Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-Term In Vivo Imaging of β-Amyloid Plaque Appearance and Growth in a Mouse Model of Cerebral β-Amyloidosis

Extracellular deposition of the amyloid-β peptide (Aβ) in the brain parenchyma is a hallmark lesion of Alzheimer's disease (AD) and a predictive marker for the progression of preclinical to symptomatic AD. Here, we used multiphoton in vivo imaging to study Aβ plaque formation in the brains of 3- to 4-month-old APPPS1 transgenic mice over a period of 6 months. A novel head fixation system provided robust and efficient long-term tracking of single plaques over time. Results revealed an estimated rate of 35 newly formed plaques per cubic millimeter of neocortical volume per week at 4–5 months of age. At later time points (i.e., in the presence of increasing cerebral β-amyloidosis), the number of newly formed plaques decreased. On average, both newly formed and existing plaques grew at a similar growth rate of 0.3 μm (radius) per week. A solid knowledge of the dynamics of cerebral β-amyloidosis in mouse models provides a powerful tool to monitor preclinical Aβ targeting therapeutic strategies and eases the interpretation of diagnostic amyloid imaging in humans.
Implementation of the Notch Filters Using Subband Decomposition

The design of the finite impulse response (FIR) notch filter with controlled null width is expressed as a derivatively contrained quadratic optimization problem. The problem is transformed into an unconstrained one by choosing a null matrix orthogonal to the derivative constraint matrix. In this paper, subband decomposition using wavelet filters is employed to construct the null matrix. Taking advantage of the vanishing moment property of the wavelet filters, the proposed method can adjust the null width of the notch filter for eliminating the intractable iterference by controlling the regularity of the wavelet filters. Simulation results show that the new method can offer comparable performance as those of the existing full-rank-based ones and thus provides a promising alternative to the existing works.
Architectural Support for Exploiting Fine Grain Parallelism

The advent of multi-core processors, particularly with projections that numbers of cores will continue to increase, has focused attention on parallel programming. It is widely recognized that current programming techniques, including those that are used for scientific parallel programming, will not allow the easy formulation of general purpose applications. An area which is receiving interest is the use of programming styles which are side-effect free. Previous work on parallel functional programming demonstrated the potential of this to permit the easy exploitation of parallelism. Recent systems like Cilk use conventional languages such as C but encourage the use of a largely functional style (side-effect free) when writing programs. An important part of the Cilk runtime is a system to balance the usage of cores. In this paper we present SLAM (Spreading Load with Active Messages), a dynamic load balancing system based on functional language evaluation techniques. We show that SLAM, provided with appropriate hardware support, significantly outperforms the Cilk system. We evaluated our system using tiled CMPs with private and shared L2 caches separately. Our results show that, for the benchmarks evaluated, SLAM outperforms Cilk by 28% on average when using 32-core CMPs with private L2 caches. For the case of the CMPs with shared L2 caches, SLAM was on average 21% faster than Cilk when using 32 cores and 62% faster when using 64 cores.
PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations

Motivation: Emergence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility of phenome-wide association scans (PheWAS) for disease–gene associations. We propose a novel method to scan phenomic data for genetic associations using International Classification of Disease (ICD9) billing codes, which are available in most EMR systems. We have developed a code translation table to automatically define 776 different disease populations and their controls using prevalent ICD9 codes derived from EMR data. As a proof of concept of this algorithm, we genotyped the first 6005 European–Americans accrued into BioVU, Vanderbilt's DNA biobank, at five single nucleotide polymorphisms (SNPs) with previously reported disease associations: atrial fibrillation, Crohn's disease, carotid artery stenosis, coronary artery disease, multiple sclerosis, systemic lupus erythematosus and rheumatoid arthritis. The PheWAS software generated cases and control populations across all ICD9 code groups for each of these five SNPs, and disease-SNP associations were analyzed. The primary outcome of this study was replication of seven previously known SNP–disease associations for these SNPs. Results: Four of seven known SNP–disease associations using the PheWAS algorithm were replicated with P-values between 2.8 × 10−6 and 0.011. The PheWAS algorithm also identified 19 previously unknown statistical associations between these SNPs and diseases at P < 0.01. This study indicates that PheWAS analysis is a feasible method to investigate SNP–disease associations. Further evaluation is needed to determine the validity of these associations and the appropriate statistical thresholds for clinical significance. Availability:The PheWAS software and code translation table are freely available at http://knowledgemap.mc. vanderbilt.edu/research. Contact: josh.denny@vanderbilt.edu
Tight bounds for universal compression of large alphabets

