Miracle-dz/UniFAR-FTUs huggingface dataset:
0 10 60 85 v 2 7 J ul 2 00 1 Some Mathematical And Numerical Questions Connected With First And Second Order Time Dependent Systems Of Partial Differential Equations

There is a tendency to write the equations of general relativity as a first order symmetric system of time dependent partial differential equations. However, for numerical reasons, it might be advantageous to use a second order formulation like one obtained from the ADM equations. Unfortunately, the type of the ADM equations is not well understood and therefore we shall discuss, in the next section, the concept of wellposedness. We have to distinguish between weakly and strongly hyperbolic systems. Strongly hyperbolic systems are well behaved even if we add lower order terms. In contrast; for every weakly hyperbolic system we can find lower order terms which make the problem totally illposed. Thus, for weakly hyperbolic systems, there is only a restricted class of lower order perturbations which do not destroy the wellposedness. To identify that class can be very difficult, especially for nonlinear perturbations. In Section 3 we will show that the ADM equations, linearized around flat with constant lapse function and shift vector, are only weakly hyperbolic. However, we can use the trace of the metric as a lapse function to make the equations into a strongly second order hyperbolic system. Using simple models we shall, in Section 4, demonstrate that approximations of second order equations have better accuracy properties than the corresponding approximations of first order equations. Also, we avoid spurious waves which travel against the characteristic direction. In the last section we discuss some difficulties connected with the preservation of constraints.
EvidEncE to thE diagnostic ProcEss for giant cEll artEritis : how to UsE an articlE on thE clinical ManifEstations of disEasE Case and Discussion :

When patients seek care from physicians, they have 2 main concerns: What is wrong with me? What should be done about it? To address the first question we engage in the complex process of diagnosis, the outcome of which is essential for effective treatment (ie, addressing the second question). Four distinct forms of medical knowledge are recognized as key to the diagnostic process: knowledge of the clinical manifestations of disease, knowledge of diagnostic tests and how to interpret them, knowledge of which diseases cause clinical problems and their prevalence, and experience from taking care of actual patients [1]. While all are important to diagnosing conditions, knowledge of clinical manifestations is the only type that can be applied to all 3 steps of the diagnostic process: selecting a differential diagnosis and assigning pretest probability, selecting and interpreting diagnostic tests and assigning posttest probability, and verifying the final diagnosis [1–3]. Indeed, we spend much of our time in training learning how diseases present and making conclusions based on findings elicited directly from patients during the history and physical examination. Making a clinical diagnosis requires knowledge about the clinical manifestations that characterize a disease and differentiate it from other diagnoses. Without complete and accurate knowledge of the clinical manifestations of disease, we risk missing clues to the correct diagnosis that may be found in the initial clinical evaluation of a patient. We also may be erroneously drawn to a faulty differential diagnosis, which could lead us to make an inaccurate diagnosis or to pursue inappropriate interventions. This article provides guidance on how to search for, interpret, and apply information contained in articles about the clinical manifestations of disease, specifically to augment the diagnostic process.
Promoting Sustainable Consumer Behaviour Through the Activation of Injunctive Social Norms: A Field Experiment in 19 Workplace Restaurants

Since production and consumption are co-dependent parts of the same system, businesses often need to complement their production-side sustainability initiatives with accompanying measures aimed at promoting sustainable consumption. As a potential, low-cost measure of steering consumer choice we studied the activation of injunctive social norms by conducting a field experiment (N = 1,289) in 19 workplace restaurants. The aim was to investigate whether the presence and absence of two injunctive norm messages relating to Baltic Sea protection and local food predicted the choice of a novel sustainable dish, roach fish patties. Results of nested analysis of variance and qualitative comparative analysis suggest that while injunctive norm activation was an ineffective measure to steer consumer choice in the overall population, it may have had an impact on smaller subgroups based on sociodemographic characteristics and previous consumption patterns. Furthermore, there was indication of a mutually reinforcing interaction effect when the two injunctive norms were activated in combination.
Convergence of the implicit-explicit Euler scheme applied to perturbed dissipative evolution equations

We present a convergence analysis for the implicit-explicit (IMEX) Euler discretization of nonlinear evolution equations. The governing vector field of such an equation is assumed to be the sum of an unbounded dissipative operator and a Lipschitz continuous perturbation. By employing the theory of dissipative operators on Banach spaces, we prove that the IMEX Euler and the implicit Euler schemes have the same convergence order, i.e., between one half and one depending on the initial values and the vector fields. Concrete applications include the discretization of diffusion-reaction systems, with fully nonlinear and degenerate diffusion terms. The convergence and efficiency of the IMEX Euler scheme are also illustrated by a set of numerical experiments. (Less)
Wide dynamic range front-end amplifier for cell recording with microelectrode arrays

