Miracle-dz/UniFAR-FTUs huggingface dataset:
The diversity and evolution of locomotor muscle properties in anurans

ABSTRACT Anuran jumping is a model system for linking muscle physiology to organismal performance. However, anuran species display substantial diversity in their locomotion, with some species performing powerful leaps from riverbanks or tree branches, while other species move predominantly via swimming, short hops or even diagonal-sequence gaits. Furthermore, many anurans with similar locomotion and morphology are actually convergent (e.g. multiple independent evolutions of ‘tree frogs’), while closely related species may differ drastically, as with the walking toad (Melanophryniscus stelzneri) and bullfrog-like river toad (Phrynoides aspera) compared with other Bufonid toads. These multiple independent evolutionary changes in locomotion allow us to test the hypothesis that evolutionary increases in locomotor performance will be linked to the evolution of faster, high-power muscles. I tested the jumping, swimming and walking (when applicable) performance of 14 species of anurans and one salamander, followed by measurement of the contractile properties of the semimembranosus and plantaris longus muscles and anatomical measurements, using phylogenetic comparative methods. I found that increased jumping performance correlated to muscle contractile properties associated with muscle speed (e.g. time to peak tetanus, maximum shortening speed, peak isotonic power), and was tightly linked to relevant anatomical traits (e.g. leg length, muscle mass). Swimming performance was not correlated to jumping, and was correlated with fewer anatomical and muscular variables. Thus, muscle properties evolve along with changes in anatomy to produce differences in overall locomotor performance. Summary: Frog muscle contractile properties (semimembranosus and plantaris) vary widely across taxa and show correlations to locomotor performance, particularly jumping performance.
Different approaches to volume assessment of lymph nodes in computer tomography scans of head and neck squamous cell carcinoma in comparison with a real gold standard

Volume assessment in head and neck squamous cell carcinoma (HNSCC) is becoming a more and more clinical important parameter, especially in treatment planning and response control. Various authors showed a significant impact of tumour volume on treatment outcome and local control. Regarding the increasing impact of induction chemotherapy and primary chemoradiation on HNSCC, the need for an adequate measuring tool to judge treatment response becomes obvious. This study was performed to compare the momentary ‘gold standard’, the diameter‐based approach, and tumour volume assessment in HNSCC with approaches based on segmentation algorithms in computer tomography (CT) scans.
A 128$\times$ 128 120 dB 15 $\mu$s Latency Asynchronous Temporal Contrast Vision Sensor

This paper describes a 128 times 128 pixel CMOS vision sensor. Each pixel independently and in continuous time quantizes local relative intensity changes to generate spike events. These events appear at the output of the sensor as an asynchronous stream of digital pixel addresses. These address-events signify scene reflectance change and have sub-millisecond timing precision. The output data rate depends on the dynamic content of the scene and is typically orders of magnitude lower than those of conventional frame-based imagers. By combining an active continuous-time front-end logarithmic photoreceptor with a self-timed switched-capacitor differencing circuit, the sensor achieves an array mismatch of 2.1% in relative intensity event threshold and a pixel bandwidth of 3 kHz under 1 klux scene illumination. Dynamic range is > 120 dB and chip power consumption is 23 mW. Event latency shows weak light dependency with a minimum of 15 mus at > 1 klux pixel illumination. The sensor is built in a 0.35 mum 4M2P process. It has 40times40 mum2 pixels with 9.4% fill factor. By providing high pixel bandwidth, wide dynamic range, and precisely timed sparse digital output, this silicon retina provides an attractive combination of characteristics for low-latency dynamic vision under uncontrolled illumination with low post-processing requirements.
Counting People Crossing a Line Using Integer Programming and Local Features

We propose an integer programming method for estimating the instantaneous count of pedestrians crossing a line of interest (LOI) in a video sequence. Through a line sampling process, the video is first converted into a temporal slice image. Next, the number of people is estimated in a set of overlapping sliding windows on the temporal slice image, using a regression function that maps from local features to a count. Given that the count in a sliding window is the sum of the instantaneous counts in the corresponding time interval, an integer programming method is proposed to recover the number of pedestrians crossing the LOI in each frame. Integrating over a specific time interval yields the cumulative count of pedestrians crossing the line. Compared with current methods for line counting, our proposed approach achieves state-of-the-art performance on several challenging crowd video data sets.
3D model search and retrieval based on the 3D Radon transform

