Miracle-dz/UniFAR-FTUs huggingface dataset:
Bar-coding neurodegeneration: identifying subcellular effects of human neurodegenerative disease proteins using Drosophila leg neurons

ABSTRACT Genetic, biochemical and histological studies have identified a number of different proteins as key drivers of human neurodegenerative diseases. Although different proteins are typically involved in different diseases, there is also considerable overlap. Addressing disease protein dysfunction in an in vivo neuronal context is often time consuming and requires labor-intensive analysis of transgenic models. To facilitate the rapid, cellular analysis of disease protein dysfunction, we have developed a fruit fly (Drosophila melanogaster) adult leg neuron assay. We tested the robustness of 41 transgenic fluorescent reporters and identified a number that were readily detected in the legs and could report on different cellular events. To test these reporters, we expressed a number of human proteins involved in neurodegenerative disease, in both their mutated and wild-type versions, to address the effects on reporter expression and localization. We observed strikingly different effects of the different disease proteins upon the various reporters with, for example, Aβ1-42 being highly neurotoxic, tau, parkin and HTT128Q affecting mitochondrial distribution, integrity or both, and Aβ1-42, tau, HTT128Q and ATX182Q affecting the F-actin network. This study provides proof of concept for using the Drosophila adult leg for inexpensive and rapid analysis of cellular effects of neurodegenerative disease proteins in mature neurons. Summary: Toxic effects of neurodegenerative disease proteins on neuronal function and morphology can be addressed using an array of transgenic fluorescent reporters in the adult Drosophila leg.
Identification of Three New Genes Involved in Morphogenesis and Antibiotic Production in Streptomyces coelicolor

ABSTRACT We report the isolation and partial characterization of three new mutants of Streptomyces coelicolor that are defective in morphogenesis and antibiotic production. The genes identified by the mutations were located and cloned by using a combination of Tn5 in vitro mutagenesis, cotransformation, and genetic complementation. Mutant SE69 produces lower amounts of antibiotics than the wild type produces, produces spores only after prolonged incubation on rich media, and identifies a gene whose predicted protein product is similar to the GntR family of transcriptional regulators; also, production of aerial mycelia on both rich and poor media is significantly delayed in this mutant. Mutant SE293 is defective in morphogenesis, overproduces antibiotics on rich media, fails to grow on minimal media, and identifies a gene whose predicted protein product is similar to the TetR family of transcriptional regulators. Preliminary evidence suggests that the SE293 gene product may control a molybdopterin binding protein located immediately adjacent to it. Mutant SJ175 sporulates sooner and more abundantly than the wild type and overproduces antibiotics on rich media, and it identifies a gene whose predicted protein product contains regions of predominantly hydrophobic residues similar to those of integral membrane proteins.
Shadow Elimination and Interpolation for Computer Vision and Graphics

報告番号: 甲17996 ; 学位授与年月日: 2003-03-28 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第5454号 ; 研究科・専攻: 工学系研究科電子情報工学専攻
Assessing the overhead and scalability of system monitors for large data centers

Current data centers are shifting towards cloud-based architectures as a means to obtain a scalable, cost-effective, robust service platform. In spite of this, the underlying management infrastructure has grown in terms of hardware resources and software complexity, making automated resource monitoring a necessity. There are several infrastructure monitoring tools designed to scale to a very high number of physical nodes. However, these tools either collect performance measure at a low frequency (missing the chance to capture the dynamics of a short-term management task) or are simply not equipped with instrumentation specific to cloud computing and virtualization. In this scenario, monitoring the correctness and efficiency of live migrations can become a nightmare. This situation will only worsen in the future, with the increased service demand due to spreading of the user base. In this paper, we assess the scalability of a prototype monitoring subsystem for different user scenarios. We also identify all the major bottlenecks and give insight on how to remove them.
Controlled partial embedding of carbon nanotubes within flexible transparent layers

