Miracle-dz/UniFAR-FTUs huggingface dataset:
[16] Modeling Polyglutamine Pathogenesis in C. Elegans

A growing number of human neurodegenerative diseases are associated with disruption of cellular protein folding homeostasis, leading to the appearance of misfolded proteins and deposition of protein aggregates and inclusions. Recent years have been witness to widespread development of invertebrate systems (specifically Drosophila and Caenorhabditis elegans) to model these disorders, bringing the many advantages of such systems, particularly the power of genetic analysis in a metazoan, to bear on these problems. In this chapter, we describe our studies using the nematode, C. elegans, as a model to study polyglutamine expansions as occur in Huntington’s disease and related ataxias. Using fluorescently tagged polyglutamine repeats of different lengths, we have examined the dynamics of aggregate formation both within individual cells and over time throughout the lifetime of individual organisms, identifying aging as an important physiological determinant of aggregation and toxicity. Expanding on these observations, we demonstrate that a genetic pathway regulating longevity can alter the time course of aging‐related polyglutamine‐mediated phenotypes. To identify novel targets and better understand how cells sense and respond to the appearance of misfolded and aggregation‐prone proteins, we use a genome‐wide RNA interference‐based genetic screen to identify modifiers of age‐dependent polyglutamine aggregation. Throughout these studies, we used fluorescence‐based, live‐cell biological and biophysical methods to study the behavior of these proteins in a complex multicellular environment.
Realistic Yukawa structures from orientifold compactifications

We perform a systematic analysis of globally consistent D-brane quivers which realize the MSSM and analyze them with respect to their Yukawa couplings. Often, desired couplings are perturbatively forbidden due to the presence of global U(1) symmetries. We investigate the conditions under which D-brane instantons will induce these missing couplings without generating other phenomenological drawbacks, such as R-parity violating couplings or a ? -term which is too large. Furthermore, we systematically analyze which quivers allow for a mechanism that can account for the small neutrino masses and other experimentally observed hierarchies. We show that only a small fraction of the globally consistent D-brane quivers exhibits phenomenology compatible with experimental observations.
Organization of visual inputs to the inferior temporal and posterior parietal cortex in macaques

It has been proposed that visual information in the extrastriate cortex is conveyed along 2 major processing pathways, a “dorsal” pathway directed to the posterior parietal cortex, underlying spatial vision, and a “ventral” pathway directed to the inferior temporal cortex, underlying object vision. To determine the relative distributions of cells projecting to the 2 pathways, we injected the posterior parietal and inferior temporal cortex with different fluorescent tracers in 5 rhesus monkeys. The parietal injections included the ventral intraparietal (VIP) and lateral intraparietal (LIP) areas, and the temporal injections included the lateral portions of cytoarchitectonic areas TE and TEO. There was a remarkable segregation of cells projecting to the 2 systems. Inputs to the parietal cortex tended to arise either from areas that have been implicated in spatial or motion analysis or from peripheral field representations in the prestriate cortex. By contrast, inputs to the temporal cortex tended to arise from areas that have been implicated in form and color analysis or from central field representations. Cells projecting to the parietal cortex were found in visual area 2 (V2), but only in the far peripheral representations of both the upper and lower visual field. Likewise, labeled cells found in visual areas 3 (V3) and 4 (V4) were densest in their peripheral representations. Heavy accumulations of labeled cells were found in the dorsal parieto-occipital cortex, including the parieto-occipital (PO) area, part A of V3 (V3A), and the dorsal prelunate area (DP). In the superior temporal sulcus, cells were found within several motion-sensitive areas, including the middle temporal area (MT), the medial superior temporal area (MST), the fundus of the superior temporal area (FST), and the superior temporal polysensory area (STP), as well as within anterior portions of the sulcus whose organization is as yet poorly defined. Cells projecting to areas TE and TEO in the temporal cortex were located within cytoarchitectonic area TG at the temporal pole and cytoarchitectonic areas TF and TH on the parahippocampal gyrus, as well as in noninjected portions of area TE buried within the superior temporal sulcus. In the prestriate cortex, labeled cells were found in V2, V3, and V4, but, in contrast to the loci labeled after parietal injections, those labeled after temporal injections were concentrated in the foveal or central field representations. Although few double-labeled cells were seen, 2 regions containing intermingled parietal- and temporal-projection cells were area V4 and the cortex at the bottom of the anterior superior temporal sulcus. (ABSTRACT TRUNCATED AT 400 WORDS)
Geometric Data Structures and Their Selected Applications

