Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying and Characterizing Binding Sites and Assessing Druggability

Identification and characterization of binding sites is key in the process of structure-based drug design. In some cases there may not be any information about the binding site for a target of interest. In other cases, a putative binding site has been identified by computational or experimental means, but the druggability of the target is not known. Even when a site for a given target is known, it may be desirable to find additional sites whose targeting could produce a desired biological response. A new program, called SiteMap, is presented for identifying and analyzing binding sites and for predicting target druggability. In a large-scale validation, SiteMap correctly identifies the known binding site as the top-ranked site in 86% of the cases, with best results (>98%) coming for sites that bind ligands with subnanomolar affinity. In addition, a modified version of the score employed for binding-site identification allows SiteMap to accurately classify the druggability of proteins as measured by their ability to bind passively absorbed small molecules tightly. In characterizing binding sites, SiteMap provides quantitative and graphical information that can help guide efforts to critically assess virtual hits in a lead-discovery application or to modify ligand structure to enhance potency or improve physical properties in a lead-optimization context.
Exercise Plus Cognitive Performance Over and Above Exercise Alone in Subjects with Mild Cognitive Impairment.

BACKGROUND Epidemiological studies highlight the relevance of regular exercise interventions to enhance or maintain neurocognitive function in subjects with cognitive impairments. OBJECTIVES The aim of this study was to ascertain the effect of aerobic exercise associated with cognitive enrichment on cognitive performance in subjects with mild cognitive impairment (MCI). METHOD Eight participants with MCI (72 ± 2 years) were enrolled in a 9-month study that consisted of two 3-months experimental interventions separated by a training cessation period of 3 months. The interventions included either aerobic exercise alone or aerobic exercise combined with cognitive enrichment. The exercise program involved two 20-min cycling exercise bouts per week at an intensity corresponding to 60% of the heart rate reserve. Cognitive performance was assessed using a task of single reaction time (SRT) and an inhibition task (Go-no-Go) before, immediately after, and 1 month after each intervention. RESULTS The exercise intervention improved the speed of responses during the Go-no-Go task without any increase in errors. This improvement was enhanced by cognitive enrichment (6 ± 1% ; p > 0.05), when compared with exercise alone (4 ± 0.5% ,). Following exercise cessation, this positive effect disappeared. No effect was observed on SRT performance. CONCLUSION Regular aerobic exercise improved cognitive performance in MCI subjects and the addition of cognitive tasks during exercise potentiated this effect. However, the influence of aerobic exercise on cognitive performance did not persist after cessation of training. Studies involving a larger number of subjects are necessary to confirm these results.
Developing CIRCA-BC and Exploring the Role of the Computer as a Third Participant in Conversation

The Computer Interactive Reminiscence Conversation Aid (CIRCA) is a software program using touch screen technology and digital materials from public archives to support conversation between people with dementia and their carers. In this 2-phase study, we first worked with seniors’ focus groups to identify and select relevant content for a regional adaptation of CIRCA (British Columbia version of CIRCA [CIRCA-BC]). We then pilot tested CIRCA-BC with 3 participants having dementia and a conversation partner, analyzing their interactions to explore how they drew on program content and format to shape their conversations together. Findings provide insight into, first, how participants’ shared and distinct social histories influence reminiscence-based conversations and, second, how the computer can be viewed as a third “participant” in the interaction. These findings offer guidelines for ongoing adaptation and application of the CIRCA program in addition to contributing further evidence regarding the role of technology in facilitating meaningful interaction between people with dementia and their carers.
Carbon-Based Composites for Supercapacitor

Supercapacitor is an emerging technology that promises to play an advance role in new generation electronic devices and systems. Carbon (activated carbon, graphene and carbon nanotube) have attracted tremendous attention for their potential applications in supercapacitor technologies due to their excellent mechanical strength, good electrical conductivity, high electron mobilities, excellent chemical stability in acidic and basic medium, good thermal stability in wide range of temperature, various morphological structures, and large specific surface area. This chapter aims to assess the current status of carbon nanomaterials and their composites for supercapacitor application by discussing the literature in this field and presenting a perspective for future research in supercapacitor technologies.
Distributed Adaptive Node-Specific Signal Estimation in Fully Connected Sensor Networks—Part I: Sequential Node Updating