This paper describes a novel method for 3D model content-based search and retrieval based on the 3D radon transform and a querying-by-3D-model approach. Descriptors are extracted using the 3D radon transform and applying a number of functionals on the transform's coefficients. Similarity measures are then created for the extracted descriptors and introduced into a 3D model-matching algorithm. This results in a very fast and accurate matching method. Experimental results are presented evaluating the performance of the proposed method in terms of precision versus recall diagrams.
Asymmetric similarity-weighted ensembles for image segmentation

Supervised classification is widely used for image segmentation. To work effectively, these techniques need large amounts of labeled training data, that is representative of the test data. Different patient groups, different scanners or different scanning protocols can lead to differences between the images, thus representative data might not be available. Transfer learning techniques can be used to account for these differences, thus taking advantage of all the available data acquired with different protocols. We investigate the use of classifier ensembles, where each classifier is weighted according to the similarity between the data it is trained on, and the data it needs to segment. We examine 3 asymmetric similarity measures that can be used in scenarios where no labeled data from a newly introduced scanner or scanning protocol is available. We show that the asymmetry is informative and the direction of measurement needs to be chosen carefully. We also show that a point set similarity measure is robust across different studies, and outperforms state-of-the-art results on a multi-center brain tissue segmentation task.
The Management of Classical Hodgkin's Lymphoma: Past, Present, and Future

The management of classical Hodgkin's lymphoma (CHL) is a success story of modern multi-agent haemato-oncology. Prior to the middle of the twentieth century CHL was fatal in the majority of cases. Introduction of single agent radiotherapy (RT) demonstrated for the first time that these patients could be cured. Developments in chemotherapy including the mechlorethamine, vincristine, procarbazine and prednisolone (MOPP) and Adriamycin, bleomycin, vinblastine and dacarbazine (ABVD) regimens have resulted in cure rates of over 80%. Even in relapse, CHL patients can be salvaged with high dose chemotherapy and autologous haematopoietic stem cell transplantation (ASCT). Challenges remain, however, in finding new strategies to manage the small number of patients who continue to relapse or progress. In addition, the young age of many Hodgkin's patients forces difficult decisions in balancing the benefit of early disease control against the survival disadvantage of late toxicity. In this article we aim to summarise past trials, define the current standard of care and appraise future developments in the management of CHL.
South China Sea throughflow impact on the Indonesian throughflow

In 2008–2009 the Makassar throughflow profile changed dramatically: the characteristic thermocline velocity maximum increased from 0.7 to 0.9 m/sec and shifted from 140 m to 70 m, amounting to a 47% increase in the transport of warmer water between 50 and 150 m during the boreal summer. HYCOM output indicates that ENSO induced change of the South China Sea (SCS) throughflow into the Indonesian seas is the likely cause. Increased SCS throughflow during El Niño with a commensurate increase in the southward flow of buoyant surface water through the Sulu Sea into the northern Makassar Strait, inhibits tropical Pacific surface water injection into Makassar Strait; during La Niña SCS throughflow is near zero allowing tropical Pacific inflow. The resulting warmer ITF reaches into the Indian Ocean, potentially affecting regional sea surface temperature and climate.
Improvement of Content Server with Contents Anycasting Using OpenFlow

In this paper, we show our design and implementation method of contents anycasting using OpenFlow that is a promising future internet enabling technology. This method aims to improve the content server by enabling it serve more clients, also this method aims to make a more efficient use of the overall bandwidth available in the network by providing more flexible and dynamic redirection of contents that is done with the help of OpenFlow's new potential abilities and thus giving new opportunities to the future internet that are currently not available. This method relies on three important ideas which are; the content based networking, decision making by the network in a similar manner to anycast and the participation of user clients in providing the service. All this is done using the newly invented OpenFlow. It is done through some modifications to the content server and client, thus imposing small changes to the application layer.
Distinct microbial populations are tightly linked to the profile of dissolved iron in the methanic sediments of the Helgoland mud area, North Sea

Iron reduction in subseafloor sulfate-depleted and methane-rich marine sediments is currently a subject of interest in subsurface geomicrobiology. While iron reduction and microorganisms involved have been well studied in marine surface sediments, little is known about microorganisms responsible for iron reduction in deep methanic sediments. Here, we used quantitative PCR-based 16S rRNA gene copy numbers and pyrosequencing-based relative abundances of bacteria and archaea to investigate covariance between distinct microbial populations and specific geochemical profiles in the top 5 m of sediment cores from the Helgoland mud area, North Sea. We found that gene copy numbers of bacteria and archaea were specifically higher around the peak of dissolved iron in the methanic zone (250–350 cm). The higher copy numbers at these depths were also reflected by the relative sequence abundances of members of the candidate division JS1, methanogenic and Methanohalobium/ANME-3 related archaea. The distribution of these populations was strongly correlated to the profile of pore-water Fe2+ while that of Desulfobacteraceae corresponded to the pore-water sulfate profile. Furthermore, specific JS1 populations also strongly co-varied with the distribution of Methanosaetaceae in the methanic zone. Our data suggest that the interplay among JS1 bacteria, methanogenic archaea and Methanohalobium/ANME-3-related archaea may be important for iron reduction and methane cycling in deep methanic sediments of the Helgoland mud area and perhaps in other methane-rich depositional environments.
Training Working Memory in Older Adults: Is There an Advantage of Using Strategies?

