Miracle-dz/UniFAR-FTUs huggingface dataset:
Translocation dynamics of sorting nexin 27 in activated T cells

Sorting nexin 27 (SNX27) belongs to the sorting nexin family of proteins, which participate in vesicular and protein trafficking. Similarly to all sorting nexin proteins, SNX27 has a functional PX domain that is important for endosome binding, but it is the only sorting nexin with a PDZ domain. We identified SNX27 as a partner of diacylglycerol kinase ζ (DGKζ), a negative regulator of T cell function that metabolises diacylglycerol to yield phosphatidic acid. SNX27 interacts with the DGKζ PDZ-binding motif in early/recycling endosomes in resting T cells; however, the dynamics and mechanisms underlying SNX27 subcellular localisation during T cell activation are unknown. We demonstrate that in T cells that encounter pulsed antigen-presenting cells, SNX27 in transit on early/recycling endosomes polarise to the immunological synapse. A fraction of SNX27 accumulates at the mature immunological synapse in a process that is dependent on vesicular trafficking, binding of the PX domain to phosphatidylinositol 3-phosphate and the presence of the PDZ region. Downmodulation of expression of either SNX27 or DGKζ results in enhanced basal and antigen-triggered ERK phosphorylation. These results identify SNX27 as a PDZ-containing component of the T cell immunological synapse, and demonstrate a role for this protein in the regulation of the Ras–ERK pathway, suggesting a functional relationship between SNX27 and DGKζ.
A Novel Drug Delivery Device Based on the Principle of Ultrasonic Cavitation

The function and the progress of site-specific delivery capsule system is presented. The model of a novel drug delivery device of gastrointestinal microcapsule in a gas pressure driving way is proposed, in which a new triggered control technique based on the principle of ultrasonic cavitation is used for inducing chemical reaction that brings gas pressure to drive gastroenteric drug delivery. The microcapsule can be used as a human drug absorption experiment tool. Index Terms — Drug delivery; capsule; ultrasonic cavitation; chemical reaction
A First Step in Combining Cognitive Event Features and Natural Language Representations to Predict Emotions

We explore the representational space of emotions by combining methods from different academic fields. Cognitive science has proposed appraisal theory as a view on human emotion with previous research showing how human-rated abstract event features can predict fine-grained emotions and capture the similarity space of neural patterns in mentalizing brain regions. At the same time, natural language processing (NLP) has demonstrated how transfer and multitask learning can be used to cope with scarcity of annotated data for text modeling. The contribution of this work is to show that appraisal theory can be combined with NLP for mutual benefit. First, fine-grained emotion prediction can be improved to human-level performance by using NLP representations in addition to appraisal features. Second, using the appraisal features as auxiliary targets during training can improve predictions even when only text is available as input. Third, we obtain a representation with a similarity matrix that better correlates with the neural activity across regions. Best results are achieved when the model is trained to simultaneously predict appraisals, emotions and emojis using a shared representation. While these results are preliminary, the integration of cognitive neuroscience and NLP techniques opens up an interesting direction for future research.
On Buffering at the Relay Node in LTE-Advanced

In this paper, we study the performance of a LTE-A relay-aided system with limited buffer size at the relay node. In presence of a link quality mismatch between the backhaul and access links of the relay node, we analyze the impact of the buffer size on the occurrence of undesirable events such as buffer overflows or underflows. Based on simulations, we find out that the size of the buffer at the RN can positively influence the throughput performance of the served users. Finally, we observe that in different relaying conditions, the buffer size setting plays an important role on the overall system performance, especially in terms of underflow and overflow occurrence.
Motion correction and the use of motion covariates in multiple‐subject fMRI analysis

The impact of using motion estimates as covariates of no interest was examined in general linear modeling (GLM) of both block design and rapid event‐related functional magnetic resonance imaging (fMRI) data. The purpose of motion correction is to identify and eliminate artifacts caused by task‐correlated motion while maximizing sensitivity to true activations. To optimize this process, a combination of motion correction approaches was applied to data from 33 subjects performing both a block‐design and an event‐related fMRI experiment, including analysis: (1) without motion correction; (2) with motion correction alone; (3) with motion‐corrected data and motion covariates included in the GLM; and (4) with non–motion‐corrected data and motion covariates included in the GLM. Inclusion of covariates was found to be generally useful for increasing the sensitivity of GLM results in the analysis of event‐related data. When motion parameters were included in the GLM for event‐related data, it made little difference if motion correction was actually applied to the data. For the block design, inclusion of motion covariates had a deleterious impact on GLM sensitivity when even moderate correlation existed between motion and the experimental design. Based on these results, we present a general strategy for block designs, event‐related designs, and hybrid designs to identify and eliminate probable motion artifacts while maximizing sensitivity to true activations. Hum. Brain Mapp, 2006. © 2006 Wiley‐Liss, Inc.
dSVM: Energy-efficient distributed Scratchpad Video Memory Architecture for the next-generation High Efficiency Video Coding

