Miracle-dz/UniFAR-FTUs huggingface dataset:
Stem cell factor and basic fibroblast growth factor are synergistic in augmenting committed myeloid progenitor cell growth.

Stem cell factor (SCF) and basic fibroblast growth factor (bFGF) are hematopoietic cytokines produced by bone marrow stromal cells. It is known that, although SCF and bFGF have limited clonogenic activity on their own, they can augment colony-stimulating factor (CSF)-mediated progenitor cell growth. Because these factors are both sequestered by stromal cells, we examined their interaction on progenitor cell growth in conjunction with granulocyte-macrophage-CSF (GM-CSF). In this study, we show that clonogenic growth derived from low-density bone marrow cells stimulated by GM-CSF is significantly augmented (P < .001) in the presence of maximal (100 ng/mL) concentrations of SCF in combination with 100 ng/mL of bFGF. When CD34+ cells are used, the synergistic effect of bFGF and SCF for GM-CSF-mediated progenitor cell growth is further increased, resulting in as much as a sevenfold increase in detectable colony-forming units granulocyte-macrophage (P < .001). These data suggest that the synergistic activity of bFGF and SCF is mediated directly on hematopoietic precursors. These observations suggest that bFGF and SCF, concentrated locally on stromal cell surfaces, might interact in concert with other hematopoietic cytokines to regulate stem cell proliferation and differentiation in hematopoietic niches in the bone marrow.
Astroglial excitability and gliotransmission: an appraisal of Ca2+ as a signalling route

Astroglial cells, due to their passive electrical properties, were long considered subservient to neurons and to merely provide the framework and metabolic support of the brain. Although astrocytes do play such structural and housekeeping roles in the brain, these glial cells also contribute to the brain's computational power and behavioural output. These more active functions are endowed by the Ca2+-based excitability displayed by astrocytes. An increase in cytosolic Ca2+ levels in astrocytes can lead to the release of signalling molecules, a process termed gliotransmission, via the process of regulated exocytosis. Dynamic components of astrocytic exocytosis include the vesicular-plasma membrane secretory machinery, as well as the vesicular traffic, which is governed not only by general cytoskeletal elements but also by astrocyte-specific IFs (intermediate filaments). Gliotransmitters released into the ECS (extracellular space) can exert their actions on neighbouring neurons, to modulate synaptic transmission and plasticity, and to affect behaviour by modulating the sleep homoeostat. Besides these novel physiological roles, astrocytic Ca2+ dynamics, Ca2+-dependent gliotransmission and astrocyte–neuron signalling have been also implicated in brain disorders, such as epilepsy. The aim of this review is to highlight the newer findings concerning Ca2+ signalling in astrocytes and exocytotic gliotransmission. For this we report on Ca2+ sources and sinks that are necessary and sufficient for regulating the exocytotic release of gliotransmitters and discuss secretory machinery, secretory vesicles and vesicle mobility regulation. Finally, we consider the exocytotic gliotransmission in the modulation of synaptic transmission and plasticity, as well as the astrocytic contribution to sleep behaviour and epilepsy.
Equivalent error bars for neural network classifiers trained by Bayesian inference

The topic of this paper is the problem of outlier detection for neural networks trained by Bayesian inference. I will show that marginalization is not a good method to get moderated probabilities for classes in outlying regions. The reason why marginalization fails to indicate outliers is analysed and an alternative measure, that is a more reliable indicator for outliers, is proposed. A simple artiicial classiication problem is used to visualize the diierences. Finally both methods are used to classify a real world problem, where outlier detection is mandatory.
Physiologically motivated image fusion for object detection using a pulse coupled neural network

This paper presents the first physiologically motivated pulse coupled neural network (PCNN)-based image fusion network for object detection. Primate vision processing principles, such as expectation driven filtering, state dependent modulation, temporal synchronization, and multiple processing paths are applied to create a physiologically motivated image fusion network. PCNN's are used to fuse the results of several object detection techniques to improve object detection accuracy. Image processing techniques (wavelets, morphological, etc.) are used to extract target features and PCNN's are used to focus attention by segmenting and fusing the information. The object detection property of the resulting image fusion network is demonstrated on mammograms and Forward Looking Infrared Radar (FLIR) images. The network removed 94% of the false detections without removing any true detections in the FLIR images and removed 46% of the false detections while removing only 7% of the true detections in the mammograms. The model exceeded the accuracy obtained by any individual filtering methods or by logical ANDing the individual object detection technique results.
Probabilities modeling of multi-class based on relevance vector machine

