Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining Shape from Shading and Stereo: A Variational Approach for the Joint Estimation of Depth, Illumination and Albedo

Shape from shading (SfS) and stereo are two fundamentally different strategies for image-based 3-D reconstruction. While approaches for SfS infer the depth solely from pixel intensities, methods for stereo are based on a matching process that establishes correspondences across images. In this paper we propose a joint variational method that combines the advantages of both strategies. By integrating recent stereo and SfS models into a single minimisation framework, we obtain an approach that exploits shading information to improve upon the reconstruction quality of robust stereo methods. To this end, we fuse a Lambertian SfS approach with a robust stereo model and supplement the resulting energy functional with a detail-preserving anisotropic second-order smoothness term. Moreover, we extend the novel model in such a way that it jointly estimates depth, albedo and illumination. This in turn makes it applicable to objects with non-uniform albedo as well as to scenes with unknown illumination. Experiments for synthetic and real-world images show the advantages of our combined approach: While the stereo part overcomes the albedo-depth ambiguity inherent to all SfS methods, the SfS part improves the degree of details of the reconstruction compared to pure stereo methods.
Employing Internet of Things technologies for building automation

Modern Wireless Sensor Networks offer an easy, lowcost and reliable alternative to the back-end for monitoring and controlling large geographical areas like Buildings and Industries. We present the design and implementation details of an open and efficient Prototype System as a solution for low-cost BMS that comprises of heterogeneous, small-factor wireless devices. Placing that in the context of Internet of Things we come up with a solution that can cooperate with other systems installed on the same site to lower power consumption and costs as well as benefit humans that use its services in an transparent way. We evaluate and assess key aspects of the performance of our prototype. Our findings indicate specific approaches to reduce the operation costs and allow the development of open applications.
Active perception: a sensorimotor account of object categorization

We describe the results of a set of experiments in which we evolved the control system of artificial agents that are asked to categorize objects with different shapes on the basis of tactile information. Agents are provided with a 3-segments arm with 6 degrees of freedom and extremely coarse touch sensors. As we will see, despite such a limited sensory systems, evolved individuals are perfectly able to solve the problem. The analysis of the obtained results shows that evolved individuals always develop a well defined behavioral strategy that allows them to easily and robustly discriminate different objects despite the limitation of their sensory apparatus. Moreover, we discuss the general advantage of the evolutionary method for the synthesis of effective artificial agents.
Set-Point Regulation of a Robot Manipulator with Flexible Joints Using Fuzzy Control

This papers aims at designing of a set-point regulation control of a two-link planar manipulator with flexible joints considering the motor measurement only. The set-point regulation control is applied to find a feedback control law that attenuates the vibration on the joints for a desired closed-loop balance at a specific configuration. The dynamic model of the flexible manipulator with rigid links and flexible joints is derived using the Lagrange-Euler principle. The nonlinear dynamics of the robotic flexible manipulator is approximated with the help of a Takagi-Sugeno fuzzy model. The control strategy proposed in this contribution is based on the Fuzzy Takagi-Sugeno model as well as the Parallel Distributed Compensation. Simulation results show that the proposed control strategy regulates the position of the robot over a desired position within the workspace.
USP28 Is Recruited to Sites of DNA Damage by the Tandem BRCT Domains of 53BP1 but Plays a Minor Role in Double-Strand Break Metabolism

ABSTRACT The DNA damage response (DDR) is critical for genome stability and the suppression of a wide variety of human malignancies, including neurodevelopmental disorders, immunodeficiency, and cancer. In addition, the efficacy of many chemotherapeutic strategies is dictated by the status of the DDR. Ubiquitin-specific protease 28 (USP28) was reported to govern the stability of multiple factors that are critical for diverse aspects of the DDR. Here, we examined the effects of USP28 depletion on the DDR in cells and in vivo. We found that USP28 is recruited to double-strand breaks in a manner that requires the tandem BRCT domains of the DDR protein 53BP1. However, we observed only minor DDR defects in USP28-depleted cells, and mice lacking USP28 showed normal longevity, immunological development, and radiation responses. Our results thus indicate that USP28 is not a critical factor in double-strand break metabolism and is unlikely to be an attractive target for therapeutic intervention aimed at chemotherapy sensitization.
Cold periods and coronary events: an analysis of populations worldwide