An energy-efficient distributed Scratchpad Video Memory Architecture (dSVM) for the next-generation parallel High Efficiency Video Coding is presented. Our dSVM combines private and overlapping (shared) Scratchpad Memories (SPMs) to support data reuse within and across different cores concurrently executing multiple parallel HEVC threads. We developed a statistical method to size and design the organization of the SPMs along with a supporting memory reading policy for energy efficiency. The key is to leverage the HEVC and video content knowledge. Furthermore, we integrate an adaptive power management policy for SPMs to manage the power states of different memory parts at run time depending upon the varying video content properties. Our experimental results illustrate that our dSVM architecture reduces the overall memory energy consumption by up to 51%-61% compared to parallelized state-of-the-art solutions [11]. The dSVM external memory energy savings increase with an increasing number of parallel HEVC threads and size of search window. Moreover, our SPM power management reacts to the current video properties and achieves up to 54% on-chip leakage energy savings.
Muscle activation during exercises to improve trunk stability in men with low back pain.

OBJECTIVES To evaluate the relative activation amplitudes from 3 abdominal and 2 trunk extensor muscle sites of persons with low back pain (LBP) performing the pelvic-tilt, the abdominal-hollowing, and level 1 of the trunk stability test (TST) exercises and to compare the activation amplitudes among muscle sites and exercises. DESIGN A prospective, comparative, repeated-measures design. SETTING Motion analysis research laboratory. PARTICIPANTS Fourteen men with LBP (mean duration, 8y; mean age +/- standard deviation, 39+/-5y). INTERVENTIONS Subjects performed 3 exercises in random order while surface electromyograms were recorded from 5 muscle sites: lower and upper rectus abdominus, external oblique, erector spinae, and multifidus. The exercises were divided into 2 phases: a movement phase and a stabilization phase. The root-mean-square (RMS) electromyographic amplitude for each phase was calculated and normalized to the highest RMS amplitude from a series of 4 exercises, which attempted to elicit maximal voluntary isometric contractions (MVICs) for each muscle. A 2-factor, repeated-measures analysis of variance (ANOVA) tested the muscle by exercise interaction and the 2 main effects for each phase separately. MAIN OUTCOME MEASURES Normalized RMS amplitude was the main dependent variable. The ensemble-average profiles for each muscle were calculated to examine the phasing of activation throughout the exercises. RESULTS The ANOVA revealed a statistically significant muscle-by-exercise interaction (P<.05) for both phases, which showed that the 3 exercises; recruited the 5 muscle sites using different patterns of relative amplitudes. The external oblique muscle site was activated to higher amplitudes than the other 4 muscle sites for all 3 exercises; the highest normalized RMS activity occurred at the external oblique during the pelvic tilt (32% MVIC). The phasic patterns among the 5 muscle sites were not consistent for the TST but were consistent among the 5 sites for the other 2 exercises. CONCLUSIONS None of the exercises recruited the abdominal muscles to intensities deemed adequate for strengthening. The TST challenges the coordination of muscle activity during the leg-loading task (stabilization phase) as evidenced by changes in amplitudes over the total exercise time for the external oblique site, but not the other 4 sites. All 3 exercises could be used as initial exercises in a dynamic stability progression when low-recruitment amplitudes of specific muscles were the objective but not for strengthening.
MArCo: Building an Artificial Conflict Mediator to Support Group Planning Interactions

The emphasis on building co-operative/collaborative environments has brought out the matter of group interactions. This, in its turn, has highlighted the issue of conflicts, inherent to group problem solving. If well employed, conflicts can act as triggers of cognitive changes, and thus help to refine the group's solution to the task. In this paper, we present a computational framework for detecting and mediating Meta-Cognitive conflicts. The theoretical framework presented here enables a computational system to analyse the ongoing interaction, to detect and mediate conflicts. In order to do so, we consider our model of strategic changes, a model of the group, and the history of the interaction. The objective of the mediation is to suggest courses of action that provoke articulation and reflection, and thus lead to more refined solutions. In order to diagnose which changes are happening to the group plan we have built a model of strategic operations, which describes what types of changes happen to a plan as well as how changes to one component of the strategy (beliefs, intentions, ordering relations, context beliefs and goals) impact the other ones. MArCo, our prototype embedding the artificial conflict mediator, shows how our conceptual framework has been put to practical use.
A Comparison of Objective Functions in Network Community Detection

