Miracle-dz/UniFAR-FTUs huggingface dataset:
The Oncogenic Fusion Proteins SET-Nup214 and Sequestosome-1 (SQSTM1)-Nup214 Form Dynamic Nuclear Bodies and Differentially Affect Nuclear Protein and Poly(A)+ RNA Export*

Genetic rearrangements are a hallmark of several forms of leukemia and can lead to oncogenic fusion proteins. One example of an affected chromosomal region is the gene coding for Nup214, a nucleoporin that localizes to the cytoplasmic side of the nuclear pore complex (NPC). We investigated two such fusion proteins, SET-Nup214 and SQSTM1 (sequestosome)-Nup214, both containing C-terminal portions of Nup214. SET-Nup214 nuclear bodies containing the nuclear export receptor CRM1 were observed in the leukemia cell lines LOUCY and MEGAL. Overexpression of SET-Nup214 in HeLa cells leads to the formation of similar nuclear bodies that recruit CRM1, export cargo proteins, and certain nucleoporins and concomitantly affect nuclear protein and poly(A)+ RNA export. SQSTM1-Nup214, although mostly cytoplasmic, also forms nuclear bodies and inhibits nuclear protein but not poly(A)+ RNA export. The interaction of the fusion proteins with CRM1 is RanGTP-dependent, as shown in co-immunoprecipitation experiments and binding assays. Further analysis revealed that the Nup214 parts mediate the inhibition of nuclear export, whereas the SET or SQSTM1 part determines the localization of the fusion protein and therefore the extent of the effect. SET-Nup214 nuclear bodies are highly mobile structures, which are in equilibrium with the nucleoplasm in interphase and disassemble during mitosis or upon treatment of cells with the CRM1-inhibitor leptomycin B. Strikingly, we found that nucleoporins can be released from nuclear bodies and reintegrated into existing NPC. Our results point to nuclear bodies as a means of preventing the formation of potentially insoluble and harmful protein aggregates that also may serve as storage compartments for nuclear transport factors.
Dedicated High Performance Computer Project Investment (DHPI) for the Fleet Numerical/Air Force Weather Agency - The Navy Side

This Dedicated HPC Project Investment (DHPI) system is in support of the Fleet Numerical/Air Force Weather Agency Joint Ensemble Forecast System (JEFS). The objective of the JEFS project is to develop an ensemble modeling system for stochastic mesoscale weather forecasts which includes both initial condition uncertainty and model formulation uncertainty. These stochastic weather forecasts provide both probability of occurrence of weather events and an estimate of forecast reliability. The DHPI system is split between the Air Force Weather Agency (AFWA) in Omaha, NE, and the Fleet Numerical Meteorology and Oceanography Center (FNMOC) in Monterey, CA. Part of the model formulation uncertainty included in the ensemble is due to different forecast models and data assimilation systems in use at FNMOC and AFWA. Given the success indicated by the results from each of the individual AFWA and FNMOC mesoscale ensemble systems, it is expected that even more reliable probability forecasts and more robust estimates of forecast reliability will be possible with a combined ensemble.
Robust aggregation protocols for large-scale overlay networks

Aggregation refers to a set of functions that provide global information about a distributed system. These junctions operate on numeric values distributed over the system and can be used to count network size, determine extremal values and compute averages, products or sums. Aggregation allows important basic functionality to be achieved in fully distributed and peer-to-peer networks. For example, in a monitoring application, some aggregate reaching a specific value may trigger the execution of certain operations; distributed storage systems may need to know the total free space available; load-balancing protocols may benefit from knowing the target average load so as to minimize the transfered load. Building on the simple but efficient idea of antientropy aggregation (a scheme based on the antientropy epidemic communication model), in this paper we introduce practically applicable robust and adaptive protocols for proactive aggregation, including the calculation of average, product and extremal values. We show how the averaging protocol can be applied to compute further aggregates like sum, variance and the network size. We present theoretical and empirical evidence supporting the robustness of the averaging protocol under different scenarios.
Sexual Behaviour Related to the Spread of Sexually Transmitted Diseases—A Population-Based Survey

Behavioural patterns pertinent to the spread of sexually transmitted diseases (STD) were assessed in a random sample population study in Sweden. From a sample of 1150 individuals aged 16–31 years, 768 (68%) completed a questionnaire on past and present sexual contacts. Response rate was highest in youngest and oldest age groups. Median age at first intercourse was 16.4 years for women and 17.1 years for men; the woman's partner at first intercourse was a median of 2 years older; men chose partners of the same age for first intercourse. The time to second partner was a median of 2 years; number of lifetime partners increased with one new partner for 2.5 years. Condoms were more frequently used in younger age groups. In all age groups, 5–10% of individuals reported a high-risk behaviour for the spread of STDs.
Science Concierge: A Fast Content-Based Recommendation System for Scientific Publications

