Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteomic strategies for analysis of cerebrospinal fluid in neurodegenerative disorders

There is a great need for biomarkers to diagnose neurodegenerative disorders, such as the cognitive disorders Alzheimer’s disease (AD) and frontotemporal dementia (FTD). Cerebrospinal fluid (CSF) is in contact with the extracellular fluid of the brain and is consequently a valuable medium for identifying biomarkers for neurological disorders. Biomarkers can be used for early identification of disease, to facilitate homogenous classification and to extend our basic knowledge of disease pathogenesis. Proteomics, an approach for biomarker discovery, generally combines various separation techniques with mass spectrometry (MS) and bioinformatics to identify and characterize proteins, reflecting a defined state at a specific time point. The aim of this thesis was to develop and evaluate proteomic strategies for analysis of CSF proteins to reveal disease mechanisms and identify potential biomarkers to distinguish AD from FTD. Two approaches to improve the detection of CSF proteins by twodimensional gel electrophoresis (2-DGE) were used. First, to enrich the proteins, CSF was prefractionated using liquid phase isoelectric focusing followed by 2-DGE profiling. Secondly, zoom 2D gels increased protein separation directly in the gels. These studies showed that in the CSF proteome of AD and FTD patients several proteins were differentially expressed, suggesting that different mechanisms are involved in the pathogenesis of these disorders. To validate some of the findings from the 2-DGE studies, β-trace, transthyretin (TTR), α-1-antitrypsin and cystatin C (CysC) were quantified in CSF. The concentrations of all these proteins, previously shown to bind amyloid-beta (Aβ) peptides, were reduced in AD CSF, while only CysC and β-trace were reduced in FTD. Furthermore, we found a strong positive correlation between β-trace, TTR and CysC, and levels of Aβ peptides specifically in the AD group, suggesting that a lack of proteins binding to Aβ peptides in AD CSF might cause increased extracellular Aβ aggregation, a major pathological hallmark in the AD brain. Additionally, we showed that incorrect storage conditions can influence the isoform levels of some CSF proteins. Thus, standardization of CSF sample handling is important in avoiding ambiguous results. Furthermore, very low-abundant neuron specific tau protein isoforms, were for the first time characterized in CSF using a targeted immunoprecipitation-MS approach, opening up new possibilities for further differentiation of tauopathies, including AD and FTD.
Emergent dialogue: eliciting values during children's collaboration with a tabletop game for change

Games for Change (G4C) is a movement and community of practice dedicated to using digital games for social change. However, a common model of persuasion built into most G4C, called Information Deficit, assumes that supporting children to learn facts will result in behavior change around social issues. There is little evidence that this approach works. We propose a model of game play, called Emergent Dialogue, which encourages children to discuss their values during interaction with factual information in a G4C. We summarize a set of guidelines based on our Emergent Dialogue model and apply them to the design of Youtopia, a tangible, tabletop learning game about sustainability. Our goal was to create a game that provided opportunities for children to express and discuss their values around sustainable development tradeoffs during game play. We evaluate our design using video, survey and questionnaire data. Our results provide evidence that our model and design guidelines are effective for supporting valuebased dialogue during collaborative game play.
Semiclassical resonances for a two-level Schrödinger operator with a conical intersection

We study the resonant set of a two-level Schrodinger operator with a linear conical intersection. This model operator can be decomposed into a direct sum of first order systems on the real half-line. For these ordinary differential systems we locally construct exact WKB solutions, which are connected to global solutions, amongst which are resonant states. The main results are a generalized Bohr-Sommerfeld quantization condition and an asymptotic description of the set of resonances as a distorted lattice.
FAST ADAPTIVE DETECTION OF SINUSOIDAL SIGNALS USING VARIABLE DIGITAL FILTERS AND ALL-PASS FILTERS

This paper proposes an adaptive line enhancer (ALE) using a variable band-pass (BP) filter and an all-pass filter. The proposed ALE has the high convergence speed and the small steady-state value of the squared error. The all-pass filter outputs the signal which consists of a sinusoidal signal which has the same phase as that of the input signal to the ALE and a white noise which has no correlation with that of the input signal to the ALE. The variable BP filter has two parameters which control its center frequency and bandwidth. In the proposed ALE, both of the center frequency and the bandwidth are adaptively adjusted using least mean squares algorithm. As the reference signal, the input signal to the ALE is adopted to adjust the center frequency and the output signal of the all-pass filter is adopted to adjust the bandwidth. Numerical examples show that the proposed ALE has the high convergence speed and the small steady-state value of the squared error.
Direct Estimation of Inhomogeneous Markov Interval Models of Spike Trains

