Miracle-dz/UniFAR-FTUs huggingface dataset:
A deviant transform based approach for color image registration

In this paper, an unusual form of image registration is proposed which focuses upon using various transforms for fast and accurate image registration. Image registration is the process of transforming different sets of data into one coordinate system. The data set can be a set of photographs, data from various sensors, from different times, or from different viewpoints. The applications of image registration are in the field of computer vision, medical imaging, military automatic target recognition, and in analyzing images and data from satellites. The proposed technique works upon satellite images. It tries to find out area of interest by comparing the unregistered image with source image and finding the part that has highest similarity matching. The paper mainly works on the concept of seeking water or land in a stored image. The proposed technique uses different transforms like Discrete Cosine Transform, Discrete Wavelet Transform, HAAR Transform and Walsh transform to achieve accurate image registration. The paper also focuses upon using normalized cross correlation as an area based technique of image registration for the purpose of comparison. The proposed algorithm is worked over various sizes of satellite images such as 256×256, 1024×1024 etc. The root mean square error is used as similarity measure. The experiment results show that the proposed algorithm can successfully register the template and can also process local distortion in high-resolution satellite images.
Exponential and Uniform Ergodicity of Markov Processes

General characterizations of geometric convergence for Markov chains in discrete time on a general state space have been developed recently in considerable detail. Here we develop a similar theory for φ-irreducible continuous time processes and consider the following types of criteria for geometric convergence: 1. the existence of exponentially bounded hitting times on one and then all suitably small sets; 2. the existence of Foster-Lyapunov or drift conditions for any one and then all skeleton and resolvent chains; 3. the existence of drift conditions on the extended generator A of the process. We use the identity AR β = β(R β - I) connecting the extended generator and the resolvent kernels R β to show that, under a suitable aperiodicity assumption, exponential convergence is completely equivalent to any of criteria 1-3. These conditions yield criteria for exponential convergence of unbounded as well as bounded functions of the chain. They enable us to identify the dependence of the convergence on the initial state of the chain and also to illustrate that in general some smoothing is required to ensure convergence of unbounded functions.
An Efficient Provably Secure Certificate-Based Blind Signature Scheme

The paper proposes a new and efficient certificate-based blind signature scheme with bilinear maps combining blind signature with certificate-based encryption. The proposed scheme solves the escrow problem, simplifies the certificate management process and retains the merits of blind signature. The new scheme is provably secure, and the analysis of the scheme's security is presented, the results demonstrate that our scheme's capability achieves high level of security under the computational Diffie-Hellman complexity assumption, and the scheme is efficient.
Spitzer Identification of the Least Massive Known Brown Dwarf with a Circumstellar Disk

Using the Infrared Array Camera (IRAC) aboard the Spitzer Space Telescope, we have obtained mid-infrared photometry of the least massive known brown dwarf in the Chamaeleon I star-forming region. For this young brown dwarf, OTS 44, we have constructed a spectral energy distribution (SED) from 0.8 to 8 μm by combining the measurements at 3.6, 4.5, 5.8, and 8.0 μm from IRAC with ground-based photometry at I, J, H, and K. The resulting SED for OTS 44 exhibits significant excess emission longward of 3 μm relative to the SED expected from the photosphere of the brown dwarf. We have successfully modeled the source of this excess emission in terms of an irradiated viscous accretion disk with ≲ 10-10 M☉ yr-1. With a spectral type of M9.5 and a mass of ~15MJup, OTS 44 is now the coolest and least massive brown dwarf observed to have a circumstellar disk. These measurements demonstrate that disks exist around brown dwarfs even down to the deuterium-burning mass limit and the approximate upper mass limit of extrasolar planetary companions.
Immunomodulatory Potential of Human Adipose Mesenchymal Stem Cells Derived Exosomes on in vitro Stimulated T Cells

