Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute cholinergic rescue of synaptic plasticity in the neurodegenerating cortex of anti‐nerve‐growth‐factor mice

Deficits in cholinergic systems innervating cerebral cortex are associated with cognitive impairment during senescence and in age‐related neurodegenerative pathologies. However, little is known about the role of cholinergic pathways in modulating cortical plasticity. Basal forebrain cholinergic neurons are a major target for nerve‐growth factor (NGF). In order to investigate the relationship between cholinergic innervation and cortical synaptic plasticity, we exploited a transgenic mouse model in which the activity of NGF in the adult nervous system is neutralized by the expression of blocking antibodies to NGF itself (anti‐NGF mice) [Ruberti, F. et al. (2000). J. Neurosci. 20, 2589–2601]. In 6‐month‐old anti‐NGF mice, we show that the reduction in cholinergic innervation of the cortex is associated with different forms of synaptic plasticity impairment. A local, acute increase in the availability of acetylcholine rescues these synaptic plasticity deficits, thus indicating that a cholinergic system mediates the impairment of cortical plasticity at this early stage of the neurodegenerative process triggered by NGF neutralization. Our results represent an important step in unveiling the pivotal role of cholinergic transmission in modulating adult cortical plasticity.
Structural Parameter Optimization of Multilayer Conductors in HTS Cable

In this paper, the design optimization of the structural parameters of multilayer conductors in high temperature superconducting (HTS) cable is reviewed. Various optimization methods, such as the particle swarm optimization (PSO), the genetic algorithm (GA), and a robust optimization method based on design for six sigma (DFSS), have been applied to realize uniform current distribution among the multi- layer HTS conductors. The continuous and discrete variables, such as the winding angle, radius, and winding direction of each layer, are chosen as the design parameters. Under the constraints of the mechanical properties and critical current, PSO is proven to be a more powerful tool than GA for structural parameter optimization, and DFSS can not only achieve a uniform current distribution, but also improve significantly the reliability and robustness of the HTS cable quality.
Control system for the waterjet cutting Machine

This paper addresses the field of factory automation within the scope of machine control. It presents the control system for a waterjet cutting machine. It involves a PC based computer numerical control (CNC) controller that has been built on a QNX real-time (RT) operating system platform. Microsoft Windows, which is a commonly accepted graphical user interface environment, serves as a human machine interface (HMI) front-end. The CNC controller and the HMI are interconnected by the Ethernet TCP/IP link. The control system is flexible and modular. It supports CAD/CAM and a network link to the office-level of factory automation. The application is thoroughly presented with the highlight on RT features; the QNX RT operating system is analyzed in detail. Moreover, Ethernet TCP/IP technology for the use in a networked automated factory is also put in the foreground.
Tracking changes in functional connectivity of brain networks from resting-state fMRI using particle filters

Recent empirical research has discovered that linkages among fMRI signals of the brain in resting-state have meaningful temporal variations. Most current studies of brain networks assume that these linkages are constant. We propose a model and an accompanying algorithm to infer and track changes in these interaction strengths, thus providing a more comprehensive way to study brain dynamics. The stochastic model employed is akin to one used for neuronal states (DCM) and a Rao-Blackwellized filtering algorithm is set up for tracking purposes. Our results show that time-varying interactions among brain regions can be successfully found which have the potential of providing great clinical value.
Modeling and Evaluation of a Streaming Traffic Controller for Vehicular Ad-Hoc Networks

In this paper we model the data traffic congestion scenario in a vehicular ad-hoc network, and we apply the Adaptive PI Rate Controller (APIRATE) to deal with the congestion. Derived from classical control theory, the APIRATE controller performs AQM (Active Queue Management) by controlling the source rate based on the instantaneous queue length of the congested node. We then study the performance of this controller in a mobile rural scenario, and show that it has better performance for streaming traffic when compared with other existing controller.
'The Millennials are Coming!': Improving Self-Efficacy in Law Students Through Universal Design in Learning

The Millennial generation has arrived in law school. This new generation of self-confident and extremely high-achieving learners merits a new interdisciplinary approach to legal education. Some institutions have explored formative assessments and regulated self-learning to improve academic success. Other universities have looked to universal design, specifically universal design in learning or universal design in instruction, as a mechanism for furthering educational goals for their students. All agree that a lack of self-efficacy can prevent Millennial students from overcoming challenges in their educational growth, and that high self-efficacy, the ability to put forth effort and persistence to successfully accomplish a goal, will lead to better learning outcomes and is a powerful predictor of educational success. None, however, have paired the theories of self-regulated learning and universal design in instruction as a vehicle to improve self-efficacy in the law school classroom. This article is the first to address the unique intersection of these learning theories and their potentially positive impact on self-efficacy for today’s learners.
Strong tracking finite-difference extended Kalman filtering for ballistic target tracking

