Miracle-dz/UniFAR-FTUs huggingface dataset:
STABILITY IN THE WEAK VARIATIONAL PRINCIPLE OF BAROTROPIC FLOWS

I find conditions under which the "Weak Energy Principle" of Katz, Inagaki and Yahalom (1993) gives necessary and sufficient conditions. My conclusion is that, necessary and sufficient conditions of stability are obtained when we have only two mode coupling in the gyroscopic terms of the perturbed Lagrangian. To illustrate the power of this new energy principle, I have calculated the stability limits of two dimensional configurations such as ordinary Maclaurin disk, an infinite self gravitating rotating sheet, and a two dimensional Rayleigh flow which has well known sufficient conditions of stability. All perturbations considered are in the same plane as the configurations. The limits of stability are identical with those given by a dynamical analysis when available, and with the results of the strong energy principle analysis when given. Thus although the "Weak Energy" method is mathematically more simple than the "Strong Energy" method of Katz, Inagaki and Yahalom )1993) since it does not involve solving second order partial differential equations, it is by no means less effective.
DIFFUSE CLUSTER-LIKE RADIO EMISSION IN POOR ENVIRONMENTS

We present a study of the spectral, polarimetric, morphological, and environmental properties of the diffuse radio source 0809+39 using observations taken with the Westerbork Synthesis Radio Telescope, the Very Large Array, and archival optical and X-ray data. The source has two distinct diffuse, steep-spectrum components, one in the north that is highly polarized, and a linear southern component undetected in polarization. We discuss several plausible origins for each component, and conclude that the northern bright polarized component is most likely a radio relic associated with a poor z ∼ 0.2 cluster of galaxies, with a radio/X-ray luminosity ratio two orders of magnitude above typical values. The southern component is aligned with a more extended filament of galaxies ∼5 Mpc long at z ∼ 0.04. Deep optical and X-ray follow-ups are still needed in order to confirm and understand the physical origins of the synchrotron emission. Whatever the details of these origins, 0809+39 highlights the utility of synchrotron radiation for illuminating the diffuse components of low density environments unrelated to rich clusters.
Conditional Inactivation of Presenilin 1 Prevents Amyloid Accumulation and Temporarily Rescues Contextual and Spatial Working Memory Impairments in Amyloid Precursor Protein Transgenic Mice

Accumulation of β-amyloid (Aβ) peptides in the cerebral cortex is considered a key event in the pathogenesis of Alzheimer's disease (AD). Presenilin 1 (PS1) plays an essential role in the γ-secretase cleavage of the amyloid precursor protein (APP) and the generation of Aβ peptides. Reduction of Aβ generation via the inhibition of γ-secretase activity, therefore, has been proposed as a therapeutic approach for AD. In this study, we examined whether genetic inactivation of PS1 in postnatal forebrain-restricted conditional knock-out (PS1 cKO) mice can prevent the accumulation of Aβ peptides and ameliorate cognitive deficits exhibited by an amyloid mouse model that overexpresses human mutant APP. We found that conditional inactivation of PS1 in APP transgenic mice (PS1 cKO;APP Tg) effectively prevented the accumulation of Aβ peptides and formation of amyloid plaques and inflammatory responses, although it also caused an age-related accumulation of C-terminal fragments of APP. Short-term PS1 inactivation in young PS1 cKO;APP Tg mice rescued deficits in contextual fear conditioning and serial spatial reversal learning in a water maze, which were associated with APP Tg mice. Longer-term PS1 inactivation in older PS1 cKO;APP Tg mice, however, failed to rescue the contextual memory and hippocampal synaptic deficits and had a decreasing ameliorative effect on the spatial memory impairment. These results reveal that in vivo reduction of Aβ via the inactivation of PS1 effectively prevents amyloid-associated neuropathological changes and can, but only temporarily, improve cognitive impairments in APP transgenic mice.
Patchy distributions of myelin and vesicular glutamate transporter 2 align with cytochrome oxidase blobs and interblobs in the superficial layers of the primary visual cortex

