks brought about by an increase in intermodular functional connectivity. These results provide compelling evidence that awareness is associated with truly global changes in the brain’s functional connectivity.
Identifying and classifying subjective claims

To understand the subjective documents, for example, public comments on the government's proposed regulation, opinion identification and classification is required. Rather than classifying documents or sentences into binary polarities as in much previous work, we identify the main claim or assertion of the writer and classify it into the predefined classes of opinion (attitude) over the topic. For the classification of the claims, we automatically build a list of multi-word subjective expressions by extending a small set of seed words, using automatically generated paraphrases from machine translation corpus. Our supervised machine learning method shows significant improvement over the baseline both in identification and classification of claims.
Dependence of Multidrug Resistance Protein-Mediated Cyclic Nucleotide Efflux on the Background Sodium Conductance

Anterior pituitary cells fire action potentials and release cyclic nucleotides both spontaneously and in response to agonist stimulation, but the relationship between electrical activity and cyclic nucleotide efflux has not been studied. In these cells, a tetrodotoxin-resistant background N+ conductance is critical for firing of action potentials, and multidrug resistance proteins (MRPs) MRP4 and MRP5 contribute to cyclic nucleotide efflux. Here, we show that abolition of the background Na+ conductance in rat pituitary cells by complete or partial replacement of extracellular Na+ with organic cations or sucrose induced a rapid and reversible hyperpolarization of cell membranes and inhibition of action potential firing, accompanied by a rapid inhibition of cyclic nucleotide efflux. Valinomycin-induced hyperpolarization of plasma membranes also inhibited cyclic nucleotide efflux, whereas depolarization of cell membranes induced by the inhibition of Ca2+ influx or stimulation of Na+ influx by gramicidin was accompanied by a facilitation of cyclic nucleotide efflux. In contrast, inhibition of cyclic nucleotide efflux by probenecid did not affect the background Na+ conductance. In human embryonic kidney 293 cells stably transfected with human MRP4 or MRP5, replacement of bath Na+ with organic cations also hyperpolarized the cell membranes and inhibited cyclic nucleotide efflux. In these cells, the Na+/H+ antiporter monensin did not affect the membrane potential and was practically ineffective in altering cyclic nucleotide efflux. In both pituitary and MRP4- and MRP5-expressing cells, 3-[[3-[2-(7-chloroquinolin-2-yl)vinyl]phenyl]-(2-dimethylcarbamoylethylsulfanyl)methylsulfanyl] propionic acid (MK571) inhibited cyclic nucleotide efflux. These results indicate that the MRP4/5-mediated cyclic nucleotide efflux can be rapidly modulated by membrane potential determined by the background Na+ conductance.
Influence of P300 latency jitter on event related potential-based brain–computer interface performance

Objective. Several ERP-based brain–computer interfaces (BCIs) that can be controlled even without eye movements (covert attention) have been recently proposed. However, when compared to similar systems based on overt attention, they displayed significantly lower accuracy. In the current interpretation, this is ascribed to the absence of the contribution of short-latency visual evoked potentials (VEPs) in the tasks performed in the covert attention modality. This study aims to investigate if this decrement (i) is fully explained by the lack of VEP contribution to the classification accuracy; (ii) correlates with lower temporal stability of the single-trial P300 potentials elicited in the covert attention modality. Approach. We evaluated the latency jitter of P300 evoked potentials in three BCI interfaces exploiting either overt or covert attention modalities in 20 healthy subjects. The effect of attention modality on the P300 jitter, and the relative contribution of VEPs and P300 jitter to the classification accuracy have been analyzed. Main results. The P300 jitter is higher when the BCI is controlled in covert attention. Classification accuracy negatively correlates with jitter. Even disregarding short-latency VEPs, overt-attention BCI yields better accuracy than covert. When the latency jitter is compensated offline, the difference between accuracies is not significant. Significance. The lower temporal stability of the P300 evoked potential generated during the tasks performed in covert attention modality should be regarded as the main contributing explanation of lower accuracy of covert-attention ERP-based BCIs.
Developing personalised e-courses: tailoring students' learning preferences to a model of self-regulated learning