(cid:3) Abstract — Finding the shortest path between two positions is a fundamental problem in transportation, routing, and communications applications. In robot motion planning, the robot should pass around the obstacles touching none of them, i.e. the goal is to find a collision-free path from a starting to a target position. This task has many specific formulations depending on the shape of obstacles, allowable directions of movements, knowledge of the scene, etc. Research of path planning has yielded many fundamentally different approaches to its solution, mainly based on various decomposition and roadmap methods. In this paper, we show a possible use of visibility graphs in point-to-point motion planning in the Euclidean plane and an alternative approach using Voronoi diagrams that decreases the probability of collisions with obstacles. The second application area, investigated here, is focused on problems of finding minimal networks connecting a set of given points in the plane using either only straight connections between pairs of points (minimum spanning tree) or allowing the addition of auxiliary points to the set to obtain shorter spanning networks (minimum Steiner tree).
Robust Visual Tracking via Convolutional Networks Without Training

Deep networks have been successfully applied to visual tracking by learning a generic representation offline from numerous training images. However, the offline training is time-consuming and the learned generic representation may be less discriminative for tracking specific objects. In this paper, we present that, even without offline training with a large amount of auxiliary data, simple two-layer convolutional networks can be powerful enough to learn robust representations for visual tracking. In the first frame, we extract a set of normalized patches from the target region as fixed filters, which integrate a series of adaptive contextual filters surrounding the target to define a set of feature maps in the subsequent frames. These maps measure similarities between each filter and useful local intensity patterns across the target, thereby encoding its local structural information. Furthermore, all the maps together form a global representation, via which the inner geometric layout of the target is also preserved. A simple soft shrinkage method that suppresses noisy values below an adaptive threshold is employed to de-noise the global representation. Our convolutional networks have a lightweight structure and perform favorably against several state-of-the-art methods on the recent tracking benchmark data set with 50 challenging videos.
Simulated Annealing for Optimization of Wind Farm Annual Profit

In this paper, a simulated annealing is designed and applied to compute the optimal placement of wind turbines in a wind farm. The objetive of this process is to find a combination of aero-generators that maximizes the annual profit obtained from a wind farm, measured as the generated power in one year. Simulated annealing (SA) is a metaheuristic for global optimization that we will use here to search in the large landscape of possible solutions. Maximizing the generated power depends on the distribution of the aero-generators and the geometry of the wind farm. In this article we analyze several case studies according to different wind conditions. We will show optimal solutions and prove that they are better concerning the present best result in the literature.
Fast Monte Carlo localization of AUV using acoustic range measurement

This paper presents a novel online nonlinear Monte Carlo algorithm for multi-sensor autonomous underwater vehicle (AUV) navigation. The approach integrates the global constraints of range to, and GPS position of, multiple surface vehicles communicated via acoustic modems and relative pose constraints arising from observations of multiple beacon boats. The proposed method can be used to more accurately navigate the AUV, to extend mission duration, and to avoid surfacing for GPS fixes. The Monte Carlo method is used for the estimation of the AUV pose. Although it is also desirable to estimate the range measurement of the surface vehicles using a particle filter (PF), implementing a PF for each beacon onboard the AUV is computationally expensive. Thus for the range estimation, an extended Kalman filter (EKF) is proposed for each beacon. We discuss why our approach is more computationally efficient and suitable for use on underwater vehicles. Simulation results are provided for AUV navigation using multiple autonomous surface vehicles (ASVs) in an ocean environment. During these simulations the proposed algorithm runs online on-board the AUV. In-water validation is currently in progress.
UML Model Based Design of the Claw Car Robot

Robots are intricate systems and applied in many aspects of today’s society. It is highly desirable to design and develop robust robotics systems. This paper aims at developing an autonomous robotic system using objectoriented software development (OOSD) methodology – UML – to ensure the quality of the system. Unified Modeling Language (UML), a typical OOSD method, is a standard visualization language for object-oriented system development that has been widely used in the design of safety critical and mission critical systems (e.g. aeronautic systems, missile defense systems, etc). In this paper, the UML class diagram is used to represent the static structure and relations of objects. The dynamic behavior is modeled in the state machine diagram. A case study is performed in the LEGO NXT tool kit, a low cost highly integrated educational robot setting, in Java programming language. In this case study, a Claw Car Robot is designed and assembled with the function of continuously moving forward and stop on the color definition. The robot can close the claw and clasp the object in its path once an object is detected. The LEGO NXT tool kit includes multiple sensors and supported by several platforms including Java and C++. This LEGO NXT tool kit is very convenient for the design and implementation of robotics systems, and has been widely adopted in institutions for educational and initial
Intergenerational Mobility Under Private vs. Public Education

Intergenerational earnings mobility is analyzed in a model where human capital is produced using schooling and parental time. In steady states more mobile societies have less inequality, but in the short run higher mobility may result from an increase in inequality. Starting from the same inequality, mobility is higher under public than under private education. A rise in income shocks, for example due to increased returns to ability, or a switch from public to private schooling both increase inequality. However, increased shocks raise mobility in the short run and do not affect it in the long run, whereas an increased role for private schooling reduces mobility in both the short and long run. That these differences may help to identify the source of changes in inequality, and other real-world implications, are illustrated in a brief discussion of time trends and cross-country differences.
Compliance Mixture Modelling with a Zero‐Effect Complier Class and Missing Data