The purpose of the present study was to test the efficacy of a working memory (WM) training in elderly people, and to compare the effects of a WM training based on an adaptive procedure with one combining the same procedure with the use of a strategy, based on the construction of visual mental images. Eighteen older adults received training with a WM task (the WM group), another 18 received the same WM training and were also taught to use a visual imagery strategy (the WM + Strategy group), and another 18 served as active controls. Training-related gains in the WM (criterion) task and transfer effects on measures of verbal and visuospatial WM, short-term memory (STM), processing speed, and reasoning were considered. Training gains and transfer effects were also assessed after 6 months. After the training, both the trained groups performed better than the control group in the WM criterion task, and maintained these gains 6 months later; they also showed immediate transfer effects on processing speed. The two trained groups also outperformed the control group in the long term in the WM tasks, in one of the STM tasks (backward span task), and in the processing speed measure. Long-term large effect sizes were found for all the tasks involving memory processes in the WM + Strategy group, but only for the processing speed task in the WM group. Findings are discussed in terms of the benefits and limits of teaching older people a strategy in combination with an adaptive WM training.
On the performance of ad hoc networks with beamforming antennas

Beamforming antennas have the potential to provide a fundamental breakthrough in ad hoc network capacity. We present a broad-based examination of this potential, focusing on exploiting the longer ranges as well as the reduced interference that beamforming antennas can provide. We consider a number of enhancements to a convectional ad hoc network system, and evaluation the impact of each enhancement using simulation. Such enhancements include "aggressive" and "conservative" channel access models for beamforming antennas, link power control, and directional neighbor discovery. Our simulations are based on detailed modeling on detailed modeling of steered as well as swiched beams using antenna patterns of varying gains, and a realistic radio and propagation model. For the scenarios studied, our results show that beamforming can yield a 28% to 118% (depending upon the density) improvement in throughput, and up to a factor-of-28 reduction in delay. Our study also tells us which mechanisms are likely to be more effective and under what conditions, which in turn identifies areas where future research is neede
Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs

Weak disposability of outputs means that firms can abate harmful emissions by decreasing the activity level. Modeling weak disposability in nonparametric production analysis has caused some confusion. This article identifies a dilemma in these approaches: conventional formulations implicitly and unintentionally assume all firms apply uniform abatement factors. However, it is usually cost-effective to abate emissions in those firms where the marginal abatement costs are lowest. This article presents a simple formulation of weak disposability that allows for non-uniform abatement factors and preserves the linear structure of the model.
Activation and Two Modes of Blockade by Strontium of Ca2+-activated K+ Channels in Goldfish Saccular Hair Cells

Effects of internal Sr2+ on the activity of large-conductance Ca2+-activated K+ channels were studied in inside-out membrane patches from goldfish saccular hair cells. Sr2+ was approximately one-fourth as potent as Ca2+ in activating these channels. Although the Hill coefficient for Sr2+ was smaller than that for Ca2+, maximum open-state probability, voltage dependence, steady state gating kinetics, and time courses of activation and deactivation of the channel were very similar under the presence of equipotent concentrations of Ca2+ and Sr2+. This suggests that voltage-dependent activation is partially independent of the ligand. Internal Sr2+ at higher concentrations (>100 μM) produced fast and slow blockade both concentration and voltage dependently. The reduction in single-channel amplitude (fast blockade) could be fitted with a modified Woodhull equation that incorporated the Hill coefficient. The dissociation constant at 0 mV, the Hill coefficient, and zd (a product of the charge of the blocking ion and the fraction of the voltage difference at the binding site from the inside) in this equation were 58–209 mM, 0.69–0.75, 0.45–0.51, respectively (n = 4). Long shut events (slow blockade) produced by Sr2+ lasted ∼10–200 ms and could be fitted with single-exponential curves (time constant, τl−s) in shut-time histograms. Durations of burst events, periods intercalated by long shut events, could also be fitted with single exponentials (time constant, τb). A significant decrease in τb and no large changes in τl−s were observed with increased Sr2+ concentration and voltage. These findings on slow blockade could be approximated by a model in which single Sr2+ ions bind to a blocking site within the channel pore beyond the energy barrier from the inside, as proposed for Ba2+ blockade. The dissociation constant at 0 mV and zd in the Woodhull equation for this model were 36–150 mM and 1–1.8, respectively (n = 3).
Trial-Based Heuristic Tree Search for Finite Horizon MDPs