Study objective: To investigate the association between cold periods and coronary events, and the extent to which climate, sex, age, and previous cardiac history increase risk during cold weather. Design: A hierarchical analyses of populations from the World Health Organisation’s MONICA project. Setting: Twenty four populations from the WHO’s MONICA project, a 21 country register made between 1980 and 1995. Patients: People aged 35–64 years who had a coronary event. Main results: Daily rates of coronary events were correlated with the average temperature over the current and previous three days. In cold periods, coronary event rates increased more in populations living in warm climates than in populations living in cold climates, where the increases were slight. The increase was greater in women than in men, especially in warm climates. On average, the odds for women having an event in the cold periods were 1.07 higher than the odds for men (95% posterior interval: 1.03 to 1.11). The effects of cold periods were similar in those with and without a history of a previous myocardial infarction. Conclusions: Rates of coronary events increased during comparatively cold periods, especially in warm climates. The smaller increases in colder climates suggest that some events in warmer climates are preventable. It is suggested that people living in warm climates, particularly women, should keep warm on cold days.
Iron and Malaria Interactions: Research Needs From Basic Science to Global Policy12

The resurgence in interest and concern regarding the potentially malign interactions between iron administration and malaria infections, especially in young children and pregnant women, has generated a research agenda that is both broad and deep. This paper highlights some of the key questions under 5 headings: basic science; clinical science and epidemiology; technological developments; country level planning; and global policy. At a time of unparalleled progress in basic science, which is illuminating the mechanisms by which iron interacts with infectious organisms, it is concluded that there are good medium-term prospects for achieving policy breakthroughs based on a secure foundation of disease-nutrient interactions. However, it is also stressed that there is much that can be done in the interim, especially in relation to health systems and implementation research that can empower systems to integrate iron interventions with programs for malaria prevention, surveillance, and treatment.
Group Cognitive Behavior Therapy Reversed Abnormal Spontaneous Brain Activity in Adult Asthmatic Patients

hours and treatment costs [3] . Furthermore, GCBT has a consistent positive effect on asthma-related quality of life and depressive symptoms [4] . However, little is known about the mechanisms that underlie these effects. With the development of neuroimaging techniques, it has become increasingly possible to observe the neurobiological underpinnings of psychotherapeutic interventions. To the best of our knowledge, GCBT-related neuroimaging studies of asthmatic patients have not yet been reported. Using functional magnetic resonance imaging (fMRI) in combination with task completion, Yoshimura et al. [5] investigated the relationship between GCBT and activity in certain brain regions in patients suffering from depression. They observed that the medial prefrontal cortex and ventral anterior cingulate cortex showed increased activity in association with positive stimuli and decreased activity in association with negative stimuli [5] . This study advances the understanding of the mechanisms by which GCBT improves depressive symptoms and further suggests that fMRI might potentially be an appropriate method to identify mechanisms of GCBT in patients with asthma. Our study sought to investigate spontaneous brain activity before and after GCBT in adult asthmatic patients with regional homogeneity (ReHo), which reflects the temporal homogeneity of the blood oxygen level-dependent (BOLD) signal. We hypothesized that abnormal brain activity associated with certain brain Bronchial asthma is a multifactorial chronic inflammatory respiratory disease that results in reversible airflow restriction. An epidemiological investigation reported that the prevalence of depression is 13.41% among Chinese asthmatic patients [1] . In addition, depressive symptoms increase the risk of adult asthma independently of health-related lifestyle factors [2] . Group cognitive behavioral therapy (GCBT) is a treatment that reduces therapist Received: August 7, 2016 Accepted after revision: November 17, 2016 Published online: May 11, 2017
Rapid Incremental Architectural Modeling From Imprecise Perspective Sketches And Geometric Constraints

We present a system for rapid reconstruction of accurate 3D models of architectural sites from freehand perspective sketches and geometric constraints that describe their spatial structure. This system is based on new approach to resolution of such constraints: they are separated from preferences — that are provided by sketches — and resolved formally in serialized manner. The reconstruction process is separated into two independent phases: first a sketch is corrected to ensure that affine and certain metric constraints would be satisfied in space and next a 3D model is elevated by resolution of only projective constraints. Usage of a geometric algebra allows to represent solutions in a simple coordinate-free form and to perform computations with any precision. The obtained formal solutions may be reused to accelerate succeeding reconstructions when the user incrementally modifies the scenes. Input of geometric constraints is simplified greatly by their automatic inference, user-validate suggestive analysis of sketch, usage of extensible set of primitives and interaction with a knowledge base. Furthermore, the system examines automatically structural and numerical consistency of imposed constraints to avoid contradictions.
A graph and hierarchical clustering based approach for population structure inference

