Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Throughput Multiplexed Quantitation of Protein Aggregation and Cytotoxicity in a Huntington’s Disease Model

A hallmark of Huntington’s disease is the presence of a large polyglutamine expansion in the first exon of the Huntingtin protein and the propensity of protein aggregation by the mutant proteins. Aberrant protein aggregation also occurs in other polyglutamine expansion disorders, as well as in other neurodegenerative diseases including Parkinson’s, Alzheimer’s, and prion diseases. However, the pathophysiological role of these aggregates in the cell death that characterizes the diseases remains unclear. Identification of small molecule probes that modulate protein aggregation and cytotoxicity caused by aggregated proteins may greatly facilitate the studies on pathogenesis of these diseases and potentially lead to development of new therapies. Based on a detergent insoluble property of the Huntingtin protein aggregates, we have developed a homogenous assay to rapidly quantitate the levels of protein aggregates in a cellular model of Huntington’s disease. The protein aggregation assay has also been multiplexed with a protease release assay for the measurement of cytotoxicity resulting from aggregated proteins in the same cells. Through a testing screen of a compound library, we have demonstrated that this multiplexed cytotoxicity and protein aggregation assay has ability to identify active compounds that prevent cell death and/or modulate protein aggregation in cells of the Huntington’s disease model. Therefore, this multiplexed screening approach is also useful for development of high-throughput screening assays for other neurodegenerative diseases involving protein aggregation.
Towards an Ecological Understanding of Dinoflagellate Cyst Functions

The life cycle of many dinoflagellates includes at least one nonflagellated benthic stage (cyst). In the literature, the different types of dinoflagellate cysts are mainly defined based on morphological (number and type of layers in the cell wall) and functional (long- or short-term endurance) differences. These characteristics were initially thought to clearly distinguish pellicle (thin-walled) cysts from resting (double-walled) dinoflagellate cysts. The former were considered short-term (temporal) and the latter long-term (resting) cysts. However, during the last two decades further knowledge has highlighted the great intricacy of dinoflagellate life histories, the ecological significance of cyst stages, and the need to clarify the functional and morphological complexities of the different cyst types. Here we review and, when necessary, redefine the concepts of resting and pellicle cysts, examining both their structural and their functional characteristics in the context of the life cycle strategies of several dinoflagellate species.
A Tool to Assess the Comfort of Wearable Computers

Wearable computer comfort can be affected by numerous factors, making its assessment based on one value with one scale inappropriate. This paper presents a tool that measures wearable comfort across six dimensions: emotion, attachment, harm, perceived change, movement, and anxiety. The dimensions for these comfort rating scales were specifically developed for wearable equipment assessment by applying multidimensional scaling to a comfort term association matrix developed using the results of groupings of wearable computer comfort terms. Testing the scales on four different types of wearable computer showed that the scales can be used to highlight differences in comfort between different types of technology for different aspects of comfort. An intraclass correlation of . 872 suggested that the scales were used with a high level of reliability. A second study showed that modifications made to a wearable computer resulted in improvements in comfort, although they were not significant (p > .05). A potential application for this research is as an aid to designers and researchers for assessing the wearability, in terms of comfort, of wearable computer devices and to determine the effectiveness of any modifications made to the design of a wearable device.
Electrochemically Active Alginate: Development, Fabrication and Application

The work presented here develops a new type of electrochemically active hydrogel based on alginate. By oxidizing a copper electrode in the presence of alginate, it is shown that the alginate will become cross linked at the electrode surface. By modulating the growth time or growth potentials, the mechanical properties of the gels can be modulated, with time being the easiest to control. It was also shown that with the reduction of the copper ions in the gel, the structure can be de-cross linked. This mechanism was harnessed to provide fluidic delivery of a small molecule representing a drug, with the optimum growth conditions for this applications found to be the application of a 2.5 V potential difference for one hour versus an aluminum counter electrode. Constructing a device from this gel, it was shown that the rate of fluidic release can be modulated by varying the potential between 1 and 5 volts potential difference. Finally, this process was further developed into a new printing technique, allowing for the printing of gradient structures with a continuum of densities throughout the structure.
Applying a family of IR models to text description-based service retrieval

