Miracle-dz/UniFAR-FTUs huggingface dataset:
Do Clouds Save the Great Barrier Reef? Satellite Imagery Elucidates the Cloud-SST Relationship at the Local Scale

Evidence of global climate change and rising sea surface temperatures (SSTs) is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an “ocean thermostat” and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR) shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006) and two relatively cool summers (2007 and 2008). Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005) and La Niña (2008) study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs.
New VLA observations of the SNR Puppis A: the radio properties and the correlation with the X-ray emission

Context. High-resolution, high-sensitivity multifrequency radio images of supernova remnants (SNRs) are essential in advancing the understanding of both the global SNR dynamics and particle acceleration mechanisms. Aims. In this paper we report on a new study of the SNR Puppis A based on VLA observations at 1425 MHz; the improvement represents a factor of two in angular resolution and almost ten times in sensitivity compared to the best previous image of Puppis A. This new image is used to compare with re-processed 327 MHz data and ROSAT and Chandra images to investigate morphological and spectral characteristics. Methods. The observations were carried out with the VLA in the DnC and CnB configurations in 2004. After combining with singledish data from Parkes, an angular resolution of 34 �� × 16 �� and an rms noise of 0.5 mJy beam −1 , were achieved. Archival VLA data at 327 MHz were also processed. The spectral index distribution was then determined by a direct comparison of the homogenized data at both 327 and 1425 MHz. In addition, to identify different spectral components, tomographic spectral analysis was performed. Results. The new 1425 MHz radio image reveals a highly structured border encircling a diffuse, featureless interior. In particular, the northern half of Puppis A displays a complex structure along the periphery, consisting of short arcs resembling “wave-like” features. These are oriented essentially perpendicular to the shock front on the NE side, but are tangential to the shock on the NW side. A remarkable correspondence between such “wave-like” features and spectral changes is observed. On the other hand, the brightest radio features (located to the E of the SNR and also detected in X-rays) have no counterpart in the spectral index distribution. Based on a uniform compilation of integrated flux densities between 19 and 8400 MHz, a global spectral index α = −0.52± 0.03 (S ∝ ν α )h as been determined. The new 1425 MHz image of Puppis A was compared with the ROSAT X-ray image of the entire SNR and with the resolved arcsec Chandra image of the bright E region. There is good overall agreement between the radio and high resolution X-ray images. At the arcsec level, however, the agreement of the radio and X-ray images is less striking. A noticeable similarity is found between Puppis A, with its E and W extensions, and analogous morphological features observed in the SNR W50. This suggests that Puppis A could be another case of a SNR shaped by the action of energetic jets.
Skull and fontanel segmentation from neonatal CT data by model based variational level set using localized coefficient

Neonatal skull is different from adults' skull. It is composed of ossified parts of flat bone and fontanels. Fontanels are fibrous membranes that at this stage of development connect the already ossified flat bones of the cranium. Since these two different tissue types have different electrical conductivities, it is important to model the geometry of the fontanels if one aims to solve the inverse problem as e.g. for source localization. In neonatal Computer Tomography (CT) images fontanels are identifiable as gaps between the bones forming the cranium. In this paper we propose an automatic method based on a level set algorithm with shape prior to segment skull and fontanels from neonatal CT images. Quantitative evaluation based on similarity between automatically and manually segmented skulls and fontanels using ten subjects show that the proposed method can appropriately segment skull and fontanels.
Using co-visitation networks for detecting large scale online display advertising exchange fraud

Data generated by observing the actions of web browsers across the internet is being used at an ever increasing rate for both building models and making decisions. In fact, a quarter of the industry-track papers for KDD in 2012 were based on data generated by online actions. The models, analytics and decisions they inform all stem from the assumption that observed data captures the intent of users. However, a large portion of these observed actions are not intentional, and are effectively polluting the models. Much of this observed activity is either generated by robots traversing the internet or the result of unintended actions of real users. These non-intentional actions observed in the web logs severely bias both analytics and the models created from the data. In this paper, we will show examples of how non-intentional traffic that is produced by fraudulent activities adversely affects both general analytics and predictive models, and propose an approach using co-visitation networks to identify sites that have large amounts of this fraudulent traffic. We will then show how this approach, along with a second stage classifier that identifies non-intentional traffic at the browser level, is deployed in production at Media6Degrees (m6d), a targeting technology company for display advertising. This deployed product acts both to filter out the fraudulent traffic from the input data and to insure that we don't serve ads during unintended website visits.
Understanding Admixture Fractions