In the recent years, it has been demonstrated that the biological activity of mesenchymal stem cells (MSCs) is mediated through the release of paracrine factors. Many of these factors are released into exosomes, which are small membranous vesicles that participate in cell–cell communication. Exosomes from MSCs are thought to have similar functions to MSCs such as repairing and regeneration of damaged tissue, but little is known about the immunomodulatory effect of these vesicles. Based on an extensive bibliography where the immunomodulatory capacity of MSCs has been demonstrated, here we hypothesized that released exosomes from MSCs may have an immunomodulatory role on the differentiation, activation and function of different lymphocyte subsets. According to this hypothesis, in vitro experiments were performed to characterize the immunomodulatory effect of human adipose MSCs derived exosomes (exo-hASCs) on in vitro stimulated T cells. The phenotypic characterization of cytotoxic and helper T cells (activation and differentiation markers) together with functional assays (proliferation and IFN-γ production) demonstrated that exo-hASCs exerted an inhibitory effect in the differentiation and activation of T cells as well as a reduced T cell proliferation and IFN-γ release on in vitro stimulated cells. In summary, here we demonstrate that MSCs-derived exosomes are a cell-derived product that could be considered as a therapeutic agent for the treatment of inflammation-related diseases.
Modern, postmodern, amodern

Postmodernism’s deconstructions were never ends in themselves. The point was always to arrive at new clarity in making the implicit explicit, requiring deconstruction to remain true to philosophy (Derrida, 1989, p. 218). Lingering questions remain as to how to accept and deal with–without trying to control and without submitting blindly to–the ways that language preformats the world as thinkable. Scott (1998) documents failed ‘high modern’ efforts in trying to improve the human condition, and points to language itself as the best model for new forms of social life capable of continually adapting broad principles to novel circumstances. Language provides the best available model because it is ‘a structure of meaning and continuity that is never still and ever open to the improvisations of its speakers’ (Scott, 1998, p. 357). Taking language as our model requires information infrastructures sensitive to multiple levels of complexity and the discontinuities that must be negotiated if we are to integrate openness and malleability with structure and navigability (Star & Ruhleder, 1996). Efforts in this direction focus on ecologizing, rather than modernizing (Fisher & Stenner, in press). Following Galison (1997), Latour, and others, the contrast emphasizes the differences between a modern focus on data, a postmodern focus on the theory-dependence of data, and an unmodern or amodern focus on data-theory-instrument and thing-concept-word assemblages embodying local meanings in globally interconnected ecosystems. In education’s ecosystems, the aim is to coherently coordinate developmental-formative, horizontal quality improvement, and vertical accountability information infrastructure applications. Negotiating the discontinuities of varying complexity across these levels of context requires understanding that:
Molecular cascades that mediate the influence of inflammation on epilepsy

Experimental evidence strongly indicates a significant role for inflammatory and immune mediators in initiation of seizures and epileptogenesis. Here we will summarize data supporting the involvement of IL‐1β, TNF‐α and toll‐like receptor 4 in seizure generation and the process of epileptogenesis. The physiological homeostasis and control over brain immune response depends on the integrity of the blood‐brain barrier, transforming growth factor (TGF)‐β signaling and leukocyte migration. To what extent targeting the immune system is successful in preventing epileptogenesis, and which signaling pathway should be beleaguered is still under intensive research.
Inflammatory Bowel Disease Cohort Studies in Korea: Present and Future

Inflammatory bowel disease (IBD) is defined as a chronic and relapsing inflammatory disorder of the intestine. Intestinal inflammation in IBD has been proposed to be attributable to the interplay between microbial, genetic, environmental, and immunological factors. The incidence and prevalence rates of IBD are rapidly increasing apparently in other parts of the world, with dramatic increases especially in East Asia. Generally, cohort studies are useful for estimating the incidence, prevalence, natural course, prognosis, and risk factors of diseases. In particular, cohort studies performed in Western countries have well described the prevalence, risk factors, and natural course of IBD and investigated its genetic pathophysiology. However, the outcomes of IBD cohort studies performed in Korea are not as persuasive as those of Western studies because of the relatively low prevalence of IBD and short follow-up periods of the cohorts in Korea. Despite this critical limitation, members of the Korean Association for the Study of Intestinal Diseases have demonstrated outstanding results. Some unique features of IBD patients in Korea are well demonstrated, such as thiopurine-induced leukopenia or risks of opportunistic tuberculosis infection in patients receiving tumor necrosis factor-α inhibitors. In this review, the present authors summarized the key points of the results of the cohort studies performed in Korea and explored future perspectives.
Precision Timed (PRET) Computation in Cyber-Physical Systems