Over the past decade, several papers, e.g., [1-7] and references therein, have considered universal compression of sources over large alphabets, often using patterns to avoid infinite redundancy. Improving on previous results, we prove tight bounds on expected- and worst-case pattern redundancy, in particular closing a decade-long gap and showing that the worst-case pattern redundancy of i.i. d. distributions is Θ(n1/3)†.
Opinion analysis of Bi-lingual Event Data from Social Networks

Social networks have recently emerged as the fastest and very effec- tive medium to express news updates, trends and expression of personal views. There have been several studies to perform detailed sentiment analysis on such data in most of the developed languages. However, Urdu lacked any such study despite being spoken by around 30 Million people around the globe and used in regions with fastest growth of broadband users. This research has been carried out as a first step in this direction, where a language resource comprising the sentiment strengths of Roman Urdu words has been proposed along with its utility by under taking a case study of spatial analysis of bi-lingual (Urdu and English) tweets in the context of a national event, i.e. genral elections 2013. The results are encouraging, showing the effective utility of the bi-lingual sentiment strength database.
Recommendation for Improving Search Engine Results

growing fast, the user's satisfaction of search engine results is decreased. This paper proposes a method for suggesting a list of queries that are related to the user input query. The related queries are based on previously issued queries by the users. The proposed method is based on clustering process in which groups of semantically similar queries are detected. This facility provides some queries which are related to the queries submitted by users in order direct them toward their required information. This method not only discovered the related queries but also rank them according to a similarity measure. Finally the method has been evaluated using real data sets from the search engine query log.
Generalized concatenated codes based on polar codes

Polar codes are demonstrated to be instances of both generalized concatenated codes and multilevel codes. It is shown that Gaussian approximation for density evolution enables one to accurately predict the performance of polar codes. A construction of generalized concatenated codes is proposed, which is based on the equal error probability design rule originally developed in the context of multilevel codes.
Simulation of user judgments in bibliographic retrieval systems

The general model and simulation algorithms for bibliographic retrieval systems presented in an earlier paper are expanded. The new model integrates the physical as well as the logical and semantic elements of these systems. A modified algorithm is developed for the simulation of user relevance judgments, and is validated, by means of recall-precision curves and a Kolmogorov-Smirnov test of recall, for two test collections. Other approaches to goodness-of-fit testing are suggested.
The Design and Implementation of the MobileSpaces Mobile Agent System

This paper presents an adaptive mobile agent system. The system consists of a core system and subcomponents like micro-kernel operating systems used in several operating systems. The core system offers only the minimal facilities and the latter is implemented as a collection of mobile agents which offer other various supplemental facilities. The system can dynamically evolve and extend its own functions by moving agents which support the functions, according to the requirements of visiting agents and the changes of the execution environment.
Microlensing constraints on the Galactic bulge initial mass function

Aims. We seek to probe the Galactic bulge IMF starting from microlensing observations. Methods. We analyse the recent results of the microlensing campaigns carried out towards the Galactic bulge presented by the EROS, MACHO and OGLE collaborations. In particular, we study the duration distribution of the events. We assume a power law initial mass function, �(µ) / µ � , and we study the slopeboth in the brown dwarf and in the main sequence ranges. Moreover, we compare the observed and expected optical depth profiles. Results. The values of the mass function slopes are strongly driven by the observed timescales of the microlensing events. The analysis of the MACHO data set gives, for the main sequence stars, � = 1.7 ± 0.5, compatible with the result we obtain with the EROS and OGLE data sets, and a similar, though less constrained slope for brown dwarfs. The lack of short duration events in both EROS and OGLE data sets, on the other hand, only allows the determination of an upper limit in this range of masses, making the overall result less robust. The optical depth analysis gives a very good agreement between the observed and the expected values, and we show that the available data do not allow one to discriminate between different bulge models.
Can Composite Fluffy Dust Particles Solve the Interstellar Carbon Crisis?