Finding relevant publications is important for scientists who have to cope with exponentially increasing numbers of scholarly material. Algorithms can help with this task as they help for music, movie, and product recommendations. However, we know little about the performance of these algorithms with scholarly material. Here, we develop an algorithm, and an accompanying Python library, that implements a recommendation system based on the content of articles. Design principles are to adapt to new content, provide near-real time suggestions, and be open source. We tested the library on 15K posters from the Society of Neuroscience Conference 2015. Human curated topics are used to cross validate parameters in the algorithm and produce a similarity metric that maximally correlates with human judgments. We show that our algorithm significantly outperformed suggestions based on keywords. The work presented here promises to make the exploration of scholarly material faster and more accurate.
Development and characterization of microsatellite loci for the endangered scrub lupine, Lupinus aridorum (Fabaceae)1

Premise of the study: Microsatellite primers were developed in scrub lupine (Lupinus aridorum, Fabaceae), an endemic species to Florida that is listed as endangered in the United States, to assess connectivity among populations, identify hybrids, and examine genetic diversity. Methods and Results: We isolated and characterized 12 microsatellite loci polymorphic in scrub lupine or in closely related species (i.e., sky-blue lupine [L. diffusus] and Gulf Coast lupine [L. westianus]). Loci showed low to moderate polymorphism, ranging from two to 14 alleles per locus and 0.01 to 0.86 observed heterozygosity. Conclusions: These loci are the first developed for Florida species of lupine and will be used to determine differentiation among species and to aid in conservation of the endangered scrub lupine.
SPC: Fast and Efficient Scalable Predictive Coding of Animated Meshes

Animated meshes are often represented by a sequence of static meshes with constant connectivity. Due to their frame‐based representation they usually occupy a vast amount of bandwidth or disk space. We present a fast and efficient scalable predictive coding (SPC) scheme for frame‐based representations of animated meshes. SPC decomposes animated meshes in spatial and temporal layers which are efficiently encoded in one pass through the animation. Coding is performed in a streamable and scalable fashion. Dependencies between neighbouring spatial and temporal layers are predictively exploited using the already encoded spatio‐temporal neighbourhood. Prediction is performed in the space of rotation‐invariant coordinates compensating local rigid motion. SPC supports spatial and temporal scalability, and it enables efficient compression as well as fast encoding and decoding. Parts of SPC were adopted in the MPEG‐4 FAMC standard. However, SPC significantly outperforms the streaming mode of FAMC with coding gains of over 33%, while in comparison to the scalable FAMC, SPC achieves coding gains of up to 15%. SPC has the additional advantage over FAMC of achieving real‐time encoding and decoding rates while having only low memory requirements. Compared to some other non‐scalable state‐of‐the‐art approaches, SPC shows superior compression performance with gains of over 16% in bit‐rate.
Detecting video events based on action recognition in complex scenes using spatio-temporal descriptor

Event detection plays an essential role in video content analysis and remains a challenging open problem. In particular, the study on detecting human-related video events in complex scenes with both a crowd of people and dynamic motion is still limited. In this paper, we investigate detecting video events that involve elementary human actions, e.g. making cellphone call, putting an object down, and pointing to something, in complex scenes using a novel spatio-temporal descriptor based approach. A new spatio-temporal descriptor, which temporally integrates the statistics of a set of response maps of low-level features, e.g. image gradients and optical flows, in a space-time cube, is proposed to capture the characteristics of actions in terms of their appearance and motion patterns. Based on this kind of descriptors, the bag-of-words method is utilized to describe a human figure as a concise feature vector. Then, these features are employed to train SVM classifiers at multiple spatial pyramid levels to distinguish different actions. Finally, a Gaussian kernel based temporal filtering is conducted to segment the sequences of events from a video stream taking account of the temporal consistency of actions. The proposed approach is capable of tolerating spatial layout variations and local deformations of human actions due to diverse view angles and rough human figure alignment in complex scenes. Extensive experiments on the 50-hour video dataset of TRECVid 2008 event detection task demonstrate that our approach outperforms the well-known SIFT descriptor based methods and effectively detects video events in challenging real-world conditions.
Domain Specific Language for Deployment of Parallel Applications on Parallel Computing Platforms

