Miracle-dz/UniFAR-FTUs huggingface dataset:
A Day in the Life of Microcystis aeruginosa Strain PCC 7806 as Revealed by a Transcriptomic Analysis

The cyanobacterium, Microcystis aeruginosa, is able to proliferate in a wide range of freshwater ecosystems and to produce many secondary metabolites that are a threat to human and animal health. The dynamic of this production and more globally the metabolism of this species is still poorly known. A DNA microarray based on the genome of M. aeruginosa PCC 7806 was constructed and used to study the dynamics of gene expression in this cyanobacterium during the light/dark cycle, because light is a critical factor for this species, like for other photosynthetic microorganisms. This first application of transcriptomics to a Microcystis species has revealed that more than 25% of the genes displayed significant changes in their transcript abundance during the light/dark cycle and in particular during the dark/light transition. The metabolism of M. aeruginosa is compartmentalized between the light period, during which carbon uptake, photosynthesis and the reductive pentose phosphate pathway lead to the synthesis of glycogen, and the dark period, during which glycogen degradation, the oxidative pentose phosphate pathway, the TCA branched pathway and ammonium uptake promote amino acid biosynthesis. We also show that the biosynthesis of secondary metabolites, such as microcystins, aeruginosin and cyanopeptolin, occur essentially during the light period, suggesting that these metabolites may interact with the diurnal part of the central metabolism.
Comparison of double crystal (+n,-m) and (+n,+m) settings containing a fully asymmetric diffraction geometry of a bent perfect crystal with the output beam expansion

In this paper neutron diffraction properties of the dispersive double crystal (+n,-m) and (+n,+m) settings containing the bent perfect crystal Si(220) in symmetric diffraction geometry and the bent perfect crystal Si(311) in the fully asymmetric diffraction geometry with the output beam expansion are studied and compared. It has been found that the properties, namely, the width of the output double diffracted beam, of both settings strongly depends on the relative combination of curvatures of Si(311) crystal slab with respect to the curvature of the Si(220) one. Moreover, after the beam expansion the fully asymmetric diffraction geometry provides in both cases a highly collimated and highly monochromatic beam of a rather large cross-section of several square centimetres. Application possibilities, of such a beam, namely for neutron phase contrast radiography will be discussed.
Segmentation and Grouping for Tactile Graphics

The goal of our research is to develop computer software capable of automating the conversion of figures and diagrams in a book to a tactile format readily understandable by blind persons. Among the challenges this goal poses is the need to find and remove text from the figures and diagrams for eventual conversion to Braille. Since conventional optical character recognition (OCR) software is poorly suited to the task of finding short pieces of text embedded within images, we are exploring new methods based on machine learning. By exploiting the consistent style of figures and diagrams in a book, we can improve text recognition accuracy over that provided by OCR. The algorithm described herein is able to recognize a high percentage of the text once provided with a small training set from which to base its predictions. We discuss the specifics of the algorithm, its effectiveness, and its relationship with existing commercial OCR software. ∗Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195. Email: mrenz@cs.washington. edu. This research is supported by the Mary Gates Endowment at the University of Washington, and by NSF Grant No. IIS-0415273.
Examination of the frequency modulation and lifting techniques for the generalized power factor correction switched‐capacitor resonant converter

A generalized method for switched‐capacitor resonant converter for use in power factor correction is proposed. Using the techniques, the voltage conversion can be generated into step‐up, step‐down and inverting. The requirement of the inductance in the circuit is minimal. The quality of the power factor improvement is substantial. The method used in the converter includes the frequency modulation and lifting techniques. The power factor improvement is significant and the circuit concept is simple. Mathematical analysis and experimental confirmation have been presented to demonstrate the novel idea. Copyright © 2007 John Wiley & Sons, Ltd.
Cytolethal Distending Toxin Enhances Radiosensitivity in Prostate Cancer Cells by Regulating Autophagy

