Miracle-dz/UniFAR-FTUs huggingface dataset:
Hepatic Golgi fractions resolved into membrane and content subfractions

Golgi fractions isolated from rat liver homogenates have been resolved into membrane and content subfractions by treatment with 100 mM Na2CO3 pH 11.3. This procedure permitted extensive extraction of content proteins and lipoproteins, presumably because it caused an alteration of Golgi membranes that minimized the reformation of closed vesicles. The type and degree of contamination of the fractions was assessed by electron microscopy and biochemical assays. The membrane subfraction retained 15% of content proteins and lipids, and these could not be removed by various washing procedures. The content subfraction was contaminated by both membrane fragments and vesicles and accounted for 5 to 10% of the membrane enzyme activities of the original Golgi fraction. The lipid compositions of the subfractions was determined, and the phospholipids of both membrane and content were found to be uniformly labeled with [33P]phosphate administered in vivo.
A Survey of Data Mining Techniques on Medical Data for Finding Locally Frequent Diseases

In the last decade there has been increasing usage of data mining techniques on medical data for discovering useful trends or patterns that are used in diagnosis and decision making. Data mining techniques such as clustering, classification, regression, association rule mining, CART (Classification and Regression Tree) are widely used in healthcare domain. Data mining algorithms, when appropriately used, are capable of improving the quality of prediction, diagnosis and disease classification. The main focus of this paper is to analyze data mining techniques required for medical data mining especially to discover locally frequent diseases such as heart ailments, lung cancer, breast cancer and so on. We evaluate the data mining techniques for finding locally frequent patterns in terms of cost, performance, speed and accuracy. We also compare data mining techniques with conventional methods.
Reversible particle movements associated with unstacking and restacking of chloroplast membranes in vitro

Freeze-fracture and freeze-etch techniques have been employed to study the supramolecular structure of isolated spinach chloroplast membranes and to monitor structural changes associated with in vitro unstacking and restacking of these membranes. High-resolution particle size histograms prepared from the four fracture faces of normal chloroplast membranes reveal the presence of four distinct categories of intramembranous particles that are nonrandomly distributed between grana and stroma membranes. The large surface particles show a one to one relationship with the EF-face particles. Since the distribution of these particles between grana and stroma membranes coincides with the distribution of photosystem II (PS II) activity, it is argued that they could be structural equivalents of PS II complexes. An interpretative model depicting the structural relationship between all categories of particles is presented. Experimental unstacking of chloroplast membranes in low-salt medium for at least 45 min leads to a reorganization of the lamellae and to a concomitant intermixing of the different categories of membrane particles by means of translational movements in the plane of the membrane. In vitro restacking of such experimentally unstacked chloroplast membranes can be achieved by adding 2-20 mM MgCl2 or 100-200 mM NaCl to the membrane suspension. Membranes allowed to restack for at least 1 h at room temperature demonstrate a resegregation of the EF-face particles into the newly formed stacked membrane regions to yield a pattern and a size distribution nearly indistinguishable from the normally stacked controls. Restacking occurs in two steps: a rapid adhesion of adjoining stromal membrane surfaces with little particle movement, and a slower diffusion of additional large intramembranous particles into the stacked regions where they become trapped. Chlorophyll a:chlorophyll b ratios of membrane fraction obtained from normal, unstacked, and restacked membranes show that the particle movements are paralleled by movements of pigment molecules. The directed and reversible movements of membrane particles in isolated chloroplasts are compared with those reported for particles of plasma membranes.
Three-level LLC series resonant DC/DC converter

Paper presents a three-level soft switching LLC series resonant dc/dc converter. Zero-voltage switching (ZVS) is achieved for each main switch without any auxiliary circuit. Voltage stress of each main switch is half of input voltage. Zero-current-switching (ZCS) is achieved for rectifier diodes. Wide input/output range can be achieved under low frequency range because of two-stage resonance. Only one magnetic component is required in this converter. Efficiency is higher in high line input, so this converter is a preferable candidate for power products with the requirement of hold up time. For design convenience, relationship between dc gain and switching frequency, load resistance is deduced. Its open load characteristic and short load characteristic are exposed to provide theory basis for no load operation and over current protection. Design consideration of four dead times is presented to assure that voltage stress for main switches is within half of input voltage and ZVS for each main switch is achieved. Finally the principle of operation and the characteristics of the presented converter are verified on a 500V-700V input 54V/10A output experimental prototype, whose efficiency reaches 94.7% under rating condition.
Bilateral Field Advantage in Visual Enumeration

A number of recent studies have demonstrated superior visual processing when the information is distributed across the left and right visual fields than if the information is presented in a single hemifield (the bilateral field advantage). This effect is thought to reflect independent attentional resources in the two hemifields and the capacity of the neural responses to the left and right hemifields to process visual information in parallel. Here, we examined whether a bilateral field advantage can also be observed in a high-level visual task that requires the information from both hemifields to be combined. To this end, we used a visual enumeration task—a task that requires the assimilation of separate visual items into a single quantity—where the to-be-enumerated items were either presented in one hemifield or distributed between the two visual fields. We found that enumerating large number (>4 items), but not small number (<4 items), exhibited the bilateral field advantage: enumeration was more accurate when the visual items were split between the left and right hemifields than when they were all presented within the same hemifield. Control experiments further showed that this effect could not be attributed to a horizontal alignment advantage of the items in the visual field, or to a retinal stimulation difference between the unilateral and bilateral displays. These results suggest that a bilateral field advantage can arise when the visual task involves inter-hemispheric integration. This is in line with previous research and theory indicating that, when the visual task is attentionally demanding, parallel processing by the neural responses to the left and right hemifields can expand the capacity of visual information processing.
The 'terror of the night' and the Morrígain: shifting faces of the supernatural

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Lossless compression of hyperspectral imagery through 2D/3D hybrid prediction

Using the significant spectral correlation within the hyperspectral images, we present a lossless compression algorithm in this paper. By means of band ordering according to spectral correlation coefficient and 2D/3D hybrid prediction, which are based on local texture and neural networks, hyperspectral data are decorrelated. The prediction residuals are then entropy coded by context-based Golomb coding. Experimental results show that this method can remove the spatial and spectral redundancy efficiently and outperforms JPEG-ES and 3D-APA on average bit rate obviously.
Design and Implementation of Semantic and Content based Hybrid Recommender System for Java Programs

During the past few years the World Wide Web has emerged as the mainstream medium of communication and information dissemination. With the rapid growth of the WWW and the advent of eservices for online shopping, social networking, email and more; The Web personalization[10,11] and recommendation system has now become one of the most important tool for both Web-based organizations as well as for end users in order to extract the “right” and “interesting” information from the World Wide Web. Recommendation system (RS) is one of the most advanced approaches which are widely used for personalization of information on the web and information retrieval systems. Recommendation systems are now popular commercially as well as in Research community. Many major e-commerce Websites are already using recommendation systems to increase their customers by providing relevant suggestions to their customers and providing them better recommendation for purchasing of products. The recommendations could be based on various parameters, such as customer‟s behavior of purchasing, rating and commenting; user characteristics such as geographical location or other demographic information. In this paper we are proposing the design and implementation of a computer programs recommender system that recommends the user; Java programs; which are similar to program that a user is currently interested in. In order to achieve this, we have prepared a tag list, which is a list of keywords, packages and classes available in Java that have been used to match the program similarity with each other. With each program in database, a heading is associated which is displayed before user to choose one. Feature extraction is achieved by identifying tags available in program heading as well as in contents of a program. A threshold value (t) is also available which determines how similar a program should be in order to be recommended to the user. The proposed system can work in three different modes: Heading based recommendations, Content based recommendations and Mixed recommendations.
Outlier Rejection in Deformable Model Tracking

Deformable model tracking is a powerful methodology that allows us to track the evolution of high-dimensional parameter vectors from uncalibrated monocular video sequences. The core of the approach consists of using low-level vision algorithms, such as edge trackers or optical flow, to collect a large number of 2D displacements, or motion measurements, at selected model points and mapping them into 3D space with the model Jacobians. However, the low-level algorithms are prone to errors and outliers, which can skew the entire tracking procedure if left unchecked. There are several known techniques in the literature, such as RANSAC, that can find and reject outliers. Unfortunately, these approaches are not easily mapped into the deformable model tracking framework, where there is no closed-form algebraic mapping from samples to the underlying parameter space. In this paper we present two simple, yet effective ways to find the outliers. We validate and compare these approaches in an 11-parameter deformable face tracking application against ground truth data.
Assessments of Muscle Oxygenation and Cortical Activity Using Functional Near-infrared Spectroscopy in Healthy Adults During Hybrid Activation

Hybrid activation (HA), patterned electrical stimulation (ES) superimposed on attempted voluntary movement in close synchrony, can augment muscle force output. It has been proposed for limb function restoration and neuromodulation. Limited studies have been performed to investigate the influences of HA on muscle oxygenation and brain cortical activity. The present study investigates muscle oxygenation and cortical activity during isometric knee extension tasks with voluntary contraction (VOL) only, ES only, and with HA at three stimulation intensities, namely 10 mA (HA-I), 30 mA (HA-II), and 50 mA (HA-III). A frequency-domain near-infrared spectroscopy system was employed to assess the muscle oxygenation in the vastus lateralis as well as the cortical activity from the bilateral sensorimotor cortices (SMCs), premotor cortices (PMCs), and supplementary motor areas (SMAs). Our results show that the increased ES contribution during HA significantly increased O2 demand in working muscle, implying that the intervention of ES accelerates the muscle metabolism during muscle contraction. For cortical activation, ES only had a similar cortical activation pattern to that during VOL but with lower activation in SMCs, PMCs, and SMAs. Augmented sensorimotor activation was observed during the HA-II condition. The enhanced level of cortical activation during HA was not only affected by the ES contribution within HA but also related to the functional specificity of cortical areas. Our results suggest that HA can effectively enhance the muscle oxygen demand as well as the activation of cortical regions, and that the ES contribution within HA is a key factor.
3D simulations of secondary electron generation and transport in a diamond amplifier for photocathodes

The Relativistic Heavy Ion Collider (RHIC) contributes fundamental advances to nuclear physics by colliding a wide range of ions. A novel electron cooling section, which is a key component of the proposed luminosity upgrade for RHIC, requires the acceleration of high-charge electron bunches with low emittance and energy spread. A promising candidate for the electron source is the recently developed concept of a high quantum efficiency photoinjector with a diamond amplifier. We have started to implement algorithms, within the VORPAL particle-in-cell framework, for modeling of secondary electron and hole generation, and for charge transport in diamond. The algorithms include elastic and various inelastic scattering processes over a wide range of charge carrier energies. Initial results from the implemented capabilities will be presented and discussed.
Complexity Analysis of Checkpoint Scheduling with Variable Costs

The parallel computing platforms available today are increasingly larger and thus, more and more subject to failures. Consequently it is necessary to develop efficient strategies providing safe and reliable completion for HPC parallel applications. Checkpointing is one of the most popular and efficient technique for developing fault-tolerant applications on such context. However, checkpoint operations are costly in terms of time, computation, and network communication. This will certainly affect the global performance of the application. In this work, we propose a performance model that expresses formally the checkpoint scheduling problem. This model exhibits the tradeoff between the impact of the checkpoints operations and the lost computation due to failures. Based on this model, we study the computational complexity of the problem of scheduling checkpoints with variable costs for general failure distributions. More precisely, we provide a new computational complexity analysis that explicits in depth the relations between the probabilistic failure model, the checkpoint cost, and the computational model. In particular, we prove that the checkpoint scheduling problem is NP-hard even in the simple case of uniform failure distribution. We also present a dynamic programming scheme for determining the optimal checkpointing times in all the variants of the problem.
Generating links to background knowledge: a case study using narrative radiology reports

Automatically annotating texts with background information has recently received much attention. We conduct a case study in automatically generating links from narrative radiology reports to Wikipedia. Such links help users understand the medical terminology and thereby increase the value of the reports. Direct applications of existing automatic link generation systems trained on Wikipedia to our radiology data do not yield satisfactory results. Our analysis reveals that medical phrases are often syntactically regular but semantically complicated, e.g., containing multiple concepts or concepts with multiple modifiers. The latter property is the main reason for the failure of existing systems. Based on this observation, we propose an automatic link generation approach that takes into account these properties. We use a sequential labeling approach with syntactic features for anchor text identification in order to exploit syntactic regularities in medical terminology. We combine this with a sub-anchor based approach to target finding, which is aimed at coping with the complex semantic structure of medical phrases. Empirical results show that the proposed system effectively improves the performance over existing systems.
Genome-Wide Association Study of Copy Number Variants Suggests LTBP1 and FGD4 Are Important for Alcohol Drinking

