Miracle-dz/UniFAR-FTUs huggingface dataset:
The TOR Pathway Modulates the Structure of Cell Walls in Arabidopsis[W]

The target of rapamycin (TOR) pathway, which is known to regulate cell growth in eukaryotes, is shown to affect cell wall structure in plants. ROL5 (REPRESSOR of LRX1) is identified as a possible mitochondrial component of the TOR pathway. Plant cell growth is limited by the extension of cell walls, which requires both the synthesis and rearrangement of cell wall components in a controlled fashion. The target of rapamycin (TOR) pathway is a major regulator of cell growth in eukaryotes, and inhibition of this pathway by rapamycin reduces cell growth. Here, we show that in plants, the TOR pathway affects cell wall structures. LRR-extensin1 (LRX1) of Arabidopsis thaliana is an extracellular protein involved in cell wall formation in root hairs, and lrx1 mutants develop aberrant root hairs. rol5 (for repressor of lrx1) was identified as a suppressor of lrx1. The functionally similar ROL5 homolog in yeast, Ncs6p (needs Cla4 to survive 6), was previously found to affect TOR signaling. Inhibition of TOR signaling by rapamycin led to suppression of the lrx1 mutant phenotype and caused specific changes to galactan/rhamnogalacturonan-I and arabinogalactan protein components of cell walls that were similar to those observed in the rol5 mutant. The ROL5 protein accumulates in mitochondria, a target of the TOR pathway and major source of reactive oxygen species (ROS), and rol5 mutants show an altered response to ROS. This suggests that ROL5 might function as a mitochondrial component of the TOR pathway that influences the plant's response to ROS.
From Byzantine Consensus to BFT State Machine Replication: A Latency-Optimal Transformation

We present a new algorithm for state machine replication that is built around a leader-driven consensus primitive. This algorithm requires only two additional communication steps between replicas and clients if the consensus leader is correct and the system is synchronous, being thus the first latency-optimal transformation from Byzantine consensus to BFT state machine replication. We also discuss how to make simple modifications to leader-driven consensus algorithms in order to make them compatible with our transformation.
Anxiety and the management of asthma in an adult outpatient population

Background: Review of the literature suggests that anxiety is more common among patients with asthma than among the general population, yet it does not appear to be given the attention it deserves as part of the overall management of asthma. The aim of this study was to investigate the relationship between anxiety and asthma management, in terms of Global Initiative for Asthma steps, lung function and medication. Methods: A total of 201 consecutive patients with respiratory physician-diagnosed asthma were recruited from an adult outpatient asthma clinic. Participants underwent a sociodemographic review, and a medical interview which included a detailed drug history. Forced expiratory volume in 1 second (FEV1) and peak expiratory flow (PEF) values were recorded using a Micro Medical® portable spirometer. The level of anxiety was assessed using the Beck Anxiety Inventory (BAI). Results: A total of 51.5% of participants registered clinically significant levels of anxiety. Of these only 21% had already been diagnosed and were receiving treatment. Females reported significantly higher BAI scores than males (p < 0.01). More females (66.3%) registered clinically significant levels of anxiety as compared with males (33.7%) (p < 0.05). There was a positive correlation between the BAI score and the prescribed dose of inhaled glucocorticoids (r s = 0.150, p < 0.05) and between anxiety and GINA treatment step (r s = 0.139, p < 0.05). There was also a positive correlation between anxiety and the number of medicines taken by patients (r s = 0.259, p < 0.001). Conclusions: Physicians treating patients with asthma should be sensitised to the association between asthma and anxiety, and should also consider assessing patients for the possibility of anxiety disorders as part of asthma management plans.
Characterisation of nickel germanide formed on amorphous and crystalline germanium

Nickel germanide formed on amorphous and crystalline germanium is investigated for material and electrical properties. The crystal quality of films formed is poorer for the germanides formed on amorphous germanium with a slight increase in sheet resistance. The grains of NiGe formed on amorphous germanium show a growth that is hexagonal like, extending into the substrate further than germanides grains formed on crystalline germanium. The NiGe formed on crystalline germanium has a much more uniform thickness and uniform grain size and shape. Hollow cone illumination shows that some recrystallisation of the amorphised region of germanium does occur.
Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique

Partial shading is an unavoidable condition which significantly reduces the efficiency and stability of a photovoltaic (PV) system. When partial shading occurs the system has multiple-peak output power characteristics. In order to track the global maximum power point (GMPP) within an appropriate period a reliable technique is required. Conventional techniques such as hill climbing and perturbation and observation (P&O) are inadequate in tracking the GMPP subject to this condition resulting in a dramatic reduction in the efficiency of the PV system. Recent artificial intelligence methods have been proposed, however they have a higher computational cost, slower processing time and increased oscillations which results in further instability at the output of the PV system. This paper proposes a fast and efficient technique based on Radial Movement Optimization (RMO) for detecting the GMPP under partial shading conditions. The paper begins with a brief description of the behavior of PV systems under partial shading conditions followed by the introduction of the new RMO-based technique for GMPP tracking. Finally, results are presented to demonstration the performance of the proposed technique under different partial shading conditions. The results are compared with those of the PSO method, one of the most widely used methods in the literature. Four factors, namely convergence speed, efficiency (power loss reduction), stability (oscillation reduction) and computational cost, are considered in the comparison with the PSO technique.
Design and Implementation of Optical True Time Delay in Optically Controlled Phased Array Antennas

The applications and the advantages of the optical electronic techniques in wideband and wide-angle phased array radar are introduced. Based on the physical model of optically controlled phased array, this paper analyses the working principle of optically controlled phased array antennas (OCPAA) in detail. Then a design example is given. According to the different pulse compression results of a linear phased array with 32 antenna elements, the optimization of OTTD number can be chosen. A design of 4-bit OTTD based on binary delay fiber lines and optical switches is given. The main performances of OTTD which affect the array antennas system are discussed
Early detection of pulmonary hypertension in primary myelofibrosis: The role of echocardiography, cardiopulmonary exercise testing, and biomarkers

of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2016 [Epub ahead of print]. [5] Ostronoff F, Othus M, Lazenby M, et al. Prognostic significance of NPM1 mutations in the absence of FLT3-internal tandem duplication in older patients with acute myeloid leukemia: a SWOG and UK National Cancer Research Institute/Medical Research Council report. J Clin Oncol. 2015;33:1157–1164. [6] Guolo F, Minetto P, Clavio M, et al. High feasibility and antileukemic efficacy of fludarabine, cytarabine, and idarubicin (FLAI) induction followed by risk-oriented consolidation: a critical review of a 10-year, single-center experience in younger, non M3 AML patients. Am J Hematol. 2016;91:755–762.
“Sorry You Had to Go Through That”

Social suffering is distress engendered by cultural, social, and political forces. Responses to stories of such suffering serve as rejoinders in an identity negotiation process and can foster either healing or compounded distress—for both individuals and communities alike. Because there is no published study (to our knowledge) that focuses on the language individuals use in responding to stories of social suffering, the present study aimed to develop a theoretically grounded and empirically derived taxonomy of these responses. In order to develop and validate such a taxonomy, we collected a total of 172 audio-recorded responses to two true stories of race-based social suffering from two samples of undergraduate students at a large university in the greater Los Angeles area. The resulting coding scheme is presented here along with evidence of its reliability and validity.
Algorithm of Scene Segmentation Based on SVM for Scenery Documentary

Shot is a basic unit of content-based video retrieval and indexing. Relevant shots are typically grouped into a high-level unit called a scene. Browsing and retrieval in these scenes enables users to locate their desired video segments quickly and efficiently. This paper introduces a novel algorithm for clustering relevant shots into a scene using the semantic concept vectors defined by us and formed by N binary classifiers based on support vector machine (SVM). At first, the video clips are segmented into the shot. The shot key frames are extracted and the color and texture features of the shot key frames are computed. Then the N trained binary classifiers are used to classify the shot key frames into different semantic classes by means of their color and texture features. So the semantic concept vectors of the shot key frames can formed. The semantic concept vectors are used to cluster the shots into the scenes in our algorithm. Experimental results have indicated that the recall and precision of our algorithm is higher than the algorithm of SIM and ToC.
DNA-GA: A new approach of network performance analysis

In this paper, we propose a new approach of network performance analysis, which is based on our previous works on the deterministic network analysis using the Gaussian approximation (DNA-GA). First, we extend our previous works to a signal-to-interference ratio (SIR) analysis, which makes our DNA-GA analysis a formal microscopic analysis tool. Second, we show two approaches for upgrading the DNA-GA analysis to a macroscopic analysis tool. Finally, we perform a comparison between the proposed DNA-GA analysis and the existing macroscopic analysis based on stochastic geometry. Our results show that the DNA-GA analysis possesses a few special features: (i) shadow fading is naturally considered in the DNA-GA analysis; (ii) the DNA-GA analysis can handle non-uniform user distributions and any type of multi-path fading; (iii) the shape and/or the size of cell coverage areas in the DNA-GA analysis can be made arbitrary for the treatment of hotspot network scenarios. Thus, DNA-GA analysis is very useful for the network performance analysis of the 5th generation (5G) systems with general cell deployment and user distribution, both on a microscopic level and on a macroscopic level.
Pier Luigi Mazzeo