Estimation of admixture fractions has become one of the most commonly used computational tools in population genomics. How ever, there is remarkably little population genetic theory on their statistical properties. We develop theoretical results that can accurately predict means and variances of admixture proportions within a population using models with recombination and genetic drift. Based on established theory on measures of multilocus disequilibrium, we show that there is a set of recurrence relations that can be used to derive expectations for higher moments of the admixture fraction distribution. We obtain closed form solutions for some special cases. Using these results, we develop a method for estimating admixture parameters from estimated admixture proportion obtained from programs such as Structure or Admixture. We apply this method to HapMap data and find that the population history of African Americans, as expected, is not best explained by a single admixture event between people of European and African ancestry. A model of constant gene flow for the past 11 generations until 2 generations ago gives a better fit.
Access network optimization

In this work we present a mathematical optimization model for planning the deployment of fast internet technology in a local exchange area. The locations of the new multi-service access nodes (MSANs) and the connections between these nodes and the main distribution frame (hub) are planned simultaneously. Additionally, the connection of several classical nodes to the new MSAN locations via dedicated copper cables is explicitly allowed in the model. The optimization model minimizes the total of node costs and connection costs. The obtained network can be used to develop two heuristics for the project roll-out. Given a limited capital as many customers as possible should be connected to the new nodes. Another possibility is to minimize the total costs such that a minimum customer coverage is satisfied.
An introduction to population genetics

What is population genetics? Like so many branches of biology, what we think of today as population genetics would hardly be recognised by the founding fathers of the discipline. If you had been studying population genetics 80 years ago, you would probably have been working on the heritability of microscopic traits in Drosophila or developing efficient crossing schemes for agricultural breeding, 30 years ago you may have been analysing levels of protein polymorphism and population differentiation. These days, if you work in population genetics you are more likely to be interested in using DNA sequence variation to map disease mutations in humans, or sites of adaptive evolution in viral genomes. But of course there is a link between all three types of study: the genetics of variation. And broadly speaking, population genetics can be defined as the study of the genetical basis of naturally occurring variation, with the aim of describing and understanding the evolutionary forces that create variation within species and which lead to differences between species. For example, this picture represent sequence level variation in a human gene called LPL, thought perhaps to play some role in hereditary heart disease. The types of questions we might want to ask of the data are A) Can we detect a link between sequence variation and a predisposition to heart disease? B) What does variation in this gene tell us about the history of humans? C) Can we detect the influence of natural selection on the recent history of the gene? And in turn such questions raise other, more technical, but still critical issues such as A) How many individuals should I sequence from? B) How much sequence should I collect from each? C) What is the best way to sample individuals in order to answer my question? These questions are not easy to address, and of course they are not independent of one another. What I hope to achieve during this course is to give you some understanding of how to begin answering such questions, and a feeling for the underlying theoretical models and methods.
Advantages and Disadvantages of Application-Oriented System Design in Embedded Systems Design

The dissemination of complex embedded systems is feasible due to the low cost provided by the technology advance. This complexity is also present in the design process. The embedded systems design tools evolution has supported this process. However, nowadays development strategies are not suitable for the design of many applications, they seldom guide the developer in the design of an application oriented final solution. This work shows advantages and disadvantages of application-oriented system design used to develop two embedded systems. The disadvantages found in these two designs may help AOSD methodology improvement in hardware generation.
A Comparative Study To Evolutionary Algorithms

Evolutionary algorithms are general iterative algorithms for combinatorial optimization. The term evolutionary algorithm is used to refer to any probabilistic algorithm whose design is inspired by evolutionary mechanisms found in biological species. These algorithms have been found to be very effective and robust in solving numerous problems from a wide range of application domains. In this paper we perform a comparative study among Genetic Algorithms (GA), Simulated Annealing (SA), Differential Evolution (DE), and Self Organising Migrating Algorithms (SOMA). These algorithms have many similarities, but they also possess distinctive features, mainly in their strategies for searching the solution state space. The four heuristics are applied on the same optimization problem Travelling Salesman Problem (TSP) and compared with respect to (1) quality of the best solution identified by each heuristic, (2) progress of the search from an initial solution until stopping criteria are met. INTRODUCTION TO EVOLUTIONARY ALGORITHMS Evolutionary algorithms (EAs) have many interesting properties and have been widely used in various optimization problems from combinatorial problems such as job shop scheduling to real valued parameter optimization (Back et al. 1997). In computer science, evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) that involves combinatorial optimization problems. Evolutionary computation uses iterative progress, such as growth or development in a population. This population is then selected in a guided random search using parallel processing to achieve the desired end. Such processes are often inspired by biological mechanisms of evolution. As evolution can produce highly optimised processes and networks, it has many applications in computer science. Problem solution using evolutionary algorithms is shown in Figure 1. Figure 1: Problem solution using evolutionary algorithms (adapted from http://jpmc.sourceforge.net )
Dose-response study of N,N-dimethyltryptamine in humans. II. Subjective effects and preliminary results of a new rating scale.