Cytolethal distending toxin (CDT) produced by Campylobacter jejuni contains three subunits: CdtA, CdtB, and CdtC. Among these three toxin subunits, CdtB is the toxic moiety of CDT with DNase I activity, resulting in DNA double-strand breaks (DSB) and, consequently, cell cycle arrest at the G2/M stage and apoptosis. Radiation therapy is an effective modality for the treatment of localized prostate cancer (PCa). However, patients often develop radioresistance. Owing to its particular biochemical properties, we previously employed CdtB as a therapeutic agent for sensitizing radioresistant PCa cells to ionizing radiation (IR). In this study, we further demonstrated that CDT suppresses the IR-induced autophagy pathway in PCa cells by attenuating c-Myc expression and therefore sensitizes PCa cells to radiation. We further showed that CDT prevents the formation of autophagosomes via decreased high-mobility group box 1 (HMGB1) expression and the inhibition of acidic vesicular organelle (AVO) formation, which are associated with enhanced radiosensitivity in PCa cells. The results of this study reveal the detailed mechanism of CDT for the treatment of radioresistant PCa.
Estimating Heterogeneous Treatment Effects of a Fractions Tutor

In this project, we aim to estimate the effect of different teaching strategies in a tutoring system on student learning and how that effect varies across different groups of students. More specifically, we want to shed light on whether choosing exercise problems adaptively based on prior student performance is more effective at teaching elementary school students about fractions than non-adaptive problem selection strategies. To this end, we analyze data of a recent study performed by Doroudi et al. (2017) and estimate heterogeneous treatments effects (HTE) using basic Monte-Carlo estimation as well as 3 recently proposed state-of-the-art methods for HTE estimation. While the estimates suggest that there may be small positive effects in 5 grade students and students of certain schools, none of the detected effects is statistically significant. This result raises the question what effect sizes current methods are able to detect for a given number of samples and shows the need for further extensive experimental comparisons across a wide range of scenarios.
Generation of a MLL-AF9-specific stem cell model of acute monocytic leukemia

Abstract Acute monocytic leukemia (AML-M5), a subtype of acute myeloid leukemia (AML), affects mostly young children and has poor prognosis. The mechanisms of treatment failure of AML-M5 are still unclear. In this study, we generated iPSC from THP-1 cells from a patient with AML-M5, using retroviruses encoding the pluripotency-associated genes (OCT3/4, SOX2, KLF4 and c-MYC). These AML-M5-derived iPSC showed features similar with those of human embryonic stem cells in terms of the morphology, gene expression, protein/antigen expression and differentiation capability. Parental-specific markers were down-regulated in these AML-M5-derived iPSCs. Expression of MLL-AF9 fusion gene (previously identified to be associated with pathogenesis of AML-M5) was observed in all iPSC clones as well as parental cells. We conclude that AML-M5-specific iPSC clones have been successfully developed. This disease model may provide a novel approach for future study of pathogenesis and therapeutic intervention of AML-M5.
Bending Investigation of Broadband Wearable All-Textile Antennas

This investigation proposes a method of consistently evaluating wearable textile antennas when operating in bent conditions. This is to emulate the usage of these antennas in practice, when operating on a real human arm in bent conditions. Two similarly-shaped Planar Inverted-F Antenna (PIFA) made from a common substrate and different flexible metallic conductors and are studied. Both antennas are bent in two different orthogonal axes on three different cylindrical sizes, 20, 40 and 60 mm in radius. These cylinders are defined using electrical properties similar to the human arm at 2.5 GHz. Bending in the axis along the antenna's radiating edge, i.e. at the x-direction using the smallest sized cylinder was found to be the worst performing configuration in terms of reflection coefficient, bandwidth, and gain.
Edge-Preserving Piecewise Linear Image Smoothing Using Piecewise Constant Filters