Blobs are a modular component of the primary visual cortex (area 17) of all primates, but not of other mammals closely related to primates. They are characterized as an even distribution of patches, puffs, or blobs of dense cytochrome oxidase (CO) expression in layer III of area 17, and are now known to differ from surrounding, nonblob cortex in thalamic, intrinsic, and extrastriate connections. Previous studies have also recognized a blob-like pattern of myelin-dense patches in layer III of area 17 of primates, and more recently the vesicular glutamate transporter (VGLUT)-2 isoform of the VGLUT family has been found to selectively distribute to layer III patches in a similar blob-like pattern. Here, we sought to determine if the blob-like patterns all identify the same modular structures in area 17 of primates by staining alternate brain sections cut parallel to the surface of area 17 of a prosimian primate (Otolemur garnettii) for CO, myelin, and VGLUT2. By aligning the sections from the three preparations, we provide clear evidence that the three preparations all identify the same modular blob structures. The results provide a further understanding of the functional nature of the blobs by demonstrating that their higher level of CO activity is related to thalamic inputs from the lateral geniculate nucleus that use VGLUT2 as their main glutamate transporter, and via myelinated axons.
Prediction of breast cancer using classification rule mining techniques in blood test datasets

Mining provides useful information from the huge volume of the data stored in repositories. The present study focus on implementing five different algorithms using the data mining WEKA. The algorithm in the study includes Naive Bayes, Zero R, One R, J48 and Random Tree algorithm. All these well-known familiar algorithms are used in classification rule mining techniques. Datasets are collected from the Arignar Anna Cancer Institute for implementing the Data Mining. These collected datasets are preprocessed and then used for implementing the algorithm. The different types of algorithms are executed using the collected datasets and, the results are shown in separate window as well as graphical or tree manner based on it applicability.
PROTA: A Privacy-pReserving prOtocol for real-time Targeted Advertising

With the widespread use of Internet, online advertising, as a newly emerged way of delivering advertisements, has become the focus of attention. Compared with traditional ways of advertising, real-time targeted online advertising is much more efficient and profitable, taking the advantage of abundant online users' profiles. Advertisements can be delivered to potential users who are actually interested in the ad content, which improves the accuracy of advertising, and thus potentially increases advertisers' profits. However, targeted advertising makes use of online users' personal profiles, which raises significant privacy concerns since personal profiles may contain sensitive information. It is interesting but challenging to design a privacy-preserving protocol, which allows advertising platform to effectively deliver ads to interested users, while protecting the users' private information. In this paper, we propose a Privacy-pReserving prOtocol for real-time Targeted Advertising (PROTA). We theoretically prove the privacy properties of PROTA, and show that the system requirements are satisfied. Evaluations are also conducted to demonstrate the feasibility of PROTA.
Intrusion Detection Using a PCB and IP address

It is typical to patch vulnerability codes after incidents occur. It requires a lot of time and effort to recover system damage by intrusions. It is necessary to detect and block intrusions by boosting the durability of systems. This paper proposes a robust method to prevent intrusions by the self-monitoring intrusion system instead of system administrators in Linux system. This method, IDIP, monitors every new scheduled process and checks the intrusion possibilities using IP information of processes. It might be implemented on kernel and a user space process. The proposed method is implemented and tested on Linux, monitors the root privileged processes and increases the level of system security. To test the proposed method, exploit codes are used to attack the vulnerable programs. Although the proposed method is implemented in Linux system, it is applicable to other operating systems.
Monopoles and instantons on partially compactified D-branes