BACKGROUND Validation of animal models of hallucinogenic drugs' subjective effects requires human data. Previous human studies used varied groups of subjects and assessment methods. Rating scales for hallucinogen effects emphasized psychodynamic principles or the drugs' dysphoric properties. We describe the subjective effects of graded doses of N,N-dimethyltryptamine (DMT), an endogenous hallucinogen and drug of abuse, in a group of experienced hallucinogen users. We also present preliminary data from a new rating scale for these effects. METHODS Twelve highly motivated volunteers received two doses (0.04 and 0.4 mg/kg) of intravenous (IV) dimethyltryptamine fumarate "nonblind," before entering a double-blind, saline placebo-controlled, randomized study using four doses of IV DMT. Subjects were carefully interviewed after resolution of drug effects, providing thorough and systematic descriptions of DMT's effects. They also were administered a new instrument, the Hallucinogen Rating Scale (HRS). The HRS was drafted from interviews obtained from an independent sample of 19 experienced DMT users, and modified during early stages of the study. RESULTS Psychological effects of IV DMT began almost immediately after administration, peaked at 90 to 120 seconds, and were almost completely resolved by 30 minutes. This time course paralleled DMT blood levels previously described. Hallucinogenic effects were seen after 0.2 and 0.4 mg/kg of dimethyltryptamine fumarate, and included a rapidly moving, brightly colored visual display of images. Auditory effects were less common. "Loss of control," associated with a brief, but overwhelming "rush," led to a dissociated state, where euphoria alternated or coexisted with anxiety. These effects completely replaced subjects' previously ongoing mental experience and were more vivid and compelling than dreams or waking awareness. Lower doses, 0.1 and 0.05 mg/kg, were primarily affective and somaesthetic, while 0.1 mg/kg elicited the least desirable effects. Clustering of HRS items, using either a clinical, mental status method or principal components factor analysis provided better resolution of dose effects than did the biological variables described previously. CONCLUSIONS These clinical and preliminary quantitative data provide bases for further psychopharmacologic characterization of DMT's properties in humans. They also may be used to compare the effects of other agents affecting relevant brain receptors in volunteer and psychiatric populations.
Single Bout Short Duration Fluid Shear Stress Induces Osteogenic Differentiation of MC3T3-E1 Cells via Integrin β1 and BMP2 Signaling Cross-Talk

Fluid shear stress plays an important role in bone osteogenic differentiation. It is traditionally believed that pulsed and continuous stress load is more favorable for fracture recovery and bone homeostasis. However, according to our clinical practice, we notice that one single stress load is also sufficient to trigger osteogenic differentiation. In the present study, we subject osteoblast MC3T3-E1 cells to single bout short duration fluid shear stress by using a parallel plate flow system. The results show that 1 hour of fluid shear stress at 12 dyn/cm2 promotes terminal osteogenic differentiation, including rearrangement of F-actin stress fiber, up-regulation of osteogenic genes expression, elevation of alkaline phosphatase activity, secretion of type I collagen and osteoid nodule formation. Moreover, collaboration of BMP2 and integrin β1 pathways plays a significant role in such differentiation processes. Our findings provide further experimental evidence to support the notion that single bout short duration fluid shear stress can promote osteogenic differentiation.
Uremia induces functional incompetence of bone marrow-derived stromal cells.

