Miracle-dz/UniFAR-FTUs huggingface dataset:
Genotoxic Agents Detected by Plant Bioassays

Seven higher plant species (Allium cepa, Arabidopsis thaliana, Glycine max, Hordeum vulgaris. Tradescantia paludosa, Vicia faba, and Zea mays) were reviewed for their ability to detect genotoxicity of chemical agents under the U.S. Environmental Protection Agency (U.S. EPA) Gene-Tox program in the late 1970s. Six bioassays-Allium and Vicia root tip chromosome breaks, Tradescantia chromosome break, Tradescantia micronucleus, Tradescantia-stamen-hair mutation, and Arabidopsis-mutation bioassays- were established from four plant systems that are currently in use for detecting the genotoxicity of environmental agents. Under the Gene-Tox program, the Crepis capillaris-chromosome-aberration test was added to the existing six bioassays. The current review is limited to chemical agents that exhibit a positive response to any of these seven plant bioassays. From 158 articles reviewed, 84 chemicals were compiled in three categories: carcinogens, clastogens, and mutagens. As none of these plant bioassays can detect tumor initiation or cancerous growth, the chemicals were categorized as carcinogens based on their characteristics defined by the U.S. EPA's Superfund Priority 1 List and/or by the chemical listings of the Sigma and Aldrich Chemical Companies. Certain mutagens were categorized in the same manner in addition to the agents detected as mutagens by these plant bioassays.
A test of inflated zeros for Poisson regression models

Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Poisson and a zero-inflated Poisson model is commonly applied in practice. However, the type I error of the test often deviates seriously from the nominal level, rendering serious doubts on the validity of the test in such applications. In this paper, we develop a new approach for testing inflated zeros under the Poisson model. Unlike the Vuong test for inflated zeros, our method does not require a zero-inflated Poisson model to perform the test. Simulation studies show that when compared with the Vuong test our approach not only better at controlling type I error rate, but also yield more power.
Skills development in infants: a possible role for widespread neurogenesis?

There are differences in the way infants learn, perceive, and understand the environment as compared to adults (Bornstein, 1989; Nelson, 2000; Craik and Bialystok, 2006). While an adult has an established, clear perception of his environment, infants are still forming perceptions of the world (Hall et al., 1989; Holt, 1991; Zitelli and Davis, 2007). The mechanisms underlying these differences are not fully understood, but studies analyzing structural changes in infant brains give credence to a few suggestions, including increased synaptogenesis, dendritic arborization, myelination, and potentially even widespread neurogenesis.
Oligodendroglioma: clinical study and survival analysis correlated with chromosomal anomalies.

OBJECT Demonstration of the loss of chromosomes 1p and 19q in the presence of a brain neoplasm marks the emergence of genotype as a prognostic indicator. The authors report gene expression data for oligodendroglioma and correlate genotype with response to therapy. Gene expression subgroups may represent distinct types of disease. METHODS Eighty-seven cases of supratentorial oligodendroglioma were selected from 145 cases treated in a single center between January 1990 and December 2001. Fluorescence in situ hybridization was used to determine the status of chromosomes 1p and 19q. Parameters evaluated included clinical data and radiological and histological features. Univariate and multivariate analyses were performed and a probability value less than 0.05 was considered significant. The patients included 48 women and 39 men. The overall mean age at presentation was 45 years for women and 36 years for men (p = 0.006). The univariate analysis identified the following as favorable prognostic factors: younger patient age (p = 10(-5)), female sex (p = 0.0025), seizure as a presenting symptom (p = 10(-5)), normal clinical examination (p = 10(-5)), absence of lesion enhancement on neuroimaging studies (p = 0.0231), lack of histological necrosis (p = 0.0003), absence of mitoses (p = 0.0014), 1p and 19q deletions (p = 0.0001), absence of recurrence (p = 0.0021), and adjuvant radiotherapy and/or chemotherapy (p = 10(-5)). The multivariate analysis identified patient age (p = 10(-5)) and chromosomal anomalies (p = 0.002) as independently linked to survival. Three molecular subtypes emerged: oligodendroglioma with 1p and 19q deletions, oligodendroglioma demonstrating polysomia and a lack of meaningful response to radiotherapy or chemotherapy, and oligodendroglioma with no 1p-9q deletion in which partial response was seen. CONCLUSIONS According to our data, oligodendrogliomas could be divided into three molecular subtypes. Although chemotherapy seems efficient for managing this tumor, additional studies should be conducted to compare the efficacy of radiotherapy and chemotherapy.
Secrecy Outage Analysis for Downlink Transmissions in the Presence of Randomly Located Eavesdroppers

