Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Complexity Motion-Compensated Beamforming Algorithm and Architecture for Synthetic Transmit Aperture in Ultrasound Imaging

Synthetic transmit aperture (STA) has been widely investigated in ultrasound system recently with characteristics of high frame rate and low hardware cost. Since the high-resolution image (HRI) of STA is formed by summation of low-resolution images (LRIs), it is susceptible to inter-firing motions. In this paper, we propose a low-complexity global motion compensation algorithm. We use the common region of interest (ROIcom) between different transmissions of STA imaging to beamform backward and forward beam vectors. Then, the magnitude and direction of motion can be evaluated by cross-correlations between specific beam vectors in STA imaging. Compared with the uncompensated image in two-dimentional (2D) motion environment, the proposed motion compensation algorithm can improve the contrast ratio (CR) and contrast-to-noise ratio (CNR) by 13.73 and 2.04 dB, respectively. Also, the proposed algorithm improves the CR and CNR about 7.84 and 1.36 dB comparing with the reference work, respectively. In the Field II breath model, the proposed method also improves the CR and CNR about 6.65 and 1.04 dB than the reference method, respectively. Moreover, we propose a low-complexity delay generator in the architecture design to further reduce the computational complexity of the whole beamforming system. Finally, we verify the proposed low-complexity motion compensation beamforming engine by using the VLSI implementation with CMOS 90 nm technology. In the post-layout result, the core size is 2.39 mm2 at 125 MHz operating frequency and the frame rate of the beamforming system is 42.23 frames per second.
Angiographic features after photodynamic therapy for choroidal neovascularisation in age related macular degeneration and pathological myopia

Aim: To describe the angiographic features after photodynamic therapy (PDT) with verteporfin in choroidal neovascularisation (CNV) associated both with age related macular degeneration (AMD) and pathological myopia (PM). Methods: 36 patients affected by subfoveal CNV in AMD and 25 patients with subfoveal CNV in PM underwent an ophthalmological examination including fluorescein angiography (FA) and indocyanine green angiography (ICGA) using the IMAGEnet System. Post-PDT examinations were performed 7, 30, and 90 days later. Results: The typical angiographic aspect after PDT for AMD related CNV was a round hypofluorescence visible both on FA and on ICGA, which included both CNV and the surrounding tissues and corresponded to the area exposed to laser light. In PM the CNV appeared hypofluorescent during the early phases and gradually became hyperfluorescent during the late phases on FA, whereas on ICGA it was detectable in its whole extension as a hyperfluorescent lesion since the early phases. Differently from AMD, there was no round hypofluorescence surrounding the CNV on FA or on ICGA. Moreover, five patients in the AMD group showed hot spots on ICGA, which spontaneously disappeared during the follow up. Classic and occult components of the AMD related CNV revealed a different angiographic response to PDT, showing with the latter only a partial closure 1 week after PDT followed by a complete reopening at the first month in 100% of cases. Conclusion: The post-PDT hypofluorescence typical of AMD related CNV, especially visible on FA, might be secondary to a combination of choriocapillary occlusion and masking effect due to swelling of retinal pigment epithelium cells. Hot spots in the AMD affected patients could be interpreted as the expression of a non-thermal choroidal vasculitis secondary to PDT.
Incremental Maintenance of Online Summaries Over Multiple Streams

We propose a novel approach based on predictive quantization (PQ) for online summarization of multiple time-varying data streams. A synopsis over a sliding window of most recent entries is computed in one pass and dynamically updated in constant time. The correlation between consecutive data elements is effectively taken into account without the need for preprocessing. We extend PQ to multiple streams and propose structures for real-time summarization and querying of a massive number of streams. Queries on any subsequence of a sliding window over multiple streams are processed in real time. We examine each component of the proposed approach, prediction, and quantization separately and investigate the space-accuracy trade-off for synopsis generation. Complementing the theoretical optimality of PQ-based approaches, we show that the proposed technique, even for very short prediction windows, significantly outperforms the current techniques for a wide variety of query types on both synthetic and real data sets.
Oxide dispersion-strengthened silver: manufacturing and properties