Most image smoothing filters in the literature assume a piecewise constant model of smoothed output images. However, the piecewise constant model assumption can cause artifacts such as gradient reversals in applications such as image detail enhancement, HDR tone mapping, etc. In these applications, a piecewise linear model assumption is more preferred. In this paper, we propose a simple yet very effective framework to smooth images of piecewise linear model assumption using classical filters with the piecewise constant model assumption. Our method is capable of handling with gradient reversal artifacts caused by the piecewise constant model assumption. In addition, our method can further help accelerated methods, which need to quantize image intensity values into different bins, to achieve similar results that need a large number of bins using a much smaller number of bins. This can greatly reduce the computational cost. We apply our method to various classical filters with the piecewise constant model assumption. Experimental results of several applications show the effectiveness of the proposed method.
Recognition of bones from X-rays of the hand†

Algorithms for the computer recognition of bones in an X-ray of the hand and wrist are described by analysing age-related changes that take place with growth in the bones. Since a straightforward structural description is inadequate because of these changes, the paper considers a shape description technique based on linear measurements (axial length, width and location) from a polygonal approximation of the bones. The recognition algorithm also needs strong a priori knowledge of the structure of the hand. System effectiveness is demonstrated on some sections of two typical X-rays of 10–12-year-old boys when histogram equalization, thresholding and edge detection, and octal code generation techniques are included in the preprocessing algorithm.
Locomotion control for the planar articulated leg robot based on the positon decoupling algorithm

This paper presents a position control algorithm based on the kinematics model to perform motion control in the planar articulated leg robot. The simplified planar robot has two articulated legs, each of which has two degrees of freedom (DoF), the knee and the hip joints, and a rotating joint without actuation, the foot. After a brief description of the planar model, the kinematics analysis is performed and developed. And then, in order to achieve the stable motion, controllers in the stance and swing phase are designed. Meanwhile, some strategies are described to contribute to the locomotion, which consists of the forward velocity estimation, placing the feet in key locations on each step, motion planning and the friction cone constraints. Last but not least, the simulations of the stable motion and the maximum velocity are carried to verify the feasibility of the planar model and the designed controllers. The results indicate that the proposed position control is effective to the motion of the planar articulated leg robot and the maximum forward velocity can reach 0.5m/s under the existing conditions.
Detection of tooth fractures in CBCT images using attention index estimation

The attention index (𝜑) is a number from zero to one that indicates a possible fracture is detected inside a selected tooth. The higher the 𝜑 number, the greater the likelihood for needed attention in the visual examination. The method developed for the 𝜑 estimation extracts a connected component with image properties that are similar to those of a typical tooth fracture. That is, in cone-beam computed tomography (CBCT) images, a fracture appears as a dark canyon inside the tooth. In order to start the visual examination process, the method provides a plane across the geometric center of the suspicious fracture component, which maximizes the number of pixels from that component inside the plane. During visual examination, the user (doctor) can change plane orientations and locations, by manipulating the mouse toward different graphical elements that represent the plane on a 3-D rendition of the tooth, while the corresponding image of the plane is shown at its side. The visual examination aims at confirming or disproving the fracture-detection event. We have designed and implemented these algorithms using the image-foresting transform methodology.
Identification of Antigens Specific to Non-Tuberculous Mycobacteria: The Mce Family of Proteins as a Target of T Cell Immune Responses

The lack of an effective TB vaccine hinders current efforts in combating the TB pandemic. One theory as to why BCG is less protective in tropical countries is that exposure to non-tuberculous mycobacteria (NTM) reduces BCG efficacy. There are currently several new TB vaccines in clinical trials, and NTM exposure may also be relevant in this context. NTM exposure cannot be accurately evaluated in the absence of specific antigens; those which are known to be present in NTM and absent from M. tuberculosis and BCG. We therefore used a bioinformatic pipeline to define proteins which are present in common NTM and absent from the M. tuberculosis complex, using protein BLAST, TBLASTN and a short sequence protein BLAST to ensure the specificity of this process. We then assessed immune responses to these proteins, in healthy South Africans and in patients from the United Kingdom and United States with documented exposure to NTM. Low level responses were detected to a cluster of proteins from the mammalian cell entry family, and to a cluster of hypothetical proteins, using ex vivo ELISpot and a 6 day proliferation assay. These early findings may provide a basis for characterising exposure to NTM at a population level, which has applications in the field of TB vaccine design as well as in the development of diagnostic tests.
HDACs Regulate miR-133a Expression in Pressure Overload–Induced Cardiac Fibrosis