Recent observations suggest that the abundance of carbon in the interstellar medium is only ~60% of its solar value, and that other heavy elements may be depleted by a similar amount. Furthermore, more than half of the interstellar carbon is observed to be in the gas in the form of C+, leaving less than ~40% of the solar carbon abundance available for the dust phase. These observations have created the so-called interstellar ”carbon crisis,” since traditional interstellar dust models require about twice that value to be tied up in graphite grains in order to explain the interstellar extinction curve. Recently, in 1996, J. S. Mathis suggested a possible solution to this crisis. In his newly proposed dust model, the majority of the interstellar carbon is contained in composite and fluffy grains that are made up of silicates and amorphous carbon grains, with 45% of their volume consisting of vacuum. Per unit mass, these grains produce more UV extinction and therefore can account for the interstellar extinction curve with about half the carbon required in traditional dust models. This paper presents a detailed assessment of the newly proposed dust model and concludes that it falls short in solving the carbon crisis, and in providing a fit to the UV-optical interstellar extinction curve. It also predicts a far-infrared emissivity in excess of that observed with the COBE/DIRBE and FIRAS instruments from the diffuse interstellar medium. This excess infrared emission is a direct consequence of the lower albedo of the composite fluffy dust particles, compared with that of the traditional Mathis, Rumpl, & Nordsieck mixture of bare silicate and graphite grains. The failure of the new model highlights the interrelationships between the various dust properties and their observational consequences, and the need to satisfy them all simultaneously in any comprehensive interstellar dust model. In light of these problems, this paper examines other possible solutions to the carbon crisis.
Sensing Urban Social Geography Using Online Social Networking Data

Growing pool of public-generated bits like online social networking data provides possibility to sense social dynamics in the urban space. In this position paper, we use a location-based online social networking data to sense geo-social activity and analyze the underlying social activity distribution of three different cities: London, Paris, and New York. We find a non-linear distribution of social activity, which follows the Power Law decay function. We perform inter-urban analysis based on social activity distribution and clustering. We believe that our study sheds new light on context-aware urban computing and social sensing.
The Aesthetic Account of Everyday Life in Organizations: A Report on Recent Developments in Organizational Research

ABSTRACT This article examines recent advances in organizational studies that disputed the dominance of conventional-positivist paradigms by addressing everyday life in organizations through the lens of aesthetic principles. First, I discuss developments in theory and methods, focusing on the “strong” version of Organizational Aesthetics that defends new conceptions about the nature of organizations and experiences of organizational life. Then, I illustrate this new account using two relevant studies. My research finds that the aesthetic account of organizations provides concepts and modes of analysis able to better respond to current conceptual and practical challenges both in organizational research and arts management.
A non-capacitance dielectric material and its application in the global characterization of high-speed power delivery networks

In this paper, the mechanism of how the local characteristic of the high-speed power delivery network conceal its global characteristic is demonstrated. A simple and novel method which can remove the effect of the local characteristic is developed by introducing an ideal non-capacitance dielectric material. With the proposed method, the high-speed global characteristic of the power delivery network can be estimated more accurately by general network parameters. The Validity of the proposed method is verified by numerical examples.
An embedded PLC development for teaching in mechatronics education

The major obstacles to teaching Programmable Logic Controller (PLC) is a variety of PLCs and the rapid pace of technological development with new models and innovations. Moreover, costs incurred in the setting up of comprehensive and modern PLC laboratory facilities, and in the required periodic updating of teaching material and equipment are, as a result, very high. After investigated the conception and features of PLC and embedded system, the development of the embedded PLC for teaching machatronics students is proposed in this paper with the seamless combination of the LabVIEW software and the ARM Microcontroller with the LabVIEW embedded module. The flexibility of the proposed PLC makes it relatively easy and less costly to teach the basic principle of different kinds of PLCs due to their variety and rapid change. The implementation of the embedded PLC is discussed and evaluated. The results of evaluation shows that embedded PLC can be taught in an uncomplicated manner.
Autocorrelation structure at rest predicts value correlates of single neurons during reward-guided choice