The issue of population structure inference arises in many contexts of population genetics. However, handling the genotype data with thousands of loci in the inference process is time-consuming and the prediction accuracy is usually influenced by the noises in genotypes. In this paper, a novel approach is proposed to rapidly infer the population structures on genotype data. TagSNPs are chosen as principle features. A graph-based feature selection method is used to eliminate the invalid loci and reduce the dimensions of genotypes. Then, a hierarchical clustering algorithm combining with the information theory is employed to predict the population structures for each individual. The performance of our approach is evaluated on the simulated data. Compared with the results of STRUCTURE, it indicates that our method can get higher prediction accuracy than STRUCTURE. We also apply our feature selection results to STRUCTURE, and the experimental results show that our feature selection approach can also be used in other inference approach to reduce the running time and improve the prediction accuracy.
An improved KNN text classification algorithm based on density

Text classification has gained booming interest over the past few years. As a simple, effective and nonparametric classification method, KNN method is widely used in document classification. However, the uneven distribution in training set will affect the KNN classified result negatively. Moreover, the uneven distribution phenomenon of text is very common in documents on the Web. To tackling on this, this paper proposes an improved KNN method denoted by DBKNN. Experimental results show that the DBKNN algorithm can better serve classification requests for large sets of unevenly distributed documents.
Application of Adapted Tango as Therapeutic Intervention for Patients With Chronic Stroke

Background and Purpose:Dance has demonstrated beneficial effects on mobility in older individuals with movement disorders; yet, effects of partnered dance remain unexamined in individuals with chronic stroke. The purpose of this study was to describe the effects of adapted tango classes on balance, mobility, gait, endurance, dual-task ability, quality of life (QOL), and enjoyment in an older individual with chronic stroke and visual impairment. Case Description:D.L. was a 73-year-old African American man, 13 years poststroke with spastic hemiplegia, visual impairment, and multiple comorbidities. Intervention:D.L. attended 20 1? -hour tango classes adapted for older individuals with sensory and motor impairments over 11 weeks. Outcomes:Measures of balance, mobility, gait, endurance, dual-task ability, and QOL were evaluated before and after the intervention and at 1-month follow-up. D.L. improved on the Berg Balance Scale, 30-s chair stand, Timed Up and Go (single, manual, and cognitive conditions), 6-Minute Walk Test, and backward gait speed. Not all measures improved: balance confidence decreased, and there was no change in forward and fast gait speed or QOL, as measured by the Short Form-12 and the Visual Function Questionnaire–25. Some gains were maintained at one-month follow-up. D.L. reported enjoying the classes, noted improvement in physical well-being, and wanted to continue the program. Discussion:Thirty hours of adapted tango lessons improved balance, mobility, endurance, and dual-task ability in a participant with chronic stroke. The participant enjoyed the classes, was adherent, and wished to continue. This is the first reported use of adapted tango dance as rehabilitation for an individual with chronic stroke and low vision.
Exploiting spectral leakage for spectrogram frequency super-resolution

The spectrogram is a classical DSP tool used to view signals in both time and frequency. Unfortunately, the Heisenberg Uncertainty Principal limits our ability to use them for detecting and measuring narrowband signal modulation in wideband environments. On a spectrogram, instantaneous frequency can only be measured to the nearest bin without additional interpolation. This work presents a novel technique for extracting higher accuracy frequency estimates. Whereas most practitioners seek to suppress spectral leakage, we use mismatched windows to exploit such artifacts in order to produce super-resolved spectral displays. We present a derivation of our methodology and exhibit several interesting examples.
Study of composite vascular scaffold combining with differentiated VSMC- and VEC-like cells in vitro and in vivo

Although research into the tissue engineering of vessels has proceeded at a tremendous pace, many deficiencies still need to be resolved. A well-adopted constructed vessel requires both functional and structural properties to stimulate the native vessel and resist stress and tension in vivo. In the present study, we developed a novel three-layer composite vascular scaffold consisting of differentiated vascular smooth muscle cell-, vascular endothelial cell-like cells, and a rabbit acellular vascular matrix (ACVM)-0.25% HLC-I scaffold. HE staining, immunohistochemical assays, immunofluorescence assays (IFAs), and scanning electron microscopy were performed to monitor the growth status of cells on the scaffold material in vitro. After the vascular endothelial cell -vascular smooth muscle cell-scaffold was implanted into nude mice for three, six, and nine weeks, samples were harvested from the implanted mice and observed visually or by HE staining and IFAs for cell viability and morphology. Additionally, burst pressure resistance experiments were used to assess the maximal pressure that the engineered vessel could resist. We found that the engineered vascular endothelial cell-vascular smooth muscle cell-scaffold vessel possessed favorable biocompatibility and considerable strength, matching native vessels in vivo and in vitro, and may be significant in the future clinical implantation of tissue-engineered vasculature.
Insights Into the Molecular Mechanism for Type 2 Diabetes Susceptibility at the KCNQ1 Locus From Temporal Changes in Imprinting Status in Human Islets