Motivated by the recent D-brane constructions of world-volume monopoles and instantons, we study the supersymmetric SU(N) Yang-Mills theory on S{sup 1}{times}R{sup 3+1}, spontaneously broken by a Wilson loop. In addition to the usual N{minus}1 fundamental monopoles, the Nth Bogomol{close_quote}nyi-Prasad-Sommerfield monopole appears from the Kaluza-Klein sector. When all N monopoles are present, net magnetic charge vanishes and the solution can be reinterpreted as a Wilson-loop instanton of unit Pontryagin number. The instanton-multimonopole moduli space is explicitly constructed, and seen to be identical to a Coulomb phase moduli space of a U(1){sup N} gauge theory in 2+1 dimensions related to Kronheimer{close_quote}s gauge theory of SU(N)-type. This extends the results by Intriligator and Seiberg to the finite couplings that, in the infrared limit of Kronheimer{close_quote}s theory, the Coulomb phase parametrizes a centered SU(N) instanton. We also elaborate on the case of restored SU(N) symmetry. {copyright} {ital 1997} {ital The American Physical Society}
Performance analysis of packet scheduling algorithm for video service in downlink LTE

Network capacity and congestion in wireless communication cannot be eluded with the development of technology, users, and services; especially with the increasing of real time data services such as video that needs larger capacity and higher Quality of Service (QoS) requisitions. Meanwhile, network resource (bandwidth) available in a communication network as one of the essential components is very limited. The bandwidth usage rule is necessary so that the efficiency of the network while serving active users can be maximized. A scheduling algorithm has an important role in regulating bandwidth allocation in a wireless communication. It is used to distribute the network resource for all active users effectively. This paper provides a study of a wide variety of scheduling techniques used in Long Term Evolution (LTE) downlink data packets to see their performance specially in handling video real time service. Research on various scheduling algorithms used in LTE network is necessary to discover the characteristics of each algorithm. Simulation results show that Frame Level Scheduling (FLS) algorithm performance is better than other PS algorithms simulated in terms of bandwidth, delay, and fairness when serving video packet data service in LTE network.
Scalable data mining for rules

Data mining is the process of automatic extraction of novel, useful, and understandable patterns in very large databases. High-performance scalable and parallel computing is crucial for ensuring system scalability and inter-activity as datasets grow inexorably in size and complexity. This thesis deals with both the algorithmic and systems aspects of scalable and parallel data mining algorithms applied to massive databases. The algorithmic aspects focus on the design of efficient, scalable, disk-based parallel algorithms for three key rule discovery techniques---association rules, sequence discovery, and decision tree classification. The systems aspects deal with the scalable implementation of these methods on both sequential machines and popular parallel hardware ranging from shared-memory systems (SMP) to hybrid hierarchical clusters of networked SMP workstations. pp The association and sequence mining algorithms use lattice-theoretic combinatorial properties to decompose the original problem into small independent sub-problems that can be solved in main memory. Using efficient search techniques and simple intersection operations all frequent patterns are enumerated in a few database scans. The parallel algorithms are asynchronous, requiring no communication or synchronization after an initial set-up phase. Furthermore, the algorithms are based on a hierarchical parallelization, utilizing both shared-memory and message-passing primitives. In classification rule mining, we present disk-based parallel algorithms on shared-memory multiprocessors, the first such study. Extensive experiments have been conducted for all three problems, showing immense improvement over previous approaches, with linear scalability in database size.
Model driven engineering for MPSOC design space exploration

This paper presents a Model Driven Engineering approach for MPSoC Design Space Exploration (DSE) to deal with the ever-growing challenge of designing complex embedded systems. This approach allows the designer to automatically select the most adequate modeling solution for application, platform, and mapping between application and platform, in an integrated and simultaneous way and at a very early design stage, before system synthesis and code generation have been performed. The exploration is based on high-level estimates of physical characteristics of each candidate solution. In an experimental setting, the DSE tool automatically performs four design activities: it selects the number of processors, maps tasks to processors, allocates processors to bus segments, and sets the voltage of each processor. Experimental results, extracted from a DSE scenario for a real application, show that the proposed estimation and exploration approach may find a suitable solution regarding the design requirements and constraints in a very short time, with an acceptable accuracy, without relying on costly synthesis-and-simulation cycles.
On-line off-line Ranking Support Vector Machine and analysis