In a cell recording system, characteristics of the cell and microelectrode array (MEA) interface impose challenging requirements on the design of front-end amplifier with regard to input-referred noise, linearity, dynamic range (DR), input impedance, pitch size and differential electrode offset (DEO) cancellation. Previous front-end amplifier designs for cell recording demonstrated 2~7μVrms input referred noise and about 1% total harmonic distortion (THD) for dozens of mVpp input signal, which corresponds to about 60dB DR. However, front-end with wider DR is needed for many new cellular applications. This paper reports the design of a new wide DR front-end amplifier which uses chopping to suppress the noise, and a new current feedback scheme to improve the linearity. The new design is implemented in a 0. 35μm CMOS process. SPICE simulation shows that the new amplifier achieves THD lower than −70dB with 20mVpp input signal and 0. 75μVrms input-referred noise. For local field potentials (<200Hz), the DR extends to 80dB. The new amplifier has more than 0. 62GΩ input impedance at 20 kHz and consumes 20μW power.
Vascular Endothelial Cells Promote Acute Plasticity in Ependymoglial Cells of the Neuroendocrine Brain

Glial and endothelial cells interact throughout the brain to define specific functional domains. Whether endothelial cells convey signals to glia in the mature brain is unknown but is amenable to examination in circumventricular organs. Here we report that purified endothelial cells of one of these organs, the median eminence of the hypothalamus, induce acute actin cytoskeleton remodeling in isolated ependymoglial cells and show that this plasticity is mediated by nitric oxide (NO), a diffusible factor. We found that both soluble guanylyl cyclase and cyclooxygenase products are involved in this endothelial-mediated control of ependymoglia cytoarchitecture. We also demonstrate by electron microscopy that activation of endogenous NO release in the median eminence induces rapid structural changes, allowing a direct access of neurosecretory axons containing gonadotropin-releasing hormone (GnRH) (the neuropeptide controlling reproductive function) to the portal vasculature. Local in vivo inhibition of NO synthesis disrupts reproductive cyclicity, a process that requires a pulsatile, coordinated delivery of GnRH into the hypothalamic-adenohypophyseal portal system. Our results identify a previously unknown function for endothelial cells in inducing neuroglial plasticity and raise the intriguing possibility that endothelial cells throughout the brain may use a similar signaling mechanism to regulate glial-neuronal interactions.
Robot Guidance by Human Pointing

In the search for intuitive man-machine interfaces the visual recognition of human gestures would provide a powerful means to guide robot movements. In our paper we report on the development of the modular neural system \See-Eagle" for the visual guidance of robot pick-and-place actions. Several neural networks are integrated to a single system that visually recognizes human hand pointing gestures from stereo pairs of color video images. The accuracy of the pointing recognition system alone allows to estimate the pointing target to an accuracy of 2 cm in a workspace area of 50 50 cm. The output of the hand recognition stage is further processed by a set of color-sensitive neural networks to determine the cartesian location of the target object that is referenced by the pointing gesture. Finally, this information is used to guide a robot to pick the target object and place it at another location that can be speciied by a second pointing gesture. The accuracy of the combined system allows to identify the location of the referenced target object to an accuracy of 1 cm in a workspace area of 50 50 cm. In our current environment, this is suucient to pick and place arbitrarily positioned target objects within the workspace. The rapidly developing technology in the elds of robotics and virtual reality requires the development of new and more powerful interfaces for connguration and control of such devices. These interfaces should be intuitive for the human operator and comfortable to use. Practical solutions so far require the operator to wear a device that can transfer the necessary information. One typical example is the data glove 21, 19]. Clearly, in the long run solutions that are contactless will be much more desirable, and vision is one of the major modalities that appears especially suited for the realization of such solutions. In the present paper, we focus on a still restricted but very important task in robot control, the guidance of robot pick-and-place actions by unconstrained human pointing gestures in a realistic laboratory environment. The input of target locations by pointing gestures provides a powerful, very intuitive and comfortable functionality for a vision-based man-machine interface for guiding robots and extends previous work that focused on the detection of hand location or the discrimination of a small, discrete number of hand gestures only 14, 1, 2, 11]. Besides two color cameras, no special device is necessary to evaluate …
Strategic leadership and its contribution to improvements in teaching and learning in Higher Education

This paper aims to provide a strong conceptual underpinning for our project, ‘Strategic Leadership for Institutional Teaching and Learning Centres: Developing a Model for the 21st century’. The project intends to: 1. investigate the forms of leadership that are present and emerging in organisational Centres for teaching and learning and whether or not they are responding to the ‘organisational redesign’ that Marginson (2000, p.28) argued that the sector required. This involves close consideration of the ways in which institutional structures and distinctive organisational cultures are being shaped by strategic leadership stakeholders to enhance teaching and learning quality. And 2. develop a model of leadership that is anticipatory, innovative and creative, strategic and contingent and which directs particular professional development and approaches in support of central groups as they confront the challenges of the 21st century. This involves the development of a Teaching and Learning Strategic Leadership Framework for professional development purposes for capacity building of leadership personnel of institutional Centres for teaching and learning.
Real-time vehicle detection with a single camera using shadow segmentation and temporal verification