Summary Randomized experiments are the gold standard for evaluating proposed treatments. The intent to treat estimand measures the effect of treatment assignment, but not the effect of treatment if subjects take treatments to which they are not assigned. The desire to estimate the efficacy of the treatment in this case has been the impetus for a substantial literature on compliance over the last 15 years. In papers dealing with this issue, it is typically assumed there are different types of subjects, for example, those who will follow treatment assignment (compliers), and those who will always take a particular treatment irrespective of treatment assignment. The estimands of primary interest are the complier proportion and the complier average treatment effect (CACE). To estimate CACE, researchers have used various methods, for example, instrumental variables and parametric mixture models, treating compliers as a single class. However, it is often unreasonable to believe all compliers will be affected. This article therefore treats compliers as a mixture of two types, those belonging to a zero‐effect class, others to an effect class. Second, in most experiments, some subjects drop out or simply do not report the value of the outcome variable, and the failure to take into account missing data can lead to biased estimates of treatment effects. Recent work on compliance in randomized experiments has addressed this issue by assuming missing data are missing at random or latently ignorable. We extend this work to the case where compliers are a mixture of types and also examine alternative types of nonignorable missing data assumptions.
Mechanism of Bacterial Inactivation by (+)-Limonene and Its Potential Use in Food Preservation Combined Processes

This work explores the bactericidal effect of (+)-limonene, the major constituent of citrus fruits' essential oils, against E. coli. The degree of E. coli BJ4 inactivation achieved by (+)-limonene was influenced by the pH of the treatment medium, being more bactericidal at pH 4.0 than at pH 7.0. Deletion of rpoS and exposure to a sub-lethal heat or an acid shock did not modify E. coli BJ4 resistance to (+)-limonene. However, exposure to a sub-lethal cold shock decreased its resistance to (+)-limonene. Although no sub-lethal injury was detected in the cell envelopes after exposure to (+)-limonene by the selective-plating technique, the uptake of propidium iodide by inactivated E. coli BJ4 cells pointed out these structures as important targets in the mechanism of action. Attenuated Total Reflectance Infrared Microspectroscopy (ATR-IRMS) allowed identification of altered E. coli BJ4 structures after (+)-limonene treatments as a function of the treatment pH: β-sheet proteins at pH 4.0 and phosphodiester bonds at pH 7.0. The increased sensitivity to (+)-limonene observed at pH 4.0 in an E. coli MC4100 lptD4213 mutant with an increased outer membrane permeability along with the identification of altered β-sheet proteins by ATR-IRMS indicated the importance of this structure in the mechanism of action of (+)-limonene. The study of mechanism of inactivation by (+)-limonene led to the design of a synergistic combined process with heat for the inactivation of the pathogen E. coli O157:H7 in fruit juices. These results show the potential of (+)-limonene in food preservation, either acting alone or in combination with lethal heat treatments.
Manubuild Construction Site Training Simulator for Offsite Manufacturing

The ManuBuild Construction Site Training Simulator provides a virtual environment for practicing new practice-based skills associated with off-site production. The ‘scenes’ of this simulator take place on a virtual construction site, and mainly targets professionals i.e. project managers, construction managers, architects, designers, suppliers, manufacturers etc. Thus, construction-related problems (e.g. key decisions, connectivity problems, faulty work, health and safety etc) can be simulated in respect of time, cost and resources (without the associated risks often associated with ‘learning-by-doing’). In this respect, the aim of this simulator is not to resolve the problems of using offsite manufacturing (OSM) per se, it does however provide a medium through which users can experience how things can go ‘wrong’ along with the resulting implications.
Improved sequence‐based prediction of protein secondary structures by combining vacuum‐ultraviolet circular dichroism spectroscopy with neural network