Ranking support vector machine (RSVM) learning is equivalent to solving a convex quadratic programming problem. Currently there exists some difficulties for exact online ranking learning. This paper presents an exact and effective method that can solve the online ranking learning problem and shows the feasibility and finite convergence of the algorithm from the perspective of theoretical analysis. Additionally, this paper extends this method for online learning to offline ranking learning and offers another algorithm for solving large-scale RSVM.
Correlation between Ureaplasma Subgroup 2 and Genitourinary Tract Disease Outcomes Revealed by an Expanded Multilocus Sequence Typing (eMLST) Scheme

The multilocus sequence typing (MLST) scheme of Ureaplasma based on four housekeeping genes (ftsH, rpL22, valS, and thrS) was described in our previous study; here we introduced an expanded MLST (eMLST) scheme with improved discriminatory power, which was developed by adding two putative virulence genes (ureG and mba-np1) to the original MLST scheme. To evaluate the discriminatory power of eMLST, a total of 14 reference strains of Ureaplasma serovars and 269 clinical strains (134 isolated from symptomatic patients and 135 obtained from asymptomatic persons) were investigated. Our study confirmed that all 14 serotype strains could successfully be differentiated into 14 eMLST STs (eSTs), while some of them could not even be differentiated by the MLST, and a total of 136 eSTs were identified among the clinical isolates we investigated. In addition, phylogenetic analysis indicated that two genetically significantly distant clusters (cluster I and II) were revealed and most clinical isolates were located in cluster I. These findings were in accordance with and further support for the concept of two well-known genetic lineages (Ureaplasma parvum and Ureaplasma urealyticum) in our previous study. Interestingly, although both clusters were associated with clinical manifestation, the sub-group 2 of cluster II had pronounced and adverse effect on patients and might be a potential risk factor for clinical outcomes. In conclusion, the eMLST scheme offers investigators a highly discriminative typing tool that is capable for precise epidemiological investigations and clinical relevance of Ureaplasma.
Single-symbol maximum likelihood decodable linear STBCs

Space-time block codes (STBCs) from orthogonal designs (ODs) and coordinate interleaved orthogonal designs (CIOD) have been attracting wider attention due to their amenability for fast (single-symbol) maximum-likelihood (ML) decoding, and full-rate with full-rank over quasi-static fading channels. However, these codes are instances of single-symbol decodable codes and it is natural to ask, if there exist codes other than STBCs form ODs and CIODs that allow single-symbol decoding? In this paper, the above question is answered in the affirmative by characterizing all linear STBCs, that allow single-symbol ML decoding (not necessarily full-diversity) over quasi-static fading channels-calling them single-symbol decodable designs (SDD). The class SDD includes ODs and CIODs as proper subclasses. Further, among the SDD, a class of those that offer full-diversity, called Full-rank SDD (FSDD) are characterized and classified. We then concentrate on square designs and derive the maximal rate for square FSDDs using a constructional proof. It follows that 1) except for N=2, square complex ODs are not maximal rate and 2) a rate one square FSDD exist only for two and four transmit antennas. For nonsquare designs, generalized coordinate-interleaved orthogonal designs (a superset of CIODs) are presented and analyzed. Finally, for rapid-fading channels an equivalent matrix channel representation is developed, which allows the results of quasi-static fading channels to be applied to rapid-fading channels. Using this representation we show that for rapid-fading channels the rate of single-symbol decodable STBCs are independent of the number of transmit antennas and inversely proportional to the block-length of the code. Significantly, the CIOD for two transmit antennas is the only STBC that is single-symbol decodable over both quasi-static and rapid-fading channels.
The substellar companion in the eclipsing white dwarf binary SDSS J141126.20+200911.1