BACKGROUND Chronic kidney disease (CKD) is associated with increased risk for cardiovascular diseases (CVD). We hypothesized that inadequate angiogenic response in uremic patients could result from dysfunction of bone marrow-derived stromal cells [mesenchymal stem cells (MSCs)]. METHODS We investigated whether MSCs are functionally competent in uremia induced by partial kidney ablation in C57Bl/6J mice. RESULTS Uremic MSCs showed decreased expression of vascular endothelial growth factor (VEGF), VEGF receptor (VEGFR)1 and stromal cell-derived factor (SDF)-1α, increased cellular senescence, decreased proliferation, defects in migration in response to VEGF and SDF-1α and in vitro tube formation. Interestingly, the expression of fibroblast-specific protein-1 was higher in uremic MSCs. Uremia decreased hypoxia-inducible factor-1α, VEGF and VEGFR1 expression under hypoxia and Akt phosphorylation in both basal and VEGF-stimulated states. A diminished mitogenic effect on endothelial proliferation was observed in conditioned media from uremic MSCs. In addition, intravital microscopic analysis showed decreased angiogenesis in uremic MSCs. CONCLUSION These results clearly demonstrate the functional incompetence in MSCs under uremic conditions and may significantly contribute to the disproportionately high risk for CVD in patients with CKD.
Pill image binarization for detecting text imprints

Identifying pill is a major concern for both patients and pharmacists nowadays. Being able to extract pill information automatically will benefit both pill information retrieval and indexing processes. We aim to extract texts from pill imprints so that they can be used to search existing pill databases. This paper presents approaches for extracting texts from pill images based on i) a technique presented by Kasar[1] and ii) processing edge masks of imprints. We also compared different thresholds for binarizing extracted text area so that it can be used with optical character recognition (OCR). The result showed that the method based on using edge mask performed better, and the Otsu threshold gave the best results for binarization of the imprint area.
Implementing the Himeno benchmark with CUDA on GPU clusters

This paper describes the use of CUDA to accelerate the Himeno benchmark on clusters with GPUs. The implementation is designed to optimize memory bandwidth utilization. Our approach achieves over 83% of the theoretical peak bandwidth on a NVIDIA Tesla C1060 GPU and performs at over 50 GFlops. A multi-GPU implementation that utilizes MPI alongside CUDA streams to overlap GPU execution with data transfers allows linear scaling and performs at over 800 GFlops on a cluster with 16 GPUs. The paper presents the optimizations required to achieve this level of performance.
Brain mechanisms underlying flavour and appetite

Complementary neurophysiological recordings in macaques and functional neuroimaging in humans show that the primary taste cortex in the rostral insula and adjoining frontal operculum provides separate and combined representations of the taste, temperature and texture (including viscosity and fat texture) of food in the mouth independently of hunger and thus of reward value and pleasantness. One synapse on, in the orbitofrontal cortex, these sensory inputs are for some neurons combined by learning with olfactory and visual inputs. Different neurons respond to different combinations, providing a rich representation of the sensory properties of food. In the orbitofrontal cortex, feeding to satiety with one food decreases the responses of these neurons to that food, but not to other foods, showing that sensory-specific satiety is computed in the primate (including human) orbitofrontal cortex. Consistently, activation of parts of the human orbitofrontal cortex correlates with subjective ratings of the pleasantness of the taste and smell of food. Cognitive factors, such as a word label presented with an odour, influence the pleasantness of the odour and the activation produced by the odour in the orbitofrontal cortex. These findings provide a basis for understanding how what is in the mouth is represented by independent information channels in the brain; how the information from these channels is combined; and how and where the reward and subjective affective value of food is represented and is influenced by satiety signals. Activation of these representations in the orbitofrontal cortex may provide the goal for eating, and understanding them helps to provide a basis for understanding appetite and its disorders.
Journal of Neuroengineering and Rehabilitation Performance Adaptive Training Control Strategy for Recovering Wrist Movements in Stroke Patients: a Preliminary, Feasibility Study

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: In the last two decades robot training in neuromotor rehabilitation was mainly focused on shoulder-elbow movements. Few devices were designed and clinically tested for training coordinated movements of the wrist, which are crucial for achieving even the basic level of motor competence that is necessary for carrying out ADLs (activities of daily life). Moreover, most systems of robot therapy use point-to-point reaching movements which tend to emphasize the pathological tendency of stroke patients to break down goal-directed movements into a number of jerky sub-movements. For this reason we designed a wrist robot with a range of motion comparable to that of normal subjects and implemented a self-adapting training protocol for tracking smoothly moving targets in order to facilitate the emergence of smoothness in the motor control patterns and maximize the recovery of the normal RoM (range of motion) of the different DoFs (degrees of Freedom).