Miracle-dz/UniFAR-FTUs huggingface dataset:
The stoichiometry of scaffold complexes in living neurons – DLC2 functions as a dimerization engine for GKAP

ABSTRACT Quantitative spatio-temporal characterization of protein interactions in living cells remains a major challenge facing modern biology. We have investigated in living neurons the spatial dependence of the stoichiometry of interactions between two core proteins of the N-methyl-D-aspartate (NMDA)-receptor-associated scaffolding complex, GKAP (also known as DLGAP1) and DLC2 (also known as DYNLL2), using a novel variation of fluorescence fluctuation microscopy called two-photon scanning number and brightness (sN&B). We found that dimerization of DLC2 was required for its interaction with GKAP, which, in turn, potentiated GKAP self-association. In the dendritic shaft, the DLC2–GKAP hetero-oligomeric complexes were composed mainly of two DLC2 and two GKAP monomers, whereas, in spines, the hetero-complexes were much larger, with an average of ∼16 DLC2 and ∼13 GKAP monomers. Disruption of the GKAP–DLC2 interaction strongly destabilized the oligomers, decreasing the spine-preferential localization of GKAP and inhibiting NMDA receptor activity. Hence, DLC2 serves a hub function in the control of glutamatergic transmission by ordering GKAP-containing complexes in dendritic spines. Beyond illuminating the role of DLC2–GKAP interactions in glutamatergic signaling, these data underscore the power of the sN&B approach for quantitative spatio-temporal imaging of other important protein complexes.
Hypermethylation of O6-methylguanine-DNA methyltransferase promoter may predict nonrecurrence after chemotherapy in colorectal cancer cases.

PURPOSE Because O(6)-methylguanine-DNA methyltransferase (MGMT) plays an essential role in repairing DNA damage caused by environmental alkylating chemicals, we were interested in determining whether we could see any obvious changes in the properties of colorectal cancers (CRCs) in which the MGMT gene had been silenced by hypermethylation and hence in which very few MGMT protein molecules were being produced. EXPERIMENTAL DESIGN We used a methylation-specific PCR assay to determine the methylation status of the MGMT promoter in the DNA molecules extracted from CRC and nontumor tissue samples from 116 patients who had undergone CRC surgery and for whom clinical outcome information was available on file. RESULTS We found evidence of MGMT promoter hypermethylation in 26 of 90 CRC cases, and we noted that the later the stage at which a tumor was diagnosed, the less likely its MGMT promoter was to be methylated (P = 0.03, adjusting for chemotherapy), especially for stage D patients (P = 0.01). We also found that CRC patients with unmethylated MGMT promoters were much more likely to experience recurrence within 36 months than patients with hypermethylated MGMT promoters (crude odds ratio, 14.0; 95% confidence interval, 2.42-81.01). After adjustment for stage, CRC patients with unmethylated MGMT promoters who had been exposed to chemotherapy were found to have a 5.3-fold greater risk of recurrence than those who had no exposure to chemotherapy (95% confidence interval, 1.15-30.92). CONCLUSIONS Hypermethylation of the MGMT promoter may be predictive of a low risk of recurrence in CRC patients receiving adjuvant chemotherapy.
Fe t 2 g band dispersion and spin polarization in thin films of Fe 3 O 4 (0 0 1)/MgO(0 0 1): Half-metallicity of magnetite revisited