Cyber-Physical Systems (CPS) are integrations of computation with physical processes. Embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical processes affect computations and vice versa. In the physical world, the passage of time is inexorable and concurrency is intrinsic. Neither of these properties is present in today’s computing and networking abstractions. As a consequence, these abstractions require some fundamental rethinking. It is tempting to believe that the CPS problems can be solved by overlaying higher-level abstractions on top of existing computing technology. Indeed, it would be a scary prospect to suggest that much of the foundation of existing technology is flawed and must be rebuilt. How could this possibly result in a practical research program that will see results in our lifetime? In this position paper, we make a case that core computing abstractions must be and can be effectively and practically rebuilt. The objective is to enable a new generation of cyberphysical systems where computation and physical processes are tightly intertwined. This requires re-introducing properties that were deliberately and systematically abstracted away in the 20-th century view of computation. We approach the problem bottom-up. We must first rebuild the computational engines, and then build revised higher level abstractions on top of these.
Provably good and practically efficient algorithms for CMP

To reduce chip-scale topography variation in Chemical Mechanical Polishing (CMP) process, dummy fill is widely used to improve the layout density uniformity. Previous researches formulated the dummy fill problem as a standard Linear Program (LP). However, solving the huge linear program formed by real-life designs is very expensive and has become the hurdle in deploying the technology. Even though there exist efficient heuristics, their performance cannot be guaranteed. In this paper, we develop a dummy fill algorithm that is both efficient and with provably good performance. It is based on a fully polynomial time approximation scheme by Fleischer [4] for covering LP problems. Furthermore, based on the approximation algorithm, we also propose a new greedy iterative algorithm to achieve high quality solutions more efficiently than previous Monte-Carlo based heuristic methods. Experimental results demonstrate the effectiveness and efficiency of our algorithms.
Improving intergroup relations between Catholics and Protestants in Northern Ireland via E-contact

Northern Ireland is characterised by extensive segregation between its predominantly Catholic and Protestant communities. With the aim of overcoming this segregation, the current study experimentally evaluated the effectiveness of electronicor E-contact as a novel indirect contact and prejudice-reduction strategy. Here, Catholic and Protestant participants were not required to meet physically but were involved in a collaborative and goal-orientated online interaction with a member of the other community. As predicted, E-contact improved both Catholics’ and Protestants’ outgroup attitudes via improved contact expectancies and reduced intergroup anxiety. These findings provide support for the contemporary role of online interactions in actively overcoming the physical and psychological barriers that often prevent prejudice reduction in segregated communities.
Learning from failed demonstrations in unreliable systems

This paper presents a method to teach a robot to play Ping Pong from failed demonstrations in a highly noisy and uncertain setting. To infer useful information from failed demonstrations, we use a MultiDonut Algorithm (Grollman and Billard, 2012) that minimises the probability of repeating a failed demonstration and generates new attempts similar but not quite the same as the demonstration. We compare human demonstrations against a random strategy and show that human demonstrations provide useful information and hence yield faster learning, especially in higher dimensions. We show that learning from observing failed attempts allows the robot to perform the task more reliably than any individual demonstrator did. We also show how this algorithm adapts to gradual deterioration in the system and increases the chances of success when interacting with an unreliable system.
Efficient deployment of connected sensing devices using circle packing algorithms