We introduce a distributed adaptive algorithm for linear minimum mean squared error (MMSE) estimation of node-specific signals in a fully connected broadcasting sensor network where the nodes collect multichannel sensor signal observations. We assume that the node-specific signals to be estimated share a common latent signal subspace with a dimension that is small compared to the number of available sensor channels at each node. In this case, the algorithm can significantly reduce the required communication bandwidth and still provide the same optimal linear MMSE estimators as the centralized case. Furthermore, the computational load at each node is smaller than in a centralized architecture in which all computations are performed in a single fusion center. We consider the case where nodes update their parameters in a sequential round robin fashion. Numerical simulations support the theoretical results. Because of its adaptive nature, the algorithm is suited for real-time signal estimation in dynamic environments, such as speech enhancement with acoustic sensor networks.
Experimental Study of the Meltblowing Process

High-speed digital imaging techniques and web measurements were used to investigate the meltblowing (MB) process. We evaluated fiber diameter, fiber orientation, fiber entanglement, fiber velocity and fiber acceleration between the die and collector. Three processing variables were studied: primary air pressure, die-to-collector distance and collector surface speed. Although results of this investigation are somewhat preliminary, they provide fundamental information about the MB process and increase our understanding of it. Introduction Meltblowing (MB) is a fast, chaotic and complicated process. These features make it difficult to study the MB process theoretically as well as experimentally and most researchers have simply studied the effects of resin and process variables on web structure or web properties. Some researchers, however, have reported on-line measurements during MB [1–9]. Bansal and Shambaugh measured fiber temperature during single-hole MB using an infrared camera [1]. Wu and Shambaugh measured fiber velocity using laser Doppler velocimetry during single-hole MB [2]. Shambaugh and others reported experimental measurements of fiber motion and fiber diameter using a single-hole die [1–7]. Multiple-exposed photographs using conventional film were produced with a strobe light in a dark room to study fiber motion and single-exposed photographs were used to estimate fiber diameter. The exposure duration of the strobe light (50 μs), however, was not short enough to eliminate image blur and obtain sharp images so the primary air velocity used during MB was low (17–55 m/s). Milligan and Utsman used a similar film-based photographic technique to investigate MB using a 30-hole die [8]. Bresee and Yan used a video imaging technique to investigate the dynamics of web formation at the collector of a 600-hole MB line [9]. Measurements of the dynamics between the die and collector of a high-speed commercial-like MB process would be expected to be especially desirable for understanding MB. To directly observe dynamic motions during this fast process, it is necessary to use a short exposure time to freeze motion in each image and a high framing rate to resolve fast fiber motions. We used a high-speed digital camera from Vision Research Inc. to acquire images as rapidly as 1,000 frames/s. The camera produced image frames with a spatial resolution as great as 512×512 pixels and 8-bit gray level resolution (256 gray levels). Electronic shuttering of the camera provided exposure times as short as 50 μs/frame. To obtain exposure times shorter than 50 μs or to obtain multiple-exposed images, a high-speed pulsed laser from Oxford Lasers, Inc. was used for illumination. The laser produced 100 watt peak power at 805 nm and pulse durations as short as 1 μs were synchronized with the camera.
The enigma of glucose and cardiovascular disease

Vivian A Fonseca Vasudevan A Raghavan Cyrus Desouza Strong epidemiological evidence indicates that diabetes is a major risk factor for cardiovascular disease (CVD), and despite advances in the treatment of CVD, outcomes in patients with diabetes mellitus (DM) remain suboptimal. In the European prospective investigation into cancer in Norfolk (EPIC–NORFOLK) study,1 the risk of CVD and total mortality associated with haemoglobin A1c (HbA1c) concentrations increased continuously through the sample distribution. An increase in HbA1c of 1 percentage point was associated with a relative risk of death from any cause of 1.24 (95% CI 1.14 to 1.34; p<0.001) in men and with a relative risk of 1.28 (95% CI 1.06 to 1.32; p<0.001) in women. Several meta-analyses2–4 arrived at similar conclusions, setting the stage for the conduct of randomised controlled trials exploring the effect of glycaemic control on CVD outcomes. Several plausible mechanisms underlie the relationship of DM and CVD, all of which lend themselves to the development of specific treatment targets, although the lowering of glucose per se appears to be an appropriate and potentially beneficial intervention. Obesity is characterised by an expanding adipose tissue mass and the development of an inflammatory state caused by the increased secretion of cytokines and adipokines from adipose tissue.5 The hyperglycaemic state causes oxidative stress and increased glycation of proteins in the body, leading to the formation of advanced glycation end products.6 These in turn contribute to exacerbation of the proinflammatory state, activation of macrophages and vascular smooth muscle cells, low-density lipoprotein oxidation and accelerated atherogenesis. It thus seems logical that a reduction in blood glucose to near normal would result in a reduction in CVD events. Although clinical trials have shown that intensive glucose control reduces the risk of microvascular complications among patients with type 2 DM, its effect …
Bandwidth selection for kernel estimation in mixed multi-dimensional spaces