W. Wang,1,2 J.-M. Mariot,3 M. C. Richter,1,4 O. Heckmann,1,4 W. Ndiaye,1 P. De Padova,5 A. Taleb-Ibrahimi,6 P. Le Fèvre,7 F. Bertran,7 F. Bondino,8 E. Magnano,8 J. Krempaský,9 P. Blaha,10 C. Cacho,11 F. Parmigiani,8,12 and K. Hricovini1,4 1Laboratoire de Physique des Matériaux et des Surfaces, Université de Cergy-Pontoise, 5 mail Gay-Lussac, 95031 Cergy-Pontoise, France 2Institute of Precision Optical Engineering, Department of Physics, Tongji University, Shangai 200092, People’s Republic of China 3Laboratoire de Chimie Physique–Matière et Rayonnement (UMR 7614), Université Pierre et Marie Curie, 11 rue Pierre et Marie Curie, 75231 Paris Cedex 05, France 4DSM, IRAMIS, Service de Physique et Chimie des Surfaces et des Interfaces, CEA-Saclay, 91191 Gif-sur-Yvette, France 5CNR, Istituto di Struttura della Materia, via Fosso del Cavaliere, 00133 Roma, Italy 6UR1-CNRS/Synchrotron SOLEIL, Saint-Aubin, B.P. 48, 91192 Gif-sur-Yvette Cedex, France 7Synchrotron SOLEIL, Saint-Aubin, B.P. 48, 91192 Gif-sur-Yvette Cedex, France 8CNR, Laboratorio TASC INFM, S.S. 14, Km 163.5 in Area Science Park, 34012 Trieste, Italy 9Paul Scherrer Institut, 5232 Villigen PSI, Switzerland 10TU Wien, Institut für Materialchemie, Getreidemarkt 9/165, 1060 Wien, Austria 11Central Laser Facility, Rutherford Appleton Laboratory, Didcot, Oxon OX11 0QX, United Kingdom 12Department of Physics, Università degli Studi di Trieste, 34127 Trieste, Italy (Received 18 October 2012; revised manuscript received 20 December 2012; published 14 February 2013)
Study of formation control and obstacle avoidance of swarm robots using evolutionary algorithms

Swarm robots cooperating in a group offer plentiful benefits and can accomplish several jobs that could be otherwise challenging either for human beings or for a single robot. Here we have considered two evolutionary based control algorithms, namely Bacterial Foraging (BFOA) and Particle swarm optimization (PSO), for flocking of a swarm to a predefine objective along an optimum path while avoiding obstacles. During the movement of the swarm, attraction, repulsion and formation coefficients of all agents are evaluated using the above stated algorithms based on some fitness function as described. The evaluated coefficients can plan the path with obstacle avoidance efficiently throughout the journey. It is shown that PSO is responsible for proficient and fast path selection whereas BFOA maintains formation throughout the trajectory. Simulation results illustrate that two competing algorithms produce robust solution in different aspects.
Affine SoftAssign with bidirectional distance for point matching

This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine transformation is updated by two optimization steps, in which the model data and the test data are matched from each other respectively. By the optimization of registration at separate steps during each iteration, the proposed algorithm can provide a good estimate of the accurate affine transformation in condition of poor initialization and lack of geometric assumptions on point sets. Some experiments about comparison with the current state-of-the art approaches, demonstrate the robustness and accuracy of our method.
Deep Analysis of Intending Peer-to-Peer Botnet

Botnet has recently been identified as one of the most important security threats of the Internet. So we should study the new technology which may be used by botmaster in the near future. In this paper we predict the new feature of the next generation botnet and present the design of an advanced P2P botnet basing on our discussion.
A Universal Relation Data Model with Semantic Abstraction

Two important features of modern database models are support for complex data structures and support for high-level data retrieval and update. The first issue has been studied by the development of various semantic data models; the second issue has been studied through universal relation data models. How the advantages of these two approaches can be combined is presently examined. A new data model that incorporates standard concepts from semantic data models such as entities, aggregations, and ISA hierarchies is introduced. It is then shown how nonnavigational queries and updates can be interpreted in this model. The main contribution is to demonstrate how universal relation techniques can be extended to a more powerful data model. Moreover, the semantic constructs of the model allow one to eliminate many of the limitations of previous universal relation models. >
Model Checking CSL for Markov Population Models

Markov population models (MPMs) are a widely used modelling formalism in the area of computational biology and related areas. The semantics of a MPM is an infinite-state continuous-time Markov chain. In this paper, we use the established continuous stochastic logic (CSL) to express properties of Markov population models. This allows us to express important measures of biological systems, such as probabilistic reachability, survivability, oscillations, switching times between attractor regions, and various others. Because of the infinite state space, available analysis techniques only apply to a very restricted subset of CSL properties. We present a full algorithm for model checking CSL for MPMs, and provide experimental evidence showing that our method is effective.
Gremlin2 Suppression Increases the BMP‐2‐Induced Osteogenesis of Human Bone Marrow‐Derived Mesenchymal Stem Cells Via the BMP‐2/Smad/Runx2 Signaling Pathway