Dynamic programming is a well-known approach for solving MDPs. In large state spaces, asynchronous versions like Real-Time Dynamic Programming have been applied successfully. If unfolded into equivalent trees, Monte-Carlo Tree Search algorithms are a valid alternative. UCT, the most popular representative, obtains good anytime behavior by guiding the search towards promising areas of the search tree. The Heuristic Search algorithm AO∗ finds optimal solutions for MDPs that can be represented as acyclic AND/OR graphs. We introduce a common framework, Trial-based Heuristic Tree Search, that subsumes these approaches and distinguishes them based on five ingredients: heuristic function, backup function, action selection, outcome selection, and trial length. Using this framework, we describe three new algorithms which mix these ingredients in novel ways in an attempt to combine their different strengths. Our evaluation shows that two of our algorithms not only provide superior theoretical properties to UCT, but also outperform state-of-the-art approaches experimentally.
Improving Shape-from-Focus by Compensating for Image Magnification Shift

Images taken with different focus settings are used in shape-from-focus to reconstruct the depth map of a scene. A problem when acquiring images with different focus settings is the shift of image features due to changes in magnification. This paper shows that those changes affect the shape-from-focus performance and that the final reconstruction can be improved by compensating for that shift. The proposed scheme takes into account the effects due to magnification changes between near and far focused images and it is able to determine the depth of the scene points with higher accuracy than traditional techniques. Experimental results of the application of the proposed method are shown.
Quick Detection of High-Degree Entities in Large Directed Networks

In this paper we address the problem of quick detection of high-degree entities in large online social networks. Practical importance of this problem is attested by a large number of companies that continuously collect and update statistics about popular entities, usually using the degree of an entity as an approximation of its popularity. We suggest a simple, efficient, and easy to implement two-stage randomized algorithm that provides highly accurate solutions to this problem. For instance, our algorithm needs only one thousand API requests in order to find the top-100 most followed users, with more than 90% precision, in the online social network Twitter with approximately a billion of registered users. Our algorithm significantly outperforms existing methods and serves many different purposes such as finding the most popular users or the most popular interest groups in social networks. An important contribution of this work is the analysis of the proposed algorithm using Extreme Value Theory - a branch of probability that studies extreme events and properties of largest order statistics in random samples. Using this theory we derive an accurate prediction for the algorithm's performance and show that the number of API requests for finding the top-k most popular entities is sub linear in the number of entities. Moreover, we formally show that the high variability of the entities, expressed through heavy-tailed distributions, is the reason for the algorithm's efficiency. We quantify this phenomenon in a rigorous mathematical way.
Predictive Control Design Based on Neural Model of a Non-linear System

This paper provides two approaches for design of Generalized Predictive Control (GPC) algorithm for a non-linear dynamic system. In the classical approach of the GPC strategy the recursive method of least square is considered for calculating of the linearized model parameters from the known analytic description of a particular non-linear system. The other purpose of this paper is to show an intelligent approach in which a feed-forward neural network (Multi Layer Perceptron - MLP) is used for modeling the same non-linear system within the frames of the predictive control. The possibility of on-line estimation of an actual parameters from the off-line trained neural model of the non-linear system by means method of the instantaneous linearization in each sample point is considered in GPC algorithm design. The validity of classical and neural GPC strategy is tested by computer simulations in Matlab/Simulink language using architecture of S-functions of the library PredicLib.
Ultrastructure of Halo Nevi

An ultrastructural study was conducted on eight halo nevi. Some of them were of recent onset. Others had an evolution of several months. The distribution of the population of the dendritic cells in the depigmented epidermis of the halo was more polymorphous at the early stage when few melanocytes with abundant cytofilaments and some Langerhans cells were seen. At an advanced clinical stage, only Langerhans cells were present in the basal layer. In the dermis abnormal nerves as in vitiligo were observed. The inflammatory infiltrate does not seem to appear at the early stage of involution of the nevus. At the advanced clinical stage, small mononuclear cells were also noticed among the inflammatory cells (lymphocyte‐like cells, macrophages, mast cells). It is suggested that an initial stage of inhibition of both the melanocytes and the nevus cells may be responsible for the development of the depigmented halo. This stage precedes the appearance of a dermal lymphomacrophagic infiltrate that leads to the destruction of the nevus.