Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast and Robust Generation of Feature Maps for Region-Based Visual Attention

Visual attention is one of the important phenomena in biological vision which can be followed to achieve more efficiency, intelligence, and robustness in artificial vision systems. This paper investigates a region-based approach that performs pixel clustering prior to the processes of attention in contrast to late clustering as done by contemporary methods. The foundation steps of feature map construction for the region-based attention model are proposed here. The color contrast map is generated based upon the extended findings from the color theory, the symmetry map is constructed using a novel scanning-based method, and a new algorithm is proposed to compute a size contrast map as a formal feature channel. Eccentricity and orientation are computed using the moments of obtained regions and then saliency is evaluated using the rarity criteria. The efficient design of the proposed algorithms allows incorporating five feature channels while maintaining a processing rate of multiple frames per second. Another salient advantage over the existing techniques is the reusability of the salient regions in the high-level machine vision procedures due to preservation of their shapes and precise locations. The results indicate that the proposed model has the potential to efficiently integrate the phenomenon of attention into the main stream of machine vision and systems with restricted computing resources such as mobile robots can benefit from its advantages.
Graphite, Tubular PAHs, and the Diffuse Interstellar Bands

Planar polycyclic aromatic hydrocarbons (PAHs) are candidates for the diffuse interstellar band (DIB) carriers. Nanometer-size Fe metallic particles, expected to be present during astrophysical graphite growth, are catalytic for formation of a related species—large tubular PAH molecules. We propose that tubular PAH molecules are a component of the interstellar medium. Electronic structure calculations, on a specific family of tubular PAH molecules derived from elongated C60, reveal intense electronic transitions in the visible and near-IR, which vary systematically with length. We analyze these molecules as DIB carriers within the known constraints.
The Effect of Gradient Noise on the Energy Landscape of Deep Networks

We analyze the regularization properties of additive gradient noise in the training of deep networks by posing it as finding the ground state of the Hamiltonian of a spherical spin glass in an external magnetic field. We show that depending upon the magnitude of the magnetic field, the Hamiltonian changes dramatically from a highly non-convex energy landscape with exponentially many critical points to a regime with polynomially many critical points and finally, "trivializes"' to exactly one minimum. This phenomenon, known as topology trivialization in the physics literature, can be leveraged to devise annealing schemes for additive noise such that the training starts in the polynomial regime but gradually morphs the energy landscape into the original one as training progresses. We demonstrate through experiments on fully-connected and convolutional neural networks that annealing schemes based on trivialization lead to accelerated training and also improve generalization error.
Application of Data Mining Methods in Eluxyl Process

Eluxyl process is a simulated moving bed process. It achieves PX (paraxylene) separation from its other aromatic isomers. One year's historical data of Eluxyl process were studied, and data mining methods were introduced to extract useful operation information from them. Three main data mining procedures were discussed. Data preprocessing was discussed first. Then PCA (principal components analysis) and K-means clustering technology were introduced and applied to discover different operational conditions in different loads. Finally fuzzy classification based on associations (FCBA) algorithm was used to discover the main reasons that lead to performance fluctuations and the rules denoting the typical operations
On the Convergence of Pattern Search Algorithms

We introduce an abstract definition of pattern search methods for solving nonlinear unconstrained optimization problems. Our definition unifies an important collection of optimization methods that neither compute nor explicitly approximate derivatives. We exploit our characterization of pattern search methods to establish a global convergence theory that does not enforce a notion of sufficient decrease. Our analysis is possible because the iterates of a pattern search method lie on a scaled, translated integer lattice. This allows us to relax the classical requirements on the acceptance of the step, at the expense of stronger conditions on the form of the step, and still guarantee global convergence.
Comparative Study of the Effects of a 1-Year Dietary Intervention of a Low-Carbohydrate Diet Versus a Low-Fat Diet on Weight and Glycemic Control in Type 2 Diabetes

OBJECTIVE To compare the effects of a 1-year intervention with a low-carbohydrate and a low-fat diet on weight loss and glycemic control in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS This study is a randomized clinical trial of 105 overweight adults with type 2 diabetes. Primary outcomes were weight and A1C. Secondary outcomes included blood pressure and lipids. Outcome measures were obtained at 3, 6, and 12 months. RESULTS The greatest reduction in weight and A1C occurred within the first 3 months. Weight loss occurred faster in the low-carbohydrate group than in the low-fat group (P = 0.005), but at 1 year a similar 3.4% weight reduction was seen in both dietary groups. There was no significant change in A1C in either group at 1 year. There was no change in blood pressure, but a greater increase in HDL was observed in the low-carbohydrate group (P = 0.002). CONCLUSIONS Among patients with type 2 diabetes, after 1 year a low-carbohydrate diet had effects on weight and A1C similar to those seen with a low-fat diet. There was no significant effect on blood pressure, but the low-carbohydrate diet produced a greater increase in HDL cholesterol.
Adaptive detectors for MIMO radar with sidelobe signal rejection capabilities