In this paper, we explore different sensor deployment problems and how these problems can be solved optimally using the current packing approaches in terms of small-scale problems. In addition, we consider the deployment of either homogenous or heterogeneous sensing devices. The deployment objectives are to maximize the coverage of the monitored field and use the best of the sensing devices characteristics as well as developing a connected deployment scheme. We propose a novel algorithm named Sequential Packing-based Deployment Algorithm (SPDA) for the deployment of heterogeneous sensors in order to maximize the coverage of the monitored field and connectivity of the deployed sensors. The algorithm is inspired from the packing theories in computational geometry where it benefits from many of the observations properties that are captured from the optimal packing solutions. The algorithm efficiency is examined using different case studies.
Efficient, Balanced Data Placement Algorithm in Scalable Storage Clusters

Data distribution and load balancing become increasingly important in large-scale distributed storage system. This paper focuses on the problem of designing an optimal, self-adaptive strategies for balanced distribution and reorganization of replicated objects among a dynamically heterogeneous nodes, and presents a novel decentralized algorithm, Dynamic Interval Mapping, which maps replicated objects to a scalable collection of nodes, it distributes objects to nodes optimally, redistributing minimum amount of objects when new nodes are added or existing nodes are removed to maintain the balanced distribution. It supports weighted allocation and guarantees that replicas of a particular object are not placed on the same node. The time complexity and storage requirements are superior to previous methods.
Specific Destruction of HIV Proviral p17 Gene in T Lymphoid Cells Achieved by the Genome Editing Technology

Recent development in genome editing technologies has enabled site-directed deprivation of a nucleotide sequence in the chromosome in mammalian cells. Human immunodeficiency (HIV) infection causes integration of proviral DNA into the chromosome, which potentially leads to re-emergence of the virus, but conventional treatment cannot delete the proviral DNA sequence from the cells infected with HIV. In the present study, the transcription activator-like effector nucleases (TALENs) specific for the HIV p17 gene were constructed, and their activities to destroy the target sequence were evaluated. SSA assay showed a high activity of a pair of p17-specific TALENs. A human T lymphoid cell line, Jurkat, was infected with a lentivirus vector followed by transfection with the TALEN–HIV by electroporation. The target sequence was destructed in approximately 10–95% of the p17 polymerase chain reaction clones, and the efficiencies depended on the Jurkat–HIV clones. Because p17 plays essential roles for assembly and budding of HIV, and this gene has relatively low nucleotide sequence diversity, genome editing procedures targeting p17 may provide a therapeutic benefit for HIV infection.
Power Estimation in Mobile Communication Systems

Accurate power estimation has an important role for power control and handoff decisions in mobile communications. Window based weighed sample average power estimators are commonly used due to their simplicity. In practice, the performances of these estimators degrade severely when the estimators are used in the presence of correlated samples. In this paper performances of the three local mean power estimators namely, sample average, optimum unbiased and maximum likelihood estimators, are analysed in the presence of correlated samples. The variance of the estimators is used as performance measures. Finally, the simulation results show that the performances of the optimum unbiased and maximum likelihood estimators are very good as compared to the performance of the sample average estimator.
Multiwavelength observations of the supernova remnant G349.7+0.2 interacting with a molecular cloud