Osteoblasts are essential for maintaining skeletal architecture and modulating bone microenvironment homeostasis. From numerous associated investigations, the BMP‐2 pathway has been well‐defined as a vital positive modulator of bone homeostasis. Gremlin2 (Grem2) is a bone morphogenetic protein (BMP) antagonists. However, the effect of Grem2 on the BMP‐2‐induced osteogenesis of human bone marrow‐derived mesenchymal stem cells (hBMSCs) remains ambiguous. This study aimed to analyze the procedure in vitro and in vivo. The differentiation of hBMSCs was assessed by determining the expression levels of several osteoblastic genes, as well as the enzymatic activity and calcification of alkaline phosphatase. We found that Grem2 expression was upregulated by BMP‐2 within the range of 0–1 μg/mL, and significant increases were evident at 48, 72, and 96 h after BMP‐2 treatment. Si‐Grem2 increased the BMP‐2‐induced osteogenic differentiation of hBMSCs, whereas overexpression of Grem2 had the opposite trend. The result was confirmed using a defective femur model. We also discovered that the BMP‐2/Smad/Runx2 pathway played an important role in the process. This study showed that si‐Grem2 increased the BMP‐2‐induced osteogenic differentiation of hBMSCs via the BMP‐2/Smad/Runx2 pathway. J. Cell. Biochem. 118: 286–297, 2017. © 2016 Wiley Periodicals, Inc.
Phytochrome Control of Specific mRNA levels in Developing Pea Buds : Kinetics of Accumulation, Reciprocity, and Escape Kinetics of the Low Fluence Response.

We have examined the time course for accumulation of each of 12 different nuclear gene transcripts in pea buds after irradiating dark grown seedlings with a single pulse low fluence red light (10(3) micromoles per square meter delivered in 100 seconds). The 12 time courses can be grouped into four general classes. Six transcripts (including RNAs coding for the chlorophyll a/b binding protein and ribulose-1,5-bisphosphate carboxylase) accumulate at a linear rate during 24 hours in darkness following the light pulse. Two transcripts increase rapidly at first but then reach a plateau after 3 hours and remain at that level for the next 21 hours. Another two transcripts exhibit a prolonged lag period before beginning to accumulate, and do not reach significant accumulation rates until 12 to 16 hours after the red light pulse. One transcript appears to undergo a transient increase in abundance in response to red light, but this is superimposed on a background of slowly increasing abundance of this RNA in control plants. This response, unlike all the others, exhibits reciprocity failure in experiments in which the same fluence of light is given over periods ranging between 50 and 4000 seconds.We have also examined the kinetics with which each of these 12 responses escapes from phytochrome-far-red absorbing form control by attempting to reverse the induction with far-red light given at various times after the red light pulse. Again, several different patterns are apparent for the different transcripts. The time at which far red reversibility first begins to be lost, the rate at which it is lost, and the final extent of reversibility remaining after 7 hours in the dark all differ for different transcripts. In addition, we have observed that some responses retain virtually complete photoreversibility for at least 7 hours. In some cases, a comparison of the time course and escape kinetic data indicates that relatively rapid turnover of the RNA must occur. It is not clear whether or not the rate of turnover is influenced by phytochrome.
Genetic Polymorphism of CYP2C9 in a Vietnamese Kinh Population

Cytochrome P450 2C9 (CYP2C9) shows genetic polymorphism with high interethnic variation, but no report has addressed the genetic polymorphism in the Vietnamese population. In the present study, the distribution of 2 common allelic variations of CYP2C9 was investigated in Vietnamese Kinh population, a major ethnic group in Vietnam. Genomic DNA from 157 Vietnamese subjects was amplified by polymerase chain reaction, and the presence of CYP2C9*2 and CYP2C9*3 allelic variants was determined by pyrosequencing. Among 157 Vietnamese subjects, no subject with the CYP2C9*2 allele was detected, but 7 subjects were heterozygous for the CYP2C9*3 allele. The allele frequency of CYP2C9*3 was 2.2% in the Vietnamese Kinh population. This genotype distribution was well correlated with previous reports suggesting no occurrence of CYP2C9*2 in Asians. These results suggest that CYP2C9*2 may be absent in Vietnamese Kinh population and that CYP2C9*3 is major allelic variant that causes interindividual variation of drug responses to CYP2C9 substrate drugs in the Vietnamese Kinh population.
Natural Language Processing - A Survey

