Miracle-dz/UniFAR-FTUs huggingface dataset:
AFFINE REGISTRATION USING MULTISCALE APPROACH

This paper introduces a multiscale framework for affine registration of image intensity functions. The idea in the introduced approach is to extend the given pattern to a set of affine covariant versions, each carrying slightly different information, and then to extract features for registration from each of them separately. The proposed approach is demonstrated by constructing several new affine registration methods by using different preprocessing techniques and combination schemes. The achieved registration methods are finally illustrated in two registration experiments involving real and synthetic images.
Comparison of Decision-Making Strategies for Self-Optimization in Autonomic Computing Systems

Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This article proposes a comparison of some state of the art approaches for decision making, applied to a self-optimizing autonomic system that allocates resources to a software application. A variety of decision mechanisms, from heuristics to control-theory and machine learning, are investigated. The results obtained with these solutions are compared by means of case studies using standard benchmarks. Our results indicate that the most suitable decision mechanism can vary depending on the specific test case but adaptive and model predictive control systems tend to produce good performance and may work best in a priori unknown situations.
THEORETICAL STUDY OF TIME-RESOLVED FLUORESCENCE ANISOTROPY FROM COUPLED CHROMOPHORE PAIRS

Calculations of time-resolved fluorescence anisotropy from a pair of chromophores coupled by an excitation transfer interaction are presented. For the purpose of investigating the effects of nuclear motion on the energy transfer and anisotropy, an illustrative model is developed that provides each chromophore with a single intramolecular vibrational mode. Account is taken of non-instantaneous excitation and timeand frequency-resolved detection. Effects of excitation pulse duration, detection window duration and frequency resolution, and excitation transfer coupling strength on the time-resolved anisotropy are examined in detail. Effects of vibrational relaxation and dephasing are also examined using a simplified Redfield description of the effects of coupling to a thermal bath. †Present Address: Department of Chemistry, University of Rhode Island, Kingston, Rhode Island 02881
The public's probabilistic numeracy: How tasks, education and exposure to games of chance shape it

As we navigate a world full of uncertainties and risks, dominated by statistics, we need to be able to think statistically. Very few studies investigating people’s ability to understand simple concepts and rules from probability theory have drawn representative samples from the public. For this reason we investigated a representative sample of 1000 Swiss citizens, using six probabilistic problems. Most reasoned appropriately in problems representing pure applications of probability theory, but failed to do so in approximations of real-world scenarios – a disparity we replicated in a sample of first-year psychology students. Additionally, education is associated with probabilistic numeracy in the former but not the latter type of problems. We discuss possible reasons for these task disparities and suggest that gaining a comprehensive picture of citizens’ probabilistic competence and its determinants requires using both types of tasks. Copyright # 2008 John Wiley & Sons, Ltd.
Scatter search for the profile minimization problem

We study the problem of minimizing the profile of a graph and develop a solution method by following the tenets of scatter search. Our procedure exploits the network structure of the problem and includes strategies that produce a computationally efficient and agile search. Among several mechanisms, our search includes path relinking as the basis for combining solutions to generate new ones. The profile minimization problem (PMP) is NP‐Hard and has relevant applications in numerical analysis techniques that rely on manipulating large sparse matrices. The problem was proposed in the early 1970s but the state‐of‐the‐art does not include a method that could be considered powerful by today's computing standards. Extensive computational experiments show that we have accomplished our goal of pushing the envelope and establishing a new standard in the solution of the PMP. © 2014 Wiley Periodicals, Inc. NETWORKS, Vol. 65(1), 10–21. 2015
Situation Awareness in Automated Vehicles through Proximal Peripheral Light Signals

With the rise of automated vehicles, car drivers will be given the opportunity to perform other tasks or activities than controlling the vehicle. However, in a car that is not entirely automated, a human driver might need to manually take over control at some point. When such a situation occurs, awareness of the traffic situation is considered essential. In this study, we evaluate a design that aims to enable the driver of an automated car to perform a task (other than driving) while still gaining situation awareness through peripheral light signals. The results show that proximal peripheral light signals can increase the situation awareness of a driver while performing an alternative task or activity.
The PPM poisson channel: Finite-length bounds and code design

This work investigates the finite-length block error probability for the pulse position modulation (PPM) Poisson channel. Amongst, expressions for the Gallager random coding bound (RCB) and the Gaussian approximation of the converse theorem are derived. Likewise, we introduce an erasure channel (EC) approximation that allows the application of known EC bounds to the PPM Poisson channel by matching the channel capacities. We show that the derived benchmarks are not only simple to compute, but also accurate. Additionally, the design of protograph-based non-binary low-density parity-check (LDPC) codes for the (PPM) Poisson channel is addressed. The order q of the finite field is directly matched to the PPM order, so that no iterative message exchange between the decoder and the demodulator is required. The suggested design turns out to be robust w.r. t. different channel parameters, yielding performances within 0.5 dB from the theoretical benchmarks.
Systematic coarse-graining of nanoparticle interactions in molecular dynamics simulation.

