Miracle-dz/UniFAR-FTUs huggingface dataset:
Activity-Independent Regulation of Dendrite Patterning by Postsynaptic Density Protein PSD-95

Dendritic morphology determines many aspects of neuronal function, including action potential propagation and information processing. However, the question remains as to how distinct neuronal dendrite branching patterns are established. Here, we report that postsynaptic density-95 (PSD-95), a protein involved in dendritic spine maturation and clustering of synaptic signaling proteins, plays a novel role in regulating dendrite outgrowth and branching, independent of its synaptic functions. In immature neurons, overexpression of PSD-95 decreases the proportion of primary dendrites that undergo additional branching, resulting in a marked reduction of secondary dendrite number. Conversely, knocking down PSD-95 protein in immature neurons increases secondary dendrite number. The effect of PSD-95 is activity-independent and is antagonized by cypin, a nonsynaptic protein that regulates PSD-95 localization. Binding of cypin to PSD-95 correlates with formation of stable dendrite branches. Finally, overexpression of PSD-95 in COS-7 cells disrupts microtubule organization, indicating that PSD-95 may modulate microtubules to regulate dendritic branching. Whereas many factors have been identified which regulate dendrite number, our findings provide direct evidence that proteins primarily involved in synaptic functions can also play developmental roles in shaping how a neuron patterns its dendrite branches.
Efficient Nonlinear Control with Actor-Tutor Architecture

A new reinforcement learning architecture for nonlinear control is proposed. A direct feedback controller, or the actor, is trained by a value-gradient based controller, or the tutor. This architecture enables both efficient use of the value function and simple computation for real-time implementation. Good performance was verified in multi-dimensional nonlinear control tasks using Gaussian softmax networks.
CARESS Working Paper # 95-02 An Economic Model of Representative Democracy ¤

This paper develops a new approach to the study of democratic policy making where politicians are selected by the people from those citizens who present themselves as candidates for public o±ce. Participation in the policy making process is, therefore, derived endogenously. The approach has a number of attractive features. First, it is a conceptualization of a pure form of representative democracy in which government is by, as well as of, the people. Second, the model is analytically tractable, being able to handle multidimensional issue and policy spaces very naturally. Third, it provides a vehicle for answering questions about the achievements of representative democracy. We study, in particular, whether representative democracy produces e±cient outcomes. ¤We are grateful to Gene Grossman, Robert Inman, John Lott Jr., Stephen Morris, Alex Tabarrok, a number of seminar participants, and, especially, Howard Rosenthal, for discussions, comments and encouragement. \The democratic method is that institutional arrangement for arriving at political decisions in which individuals acquire the power to decide by means of a competitive struggle for the people's vote," (Schumpeter (1954), page 269). \In the real world, individuals, as such, do not make ̄scal choices. They seem limited to choosing \leaders," who will, in turn, make ̄scal decisions. " (Buchanan (1967), page v).
Human-robot collaboration for tooling path guidance

Human robot collaboration (HRC) is a hot research topic nowadays and achieves great success and development from the laboratory to the daily life service and industrial applications. This paper briefly introduces the background of HRC and its application in industries as well as technical characteristics. Finally, an intelligent industrial work assistant (iiwa) robot is setup as a HRC experiment platform to perform collaborative tasks. The demo gives an outlook that human and robot working alongside is viable and successful.
Bayesian 3D Tracking from Monocular Video

We develop a Bayesian modeling approach for tracking people in 3D from monocular video with unknown cameras. Modeling in 3D provides natural explanations for occlusions and smoothness discontinuities that result from projection, and allows priors on velocity and smoothness to be grounded in physical quantities: meters and seconds vs. pixels and frames. We pose the problem in the context of data association, in which observations are assigned to tracks. A correct application of Bayesian inference to multi-target tracking must address the fact that the model's dimension changes as tracks are added or removed, and thus, posterior densities of different hypotheses are not comparable. We address this by marginalizing out the trajectory parameters so the resulting posterior over data associations has constant dimension. This is made tractable by using (a) Gaussian process priors for smooth trajectories and (b) approximately Gaussian likelihood functions. Our approach provides a principled method for incorporating multiple sources of evidence, we present results using both optical flow and object detector outputs. Results are comparable to recent work on 3D tracking and, unlike others, our method requires no pre-calibrated cameras.
Repulsive Forces Between Looping Chromosomes Induce Entropy-Driven Segregation