Community detection, as an important unsupervised learning problem in social network analysis, has attracted great interests in various research areas. Many objective functions for community detection that can capture the intuition of communities have been introduced from different research fields. Based on the classical single objective optimization framework, this paper compares a variety of these objective functions and explores the characteristics of communities they can identify. Experiments show most objective functions have the resolution limit and their communities structure have many different characteristics.
Expression of Cyclooxygenase-2, 12-Lipoxygenase, and Inducible Nitric Oxide Synthase in Head and Neck Squamous Cell Carcinoma

AimThe objective of this study was to investigate whether cyclooxygenase-2 (COX-2), 12-lipoxygenase (12-LOX), and inducible nitric oxide synthase (iNOS) have a role in carcinogenesis of head and neck squamous cell carcinoma (HNSCC). Materials and MethodsTwenty-two patients with HNSCC were included in the study. Cancer tissues and adjacent normal mucosa were obtained from each patient. Real-time PCR was used to assess the expression of COX-2, 12-LOX, and iNOS. ResultsCOX-2 and 12-LOX mRNA expressions are significantly increased in HNSCC compared with adjacent normal mucosa. Expression of iNOS was not significantly elevated in overall head and neck cancer tissues compared with normal mucosa. However, iNOS expression was found to be significantly elevated in patients with laryngeal cancer. ConclusionThese data suggest that COX-2 and 12-LOX may play a role in carcinogenesis of head and neck cancer. iNOS as well as COX-2 and 12-LOX may play a role in carcinogenesis of laryngeal cancer.
Quality of offering on the world wide web

The definition of quality in a ‘life’ environment, such as that of the World Wide Web has proven to have many, often conflicting interpretations. Factors such as the point of view, the expertise and type of usage of the critic can influence dramatically such a definition and its results. Thus, the key point is to distance oneself from single perspectives and obtain a complete picture of the system as a single entity working towards a specific goal. This paper is an attempt at creating a general model of quality procedures. It will concentrate mainly in customer service, system viability and quality of offering evaluation. Some of the material mentioned is based on adapted classical models that can be used equally to apply and observe standards of offerings in the wider WEB community. Copyright © 2002 John Wiley & Sons, Ltd.
To divide and conquer search ranking by learning query difficulty

Learning to rank plays an important role in information retrieval. In most of the existing solutions for learning to rank, all the queries with their returned search results are learnt and ranked with a single model. In this paper, we demonstrate that it is highly beneficial to divide queries into multiple groups and conquer search ranking based on query difficulty. To this end, we propose a method which first characterizes a query using a variety of features extracted from user search behavior, such as the click entropy, the query reformulation probability. Next, a classification model is built on these extracted features to assign a score to represent how difficult a query is. Based on this score, our method automatically divides queries into groups, and trains a specific ranking model for each group to conquer search ranking. Experimental results on RankSVM and RankNet with a large-scale evaluation dataset show that the proposed method can achieve significant improvement in the task of web search ranking.
Dual FRET assay for detecting receptor protein interaction with DNA

We present here a new assay that is based on the idea of the molecular beacon. This assay makes it possible to investigate two proteins interacting with DNA at two binding sites that are close to each other. The effectiveness of the test depends on the exclusive binding of three DNA fragments in the presence of two proteins, and the monitoring of the process depends upon observing the quenching of two independent fluorescence donors. As a model we used the components of the heterodimeric ecdysteroid receptor proteins ultraspiracle (Usp) and ecdysone receptor (EcR) from Drosophila melanogaster and a response element from the promoter of the hsp27 gene. The response element consists of two binding sites (half-sites) for the DNA binding domains (DBDs). We have shown that protein–protein interactions mediate cooperative binding of the ecdysteroid receptor DBDs to a hsp27pal response element. The analysis of the microscopic dissociation constants obtained with the DMB led to the conclusion that there was increased affinity of UspDBD to the 5′ half-site in the presence of EcRDBD when the 3′ half-site was occupied, and increased affinity of EcRDBD to the 3′ half-site when the 5′ half-site was occupied.
A NEW METHOD FOR BUILDING EXTRACTION IN URBAN AREAS FROM HIGH-RESOLUTION LIDAR DATA

In this paper, a new method for the automated generation of 3D building models from directly observed point clouds generated by LIDAR sensors is presented. By a hierarchic application of robust interpolation using a skew error distribution function, the LIDAR points being on the terrain are separated from points on buildings and other object classes, and a digital terrain model (DTM) can be computed. Points on buildings have to be separated from other points classified as off-terrain points, which is accomplished by an analysis of the height differences of a digital surface model passing through the original LIDAR points and a digital terrain model. Thus, a building mask is derived, and polyhedral building models are created in these candidate regions in a bottom-up procedure by applying curvature-based segmentation techniques. Intermediate results will be presented for a test site located in the City of Vienna. * Corresponding author.
A Self-Stabilizing Distributed Approximation Algorithm for the Minimum Connected Dominating Set