A recently developed multiscale coarse-graining procedure [Izvekov, S. ; Voth, G. A. J. Phys. Chem. B 2005, 109, 2469] is extended to derive coarse-grained models for nanoparticles. The methodology is applied to C(60) and to carbonaceous nanoparticles produced in combustion environments. The coarse-graining of the interparticle force field is accomplished applying a force-matching procedure to data obtained from trajectories and forces from all-atom MD simulations. The CG models are shown to reproduce accurately the structural properties of the nanoparticle systems studied, while allowing for MD simulations of much larger self-assembled nanoparticle systems.
Four New Path Following Controllers for Rhombic Like Vehicles

This paper addresses the path following problem of a wheeled mobile robot with rhombic like kinematics (two drivable and steerable wheels) operating in cluttered environments. Four new path following controllers are developed to steer the kinematic model of a rhombic like vehicle along a desired path: three are based on feedback laws derived at a kinematic level with geometrical inspiration; while the fourth is a nonlinear controller, built upon a kinematic model of the vehicle using Lyapunov functions. By fully exploiting the kinematic capabilities of this type of vehicles, all the developed controllers are capable of performing under two situations: when both wheels follow the same path, or when each wheel follows a different path. Simulated and experimental results are presented in the paper to illustrate the performance of the controllers. The main conclusions of these controllers are summarized, leading to a possible application in the vehicles that will operate in the remote handling missions of the International Thermonuclear Experimental Reactor (ITER).
SiGe-On-Insulator (SGOI): Two Structures for CMOS Application

Two SiGe-on-insulator (SGOI) structures for CMOS application are presented: surface-channel strained-Si on SGOI (SSOI) and dual-channel SGOI structures. Comparisons between two structures are made from both device performance and CMOS process point of view. We have demonstrated both structures on SGOI, and have fabricated n-MOSFET’s and pMOSFET’s on those two structures respectively. Device characteristics are presented. The devices show enhancement on both electron and hole mobilities.
On local representation of distances in trees

We consider distributed representation scheme for trees, supporting some special relationships between nodes at small distance. For instance, we show that for a tree <i>T</i> and an integer <i>k</i> we can assign local information on nodes such that we can decide for two nodes <i>u</i> and <i>v</i> if the distance between <i>u</i> and <i>v</i> is at most <i>k</i> and if so, compute it only using the local information assigned. For trees withn nodes, the local information assigned by our scheme is binary label of log <i>n</i> + <i>O</i>(<i>k</i>log(<i>k</i>log(<i>n</i>/<i>k</i>))) bits, improving a recent result of Alstrup, Bille and Rauhe.
SOCS2 correlates with malignancy and exerts growth-promoting effects in prostate cancer

Deregulation of cytokine and growth factor signaling due to an altered expression of endogenous regulators is well recognized in prostate cancer (PCa) and other cancers. Suppressor of cytokine signaling 2 (SOCS2) is a key regulator of the GH, IGF, and prolactin signaling pathways that have been implicated in carcinogenesis. In this study, we evaluated the expression patterns and functional significance of SOCS2 in PCa. Protein expression analysis employing tissue microarrays from two independent patient cohorts revealed a significantly enhanced expression in tumor tissue compared with benign tissue as well as association with Gleason score and disease progression. In vitro and in vivo assays uncovered the involvement of SOCS2 in the regulation of cell growth and apoptosis. Functionally, SOCS2 knockdown inhibited PCa cell proliferation and xenograft growth in a CAM assay. Decreased cell growth after SOCS2 downregulation was associated with cell-cycle arrest and apoptosis. In addition, we proved that SOCS2 expression is significantly elevated upon androgenic stimulation in androgen receptor (AR)-positive cell lines, providing a possible mechanistic explanation for high SOCS2 levels in PCa tissue. Consequently, SOCS2 expression correlated with AR expression in the malignant tissue of patients. On the whole, our study linked increased SOCS2 expression in PCa with a pro-proliferative role in vitro and in vivo.
WOOD MACHINING PROPERTIES OF AUSTRALIAN PLANTATION-GROWN EUCALYPTS