We present molecular-line observations at millimetre, centimetre and infrared wavelengths of the region containing OH(1720 MHz) masers in the supernova remnant (SNR) G349.7+0.2, using the Australia Telescope (AT) Mopra antenna, the Swedish-ESO Submillimeter Telescope, the AT Compact Array and the UNSW Infrared Fabry-Perot narrow-band filter installed on the Anglo Australian Telescope. Several molecular transitions were observed between 1.6 and 3 mm to constrain the physical parameters of the molecular cloud interacting with the SNR and to investigate the effects of the SNR shock on the gas chemistry. We detected shockexcited near-infrared H2 emission towards the centre of the SNR, revealing highly clumped molecular gas and a good correlation with published mid-infrared images from the Spitzer Space Telescope. An excellent correlation between the H2 clumps and OH(1720 MHz) maser positions supports the shock excitation of the OH(1720 MHz) maser emission. Furthermore, we detected OH absorption at 1665 and 1667 MHz which shows a good correlation with the shocked H2 emission and the masers. We found maser emission at 1665 MHz near the OH(1720 MHz) masers in this SNR, which is found to be associated with a GLIMPSE source SSTGLMC G349.7294+00.1747. We also detected 1665 and 1667 MHz OH masers, and weak 4.8 GHz H2CO absorption towards the ultra-compact H II region IRAS 17147‐3725 located to the southeast of the SNR. We found no 4.7- or 6-GHz excited-state OH masers or 6-GHz CH3OH maser towards either the SNR or the H II region.
Safety, Tolerability, and Cerebrospinal Fluid Penetration of Ursodeoxycholic Acid in Patients With Amyotrophic Lateral Sclerosis

Objective:Amyotrophic lateral sclerosis is a progressive degenerative disease, which typically leads to death in 3 to 5 years. Neuronal cell death offers a potential target for therapeutic intervention. Ursodeoxycholic acid is a cytoprotective, endogenous bile acid that has been shown to be neuroprotective in experimental Huntington and Alzheimer diseases, retinal degeneration, and ischemic and hemorrhagic stroke. The objective of this research was to study the safety and the tolerability of ursodeoxycholic acid in amyotrophic lateral sclerosis and document effective and dose-dependent cerebrospinal fluid penetration. Methods:Eighteen patients were randomly assigned to receive ursodeoxycholic acid at doses of 15, 30, and 50 mg/kg of body weight per day. Serum and cerebrospinal fluid were obtained for analysis after 4 weeks of treatment. Treatment-emergent clinical and laboratory events were monitored weekly. Results:Our data indicated that ursodeoxycholic acid is well tolerated by all subjects at all doses. We also showed that ursodeoxycholic acid is well absorbed after oral administration and crosses the blood-brain barrier in a dose-dependent manner. Conclusions:These results show excellent safety and tolerability of ursodeoxycholic acid. The drug penetrates the cerebrospinal fluid in a dose-dependent manner. A large, placebo-controlled clinical trial is needed to assess the efficacy of ursodeoxycholic acid in treating amyotrophic lateral sclerosis.
Extension and characteristics of an ECRH plasma in LHD

One of the main objectives of LHD is to extend the plasma confinement database for helical systems and to demonstrate such extended plasma confinement properties to be sustained in the steady state. Among the various plasma parameter regimes, the study of confinement properties in the collisionless regime is of particular importance. Electron cyclotron resonance heating (ECRH) has been extensively used for these confinement studies of LHD plasma from the initial operation. The system optimizations including the modification of the transmission and antenna system are performed with special emphasis on the local heating properties. As a result, a central electron temperature of more than 10 keV with an electron density of 0.6 × 1019 m−3 is achieved near the magnetic axis. The electron temperature profile is characterized by a steep gradient similar to those of an internal transport barrier observed in tokamaks and stellarators. The 168 GHz ECRH system demonstrated efficient heating at densities more than 1.0 × 1020 m−3. The continuous wave ECRH system is successfully operated to sustain a 756 s discharge.
District Magnitude and Representation of the Majority?s Preferences: Quasi-Experimental Evidence from Popular and Parliamentary Votes

Members of parliament have more effective incentives to cater for the majority? s preferences when they are elected in districts with few seats in parliament rather than in districts with many seats. We empirically investigate this hypothesis by matching voting behavior on legislative proposals of Swiss members of parliament with real referenda outcomes on the same issues for the years 1996 to 2008. This quasi-experimental data allows us to identify the impact of electoral systems through district magnitude on how members of parliament represent citizens? preferences. We find systematic, statistically significant and economically relevant evidence that members of parliament from districts with few seats vote along the majority? s preferences.