The systematic design of personalised e-learning courses so as to place emphasis on preferred ways of studying and to motivate learners to manage their own learning process poses a major challenge. To meet this challenge, the design and implementation of the 'SR-INSPIREus-Learning Framework' applying aspects of self-regulated learning SRL theory for modelling learning strategies that match various learning preferences and exploit the adaptive functionalities of INSPIREus, is proposed. A preliminary quasi-experimental study with comparison groups in pre/post tests and experimental and control groups was conducted in order to examine aspects of SRL cognitive and affective domain and learners' performance. The findings provide evidence about the potential of the framework in increasing specific aspects of SRL and students' performance.
Language Modeling with Functional Head Constraint for Code Switching Speech Recognition

In this paper, we propose novel structured language modeling methods for code mixing speech recognition by incorporating a well-known syntactic constraint for switching code, namely the Functional Head Constraint (FHC). Code mixing data is not abundantly available for training language models. Our proposed methods successfully alleviate this core problem for code mixing speech recognition by using bilingual data to train a structured language model with syntactic constraint. Linguists and bilingual speakers found that code switch do not happen between the functional head and its complements. We propose to learn the code mixing language model from bilingual data with this constraint in a weighted finite state transducer (WFST) framework. The constrained code switch language model is obtained by first expanding the search network with a translation model, and then using parsing to restrict paths to those permissible under the constraint. We im
A Task Taxonomy for Network Evolution Analysis

Visualization has proven to be a useful tool for understanding network structures. Yet the dynamic nature of social media networks requires powerful visualization techniques that go beyond static network diagrams. To provide strong temporal network visualization tools, designers need to understand what tasks the users have to accomplish. This paper describes a taxonomy of temporal network visualization tasks. We identify the 1) entities, 2) properties, and 3) temporal features, which were extracted by surveying 53 existing temporal network visualization systems. By building and examining the task taxonomy, we report which tasks are well covered by existing systems and make suggestions for designing future visualization tools. The feedback from 12 network analysts helped refine the taxonomy.
Cations Affect the Rate of Gating Charge Recovery in Wild-type and W434F Shaker Channels through a Variety of Mechanisms

In this study we examine the effects of ionic conditions on the gating charge movement in the fast inactivation–removed wild-type Shaker channel and its W434F mutant. Our results show that various ionic conditions influence the rate at which gating charge returns during repolarization following a depolarizing pulse. These effects are realized through different mechanisms, which include the regulation of channel closing by occupying the cavity, the modulation of transitions into inactivated states, and effects on transitions between closed states via a direct interaction with the channel's gating charges. In generating these effects the cations act from the different binding sites within the pore. Ionic conditions, in which conducting wild-type channels close at different rates, do not significantly affect the rate of charge recovery upon repolarization. In these conditions, channel closing is fast enough not to be rate-limiting in the charge recovery process. In the permanently P-inactivated mutant channel, however, channel closing becomes the rate-limiting step, presumably due to weakened ion–ion interactions inside the pore and a slower intrinsic rate of gate closure. Thus, variations in closing rate induced by different ions are reflected as variations in the rate of charge recovery. In 115 mM internal Tris+ and external K+, Cs+, or Rb+, low inward permeation of these ions can be observed through the mutant channel. In these instances, channel closing becomes slower than in Tris+ O//Tris+ I solutions showing resemblance to the wild-type channel, where higher inward ionic fluxes also retard channel closing. Our data indicate that cations regulate the transition into the inactivated states from the external lock-in site and possibly the deep site. The direct action of barium on charge movement is probably exerted from the deep site, but this effect is not very significant for monovalent cations.
Feasible constrained nonlinear predictive control on power plant

Thermal power plant is required to ensure a fast load change without violating thermal constraints. While model predictive control has been widely used in power plant, incorporating of constraints is a major problem. Two alternative methods of exploiting the nonlinear predictive control are described. One is the input-output feedback linearization technique. The other is the neuro-fuzzy networks(NFNs). Steam-boiler generation control using the two nonlinear predictive methods show satisfactory results and improved performance compared with conventional predictive method. Comparing results considering both the integral absolute value and the relative optimization time needed for completing the simulation have also been addressed in detail.