The specific problem we address in this chapter is object tracking over wide-areas such as an airport, the downtown of a large city or any large public area. Surveillance over these areas consists of the search for suspicious behavior such as persons loitering, unauthorized access, or persons attempting to enter a restricted zone. Until now, these surveillance tasks have been executed by human being who continually observe computer monitors to detect unauthorized activity over many cameras.It is known that the attention level drastically sinks after few hours. It is highly probable that suspicious activity would be unregistered by a human operator. A computer vision system, can take the place of the operator and monitor both immediate unauthorized behavior and long-term suspicious behavior. The "intelligent" system would, then, alert a responsible person for a deeper investigation. In most cases, it is not possible for a single camera to observe the complete area of interest because sensor resolution is finite and structures in the scene limit the visible areas. In the realistic application, surveillance systems which cover large areas are composed by multiple cameras with non overlapping Field of Views (FOVs). Multiple camera tracking is important to establish correspondence among detected objects across different cameras. Given a set of tracks in each camera we want to find which of these tracks belong to the same object in the real world. Note that tracking across multiple cameras is a challenging task because the observations are often widely separated in time and space, especially when viewed from non overlapped FOVs. Simple prediction schemes cannot be used to estimate the object position. It could be observed that object’s appearance in one camera view might be very different from its appearance in another camera view due to the difference in illumination, pose and camera properties. It is preferable that any multi-view tracking approach does not require camera calibration or complete site modelling. In fact, the benefit of calibrated cameras or site models is unavailable in most situations. Maintaining calibration between a large sensors network is a discouraging task, it is very onerous recalibrate any sensor when it (sensor) slight changes its position. This chapter presents an algorithm that deals with all described constraints and tracks objects across multiple un-calibrated cameras with non-overlapping FOVs. We investigate different techniques to evaluate intra-camera and inter-camera tracking algorithm based on object appearances. Object appearance can be modelled by its color or brightness, and it is a function of the scene illumination, object geometry, object surface material properties and camera Object Tracking in Multiple Cameras with Disjoint Views 11
The liver‐specific microRNA‐122*, the complementary strand of microRNA‐122, acts as a tumor suppressor by modulating the p53/mouse double minute 2 homolog circuitry

The tumor suppressor p53 is a central regulator of signaling pathways that controls the cell cycle and maintains the integrity of the human genome. p53 level is regulated by mouse double minute 2 homolog (Mdm2), which marks p53 for proteasomal degradation. The p53‐Mdm2 circuitry is subjected to complex regulation by a variety of mechanisms, including microRNAs (miRNAs). We found a novel effector of this regulatory circuit, namely, miR‐122*, the passenger strand of the abundantly expressed liver‐specific miR‐122. Here, we demonstrate that miR‐122* levels are reduced in human hepatocellular carcinoma (HCC). We found that miR‐122* targets Mdm2, thus participating as an important player in the p53‐Mdm2 circuitry. Moreover, we observed significant negative correlation between levels of miR‐122* and Mdm2 in a large set of human HCC samples. In vivo tumorigenicity assays demonstrate that miR‐122* is capable of inhibiting tumor growth, emphasizing the tumor‐suppressor characteristics of this miRNA. Furthermore, we show that blocking miR‐122 in murine livers with an antagomiR‐122 (miRNA inhibitor) results in miR‐122* accumulation, leading to Mdm2 repression followed by elevated p53 protein levels. Conclusion: miR‐122*, the passenger strand of miR‐122, regulates the activity of p53 by targeting Mdm2. Importantly, similarly to miR‐122, miR‐122* is significantly down‐regulated in human HCC. We therefore propose that miR‐122* is an important contributor to the tumor suppression activity previously attributed solely to miR‐122. (Hepatology 2016;64:1623‐1636)
Multiclass SVMs for Olfactory Classi cation CS 229 Final Project Report

The study of olfactory classi cation has many attractions, philosophical and theoretical as well as practical and functional. As part of the study of human cognition, it is widely recognized that the olfactory sense is a fundamental component of the human perceptual system. The human brain is believed to have evolved around the olfactory sense, and consequently the algorithms evolved for olfaction form the foundations of the algorithms used by the other senses. Input from all sensory modalities converges in the entorhinal cortex, indicating a degree of common processing function across the senses [14]. Olfaction is also an important and valuable perceptual mechanism for making distinctions about objects in and states of the physical world. The development of the so-called electronic nose over the past thirty years has led to a wide variety of applications, from quality analysis in the food and pharmaceutical industries to explosive and biological agent screening in security and defense applications. More potential applications present themselves, dependent on advances in sensor technology and signal processing algorithms, among them medical diagnosis, environmental quality monitoring, autonomous bomb disposal robot navigation, and smart re alarm and industrial monitoring systems, among others. This research project concentrates on the problem of classi cation of an unknown odorant into one of a set of previously observed classes, the problem in general of multiclass classi cation in a supervised learning framework. In the olfactory sensing context there are several components required of a sucessful classi cation algorithm: preprocessing, feature extraction, and classi cation. Previous research has applied various statistical learning techniques to each of these sub-problems. For preprocessing, techniques include feature normalization and baseline subtraction; for feature extration, methods include principal component analysis, linear discriminant analysis, and Sammon and Kohonen maps; and for classi cation, techinques include Bayesian classi ers, K-nearest neighbors, arti cial neural networks, radial basis functions and, recently, support vector machines. The paper proceeds in the standard fashion. In Section 2, we describe the problem of olfactory sensing in general and describe the distinguishing characteristics of the particular problem considered in this research paper. In Section 3, we identify the major trends in previous and current research into this problem. In Section 4, we describe the approach taken in this paper and locate our techniques within the broader scope of related research. In Section 5 we describe the results obtained , and nally in Section 6 we discuss the results and outline directions for further research.
Effects of Endotoxin and Psychological Stress on Redox Physiology, Immunity and Feather Corticosterone in Greenfinches