We present high time resolution SDSS-g′ and SDSS-z′ light curves of the primary eclipse in SDSS J141126.20+200911.1, together with time-resolved X-Shooter spectroscopy and near-infrared (NIR) JHKs photometry. Our observations confirm the substellar nature of the companion, making SDSS J141126.20+200911.1 the first eclipsing white dwarf/brown dwarf binary known. We measure a (white dwarf model dependent) mass and radius for the brown dwarf companion of M2 = 0.050 ± 0.002 M⊙ and R2 = 0.072 ± 0.004 M⊙, respectively. The lack of a robust detection of the companion light in the z′-band eclipse constrains the spectral type of the companion to be later than L5. Comparing the NIR photometry to the expected white dwarf flux reveals a clear Ks-band excess, suggesting a spectral type in the range L7–T1. The radius measurement is consistent with the predictions of evolutionary models, and suggests a system age in excess of 3 Gyr. The low companion mass is inconsistent with the inferred spectral type of L7–T1, instead predicting a spectral type nearer T5. This indicates that irradiation of the companion in SDSS J141126.20+200911.1 could be causing a significant temperature increase, at least on one hemisphere.
THE JET OF 3C 17 AND THE USE OF JET CURVATURE AS A DIAGNOSTIC OF THE X-RAY EMISSION PROCESS

We report on the X-ray emission from the radio jet of 3C 17 from Chandra observations and compare the X-ray emission with radio maps from the VLA archive and with the optical–IR archival images from the Hubble Space Telescope. X-ray detections of two knots in the 3C 17 jet are found and both of these features have optical counterparts. We derive the spectral energy distribution for the knots in the jet and give source parameters required for the various X-ray emission models, finding that both inverse Compton (IC)/cosmic microwave background (CMB) and synchrotron are viable to explain the high energy emission. A curious optical feature (with no radio or X-ray counterparts) possibly associated with the 3C 17 jet is described. We also discuss the use of curved jets for the problem of identifying IC X-ray emission via scattering on CMB photons.
Finite-Dimensional Constrained Fuzzy Control for a Class of Nonlinear Distributed Process Systems

This correspondence studies the problem of finite-dimensional constrained fuzzy control for a class of systems described by nonlinear parabolic partial differential equations (PDEs). Initially, Galerkin's method is applied to the PDE system to derive a nonlinear ordinary differential equation (ODE) system that accurately describes the dynamics of the dominant (slow) modes of the PDE system. Subsequently, a systematic modeling procedure is given to construct exactly a Takagi-Sugeno (T-S) fuzzy model for the finite-dimensional ODE system under state constraints. Then, based on the T-S fuzzy model, a sufficient condition for the existence of a stabilizing fuzzy controller is derived, which guarantees that the state constraints are satisfied and provides an upper bound on the quadratic performance function for the finite-dimensional slow system. The resulting fuzzy controllers can also guarantee the exponential stability of the closed-loop PDE system. Moreover, a local optimization algorithm based on the linear matrix inequalities is proposed to compute the feedback gain matrices of a suboptimal fuzzy controller in the sense of minimizing the quadratic performance bound. Finally, the proposed design method is applied to the control of the temperature profile of a catalytic rod.
Reliable and Trustworthy Memory Acquisition on Smartphones

With the wide usage of smartphones in our daily life, new malware is emerging to compromise the mobile OS and then steal or manipulate sensitive data from mobile applications. Forensic analysis tools demand a reliable and trustworthy memory acquisition of the operating systems running on the smartphones for further digital forensic analysis. However, a compromised OS may launch denial of service attacks to prevent a valid memory acquisition by forensic examiners. In this paper, we develop a TrustZone-based memory acquisition mechanism called TrustDump that is capable of reliably and securely obtaining the RAM memory and CPU registers of the mobile OS even if the OS has crashed or been compromised. TrustDump is isolated from the mobile OS by TrustZone. Instead of using a hypervisor to ensure the isolation between the OS and the memory acquisition tool, we rely on ARM TrustZone to achieve a hardware-assisted isolation with a small trusted computing base. TrustDump can include basic online analysis modules to catch malware in an early stage. Moreover, the acquired memory and register data can be sent to a remote server through a fast Micro-USB port for real-time forensics analysis when the OS runs or a slow serial port for further forensic analysis when the OS has crashed. A trusted graphical user interface is integrated in the TrustZone to authenticate the user and prevent the misuse of our memory acquisition tool. We build a TrustDump prototype on Freescale i.MX53 QSB.