One striking feature of chromatin organization is that chromosomes are compartmentalized into distinct territories during interphase, the degree of intermingling being much smaller than expected for linear chains. A growing body of evidence indicates that the formation of loops plays a dominant role in transcriptional regulation as well as the entropic organization of interphase chromosomes. Using a recently proposed model, we quantitatively determine the entropic forces between chromosomes. This Dynamic Loop Model assumes that loops form solely on the basis of diffusional motion without invoking other long-range interactions. We find that introducing loops into the structure of chromatin results in a multi-fold higher repulsion between chromosomes compared to linear chains. Strong effects are observed for the tendency of a non-random alignment; the overlap volume between chromosomes decays fast with increasing loop number. Our results suggest that the formation of chromatin loops imposes both compartmentalization as well as order on the system without requiring additional energy-consuming processes.
Before You Send That: Comparing the Outcomes of Face-to-Face and Cyber Incivility

The increasing use of information and communication technologies has allowed for a new type incivility known as cyber incivility. This study compared the correlations of face-to-face and cyber incivility with job satisfaction, burnout, and turnover intentions. Data were collected from 231 participants who completed an online survey asking about the aforementioned work outcomes and face-to-face and cyber incivility. Results indicated that face-to-face and cyber incivility were both significantly correlated with each of the work outcomes, consistent with previous research. Contrary to the hypotheses, Fisher’s r-to-z transformations showed that face-to-face incivility was more strongly correlated with job satisfaction, burnout, and turnover intentions than cyber incivility. Taken together, these results suggest that organizations should focus on interventions to reduce both face-to-face and cyber incivility.
DPG: A Cache-Efficient Accelerator for Sorting and for Join Operators

We present a new algorithm for fast record retrieval, distribute-probe-gather, or DPG. DPG has important applications both in sorting and in joins. Current main memory sorting algorithms split their work into three phases: extraction of key-pointer pairs; sorting of the key-pointer pairs; and copying of the original records into the destination array according the sorted key-pointer pairs. The copying in the last phase dominates today's sorting time. Hence, the use of DPG in the third phase provides an accelerator for existing sorting algorithms. DPG also provides two new join methods for foreign key joins: DPG-move join and DPG-sort join. The resulting join methods with DPG are faster because DPG join is cache-efficient and at the same time DPG join avoids the need for sorting or for hashing. The ideas presented for foreign key join can also be extended to faster record pair retrieval for spatial and temporal databases.
Pharmacological and Genetic Accumulation of Hypoxia-Inducible Factor-1α Enhances Excitatory Synaptic Transmission in Hippocampal Neurons through the Production of Vascular Endothelial Growth Factor