Synchrotron‐radiation vacuum‐ultraviolet circular dichroism (VUVCD) spectroscopy can significantly improve the predictive accuracy of the contents and segment numbers of protein secondary structures by extending the short‐wavelength limit of the spectra. In the present study, we combined VUVCD spectra down to 160 nm with neural‐network (NN) method to improve the sequence‐based prediction of protein secondary structures. The secondary structures of 30 target proteins (test set) were assigned into α‐helices, β‐strands, and others by the DSSP program based on their X‐ray crystal structures. Combining the α‐helix and β‐strand contents estimated from the VUVCD spectra of the target proteins improved the overall sequence‐based predictive accuracy Q3 for three secondary‐structure components from 59.5 to 60.7%. Incorporating the position‐specific scoring matrix in the NN method improved the predictive accuracy from 70.9 to 72.1% when combining the secondary‐structure contents, to 72.5% when combining the numbers of segments, and finally to 74.9% when filtering the VUVCD data. Improvement in the sequence‐based prediction of secondary structures was also apparent in two other indices of the overall performance: the correlation coefficient (C) and the segment overlap value (SOV). These results suggest that VUVCD data could enhance the predictive accuracy to over 80% when combined with the currently best sequence‐prediction algorithms, greatly expanding the applicability of VUVCD spectroscopy to protein structural biology. Proteins 2008. © 2008 Wiley‐Liss, Inc.
Experiments on Document Chunking and Query Formation for Plagiarism Source Retrieval

This paper presents the details of the system we prepare as a participant of the PAN 2014 task on 'Source Retrieval: Uncovering Plagiarism, Authorship, and Social Software Misuse'. Our work is focused on intelligent chunking of suspicious documents and a hybrid approach of query formation. A method based on term frequency and word co-occurrence is proposed to extract query terms from a non-overlapping chunk of topically related sentences. The queries are then submitted to the ChatNoir search API to retrieve documents that are likely to be the sources of plagiarism. Finally a snippet matching and duplicate download restriction based filtering technique reduces the number of downloads. The evaluation results of the PAN14 Source Retrieval task show that the performance of our system is highly promising. The f-measure accuracy of the system is . 3871 with a recall of . 5083 which is the highest among all the participants.
Active shape model-based user identification for an intelligent wheelchair

Recently, some novel human-machine interfaces (HMI) have been created for disabled and elderly people to control intelligent wheelchairs (IW) using facial and head gestures. To operate a wheelchair in this new visual-based control mode, user identification should be conducted beforehand. Rather than traditional user identification that requires the user to input his/her username and password by typing, the state-of-the-art biometric-based user identification provides a more convenient way for the disabled users. This paper first elaborates active shape model in details; then, video-based user identification using Mahalanobis distance is presented. As an extension, an adaptive learning module is designed to append or update the user’s face record in the constructed face database. Experimental results show that our login subsystem is able to function well for a comparatively small face database.
The Effect of Payments for Ecosystem Services Programs on the Relationship of Livelihood Capital and Livelihood Strategy among Rural Communities in Northwestern China

The security and quality of livelihoods for peasant households is the core issue for rural areas in China. A stable livelihood contributes to the harmonious development of related polices, poverty eradication and sustainable use of resources. In Qinghe County, located in the extremely arid zone of Northwest China, 238 validated surveys were conducted. The analysis focuses on the importance of livelihood capitals for the selection of on- or off-farm livelihood strategies among beneficiaries of different kinds of ecological compensation packages. The goal is to see if different groups of beneficiaries are better able to pursue off-farm livelihoods activity, which reduces pressure on the resource base, and whether specific capitals are especially effective in helping households pursue off-farm livelihoods, which benefits their well-being. The findings show that proportionally more herdsmen (who participated in a pastureland rehabilitation program) were able to pursue off-farm livelihoods than farmers (who participated in the cultivated land reforestation program), and especially agro-pastoralists (who participated in both programs). Further, models of livelihood strategy show that human and financial capitals facilitate off-farm livelihoods, while productive capital tends to lead to on-farm livelihoods. These findings indicate that there is no single determinant of livelihood strategy, and future policies must consciously differentiate among beneficiaries to reach the desired result.
The Influence of El Niñ O–southern Oscillation and the Atlantic Multidecadal Oscillation on Caribbean Tropical Cyclone Activity

Caribbean basin tropical cyclone activity shows significant variability on interannual as well as multidecadal time scales. Comprehensive statistics for Caribbean hurricane activity are tabulated, and then large-scale climate features are examined for their impacts on this activity. The primary interannual driver of variability is found to be El Niñ o–Southern Oscillation, which alters levels of activity due to changes in levels of vertical wind shear as well as through column stability. Much more activity occurs in the Caribbean with La Niñ a conditions than with El Niñ o conditions. On the multidecadal time scale, the Atlantic multidecadal oscillation is shown to play a significant role in Caribbean hurricane activity, likely linked to its close relationship with multidecadal alterations in the size of the Atlantic warm pool and the phase of the Atlantic meridional mode. When El Niñ o–Southern Oscillation and the Atlantic multidecadal oscillation are examined in combination, even stronger relationships are found due to a combination of either favorable or unfavorable dynamic and thermodynamic factors. For example, 29 hurricanes tracked into the Caribbean in the 10 strongest La Niñ a years in a positive Atlantic multidecadal oscillation period compared with only two hurricanes tracking through the Caribbean in the 10 strongest El Niñ o years in a negative Atlantic multidecadal oscillation period.