Applications of carbon nanotubes (CNTs) like field emission displays, super-capacitors, and cell growth scaffolds can benefit from controllable embedding of the CNTs in a material such that the CNTs are anchored and protrude a desired length. We demonstrate a simple method for anchoring densely packed, vertically aligned arrays of CNTs into silicone layers using spin-coating, CNT insertion, curing, and growth substrate removal. CNT arrays of 51 and 120 µm in height are anchored into silicone layers of thickness 26 and 36 µm, respectively. Scanning electron microscopy (SEM) and optical microscopy are used to characterize the sample morphology, a 5.5 m s−1 impinging water jet is used to apply shear stress, and a tensile test shows that the silicone layer detaches from the substrate before the CNTs are ripped from the layer. The CNTs are thus well anchored in the silicone layers. The spin-coating process gives control over layer thickness, and the method should have general applicability to various nanostructures and anchoring materials.
Multivariate Prediction of Subcutaneous Glucose Concentration in Type 1 Diabetes Patients Based on Support Vector Regression

Data-driven techniques have recently drawn significant interest in the predictive modeling of subcutaneous (s.c.) glucose concentration in type 1 diabetes. In this study, the s.c. glucose prediction is treated as a multivariate regression problem, which is addressed using support vector regression (SVR). The proposed method is based on variables concerning: 1) the s.c. glucose profile; 2) the plasma insulin concentration; 3) the appearance of meal-derived glucose in the systemic circulation; and 4) the energy expenditure during physical activities. Six cases corresponding to different combinations of the aforementioned variables are used to investigate the influence of the input on the daily glucose prediction. The proposed method is evaluated using a dataset of 27 patients in free-living conditions. Tenfold cross validation is applied to each dataset individually to both optimize and test the SVR model. In the case, where all the input variables are considered, the average prediction errors are 5.21, 6.03, 7.14, and 7.62 mg/dl for 15-, 30-, 60-, and 120-min prediction horizons, respectively. The results clearly indicate that the availability of multivariable data and their effective combination can significantly increase the accuracy of both short-term and long-term predictions.
Measurements of NO2 and HNO3 during a stratospheric warming at 54°N in February 1979

The altitude distribution of HNO3 was measured during a stratospheric warming on a balloon flight from Cold Lake, Alberta, on 11 February, 1979. The HNO3 profile measured appears to be layered and have a greater thickness than that of a typical summer profile. Ground based observations of the zenith sky were made from 31 January to 12 February and yield the total abundance of stratospheric NO2. Stratospheric NO2 column amounts deduced from these ground based measurements and another set taken during February, 1977 exhibit a diurnal variation under dynamical conditions of both stable vortex flow (1977) and stratospheric warming (1979). Using these measurements, the NO measurements of Knight et al. (1982), and model calculations we find that above 20 km there does not appear to be a pronounced seasonal change in total odd nitrogen. However, below 24 km the conversion of NOw = NO + NO2 + 2 × N2O5 + HO2NO2 to HNO3 occurs more rapidly than calculated using current homogeneous chemistry.
Study of Multivariate Data Clustering Based on K-Means and Independent Component Analysis

For last two decades, clustering is well-recognized area in the research field of data mining. Data clustering plays the major research at pattern recognition, Signal processing, bioinformatics and Artificial Intelligence. Clustering process is an unsupervised learning techniques where it generates a group of object based on their similarity in such a way that the objects belonging to other groups are similar and those belonging to other are dissimilar. This paper analysis the three different data types clustering techniques like K-Means, Principal components analysis (PCA) and Independent component analysis (ICA) in real and simulated data. The recent developments by considering a rather unexpected application of the theory of Independent component analysis (ICA) found in data clustering, outlier detection and multivariate data visualization. Accurate identification of data clustering plays an important role in statistical analysis. In this paper we explore the connection among these three techniques to identify multivariate data clustering and develop a new method k-means on PCA or ICA then the result shows that ICA based clustering performs well than others.
Object cosegmentation