Hypoxia-inducible factor-1 (HIF-1) is an important transcriptional factor in mammalian cells for coordination of adaptive responses to hypoxia. It consists of a regulatory subunit HIF-1α, which accumulates under hypoxic conditions, and a constitutively expressed subunit HIF-1β. In addition to the well characterized oxygen-dependent mode of action of HIF-1, recent work has shown that various growth factors and cytokines stimulate HIF-1α expression, thereby triggering transcription of numerous hypoxia-inducible genes by oxygen-independent mechanisms. In this study, we examined whether accumulation of HIF-1α induced by insulin-like growth factor-1 (IGF-1) has a regulatory role in excitatory synaptic transmission in hippocampal neuron cultures. Our results show that IGF-1 induced a time- and dose-dependent increase in HIF-1α expression that was blocked by pretreatment with selective IGF-1 receptor antagonist, transcriptional inhibitor, and translational inhibitors. In addition, pharmacological blockade of the phosphatidylinositol 3-kinase/Akt/mammalian target of the rapamycin signaling pathway, but not extracellular signal-regulated kinase, inhibited IGF-1-induced HIF-1α expression. More importantly, the increase in HIF-1α expression induced by IGF-1 was accompanied by increasing levels of vascular endothelial growth factor (VEGF) mRNA and protein, which enhanced excitatory synaptic transmission. In parallel, blockade of HIF-1α activity by echinomycin or lentiviral infection with dominant-negative mutant HIF-1α or short hairpin RNA targeting HIF-1α inhibited the increase in expression of VEGF and the enhancement of synaptic transmission induced by IGF-1. Conversely, transfection of constitutively active HIF-1α into neurons mimicked the effects of IGF-1 treatment. Together, these results suggest that HIF-1α accumulation can enhance excitatory synaptic transmission in hippocampal neurons by regulating production of VEGF.
A Novel Cloud based and Cyclic Approach for Supervised Learning

The Clouds provide more services to the users. In the past era the software users have to purchase the software with licence. But now a days clouds provide these softwares on pay and use basis to use it. This pay and use service brought more comfort to the users. Through this paper, we propose `A Novel Cloud based and Cyclic Approach for Supervised Learning', in the area of Data Mining. Because the data warehouses are utilizing the virtualized Iaas cloud service. i.e., the data warehouses are stored in the clouds and utilizing services of cloud. We concentrated more on classification problem in the area of data mining, because the global business scenario is entirely changed. According to these changes the need of classification become essential in all areas. Particularly to the data, which is stored in the virtual data warehouses. In the cloud hosted data warehouses the current test data set will become as training data set after some period of time. In our proposed approach we introduced the post-mortem technique on the classification model to know the facts, how good the model is induced to classify the data set from the training data set. To provoke a high-quality and an efficient classification model, the model must go through the post-mortem operation to know the reality of the classification. The test data set must go through the pre-processing operation to make the data set pure and clean. This process must be done in routine.
A Three-Dimensional Deflagration Model for Type Ia Supernovae Compared with Observations

A simulation of the thermonuclear explosion of a Chandrasekhar-mass C+O white dwarf, the most popular scenario of a Type Ia supernova (SN Ia), is presented. The underlying modeling is pursued in a self-consistent way, treating the combustion wave as a turbulent deflagration using well tested methods developed for laboratory combustion and based on the concept of "large-eddy simulations" (LESs). Such consistency requires to capture the onset of the turbulent cascade on resolved scales. This is achieved by computing the dynamical evolution on a 10243 moving grid, which resulted in the best-resolved three-dimensional SN Ia simulation carried out thus far, reaching the limits of what can be done on present supercomputers. Consequently, the model has no free parameters other than the initial conditions at the onset of the explosion, and therefore it has considerable predictive power. Our main objective is to determine to which extent such a simulation can account for the observations of normal SNe Ia. Guided by previous simulations with less resolution and a less sophisticated flame model, initial conditions were chosen that yield a reasonably strong explosion and a sufficient amount of radioactive nickel for a bright display. We show that observables are indeed matched to a reasonable degree. In particular, good agreement is found with the light curves of normal SNe Ia. Moreover, the model reproduces the general features of the abundance stratification as inferred from the analysis of spectra. This indicates that it captures the main features of the explosion mechanism of SNe Ia. However, we also show that even a seemingly best-choice pure deflagration model has shortcomings that indicate the need for a different mode of nuclear burning at late times, perhaps the transition to a detonation at low density.
Modeling Volatility: Indian Stock and Foreign Exchange Markets