In the study reported in this paper, we apply a family of Information Retrieval (IR) models to overcome the problem of retrieving services, whose descriptions match users' queries given a free text style. This family is composed by four models which have not been applied in prior research on IR-based service discovery. Among these models, two of them are based on matrix factorisation models applied to Latent Semantic Indexing (LSI). Moreover, we propose other two models based on query expansion. The first one expands the query with terms retrieved from the lexicon called WordNet, taking into account parts of speech of the query. The second model also expands the query, but with terms extracted from an automatically generated co-occurrence thesaurus. The results of the experiments suggest that the last model outperforms the other models applied in this work besides those most recent and prominent in the state-of-the-art on IR-based service discovery.
Factor analysis based VTS discriminative adaptive training

Vector Taylor Series (VTS) model based compensation is a powerful approach for noise robust speech recognition. An important extension to this approach is VTS adaptive training (VAT), which allows canonical models to be estimated on diverse noise-degraded training data. These canonical model can be estimated using EM-based approaches, allowing simple extensions to discriminative VAT (DVAT). However to ensure a diagonal corrupted speech covariance matrix the Jacobian (loading matrix) relating the noise and clean speech is diagonalised. In this work an approach for yielding optimal diagonal loading matrices based on minimising the expected KL-divergence between the diagonal loading matrix and “correct” distributions is proposed. The performance of DVAT using the standard and optimal diagonalisation was evaluated on both in-car collected data and the Aurora4 task.
Field‐aligned currents during IMF ∼0

We report on field‐aligned currents (FAC) obtained from precise magnetic field measurements made on‐board the Ørsted and Magsat satellites when the interplanetary magnetic field (IMF) was near zero. We found that Region 1/Region 2 currents persist through southward IMF, IMF ∼ 0, and northward IMF; also the central area of both the northern and southern polar caps is always filled with FACs, even during slightly southward IMF. A statistical distribution of the latter currents resembles the dayside NBZ system with the downward/upward currents at post‐noon/pre‐noon hours, discovered earlier from Magsat observations. We hypothesize that the quasi‐viscous interaction of the solar wind with the magnetospheric lobes may cause a sunward convection of the lobes' field lines through the bunch's core, effectively mapping the FACs of NBZ‐type down to the near‐pole area.
Multi-objective optimization of stacked radial passive magnetic bearing

Modeling, design, and optimization for performances of passive magnetic bearings (PMBs) are indispensable, as they deliver lubrication free, friction less, zero wear, and maintenance-free operations. However, single-layer PMBs has lower load-carrying capacity and stiffness necessitating development of stacked structure PMBs for maximum load and stiffness. Present work is focused on multi-objective optimization of radial PMBs to achieve maximum load-carrying capacity and stiffness in a given volume. Three-dimensional Coulombian equations are utilized for estimating load and stiffness of stacked radial PMBs. Constraints, constants, and bounds for the optimization are extracted from the available literature. Optimization is performed for force and stiffness maximization in the obtained bounds with three PMB configurations, namely (i) mono-layer, (ii) conventional (back to back), and (iii) rotational magnetized direction. The optimum dimensions required for achieving maximum load without compromising stiffness for all three configurations is investigated. For designers ease, equations to estimate the optimized values of load, stiffness, and stacked PMB variables in terms of single-layer PMB are proposed. Finally, the effectiveness of the proposed method is demonstrated by considering the PMB dimensions from the available literature.
Human Fetuin-A Rs4918 Polymorphism and its Association with Obesity in Healthy Persons and in Patients with Myocardial Infarction in Two Hungarian Cohorts

