Miracle-dz/UniFAR-FTUs huggingface dataset:
Developmental risks and psychosocial adjustment among low-income Brazilian youth

Exposure to developmental risks in three domains (community, economic, and family), and relations between risks and psychosocial well-being, were examined among 918 impoverished Brazilian youth aged 14–19 (M = 15.8 years, 51.9% female) recruited in low-income neighborhoods in one city in Southern Brazil. High levels of developmental risks were reported, with levels and types of risks varying by gender, age, and (to a lesser extent) race. Associations between levels of risks in the various domains and indicators of psychological (e.g., self-esteem, negative emotionality) and behavioral (e.g., substance use) adjustment differed for male and female respondents. Findings build on prior research investigating the development of young people in conditions of pervasive urban poverty and reinforce the value of international research in this endeavor.This study was funded by grants from the World Bank and CNPq to Silvia H. Koller. Manuscript preparation was partially supported by a Faculty Development Fellowship to Marcela Raffaelli from the College of Arts and Sciences, University of Nebraska–Lincoln, and by a Visiting Fellowship at the Key Centre for Women's Health in Society, School of Population Health at the University of Melbourne. The authors acknowledge the assistance of J'aims Ribeiro in developing the questionnaire.
Prosocial Goal Pursuit in Crowdfunding: Evidence from Kickstarter

In reward-based crowdfunding, creators of entrepreneurial projects solicit capital from potential consumers to reach a funding goal and offer future products/services in return. The authors examine consumers’ contribution patterns using a novel data set of 28,591 projects collected at 30-minute resolution from Kickstarter. Extending prior research that assumes that economic considerations (e.g., project quality, campaign success likelihood) drive backers’ decisions, the authors provide the cleanest field evidence so far that consumers also have prosocial motives to help creators reach their funding goals. They find that projects collect funding faster right before (vs. right after) meeting their funding goals because consumers not only are more likely to fund projects but also contribute greater amounts of money prior to goal attainment. This effect is amplified when the nature of a project tends to evoke consumers’ prosocial motivation and when a project’s creator is a single person. These results suggest that consumers’ prosocial motives not only play a role in reward-based crowdfunding but also can outweigh the opposing effects of economic factors including rational herding and certainty about campaign success.
Castes in India : implications of social identity in economics

This dissertation is part of the current of thought that aims at reintegrating social identity and institutions in the economic analysis. The first chapter presents a model that describes segregation as one of the equilibria arising from un an unequal distribution of power and without having to specify segregationist preferences. In a second chapter, caste is shown to have a strong impact on the way Scheduled Castes and Tribes perceive their social status. However, other factors such as occupation or income also have an impact on perceived social status. The third chapter shows that there is a relationship between the number of crimes against Scheduled Castes and Tribes and the way water is distributed, thereby evidencing that untouchability practices are still vigorous, despite being outlawed by the Constitution. This suggests that some groups may be excluded from accessing public goods in India that turn out to be club goods. This is further investigated in chapter 4 where results strongly suggest that there is caste patronage in accessing publicly provided goods. In conclusion, we set forth an agenda for future research that resolves around better understanding social identities formation a well as the reasons for their rise.
On the evolution of monetary policy

This paper investigates the evolution of monetary policy in the U.S. using a standard set of macroeconomic variables. Many recent papers have addressed the issue of whether the monetary transmission mechanism has changed (e.g. due to the Fed taking a more aggressive stance against inflation) or whether apparent changes are simply due to changes in the volatility of exogenous shocks. A subsidiary question is whether any such changes have been gradual or abrupt. In this paper, we shed light on these issues using a mixture innovation model which extends the class of time varying Vector Autoregressive models with stochastic volatility which have been used in the past. The advantage of our extension is that it allows us to estimate whether, where, when and how parameter change is occurring (as opposed to assuming a particular form of parameter change). Our empirical results strongly indicate that the transmission mechanism, the volatility of exogenous shocks and the correlations between exogenous shocks are all changing (albeit at different times and to different extents) Furthermore, evolution of parameters is gradual.
Muscular production of individuated finger movements: the roles of extrinsic finger muscles