This paper attempts to evaluate the ability of the different statistical models used for forecasting volatility in the context of Indian stock and foreign exchange markets. The financial market volatility has remained very calm from 2004 to late 2006 and registered below long-term averages as measured by VIX index. However, the financial crisis of 2008 changed the entire picture rendering markets extremely ‘volatile’. Therefore, this paper examines the properties of several models used in volatility forecasting; Historical volatility models (EWMA), ARCH and GARCH family models (TARCH, EGARCG, PARCH, etc.) and their accuracy in modeling and forecasting the volatility of Indian Rupee against USD and index return movements. The problem that this paper seeks to answer is identifying the ideal model which better explains the volatility and asymmetry of stock and foreign exchange markets. NSE and BSE index return series is used for examining the stock market volatility. In this direction, the paper is divided into two parts: model selection and comparison of various models on the basis of forecast error statistics. Based on the forecast statistics we find that TARCH and PARCH will lead to better volatility forecast for BSE and NSE return series for the stock market evaluation and ARMA (1,1)/ ARCH/ EGARCH for the foreign exchange market.
Viewpoint-based Test Architecture Design

Software test recently becomes large-scale and complicated artifact as software itself. Research and practices has to be boosted such as test architecture. In this paper first we mention TDLC: Test Development Life Cycle, which includes test requirement design phase and test architecture design phase instead of test planning from engineering view. Second we discuss concepts of test architecture and propose NGT: Notation for Generic Testing, which is a set of concepts or notation for design of software test architecture. Viewpoint is discussed as a key concept of test architecture representing a group of test cases and test objective. And this paper gives an example of test architecture model. Finally this paper shows possibility that viewpoint diagram will be a platform of test architecture design technology such as test design patterns, test architecture style, variability analysis of product line engineering and so on.
Oligomerization and endocytosis of Hedgehog is necessary for its efficient exovesicular secretion

Hedgehog (Hh)-containing exovesicles are mediators of long-range signaling in Drosophila wing imaginal discs. ESCRT-dependent multivesicular body (MVB) biogenesis is essential for generating Hh exovesicles. Oligomerization of Hh at the cell surface is necessary for its endocytic delivery to MVBs and therefore is required for its release as exovesicles.
Selective and Efficient Generation of ortho-Brominated para-Substituted Phenols in ACS-Grade Methanol

The mono ortho-bromination of phenolic building blocks by NBS has been achieved in short reaction times (15-20 min) using ACS-grade methanol as a solvent. The reactions can be conducted on phenol, naphthol and biphenol substrates, giving yields of >86% on gram scale. Excellent selectivity for the desired mono ortho-brominated products is achieved in the presence of 10 mol % para-TsOH, and the reaction is shown to be tolerant of a range of substituents, including CH3, F, and NHBoc.
Persistent Infection with Primate Foamy Virus Type 1 Increases Human Immunodeficiency Virus Type 1 Cell Binding via a Bet-Independent Mechanism

ABSTRACT We report that human T cells persistently infected with primate foamy virus type 1 (PFV-1) display an increased capacity to bind human immunodeficiency virus type 1 (HIV-1), resulting in increased cell permissiveness to HIV-1 infection and enhanced cell-to-cell virus transmission. This phenomenon is independent of HIV-1 receptor, CD4, and it is not related to PFV-1 Bet protein expression. Increased virus attachment is specifically inhibited by heparin, indicating that it should be mediated by interactions with heparan sulfate glycosaminoglycans expressed on the target cells. Given that both viruses infect similar animal species, the issue of whether coinfection with primate foamy viruses interferes with the natural course of lentivirus infections in nonhuman primates should be considered.
Combining Ranking and Classification to Improve Emotion Recognition in Spontaneous Speech

We introduce a novel emotion recognition approach which integrates ranking models. The approach is speaker independent, yet it is designed to exploit information from utterances from the same speaker in the test set before making predictions. It achieves much higher precision in identifying emotional utterances than a conventional SVM classifier. Furthermore we test several possibilities for combining conventional classification and predictions based on ranking. All combinations improve overall prediction accuracy. All experiments are performed on the FAU AIBO database which contains realistic spontaneous emotional speech. Our best combination system achieves 6.6% absolute improvement over the Interspeech 2009 emotion challenge baseline system on the 5-class classification tasks.
Teachers' Perceptions of their Resilience as they Teach a Social and Emotional Program: A Narrative Case Study