This study assessed the moulding, drilling, turning, sanding, and routing properties of seven plantation-grown hardwood species from southeast Australia to evaluate their potential as a resource for the manufacture of high quality furniture and furnishings. Eucalyptus grandis, Eucalyptus saligna, Corymbia maculata, Eucalyptus camaldulensis, Eucalyptus sideroxylon, Eucalyptus cladocalyx, and Eucalyptus globulus were machined using different tools, and the surface quality obtained was visually graded. A sanding sequence of 100-150 grit produced satisfactory surfaces for furniture manufacturing for most studied species. Usually, a feeding direction against the rotational direction of the tool showed best results and reduced incidence of corner breakout when routing. Overall, high-density plantationgrown Australian hardwood species performed well during machining trials with the use of appropriate parameters and cutting tools allowing overcoming some typical processing difficulties for some species. The data obtained within this study will allow optimising the machining process of plantation-grown wood in Australia and increase value from the current plantation resource.
Iterative Bregman Projections for Regularized Transportation Problems

This article details a general numerical framework to approximate so-lutions to linear programs related to optimal transport. The general idea is to introduce an entropic regularization of the initial linear program. This regularized problem corresponds to a Kullback-Leibler Bregman di-vergence projection of a vector (representing some initial joint distribu-tion) on the polytope of constraints. We show that for many problems related to optimal transport, the set of linear constraints can be split in an intersection of a few simple constraints, for which the projections can be computed in closed form. This allows us to make use of iterative Bregman projections (when there are only equality constraints) or more generally Bregman-Dykstra iterations (when inequality constraints are in-volved). We illustrate the usefulness of this approach to several variational problems related to optimal transport: barycenters for the optimal trans-port metric, tomographic reconstruction, multi-marginal optimal trans-port and in particular its application to Brenier's relaxed solutions of in-compressible Euler equations, partial un-balanced optimal transport and optimal transport with capacity constraints.
Term relevance dependency model for text classification

Text classification (TC) has long been an important research topic in information retrieval (IR) related areas. Conventional language model (LM)-based TC is solely based on matching the words in the documents and classes by using a naïve Bayes classifier (NBC). In the literature, both the term association model (TA), which further considers word-to-word information, and the relevance model (RM), which further considers word-to-document information, have been shown to outperform a simple LM for IR. In this paper, we study a novel integration of TA with RM for LM-NBC-based TC. The new model is called the term relevance dependency model. In the model, the probability of a word given a class is represented by a term association LM probability learned by a RM framework. The results of TC experiments on the 20newsgroups and Reuters-21578 corpora demonstrate that the new model outperforms the standard NBC and several other LM-NBC-based methods.
Segmenting Time Ser ies for Weather Forecasting

We are investigating techniques for producing textual summaries of time series data. Deep reasoning techniques have proven impractical because we lack perfect knowledge about users and their tasks. Data analysis techniques such as segmentation are more attractive, but they have been developed for data mining, not for communication. We examine how segmentation should be modified to make it suitable for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system.
Proteomic profiling of expression of proteasomal subunits from livers of mice treated with diethylnitrosamine

The liver plays a central role in transforming and clearing chemicals and is susceptible to the toxicity from these agents. Diethylnitrosamine is metabolized primarily in the liver by cytochrome P‐450 and can cause DNA damage. The 26S proteasome is a large proteolytic complex that degrades ubiquitinated proteins, and regulates many physiological processes. We used proteomics‐based approaches to examine expressional differences of liver proteasomal subunits from diethylnitrosamine‐treated mice. The expression of most proteasomal subunits was observed to be upregulated in the analysis of 2DE and MALDI‐TOF MS/MS. Some of these differentially expressed proteasomal subunits were further confirmed by Western blot, RT‐PCR, and immunohistochemistry. Our results provided useful information on the relationship between the proteasomal complex and related diseases.
Self-Awareness of Deficits following Acquired Brain Injury: Considerations for Rehabilitation

Limitations in self-awareness of deficits after acquired brain injury can hamper client participation in rehabilitation programmes. The concept of self-awareness encompasses awareness of brain injury related deficits, an appreciation of the functional consequences of deficits, and the ability to translate that information into realistic goals. A literature review suggests that the development of self-awareness can be associated with emotional distress in the individual. Self-awareness and emotional adjustment factors may both affect behavioural change in the individual, which may influence outcome. The widely held belief that self-awareness is necessary for successful outcomes from rehabilitation requires further investigation.
PIMM: Packet Interval-Based Power Modeling of Multiple Network Interface-Activated Smartphones

State-of-the-art smartphones can utilize multiple network interfaces simultaneously, e.g., WiFi and LTE, to enhance the throughput and network connectivity in various use cases. In this paper, we present an accurate power modeling for the smartphones, especially, those capable of activating/utilizing multiple networks simultaneously. All kinds of traffic patterns are accurately converted into the estimated power consumption using our proposed algorithm by incorporating the variation of packet interval, packet length, and WiFi/LTE channel quality on a per-packet basis. The accuracy of our model is comparatively evaluated by comparing the estimated power with the measured power in various scenarios. We find that our model reduces estimation error by 7%-35% even for single network transmissions, and by 25% for multiple network transmissions compared with existing power models.
Cardiac lesions and initial laboratory data in Kawasaki disease: a nationwide survey in Japan.