Self-stabilization is a theoretical framework of non-masking fault-tolerant distributed algorithms. A self-stabilizing system tolerates any kind and any finite number of transient faults, such as message loss, memory corruption, and topology change. Because such transient faults occur so frequently in mobile ad hoc networks, distributed algorithms on them should tolerate such events. In this paper, we propose a self-stabilizing distributed approximation algorithm for the minimum connected dominating set, which can be used, for example, as a virtual backbone or routing in mobile ad hoc networks. The size of the solution by our algorithm is at most 8 |Dopt | + 1, where Dopt is a minimum connected dominating set. The time complexity is O(n2) steps.
Analysis of Network Lifetime in Cluster-Based Sensor Networks

Convergecast, which is frequently used in wireless sensor network applications, causes what is commonly called the {energy hole problem}. Aggregating data using spatial correlation in cluster-based networks is one way of solving this problem. In this letter, we derive the upper bound on the network lifetime in cluster-based sensor networks. Then, we investigate the effects of the number of clusters and spatial correlation on the network lifetime bound.
IMAGING A NANOSTRUCTURE BY THE LYAPUNOV EXPONENT COMPUTATION

A model of the AFM (atomic force microscope) with certain tip-nanostructure interaction, cantilever elasticity and damping of its oscillations is proposed. Stable and unstable motion of the AFM tip interacting with the graphene sheet is investigated by the Lyapunov exponent computation. In our approximation, a hundred Si atoms (top of the AFM tip) interact with C atoms of the nanostructure. Тhis interaction is described by Lennard-Jones potential, and the distance between the top and the center of the cantilever mass is a constant. Complex influence of the initial tip-nanostructure distance and nanostructure size on stability has been examined. We discuss a possible new mode of the AFM operation based on the Lyapunov exponent computation. Maxima and minima of the Lyapunov exponent show where certain parts of the elementary cells are placed.
Simulation of unsteady flow: dynamic stall on a pitching wing

La entrada en perdida dinamica se ha estudiado utilizando CFD para el caso de un perfil NACA0012 3D haciendo un movimiento de cabeceo, a un numero de Reynolds moderado. Los resultados se compararan con resultados experimentales. Utilizando el metodo "Transition SST" para un Reynolds de 1.35e5, con un movimiento entre -5o y 25o a una frecuencia reducida de 0.1. Se ha estudiado el coeficiente de lift y se ha comparado con los datos experimentales. Resultados anteriores en 2D funcionan bien en la subida del ala pero fallan en la bajada. Se ha observado que durante la subida un vortex se forma al borde de ataque, que interactua con el vortex de la cola y al inicio de la bajada se desprende. Para confirmar que el flujo en la bajada es 3D y es la causa del mal comportamiento en las simulaciones 2D, una simulacion 3D se ha llevado a cabo imitando un procedimiento experimental.
Hierarchical Heuristic Search Using a Gaussian Mixture Model for UAV Coverage Planning

During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.
Bursting response to current‐evoked depolarization in rat ca1 pyramidal neurons is correlated with lucifer yellow dye coupling but not with the presence of calbindin‐D28k

Calbindin‐D28k (CaBP) immunohistochemistry has been combined with electrophysiological recording and Lucifer Yellow (LY) Cell identification in the CA1 region of the rat hippocampal formation. CaBP is shown to be contained within a distinct sub‐population of CA1 pyramidal cells which is equivalent to the superficial layer described by Lorente de Nó (1934). The neurogenesis of these CaBP‐Positive neurons occurs 1–2 days later than the CaBP‐negative neurons in the deep pyramidal cell layer, as shown by 3H‐thymidine autoradiography. No correlation could be found between the presence or absence of CaBP and the type of electrophysiological response to current‐evoked depolarizing pulses. The latter could be separated into bursting or non‐bursting types and the bursting‐type response was nearly always found to be associated with the presence of LY dye coupling. Furthermore, when dye coupling involved three neurons, a characteristic pattern was observed which may represent the coupling of phenotypically identical neurons into distinct functional units within the CA1 pyramidal cell layer. In this particular casse the three neurons were all likely to be CaBP‐positive.
MDCT of congenital coronary artery fistulas.

OBJECTIVE The purpose of this article is to describe the evaluation of congenital coronary artery fistulas (CAFs) with MDCT angiography with ECG gating (MDCTA), including the clinical manifestations, scanning techniques, differential diagnosis, and other imaging methods that may be used. CONCLUSION Congenital CAFs are rare coronary artery anomalies of termination. MDCTA is a first-line modality for pretreatment planning, and imaging findings should be recognized because CAFs may be detected incidentally.