Individuated finger movements--those in which one or more fingers are moved relatively independently of the movement or posture of other body parts--are produced in part by the action of the extrinsic finger muscles. Flexion/extension movements of the fingers are particularly dependent on these extrinsic muscles, most of which are multitendoned. How can contraction of multitendoned muscles move one digit without producing equivalent motion in other digits? This question was addressed by recording EMG activity from muscles of the forearm as trained rhesus monkeys performed flexion and extension individuated movements of each digit of the hand and of the wrist. Recordings showed that during movements of different fingers, a given muscle could act as an agonist, antagonist, or stabilizer of the digits it serves. Furthermore, during a given finger movement, several different muscles typically were active. A three-level connection model was developed that computed the relative motion of the digits during each finger movement based on the changes in EMG activity in the recorded muscles. The model showed that EMG activity changes in the extrinsic finger muscles, and the thenar muscles, could account for most of the motion of both the instructed digit and noninstructed digits. These results indicate that individuated finger movements were produced not by independent sets of muscles acting on each digit, but by the activity of several muscles, many of which act on more than one digit, combined such that the net effect was movement of one digit more than others.
Protein Depth Calculation and the Use for Improving Accuracy of Protein Fold Recognition

Protein structure and function are largely specified by the distribution of different atoms and residues relative to the core and surface of the molecule. Relative depths of atoms therefore are key attributions that have been widely used in protein structure modeling and function annotation. However, accurate calculation of depth is time consuming. Here, we developed an algorithm which uses Euclidean distance transform (EDT) to convert the target protein structure into a 3D gray-scale image, where depths of atoms in the protein can be conveniently and precisely derived from the minimum distance of the pixels to the surface of the protein. We tested the proposed EDT-based method on a set of 261 non-redundant protein structures, which shows that the method is 2.6 times faster than the widely used method proposed by Chakravarty and Varadarajan. Depth values by EDT method are highly accurate with a Pearson's correlation coefficient ≈1 compared to the calculations from exhaustive search. To explore the usefulness of the method in protein structure prediction, we add the calculated residue depth to the scoring function of the state of the art, profile-profile alignment based fold-recognition program, which shows an additional 3% improvement in the TM-score of the alignments. The data demonstrate that the EDT-based depth calculation program can be used as an efficient tool to assist protein structure analysis and structure-based function annotation.
Visualizing massive multi-digraphs

We describe MGV, an integrated visualization and exploration system for massive multi-digraph navigation. MGV's only assumption is that the vertex set of the underlying digraph corresponds to the set of leaves of a predetermined tree T. MGV builds an out-of-core graph hierarchy and provides mechanisms to plug in arbitrary visual representations for each graph hierarchy slice. Navigation from one level to another of the hierarchy corresponds to the implementation of a drill-down interface. In order to provide the user with navigation control and interactive response, MGV incorporates a number of visualization techniques like interactive pixel-oriented 2D and 3D maps, statistical displays, multi-linked views, and a zoomable label based interface. This makes the association of geographic information and graph data very natural. MGV follows the client-server paradigm and it is implemented in C and Java-3D. We highlight the main algorithmic and visualization techniques behind the tools and point out along the way several possible application scenarios. Our techniques are being applied to multi-graphs defined on vertex sets with sizes ranging from 100 million to 250 million vertices.
Holomorphic Anomaly Of Unitarity Cuts And One-Loop Gauge Theory Amplitudes

We show how the holomorphic anomaly found in hep-th/0409245 can be used to efficiently compute certain classes of unitarity cuts of one-loop N=4 amplitudes of gluons. These classes include all cuts of n-gluon one-loop MHV amplitudes and of n-gluon next-to-MHV amplitudes with helicities (1+,2+,3+,4-,., n-). As an application of this method, we present the explicit computation of the (1,2,3)-cut of the n-gluon one-loop N=4 leading-color amplitude A_{n;1}(1+,2+,3+,4-,., n-). The answer is given in terms of scalar box functions and provides information about the corresponding amplitudes. A possible way to generalize this method to all kinds of unitarity cuts is also discussed.
Topological Properties , Optimal Routing , and Embedding on the K-valent Graph

This paper introduces a new family of Cayley graphs, named the k-valent graph, for building interconnection networks. We show that the k-valent graph possesses many valuable topological properties, such as regular with the node-degree k, logarithmic diameter subject to the number of nodes for some fixed k ≥ 6, and maximally fault tolerance. We also show that the k-valent graph contains trivalent graphs defined in [P. Vadapalli and P. K. Srimani, “Trivalent Cayley graphs for interconnection networks,” Information Processing Letters, vol. 54, pp. 329–335, 1995. ] as its subclass of graphs. An algorithm is proposed to determine a shortest path between arbitrary two nodes. Besides, embedding of cycles or cliques on the kvalent graph is also discussed.
Exponential Synchronization of Coupled Switched Neural Networks With Mode-Dependent Impulsive Effects