Vehicle detection with a monocular video sensor offers significant potential in a wide area of promising automotive applications. In this work the shadows in daylight scenes are used to detect vehicles in low-quality camera images and determine their positions and velocities in relation to the own vehicle. We propose a new algorithm that segments shadows in a top-down-view. In contrast to other works no specific thresholds or strong shadow edges are needed. Instead we binarize the image at multiple thresholds and analyze the results to generate vehicle position hypotheses. These hypotheses are verified with a RANSAC-based temporal verification approach. The accuracy of our method is evaluated using monocular real world sequences and ground truth data. Our algorithm works robustly under various lighting conditions in real-time at full video frame rate.
Interarrival statistics for time sharing systems

The optimization of tlme-shared system performance requires the description of the stochastic processes governing the user inputs and the program activity. This paper provides a statistical description of the user input process in the SDC-ARPA general-purpose Time.Sharing System (TSS). The input process is assumed to be stationary, and to be defined by the interarrival time distribution. The data obtained appear to justify satisfactorily the common assumption that the interarrival times are serially independent. The data do not appear to justify, except as a very rough approximation, the usual assumption of an exponential distribution for interarrival time. A much more satisfactory approximation to the data can be obtained with a biphase or trlphase hyperexponential distribution.
Developments and Trends in the Parallel Solutionof Linear

In this review paper, we consider some important developments and trends in algorithm design for the solution of linear systems concentrating on aspects that involve the exploitation of parallelism. We brieey discuss the solution of dense linear systems, before studying the solution of sparse equations by direct and iterative methods. We consider preconditioning techniques for iterative solvers and discuss some of the present research issues in this eld.
Assessment of diffusion and perfusion deficits in patients with small subcortical ischemia.

BACKGROUND AND PURPOSE Using perfusion- and diffusion-weighted MR imaging in acute ischemic stroke of the middle cerebral artery (MCA), previous studies have shown a typical pathophysiologic pattern that is characterized by a perfusion deficit larger than the diffusion lesion (mismatch), with the final lesion usually comprising the initial diffusion lesion (core) plus parts of the initial mismatch area. Little is known about underlying pathophysiology in small ischemic stroke. In this study, we used perfusion- and diffusion-weighted MR imaging to investigate the underlying pathophysiology of small subcortical ischemia. METHODS Six consecutive patients (age range, 42-76 years) with small subcortical ischemia were examined by using a 1.5-T MR system 2-5, 22-55, and 144-392 hours after the onset of symptoms. T2-weighted, diffusion-weighted imaging at b=0 s/mm2 and b=1000 s/mm2, and bolus-track perfusion-weighted imaging were performed. Lesion sizes were determined on the basis of T2-weighted findings as well as those of apparent diffusion coefficient (ADC) maps and CBF. RESULTS In every patient, the initial CBF lesion was smaller than the initial ADC lesion. Both the CBF lesion and the ADC lesion increased in size from first to second examination. In all instances, however, the CBF lesion remained smaller than the ADC lesion. The CBF lesion observed during the acute phase and the one seen on the following days were both smaller than the final T2 lesion. CONCLUSION Our data suggest that in contrast to previous findings in MCA ischemia in small subcortical infarcts tissue damage may spread beyond the area of the initial perfusion disturbance. In light of the small number of patients, further studies will have to address the relevance of this observation.
The Levels of Serum Low-Density Lipoprotein Cholesterol Using Direct Measurement in Healthy Japanese School Children

This study aimed to investigate the levels of serum low-density lipoprotein cholesterol (LDLC) using direct measurement in healthy Japanese school children. The subjects were 621 children (325 boys and 296 girls) aged 9 to 10 in the 4th grade, and 688 children (334 boys and 354 girls) aged 12 to 13 in the 7th grade. The levels of serum LDLC and high-density lipoprotein cholesterol were measured by direct determination (Cholestest LDL and Cholestest NHDL; Daiichi Pure Chemicals Co., Ltd., Tokyo, Japan). In boys in the 4th grade, the mean, the 75th, the 90th and the 95th percentiles of LDLC levels (mg/dl) were 91.6, 104, 124 and 134, respectively. In girls in the 4th grade, they were 92.8, 108, 122 and 130. In boys in the 7th grade, they were 83.4, 96, 113 and 123. In girls in the 7th grade, they were 93.0, 106, 126 and 137. Serum LDLC levels in boys in the 7th grade were lower than those of other groups. The direct measurement of serum LDLC level is useful for evaluation of dyslipidemia in healthy school children, because the method is applicable to non-fasting serum.
A GA-PSO layered encoding evolutionary approach to 0/1 knapsack optimization