Resilience education typically focuses on developing the resilience capabilities of students. Worldwide, classrooms are experiencing rapid change as a response to advances in technology, stronger recognition of prior knowledge of students, instant access to more information than the teacher knows, double-income families, children who have grown up in childcare, and multiple varieties of blended families—to name a few trends dominating contemporary times (Jones, 2006; Skaalvik & Skaalvik, 2011). Research confirms that less resilient students may be at risk of failing or dropping out of school (Hess & Copeland, 2001; Luthar & Barkin, 2012). This perceived lack of resilience in students has given rise to the development of multiple off-the-shelf scripted programs so that resilience skills can be taught (Morrison & Redding Allen, 2007). In this context, there is a growing body of literature that highlights risk factors posed by a lack of resilience in teachers, suggesting if they are not resilient they may be ineffective (Day & Gu, 2009; Gu & Day, 2007) or so stressed they leave the profession (Beltman, Mansfield, & Price, 2011; Howard & Johnson, 2004). In initial teacher education programs preservice students develop a range of capabilities, often dominated by subject knowledge specialisation, but this may not fully equip them for the reality of life in the classroom (Gu & Day, 2007). A critical review of the literature reveals there is a gap in the field regarding the resilience of teachers in regard to the roles they must fulfil outside of their main teaching area, in particular in the role of pastoral care teacher, where they may be required to focus on the development of resilience in their students (Jones, 2006).
Framework and tools for run-time reconfigurable designs

The paper describes a framework and tools for automating the production of designs that can be partially reconfigured at run time. The approach involves several stages, including: (i) a partial evaluation stage, which produces configuration files for a given design, where the number of configurations is minimised during the compile-time sequencing stage; (ii) an incremental configuration calculation stage, which takes the output of the partial evaluator and generates an initial configuration file and incremental configuration files that partially update preceding configurations; and (iii) an optimisation stage for devices or systems supporting simultaneous configuration of multiple components. While many of the techniques are independent of the design language and device used, experimental tools have been developed that target Xilinx 6200 devices. Simultaneous configuration, for example, can be used to reduce the time for reconfiguring an adder to a subtractor from time linear with respect to its size to constant time at best and logarithmic time at worst. The tools have been used in developing a variety of designs, including arithmetic, video and database applications.
Evaluating the practical low speed limits for back-EMF tracking-based sensorless speed control using drive stiffness as a key metric

Although it is widely known that back-EMF tracking has a low speed limit, there is very little published literature evaluating this limit. This paper shows that the low speed limit is mainly a function of the amplitude of the inverter harmonics, which means that theory and simulation will provide erroneous results when inverter harmonics are not incorporated. This paper will also provide a method for evaluating this low speed limit using drive stiffness as the metric. The experimental results shows quantitatively how the drive stiffness suffers as speed decreases, which ultimately sets the practical low speed limit.
Investigating the abstractness of children's early knowledge of argument structure

In the current debate about the abstractness of children's early grammatical knowledge, Tomasello & Abbott-Smith (2002) have suggested that children might first develop ‘weak’ or ‘partial’ representations of abstract syntactic structures. This paper attempts to characterize these structures by comparing the development of constructions around verbs in Tomasello's (1992) case study of Travis, with those of 10 children (Stage I–II) in a year-length, longitudinal study. The results show some evidence that children's early knowledge of argument structure is verb-specific, but also some evidence that children can generalize knowledge about argument structure across verbs. One way to explain these findings is to argue that children are learning limited scope formulae around high frequency subjects and objects, which serve as building blocks for more abstract structures such as S+V and V+O. The implication is that children may have some verb-general knowledge of the transitive construction as early as Stage I, but that this knowledge is still far from being fully abstract knowledge.