To increase the computing performance the current trend is towards applying parallel computing in which parallel tasks are executed on multiple nodes. The deployment of tasks on the computing platform usually impacts the overall performance and as such needs to be modelled carefully. In the architecture design community the deployment viewpoint is an important viewpoint to support this mapping process. In general the derived deployment views are visual notations that are not amenable for run-time processing, and do not scale well for deployment of large scale parallel applications. In this paper we propose a domain specific language (DSL) for modeling the deployment of parallel applications and for providing automated support for the deployment process. The DSL is based on a metamodel that is derived after a domain analysis on parallel computing. We illustrate the application of the DSL for a traffic simulation system and provide a set of important scenarios for using the DSL.
Icariin Attenuates Synaptic and Cognitive Deficits in an Aβ1–42-Induced Rat Model of Alzheimer's Disease

Icariin (ICA), a prenylated flavanol glycoside present in abundant quantities in Epimedium sagittatum, has shown promise in the treatment and prevention of Alzheimer's disease. Damage to synaptic plasticity induced by amyloid-beta-mediated neurotoxicity is considered a main pathological mechanism driving the learning and memory deficits present in patients with Alzheimer's disease. This study investigated the neuroprotective effects of icariin in an Aβ1–42-induced rat model of Alzheimer's disease. Our results showed that Aβ1–42 injection induced loss of learning and memory behaviour in the Morris water maze, which could be reversed with intragastric administration of ICA. Furthermore, ICA reversed decreases in PSD-95, BDNF, pTrkB, pAkt, and pCREB expressions and prevented deterioration of synaptic interface structure. These findings indicate that ICA may improve synaptic plasticity through the BDNF/TrkB/Akt pathway and provide further evidence for its clinical application to improve learning and memory in patients with Alzheimer's disease.
A Real Time Embedded Face Detector on FPGA

Intelligent computing systems demand human computer interfaces that detect and recognize the faces of human users at human interaction speeds. A real-time face detector accurately locates human faces in real-time video streams. While software implementations are effective with regards to accuracy and ease of integration, they suffer from low detection throughput on realtime video signals. In this paper we identify benefits and drawbacks of evolving face detection from software to hardware. We illustrate these tradeoffs by detailing the implementation of an artificial neural network face detector on a midsize FPGA. The prototype achieves 94% detection accuracy at real-time detection rates.
Learning a metric for class-conditional KNN

Naïve Bayes Nearest Neighbour (NBNN) is a simple and effective framework which addresses many of the pitfalls of K-Nearest Neighbour (KNN) classification. It has yielded competitive results on several computer vision benchmarks. Its central tenet is that during NN search, a query is not compared to every example in a database, ignoring class information. Instead, NN searches are performed within each class, generating a score per class. A key problem with NN techniques, including NBNN, is that they fail when the data representation does not capture perceptual (e.g. class-based) similarity. NBNN circumvents this by using independent engineered descriptors (e.g. SIFT). To extend its applicability outside of image-based domains, we propose to learn a metric which captures perceptual similarity. Similar to how Neighbourhood Components Analysis optimizes a differentiable form of KNN classification, we propose “Class Conditional” metric learning (CCML), which optimizes a soft form of the NBNN selection rule. Typical metric learning algorithms learn either a global or local metric. However, our proposed method can be adjusted to a particular level of locality by tuning a single parameter. An empirical evaluation on classification and retrieval tasks demonstrates that our proposed method clearly outperforms existing learned distance metrics across a variety of image and non-image datasets.
A framework for organizing cancer-related variations from existing databases, publications and NGS data using a High-performance Integrated Virtual Environment (HIVE)

Years of sequence feature curation by UniProtKB/Swiss-Prot, PIR-PSD, NCBI-CDD, RefSeq and other database biocurators has led to a rich repository of information on functional sites of genes and proteins. This information along with variation-related annotation can be used to scan human short sequence reads from next-generation sequencing (NGS) pipelines for presence of non-synonymous single-nucleotide variations (nsSNVs) that affect functional sites. This and similar workflows are becoming more important because thousands of NGS data sets are being made available through projects such as The Cancer Genome Atlas (TCGA), and researchers want to evaluate their biomarkers in genomic data. BioMuta, an integrated sequence feature database, provides a framework for automated and manual curation and integration of cancer-related sequence features so that they can be used in NGS analysis pipelines. Sequence feature information in BioMuta is collected from the Catalogue of Somatic Mutations in Cancer (COSMIC), ClinVar, UniProtKB and through biocuration of information available from publications. Additionally, nsSNVs identified through automated analysis of NGS data from TCGA are also included in the database. Because of the petabytes of data and information present in NGS primary repositories, a platform HIVE (High-performance Integrated Virtual Environment) for storing, analyzing, computing and curating NGS data and associated metadata has been developed. Using HIVE, 31 979 nsSNVs were identified in TCGA-derived NGS data from breast cancer patients. All variations identified through this process are stored in a Curated Short Read archive, and the nsSNVs from the tumor samples are included in BioMuta. Currently, BioMuta has 26 cancer types with 13 896 small-scale and 308 986 large-scale study-derived variations. Integration of variation data allows identifications of novel or common nsSNVs that can be prioritized in validation studies. Database URL: BioMuta: http://hive.biochemistry. gwu.edu/tools/biomuta/index.php; CSR: http://hive.biochemistry. gwu.edu/dna.cgi? cmd=csr; HIVE: http://hive.biochemistry. gwu.edu
A New Control Structure for Multiterminal DC Grids to Damp Interarea Oscillations