Assessment of costs accompanying activation of immune system and related neuroendocrine pathways is essential for understanding the selective forces operating on these systems. Here we attempted to detect such costs in terms of disruption to redox balance and interference between different immune system components in captive wild-caught greenfinches (Carduelis chloris). Study birds were subjected to an endotoxin-induced inflammatory challenge and temporary exposure to a psychological stressor (an image of a predator) in a 2*2 factorial experiment. Injection of bacterial endotoxin resulted in up-regulation of two markers of antioxidant protection – erythrocyte glutathione, and plasma oxygen radical absorbance (OXY). These findings suggest that inflammatory responses alter redox homeostasis. However, no effect on markers of oxidative damage to proteins or DNA in erythrocytes could be detected. We found no evidence that the endotoxin injection interfered with antibody production against Brucella abortus antigen or the intensity of chronic coccidiosis. The hypothesis of within-immune system trade-offs as a cost of immunity was thus not supported in our model system. We showed for the first time that administration of endotoxin can reduce the level of corticosterone deposited into feathers. This finding suggests a down-regulation of the corticosterone secretion cascade due to an endotoxin-induced immune response, a phenomenon that has not been reported previously. Exposure to the predator image did not affect any of the measured physiological parameters.
Perplexities in Discrimination of Attention Deficit Hyperactivity Disorder (ADHD): Specific Behaviors that may hold some Answers

Perplexities in Discrimination of Attention Deficit Hyperactivity Disorder (ADHD): Specific Behaviors That May Hold Some Answers. (May 2009) Judith R. Harrison, B.S., Lamar University; M.A., Stephen F. Austin State University Chair of Advisory Committee: Dr. Kimberly J. Vannest Attention deficit hyperactivity disorder (ADHD) is a source of diagnostic and intervention confusion and uncertainty for practitioners and parents. Questions creating some of the confusion were answered in a series of three studies. The sample was parent and teacher behavioral ratings for 389 children and 502 adolescents with ADHD and 3131 children and 3161 adolescents without ADHD in public and private schools and mental health clinics in forty states. In the first study, data was derived from participant T-scores on the Behavior Assessment System for Children (2 ed.) to evaluate the construct validity using first and second order factor analyses. Sufficient construct validity was established.
Appraise: an Open-Source Toolkit for Manual Evaluation of MT Output

Appraise: an Open-Source Toolkit for Manual Evaluation of MT Output We describe Appraise, an open-source toolkit supporting manual evaluation of machine translation output. The system allows to collect human judgments on translation output, implementing annotation tasks such as 1) quality checking, 2) translation ranking, 3) error classification, and 4) manual post-editing. It features an extensible, XML-based format for import/export and can easily be adapted to new annotation tasks. The current version of Appraise also includes automatic computation of inter-annotator agreements allowing quick access to evaluation results. Appraise is actively developed and used in several MT projects.
Disintegration Kinetics of Microbial Cells

Results of the disintegration of yeast Saccharomyces cerevisiae in the bead mill with a multi disk impeller are presented. The degree of disintegration was specified on the basis of absorbency measurements at the wavelength 260 nm. The process was investigated by two integrated methods. The experimental values of maximum absorbency Am2 appeared to be smaller than theoretical ones Am1, which resulted from searching for the highest values of correlation coefficient between variables t and ln[Am1 / (Am1 – A)]. A significant increase of the process rate constant was observed when the slurry concen‐ tration increased in the range from 0.05 to 0.20 g d.m. /cm3. This phenomenon was explained by an additional mechanism of cell destruction, which was induced by fragments of ground walls. The rate constant changed during the process due to a change of inner process conditions, and not directly as a result of a changing number of microbial cells. Modeling of the process in which the first-order differential equation is used to describe the kinetics is correct, with the process rate constant being a function of parameters that describe inner conditions changing during the process.