The utility and power of Natural Language Processing (NLP) seems destined to change our technological society in profound and fundamental ways. However there are, to date, few accessible descriptions of the science of NLP that have been written for a popular audience, or even for an audience of intelligent, but uninitiated scientists. This paper aims to provide just such an overview. In short, the objective of this article is to describe the purpose, procedures and practical applications of NLP in a clear, balanced, and readable way. We will examine the most recent literature describing the methods and processes of NLP, analyze some of the challenges that researchers are faced with, and briefly survey some of the current and future applications of this science to IT research in general.
Distribution and spatio-temporal biomass trends of red mullets across the Mediterranean

The present work examines the spatio-temporal biomass trends of Mullus barbatus and Mullus surmuletus in the Mediterranean Sea through the analysis of a time series of data coming from the Mediterranean International Trawl Surveys (MEDITS), accomplished annually from 1994 to 2015. The biomass of both species showed clear declining trends below 150 to 200 m depth, which were steeper in the case of M. barbatus. Increases in temporal biomass trends were observed for M. barbatus from 2008 onward in most geographic sub-areas (GSAs), while stability was mostly observed for M. surmuletus. For both species, dynamic factor analysis revealed similarities among neighbouring GSAs and the subsequent cluster analysis identified two major GSA groups corresponding to the eastern and western basins of the Mediterranean. Overall, the results suggested that the combined effects of fishing and environmental conditions determine species abundance variations, but the relative importance of each component may vary among areas.
Sequence-to-sequence Modelling of F0 for Speech Emotion Conversion

Voice interfaces are becoming wildly popular and driving demand for more advanced speech synthesis and voice transformation systems. Current text-to-speech methods produce realistic sounding voices, but they lack the emotional expressivity that listeners expect, given the context of the interaction and the phrase being spoken. Emotional voice conversion is a research domain concerned with generating expressive speech from neutral synthesised speech or natural human voice. This research investigated the effectiveness of using a sequence-to-sequence (seq2seq) encoder-decoder based model to transform the intonation of a human voice from neutral to expressive speech, with some preliminary introduction of linguistic conditioning. A subjective experiment conducted on the task of speech emotion recognition by listeners successfully demonstrated the effectiveness of the proposed sequence-to-sequence models to produce convincing voice emotion transformations. In particular, conditioning the model on the position of the syllable in the phrase significantly improved recognition rates.
Elastic neural network method for load prediction in cloud computing grid

Cloud computing still has no standard definition, yet it is concerned with Internet or network on-demand delivery of resources and services. It has gained much popularity in last few years due to rapid growth in technology and the Internet. Many issues yet to be tackled within cloud computing technical challenges, such as Virtual Machine migration, server association, fault tolerance, scalability, and availability. The most we are concerned with in this research is balancing servers load; the way of spreading the load between various nodes exists in any distributed systems that help to utilize resource and job response time, enhance scalability, and user satisfaction. Load rebalancing algorithm with dynamic resource allocation is presented to adapt with changing needs of a cloud environment. This research presents a modified elastic adaptive neural network (EANN) with modified adaptive smoothing errors, to build an evolving system to predict Virtual Machine load. To evaluate the proposed balancing method, we conducted a series of simulation studies using cloud simulator and made comparisons with previously suggested approaches in the previous work. The experimental results show that suggested method betters present approaches significantly and all these approaches.
Locating the tightest link of a network path

The tightest link of a network path is the link where the end-to-end available bandwidth is limited. We propose a new probe technique, called Dual Rate Periodic Streams (DRPS), for finding the location of the tightest link. A DRPS probe is a periodic stream with two rates. Initially, it goes through the path at a comparatively high rate. When arrived at a particular link, the probe shifts its rate to a lower level and keeps the rate. If proper rates are set to the probe, we can control whether the probe is congested or not by adjusting the shift time. When the point of rate shift is in front of the tightest link, the probe can go through the path without congestion, otherwise congestion occurs. Thus, we can find the location of the tightest link by congestion detection at the receiver.
Following disease progression in motor neuron disorders with 3 MUNE methods.