Kernel estimation techniques, such as mean shift, suffer from one major drawback: the kernel bandwidth selection. The bandwidth can be fixed for all the data set or can vary at each points. Automatic bandwidth selection becomes a real challenge in case of multidimensional heterogeneous features. This paper presents a solution to this problem. It is an extension of \cite{Comaniciu03a} which was based on the fundamental property of normal distributions regarding the bias of the normalized density gradient. The selection is done iteratively for each type of features, by looking for the stability of local bandwidth estimates across a predefined range of bandwidths. A pseudo balloon mean shift filtering and partitioning are introduced. The validity of the method is demonstrated in the context of color image segmentation based on a 5-dimensional space.
Reading motor intention through mental imagery

Motor imagery is defined as a dynamic state during which the representation of a given motor act is internally rehearsed without overt motor output. Some evidence in experimental psychology has suggested that imagery ability is crucial for the correct understanding of social intention. The present study was conducted first to confirm that the nature of the motor intention leads to early modulations of movement kinematics. Secondly, we tested whether humans use imagery to read an agent’s intention when observing the very first element of a complex action sequence. Results revealed early variations in movement kinematics between three different social actions and further showed that human agents can use these early deviants to anticipate above chance level the end-result before seeing the second half of the sequence. Response times in the observation task were similar in duration to those measured in the true production task, suggesting the use of motor imagery for trial categorization. Nevertheless, in a third study, the use of an artificial (neural network) classifier demonstrated that classification within the first 500 ms is possible without cognitive imagery processing. Hence, our results suggest that low-level motor indices afford intention reading without need for motor imagery but that human agents may use imaging beyond simulation to create an embodied sense of interactivity.
Peer Assessment for Action Learning of Data Structures and Algorithms

This paper describes an experience with use of peer assessment in tutorials as a tool to promote deep learning from early stages of a course on Data Structures and Algorithms. The goal was to improve the utility of tutorials in encouraging more efficient learning habits. Since assessment forms a key part of the actual curriculum, tutorial exercises were for credit, but the emphasis was on formative assessment. The novelty in this approach is that peer assessment has not been extensively studied in Computer Science Education for content of the kind covered in this course. Evaluation is limited by the fact that other details of the course were changed. Two surveys were conducted, one soon after the first assignment, the other soon after the second assignment. Of various aspects of the course surveyed, the tutorial quizzes were the least popular, but improved in popularity between the two surveys. The overall effect based on general observation of the class appeared to be positive. Results were closer to a normal distribution than for the previous 2 years. Performance in the first assignment, which required understanding of how the theory is applied in a practical situation, suggested that deep learning had taken place.
Reducibility of sequential test generation to combinational test generation for several delay fault models

This paper presents a new structure, called discontinuous reconvergence structure (DR-structure), of sequential circuits with easy testability for delay faults. We show that the delay fault test generation problem for sequential circuits with DR-structure can be reduced to that for their time-expansion models, which are combinational circuits. Based on the reducibility, we propose a test generation method for delay faults in sequential circuits with DR-structure. This method can be applied to several delay fault models. By some experiments, we show that the proposed method is effective in the hardware overhead, the test generation time and the fault efficiency.
Some thoughts on similarity measures

Intrinsic versus extrinsic measures. The most c o m m o n l y used similarity measures are probably the cosine measure and a var ie ty of measures based on a dis tance calculat ion. Put t ing aside ques t ions o f or thogonal i ty (which may be important), it seems that these two kinds of measures have very different characteristics. The cosine measure is an "extrinsic" measure: it measures the similarity of documents by the angle between their vectors. But the vectors are drawn from the origin, <0,0,. 0> of the document space. That is, the measure makes use of an external reference point, and when that point is changed, the measure o f d o c u m e n t similarity changes, even though the documents in question have not.
Efficiency Enhancement in Plasmonic Dye-Sensitized Solar Cell Employing High Performance TiO2 Photoanode Doped with Silver Nanoparticles