Antenna beam patterns in MIMO radar systems (as in any radar system) exhibit sidelobes. Naturally it is possible for clutter and other undesirable signals to be detected accidently through these sidelobes. In a MIMO radar system this has the effect of misaligning the mainbeam steering vector and consequently reducing detection performance. In this paper we develop and examine two adaptive processing schemes aimed at reducing unwanted signals entering the system through sidelobes and hence restoring the steering vector to its true position. In this way signal to noise and detection performance are also largely restored. The MIMO version of an adaptive beamformer orthogonal rejection test (MIMO-ABORT) method together an adaptive detector with conic rejection (MIMO-ACR) are developed, that exploit the generalized likelihood ratio principle. Subsequently the Constant False Alarm Rate (CFAR) properties of the two proposed detectors are demonstrated. The performance of the MIMO-ABORT and the MIMO-ACR detectors are numerically evaluated. The results show that the two detectors can reject sidelobe signals with good performance at the cost of a slight reduction in mainlobe signal detection performance, as compared with MIMO version of Kelly's GLRT (MIMO-GLRT).
Mechanism Analysis and Modelling of Passengers' Travel Choice

Using questionnaire Survey data, this paper employed the model of structural similarity coefficient to analyze the transportation choice mechanism of passengers, and then take air passengers as an example, established the factors affecting model of passengers' travel choice based on ordinal-logit technique. The research shows that price, time, comfort and freedom are the four basic factors for passenger travel alternatives. According to passenger's similar decisionmaking mechanism of supply and demand, passengers select transportations on the basis of the similarity coefficient between passenger demand structure and traffic supply structure. Age and gender is passenger's physical attributes, but their impact on passenger travel choice willingness is not significant, Education and income level have significant positively impact, especially the income levels. In terms of "time value", the influence of education level and income levels also reached significant level. In addition to age, other factors have significant impact on proportion and frequency by plane.
A comparison of finite element and atomistic modelling of fracture

Are the cohesive laws of interfaces sufficient for modelling fracture in polycrystals using the cohesive zone model? We examine this question by comparing a fully atomistic simulation of a silicon polycrystal with a finite element simulation with a similar overall geometry. The cohesive laws used in the finite element simulation are measured atomistically. We describe in detail how to convert the output of atomistic grain boundary fracture simulations into the piecewise linear form needed by a cohesive zone model. We discuss the effects of grain boundary microparameters (the choice of section of the interface, the translations of the grains relative to one another and the cutting plane of each lattice orientation) on the cohesive laws and polycrystal fracture. We find that the atomistic simulations fracture at lower levels of external stress, indicating that the initiation of fracture in the atomistic simulations is likely dominated by irregular atomic structures at external faces, internal edges, corners and junctions of grains. Thus, the cohesive properties of interfaces alone are not likely to be sufficient for modelling the fracture of polycrystals using continuum methods.
Acute partial transverse myelitis: risk factors for conversion to multiple sclerosis

Acute partial transverse myelitis (APTM) may be the first clinical manifestation of multiple sclerosis (MS), of relapsing myelitis, or remain a monophasic event. Identification of risk factors associated with relapse or conversion to MS is important, as prognostic information might help to guide management. The objective of this study was to define clinical, laboratory and neuroimaging factors in patients with first‐ever APTM that predict relapses or conversion to MS. We identified 73 patients with a first‐ever APTM admitted to our institution from January 1999 to June 2005. The follow‐up time ranged from 12 to 90 months (mean follow‐up 46 months). Patient demographics, clinical impairment at onset and after 3 months, ancillary tests including cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), evoked potentials, recurrent and new symptoms and signs during follow‐up were analysed. APTM remained a monophasic event in 35 patients (47.9%), conversion to MS occurred in 32 (43.8%) and recurred as relapsing myelitis in six patients (8.2%). According to univariate analysis, a family history of MS (P = 0.02), higher expanded disability status scale (EDSS) at onset (P = 0.03) and lesions on brain MRI (P = 0.03) were predictive factors for conversion to MS. CSF‐specific oligoclonal bands (P = 0.04) or abnormal IgG‐index (P = 0.04) were associated with increased risk for MS as well. In patients with a first‐ever APTM, a family history of MS, high EDSS at presentation, lesions on brain MRI, CSF‐specific oligoclonal bands or abnormal IgG‐index may indicate an increased risk for conversion to MS.
reveals dual regulatory roles of YY 1 Analysis of overrepresented motifs in human core promoters data

data Supplementary http://www.genome. org/cgi/content/full/17/6/798/DC1 "Supplemental Reseach Data" References http://www.genome. org/cgi/content/full/17/6/798#otherarticles Article cited in: http://www.genome. org/cgi/content/full/17/6/798#References This article cites 35 articles, 21 of which can be accessed free at: Open Access Freely available online through the Genome Research Open Access option. service Email alerting click here top right corner of the article or Receive free email alerts when new articles cite this article sign up in the box at the Notes
Modelling of directional data using Kent distributions