BACKGROUND Cardiac lesions, such as coronary dilatation, aneurysms, narrowing, myocardial infarction, and valvular lesions, sometimes occur in Kawasaki disease, but most studies have only evaluated cardiac lesions in the later phase of the disease. This study was undertaken to clarify the related factors between cardiac lesions and laboratory data in the initial phase of Kawasaki disease. METHODS We conducted a cross-sectional study using data for 26 691 patients from the 22nd nationwide survey of Kawasaki disease in Japan, the observation period of which was from January 2011 through December 2012. We excluded patients with recurrent Kawasaki disease and who were more than seven days from the start of symptoms at admission. We analyzed 23 155 cases (13 353 boys; mean age: 923 ± 734 days) with available laboratory data for white blood cell count, platelet count, serum albumin, and C-reactive protein (CRP). RESULTS Cardiac lesions were detected in 984 cases (656 boys and 328 girls); lesions were classified as coronary dilatation (764 cases), coronary aneurysm (40), giant coronary aneurysm (6), coronary narrowing (3), and valvular lesions (204). The significant related factors of initial coronary dilatation were male sex (odds ratio [OR] 1.73), older age (OR per 100 days increase 1.03), higher platelet count (OR per 10 000 cells/µL increase 1.006), lower albumin (OR per 1 g/dL increase 0.66), and higher CRP (OR per 1 mg/dL increase 1.02). The factors related to coronary aneurysm were higher platelet count (OR 1.01) and lower albumin (OR 0.34). No factors were significantly related to giant coronary aneurysm. The related factors of valvular lesions were age (OR 0.98), and higher CRP (OR 1.05). CONCLUSIONS Clinicians should consider male sex, older age, higher platelet count, lower albumin levels, and higher CRP levels when assessing risk of cardiac lesions in the initial phase of Kawasaki disease.
Dorsal and lateral fates in the mouse neural tube require the cell-autonomous activity of the open brain gene.

The processes that specify early regional identity in dorsal and lateral regions of the mammalian neural tube are not well understood. The mouse open brain (opb) gene plays an essential role in dorsal neural patterning: in the caudal spinal cord of opb mutants, dorsal cell types are absent and markers of ventral fates, including Shh, expand into dorsal regions. Analysis of the opb mutant phenotype and of opb/opb <--> wild-type chimeric embryos reveals that early in neural development, the wild-type opb gene (opb(+)) is required cell autonomously for the expression of Pax7 in dorsal cells and Pax6 in lateral cells. Thus the opb(+) gene product acts intracellularly in the reception or interpretation of signals that determine cell types in the dorsal 80% of the neural tube. At later stages, the lack of opb(+) causes a non-cell-autonomous expansion of ventral cell types into dorsal regions of the neural tube, revealing that opb(+) controls the production of a diffusible molecule that defines the domain of Shh expression. The data indicate that opb(+) could act as either a novel component of a dorsalizing pathway or a novel intracellular negative regulator of the Shh signal transduction pathway.
Optimized large vocabulary WFST speech recognition system

Speech recognition decoder is an important part of large vocabulary speech recognition application. The speed and the accuracy is the main concern of its application. Recently, weighted finite state transducers (WFST) has become the dominant description of decoding network. However, the large memory and time cost of constructing the final WFST decoding network is the bottleneck of this technique. The goal of this article is to construct a tight, flexible WFST decoding network as well as a fast, scalable decoder. A tight representation of silence in speech is proposed and the decoding algorithm with improved pruning strategies is also suggested. The experimental results show that the proposed network presentation will cut off 37% memory cost and 19% time cost of constructing the final decoding network. And with the decoding strategies of WFST feature specified beams the proposed decoder's efficiency and accuracy are also significantly improved.
Modeling and Simulation of Ethyl Acetate Reactive Distillation Column Using Aspen Plus

software. Reactive distillation is a process where simultaneous chemical reaction and vapour-liquid phase separation take place. This represents an exciting alternative to traditional liquid phase chemical reaction processing. In reactive distillation, separation of products from unconverted reactants allows for greater conversion, because product removal displaces equilibrium and forces the reaction towards completion. The combination of reaction and distillation helps in achieving products of higher purity and higher conversion of reactants as compared to old conventional processes. Both reaction and distillation acting simultaneously offers certain advantages that c an’t be achieved by conventional processing. The Aspen Plus TM simulator was used and RADFRAC model was used in Aspen Plus TM which is meant for the reactive distillation simulation. Reactive distillation is also important from the economic point of view as it involves chemical reaction and distillation in the same unit and hence it is preffered over the old conventional processes which involve chemical reaction and distillation separately.