Correlates of value are routinely observed in the prefrontal cortex (PFC) during reward-guided decision making. In previous work (Hunt et al., 2015), we argued that PFC correlates of chosen value are a consequence of varying rates of a dynamical evidence accumulation process. Yet within PFC, there is substantial variability in chosen value correlates across individual neurons. Here we show that this variability is explained by neurons having different temporal receptive fields of integration, indexed by examining neuronal spike rate autocorrelation structure whilst at rest. We find that neurons with protracted resting temporal receptive fields exhibit stronger chosen value correlates during choice. Within orbitofrontal cortex, these neurons also sustain coding of chosen value from choice through the delivery of reward, providing a potential neural mechanism for maintaining predictions and updating stored values during learning. These findings reveal that within PFC, variability in temporal specialisation across neurons predicts involvement in specific decision-making computations. DOI: http://dx.doi. org/10.7554/eLife.18937. 001
Correlation between attention assessment tasks

Paying attention makes all the difference, in both professional and personal lives. This cognitive attribute therefore needs to be enhanced. To measure the enhancement it is essential that the cognitive attribute of attention be assessed before and after intervention. There are several types of tasks that may vary by a shade for assessing attention. The present study on young healthy engineering students reveals that the scores attained by subjects in three different tasks of attention namely Continuous Performance Task (CPT) and Go/No-GoP and Go/No-GoR are uncorrelated and therefore all 3 tasks will be required for assessing visual spatial attention. Keyword: Attention, Attention Task, Psychology Experiment Building Language (PEBL), Pearson Coefficient.
Endorsed Transactions on Ambient Systems Editorial 1 Special Issue “ Technology for Mental Health ”

Help4Mood is a system that supports the treatment of people with depression in the community. It collects rich cognitive, psychomotor, and motor data through a Personal Monitoring System and a Virtual Agent, which is then analysed by a Decision Support System; analysis results are fed back to patients and their treating clinicians. In this paper, we describe how the complex data is managed and discuss ethical issues. Data is stored in functional units that correspond to treatment relevant entities. Custom XML DTDs are defined for each unit, which are used to exchange information between system components. As far as possible, observations and findings are coded using SNOMED CT to ensure interoperability with other applications such as Electronic Health Records.
Discovering Subgroups of Patients from DNA Copy Number Data Using NMF on Compacted Matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.
Investigating how to effectively combine static concern location techniques

As software systems continue to grow and evolve, locating code for maintenance tasks becomes increasingly difficult. Studies have shown that combining static global concern location techniques like search with more structure-based local techniques can improve effectiveness. However, no studies have yet investigated why this occurs. In this paper, we investigate why combining global and local techniques improves effectiveness, and under what conditions. We explore such questions as: "What are the limits of lexical information in locating concerns? ", "How far away does a local technique have to go to locate the remaining relevant elements? ", and "How sensitive are these results to the query or scoring thresholds of the techniques? ". The results of our study can inform design decisions to maximize effective global and local combinations in future concern location techniques.
Kinetic Models of Synaptic Transmission

The remarkably successful quantitative description of the action potential introduced by Hodgkin and Huxley (1952) is still widely used over 40 years since its introduction. The classical Hodgkin-Huxley description was not only accurate, it was also readily extensible to many other voltage-dependent currents. More recent single channel recording techniques (Sakmann and Neher, 1995) have been used to prove that voltage-dependent currents arise from populations of individual ion channels undergoing rapid transitions between conducting and non-conducting states. The macroscopic behavior of the currents can be accurately captured using kinetic models that describe the transitions between conformational states of these ion channels. This class of models, of which the Hodgkin-Huxley model is an instance, are commonly known as Markov models. Kinetic models not only provide good descriptions of voltage-dependent ionic currents but are general enough to describe almost all processes essential to neurophysiology. We will focus in this chapter on synaptically-gated currents of all kinds, including neuromodulators, which are readily modeled by Markov kinetics. Moreover, many important biochemical reactions, including second-messenger systems, synaptic release, and enzymatic cascades can also be described by kinetic schemes. As a consequence, kinetic models provide means to build coherent neural models in which subcellular, cellular, and network properties are described within the same formalism (see Destexhe et al., 1994c). Kinetic models are inherently exible in their level of detail, ranging from the most detailed and biophysically realistic gating models to highly simpli ed representations. Some detailed models determined from voltage-clamp studies have more than a dozen states (e.g.,