Cosegmentation is typically defined as the task of jointly segmenting “something similar” in a given set of images. Existing methods are too generic and so far have not demonstrated competitive results for any specific task. In this paper we overcome this limitation by adding two new aspects to cosegmentation: (1) the “something” has to be an object, and (2) the “similarity” measure is learned. In this way, we are able to achieve excellent results on the recently introduced iCoseg dataset, which contains small sets of images of either the same object instance or similar objects of the same class. The challenge of this dataset lies in the extreme changes in viewpoint, lighting, and object deformations within each set. We are able to considerably outperform several competitors. To achieve this performance, we borrow recent ideas from object recognition: the use of powerful features extracted from a pool of candidate object-like segmentations. We believe that our work will be beneficial to several application areas, such as image retrieval.
Shear wave splitting along a nascent plate boundary: the North Anatolian Fault Zone

SUMMARY The North Anatolian Fault Zone (NAFZ) is a transform structure that constitutes the boundary between the Anatolian Plate to the south and the Eurasia Plate to the north. We analysed the properties of the upper-mantle strain field and mantle anisotropy in the vicinity of NAFZ via splitting of SKS and SKKS phases. We used data from the North Anatolian Fault (NAF) passive seismic experiment. This is the first study that analyses the upper-mantle anisotropy in this region and our results indicate that the observed upper-mantle strain field is uniform underneath the array with consistent NE–SW polarization directions for fast split waves. The measured lag times between the arrivals of the fast and slow split waves varies from 0.5 to 1.6 s for the study area. Smaller lag times are obtained consistently in the eastern part of the array. However, we do not observe any significant variation in either the polarization directions or the delay times across the plate boundary (NAFZ). The uniformity of the fast polarization directions throughout the study area and the strength of anisotropy favour an asthenospheric source for the anisotropy. The regional tectonic framework favours a SW direction of asthenospheric flow due to the forces acting on the upper-mantle exerted by the slab-roll-back taking place along the Aegean and the Cyprean Subduction Zones.
Twin Peaks: A Software Platform for Heterogeneous Computing on General-Purpose and Graphics Processors

Modern processors are evolving into hybrid, heterogeneous processors with both CPU and GPU cores used for generalpurpose computation. Several languages such as Brook, CUDA , and more recently OpenCL are being developed to fully harness the potential of these processors. These languages typically involve the control code running on the CPU and the performance-critical, data-parallel kernel code running on the GPUs. In this paper, we present Twin Peaks, a software platform for heterogeneous computing that executes code originally targeted for GPUs effi ciently on CPUs as well. This permits a more balanced execution between the CPU and GPU, and enables portability of code between these architectures and to CPU-only environments. We propose several techniques in the runtime system to efficiently utilize the caches and functional units present in CPUs. Using OpenCL as a canonical language for heterogeneous computing, and running several experiments on real hardware, we show that our techniques enable GPGPU-style code to execute efficiently on multi core CPUs with minimal runtime overhead. These results also show that for maximum performance, it is beneficial for applications to utilize both CPUs and GPUs as accelerator targets. Categories a nd Subject D escriptors: D.1. 3 [Programming Techniques] : Concurrent Programming G eneral Terms: Design , Experimentation, Performance. K eywords: GPGPU, Multicore , OpenCL, Programmability, Runtime.
The effects of a deep mantle endothermic phase change on the structure of thermal convection in silicate planets

Previous studies of the effects of silicate phase transitions on mantle convection have tended to use numerical models in which the phase transitions have the same depths as found in the Earth's mantle, or in which a single transition is placed at a depth equal to half the layer thickness. This study presents a systematic investigation designed to examine the effects of an endothermic phase transition near the core-mantle boundary of terrestrial type planets. The results indicate that a deep mantle endothermic phase change may trap the lower thermal boundary layer, allowing only one upwelling to penetrate the phase transition. In these situations the deep endothermic phase change excites a dipolar convection pattern. This mechanism may have a role in the degree one power observed in the distribution of the Earth's hotspots and the development of the Martian crustal dichotomy.
Inhibition of Mitochondrial Permeability Transition Pore Opening by Ischemic Preconditioning Is Probably Mediated by Reduction of Oxidative Stress Rather Than Mitochondrial Protein Phosphorylation