We analyze the secrecy outage probability in the downlink for wireless networks with spatially (Poisson) distributed eavesdroppers (EDs) under the assumption that the base station employs transmit antenna selection (TAS) to enhance secrecy performance. We compare the cases, where the receiving user equipment (UE) operates in half-duplex (HD) mode and full-duplex (FD) mode. In the latter case, the UE simultaneously receives the intended downlink message and transmits a jamming signal to strengthen secrecy. We investigate two models of (semi)passive eavesdropping: 1) EDs act independently and 2) EDs collude to intercept the transmitted message. For both of these models, we obtain expressions for the secrecy outage probability in the downlink for the HD and FD UE operation. The expressions for the HD systems have very accurate approximate or exact forms in terms of elementary and/or special functions for all path loss exponents. Those related to the FD systems have exact integral forms for general path loss exponents, while exact closed forms are given for specific exponents. A closed-form approximation is also derived for the FD case with colluding EDs. The resulting analysis shows that the reduction in the secrecy outage probability is logarithmic in the number of antennas used for TAS and identifies conditions, under which HD operation should be used instead of FD jamming at the UE. These performance trends and exact relations between system parameters can be used to develop adaptive power allocation and duplex operation methods in practice. Examples of such techniques are alluded to herein.
Identifying Single Copy Orthologs in Metazoa

The identification of single copy (1-to-1) orthologs in any group of organisms is important for functional classification and phylogenetic studies. The Metazoa are no exception, but only recently has there been a wide-enough distribution of taxa with sufficiently high quality sequenced genomes to gain confidence in the wide-spread single copy status of a gene. Here, we present a phylogenetic approach for identifying overlooked single copy orthologs from multigene families and apply it to the Metazoa. Using 18 sequenced metazoan genomes of high quality we identified a robust set of 1,126 orthologous groups that have been retained in single copy since the last common ancestor of Metazoa. We found that the use of the phylogenetic procedure increased the number of single copy orthologs found by over a third more than standard taxon-count approaches. The orthologs represented a wide range of functional categories, expression profiles and levels of divergence. To demonstrate the value of our set of single copy orthologs, we used them to assess the completeness of 24 currently published metazoan genomes and 62 EST datasets. We found that the annotated genes in published genomes vary in coverage from 79% (Ciona intestinalis) to 99.8% (human) with an average of 92%, suggesting a value for the underlying error rate in genome annotation, and a strategy for identifying single copy orthologs in larger datasets. In contrast, the vast majority of EST datasets with no corresponding genome sequence available are largely under-sampled and probably do not accurately represent the actual genomic complement of the organisms from which they are derived.
Fast Classification of Hyperspectral Images Using Globally Regularized Archetypal Representation With Approximate Solution

Representation learning plays a crucial rule in pattern recognition. Recently, sparse representation (SR) has become a popular technique in high-dimensional signal processing. In this paper, we provide an alternative archetypal representation (AR) to conduct the representation learning. Compared with SR, AR preserves the sparsity of the learned representation, but has a lower complexity and better interpretation. For the classification of hyperspectral image, spatial information plays an important role in improving the classification performance. Instead of representing each sample individually, we propose a globally regularized AR model, which uses graph regularization to include the contextual information into the learned representation. Although the entire model is convex, it is time consuming to obtain the optimal solution, which limits its large-scale applications. To address the computational issue, we further propose an efficient approximate solver based on line search on a feasible solution trajectory. It turns out that the approximate solution is very close the optimal solution, with a relative error less than 5% usually, but speeds up the optimization dozens of times. Experiments demonstrate that the learned representation with the approximate solution is discriminant comparable to the optimal solution. Using the learned representation as a high-level feature, a linear support vector machine works effectively to produce a high-accuracy classification.
The genetic approach to the Epstein-Barr virus: from basic virology to gene therapy

The Epstein-Barr virus (EBV) infects humans and the genome of this infectious agent has been detected in several tumour types, ranging from lymphomas to carcinomas. The analysis of the functions of the numerous viral proteins encoded by EBV has been impeded by the large size of the viral genome, which renders the construction of viral mutants difficult. To overcome these limitations, several genetic systems have been developed that allow the modification of the viral genome. Two different approaches, depending on the host cell type in which the viral mutants are generated, have been used in the past. Traditionally, mutants were constructed in EBV infected eukaryotic cells, but more recently, approaches that make use of a recombinant EBV cloned in Escherichia coli have been proposed. The phenotype associated with the inactivation or modification of nearly 20 of the 100 EBV viral genes has been reported in the literature. In most of the reported cases, the EBV latent genes that mediate the ability of EBV to immortalise infected cells were the targets of the genetic analysis, but some virus mutants in which genes involved in DNA lytic replication or infection were disrupted have also been reported. The ability to modify the viral genome also opens the way to the construction of viral strains with medical relevance. A cell line infected by a virus that lacks the EBV packaging sequences can be used as a helper cell line for the encapsidation of EBV based viral vectors. This cell line will allow the evaluation of EBV as a gene transfer system with applications in gene therapy. Finally, genetically modified non-pathogenic strains will provide a basis for the design of an attenuated EBV live vaccine.
Low-cost self-aligned SiGeC HBT module for high-performance bulk and SOI RFCMOS platforms

A low-cost SiGeC HBT module for bulk and SOI RFCMOS platforms is described. The device features an all-implanted collector and a novel fragmented emitter layout, and requires 4 masks only. Record performances are demonstrated, with cut-off frequencies fT/f max as large as 230/240GHz and 140/200GHz on bulk and thin SOI substrates respectively
Runtime resource management for embedded and HPC systems

Resource management is a well known problem in almost every computing system ranging from embedded to High Performance Computing (HPC) and is useful to optimize multiple orthogonal system metrics such as power consumption, performance and reliability. To achieve such an optimization a resource manager must suitably allocate the available system resources -- e.g. processing elements, memories and interconnect -- to the running applications. This kind of process incurs in two main problems: a) system resources are usually shared between multiple applications and this induces resource contention; and b) each application requires a different Quality of Service, making it harder for the resource manager to work in an application-agnostic mode. In this scenario, resource management represents a critical and essential component in a computing system and should act at different levels to optimize the whole system while keeping it flexible and versatile. In this paper we describe a multi-layer resource management strategy that operates at application, operating system and hardware level and tries to optimize resource allocation on embedded, desktop multi-core and HPC systems.
From Single Variants to Protein Cascades

Understanding the role of genetics in disease has become a central part of medical research. Non-synonymous single nucleotide variants (nsSNVs) in coding regions of human genes frequently lead to pathological phenotypes. Beyond single variations, the individual combination of nsSNVs may add to pathogenic processes. We developed a multiscale pipeline to systematically analyze the existence of quantitative effects of multiple nsSNVs and gene combinations in single individuals on pathogenicity. Based on this pipeline, we detected in a data set of 842 nsSNVs discovered in 76 genes related to cardiomyopathies, associated nsSNV combinations in seven genes present in at least 70% of all 639 patient samples, but not in a control cohort of healthy humans. Structural analyses of these revealed primarily an influence on the protein stability. For amino acid substitutions located at the protein surface, we generally observed a proximity to putative binding pockets. To computationally analyze cumulative effects and their impact, pathogenicity methods are currently being developed. Our approach supports this process, as shown on the example of a cardiac phenotype but can be likewise applied to other diseases such as cancer.
Towards Multi-Document Summarization of Scientific Articles:Making Interesting Comparisons with SciSumm

We present a novel unsupervised approach to the problem of multi-document summarization of scientific articles, in which the document collection is a list of papers cited together within the same source article, otherwise known as a co-citation. At the heart of the approach is a topic based clustering of fragments extracted from each co-cited article and relevance ranking using a query generated from the context surrounding the co-cited list of papers. This analysis enables the generation of an overview of common themes from the co-cited papers that relate to the context in which the co-citation was found. We present a system called SciSumm that embodies this approach and apply it to the 2008 ACL Anthology. We evaluate this summarization system for relevant content selection using gold standard summaries prepared on principle based guidelines. Evaluation with gold standard summaries demonstrates that our system performs better in content selection than an existing summarization system (MEAD). We present a detailed summary of our findings and discuss possible directions for future research.
Novel MMC control for active balancing and minimum ripple current in series-connected battery strings

The performance of a string of series-connected batteries is typically restricted by the worst battery cell in the string and a single failure point will render the entire string unusable. To address these issues, we present a decentralised battery management system based on a modular multilevel converter (MMC) with a distributed inductor. This novel MMC design enables each MMC cell to operate autonomously, without central control, by sensing the local inductor voltage. Batteries are loaded with a current proportional to their capacity, and the MMC cells also work together to minimize the output ripple voltage of the full series stack. We show experimentally that the novel decentralized controller implemented in each MMC cell can reduce the output voltage ripple by 69%. We also give an extensive theoretical analysis of the waveforms produced by the MMC using Fourier decomposition. This analysis has applications in all modular multilevel converters.
A Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6

We present and describe a catalog of galaxy photometric redshifts (photo-z’s) for the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6). We use the neural network (NN) technique to calculate photo-z’s and the nearest neighbor error (NNE) method to estimate photo-z errors for ~77 million objects classified as galaxies in DR6 with r < 22. The photo-z and photo-z error estimators are trained and validated on a sample of ~640,000 galaxies that have SDSS photometry and spectroscopic redshifts measured by SDSS, the Two Degree Field, the SDSS Luminous Red Galaxy and Quasi-stellar Object Survey (2SLAQ), the Canada-France Redshift Survey (CFRS), the Canadian Network for Observational Cosmology Field Galaxy Survey (CNOC2), the Team Keck Redshift Survey (TKRS), the Deep Extragalactic Evolutionary Probe (DEEP), and DEEP2. For the two best NN methods we have tried, we find that 68% of the galaxies in the validation set have a photo-z error smaller than σ68 = 0.021 or 0.024. After presenting our results and quality tests, we provide a short guide for users accessing the public data.
High-speed photographic study of impact on fibers and woven fabrics

The paper describes a study of the behaviour of fibres and woven fabrics when impacted at velocities in the range up to - l000m 1. The projectiles, typically steel balls of 2 or 5mm diameter, were accelerated by a double diaphragm gas gun which allowed velocities to be controlled within a few metres per second. The impact events were viewed using high-speed photography. Photography at microsecond framing intervals was made using an image converter camera (the Hadland Imacon). This camera was triggered when the projectile interrupted a laser beam positioned just in front of the specimen. In experiments with single fibres, it was possible to measure the transverse wave speeds. Experiments were made with a number of fibre materials covering a wide range of moduli and strength properties. A number of experiments were also made with woven fabrics of different densities and laminates. The velocity range covered included non-penetrating and penetrating events. The fibre materials which had the best ballistic performance were those which combined a high dynamic modulus with the ability to reach large strains before failure. The high modulus is important since it affects both the strength and the stress wave velocities. If a material has high wave velocities it can spread the load onto other fibres and layers more quickly which is beneficial.
Improving swallowing outcomes in patients with head and neck cancer using a theory-based pretreatment swallowing intervention package: protocol for a randomised feasibility study

Introduction The incidence of head and neck cancer (HNC) in the UK is rising, with an average of 31 people diagnosed daily. Patients affected by HNC suffer significant short-term and long-term post-treatment morbidity as a result of dysphagia, which affects daily functioning and quality of life (QOL). Pretreatment swallowing exercises may provide additional benefit over standard rehabilitation in managing dysphagia after primary HNC treatments, but uncertainty about their effectiveness persists. This study was preceded by an intervention development phase to produce an optimised swallowing intervention package (SIP). The aim of the current study is to assess the feasibility of this new intervention and research processes within a National Health Service (NHS) setting. Method and analysis A two-arm non-blinded randomised controlled feasibility study will be carried out at one tertiary referral NHS centre providing specialist services in HNC. Patients newly diagnosed with stage III and IV disease undergoing planned surgery and/or chemoradiation treatments will be eligible. The SIP will be delivered pre treatment, and a range of swallowing-related and QOL measures will be collected at baseline, 1, 3 and 6 months post-treatment. Outcomes will test the feasibility of a future randomised controlled trial (RCT), detailing rate of recruitment and patient acceptance to participation and randomisation. Salient information relating to protocol implementation will be collated and study material such as the case report form will be tested. A range of candidate outcome measures will be examined for suitability in a larger RCT. Ethics and dissemination Ethical approval was obtained from an NHS Research Ethics Committee. Findings will be published open access in a peer-reviewed journal, and presented at relevant conferences and research meetings. Trial registration number ISRCTN40215425; Pre-results.
A bottom-up dictionary learning based classification for face recognition

The design of image descriptor and classifier are two important issues in face recognition. Although many facial image descriptors (e.g., subspace learning, local binary pattern) and classifier (e.g., support vector machine, sparse representation based classifier) have been proposed, these two components seldomly belong to a same framework, which may prevent the discrimination being fully exploited. Inspired by the success of dictionary learning based descriptor and classifier, in this paper, we proposed a bottom-up dictionary learning based classification (BUDL-C) for face recognition. In BUDLC, we generate the image descriptor via encoding local patches on a learned dictionary with a regularization of spatial and appearance consistence. Then with the generated image descriptor, a structured discriminative dictionary is learned for the image classifier by using the mixed-norm joint sparse representation. The BUDLC are extensively evaluated on several benchmark face databases, such as AR, Multi-PIE and LFW. Experimental results demonstrate that our algorithm outperforms many existing face recognition approaches.
Using of finite element method for modeling of active cochlea

Human hearing system in general, and particularly the cochlea, is very interesting for investigation. The most important reason for it is hearing loss - a health problem that affects a large part of the world's human population. The highest percentage of people with hearing problems are older people, but the problem also occurs in newborns. Experimental research in this area provides some information about the level of hearing loss. Therefore, it is very useful to have a numerical model of the hearing system that can significantly contribute to the understanding of the origin of the mentioned health problem. Two numerical models are developed to investigate hearing problems: passive 3D cochlea model and 2D cochlea cross-section model. Those models are weakly coupled in order to make an active cochlea model [1].