Abstract A necessary ingredient for a quantitative theory of neural coding is appropriate “spike kinematics”: a precise description of spike trains. While summarizing experiments by complete spike time collections is clearly inefficient and probably unnecessary, the most common probabilistic model used in neurophysiology, the inhomogeneous Poisson process, often seems too crude. Recently a more general model, the inhomogeneous Markov interval model (Berry & Meister, 1998; Kass & Ventura, 2001), was considered, which takes into account both the current experimental time and the time from the last spike. Several techniques were proposed to estimate the parameters of these models from data. Here we propose a direct method of estimation that is easy to implement, fast, and conceptually simple. The method is illustrated with an analysis of sample data from the cat's superior colliculus.
Pseudo-likelihood analysis of context-dependent codon substitution models

We consider Markov processes for coding DNA sequence evolution. In context dependent models the instantaneous substitution rate for a codon depends on the neighboring codons. This makes the model analytically intractable, and previously Markov chain Monte Carlo methods have been used for statistical inference. We introduce an approximative estimation method based on pseudo-likelihood that makes inference analytically tractable. We demonstrate that the pseudo-likelihood estimates are very accurate, and from analyzing 348 human-mouse coding sequences we conclude that incorporating the CpG effect improves the model fits considerably.
Psychologie als Wissenschaft

Die Psychologie behandelt Fragen, die den Menschen von alters her bewegen: Was ist Persönlichkeit, was sind Gefühle und woher kommen sie? Welchen Einfluss haben unsere Gedanken und Erwartungen auf unser Leben? Warum verhalten wir uns in Gruppen manchmal anders, als wenn wir allein sind? Was bestimmt unsere seelische Entwicklung im Laufe der Jahre? Warum bleiben manche Menschen unter Stress psychisch stabil und andere nicht? Was genau sind psychische Störungen und wie kann man sie behandeln?
Control System and Mechanism Design of the Self-Propelled Electrostatic Sprayer

In this paper, a self-propelled electrostatic sprayer is designed to meet the needs of the agriculture engineering. The machine can automatically detect the target, and then spraying the target directionally, which can minimize the contamination of the drug solution to the environment. In order to make human separate with machine in the course of their work and avoid physical injury in the process of liquid spraying, the walking body, turning body and working body of the machine are controlled by a wireless remote control system. The self-propelled electrostatic sprayer achieves the desired objectives and requirements.
Using Forward Looking Infrared (FLIR) imagery to detect polar bear maternal dens: Operations manual

The opinions, findings, conclusions or recommendations expressed in this report or product are those of the authors and do not necessarily reflect the views of the Minerals Management Semce or Geological Survey, nor does the mention of trade names or commercial products constitute endorsement or recommendation for use by the Federal Government. INTRODUCTION Recent research has shown that Forward Looking Infia-Red (FLIR) imagery can detect polar bear dens despite total snow cover over their deming habitat. FLIR imagers detect a AT or difference in temperature between objects in the imager's field of view. During the Arctic winter, the groundlsnow surface is typically cold, providing a dark background in the FLIR imager. Sources of heat appear as lighter or white areas. Dens, in particular, appear as small bright "hotspots", usually with k z y boundaries (Appendix 1). Most commonly, since bears chose deep snow drifts for deming, dens can be distinguished from the normally dark (cold) band of drifted snow surrounding them. This innovation has the potential to prevent human activities fiom disturbing deming polar bears by allowing managers to discover dens before potentially disruptive activities begin. This is important because expanding resource extraction in Alaska's Arctic regions may threaten the welfare of polar bears and their habitat. In recent years, exploration and development activities have expanded east and west of the original oil fields of Prudhoe Bay. Hydrocarbon extraction is now occurring or planned along much of the central Beaufort Sea coast. As development continues into the National Petroleum Reserve, the scope of expansion could include 213 of the northern coastal region of Alaska. Industrial activities are a potential threat to polar bears, especially as they might disturb bears in maternal dens humans and their activities have increased in recent years, there has been a concurrent increase in the number of female polar bears deming on land (Amstrup and Gardner 1994). Therefore, the probability of disrupting maternal deming can be expected to increase in the future. Using FLIR surveys to detect bears in dens could reduce or eliminate that probability. The purpose of this manual is to provide agency and private sector land managers with the information necessary to perform effective FLIR surveys to detect maternal dens. A list of personnel who can provide additional information is provided in Appendix 2.
Human Body Detection using Histogram of Oriented Gradients and SVM