Abstract Novel oxide dispersion-strengthened (ODS) silver alloys were synthesised by mechanical alloying and subsequent consolidation via hot pressing in protective atmosphere. The effect of dispersoid size and volume fraction on the electrical and mechanical properties is exemplified with Cr2O3, CaO and Y2O3 as model candidates for a systematic study of the principles of particle selection. The results for the development of the microstructure under different processing conditions show that control of the impurity level is of primary importance for achieving high-quality, fully dense material. Hence, a modified cryo-milling technique at liquid-N2 temperature was applied. Data at ambient temperature are presented, revealing that the mechanical and electrical properties can be tailored within a wide range as a function of the microstructure. These results are explained by microstructural concepts for room temperature yielding and electrical conductivity.
Argument extraction for supporting public policy formulation

In this paper we describe an application of language technology to policy formulation, where it can support policy makers assess the acceptance of a yet-unpublished policy before the policy enters public consultation. One of the key concepts is that instead of relying on thematic similarity, we extract arguments expressed in support or opposition of positions that are general statements that are, themselves, consistent with the policy or not. The focus of this paper in this overall pipeline, is identifying arguments in text: we present and empirically evaluate the hypothesis that verbal tense and mood are good indicators of arguments that have not been explored in the relevant literature.
Development of a RT-PCR for the Detection of European Brown Hare Syndrome Virus

To develop the reverse transcriptase polymerase chain reaction (RT-PCR) for the detection of European brown hare syndrome virus (EBHSV), 3 specific primers and 9 overlapping oligo primers were designed to amplify a fragment of 335 nucleotides from the genome of EBHSV according to the genome sequences published in GenBank, and a 359 bp DNA fragment of the capsid protein(VP60)gene of EBHSV was synthesized in vitro by using overlap extension PCR to construct the recombinant plasmids pGM-T-EBHSV, then the RT-PCR method was described through the optimization of reaction conditions, sensitivity and specificity tests. Results showed the RT-PCR method was supplied for the detection of EBHSV with good specificity and sensitivity. The sensitivity of the RT-PCR could reach about 50 copies of cloned viral genomic fragments (pGM-T-EBHSV), and no amplifications for RHDV, Pasteurella multocida, E.coli and Salmonella from rabbits detection by this approach.
Molecular cloning and characterization of UDP-glucose : furaneol glucosyltransferase gene from grapevine cultivar Muscat

2,5-Dimethyl-4-hydroxy-3(2H)-furanone (furaneol) is an important aroma compound in fruits, such as pineapple and strawberry, and is reported to contribute to the strawberry-like note in some wines. Several grapevine species are used in winemaking, and furaneol is one of the characteristic aroma compounds in wines made from American grape (Vitis labrusca) and its hybrid grape. Furaneol glucoside was recently isolated as an important furaneol derivative from the hybrid grapevine cultivar, Muscat Bailey A (V. labrusca × V. vinifera), and this was followed by its isolation from some fruits such as strawberry and tomato. Furaneol glucoside is a significant ‘aroma precursor of wine’ because furaneol is liberated from it during alcoholic fermentation. In this study, a glucosyltransferase gene from Muscat Bailey A (UGT85K14), which is responsible for the glucosylation of furaneol was identified. UGT85K14 was expressed in the representative grape cultivars regardless of species, indicating that furaneol glucoside content is regulated by the biosynthesis of furaneol. On the other hand, furaneol glucoside content in Muscat Bailey A berry during maturation might be controlled by the expression of UGT85K14 along with the biosynthesis of furaneol. Recombinant UGT85K14 expressed in Escherichia coli is able to transfer a glucose moiety from UDP-glucose to the hydroxy group of furaneol, indicating that this gene might be UDP-glucose: furaneol glucosyltransferase in Muscat Bailey A.
Verification and Performance of the DeNovo cache coherence protocol