This paper studies the problem of tracking a ballistic target in the reentry phase. We propose an adaptive algorithm, strong tracking finite-difference extended Kalman filter (STFDEKF), for ballistic target tracking in reentry. This method uses polynomial approximations obtained with a Sterling interpolation formula to approximate the derivative of the nonlinear function, and uses strong tracking factors to modify the prior covariance matrix. The proposed algorithm improves the tracking accuracy, enlarges the applied area and enhances the filtering convergence. We compare the performance of the proposed algorithm with that of the extended Kalman filter (EKF) and the finite-difference extended Kalman filter (FDEKF) using a Monte Carlo simulation. The simulation results show that STFDEKF outperforms EKF and FDEKF in terms of tracking accuracy and filter credibility, although it has higher computational cost. We conclude that the STFDEKF is an effective algorithm for the ballistic target tracking problem being studied.
Design and realization of a PM linear synchronous motor with a very high thrust/normal force ratio

An important drawback in PM linear synchronous motor applications is the high normal force (compared to the thrust developed by the motor itself) due to the stator-cursor magnetic attraction. A new linear motor with a very high thrust/normal force ratio has been designed and a prototype has been constructed. The motor is a PM linear synchronous motor with the PMs mounted on an ironless cursor. The motor performance have been evaluated in terms of generated forces (thrust and normal force) considering the values obtained by simulations and laboratory tests. Laboratory generated forces measurements have been performed by an "ad hoc" instrumentation described in the paper itself.
Preliminary Version Specifications using XQuery Expressions on Traces

This paper contributes to the interoperability of web services by proposing the flexible specification technique SXQT in conjunction with the automatic validation, a straightforward approach for detecting non-conformance. SXQT allows different levels of abstraction by specifying individual requirements on a web service’s protocol, i.e. its SOAP messages and behaviour including SOAP modules. The automatic validation detects non-conformance by comparing occurring message sequences with the protocol’s specification.
2.4 GHz / 3.5 GHz dual-band wide-tuning-range quadrature VCO using harmonic-injection coupling technique

In this paper, a dual-band wide-tuning-range quadrature VCO (QVCO) using a harmonic-injection coupling technique is proposed. The tuning range of a switched-capacitor and a switched-inductor LC-tank are investigated. Based on the investigation, a switched-inductor tank is employed since it provides a wide tuning range. A harmonic-injection coupling technique, which eliminates the noise sources of coupling transistors, is applied to generate the quadrature outputs. The QVCO is designed for 3.5GHz WiMAX and 2.4 GHz ISM applications. A tuning range of 24.9% and 20.7% are obtained. The measured phase noise is -123.5 dBc/Hz and -125.9 dBc/Hz at a 1MHz offset, respectively. Significant FOMT of -191.7 and -192.4 are achieved.
Simpler Analyses of Local Search Algorithms for Facility Location

We study local search algorithms for metric instances of facility location problems: the uncapacitated facility location problem (UFL), as well as uncapacitated versions of the $k$-median, $k$-center and $k$-means problems. All these problems admit natural local search heuristics: for example, in the UFL problem the natural moves are to open a new facility, close an existing facility, and to swap a closed facility for an open one; in $k$-medians, we are allowed only swap moves. The local-search algorithm for $k$-median was analyzed by Arya et al. (SIAM J. Comput. 33(3):544-562, 2004), who used a clever ``coupling'' argument to show that local optima had cost at most constant times the global optimum. They also used this argument to show that the local search algorithm for UFL was 3-approximation; their techniques have since been applied to other facility location problems. In this paper, we give a proof of the $k$-median result which avoids this coupling argument. These arguments can be used in other settings where the Arya et al. arguments have been used. We also show that for the problem of opening $k$ facilities $F$ to minimize the objective function $\Phi_p(F) = \big(\sum_{j \in V} d(j, F)^p\big)^{1/p}$, the natural swap-based local-search algorithm is a $\Theta(p)$-approximation. This implies constant-factor approximations for $k$-medians (when $p=1$), and $k$-means (when $p = 2$), and an $O(\log n)$-approximation algorithm for the $k$-center problem (which is essentially $p = \log n$).
Speaking of Values: The Framing of American Politics

be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher, bepress, which has been given certain exclusive rights by the author. The Forum is produced by The Berkeley Electronic Press (bepress).
Novel Backprojection Method for Monocular Head Pose Estimation