This paper investigates the synchronization problem of coupled switched neural networks (SNNs) with mode-dependent impulsive effects and time delays. The main feature of mode-dependent impulsive effects is that impulsive effects can exist not only at the instants coinciding with mode switching but also at the instants when there is no system switching. The impulses considered here include those that suppress synchronization or enhance synchronization. Based on switching analysis techniques and the comparison principle, the exponential synchronization criteria are derived for coupled delayed SNNs with mode-dependent impulsive effects. Finally, simulations are provided to illustrate the effectiveness of the results.
The genealogy of branching processes and the age of our most recent common ancestor

We obtain a weak approximation for the reduced family tree in a near-critical Markov branching process when the time interval considered is long; we also extend Yaglom's theorem and the exponential law to this case. These results are then applied to the problem of estimating the age of our most recent common female ancestor, using mitochondrial DNA sequences taken from a sample of contemporary humans.
Jasmine: a software system modelling facility

<italic>Jasmine</italic> is a programming-in-the-large system designed by the authors at Xerox Information Systems Division. Jasmine consists of workstation tools and network services that help programmers develop, release, and maintain large software systems. Jasmine has three primary parts: <supscrpt>(1)</supscrpt> <italic>system models</italic> that describe the structure and versions of software, <supscrpt>(2)</supscrpt> context-relative, distributed naming of software components (supporting replication), and <supscrpt>(3)</supscrpt> a collection of tools that use (1) and (2) to manipulate software systems. We present an overview of these parts of Jasmine.
Efficient Decoding of Systematic (23, 12, 7) and (41, 21, 9) Quadratic Residue Codes

In this paper, a new algorithms decoding the (23, 12, 7) and the (41, 21, 9) Quadratic Residue (QR) codes are presented. The key ideas behind this decoding technique are based on one-to-one mapping between the syndromes "S 1 " and correctable error patterns. Such algorithms determine the error locations directly by lookup tables without the operations of m ultiplication over a finite fiel d. Moreover, the m ethod of utilizing shift-search algorithm, to dr amatically reduce the memory requirement is given for decoding QR codes. The algorithm has been verified through a software simulation that program in C-language. The new approach is modular, regular and natur al ly suitable for DSP software implementation.
On box-operations for L-Values and their applicability to soft-decision algorithms

Modern digital communication systems can benefit from soft-decision algorithms in receiver implementations. Such algorithms require reliability information about every data bit which is typically given in terms of Log-Likelihood Ratios (LLRs) or short L-Values. Several efficient receiver implementations based on L-Values have already been proposed in the literature. Many of them exploit the famous Box-Plus operation. Its inverse has also been introduced in terms of the Box-Minus operation. In this letter, at first the specific characteristics of both operations, the Box-Plus as well as the Box-Minus operation, will briefly be reviewed. Secondly, as a novelty we will define two more operators, the Box-Multiply and the Box-Divide operation. An illustrative example will demonstrate the necessity for these two new operators. Finally, we will propose a practical solution for eliminating a critical side constraint of the Box-Minus operation which was known to be a limiting factor so far.
Robust Visual Tracking via Exclusive Context Modeling

In this paper, we formulate particle filter-based object tracking as an exclusive sparse learning problem that exploits contextual information. To achieve this goal, we propose the context-aware exclusive sparse tracker (CEST) to model particle appearances as linear combinations of dictionary templates that are updated dynamically. Learning the representation of each particle is formulated as an exclusive sparse representation problem, where the overall dictionary is composed of multiple group dictionaries that can contain contextual information. With context, CEST is less prone to tracker drift. Interestingly, we show that the popular L1 tracker [1] is a special case of our CEST formulation. The proposed learning problem is efficiently solved using an accelerated proximal gradient method that yields a sequence of closed form updates. To make the tracker much faster, we reduce the number of learning problems to be solved by using the dual problem to quickly and systematically rank and prune particles in each frame. We test our CEST tracker on challenging benchmark sequences that involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that CEST consistently outperforms state-of-the-art trackers.
Bringing Instruments to a Service-Oriented Interactive Grid