High performance TiO2 photoanodes undoped and doped with silver nanoparticels of size about 15 nm were fabricated. Employing these electrodes dye-sensitized solar cells (DSSCs) were fabricated using N719 dye as sensitizer and iodide-triodide as redox couple. Current-voltage measurements were performed under the illumination of 100 mW cm-2 (AM 1.5). The electrical parameters of the fabricated cells were extracted from the current-voltage data that include open-circuit voltage, short-circuit current, shunt resistance, series resistance, fill-factor, ideality factor and solar energy-to-electricity conversion efficiency. The comparison of parameters revealed improvement in both the photovoltaic and electrical parameters of the plasmonic cell. The conversion efficiency measured for the reference cell without Ag NPs in TiO2 was 7.43 %, whereas the efficiency of plasmonic device with TiO2:Ag NPs was 9.26 %, resulting an overall efficiency improvement of 23% with Ag NPs. The increased performance of the plasmonic DSSC can be assigned to the improvement of its photovoltaic and electrical parameters. The improved short-circuit photocurrent density appears to be boosted due the enhanced light harvesting capability of the photoanode caused by the localized surface plasmon resonance effect induced in Ag nanoparticles. While, the rise in Voc can be credited to the upward shift of Fermi level of TiO2 due to the dopping of Ag nanoparticles in TiO2 network.
Link sleeping optimization for green virtual network infrastructures

Power consumption in Information and Communication Technology (ICT) is 10% of total energy consumed in industrial countries. According to the latest measurements, this amount is increasing rapidly in recent years. In the literature, a variety of new schemes have been proposed to save energy in operational communication networks. In this paper, we propose a novel optimization algorithm for network virtualization environment, by sleeping reconfiguration on the maximum number of physical links during off-peak hours, while still guaranteeing the connectivity and off-peak bandwidth availability for supporting parallel virtual networks over the top. Simulation results based on the GÉANT network topology show our novel algorithm is able to put notable number of physical links to sleep during off-peak hours while still satisfying the bandwidth demands requested by ongoing traffic sessions in the virtual networks.
Plasticity in Value Systems and its Role in Adaptive Behavior

Adaptive behavior requires the sensing of salient behavioral consequences which can act to modulate changes in neural connections linking sensory and motor structures. In previous work, we proposed that salient sensory events trigger neuronal value systems capable of modulating synaptic plasticity. Here, we investigate the capacity of value systems to modulate their own responses in the context of various conditioning tasks. To this end, we implement a modifiable value system incorporating anatomical and physiological properties within Darwin V, a neuronal model embedded in a mobile real world device. While exploring an environment containing stimulus objects, Darwin V's visual maps develop object-related neuronal responses. Phasic responses of a value system initially triggered only by object-"taste" (innate value) modulate changes in connections between visual and motor neurons, thus linking specific visual responses to appropriate motor outputs. Over time, Darwin V is able behaviorally to discriminate between "striped" objects with positive value (appetitive behavior) and objects with "blobs" with negative value (aversive behavior) based on vision alone. In parallel with modification of visuo-motor connections, value-dependent modification also occurs in connections from visual sensory maps to the value system itself. As a result, visual activity patterns become able directly to trigger value signals (acquired value). If acquired value is disabled, transfer of the value signal to stimuli preceding innately salient events does not occur, and behavioral responses due to aversive conditioning are subject to rapid extinction. If an auditory signal reliably precedes the visual appearance of an aversive object, Darwin V could be conditioned first to reject the object based on vision (primary conditioning), and subsequently based on sound alone (secondary conditioning). We compare the functional characteristics of value-dependent learning to formal notions of reinforcement learning. We suggest that plasticity in sensory afferents to value systems may provide a neurobiological basis for mediating the changing effects of saliency on adaptive behavioral responses.
Incidence of Sickle Cell Trait — United States, 2010

Persons with sickle cell trait (SCT) are heterozygous carriers of an abnormal ß-globin gene that results in the production of an abnormal hemoglobin, Hb S, which can distort red blood cells (http://www.cdc.gov/ncbddd/sicklecell/facts.html). All state newborn screening (NBS) programs have provided universal sickle cell disease (SCD) screening for newborns since 2006. Screening for SCD detects both SCD and SCT. To obtain up-to-date measures of the occurrence of SCT among newborns by race/ethnicity and state of birth, data collected by state NBS programs in 2010 were examined. In 2010, the incidence of SCT in participating states was 15.5 per 1,000 newborns overall; 73.1 among black newborns and 6.9 among Hispanic newborns. Incidence by state ranged from 0.8 per 1,000 screened newborns in Montana to 34.1 per 1,000 in Mississippi. Although the occurrence of SCT varies greatly from state-to-state and among different races and ethnicities, every state and racial/ethnic population includes persons living with the condition. The period immediately following NBS is ideal for primary care providers and genetic counselors to begin educating the families of identified persons with SCT about potential health complications and reproductive considerations.