The molecular basis of type 2 diabetes predisposition at most established susceptibility loci remains poorly understood. KCNQ1 maps within the 11p15.5 imprinted domain, a region with an established role in congenital growth phenotypes. Variants intronic to KCNQ1 influence diabetes susceptibility when maternally inherited. By use of quantitative PCR and pyrosequencing of human adult islet and fetal pancreas samples, we investigated the imprinting status of regional transcripts and aimed to determine whether type 2 diabetes risk alleles influence regional DNA methylation and gene expression. The results demonstrate that gene expression patterns differ by developmental stage. CDKN1C showed monoallelic expression in both adult and fetal tissue, whereas PHLDA2, SLC22A18, and SLC22A18AS were biallelically expressed in both tissues. Temporal changes in imprinting were observed for KCNQ1 and KCNQ1OT1, with monoallelic expression in fetal tissues and biallelic expression in adult samples. Genotype at the type 2 diabetes risk variant rs2237895 influenced methylation levels of regulatory sequence in fetal pancreas but without demonstrable effects on gene expression. We demonstrate that CDKN1C, KCNQ1, and KCNQ1OT1 are most likely to mediate diabetes susceptibility at the KCNQ1 locus and identify temporal differences in imprinting status and methylation effects, suggesting that diabetes risk effects may be mediated in early development.
On Black Hole Creation in Planckian Energy Scattering

In a series of papers Amati, Ciafaloni and Veneziano and ’t Hooft conjectured that black holes occur in the collision of two light particles at planckian energies. In this talk based on [10] we discuss a possible scenario for such a process by using the Chandrasekhar-Ferrari-Xanthopoulos duality between the Kerr black hole solution and colliding plane gravitational waves.
Accelerated Changes in White Matter Microstructure during Aging: A Longitudinal Diffusion Tensor Imaging Study

It is well established that human brain white matter structure changes with aging, but the timescale and spatial distribution of this change remain uncertain. Cross-sectional diffusion tensor imaging (DTI) studies indicate that, after a period of relative stability during adulthood, there is an accelerated decline in anisotropy and increase in diffusivity values during senescence; and, spatially, results have been discussed within the context of several anatomical frameworks. However, inferring trajectories of change from cross-sectional data can be challenging; and, as yet, there have been no longitudinal reports of the timescale and spatial distribution of age-related white matter change in healthy adults across the adult lifespan. In a longitudinal DTI study of 203 adults between 20 and 84 years of age, we used tract-based spatial statistics to characterize the pattern of annual change in fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity and examined whether there was an acceleration of change with age. We found extensive and overlapping significant annual decreases in fractional anisotropy, and increases in axial diffusivity, radial diffusivity, and mean diffusivity. Spatially, results were consistent with inferior-to-superior gradients of lesser-to-greater vulnerability. Annual change increased with age, particularly within superior regions, with age-related decline estimated to begin in the fifth decade. Charting white matter microstructural changes in healthy aging provides essential context to clinical studies, and future studies should compare age trajectories between healthy participants and at-risk populations and also explore the relationship between DTI rates of change and cognitive decline.
Feature Weighting for Segmentation

This paper proposes the use of feature weights to reveal the hierarchical nature of music audio. Feature weighting has been exploited in machine learning, but has not been applied to music audio segmentation. We describe both a global and a local approach to automatic feature weighting. The global approach assigns a single weighting to all features in a song. The local approach uses the local separability directly. Both approaches reveal structure that is obscured by standard features, and emphasize segments of a particular size.
Novel Signatures for Gait Analysis Using Level Sets

Gait analysis has gained prominence towards detecting suspicious activity in public area which is generally kept under surveillance. In this paper we present the results of recognizing a person based on his gait movement. Novel signatures were built through distance mapped level set contour based on boundary and skeletal information. Gait video sequence experimented upon is silhouette corresponding to 16 subjects with 50 frames per subject. Results were found to be encouraging at first level where signatures have been compared with available subjects' gait video. The robustness is tested with morphological distortions on the query image. The subject has been found to be detected with reasonable acceptance.
Genetic Parameters for Linear Type Traits and Milk, Fat, and Protein Production in Holstein Cows in Brazil

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (−0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd.