Miracle-dz/UniFAR-FTUs huggingface dataset:
Phospholipid Distribution and Fatty Acid Composition in Different Brain Regions During Chick Embryo Development

Abstract: The phospholipid profile of different chick embryo brain regions was studied from 11 to 21 days of development, revealing interesting changes in content and distribution. Total phospholipid phosphorus (P), in micrograms of P per microgram of DNA, increases significantly during development of cerebral hemispheres (CHs), optic lobes (OLs), and brainstem (BS). Compared with CH and OL, the BS shows at all stages a significantly higher concentration of phospholipid P, which in contrast decreases in the cerebellum (CB) during development. Moreover, the data show interesting differences between the right and the left portion of the brain. The distribution of phospholipid P and the fatty acid composition of phospholipids were asymmetric between left and right OL and CH, as were the concentrations of DNA and cholesterol, demonstrating lateralized neurochemical development in these structures, i.e., left OL, right OL, left CH, and right CH. The data are discussed also in relation to the potential importance of neurochemical lateralization for determining lateralized embryonic and postnatal behavior of this species.
A new stochastic estimator for tremor frequency tracking

An important parameter in analysis of physiological tremor is the diagnosis and study of neurological disorders. The instantaneous tremor frequency (ITF) is an important parameter in tremor analysis. This paper proposes a novel stochastic filter, the multiple extended Kalman filter (M-EKF), for tracking of ITF from neural microelectrode recordings. The M-EKF mitigates degradations in filter performance resulting from a mismatch between assumed initial conditions and those of a particular realization of a stochastic system. Specifically, the M-EKF is comprised of a bank of extended Kalman filters (EKF), each initialized with different conditions, selected according to the unscented transform. The final estimate is a weighted average of the individual estimates provided by each EKF where the weights reflect how closely the assumed EKF initial conditions match those of the true system. The M-EKF is applied to a synthetic tremor model to display its superior performance to that of the EKF and the unscented Kalman filter.
TEPITOPEpan: Extending TEPITOPE for Peptide Binding Prediction Covering over 700 HLA-DR Molecules

Motivation Accurate identification of peptides binding to specific Major Histocompatibility Complex Class II (MHC-II) molecules is of great importance for elucidating the underlying mechanism of immune recognition, as well as for developing effective epitope-based vaccines and promising immunotherapies for many severe diseases. Due to extreme polymorphism of MHC-II alleles and the high cost of biochemical experiments, the development of computational methods for accurate prediction of binding peptides of MHC-II molecules, particularly for the ones with few or no experimental data, has become a topic of increasing interest. TEPITOPE is a well-used computational approach because of its good interpretability and relatively high performance. However, TEPITOPE can be applied to only 51 out of over 700 known HLA DR molecules. Method We have developed a new method, called TEPITOPEpan, by extrapolating from the binding specificities of HLA DR molecules characterized by TEPITOPE to those uncharacterized. First, each HLA-DR binding pocket is represented by amino acid residues that have close contact with the corresponding peptide binding core residues. Then the pocket similarity between two HLA-DR molecules is calculated as the sequence similarity of the residues. Finally, for an uncharacterized HLA-DR molecule, the binding specificity of each pocket is computed as a weighted average in pocket binding specificities over HLA-DR molecules characterized by TEPITOPE. Result The performance of TEPITOPEpan has been extensively evaluated using various data sets from different viewpoints: predicting MHC binding peptides, identifying HLA ligands and T-cell epitopes and recognizing binding cores. Among the four state-of-the-art competing pan-specific methods, for predicting binding specificities of unknown HLA-DR molecules, TEPITOPEpan was roughly the second best method next to NETMHCIIpan-2.0. Additionally, TEPITOPEpan achieved the best performance in recognizing binding cores. We further analyzed the motifs detected by TEPITOPEpan, examining the corresponding literature of immunology. Its online server and PSSMs therein are available at http://www.biokdd. fudan.edu. cn/Service/TEPITOPEpan/.
Security in Mobile Telephony : The Security Levels in the Different Handy Generations

In mobile telephony, there are several vulnerabilities like interception, fabrication, and denial of services. Security aspects have been improved in every new generation of mobile system. This seminar paper explains security in each generation and discusses how security is ensured in mobile telephony. This paper was written for the Security Computer Systems course held by Björn Victor at the University of Uppsala, Sweden.
Bardoxolone methyl (CDDO-Me) as a therapeutic agent: an update on its pharmacokinetic and pharmacodynamic properties

Triterpenoids have been used for medicinal purposes in many Asian countries because of their anti-inflammatory, antioxidant, antiproliferative, anticancer, and anticarcinogenic properties. Bardoxolone methyl, the C-28 methyl ester of 2-cyano-3,12-dioxoolean-1,9-dien-28-oic acid (CDDO) known as CDDO-Me or RTA 402, is one of the derivatives of synthetic triterpenoids. CDDO-Me has been used for the treatment of chronic kidney disease, cancer (including leukemia and solid tumors), and other diseases. In this review, we will update our knowledge of the clinical pharmacokinetics and pharmacodynamics of CDDO-Me, highlighting its clinical benefits and the underlying mechanisms involved. The role of the Kelch-like erythroid cell-derived protein with CNC homology-associated protein 1 (Keap1)/the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway in the therapeutic activities of CDDO-Me will be discussed. CDDO-Me contains α,β-unsaturated carbonyl groups on rings A and C that can generate reversible adducts with the thiol groups of Cys residues in target proteins such as Keap1 and IκB kinase. At low nanomolar concentrations, CDDO-Me protects the cells against oxidative stress via inhibition of reactive oxygen species generation, while CDDO-Me at low micromolar concentrations induces apoptosis by increasing reactive oxygen species and decreasinging intracellular glutathione levels. Through Keap1/Nrf2 and nuclear factor-κB pathways, this agent can modulate the activities of a number of important proteins that regulate inflammation, redox balance, cell proliferation and programmed cell death. In a Phase I trial in cancer patients, CDDO-Me was found to have a slow and saturable oral absorption, a relatively long terminal phase half-life (39 hours at 900 mg/day), nonlinearity (dose-dependent) at high doses (600–1,300 mg/day), and high interpatient variability. As a multifunctional agent, CDDO-Me has improved the renal function in patients with chronic kidney disease associated with type 2 diabetes. CDDO-Me has shown a promising anticancer effect in a Phase I trial. This agent is generally well tolerated, but it may increase adverse cardiovascular events. Presently, it is being further tested for the treatment of patients with chronic kidney disease, cancer, and pulmonary arterial hypertension.
Bayesian Inference of Spatial Organizations of Chromosomes

Knowledge of spatial chromosomal organizations is critical for the study of transcriptional regulation and other nuclear processes in the cell. Recently, chromosome conformation capture (3C) based technologies, such as Hi-C and TCC, have been developed to provide a genome-wide, three-dimensional (3D) view of chromatin organization. Appropriate methods for analyzing these data and fully characterizing the 3D chromosomal structure and its structural variations are still under development. Here we describe a novel Bayesian probabilistic approach, denoted as “Bayesian 3D constructor for Hi-C data” (BACH), to infer the consensus 3D chromosomal structure. In addition, we describe a variant algorithm BACH-MIX to study the structural variations of chromatin in a cell population. Applying BACH and BACH-MIX to a high resolution Hi-C dataset generated from mouse embryonic stem cells, we found that most local genomic regions exhibit homogeneous 3D chromosomal structures. We further constructed a model for the spatial arrangement of chromatin, which reveals structural properties associated with euchromatic and heterochromatic regions in the genome. We observed strong associations between structural properties and several genomic and epigenetic features of the chromosome. Using BACH-MIX, we further found that the structural variations of chromatin are correlated with these genomic and epigenetic features. Our results demonstrate that BACH and BACH-MIX have the potential to provide new insights into the chromosomal architecture of mammalian cells.
Deformation-specific and deformation-invariant visual object recognition: pose vs. identity recognition of people and deforming objects

When we see a human sitting down, standing up, or walking, we can recognize one of these poses independently of the individual, or we can recognize the individual person, independently of the pose. The same issues arise for deforming objects. For example, if we see a flag deformed by the wind, either blowing out or hanging languidly, we can usually recognize the flag, independently of its deformation; or we can recognize the deformation independently of the identity of the flag. We hypothesize that these types of recognition can be implemented by the primate visual system using temporo-spatial continuity as objects transform as a learning principle. In particular, we hypothesize that pose or deformation can be learned under conditions in which large numbers of different people are successively seen in the same pose, or objects in the same deformation. We also hypothesize that person-specific representations that are independent of pose, and object-specific representations that are independent of deformation and view, could be built, when individual people or objects are observed successively transforming from one pose or deformation and view to another. These hypotheses were tested in a simulation of the ventral visual system, VisNet, that uses temporal continuity, implemented in a synaptic learning rule with a short-term memory trace of previous neuronal activity, to learn invariant representations. It was found that depending on the statistics of the visual input, either pose-specific or deformation-specific representations could be built that were invariant with respect to individual and view; or that identity-specific representations could be built that were invariant with respect to pose or deformation and view. We propose that this is how pose-specific and pose-invariant, and deformation-specific and deformation-invariant, perceptual representations are built in the brain.
Rough Texton based Fundus Image Retrieval

Content based image retrieval (CBIR), is a robust technique widely used in the field of image retrieval. This method uses visual contents like color, texture and shape, to search images from a large scale database of images. Among the primary image contents, texture is an important spatial feature. Texton is a statistical approach used to analyze the texture of an image. Texture-based approach proposed here can take into account the vagueness of images also while retrieving images just as an expert manually retrieves medical images.
A cost-effective approach to the design and layout of a 14-b current-steering DAC macrocell

This brief discusses the economical design of a 14-b current-steering digital-to-analog converter (DAC) macrocell for integration with other analog and digital macrocells in a system-on-chip (SOC). The DAC design is targeted for a standard 0.13-/spl mu/m six-metal single-poly CMOS process. A novel algorithm sets the switching order of individual current sources and minimizes systematic mismatch errors. The design approach minimizes total fabrication cost of the SOC without a loss to specified DAC design requirements. Total macrocell design area is 2.9 mm/sup 2/.
Stochastic Dynamics of Lagrangian Pore‐Scale Velocities in Three‐Dimensional Porous Media

Upscaling dispersion, mixing, and reaction processes from the pore to the Darcy scale is directly related to the understanding of the dynamics of pore‐scale particle velocities, which are at the origin of hydrodynamic dispersion and non‐Fickian transport behaviors. With the aim of deriving a framework for the systematic upscaling of these processes from the pore to the Darcy scale, we present a detailed analysis of the evolution of Lagrangian and Eulerian statistics and their dependence on the injection condition. The study is based on velocity data obtained from computational fluid dynamics simulations of Stokes flow and advective particle tracking in the three‐dimensional pore structure obtained from high‐resolution X‐ray microtomography of a Berea sandstone sample. While isochronously sampled velocity series show intermittent behavior, equidistant series vary in a regular random pattern. Both statistics evolve toward stationary states, which are related to the Eulerian velocity statistics. The equidistantly sampled Lagrangian velocity distribution converges on only a few pore lengths. These findings indicate that the equidistant velocity series can be represented by an ergodic Markov process. A stochastic Markov model for the equidistant velocity magnitude captures the evolution of the Lagrangian velocity statistics. The model is parameterized by the Eulerian velocity distribution and a relaxation length scale, which can be related to hydraulic properties and the medium geometry. These findings lay the basis for a predictive stochastic approach to upscale solute dispersion in complex porous media from the pore to the Darcy scale.
Transmission Selects for HIV-1 Strains of Intermediate Virulence: A Modelling Approach

Recent data shows that HIV-1 is characterised by variation in viral virulence factors that is heritable between infections, which suggests that viral virulence can be naturally selected at the population level. A trade-off between transmissibility and duration of infection appears to favour viruses of intermediate virulence. We developed a mathematical model to simulate the dynamics of putative viral genotypes that differ in their virulence. As a proxy for virulence, we use set-point viral load (SPVL), which is the steady density of viral particles in blood during asymptomatic infection. Mutation, the dependency of survival and transmissibility on SPVL, and host effects were incorporated into the model. The model was fitted to data to estimate unknown parameters, and was found to fit existing data well. The maximum likelihood estimates of the parameters produced a model in which SPVL converged from any initial conditions to observed values within 100–150 years of first emergence of HIV-1. We estimated the 1) host effect and 2) the extent to which the viral virulence genotype mutates from one infection to the next, and found a trade-off between these two parameters in explaining the variation in SPVL. The model confirms that evolution of virulence towards intermediate levels is sufficiently rapid for it to have happened in the early stages of the HIV epidemic, and confirms that existing viral loads are nearly optimal given the assumed constraints on evolution. The model provides a useful framework under which to examine the future evolution of HIV-1 virulence.
Synthesising Labelled Transitions and Operational Congruences in Reactive Systems, Part 1

The dynamics of process calculi, e.g. CCS, have often been defined using a labelled transition system (LTS). More recently it has become common when defining dynamics to use reaction rules ---i.e. unlabelled transition rules--- together with a structural congruence. This form, which I call a reactive system, is highly expressive but is limited in an important way: LTSs lead more naturally to operational equivalences and preorders. This paper shows how to synthesise an LTS for a wide range of reactive systems. A label for an agent (process) `a' is defined to be any context `F' which intuitively is just large enough so that the agent `Fa' (`a' in context `F') is able to perform a reaction step. The key contribution of my work is the precise definition of ``just large enough'' in terms of the categorical notion of relative pushout (RPO). I then prove that several operational equivalences and preorders (strong bisimulation, weak bisimulation, the traces preorder, and the failures preorder) are congruences when sufficient RPOs exist.
A semi-supervised version of heteroscedastic linear discriminant analysis