With the advent of multicores, parallel programming has gained a lot of importance. For parallel programming to be viable for the predicted hundreds of cores per chip, shared memory programming languages and environments must evolve to enforce disciplined practices like “determinism-by-default semantics” and ban “wild shared-memory behaviors” like arbitrary data races and potential non-determinism everywhere. This evolution can not only benefit software development, but can also greatly reduce the complexity in hardware. DeNovo is a hardware architecture designed from the ground up to exploit the opportunities exposed by such disciplined software models to make the hardware much simpler and efficient at the same time. This thesis describes an effort to formally verify and evaluate the DeNovo cache coherence protocol. By using a model checking tool, we uncovered three bugs in the protocol implementation which had not been found either in the testing phase or in the simulation runs. All of these bugs were caused by errors in translating the high level description into the implementation. Surprisingly, we also found six bugs in a state-of-the-art implementation of the widely used MESI protocol. Most of these bugs were hard to analyze and took several days to fix. We provide quantitative evidence that DeNovo is a much simpler protocol by showing that the DeNovo protocol has about 15X fewer reachable states when compared to MESI when using the Murphi model checking tool for verification. This translates to about 20X difference in the runtime of the tool. Finally, we show that this simplicity of the DeNovo protocol does not compromise performance for the applications we evaluated. On the contrary, for some applications, DeNovo achieves up to 67% reduction in memory stall time and up to 70% reduction in network traffic when compared to MESI.
Predicting Personality on Social Media with Semi-supervised Learning

Personality research on social media is a hot topic recently due to the rapid development of social media as well as the central importance of personality study in psychology, but most studies are conducted on inadequate label samples. Our research aims to explore the usage of unlabeled samples to improve the prediction accuracy. By conducting n user study with 1792 users, we adopt local linear semi-supervised regression algorithm to predict the personality traits of Micro blog users. Given a set of Micro blog users' public information (e.g., Number of followers) and a few labeled users, the task is to predict personality of other unlabeled users. The local linear semi-supervised regression algorithm has been employed to establish prediction model in this paper, and the experimental results demonstrate the usage of unlabeled data can improve the accuracy of prediction.
Outliers detection on protein localization sites by partitional clustering methods

A large molecule composed of one or more chains of amino acids in a specific order, the order is determined by the base sequence of nucleotides in the gene that codes for the protein. Proteins are required for the structure, function, and regulation of the body's cells, tissues, and organs and each protein has unique functions. Localization sites of proteins are identified by the mechanism and moved to its corresponding organelles. In this paper, we introduce the method clustering and its type's K-Means and K-Medoids. The clustering algorithms are improved by implementing the two initial centroid selection methods instead of selecting centroid randomly. K-Means algorithm can be improved by implementing the initial cluster centroids are selected by the two proposed algorithms instead of selecting centroids randomly, which is compared by using Davie Bouldin index measure, hence the proposed algorithm1 overcomes the drawbacks of selecting initial cluster centers then other methods. In the yeast dataset, the defective proteins (objects) are considered as outliers, which are identified by the clustering methods with ADOC (Average Distance between Object and Centroid) function. The outlier's detection method and performance analysis method are studied and compared, the experimental results shows that the K-Medoids method performs well when compare with the K-Means clustering.
Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions

In this work we develop efficient methods for learning random MAP predictors for structured label problems. In particular, we construct posterior distributions over perturbations that can be adjusted via stochastic gradient methods. We show that any smooth posterior distribution would suffice to define a smooth PAC-Bayesian risk bound suitable for gradient methods. In addition, we relate the posterior distributions to computational properties of the MAP predictors. We suggest multiplicative posteriors to learn super-modular potential functions that accompany specialized MAP predictors such as graph-cuts. We also describe label-augmented posterior models that can use efficient MAP approximations, such as those arising from linear program relaxations.
Dissection of Protein Interactomics Highlights MicroRNA Synergy

