Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Dense Convolutional Embeddings for Semantic Segmentation

This paper proposes a new deep convolutional neural network (DCNN) architecture that learns pixel embeddings, such that pairwise distances between the embeddings can be used to infer whether or not the pixels lie on the same region. That is, for any two pixels on the same object, the embeddings are trained to be similar; for any pair that straddles an object boundary, the embeddings are trained to be dissimilar. Experimental results show that when this embedding network is used in conjunction with a DCNN trained on semantic segmentation, there is a systematic improvement in per-pixel classification accuracy. Our contributions are integrated in the popular Caffe deep learning framework, and consist in straightforward modifications to convolution routines. As such, they can be exploited for any task involving convolution layers.
A CG Learning Tool with Guided Programming Environment

3 dimensional computer graphics (3DCG) becomes an easily accessible technology for general public. The 3DCG production skill is becoming one of mandatory technical capabilities for IT engineers. The learning aids such as text books and related web pages consist of captured 2D images for understanding 3DCG theories and program codes for explaining specific algorithms. The learners should work with multiple materials and tools including the books, some tools for learning 3D modeling, rendering, and animation, and a development tool for acquiring graphics programming skill. These efforts require enormous amount of time and impose a heavy burden on the learners. To solve the problem, we have been developing a self-contained 3DCG learning support system. It helps the learners to intuitively acquire the 3DCG production skills through a hands-on graphics programming environment.
Conformations of variably linked chimeric proteins evaluated by synchrotron X‐ray small‐angle scattering

We constructed chimeric proteins that consist of two green fluorescent protein variants, EBFP and EGFP, connected by flexible linkers, (GGGGS)n (n = 3∼4), and helical linkers, (EAAAK)n (n = 2∼5). The conformations of the chimeric proteins with the various linkers were evaluated using small‐angle X‐ray scattering (SAXS). The SAXS experiments showed that introducing the short helical linkers (n = 2∼3) causes multimerization, while the longer linkers (n = 4∼5) solvate monomeric chimeric proteins. With the moderate‐length linkers (n = 4), the observed radius of gyration (Rg) and maximum dimension (Dmax) were 38.8 Å and 120 Å with the flexible linker, and 40.2 Å and 130 Å with the helical linker, respectively. The chimeric protein with the helical linker assumed a more elongated conformation as compared to that with the flexible linker. When the length of the helical linker increased (n = 5), Rg and Dmax increased to 43.2 Å and 140 Å, respectively. These results suggest that the longer helix effectively separates the two domains of the chimeric protein. Considering the connectivity of the backbone peptide of the protein, the helical linker seems to connect the two domains diagonally. Surprisingly, the chimeric proteins with the flexible linker exhibited an elongated conformation, rather than the most compact side‐by‐side conformation expected from the fluorescence resonance energy transfer (FRET) analysis. Furthermore, the SAXS analyses suggest that destabilization of the short helical linker causes multimerization of the chimeric proteins. Information about the global conformation of the chimeric protein is thus be necessary for optimization of the linker design. Proteins 2004. © 2004 Wiley‐Liss, Inc.
Cooperation of constraint domains in the TOY system

This paper presents a computational model for the cooperation of constraint domains, based on a generic Constraint Functional Logic Programming (CFLP) Scheme and designed to support declarative programming with functions, predicates and the cooperation of different constraint domains equipped with their respective solvers. We have developed an implementation in the CFLP system TOY, supporting an instance of the scheme which enables the cooperation of symbolic Herbrand constraints, finite domain integer constraints, and real arithmetic constraints. We provide a theoretical result and an analysis of benchmarks showing a good performance with respect to the closest related approach we are aware of
PAS kinase is activated by direct SNF1-dependent phosphorylation and mediates inhibition of TORC1 through the phosphorylation and activation of Pbp1

The interplay between AMPK, Psk1, and TORC1 reduces cell growth and proliferation when energy is low. This interplay occurs through Snf1-dependent activation of Psk1, followed by phosphorylation of poly(A)-binding protein binding protein 1 (Pbp1) and subsequent inhibitory sequestration of TORC1 to stress granules.
Keeping Score for All: The Effects of Inclusion and Accommodation Policies on Large-Scale Educational Assessment. Executive Summary.