The modelling of data on a spherical surface requires the consideration of directional probability distributions. To model asymmetrically distributed data on a three-dimensional sphere, Kent distributions are often used. The moment estimates of the parameters are typically used in modelling tasks involving Kent distributions. However, these lack a rigorous statistical treatment. The focus of the paper is to introduce a Bayesian estimation of the parameters of the Kent distribution which has not been carried out in the literature, partly because of its complex mathematical form. We employ the Bayesian information-theoretic paradigm of Minimum Message Length (MML) to bridge this gap and derive reliable estimators. The inferred parameters are subsequently used in mixture modelling of Kent distributions. The problem of inferring the suitable number of mixture components is also addressed using the MML criterion. We demonstrate the superior performance of the derived MML-based parameter estimates against the traditional estimators. We apply the MML principle to infer mixtures of Kent distributions to model empirical data corresponding to protein conformations. We demonstrate the effectiveness of Kent models to act as improved descriptors of protein structural data as compared to commonly used von Mises-Fisher distributions.
Degradation of barnacle nauplii: implications to chitin regulation in the marine environment

The exoskeleton of most invertebrate larval forms is made of chitin, which is a linear polysaccharide of β (1→4)-linked N-acetylglucosamine (GlcNAc) residues. These larval forms offer extensive body surface for bacterial attachment and colonization. In nature, degradation of chitin involves a cascade of processes brought about by chitinases produced by specific bacteria in the marine environment. Microbial decomposition of larval carcasses serves as an alternate mechanism for nutrient regeneration, elemental cycling and microbial production. The present study was undertaken to assess the influence of chitinase enzyme on the degradation of the nauplii of barnacle, Balanus amphitrite. The survival and abundance of bacteria during the degradation process under different experimental conditions was monitored. To the best of our knowledge, no such study is conducted to understand the degradation of larval exoskeleton using chitinase and its influence on bacteria. An increase in the chitinase activity with increase in temperature was observed. Scanning electron micrographs of chitinase treated nauplii showed scars on the surface of the barnacle nauplii initially and further disruption of the exoskeleton was observed with the increase in the treatment time. Bacterial abundance of the chitinase treated nauplii increased with the increase in enzyme concentration. Pathogenic bacteria such as Vibrio cholerae, V. alginolyticus, V. parahaemolyticus which were initially associated with the exoskeleton were absent after chitinase treatment, however, Bacillus spp. dominated subsequent to chitinase treatment and this might have important implications to marine ecosystem functioning.
Association between troponin T and ICU mortality, a changing trend

Background Initially elevated levels of troponin predict adverse outcomes in patients admitted to the intensive care unit (ICU). No research team has investigated the changes in concentration of cardiac troponin T (cTnT) during ICU stay and their association with patient outcome. Objective We investigated whether the change in cTnT levels during ICU stay could predict outcomes (death or survival). Methods In this cohort study, all patients admitted to the medical ICU (10 beds) from January to July 2008 were enrolled. Troponin levels were evaluated within the first 24 hours of ICU admission and on the fourth, seventh and 10th days after admission. Results The study population (135 patients) had a mean age of 60.9 ± 21.5 years. The outcome was significantly different with regard to normal or elevated cTnT concentrations on the first and seventh days of follow up (p = 0.03 and 0.023, respectively). This difference was non-significant for cTnT levels on the fourth and 10th days after admission (p = 0.69 and 0.78, respectively). The change in cTnT levels was not significantly different between the deceased and discharged patients (p = 0.4). Conclusion Changes in cTnT levels during ICU stay did not show a significant trend (power: 0.26). Patients whose cTnT levels were increased on the first and seventh days of ICU stay had a worse survival, which could be associated with cardiac events on admission or at specific times during the stay in ICU.
AUTOMATIC BUILDING EXTRACTION FROM HIGH RESOLUTION STEREO SATELLITE IMAGES