Human detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Detecting humans accurately is the first fundamental step for many computer vision applications such as video surveillance, smart vehicles, intersection traffic analysis and so on. This paper consists of efficient human detection in static images using Histogram of Oriented Gradients (HOG) for local feature extraction and support vector machine (SVM) classifiers. Histogram of oriented gradient (HOG) gives an accurate description of the contour of human body. Based on HOG and support vector machine (SVM) theory, a classifier for human is obtained. I have to evaluate the performance of pedestrian histogram of oriented gradients (HOG) and Support Vector Machine on INRIA human database images.
Nonintrusive Eye Gaze Tracking using a single eye image

This paper proposes an Eye Gaze Tracking (EGT) technique using a single eye image that can be easily calibrated and mapped for Human Computer Interaction (HCI). The technique employs both geometric and trigonometric relationships to find a user's Point of Regard, followed by calculating user-dependent variables for final mapping onto a user interface (UI). Experimental results show acceptable accuracy with minimal focal errors.
Heuristics for Vector Bin Packing

Inspired by virtual machine placement problems, we study heuristics for the Vector Bin Packing problem, where we are required to pack n items represented by d-dimensional vectors, into as few bins of size 1 each as possible. We systematically study variants of the First Fit Decreasing (FFD) algorithm that have been proposed for this problem. Inspired by bad instances for FFD-type algorithms, we propose new geometric heuristics that run nearly as fast as FFD for reasonable values of n and d. We report on empirical evaluations of the FFD-based, as well as the new heuristics on large families of distributions. We identify which FFD variants work best in most cases and show that our new heuristics usually outperform FFD-based heuristics and can sometimes reduce the number of bins used by up to ten percent. Further, in all cases where we were able to compute the optimal solution we found our new heuristics within few percent of optimal. We conclude that these new heuristics are an excellent alternative to FFD-based heuristics and are prime candidates to be used in practice.
Communication over Channels with Causal Side Information at the Transmitter

This work deals with communication over the AWGN channel with additive discrete interference, where the sequence of interference symbols is known causally at the transmitter. We use Shannon’s treatment for channels with side information at the transmitter as a framework to derive “optimal precoding” and “channel code design criterion” for the channel with known interference at the transmitter. Communication over Shannon’s state-dependent discrete memoryless channel where the state sequence is known causally at the transmitter requires encoding over the so-called associated channel which has exponential input alphabet cardinality with respect to the number of states. We show that by using at most linearly many input symbols of the associated channel, the capacity is achievable. In particular, we consider M -ary signal transmission over the AWGN channel with additive Q-ary interference where the sequence of i.i. d. interference symbols is known causally at the transmitter. We investigate the problem of maximization of the transmission rate under the uniformity constraint, where the channel input given any current interference symbol is uniformly distributed over the channel input alphabet. For this setting, we propose the general structure of a communication system with optimal precoding. We also investigate the extension of the proposed precoding scheme to continuous channel input alphabet. We also consider the problem of channel code design with causal side information at the encoder. We derive the code design criterion at high SNR by defining a new distance measure between the input symbols of the Shannon’s associated channel. For the case of the binary-input channel, i.e., M = 2, we show that it is sufficient
Interactive Form-Finding of Elastic Origami

In this paper, we propose a novel computational method to simulate and design origami whose form is governed by the equilibrium of forces from the elastic bending of each panel. In special, we explore statically indeterminate origami structure that can be manipulated by pin supporting finite number of vertices. The computational method is proposed so that we can interactively explore the design space of such origami form. The concept of kinematic origami tessellation based on bending of panels is introduced.
Visual Discrimination of Cantonese Tone by Ton Speakers , and by Non-Tonal Languag

A previous study by the first two authors suggests there is visual information for tone perception: under certain conditions Cantonese speakers are able to identify spoken words as one of six Cantonese words differing only in tone on the basis of lip and face movements at a rate better than chance [1]. Here, non-native (tonal, Thai, and non-tonal, English) language speakers were tested on a discrimination version of this task in three modes: auditory-visual (AV), auditory only (AO), and visual only (VO). Auditory stimuli were presented either in the clear or accompanied by noise. In all conditions, even VO, performance was significantly better than chance. In the clear, both English and Thai perceivers performed better in the AO and AV conditions than in the VO condition. With auditory noise added, Thai perceivers performed better in the AV than the AO condition. The results support the existence of visual information for tone, and show that this is available in the absence of experience with the language in question, and even in the absence of experience with the lexical use of tone.
4 Parallel Information Retrieval 14.1 Parallel Query Processing