Current Grid technologies offer unlimited computational power and storage capacity for scientific research and business activities in heterogeneous areas over the world. Thanks to the Grid, different Virtual Organizations can operate together in order to achieve common goals. However, concrete use cases demand a more close interaction between various types of instruments accessible from the Grid, and the classical Grid infrastructure, typically composed of Computing and Storage Elements. We cope with this open problem by proposing and realizing the first release of the Instrument Element (IE), i.e., a new Grid component that provides the Computational/Data Grid with an abstraction of real instruments, and the Grid users with a more interactive interface to control these instruments. In this thesis we describe in detail the proposed software architecture of the IE, also by discussing the functional and non-functional requirements on which its design is based. The non-functional requirements demands not only deep interaction between users and devices to control instruments, but also the adoption of high interoperable solutions, which only Service Oriented Architecture (SOA) based technologies, like Web/Grid Services, can offer. Therefore, in order to solve the trade-off between the necessity of universality/interoperability and performance, we propose a set of solution that improves the performances of a SOA System, in terms of both throughput and latency of service invocations. Moreover, in order to fulfill the Quality of Service (QoS) nonfunctional requirement, we also devise a methodology that allows remote method execution times to be predicted. This makes it possible, for example, to select an alternative service that better guarantees the fulfilment of execution deadlines. Still according to our analysis of non-functional requirements, we also address the problem of determining fast communication methods to permit instruments to properly inter-operate. In this regard, we investigate different publish/subscribe architectures, and we show that RMM-JMS is the best candidate solution for accomplishing this task. It is worth noting that even though all these solutions and results have been motivated, devised and exploited during the design of our IE, any application based on Web and Grid Services can benefit from them. Finally, all our proposals are validated using suitable benchmarks and extensive tests and comparison with alternative solutions.
Audiovisual Person Tracking with a Mobile Robot

Mobile service robots are recently gaining increased attention from industry as they are envisaged as a future market. Such robots need natural interaction capabilities to allow unexperienced users to make use of these robots in home and office environments. In order to enable the interaction between humans and a robot, the detection and tracking of persons in the vicinity of the robot is necessary. In this paper we present a person tracking system for a mobile robot which enables the robot to track several people simultaneously. Our approach is based on a variety of input cues that are fused using a multi-modal anchoring framework. The sensors providing input data are two microphones for sound source localization, a pan-tilt camera for face and torso recognition, and a laser range finder for leg detection. Through processing camera images to extract the torso position, our robot can follow a person guiding the robot that is not oriented towards the robot and that is not speaking. In this case the torso information is especially important for robust tracking during temporary failure of the leg detection.
Adaptive backstepping control of linear motor based on Maxwell slip model of friction

The purpose of this paper is to demonstrate possibility of using Maxwell slip model together with adaptive backstepping to improve performance of linear motor velocity control. We consider a simplified model of a permanent magnet linear motor powered by a PWM inverter. We formulate the control algorithm and prove its stability by Lyapunov function approach, and finally we describe several numerical experiments demonstrating maim features of the proposed control and the influence of the parameters.
Disease Animal Models of TDP-43 Proteinopathy and Their Pre-Clinical Applications

Frontotemperal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) are two common neurodegenerative diseases. TDP-43 is considered to be a major disease protein in FTLD/ALS, but it’s exact role in the pathogenesis and the effective treatments remains unknown. To address this question and to determine a potential treatment for FTLD/ALS, the disease animal models of TDP-43 proteinopathy have been established. TDP-43 proteinopathy is the histologic feature of FTLD/ALS and is associated with disease progression. Studies on the disease animal models with TDP-43 proteinopathy and their pre-clinical applications are reviewed and summarized. Through these disease animal models, parts of TDP-43 functions in physiological and pathological conditions will be better understood and possible treatments for FTLD/ALS with TDP-43 proteinopathy may be identified for possible clinical applications in the future.
Segment optimisation for object - based landslide detection

Advances in remote sensing technology and image analysis systems have led to an increase in automatic feature extraction technique for several novel applications. Object-oriented analysis (OOA) of high resolution remote sensing data is one such technique, wherein objects/segments are the image primitives that form the basis for automatic feature extraction, and thus have critical influence on the accuracy of the subsequent processing. In this study we assess how the fractal net evolution segmentation approach, embedded in Definiens Developer, can be optimised for automatic detection of landslides. Landslides are important natural mass wasting processes, and their fast detection using high resolution satellite and elevation data can inform disaster mitigation strategies. In recent work we showed how spectral, contextual and morphometric information can be successfully used to detect and characterise landslides of different types. However, given the complex shape and size of landslides, as well as their spectral heterogeneity, segmentation with a single set of parameters is not possible and remains a weakness in our method. Here we assess multiple segmentation strategies to derive an appropriate segmentation for various classes to be identified in subsequent rule-based classification. Segments were subjected to spatial autocorrelation analysis using Moran’s I index and intrasegment variance analysis to optimise the parameter selection for multiresolution segmentation. Instead of one object level pertaining to a single parameter, multiple object levels with a set of optimum parameters were used to detect landslides of variable sizes. We test our approaches with Resourcesat-1 LISS-IV multispectral imagery (5.8 m) and a 10 m DEM derived from 2.5 m stereoscopic Cartosat-1 data for two landslide prone areas in the High Indian Himalayas. * Corresponding author.