An approach was developed for automatic building extraction from high resolution stereo satellite images. The approach utilizes the spectral properties of the pan-sharpened multispectral bands and the elevation model generated from the stereo panchromatic bands. First, the pan-sharpened multispectral bands are classified using the Maximum Likelihood Classifier (MLC) to separate the buildings from other classes. Next, the Normalized Digital Surface Model (nDSM) is calculated by subtracting Digital Terrain Model (DTM) from Digital Surface Model (DSM). Those areas of nDSM that fall above the user defined threshold are considered to represent the 3D objects. To separate the buildings from the trees, a Normalized Difference Vegetation Index (NDVI) is used. The areas considered to be the buildings on both the classified image and the nDSM are overlaid and the union areas are accepted to represent the candidate building patches. The further processing operations are then carried out using these candidate building patches only. Next, the candidate building patches are applied a Canny edge detector and the detected edges are vectorized using a boundary tracing algorithm, which provides the general boundaries of the buildings. However, the vector boundaries may contain undulations. To remove the undulations therefore, the Douglas Peucker algorithm is used and the topological errors are removed using the vector filters. The approach was implemented in an urban area of Batıkent, Ankara, Turkey using the IKONOS PSM and stereo PAN images. The DTM was generated using the existing 1:1 000-scale digital vector map. The DSM was generated from stereo PAN images and the classification was performed using the PSM bands. The approach was tested using ten urban blocks each containing different types and shapes of buildings. The results show that the proposed approach appears to be quite satisfactory for extracting the buildings with the 80.7 percent detection rate and 72 percent quality rate. The rate of incorrectly labeled building areas was computed to be 0.15, while the rate of missed building areas was found to be 0.24.
Object-Oriented Programming: Themes and Variations

Many of the ideas behind object-oriented programming have roots going back to SIMULA. The first substantial interactive, display-based implementation was the SMALLTALK language. The object-oriented style has often been advocated for simulation programs, systems programming, graphics, and AI programming. The history of ideas has some additional threads including work on message passing as in ACTORS, and multiple inheritance as in FLAVORS. It is also related to a line of work in AI on the theory of frames and their implementation in knowledge representation languages such as KRL, KEE, FRL, and UNITS.
Controlling Cell Functions and Fate with Surfaces and Hydrogels: The Role of Material Features in Cell Adhesion and Signal Transduction

In their natural environment, cells are constantly exposed to a cohort of biochemical and biophysical signals that govern their functions and fate. Therefore, materials for biomedical applications, either in vivo or in vitro, should provide a replica of the complex patterns of biological signals. Thus, the development of a novel class of biomaterials requires, on the one side, the understanding of the dynamic interactions occurring at the interface of cells and materials; on the other, it requires the development of technologies able to integrate multiple signals precisely organized in time and space. A large body of studies aimed at investigating the mechanisms underpinning cell-material interactions is mostly based on 2D systems. While these have been instrumental in shaping our understanding of the recognition of and reaction to material stimuli, they lack the ability to capture central features of the natural cellular environment, such as dimensionality, remodelling and degradability. In this work, we review the fundamental traits of material signal sensing and cell response. We then present relevant technologies and materials that enable fabricating systems able to control various aspects of cell behavior, and we highlight potential differences that arise from 2D and 3D settings.
Metropolitan Fixed Assets Change Judgment using Aerial Photographs

The Tokyo Metropolitan Government is the largest municipality in Japan and conducts building change identification work. Recently, Tokyo terminated its traditional visual identification work that has been in use for 20 years and shifted to a new automated system. This paper is intended to introduce the Fixed Assets Change Judgment (FACJ) system and its core tool, RealScape. RealScape automatically detects the changes in the height and color of buildings based on three-dimensional (3D) analysis of aerial photographs. It employs a unique pixel-by-pixel stereo processing method and enables the foot-level precision for each building. RealScape detects building changes more accurately than visual judgment operations by humans and reduces the labor costs to one third of the traditional approach and the required judgment duration to about two weeks per 100km 2 .
Robust Patch-Based Pedestrian Tracking Using Monocular Calibrated Cameras

Although several methods for pedestrian tracking can be found in the literature, robustly tracking a person in unconstrained environments is an open and active research problem. In this paper, we propose a method that represents each pedestrian as a set of multiple fragments, aiming robustness with respect to occlusions. These patches are tracked individually and their translation vectors are combined robustly in the world coordinate frame using Weighted Vector Median Filters (WVMF). Additionally, the algorithm uses the camera parameters to both estimate the person scale in a straightforward manner and to limit the search region used to track each fragment. Experiments carried out using two publicly available datasets (PETS and Town Centre) are presented, and they indicate that the proposed method is robust to partial occlusions and large scale changes. According to our experiments, the proposed approach outperforms, regarding the quality of localization, some of the methods in the current state of the art.