Despite a large amount of microRNAs (miRNAs) have been validated to play crucial roles in human biology and disease, there is little systematic insight into the nature and scale of the potential synergistic interactions executed by miRNAs themselves. Here we established an integrated parameter synergy score to determine miRNA synergy, by combining the two mechanisms for miRNA-miRNA interactions, miRNA-mediated gene co-regulation and functional association between target gene products, into one single parameter. Receiver operating characteristic (ROC) analysis indicated that synergy score accurately identified the gene ontology-defined miRNA synergy (AUC = 0.9415, p<0.001). Only a very small portion of the random miRNA-miRNA combinations generated potent synergy, implying poor expectancy of widespread synergy. However, targeting more key genes made two miRNAs more likely to act synergistically. Compared to other miRNAs, miR-21 was a highly exceptional case due to frequent appearance in the top synergistic miRNA pairs. This result highlighted its essential role in coordinating or strengthening physiological and pathological functions of other miRNAs. The synergistic effect of miR-21 and miR-1 were functionally validated for their significant influences on myocardial apoptosis, cardiac hypertrophy and fibrosis. The novel approach established in this study enables easy and effective identification of condition-restricted potent miRNA synergy simply by concentrating the available protein interactomics and miRNA-target interaction data into a single parameter synergy score. Our results may be important for understanding synergistic gene regulation by miRNAs and may have significant implications for miRNA combination therapy of cardiovascular disease.
The role of defoliation and root rot pathogen infection in driving the mode of drought-related physiological decline in Scots pine (Pinus sylvestris L.).

Drought-related tree die-off episodes have been observed in all vegetated continents. Despite much research effort, however, the multiple interactions between carbon starvation, hydraulic failure and biotic agents in driving tree mortality under field conditions are still not well understood. We analysed the seasonal variability of non-structural carbohydrates (NSCs) in four organs (leaves, branches, trunk and roots), the vulnerability to embolism in roots and branches, native embolism (percentage loss of hydraulic conductivity (PLC)) in branches and the presence of root rot pathogens in defoliated and non-defoliated individuals in a declining Scots pine (Pinus sylvestris L.) population in the NE Iberian Peninsula in 2012, which included a particularly dry and warm summer. No differences were observed between defoliated and non-defoliated pines in hydraulic parameters, except for a higher vulnerability to embolism at pressures below -2 MPa in roots of defoliated pines. No differences were found between defoliation classes in branch PLC. Total NSC (TNSC, soluble sugars plus starch) values decreased during drought, particularly in leaves. Defoliation reduced TNSC levels across tree organs, especially just before (June) and during (August) drought. Root rot infection by the fungal pathogen Onnia P. Karst spp. was detected but it did not appear to be associated to tree defoliation. However, Onnia infection was associated with reduced leaf-specific hydraulic conductivity and sapwood depth, and thus contributed to hydraulic impairment, especially in defoliated pines. Infection was also associated with virtually depleted root starch reserves during and after drought in defoliated pines. Moreover, defoliated and infected trees tended to show lower basal area increment. Overall, our results show the intertwined nature of physiological mechanisms leading to drought-induced mortality and the inherent difficulty of isolating their contribution under field conditions.
The NADPH Oxidase Complexes in Botrytis cinerea: Evidence for a Close Association with the ER and the Tetraspanin Pls1