Alcohol dependence (AD) is a complex disorder characterized by psychiatric and physiological dependence on alcohol. AD is reflected by regular alcohol drinking, which is highly inheritable. In this study, to identify susceptibility genes associated with alcohol drinking, we performed a genome-wide association study of copy number variants (CNVs) in 2,286 Caucasian subjects with Affymetrix SNP6.0 genotyping array. We replicated our findings in 1,627 Chinese subjects with the same genotyping array. We identified two CNVs, CNV207 (combined p-value 1.91E-03) and CNV1836 (combined p-value 3.05E-03) that were associated with alcohol drinking. CNV207 and CNV1836 are located at the downstream of genes LTBP1 (870 kb) and FGD4 (400 kb), respectively. LTBP1, by interacting TGFB1, may down-regulate enzymes directly participating in alcohol metabolism. FGD4 plays a role in clustering and trafficking GABAA receptor and subsequently influence alcohol drinking through activating CDC42. Our results provide suggestive evidence that the newly identified CNV regions and relevant genes may contribute to the genetic mechanism of alcohol dependence.
Bundling and Unbundling Tasks in an ERP Acquisition Transaction: An Analysis of Asset Acquisition Incentives

The market for the corporate acquisition of Enterprise Resource Planning (ERP) systems was estimated at $45.5 billion in 2011. Failure of these transactions is a continuing issue for both business and researchers. As the system acquisitions and transactions that govern them grow increasingly complex, a better understanding of the transactions and how to govern them is imperative. This study begins the examination of such transactions through the lens of Incentive-System Theory, an extension of Transaction Cost Economics Theory. A case study was conducted at a large (several hundred outlets) retailer/distributor in the US currently engaged in the acquisition of an ERP through a major ERP vendor. The initial findings suggest Incentive-System Theory is a viable lens and one that may suggest improvements in the way such transactions are structured. Limitations and paths for future research to extend the theory and its application are discussed.
Downlink coverage probability in MIMO HetNets with flexible cell selection

In this paper, we study the coverage probability of a K-tier multiple-input multiple-output heterogeneous cellular network (MIMO HetNet) assuming (i) zero-forcing precoding at all the base stations (BSs), (ii) Rayleigh fading, (iii) independent Poisson Point Process (PPP) model for the locations of BSs of each tier, and (iv) general cell selection rule that maximizes average received signal-to-interference-plus-noise ratio (SINR) at the users. Our analysis highlights key differences between MIMO HetNets and the more familiar single antenna HetNets in terms of cell selection. While it is challenging to derive exact cell selection rule to maximize average downlink SINR in MIMO HetNets, we show that adding an appropriately chosen per-tier selection bias yields a close approximation. The bias value for each tier is given in closed form. One interpretation of this result is that MIMO HetNets may balance load more naturally across different tiers in certain special cases compared to single antenna HetNets where an artificial selection bias is often needed for load balancing.
Comprehensive pathogen detection associated with four recurrent episodes of Kawasaki disease in a patient during a single year using next-generation sequencing

Introduction: Kawasaki disease (KD) is the most common multisystem vasculitis in childhood. Pathogens can be associated with the onset of KD. However, a lack of consistency prevails among reports about this disease. Case presentation: For this case of a 1-year-old boy with four recurrent episodes of KD within a year, we analysed profiles of pathogen reads in his serum and pharynx specimens using next-generation sequencing. Comparative analysis of the identified bacterial reads from serum samples found significant correlation of bacteria such as Streptococcus and Haemophilus spp. with the first and fourth episodes (R2 = 0.9506) before treatment. In the first convalescent phase, the number of Streptococcus spp. was reduced remarkably (P < 0.0001). From sequencing of the pharynx specimen from the fourth episode, a similar correlation was found with serum from the fourth episode (R2 = 0.6633). Conclusion: In this case, Streptococcus spp. may have been associated with onset of KD. Further studies must be undertaken to evaluate the putative association of micro-organism infection with KD pathogenesis.
Mutations in the MPV17 gene are responsible for rapidly progressive liver failure in infancy

MPV17 is a mitochondrial inner membrane protein of unknown function recently recognized as responsible for a mitochondrial DNA depletion syndrome. The aim of this study is to delineate the specific clinical, pathological, biochemical, and molecular features associated with mitochondrial DNA depletion due to MPV17 gene mutations. We report 4 cases from 3 ethnically diverse families with MPV17 mutations. Importantly, 2 of these cases presented with isolated liver failure during infancy without notable neurologic dysfunction. Conclusion: We therefore propose that mutations in the MPV17 gene be considered in the course of evaluating the molecular etiology for isolated, rapidly progressive infantile hepatic failure. (HEPATOLOGY 2007.)