Based on the probability of memberships estimated by RVM (relevance vector machine) basic model, probabilistic output approaches for multi-class memberships in one-against-all strategy by multivariate sigmoid function and in one-against-one strategy by pairwise coupling are presented respectively. Experiment results based on artificial Gauss datasets and UCI datasets show the proposed approaches can calculate posterior probability precisely and are computational efficient, as well can ensure high classification performance.
Combining classification techniques to define topo-climatic landscapes

Landscape classification tackles issues related to the representation and analysis of continuous and variable ecological data. In this study, a methodology is created in order to define topo-climatic landscapes (TCL) in the north-west of Catalonia (north-east of the Iberian Peninsula). TCLs relate the ecological behaviour of a landscape in terms of topography, physiognomy and climate, which compound the main drivers of an ecosystem. Selected variables are derived from different sources such as remote sensing and climatic atlas. The proposed methodology combines unsupervised interative cluster classification with a supervised fuzzy classification. As a result, 28 TCLs have been found for the study area which may be differentiated in terms of vegetation physiognomy and vegetation altitudinal range type. Furthermore a hierarchy among TCLs is set, enabling the merging of clusters and allowing for changes of scale. Through the topo-climatic landscape map, managers may identify patches with similar environmental conditions and asses at the same time the uncertainty involved.
Planar Hexagonal Meshing for Architecture

Mesh surfaces with planar hexagonal faces, what we refer to as PH meshes, offer an elegant way of paneling freeform architectural surfaces due to their node simplicity (i.e., valence-3 nodes) and naturally appealing layout. We investigate PH meshes to understand how the shape, size, and pattern of PH faces are constrained by surface geometry. This understanding enables us to develop an effective method for paneling freeform architectural surfaces with PH meshes. Our method first constructs an ideal triangulation of a given smooth surface, guided by surface geometry. We show that such an ideal triangulation leads to a Dupin-regular PH mesh via tangent duality on the surface. We have developed several novel and effective techniques for improving undesirable mesh layouts caused by singular behaviors of surface curvature. We compute support structures associated with PH meshes, including exact vertex offsets and approximate edge offsets, as demanded in panel manufacturing. The efficacy of our method is validated by a number of architectural examples.
Air jet driven force feedback in virtual reality

An untethered VR system with force feedback based on the use of air pressure gives the user the feeling of touching an object. The result is an untethered human interface that's easy to use in everyday life. The system uses a projection-based stereo display and optical position tracking. The user employs red and blue 3D glasses and a lightweight paddle. This article is available with a short video documentary on CD-ROM.
A Low Complexity User Grouping Based Multiuser MISO Downlink Precoder

We consider low complexity precoding for the Multiple Input Single Output (MISO) Gaussian Broadcast channel with $N_t$ antennas at the base station and $N_u$ single antenna users in the downlink. Theoretical studies have suggested high throughput communication with increasing spatial dimensions i.e., $min(N_t,N_u)$. Nevertheless, most modern communication standards are unable to exploit the spatial dimension fully, since they are restricted to orthogonal communication techniques like TDMA/FDMA (Time/Frequency Division Multiplexed Access) which are known to be sub-optimal. This restriction is mostly due to the prohibitive complexity of optimal/near-optimal precoding schemes. On the other hand low complexity techniques like Zero Forcing (ZF) and MMSE have poor sum rate performance. In this paper, we propose a novel low-complexity user grouping based precoding scheme which schedules all users on the same time-frequency resource (i.e., optimal utilization of resources). The proposed precoder is analytically shown to achieve a sum rate performance significantly better than the ZF precoder at similar complexity. Through simulations, it is also observed to achieve a significant fraction of the sum rate achieved by the optimal schemes.
Optimization and Control of Cyclic Biped Locomotion on a Rolling Cylinder

This paper investigates the optimization and control of biped walking motion on a rolling cylinder. We design a balance controller for a simplified linear model of a biped robot, which comprises a foot connected to a lump mass through an ankle joint and a translational spring and damper. We also derive a collision model for the system consisting of the cylinder, supporting leg, and swing leg. With the balance controller and collision model, the robot motion is uniquely determined by the initial state. We can therefore optimize the initial state so that the robot achieves a cyclic gait with a constraint on the desired average rolling velocity. Once an optimal initial state is obtained, we further discuss how to maintain the cyclic motion under disturbances. More specifically, we present a method for computing the joint angles and velocities of the swing leg before it collides with the cylinder. The optimization and control results are demonstrated in simulation.
Propagation, Power Absorption, and Temperature Analysis of UWB Wireless Capsule Endoscopy Devices Operating in the Human Body