NADPH oxidases (Nox) are major enzymatic systems that generate reactive-oxygen species (ROS) in multicellular eukaryotes. In several fungi they have been shown to be involved in sexual differentiation and pathogenicity. However, in contrast to the well characterized mammalian systems, basic information on the composition, recruitment, and localization of fungal Nox complexes and on the molecular mechanisms of their cellular effects are still lacking. Here we give a detailed analysis of components of the Nox complexes in the gray mold fungus Botrytis cinerea. It had previously been shown that the two catalytic transmembrane subunits BcNoxA and B are important for development of sclerotia and for full virulence, with BcNoxA being involved in spreading of lesions and BcNoxB in penetration; BcNoxR functions as a regulator of both subunits. Here we present evidence (using for the first time a functional GFP fusion able to complement the ΔbcnoxA mutant) that BcNoxA localizes mainly to the ER and at the plasma membrane; BcNoxB shows a similar localization pattern, while the regulator BcNoxR is found in vesicles throughout the hyphae and at the hyphal tip. To identify possible interaction partners, which could be involved in the localization or recruitment of the Nox complexes, we functionally characterized the tetraspanin Pls1, a transmembrane protein, which had been suggested to be a NoxB-interacting partner in the saprophyte Podospora anserina. Knock-out experiments and GFP fusions substantiate a link between BcNoxB and BcPls1 because both deletion mutants have overlapping phenotypes (especially a defect in penetration), and the proteins show a similar localization pattern (ER). However, in contrast to the corresponding protein in P. anserina BcPls1 is important for female fertility, but not for ascospore germination.
Towards methods for systematic research on big data

Big Data is characterized by the five V's - of Volume, Velocity, Variety, Veracity and Value. Research on Big Data, that is, the practice of gaining insights from it, challenges the intellectual, process, and computational limits of an enterprise. Leveraging the correct and appropriate toolset requires careful consideration of a large software ecosystem. Powerful algorithms exist, but the exploratory and often ad-hoc nature of analytic demands and a distinct lack of established processes and methodologies make it difficult for Big Data teams to set expectations or even create valid project plans. The exponential growth of data generated exceeds the capacity of humans to process it, and compels us to develop automated computing methods that require significant and expensive computing power in order to scale effectively. In this paper, we characterize data-driven practice and research and explore how we might design effective methods for systematizing such practice and research [19, 22]. Brief case studies are presented in order to ground our conclusions and insights.
Onion-AE: Foundations of Nested Encryption

Abstract Nested symmetric encryption is a well-known technique for low-latency communication privacy. But just what problem does this technique aim to solve? In answer, we provide a provable-security treatment for onion authenticated-encryption (onion-AE). Extending the conventional notion for authenticated-encryption, we demand indistinguishability from random bits and time-of-exit authenticity verification. We show that the encryption technique presently used in Tor does not satisfy our definition of onion-AE security, but that a construction by Mathewson (2012), based on a strong, tweakable, wideblock PRP, does do the job. We go on to discuss three extensions of onion-AE, giving definitions to handle inbound flows, immediate detection of authenticity errors, and corrupt ORs.
The effect of feeding a diet naturally contaminated with deoxynivalenol on production traits and selected biochemical indicators of broiler chickens

The effect of feeding a diet naturally contaminated with deoxynivalenol (DON) (0-21 days: 1.50 mg·kg -1 ; 22-39 days: 1.54 mg·kg -1 ) was studied in 40 broiler chickens. Birds were divided into two groups fed a control diet and a diet contaminated with DON (n = 20 in each). Feed intake was measured daily and individual live weight weekly; daily weight gain and feed to gain ratio were calculated. Five animals from each group were euthanized on days 21 and 39 when blood (blood plasma and red blood cell haemolysates) and liver samples were collected. Concentration of triglyceride, uric acid and glucose and activities of ALT, AST and LDH were measured in blood plasma. Indicators of lipid peroxide and glutathione redox status, malondialdehyde and reduced glutathione concentration and glutathione-peroxidase activity were measured in blood plasma, red blood cell haemolysates and liver homogenates. The low dose of DON did not cause difference in the production traits, but caused significantly lower concentration of uric acid and glucose, and significantly higher concentration of triglyceride in blood plasma on day 21. Enzyme activities in blood plasma did not differ significantly between the treatment groups. Among the markers of lipid peroxide and glutathione redox status, malondialdehyde content was significantly higher in liver homogenate on day 21 in the group fed with DON contaminated diet, but reduced glutathione content and glutathione peroxidase activity did not differ significantly between the treatment groups. The results showed that diet contaminated even with a low content of deoxynivalenol caused alterations in selected biochemical indicators of blood and liver of broiler chicken.