This free executive summary is provided by the National Academies as part of our mission to educate the world on issues of science, engineering, and health. If you are interested in reading the full book, please visit us online at http://www.nap. edu/catalog/11029.html . You may browse and search the full, authoritative version for free; you may also purchase a print or electronic version of the book. If you have questions or just want more information about the books published by the National Academies Press, please contact our customer service department toll-free at 888-624-8373.
Predicting Dialogue Outcomes over Structured Latent Representations

Studying dialogue relations as a complex structured output prediction problem, independently of the dialogue outcome, has been the focus of significant research efforts, such as discourse relations [9], rhetorical structure [8, 1] and dialogue act modeling [13]. While these works capture linguisticallymotivated fine-grained dialogue relations, they require considerable effort and linguistic knowledge. Furthermore, the subjective nature of our task, focusing on dialogue relations relevant to the dialogue outcome, allow for many different interpretations of the interactions leading to the observed outcome.
Coordinated Control of a Dual-Stage Positioning System Using Constrained Model Predictive Control

Dual-stage positioning systems have been widely used in factory automation, robotic manipulators, high-density data storage systems, and manufacturing systems. Trajectory generation and control of dual-stage positioning systems is of great importance and is made complicated by the presence of physical and operational constraints. In this work, we describe how to generate feasible reference trajectories for a dual-stage positioning system consisting of a fine stage and a coarse stage, and how to use them in a model predictive control algorithm for which recursive feasibility is guaranteed. The reference generation algorithm is guaranteed to generate trajectories that satisfy all the constraints for the fine and coarse stages. We also describe a constrained model predictive control algorithm used to control the coarse stage. The simulation results of applying the developed methodology to track a pre-determined pattern is presented.Copyright © 2014 by ASME
The N-terminal domains of TRF1 and TRF2 regulate their ability to condense telomeric DNA

TRF1 and TRF2 are key proteins in human telomeres, which, despite their similarities, have different behaviors upon DNA binding. Previous work has shown that unlike TRF1, TRF2 condenses telomeric, thus creating consequential negative torsion on the adjacent DNA, a property that is thought to lead to the stimulation of single-strand invasion and was proposed to favor telomeric DNA looping. In this report, we show that these activities, originating from the central TRFH domain of TRF2, are also displayed by the TRFH domain of TRF1 but are repressed in the full-length protein by the presence of an acidic domain at the N-terminus. Strikingly, a similar repression is observed on TRF2 through the binding of a TERRA-like RNA molecule to the N-terminus of TRF2. Phylogenetic and biochemical studies suggest that the N-terminal domains of TRF proteins originate from a gradual extension of the coding sequences of a duplicated ancestral gene with a consequential progressive alteration of the biochemical properties of these proteins. Overall, these data suggest that the N-termini of TRF1 and TRF2 have evolved to finely regulate their ability to condense DNA.
DRIFTS Sensor: Soil Carbon Validation at Large Scale (Pantelleria, Italy)

A fast and accurate measurement of soil carbon is needed in current scientific issues. Today there are many sensors suitable for these purposes, but choosing the appropriate sensor depends on the spatial scale at which the studies are conducted. There are few detailed studies that validate these types of measures allowing their immediate use. Here it is validated the quick use of a sensor in execution at Pantelleria, chosen for size, use and variability of the parameter measured, to give an operational tool for carbon stocks studies. The DRIFT sensor used here has been validated in the first 60 cm of the soil of the whole island, and it has shown predictivity higher than 90%.
Point Correspondence Validation under Unknown Radial Distortion

Standard two-view epipolar geometry assumes that images are taken using pinhole cameras. Real cameras, however, approximate ideal pinhole cameras using lenses and apertures. This leads to radial distortion effects in images that are not characterisable by the standard epipolar geometry model. The existence of radial distortion severely impacts the efficacy of point correspondence validation based on the epipolar constraint. Many previous works deal with radial distortion by augment- ing the epipolar geometry model (with additional parameters such as distortion coefficients and centre of distortion) to enable the modelling of radial distortion effects. Indirectly, this assumes that an accurate model of the radial distortion is known. In this paper, we take a different approach: we view radial distortion as a violation to the basic epipolar geometry equation. Instead of striving to model radial distortion, we adjust the epipolar geometry to account for the distortion effects. This adjustment is performed via moving least squares (MLS) surface approxi- mation, which we extend to allow for projective estimation. We also combine M-estimators with MLS to allow robust matching of interest points under severe radial distortion. Compared to previous works, our method is much simpler and involves just solving linear subproblems. It also exhibits a higher tolerance in cases where the exact model of radial distortion is unknown.
Chapter 6 The Influence of Collectivism on Microfinance in Senegal

Abstract Microfinance, despite its mixed results in economic literature, continues to proliferate in many developing countries. This research project investigates the relationship between collectivism and microfinance. It analyzes the question: how does a collectivist culture and its norms influence the ways in which borrowers spend loaned funds and interact with microfinance institutions (MFIs)? The authors generate a theoretical model for how norms of informal redistribution affect borrowing decisions and use a robust dataset of all of the loans facilitated by Kiva, a global MFI, to compare microloan borrowing in countries with different cultures of collectivism. A case study of Senegal, a culturally collectivist country, includes surveys and detailed interviews of individuals and MFIs. The authors find that the strong social networks associated with collectivism are well adapted to the structures of many MFIs. However, the authors also uncover that some of the collectivist social norms, such as norms of informal redistribution, can deter individuals from using microfinance.
Comparative Study of BPSK and QPSK for Wireless Networks over NS2

Modulation plays an important role in transmission of single from transmitter to receiver in all communication systems. But it is vital in wireless communication and a lot of communication features including (data rate, error rate, symbol rate, bandwidth etc) depends upon it. In NS2 wireless network simulation BPSK is used for digital encoding and modulation of data [1,2]. The BPSK method is used by wireless/phy object that is inherited by Modulation Class. In this paper QPSK is used in place of BPSK and analyzed in terms of data rate, error rate and power consumption in NS 2 simulation. Also the proposed code for QPSK modulation is given in this paper. General Terms BPSK (Binary Phase Shift Keying), QPSK (Quadrature phase shift keying), Nb (Spectral noise of a single bit), Eb (Bit Energy during transmission), Sb (bit state representation), Pb (Bit Error Rate), φ(t) (signal space).
ON USING BOOTSTRAP APPROACH FOR UNCERTAINTY ESTIMATION

Computer-Intensive methods for estimation assessment provide valuable information concerning the adequacy of applied probabilistic models. The bootstrap method is an extensive computational approach to uncertainty estimation based on resampling and statistical estimation. It is a powerful tool, especially when only a small data set is used to predict the behaviour of systems or processes. This paper provides a methodology to investigate uncertainty evaluation by bootstrap and a procedure to obtain confidence bands for linear and nonlinear models used in data analysis and design measurements. Also statistical considerations for proficiency testing are given. Numerical examples and graphical visualizations will be shown for a case study.
Determination of the essential matrix using discrete and differential matching constraints

We present a method to determine the essential matrix using both discrete and differential matching constraints. Differential constraints, derived from optical flow, are abundant in contrast to the discrete constraints, derived from feature correspondences, which are scarce when just a limited number of salient features are available. We formulate a likelihood of the camera motion given the correspondences of a set of features and the image velocities of these features. We show how this likelihood can be used to determine the essential matrix both in a robust hypothesize-and-test framework, and then in non-linear iterative refinement. Our results show that the use of the extra optical flow constraints gives better estimates of the essential matrix, when compared to using the discrete data alone.
Using social annotations to improve language model for information retrieval

This poster is concerned with the problem of exploring the use of social annotations for improving language models for information retrieval (denoted as LMIR). Two properties of social annotations, namely keyword property and structure property are studied for this aim. The keyword property improves LMIR by concatenating all the annotations of a document to generate a summary of the document. The structure property can boost LMIR further when similarity among annotations and similarity among documents are taken into consideration simultaneously. The two properties of social annotations are leveraged for the use of language modeling with a mixture model named as "Language Annotation Model" (denoted as LAM). Evaluations using del.icio. us data show that LAM outperforms the traditional LMIR approaches significantly.
Movie Recommendation Using Unrated Data

Model based movie recommender systems have been thoroughly investigated in the past few years, and they rely on rating data. In this paper, we take into account unrateddata of genre information to improve the performance of movie recommendation. We propose a novel method to measure users' preference on movie genres, and use Pearson Correlation Coefficient(PCC) to compute the user similarity. A matrix factorization framework is introduced for genre preference regularization. Experimental results on Movie Lens data set demonstrate that the approach performs well. Our method can also be used to increase the genre diversity of recommendations to some extent.
Automated Abstractions for Patrolling Security Games

Recently, there has been a significant interest in studying security games to provide tools for addressing resource allocation problems in security applications. Patrolling security games (PSGs) constitute a special class of security games wherein the resources are mobile. One of the most relevant open problems in security games is the design of scalable algorithms to tackle realistic scenarios. While the literature mainly focuses on heuristics and decomposition techniques (e.g., double oracle), in this paper we provide, to the best of our knowledge, the first study on the use of abstractions in security games (specifically for PSGs) to design scalable algorithms. We define some classes of abstractions and we provide parametric algorithms to automatically generate abstractions. We show that abstractions allow one to relax the constraint of patrolling strategies' Markovianity (customary in PSGs) and to solve large game instances. We additionally pose the problem to search for the optimal abstraction and we develop an anytime algorithm to find it.
An Evidence-Based Research Agenda for Action-Based Entrepreneurship Education

A growing research stream is ‘action-based’ entrepreneurship education, where students actively engage in entrepreneurship and learning is primarily student-centered rather than teacher-led. In the present paper, we look to the practice of teaching in order to clarify key challenges and identify a future research agenda for entrepreneurship education. The research design revolves around a global forum for venture creation programs which consists of eleven programs in six different countries in Europe and North America. The method involves written material in order to develop a model and later semi-structured interviews based on the model. The present paper builds on previous developments within research and teaching practice regarding action-based entrepreneurship education and suggests that further research should focus on (1) students’ perspective in developing strategies to handle venture creation and academic work simultaneously, (2) strategies to develop curriculum, deliverables and assessment schemes that acknowledge the diversity among students’ venture creation processes, (3) development of tailor-made quality assurance and impact measures and (4) exploring the role of faculty in terms of their prior experience and involvement for students’ learning. We suggest that a future research agenda focus on these four issues from the teachers’ point of view, the learners’ point of view and the institutional point of view in a systematic way. Thereby, the present paper contributes to the research field of entrepreneurship education by providing an evidence-based research agenda for entrepreneurship education.
An Exclusion Zone for Ca2+ Channels around Docked Vesicles Explains Release Control by Multiple Channels at a CNS Synapse

The spatial arrangement of Ca2+ channels and vesicles remains unknown for most CNS synapses, despite of the crucial importance of this geometrical parameter for the Ca2+ control of transmitter release. At a large model synapse, the calyx of Held, transmitter release is controlled by several Ca2+ channels in a "domain overlap" mode, at least in young animals. To study the geometrical constraints of Ca2+ channel placement in domain overlap control of release, we used stochastic MCell modelling, at active zones for which the position of docked vesicles was derived from electron microscopy (EM). We found that random placement of Ca2+ channels was unable to produce high slope values between release and presynaptic Ca2+ entry, a hallmark of domain overlap, and yielded excessively large release probabilities. The simple assumption that Ca2+ channels can be located anywhere at active zones, except below a critical distance of ~ 30 nm away from docked vesicles ("exclusion zone"), rescued high slope values and low release probabilities. Alternatively, high slope values can also be obtained by placing all Ca2+ channels into a single supercluster, which however results in significantly higher heterogeneity of release probabilities. We also show experimentally that high slope values, and the sensitivity to the slow Ca2+ chelator EGTA-AM, are maintained with developmental maturation of the calyx synapse. Taken together, domain overlap control of release represents a highly organized active zone architecture in which Ca2+ channels must obey a certain distance to docked vesicles. Furthermore, domain overlap can be employed by near-mature, fast-releasing synapses.
Experience and Activity-Dependent Maturation of Perisomatic GABAergic Innervation in Primary Visual Cortex during a Postnatal Critical Period

The neocortical GABAergic network consists of diverse interneuron cell types that display distinct physiological properties and target their innervations to subcellular compartments of principal neurons. Inhibition directed toward the soma and proximal dendrites is crucial in regulating the output of pyramidal neurons, but the development of perisomatic innervation is poorly understood because of the lack of specific synaptic markers. In the primary visual cortex, for example, it is unknown whether, and to what extent, the formation and maturation of perisomatic synapses are intrinsic to cortical circuits or are regulated by sensory experience. Using bacterial artificial chromosome transgenic mice that label a defined class of perisomatic synapses with green fluorescent protein, here we show that perisomatic innervation developed during a protracted postnatal period after eye opening. Maturation of perisomatic innervation was significantly retarded by visual deprivation during the third, but not the fifth, postnatal week, implicating an important role for sensory input. To examine the role of cortical intrinsic mechanisms, we developed a method to visualize perisomatic synapses from single basket interneurons in cortical organotypic cultures. Characteristic perisomatic synapses formed through a stereotyped process, involving the extension of distinct terminal branches and proliferation of perisomatic boutons. Neuronal spiking in organotypic cultures was necessary for the proliferation of boutons and the extension, but not the maintenance, of terminal branches. Together, our results suggest that although the formation of perisomatic synapses is intrinsic to the cortex, visual experience can influence the maturation and pattern of perisomatic innervation during a postnatal critical period by modulating the level of neural activity within cortical circuits.
HURT GROWTH ? Theory and evidence from 75 aid-recipient countries by

In this paper, foreign aid transfers can distort individual incentives, and hence hurt growth, by encouraging rent seeking as opposed to productive activities. We construct a model of a growing small open economy that distinguishes two effects from foreign transfers: (i) a direct positive effect, as higher transfers allow the financing of infrastructure; (ii) an indirect negative effect, as higher transfers induce rent-seeking competition by self-interested individuals. In this framework, the growth impact of aid is examined jointly with the determination of rent-seeking behavior. We test the main predictions of the model for a crosssection of 75 aid-recipient countries between 1975 and 1995. There is evidence that aid has a direct positive effect on growth, which is however significantly mitigated by the adverse indirect effects of associated rent-seeking activities. This is especially the case in recipient countries with relatively large public sectors.