Background—MicroRNAs (miRNAs) and histone deacetylases (HDACs) serve a significant role in the pathogenesis of a variety of cardiovascular diseases. The transcriptional regulation of miRNAs is poorly understood in cardiac hypertrophy. We investigated whether the expression of miR-133a is epigenetically regulated by class I and IIb HDACs during hypertrophic remodeling. Methods and Results—Transverse aortic constriction (TAC) was performed in CD1 mice to induce pressure overload hypertrophy. Mice were treated with class I and IIb HDAC inhibitor (HDACi) via drinking water for 2 and 4 weeks post TAC. miRNA expression was determined by real-time polymerase chain reaction. Echocardiography was performed at baseline and post TAC end points for structural and functional assessment. Chromatin immunoprecipitation was used to identify HDACs and transcription factors associated with miR-133a promoter. miR-133a expression was downregulated by 0.7- and 0.5-fold at 2 and 4 weeks post TAC, respectively, when compared with vehicle control (P<0.05). HDAC inhibition prevented this significant decrease 2 weeks post TAC and maintained miR-133a expression near vehicle control levels, which coincided with (1) a decrease in connective tissue growth factor expression, (2) a reduction in cardiac fibrosis and left atrium diameter (marker of end-diastolic pressure), suggesting an improvement in diastolic function. Chromatin immunoprecipitation analysis revealed that HDAC1 and HDAC2 are present on the miR-133a enhancer regions. Conclusions—The results reveal that HDACs play a role in the regulation of pressure overload–induced miR-133a downregulation. This work is the first to provide insight into an epigenetic-miRNA regulatory pathway in pressure overload–induced cardiac fibrosis.
A Level-Synchronous Approach to Ill-formed Sentence Parsing and Error Recovery

In this paper, a level-synchronous parsing mechanism, named Phrase-Level Building (PLB), is proposed to incorporate wide-scope contextual information for parsing ill-formed sentences. This mechanism regards the task of parsing a sentence as the task of building the phrase-levels for the sentence. Therefore, the wide-scope contextual information in the phrase-levels can be used to help narrow down the search space and to select the most likely partial parses. Compared with the system which uses both the stochastic context-free grammar and the heuristics of preferring the longest phrase, the proposed PLB approach improves the precision rate for brackets in the partial parse forests from 69.37% to 79.49%. The recall rate for brackets is also improved from 78.73% to 81.39%. The proposed PLB parsing method can also be used to recover errors in ill-formed sentences, so that more complete syntactic information can be provided in later stages. Experimental results show that 35% of the ill-formed sentences can be recovered to well-formed parses. The recall rate for brackets is also significantly improved from 68.49% to 76.60% while the precision rate for brackets is improved slightly from 79.49% to 80.69%.
Efficacy of Short-Term High-Dose Statin in Preventing Contrast-Induced Nephropathy: A Meta-Analysis of Seven Randomized Controlled Trials

Background A few studies focused on statin therapy as specific prophylactic measures of contrast-induced nephropathy have been published with conflicting results. In this meta-analysis of randomized controlled trials, we aimed to assess the effectiveness of shor-term high-dose statin treatment for the prevention of CIN and clinical outcomes and re-evaluate of the potential benefits of statin therapy. Methods We searched PubMed, OVID, EMBASE, Web of science and the Cochrane Central Register of Controlled Trials databases for randomized controlled trials comparing short-term high-dose statin treatment versus low-dose statin treatment or placebo for preventing CIN. Our outcome measures were the risk of CIN within 2–5 days after contrast administration and need for dialysis. Results Seven randomized controlled trials with a total of 1,399 patients were identified and analyzed. The overall results based on fixed-effect model showed that the use of short-term high-dose statin treatment was associated with a significant reduction in risk of CIN (RR = 0.51, 95% CI 0.34–0.76, p = 0.001; I2 = 0%). The incidence of acute renal failure requiring dialysis was not significant different after the use of statin (RR = 0.33, 95% CI 0.05–2.10, p = 0.24; I2 = 0%). The use of statin was not associated with a significant decrease in the plasma C-reactive protein level (SMD −0.64, 95% CI: −1.57 to 0.29, P = 0.18, I2 = 97%). Conclusions Although this meta-analysis supports the use of statin to reduce the incidence of CIN, it must be considered in the context of variable patient demographics. Only a limited recommendation can be made in favour of the use of statin based on current data. Considering the limitations of included studies, a large, well designed trial that incorporates the evaluation of clinically relevant outcomes in participants with different underlying risks of CIN is required to more adequately assess the role for statin in CIN prevention.
Maternal caffeine intake from coffee and tea, fetal growth, and the risks of adverse birth outcomes: the Generation R Study.

BACKGROUND Caffeine is a widely used and accepted pharmacologically active substance. The effect of caffeine intake during pregnancy on fetal growth and development is still unclear. OBJECTIVE We examined the associations of maternal caffeine intake, on the basis of coffee and tea consumption, with fetal growth characteristics measured in each trimester of pregnancy and the risks of adverse birth outcomes. DESIGN Associations were studied in 7346 pregnant women participating in a population-based prospective cohort study from early pregnancy onward in the Netherlands (2001-2005). Caffeine intake in the first, second, and third trimesters was on the basis of coffee and tea consumption and was assessed by questionnaires. Fetal growth characteristics were repeatedly measured by ultrasound. Information about birth outcomes was obtained from hospital records. RESULTS We observed no consistent associations of caffeine intake with fetal head circumference or estimated fetal weight in any trimester. Higher caffeine intake was associated with smaller first-trimester crown-rump length, second- and third-trimester femur length, and birth length (P for trend <0.05). Offspring of mothers who consumed > or =6 caffeine units/d tended to have increased risks of small-for-gestational-age infants at birth. CONCLUSIONS Our results suggest that caffeine intake of > or =6 units/d during pregnancy is associated with impaired fetal length growth. Caffeine exposure might preferentially adversely affect fetal skeletal growth. Further studies are needed to assess these associations in non-European populations and to assess the postnatal consequences.
Online topology estimation for vector autoregressive processes in data networks

An important problem in data sciences pertains to inferring causal interactions among a collection of time series. Upon modeling these as a vector autoregressive (VAR) process, this paper deals with estimating the model parameters to identify the underlying causality graph. To exploit the sparse connectivity of causality graphs, the proposed estimators minimize a group-Lasso regularized functional. To cope with real-time applications, big data setups, and possibly time-varying topologies, two online algorithms are presented to recover the sparse coefficients when observations are received sequentially. The proposed algorithms are inspired by the classic recursive least squares (RLS) algorithm and offer complementary benefits in terms of computational efficiency. Numerical results showcase the merits of the proposed schemes in both estimation and prediction tasks.
Exploiting Social Q&A Collection in Answering Complex Questions

This paper investigates techniques to automatically construct training data from social Q&A collections such as Yahoo! Answer to support a machine learning-based complex QA system 1 . We extract cue expressions for each type of question from collected training data and build question-type-speciﬁc classiﬁers to improve complex QA system. Experiments on 10 types of complex Chinese questions verify that it is effective to mine knowledge from social Q&A collections for answering complex questions, for instance, the F 3 improvement of our sys-tem over the baseline and translation-based model reaches 7.9% and 5.1%, respectively.