Inhibition of mitochondrial permeability transition pore (MPTP) opening at reperfusion is critical for cardioprotection by ischemic preconditioning (IP). Some studies have implicated mitochondrial protein phosphorylation in this effect. Here we confirm that mitochondria rapidly isolated from preischemic control and IP hearts show no significant difference in calcium-mediated MPTP opening, whereas IP inhibits MPTP opening in mitochondria isolated from IP hearts following 30 minutes of global normothermic ischemia or 3 minutes of reperfusion. Analysis of protein phosphorylation in density-gradient purified mitochondria was performed using both 2D and 1D electrophoresis, with detection of phosphoproteins using Pro-Q Diamond or phospho-amino-specific antibodies. Several phosphoproteins were detected, including voltage-dependent anion channels isoforms 1 and 2, but none showed significant IP-mediated changes either before ischemia or during ischemia and reperfusion, and neither Western blotting nor 2D fluorescence difference gel electrophoresis detected translocation of protein kinase C (&agr;, ϵ, or &dgr; isoforms), glycogen synthase kinase 3&bgr;, or Akt to the mitochondria following IP. In freeze-clamped hearts, changes in phosphorylation of GSK3&bgr;, Akt, and AMP-activated protein kinase were detected following ischemia and reperfusion but no IP-mediated changes correlated with MPTP inhibition or cardioprotection. However, measurement of mitochondrial protein carbonylation, a surrogate marker for oxidative stress, suggested that a reduction in mitochondrial oxidative stress at the end of ischemia and during reperfusion may account for IP-mediated inhibition of MPTP. The signaling pathways mediating this effect and maintaining it during reperfusion are discussed.
Diagnostic initialization generated extremely strong thermohaline sources and sinks in the South China Sea

Abstract : Ocean modeling is usually constrained by the lack of observed velocity data for the initial condition. Diagnostic initialization is widely used to generate velocity data as an initial condition for ocean modeling. Diagnostic initialization integrates the model from known temperature, salinity, and zero velocity fields and holds temperature and salinity unchanged. After a period of the diagnostic run, the velocity field is established, and the temperature, salinity, and velocity fields are treated as the initial conditions for numerical modeling. During the diagnostic initialization period, the heat and salt "source/sink" terms are generated at each time step. In this thesis, the Princeton Ocean Model was applied to the South China Sea. The study demonstrated extremely strong thermohaline sources and sinks generated by the diagnostic initialization. Such extremely strong and spatially nonuniform initial heating/cooling (salting/freshening) rates in the ocean model may cause drastic change in thermohaline and velocity fields initially (after the diagnostic run). There is a need to overcome such problems or find alternative methods as diagnostic initialization is extensively used. (54 figures, 6 refs.)
An automated syllabus digital library system for higher education in Ireland

Purpose – With the significant growth in electronic education materials such as syllabus documents and lecture notes, available on the internet and intranets, there is a need for robust central repositories of such materials to allow both educators and learners to conveniently share, search and access them. The purpose of this paper is to report on the work to develop a national repository for course syllabi in Ireland.Design/methodology/approach – The paper describes a prototype syllabus repository system for higher education in Ireland, which has been developed by utilising a number of information extraction and document classification techniques, including a new fully unsupervised document classification method that uses a web search engine for automatic collection of training set for the classification algorithm.Findings – Preliminary experimental results for evaluating the performance of the system and its various units, particularly the information extractor and the classifier, are presented and dis.
Physiological and proteomic approaches to evaluate the role of sterol binding in elicitin-induced resistance