Heteroscedastic Linear Discriminant Analysis (HLDA) was introduced in [1] as an extension of Linear Discriminant Analysis to the case where the class-conditional distributions have unequal covariances. The HLDA transform is computed such that the likelihood of the training (labeled) data is maximized, under the constraint that the projected distributions are orthogonal to a nuisance space that does not offer any discrimination. In this paper we consider the case of semi-supervised learning, where a large amount of unlabeled data is also available. We derive update equations for the parameters of the projected distributions, which are estimated jointly with the HLDA transform, and we empirically compare it with the case where no unlabeled data are available. Experimental results with synthetic data and real data from a vowel recognition task show that, in most cases, semi-supervised HLDA results in improved performance over HLDA.
Behavioral optimization using the manipulation of timing constraints

We introduce a transformation, named rephasing, that manipulates the timing parameters in control-data-flow graphs (CDFG's) during the high-level synthesis of data-path-intensive applications. Timing parameters in such CDFG's include the sample period, the latencies between input-output pairs, the relative times at which corresponding samples become available on different inputs, and the relative times at which the corresponding samples become available at the delay nodes. While some of the timing parameters may be constrained by performance requirements, or by the interface to the external world, others remain free to be chosen during the process of high-level synthesis. Traditionally high-level synthesis systems for data-path-intensive applications either have assumed that all the relative times, called phases, when corresponding samples are available at input and delay nodes are zero (i.e., all input and delay node samples enter at the initial cycle of the schedule) or have automatically assigned values to these phases as part of the data-path allocation/scheduling step in the case of newer schedulers that use techniques like overlapped scheduling to generate complex time shapes. Rephasing, however, manipulates the values of these phases as an algorithm transformation before the scheduling/allocation stage. The advantage of this approach is that phase values can be chosen to transform and optimize the algorithm for explicit metrics such as area, throughput, latency, and power. Moreover, the rephasing transformation can be combined with other transformations such as algebraic transformations. We have developed techniques for using rephasing to optimize a variety of design metrics, and our results show significant improvements in several design metrics. We have also investigated the relationship and interaction of rephasing with other high-level synthesis tasks.
Multi-module vulnerability analysis of web-based applications

In recent years, web applications have become tremendously popular, and nowadays they are routinely used in security-critical environments, such as medical, financial, and military systems. As the use of web applications for critical services has increased, the number and sophistication of attacks against these applications have grown as well. Current approaches to securing web applications focus either on detecting and blocking web-based attacks using application-level firewalls, or on using vulnerability analysis techniques to identify security problems before deployment. The vulnerability analysis of web applications is made difficult by a number of factors, such as the use of scripting languages, the structuring of the application logic into separate pages and code modules, and the interaction with back-end databases. So far, approaches to web application vulnerability analysis have focused on single application modules to identify insecure uses of information provided as input to the application. Unfortunately, these approaches are limited in scope, and, therefore, they cannot detect multi-step attacks that exploit the interaction among multiple modules of an application. We have developed a novel vulnerability analysis approach that characterizes both the extended state and the intended workflow of a web application. By doing this, our analysis approach is able to take into account inter-module relationships as well as the interaction of an application's modules with back-end databases. As a result, our vulnerability analysis technique is able to identify sophisticated multi-step attacks against the application's workflow that were not addressed by previous approaches. We implemented our technique in a prototype tool, called MiMoSA, and tested it on several applications, identifying both known and new vulnerabilities.
NUMA impact on network storage protocols over high-speed raw Ethernet P ilar

Current storage trends dictate placing fast storage devices in all servers and using them as a single distributed storage system. In this converged model where storage and compute resources co-exist in the same server, the role of the network is becoming more important: network overhead is becoming a main limitation to improving storage performance. In our previous work we have designed Tyche, a network protocol for converged storage that bundles multiple 10GigE links transparently and reduces protocol overheads over raw Ethernet without hardware support. However, current technology trends and server consolidation dictates building servers with large amounts of resources (CPU, memory, network, storage). Such servers need to employ Non-Uniform Memory Architectures (NUMA) to scale memory performance. NUMA introduces significant problems with the placement of data and buffers at all software levels. In this paper, we first use Tyche to examine the performance implications of NUMA servers on end-to-end network storage performance. Our results show that NUMA effects have significant negative impact and can reduce throughput by almost 2x on servers with as few as 8 cores (16 hyper-threads). Then, we propose extensions to network protocols that can mitigate this impact. We use information about the location of data, cores, and NICs to properly align data transfers and minimize the impact of NUMA servers. Our design almost entirely eliminates NUMA effects by encapsulating all protocol structures to a “channel” concept and then carefully mapping channels and their resources to NICs and NUMA nodes.