Background Human fetuin A (AHSG) has been associated with the development of obesity, insulin resistance, type 2 diabetes mellitus, and atherosclerosis. Observations on the role of AHSG rs4918 single-nucleotide polymorphism are contradictory. We investigated the association between variants of rs4918 and parameters of obesity, lipid status, tumor necrosis factor-α (TNFα), adipokines (adiponectin, resistin, leptin), and insulin resistance in healthy persons and in patients with previous myocardial infarction. Material/Methods This was a cross-sectional study comprising cohort 1 (81 healthy individuals) and cohort 2 (157 patients with previous myocardial infarction). We used the allele-specific KASP genotyping assay to detect rs4918 polymorphism. Results In cohort 1, G-nucleotide carriers had significantly lower serum TNFα, adiponectin, and higher leptin concentrations than in non-G carriers. These differences, however, were not observed in cohort 2. In cohort 2, G-carriers had lower BMI and waist circumferences than in non-G carriers. The G allele was more frequent among lean than obese patients (RR=1.067, 95%CI=1.053–2.651, p=0.015). An association between BMI and rs4918 polymorphism was observed among patients without diabetes (CC/CG/GG genotypes: p=0.003, G vs. non-G allele: p=0.008) but not in diabetics. In addition, a strong linearity between BMI and the CC/CG/GG genotypes (association value: 4.416, p=0.036) and the frequency of the G allele (7.420, p=0.006) could be identified. In cohort 2, non-obese, non-diabetic G-carriers still had lower BMI and waist circumferences than in non-G carriers. Conclusions The rs4918 minor variant is associated with lower TNFα and adiponectin, higher leptin levels in healthy persons, and more favorable anthropomorphic parameters of obesity in cohort 2.
Fingerpointing for Hadoop ( CMU-PDL-08-104 )

Localizing performance problems (or fingerpointing) is essential for distributed systems such as Hadoop that support long-running, parallelized, data-intensive computations over a large cluster of nodes. Manual fingerpointing does not scale in such environments because of the number of nodes and the number of performance metrics to be analyzed on each node. ASDF is an automated, online fingerpointing framework that transparently extracts and parses different time-varying data sources (e.g., sysstat, Hadoop logs) on each node, and implements multiple techniques (e.g., log analysis, correlation, clustering) to analyze these data sources jointly or in isolation. We demonstrate ASDF’s online fingerpointing for documented performance problems in Hadoop, under different workloads; our results indicate that ASDF incurs an average monitoring overhead of 0.38% of CPU time, and exhibits average online fingerpointing latencies of less than 1 minute with false-positive rates of less than 1%. 1ASDF stands for Automated System for Diagnosing Failures Acknowledgements: The authors would like to acknowledge Julio Lopez for discussions on Hadoop, Kathleen Carley for her insights on visualization, and Christos Faloutsos for discussions on data mining. This material is based on research sponsored in part by the National Science Foundation, via CAREER grant CCR-0238381 and grant CNS-0326453.
Parallel solution of the wave equation using higher order finite elements

We present a parallel solver for wave propagation problems based on the higher-order explicit finite elements developed by Cohen et al. (1995) These elements were introduce to allow mass-lumping while preserving high accuracy. Our approach is based on a coarse-grain, domain-splitting parallelism, and uses the new MPI (Message Passing Interface) standard as a message passing library. The program currently runs on a network of workstations, on a Cray T3D and on an IBM SP/2.
Geometric distortion-resilient image hashing system and its application scalability

Media hashing is an alternative approach to many applications previously accomplished with watermarking. The major disadvantage of the existing media hashing technologies is their poor resistance to geometric attacks. In this paper, a novel geometric distortion-invariant image hashing scheme, which can be employed to perform copy detection and content authentication of digital images, is proposed. Our major contributions are threefold: (i) mesh-based robust hashing function is proposed; (ii) sophisticated hash database for error-resilient and fast matching is constructed; and (iii) the application scalability of our scheme for content copy tracing and authentication is studied. In addition, we further investigate several media hashing issues, including robustness and discrimination, error analysis, and complexity, for the proposed image hashing system. Exhaustive experimental results obtained from benchmark attacks confirm the excellent performance of the proposed method.
Sparsity and Compressed Sensing in Radar Imaging

Remote sensing with radar is typically an ill-posed linear inverse problem: a scene is to be inferred from limited measurements of scattered electric fields. Parsimonious models provide a compressed representation of the unknown scene and offer a means for regularizing the inversion task. The emerging field of compressed sensing combines nonlinear reconstruction algorithms and pseudorandom linear measurements to provide reconstruction guarantees for sparse solutions to linear inverse problems. This paper surveys the use of sparse reconstruction algorithms and randomized measurement strategies in radar processing. Although the two themes have a long history in radar literature, the accessible framework provided by compressed sensing illuminates the impact of joining these themes. Potential future directions are conjectured both for extension of theory motivated by practice and for modification of practice based on theoretical insights.
Hybrid pre-query term expansion using latent semantic analysis

Latent semantic retrieval methods (unlike vector space methods) take the document and query vectors and map them into a topic space to cluster related terms and documents. This produces a more precise retrieval but also a long query time. We present a new method of document retrieval which allows us to process the latent semantic information into a hybrid latent semantic-vector space query mapping. This mapping automatically expands the users query based on the latent semantic information in the document set. This expanded query is processed using a fast vector space method. Since we have the latent semantic data in a mapping, we are able to store and retrieve vector information in the same fast manner that the vector space method offers. Multiple mappings are combined to produce hybrid latent semantic retrieval which provide precision results 5% greater than the vector space method and fast query times.
Building Hierarchical Micro-Structure on the Carbon Fabrics to Improve Their Reinforcing Effect in the CFRP Composites

Nano-fibers grafted on carbon fibers (CFs) has been of one of the most popular methods used for the carbon fibers surface treatment, which could significantly influence the inter facial properties between polymer matrix and carbon fibers in composites. This chap - ter demonstrated three novel carbon fibers surface treatment methods, they are carbon nanotubes (CNTs) grafted on CFs using catalysts formed in an ethanol flame, carbon fiber forests (CFFs) by carbon fiber surface brushing and abrading and ZnO nanowire grown onto CFs though a facile hydrothermal method respectively. Based on metal catalyst par - ticles or dopamine-based functionalization formed onto the nano-fiber/CF interface, a good interfacial bonding strength between the nano-fiber and CFs was observed by an instrumented tip of an atomic force microscope and further improvement of interfacial shear strength with epoxy as measured by the single fiber pull out/microbond test was realized. The hierarchical micro-fibers on CF fabrics were then utilized to fabricate the laminates to characterize anti-delamination capacity (the mode I and mode II interlami - nar fracture toughness) of these composite laminates, wherein carbon fiber fabrics were grafted with CNTs, short CFs and ZnO nanowires respectively.
Specificity of the Linear Array HPV Genotyping Test for detecting human papillomavirus genotype 52 (HPV-52).

INTRODUCTION HPV-52 is one of the most frequent human papillomavirus (HPV) genotypes causing significant cervical pathology. The most widely used HPV genotyping assay, the Roche Linear Array HPV Genotyping Test (Linear Array), is unable to identify HPV-52 status in samples containing HPV-33, HPV-35, and/or HPV-58. METHODS Linear Array HPV-52 analytical specificity was established by testing 100 specimens reactive with the Linear Array HPV-33/35/52/58 cross-reactive probe, but not with the HPV-33, HPV-35, and/or HPV-58 individual probes, using an HPV-52-specific real-time PCR assay with a detection level of 3.9 DNA copies/reaction. In addition, we established the prevalence of HPV-52 in 49 samples reactive with the Linear Array HPV-33/35/52/58 cross-reactive probe, but containing either HPV-33, HPV-35, and/or HPV-58 using the same approach. RESULTS The HPV-52-specific assay detected HPV-52 in all 100 samples reactive with the Linear Array HPV-33/35/52/58 cross-reactive probe, but not with the HPV-33, HPV-35, and/or HPV-58 probes. The presence of up to six other HPV genotypes did not influence the HPV-52 analytical performance of Linear Array. Only 6/49 (12.2%) samples reactive with the Linear Array HPV-33/35/52/58 cross-reactive probe, but containing either HPV-33, HPV-35 or/and HPV-58, were HPV-52 positive. CONCLUSIONS Linear Array is a highly reliable test for detecting HPV-52 in the absence of genotypes HPV-33, HPV-35, and HPV-58. Additional testing using an HPV-52-specific test is necessary when HPV-33, HPV-35, and/or HPV-58 are present in the sample.
A New Steganographic Method for Palette-Based Images

In this paper, we present a new steganographic technique for embedding messages in palette-based images, such as GIF files. The new technique embeds one message bit into one pixel (its pointer to the palette). The pixels for message embedding are chosen randomly using a pseudorandom number generator seeded with a secret key. For each pixel at which one message bit is to be embedded, the palette is searched for closest colors. The closest color with the same parity as the message bit is then used instead of the original color. This has the advantage that both the overall change due to message embedding and the maximal change in colors of pixels is smaller than in methods that perturb the least significant bit of indices to a luminance-sorted palette, such as EzStego [1]. Indeed, numerical experiments indicate that the new technique introduces approximately four times less distortion to the carrier image than EzStego. The maximal color change is 4− 5 times smaller for the new technique than that of EzStego. A technique that introduces less distortion to the carrier image will generally cause changes that are more difficult to detect, and will therefore provide more security.
Genetic Linkage Mapping of Economically Important Traits in Cultivated Tetraploid Potato (Solanum tuberosum L.)

The objective of this study was to construct a single nucleotide polymorphism (SNP)-based genetic map at the cultivated tetraploid level to locate quantitative trait loci (QTL) contributing to economically important traits in potato (Solanum tuberosum L.). The 156 F1 progeny and parents of a cross (MSL603) between “Jacqueline Lee” and “MSG227-2” were genotyped using the Infinium 8303 Potato Array. Furthermore, the progeny and parents were evaluated for foliar late blight reaction to isolates of the US-8 genotype of Phytophthora infestans (Mont.) de Bary and vine maturity. Linkage analyses and QTL mapping were performed using a novel approach that incorporates allele dosage information. The resulting genetic maps contained 1972 SNP markers with an average density of 1.36 marker per cM. QTL mapping identified the major source of late blight resistance in “Jacqueline Lee. ” The best SNP marker mapped ∼0.54 Mb from a resistance hotspot on the long arm of chromosome 9. For vine maturity, the major-effect QTL was located on chromosome 5 with allelic effects from both parents. A candidate SNP marker for this trait mapped ∼0.25 Mb from the StCDF1 gene, which is a candidate gene for the maturity trait. The identification of markers for P. infestans resistance will enable the introgression of multiple sources of resistance through marker-assisted selection. Moreover, the discovery of a QTL for late blight resistance not linked to the QTL for vine maturity provides the opportunity to use marker-assisted selection for resistance independent of the selection for vine maturity classifications.
Robust collaborative filtering

The widespread deployment of recommender systems has lead to user feedback of varying quality. While some users faithfully express their true opinion, many provide noisy ratings which can be detrimental to the quality of the generated recommendations. The presence of noise can violate modeling assumptions and may thus lead to instabilities in estimation and prediction. Even worse, malicious users can deliberately insert attack profiles in an attempt to bias the recommender system to their benefit. Robust statistics is an area within statistics where estimation methods have been developed that deteriorate more gracefully in the presence of unmodeled noise and slight departures from modeling assumptions. In this work, we study how such robust statistical methods, in particular M-estimators, can be used to generate stable recommendation even in the presence of noise and spam. To that extent, we present a Robust Matrix Factorization algorithm and study its stability. We conclude that M-estimators do not add significant stability to recommendation; however the presented algorithm can outperform existing recommendation algorithms in its recommendation quality.