Cryptogein is a proteinaceous elicitor secreted by Phytophthora cryptogea that can induce resistance to P. parasitica in tobacco plants. On the basis of previous computer modelling experiments, by site-directed mutagenesis a series of cryptogein variants was prepared with altered abilities to bind sterols, phospholipids or both. The sterol binding and phospholipid transfer activities corresponded well with the previously reported structural data. Induction of the synthesis of reactive oxygen species (ROS) in tobacco cells in suspension and proteomic analysis of intercellular fluid changes in tobacco leaves triggered by these mutant proteins were not proportional to their ability to bind or transfer sterols and phospholipids. However, changes in the intercellular proteome corresponded to transcription levels of defence genes and resistance to P. parasitica and structure-prediction of mutants did not reveal any significant changes in protein structure. These results suggest, contrary to previous proposals, that the sterol-binding ability of cryptogein and its mutants, and the associated conformational change in the ω-loop, might not be principal factors in either ROS production or resistance induction. Nevertheless, the results support the importance of the ω-loop for the interaction of the protein with the high affinity binding site on the plasma membrane.
Diffusion Tensor Imaging-Based Research on Human White Matter Anatomy

The aim of this study is to investigate the white matter by the diffusion tensor imaging and the Chinese visible human dataset and to provide the 3D anatomical data of the corticospinal tract for the neurosurgical planning by studying the probabilistic maps and the reproducibility of the corticospinal tract. Diffusion tensor images and high-resolution T1-weighted images of 15 healthy volunteers were acquired; the DTI data were processed using DtiStudio and FSL software. The FA and color FA maps were compared with the sectional images of the Chinese visible human dataset. The probability maps of the corticospinal tract were generated as a quantitative measure of reproducibility for each voxel of the stereotaxic space. The fibers displayed by the diffusion tensor imaging were well consistent with the sectional images of the Chinese visible human dataset and the existing anatomical knowledge. The three-dimensional architecture of the white matter fibers could be clearly visualized on the diffusion tensor tractography. The diffusion tensor tractography can establish the 3D probability maps of the corticospinal tract, in which the degree of intersubject reproducibility of the corticospinal tract is consistent with the previous architectonic report. DTI is a reliable method of studying the fiber connectivity in human brain, but it is difficult to identify the tiny fibers. The probability maps are useful for evaluating and identifying the corticospinal tract in the DTI, providing anatomical information for the preoperative planning and improving the accuracy of surgical risk assessments preoperatively.
Evaluating wind fields from a diagnostic model over complex terrain in the Phoenix region and implications to dispersion calculations for regional emergency response

This paper compares the wind field from a diagnostic model (CALMET) over complex terrain in the Phoenix region in the USA with observations that are gridded by a state‐of‐the‐art Four‐Dimensional Data Assimilation (FDDA) system. The wind difference between the CALMET and FDDA wind fields is larger at night than in the day. The magnitude of the wind difference can be smaller than 5% of the mean wind speed at low levels in areas with dense observational stations, while it can be larger than 80% in areas without observational stations or at high altitudes. The vector‐mean wind direction difference over the domain is 15° on the surface level and 25° between 10 and 1500 m. To evaluate the effects of the wind difference on dispersion calculations, dispersion of a hypothetical passive tracer released from surface point sources is simulated by the second‐order closure integrated puff (SCIPUFF) model driven by the CALMET and FDDA wind fields, respectively. Differences in the two simulated tracer concentration fields increase with time due to accumulation of effects of the wind differences both near the surface and at higher altitudes. Even for release in the area with the densest distribution of surface stations, the relative difference in the peak surface concentration from CALMET‐SCIPUFF and from FDDA‐SCIPUFF is less than 10% only within 0.5 h after the release in the afternoon, and increases to 70% at 1.5 h; this is because of large differences in wind above the surface. For release in the area with few stations, the difference can be larger than 100% or even larger after 1.5 h from the release. To improve dispersion simulations driven by the CALMET wind in the region, observations at upper‐air stations are needed and the current surface observation network needs to be reorganized or more stations are needed to account for the influence of terrain. Copyright © 2009 Royal Meteorological Society