With the increasing use of wireless capsule endoscopy (WCE) devices in healthcare, it is of utmost importance to analyze the electromagnetic power absorption and thermal effects caused by in-body propagation of wireless signals from these devices. This paper studies the path loss, specific absorption rate (SAR), specific absorption (SA), and temperature variation of the human body caused by an impulse-radio ultra-wideband (UWB) based WCE operating inside the human abdomen. In addition, the design and in-body performance of an UWB antenna with dimensions of 11.85×9×1.27 mm and operating from 3.5 to 4.5 GHz is described in this paper. Path loss is evaluated using both experimental and simulation based methods to characterize the in-body propagation channel. The experimental setup uses a pig's abdominal tissue samples to demonstrate the propagation characteristics of human tissue while a voxel model of the human body consisting of human tissue simulating materials is used in the simulations. The tissue properties, such as relative permittivity, are characterized according to the incident signal frequency and age of the tissue sample during simulations. The SAR and SA variations for different positions of the WCE device inside the colon and the small intestine of the human body model are analyzed using the finite integration technique as the discretization model. The dependency of the electromagnetic effects on the antenna positioning is investigated by using different positions of the antenna inside the human body.
Religious Organizations and the Impact of Human Rights and Equality Laws in England and Wales

ABSTRACT The framework for equality and the multiple aspects of identity that are protected in law, including on the basis of religion and belief, are continuously being redefined and reshaped through ongoing legal claims in England and Wales. In this article, we examine how religious organizations view equality and the extent to which different identity rights can be protected. We conducted a survey of religious organizations in England and Wales to examine attitudes and experiences in relation to changes in the equality laws. We found that equality is variously understood and many religious organizations give only limited recognition to certain legally protected characteristics including gender, sexual orientation and also the identities of other religious organizations. If the integration of equality in the form of identity rights is to be fully achieved within the legal framework of a liberal democratic state and alongside so-called British values, both religious and non-religious citizens alike need to take a greater responsibility for the understanding and recognition of identity differences. Equalities legislation is creating a constitutional framework for citizenship and it is important this new citizenship is structured around equality in practice at the individual and organizational level.
Comparison of cloud service providers based on direct and recommended trust rating

Cloud computing provides many opportunities for enterprises by offering a range of computing services. In today's competitive environment, the service dynamism, elasticity, and choices offered by this highly scalable technology are too attractive for enterprises to ignore. These opportunities have opened up a new dimension of challenges by introducing a different type of trust scenario. Today, the problem of trusting cloud computing is of supreme concern for most enterprises. The diversity of cloud service offerings makes it necessary for customers to evaluate the service levels of different cloud providers in an objective way such that required quality, reliability or security of an application can be ensured. In this paper, a model for Trust Management based on Fuzzy Logic is used to compare the cloud service providers available in the market.
Vascular Health and Risk Management Dovepress Carotid Revascularization: Risks and Benefits

Despite a decline during the recent decades in stroke-related death, the incidence of stroke has remained unchanged or slightly increased, and extracranial carotid artery steno-sis is implicated in 20%–30% of all strokes. Medical therapy and risk factor modification are first-line therapies for all patients with carotid occlusive disease. Evidence for the treatment of patients with symptomatic carotid stenosis greater than 70% with either carotid artery stenting (CAS) or carotid endarterectomy (CEA) is compelling, and several trials have demonstrated a benefit to carotid revascularization in the symptomatic patient population. Asymptomatic carotid stenosis is more controversial, with the largest trials only demonstrating a 1% per year risk stroke reduction with CEA. Although there are sufficient data to advocate for aggressive medical therapy as the primary mode of treatment for asymptomatic carotid stenosis, there are also data to suggest that certain patient populations will benefit from a stroke risk reduction with carotid revascularization. In the United States, consensus and practice guidelines dictate that CEA is reasonable in patients with high-grade asymptomatic stenosis, a reasonable life expectancy, and perioperative risk of less than 3%. Regarding CAS versus CEA, the best-available evidence demonstrates no difference between the two procedures in early perioperative stroke, myocardial infarction, or death, and no difference in 4-year ipsilateral stroke risk. However, because of the higher perioperative risks of stroke in patients undergoing CAS, particularly in symptomatic, female, or elderly patients, it is difficult to recommend CAS over CEA except in populations with prohibitive cardiac risk, previous carotid surgery, or prior neck radiation. Current treatment paradigms are based on identifying the magnitude of perioperative risk in patient subsets and on using predictive factors to stratify patients with high-risk asymptomatic stenosis.
Pragmatic integrated scheduling for clustered VLIW architectures

Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Scheduling for clustered architectures involves spatial concerns (where to schedule) as well as temporal concerns (when to schedule). Various clustered VLIW configurations, connectivity types, and inter‐cluster communication models present different performance trade‐offs to a scheduler. The scheduler is responsible for resolving the conflicting requirements of exploiting the parallelism offered by the hardware and limiting the communication among clusters to achieve better performance. In this paper, we describe our experience with developing a pragmatic scheme and also a generic graph‐matching‐based framework for cluster scheduling based on a generic and realistic clustered machine model. The proposed scheme effectively utilizes the exact knowledge of available communication slots, functional units, and load on different clusters as well as future resource and communication requirements known only at schedule time. The proposed graph‐matching‐based framework for cluster scheduling resolves the phase‐ordering and fixed‐ordering problem associated with earlier schemes for scheduling clustered VLIW architectures. The experimental evaluation in the context of a state‐of‐art commercial clustered architecture (using real‐world benchmark programs) reveals a significant performance improvement over the earlier proposals, which were mostly evaluated using compiled simulation of hypothetical clustered architectures. Our results clearly highlight the importance of considering the peculiarities of commercial clustered architectures and the hard‐nosed performance measurement. Copyright © 2007 John Wiley & Sons, Ltd.
IPFViewer a visual analysis system for hierarchical ensemble data

Analyzing ensemble data is very challenging due to the complexity of the task. In this paper, we describe IPFViewer, a visual analysis system for ensemble data, that is hierarchical, multidimensional and multimodal. The exemplary data set comes from a steel production facility and comprises data about their melting charges, samples and defects. Our system differs from existing ones in that it encourages the usage of side-by-side visualization of ensemble members. Besides trend analysis, outlier detection and visual exploration, side-by-side visualization of detailed ensemble members enables rapid checking for repeatability of single ensemble member analysis results. IPFViewer supports the following data interaction methods: Hierarchical sorting and filtering, reference data selection, automatic percentile selection and ensemble member aggregation, while the focus for visualization is on small multiples of multiple views.
Boosting cross-media retrieval via visual-auditory feature analysis and relevance feedback

Different types of multimedia data express high-level semantics from different aspects. How to learn comprehensive high-level semantics from different types of data and enable efficient cross-media retrieval becomes an emerging hot issue. There are abundant statistical and semantic correlations among heterogeneous low-level media content, which makes it challenging to query cross-media data effectively. In this paper, we propose a new cross-media retrieval method based on short-term and long-term relevance feedback. Our method mainly focuses on two typical types of media data, i.e. image and audio. First, we build multimodal representation via statistical canonical correlation between image and audio feature matrices, and define cross-media distance metric for similarity measure; then we propose optimization strategy based on relevance feedback, which fuses short-term learning results and long-term accumulated knowledge into the objective function. Experiments on image-audio dataset have demonstrated the superiority of our method over several existing algorithms.
On the Parallel Execution Time of Tiled Loops

Many computationally-intensive programs, such as those for differential equations, spatial interpolation, and dynamic programming, spend a large portion of their execution time in multiply-nested loops that have a regular stencil of data dependences. Tiling is a well-known compiler optimization that improves performance on such loops, particularly for computers with a multilevel hierarchy of parallelism and memory. Most previous work on tiling is limited in at least one of the following ways: they only handle nested loops of depth two, orthogonal tiling, or rectangular tiles. In our work, we tile loop nests of arbitrary depth using polyhedral tiles. We derive a prediction formula for the execution time of such tiled loops, which can be used by a compiler to automatically determine the tiling parameters that minimizes the execution time. We also explain the notion of rise, a measure of the relationship between the shape of the tiles and the shape of the iteration space generated by the loop nest. The rise is a powerful tool in predicting the execution time of a tiled loop. It allows us to reason about how the tiling affects the length of the longest path of dependent tiles, which is a measure of the execution time of a tiling. We use a model of the tiled iteration space that allows us to determine the length of the longest path of dependent tiles using linear programming. Using the rise, we derive a simple formula for the length of the longest path of dependent tiles in rectilinear iteration spaces, a subclass of the convex iteration spaces, and show how to choose the optimal tile shape.
Convergence of optical and millimeter-wave broadband wireless access networks

This paper discusses hybrid fiber optic access network architectures combining baseband wireline and mm-wave channels. We focus on mm-wave radio over fiber (RoF) optical access network architectures which combine radio subcarrier multiplexing techniques to improve system efficiency with fiber dispersion mitigation provided by optical single sideband modulation techniques. Besides discussing the network architecture we focus on the intermodulation effects arising from the nonlinear characteristics of the optical modulator and the reflective semiconductor optical amplifier.
Tracking algorithm using background-foreground motion models and multiple cues [surveillance video applications]

We present a stochastic tracking algorithm for surveillance videos where targets are dim and of low resolution. Our tracker is mainly based on the particle filter algorithm. Two important novel features of the tracker include: a motion model consisting of both background and foreground motion parameters; multiple cues are adaptively integrated in a system observation model when estimating the likelihood functions. Based on these features, the accuracy and robustness of the tracker has been improved, which is very important for surveillance problems. We present the results of applying the proposed algorithm to many videos.