This paper analyzes the control structure of the multiterminal dc (MTDC) system to damp ac system interarea oscillations through active power modulation. A new control structure is presented that maximizes the relative controllability without the need for communication among the dc terminals. In point-to-point high-voltage dc (HVDC) transmission, the active power modulation of the two terminals occurs in opposite directions. In this case, the control direction is given and only needs to be phase compensated to align for maximal damping. In the case of MTDC systems, the control direction interrelates with the active power modulation share of the dc terminals and the relative controllability depends on this. The new control structure eliminates the need for communication between the dc terminals by performing dc voltage feedback loop shaping. This makes it possible to modulate the power in one terminal and let the other terminals react on the dc voltage change. Through loop shaping, where the feedback gain varies in the frequency plane compared to the regular droop design, the control direction is aligned with the direction of highest relative controllability. Loop shaping takes place without influencing the high frequency or steady-state gain. Simulations in the Nordic32 test system show the validity of the proposed controller and its structure.
The investigation and identification of a Civil Defense canister

A Civil Defense canister was found in a high school storage area with no radioactive labels or instructions. Initial screening with a 2“ x 2” NaI detector indicated elevated count rates above background. Using field instruments with gamma peak analysis features and a laboratory counting system, the collective effort indicated that the contents included 238U and 235U. A Civil Defense Item Specification introduced later in the investigation show that the canister contained approximately 3.0 g of uranyl acetate. The specification also stated that the purpose of the canister was to determine the amount of radioactive material in water and solid, or liquid food samples.
Information Retrieval as Counterfactual

Relevance, one of the fundamental notions in information retrieval (IR), has long been studied from a cognitive point of view. It is known that relevance depends not only on the topic of the document and the information need expressed in a query, but also on other 'situational' factors in the retrieval situation, such as the user's previous knowledge, background, intentions and so on. Formal models, on the other hand, usually consider relevance from a system point of view, i.e. they isolate relevance in a restricted context in which only the topic matters. One of the reasons for this very partial modeling is due to the inappropriateness of standard formal tools for describing relevance in a general context. This paper is an attempt to identify a more appropriate logical framework for the modeling. Counterfactual conditional logic is examined with respect to the IR requirements, indicating the logic's high potential value for this task. A particular conditional logic is then defined which, in comparison with previous developments on conditional logic, is better suited to IR. The new model gives an insight into the phenomena related to the 'situational' factors of relevance judgment which, until now, have not been considered.
Biological Characterization of Microenvironments in a Hypersaline Cold Spring Mars Analog

While many habitable niches on Earth are characterized by permanently cold conditions, little is known about the spatial structure of seasonal communities and the importance of substrate-cell associations in terrestrial cyroenvironments. Here we use the 16S rRNA gene as a marker for genetic diversity to compare two visually distinct but spatially integrated surface microbial mats on Axel Heiberg Island, Canadian high arctic, proximal to a perennial saline spring. This is the first study to describe the bacterial diversity in microbial mats on Axel Heiberg Island. The hypersaline springs on Axel Heiberg represent a unique analog to putative subsurface aquifers on Mars. The Martian subsurface represents the longest-lived potentially habitable environment on Mars and a better understanding of the microbial communities on Earth that thrive in analog conditions will help direct future life detection missions. The microbial mats sampled on Axel Heiberg are only visible during the summer months in seasonal flood plains formed by melt water and run-off from the proximal spring. Targeted-amplicon sequencing revealed that not only does the bacterial composition of the two mat communities differ substantially from the sediment community of the proximal cold spring, but that the mat communities are distinct from any other microbial community in proximity to the Arctic springs studied to date. All samples are dominated by Gammaproteobacteria: Thiotichales is dominant within the spring samples while Alteromonadales comprises a significant component of the mat communities. The two mat samples differ in their Thiotichales:Alteromonadales ratio and contribution of Bacteroidetes to overall diversity. The red mats have a greater proportion of Alteromonadales and Bacteroidetes reads. The distinct bacterial composition of the mat bacterial communities suggests that the spring communities are not sourced from the surface, and that seasonal melt events create ephemerally habitable niches with distinct microbial communities in the Canadian high arctic. The finding that these surficial complex microbial communities exist in close proximity to perennial springs demonstrates the existence of a transiently habitable niche in an important Mars analog site.