INTRODUCTION: The objective of this study was to evaluate a recently developed motor unit number estimation (MUNE) method, MScanFit MUNE (MScan), as a measure of disease progression in amyotrophic lateral sclerosis (ALS) compared to compound muscle action potential (CMAP) amplitude and two traditional MUNE methods. METHODS: ALS patients were evaluated clinically by ALS Functional Rating Scale-Revised (ALSFRS-R). MScan, multiple point stimulation MUNE (MPS) and motor unit number index (MUNIX) were performed in the abductor pollicis brevis (APB) muscle at baseline (27 patients), 4 months (23 patients) and 8 months (16 patients). RESULTS: Of the 5 measures, MScan registered the largest decline (8.7% per month) compared with MPS (3.4%), MUNIX (4.8%), CMAP amplitude (2.0%) and ALSFRS-R (1.9%). Only MScan and ALSFRS-R registered significant decrements over 4 and 8 months. DISCUSSION: MScan may be a sensitive objective tool for quantifying motor unit loss in ALS. This article is protected by copyright. All rights reserved.
Temporal Model of the Online Customer Review Helpfulness Prediction

Customer reviews provide opinions and relevant information that will affect the purchase behavior of other customers. Many studies focused on the prediction of the helpfulness of customer reviews to find the helpful reviews, which are traditionally determined by the helpful voting results. In our study, we find that the voting result of an online review is not a constant over time. Therefore, predicting the voting result based on the analysis of text is not enough; the temporal issue must be considered. We propose a system that can rank the reviews based on a set of linguistic features with a linear regression model. To evaluate our system, we collect Chinese custom reviews in eight product categories (books, digital cameras, tablet PC, backpacks, movies, men shoes, toys and cell phones) from Amazon.cn with the voting result on the helpfulness of the reviews. Since the voting result may be affected by voting time and total voting number, we define a new evaluation index and compare the regression results. The results show that the system has less prediction error when it takes the time information into the prediction model.
The Privileged Role of the Late-Night Joke: Exploring Humor's Role in Disrupting Argument Scrutiny

This article explores humor's impact on cognitive processing of political messages. Although recent research has pointed to effects of late-night comedy viewing on political attitudes and cognitions (Moy, Xenos, & Hess, 2003; Young, 2004, 2006), scant attention has been paid to the development of a theoretical model to account for these outcomes. This manuscript posits that humor suspends argument scrutiny of the premise of a given text through various cognitive mechanisms involving processing ability and motivation. Four different pathways accounting for humor's reduction of argument scrutiny are discussed. Humor's reduction of argument scrutiny is tested with an experiment with a three condition between subjects design in which participants engaged in a thought-listing exercise after exposure to either humorous political messages (late-night political jokes) or non-humorous equivalents (unfunny translations of those jokes). Results indicate that humor reduces critical argument scrutiny—in part through the “discounting cue” mechanism. Implications for persuasion are discussed.
Sangoshthi: Empowering Community Health Workers through Peer Learning in Rural India

The Healthcare system of India provides outreach services to the rural population with a key focus on the maternal and child health through its flagship program of Community Health Workers (CHWs). The program since its launch has reached a scale of over 900000 health workers across the country and observed significant benefits on the health indicators. However, traditional face to face training mechanisms face persistent challenge in providing adequate training and capacity building opportunities to CHWs which leads to their sub-optimal knowledge and skill sets. In this paper, we propose Sangoshthi, a low-cost mobile based training and learning platform that fits well into the environment of low-Internet access. Sangoshthi leverages the architecture that combines Internet and IVR technology to host real time training sessions with the CHWs having access to basic phones only. We present our findings of a four week long field deployment with 40 CHWs using both qualitative and quantitative methods. Sangoshthi offers a lively environment of peer learning that was well received by the CHW community and resulted into their knowledge gains (16%) and increased confidence levels to handle the cases. Our study highlights the potential of complementary training platforms that can empower CHWs in-situ without the need of additional infrastructure.