Information retrieval systems often have to deal with very large amounts of data. They must be able to process many gigabytes or even terabytes of text, and to build and maintain an index for millions of documents. To some extent the techniques discussed in Chapters 5–8 can help us satisfy these requirements, but it is clear that, at some point, sophisticated data structures and clever optimizations alone are not sufficient anymore. A single computer simply does not have the computational power or the storage capabilities required for indexing even a small fraction of the World Wide Web. In this chapter we examine various ways of making information retrieval systems scale to very large text collections such as the Web. The first part (Section 14.1) is concerned with parallel query processing, where the search engine's service rate is increased by having multiple index servers process incoming queries in parallel. It also discusses redundancy and fault tolerance issues in distributed search engines. In the second second part (Section 14.2), we shift our attention to the parallel execution of off-line tasks, such as index construction and statistical analysis of a corpus of text. We explain the basics of MapReduce, a framework designed for massively parallel computations carried out on large amounts of data. There are many ways in which parallelism can help a search engine process queries faster. The two most popular approaches are index partitioning and replication. Suppose we have a total of n index servers. Following the standard terminology, we refer to these servers as nodes. By creating n replicas of the index and assigning each replica to a separate node, we can realize an n-fold increase of the search engine's service rate (its theoretical throughput) without affecting the time required to process a single query. This type of parallelism is referred to as inter-query parallelism, because multiple queries can be processed in parallel but each individual query is processed sequentially. Alternatively, we could split the index into n parts and have each node work only on its own small part of the index. This approach is referred to as intra-query 1 While nobody knows the exact size of the indexable part of the Web, it is estimated to be at least 100 billion pages. In August 2005, when Yahoo! last disclosed the size of its index, it had reached a total size of 19.2 billion documents
Person detection in surveillance environment with HoGG: Gabor filters and Histogram of Oriented Gradient

In this paper, a novel method (HoGG) for human detection in non-controlled surveillance environments based on Gabor filters and Histograms of Oriented Gradients is proposed. Complete performance results of several alternative algorithms for human detection are presented. In order to evaluate these methods in non-controlled situations, a set of standard video surveillance databases (PETS 2006, PETS 2007, PETS 2009 and CAVIAR) as well as the classical (in people detection area) INRIA database are used. An exhaustive test design has been built based on two complementary evaluations: an evaluation oriented to count persons and a novel evaluation oriented to identification. The proposed method has surpassed the alternative methods in most of the analyzed situations, this is a relevant improvement of the widely used HoG algorithm.
Effects of uric acid-lowering therapy on renal outcomes: a systematic review and meta-analysis.

BACKGROUND Non-randomized studies suggest an association between serum uric acid levels and progression of chronic kidney disease (CKD). The aim of this systematic review is to summarize evidence from randomized controlled trials (RCTs) concerning the benefits and risks of uric acid-lowering therapy on renal outcomes. METHODS Medline, Excerpta Medical Database and Cochrane Central Register of Controlled Trials were searched with English language restriction for RCTs comparing the effect of uric acid-lowering therapy with placebo/no treatment on renal outcomes. Treatment effects were summarized using random-effects meta-analysis. RESULTS Eight trials (476 participants) evaluating allopurinol treatment were eligible for inclusion. There was substantial heterogeneity in baseline kidney function, cause of CKD and duration of follow-up across these studies. In five trials, there was no significant difference in change in glomerular filtration rate from baseline between the allopurinol and control arms [mean difference (MD) 3.1 mL/min/1.73 m2, 95% confidence intervals (CI) -0.9, 7.1; heterogeneity χ2=1.9, I2=0%, P=0.75]. In three trials, allopurinol treatment abrogated increases in serum creatinine from baseline (MD -0.4 mg/dL, 95% CI -0.8, -0.0 mg/dL; heterogeneity χ2=3, I2=34%, P=0.22). Allopurinol had no effect on proteinuria and blood pressure. Data for effects of allopurinol therapy on progression to end-stage kidney disease and death were scant. Allopurinol had uncertain effects on the risks of adverse events. CONCLUSIONS Uric acid-lowering therapy with allopurinol may retard the progression of CKD. However, adequately powered randomized trials are required to evaluate the benefits and risks of uric acid-lowering therapy in CKD.
ENHANCEMENT OF K-MEANS CLUSTERING ALGORITHM FOR POSITION THE CENTRES OF RADIAL BASIS FUNCTION (RBF) NETWORK

This is research is for two updating methods to improve the clustering performance of adaptive k-means clustering. The proposed updating methods are suitable for off-line and on-line clustering. The capability of the updating methods are then compared to the existing updating methods using simulated and real data sets. Simulation results showed that the proposed updating methods have significantly improved the overall performance of RBF network. This paper also investigates some properties of adaptation method for on-line adaptive k-means clustering algorithm.