Estimating a driver’s head pose is an important task in driver-assistance systems because it can provide information about where a driver is looking, thereby giving useful cues about the status of the driver (i.e., paying proper attention, fatigued, etc.). This study proposes a system for estimating the head pose using monocular images, which includes a novel use of backprojection. The system can use a single image to estimate a driver’s head pose at a particular time stamp, or an image sequence to support the analysis of a driver’s status. Using our proposed system, we compared two previous pose estimation approaches. We introduced an approach for providing ground-truth reference data using a mannequin model. Our experimental results demonstrate that the proposed system provides relatively accurate estimations of the yaw, tilt, and roll angle. The results also show that one of the pose estimation approaches (perspective-n-point, PnP) provided a consistently better estimate compared to the other (pose from orthography and scaling with iterations, POSIT) using our proposed system.
An Operations Perspective on Product Take‐Back Legislation for E‐Waste: Theory, Practice, and Research Needs

Agrowing stream of environmental legislation enforces collection and recycling of used electrical and electronics products. Based on our experiences with producers coping with e-waste legislation, we find that there is a strong need for research on the implications of such legislation from an operations perspective. In particular, as a discipline at the interface of systems design and economic modeling, operations focused research can be extremely useful in identifying appropriate e-waste take-back implementations for different business environments and how producers should react to them.
Inter-Event Dependencies support Event Extraction from Biomedical Literature

The description of events in biomedical literature often follows discourse patterns. For example, authors may firstly mention the transcription of a gene, and then go on to describe how this transcription is regulated by another gene. Capturing such patterns can be beneficial when we want to extract event mentions from literature. For instance, detecting the mention of a transcription of gene A gives us a hint to actively look for mentions of regulations involving A. With this hint we could find such mentions even if they follow unseen lexical or syntactic patterns. To exploit such hints we need to perform event extraction in a cross sentence manner. It is shown that imperatively defined factor graphs (IDF) are an intuitive way to build Markov Networks that model inter-dependencies between mentions of events within sentences, and across sentence-boundaries. Small pieces of procedural code define the graph structure, feature functions and hooks for efficient inference. Empirically, this leads to an efficient cross-sentence event extractor with very competitive results on the BioNLP shared task. One of our inter-event features shows an impact of 1:94 points in F1 for the class of regulation events.
Speaker Modeling Using Local Binary Decisions

Achieving an accurate speaker modeling is a crucial step in any speaker-related algorithm. Many statistical speaker modeling techniques that deviate from the classical GMM/UBM approach have been proposed for some time now that can accurately discriminate between speakers. Although many of them imply the evaluation of high dimensional feature vectors and represent a speaker with a single vector, therefore not using any temporal information. In addition, they place most emphasis on modeling the most recurrent acoustic events, instead of less occurring speaker discriminant information. In this paper we explain the main benefits of our recently proposed binary speaker modeling technique and show its benefits in two particular applications, namely for speaker recognition and speaker diarization. Both applications achieve near to state-of-the-art results while benefiting from performing most processing in the binary space.
SNOW MASS RETRIEVAL BY MEANS OF SAR INTERFEROMETRY

The feasibility for retrieving the mass of snow on ground (the snow water equivalent, SWE) by means of repeat-pass SAR interferometry has been investigated. Because the SAR signal of ground covered by dry snow is dominated by backscatter from the snow/ground interface, the differential phase shift due to propagation in the snow can be directly related to SWE. The factors of relevance for coherence of snow covered areas were studied by theoretical modeling and analysis of repeat pass SAR data, showing that the C-band coherence often deteriorates rapidly in case of snow fall whereas coherence is much better preserved at L-band. Case studies on SWE retrieval are presented for 3-day repeatpass ERS SAR data of the Austrian Alps and 4-month repeat-pass L-band airborne SAR data of Oberpfaffenhofen. The investigations confirm the potential of repeat-pass InSAR data for mapping SWE with high spatial detail, suggesting clear preference for L-band. For fully assessing the InSAR capabilities for SWE retrieval, dedicated experiments with co-located, spatially detailed field measurements need to be carried out.
Technical Note : Algorithms for Optimal Dyadic Decision Trees

A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data sets. This paper enhances and extends this algorithm by: introducing an adaptive grid search for the regularization parameter that guarantees optimal solutions for all relevant trees sizes, replacing the dynamic programming algorithm with a memoized recursive algorithm whose run time is substantially smaller for most regularization parameter values on the grid, and incorporating new data structures and data pre-processing steps that provide significant run time enhancement in practice.
An overview of channel coding for underwater acoustic communications

The TRIDENT (TRansmission d'Images et de Données EN Temps réeel) project was launched a few years ago by GESMA (Groupe d'Etudes Sous Marine de l'Atlantique). The initial objectives were to develop a multiple-rate underwater acoustic link for images, text and data transmission. Later, the speech option was added, and more recently channel coding options have been introduced to the TRIDENT platform. Convolutional codes (CC) and Reed Solomon (RS) block codes were then checked, but these simple codes were not able to significantly improve the Bit Error Rate (BER) at the channel decoding output. For this reason, GESMA decided to introduce turbo codes options, more specifically the Reed Solomon Block Turbo Codes (RS-BTC), to enhance the channel decoding efficiency. The data transmitted are interleaved and frame recovery is performed in reception. After system validation in static conditions, in the Penfeld river in Brest, France, sea trials were conducted in the Bay of Brest in dynamic conditions. This paper presents various possibilities offered by the platform for images and speech transmissions and the RS-BTC channel coding options.
A data prefetching mechanism for object-oriented embedded systems using run-time profiling

A table-based implementation of an application specific data prefetching approach is presented in this paper. This approach is proposed to improve the performance of the application specific instruction-set processors (ASIP) we develop customized to an object-oriented application. In this approach, the cache controller prefetches all data fields of an object required by a class method, when the class method is invoked. In the proposed table-based implementation, the cache controller monitors the class method calls and records the index of object data members that each method accessed. This information is used to prefetch the data items needed by a class method on next invocations of that method. This approach adapts the prefetching mechanism to the running application. The experimental results show that on average, this prefetching approach improves the miss ratio by 65%.
Accuracy of Endoscopic Ultrasonography for Determining the Treatment Method for Early Gastric Cancer

Background. Endoscopic resection (ER) for early gastric cancer (EGC) is a minimally invasive and curative treatment. The value of endoscopic ultrasonography (EUS) in determining the therapeutic strategy for EGC was assessed in this study. Materials and Methods. Pretreatment EUS was performed on 406 EGCs. The lesions were divided into the histological categories m/sm1 and sm2. The EUS-determined depths of invasion were classified as EUS-M/SM1, EUS-SM2, and EUS-MP or deeper. An analysis of the factors influencing the EUS-based depth determination was then conducted. Results. Most (92.8%) of the EUS-M/SM1 group belonged to the m/sm1 histological category. Ulcerated lesions, tumor size of larger than 2 cm, and the use of an ultrasound endoscope were independently associated with misdiagnosis of the depth of EGC by EUS. The ulcerated lesions had a significantly higher probability of overestimation. Conclusions. EUS is a useful method for determining the therapeutic strategy for EGC. Special attention should be paid not to overestimate the depth of cancer invasion when determining the ulcerated lesions and the type of curative procedure to be used.
The Estimation of Regional Crop Yield Using Ensemble-Based Four-Dimensional Variational Data Assimilation

To improve crop model performance for regional crop yield estimates, a new four-dimensional variational algorithm (POD4DVar) merging the Monte Carlo and proper orthogonal decomposition techniques was introduced to develop a data assimilation strategy using the Crop Environment Resource Synthesis (CERES)-Wheat model. Two winter wheat yield estimation procedures were conducted on a field plot and regional scale to test the feasibility and potential of the POD4DVar-based strategy. Winter wheat yield forecasts for the field plots showed a coefficient of determination (R2) of 0.73, a root mean square error (RMSE) of 319 kg/ha, and a relative error (RE) of 3.49%. An acceptable yield at the regional scale was estimated with an R2 of 0.997, RMSE of 7346 tons, and RE of 3.81%. The POD4DVar-based strategy was more accurate and efficient than the EnKF-based strategy. In addition to crop yield, other critical crop variables such as the biomass, harvest index, evapotranspiration, and soil organic carbon may also be estimated. The present study thus introduces a promising approach for operationally monitoring regional crop growth and predicting yield. Successful application of this assimilation model at regional scales must focus on uncertainties derived from the crop model, model inputs, data assimilation algorithm, and assimilated observations.
Household-Sector Money Demand for the UK

We test for the existence of a long-run money demand relationship for the UK involving household-sector Divisia and simple sum monetary indexes for the period from 1977 to 2008. We construct our Divisia index using non-break-adjusted levels and break-adjusted flows following the Bank of England. We test for cointegration between the real Divisia and simple sum indexes, their corresponding opportunity cost measures, real income and real share prices. Our results support the existence of a long-run money demand relationship for both the Divisia and simple sum indexes.
Educational Performance Gaps in Eastern Europe

To assess the educational performance gaps in Eastern Europe, this article takes a look at the differences in PISA test scores between Finland and seven Eastern European countries, as well as between Eastern European countries. The methodology applied is a semiparametric version of the threefold Blinder–Oaxaca decomposition. We find that main part of the average test score gap cannot be explained by the individual characteristics. Furthermore, our analysis at different quantiles provides evidence that the average test score gaps are due to the fact that poorly performing students in Finland score much higher than poorly performing students in Eastern Europe.