This paper presents a layered encoding cascade evolutionary approach to solve a 0/1 knapsack optimization problem. A layered encoding structure is proposed and developed based on the schema theorem and the concepts of cascade correlation and multi-population evolutionary algorithms. Genetic algorithm (GA) and particle swarm optimization (PSO) are combined with the proposed layered encoding structure to form a generic optimization model denoted as LGAPSO. In order to enhance the finding of both local and global optimum in the evolutionary search, the model adopts hill climbing evaluation criteria, feature of strength Pareto evolutionary approach (SPEA) as well as nondominated spread lengthen criteria. Four different sizes benchmark knapsack problems are studied using the proposed LGAPSO model. The performance of LGAPSO is compared to that of the ordinary multi-objective optimizers such as VEGA, NSGA, NPGA and SPEA. The proposed LGAPSO model is shown to be efficient in improving the search of knapsack’s optimum, capable of gaining better Pareto trade-off front.
Sedimentary Carbon Oxidation and Denitrification on the Shelf Break of the Alaskan Beaufort and Chukchi Seas

Sediment-water fluxes were measured on transects across the northern Alaskan continental margin. Dissolved oxygen fluxes approximated total carbon dioxide fluxes when fluxes were low, but oxygen underestimated the higher total carbon dioxide fluxes. This follows a diagenetic model in which aerobic sediments occur below 86 � mol total carbon di- oxide m -2 h -1 and anaerobic conditions intensify with increased organic matter loading. The relationship between the fluxes of nitrogen gas and total carbon dioxide agreed with the Redfield ratio, indicating that regenerated nitrogen pre- dominantly returned to the overlying waters as nitrogen gas. On each transect, highest fluxes were found in a 20 km wide band located seaward of the 100 m continental shelf break. The magnitude of fluxes in these richer sediments exceeded that expected from the low productivity found on the outer continental shelf, suggesting upwelling-induced higher produc- tivity at the shelf break.
Iron Oxide Nanocrystals for Magnetic Hyperthermia Applications

Magnetic nanocrystals have been investigated extensively in the past several years for several potential applications, such as information technology, MRI contrast agents, and for drug conjugation and delivery. A specific property of interest in biomedicine is magnetic hyperthermia—an increase in temperature resulting from the thermal energy released by magnetic nanocrystals in an external alternating magnetic field. Iron oxide nanocrystals of various sizes and morphologies were synthesized and tested for specific losses (heating power) using frequencies of 111.1 kHz and 629.2 kHz, and corresponding magnetic field strengths of 9 and 25 mT. Polymorphous nanocrystals as well as spherical nanocrystals and nanowires in paramagnetic to ferromagnetic size range exhibited good heating power. A remarkable 30 °C temperature increase was observed in a nanowire sample at 111 kHz and magnetic field of 25 mT (19.6 kA/m), which is very close to the typical values of 100 kHz and 20 mT used in medical treatments.
A novel technique to measure data retention voltage of large SRAM arrays

This paper presents a new technique to accurately measure the data retention voltage (DRV) of large SRAM arrays in the presence of process variations. The proposed technique relies on a built-in-self-test (BIST) unit along with a DC-DC converter. The BIST unit implements a modified version of the March C- test that accounts for data retention faults. Whereas, the DC-DC converter is used to scale down the supply voltage of the array as is done when the array is in data retention mode. The proposed technique can accurately measure the DRV to ensure the SRAM operates at its minimum energy point. The circuit was developed in 90nm technology and simulated using HSPICE. Monte-Carlo simulation of 100k samples determined the DRV as 150mV whereas the proposed technique showed that the DRV of the SRAM under test could be lowered to 80mV which would result in significant power savings.
Hyperspectral remote sensing of phytoplankton assemblages in the ocean: Effects of the vertical distribution

The increasing availability of hyperspectral technology on remote sensing observing platforms provides marine scientists the potential to better map the phytoplankton community composition in the ocean globally. In this study, this approach is examined using unsupervised cluster techniques applied to data sets of hyperspectral remote sensing reflectance obtained by radiative simulations. Different oceanic environments in terms of phytoplankton biodiversity were satisfactorily classified. Furthermore, an assessment of the effect of a variable stratified water column scenario on the remote sensing reflectance points out that vertical distributions of phytoplankton communities along the water column play an essential role in the accurate phytoplankton assemblages mapping by remote sensing.
Monocular vision based distance estimation algorithm for pedestrian collision avoidance systems

This paper presents a novel and effective distance estimation algorithm based on monocular vision for pedestrian collision avoidance systems (PCAS). Vehicle - camera geometry and intrinsic parameters of camera are used to estimate the distances of pedestrians detected in front of the ego vehicle. An innovative method to estimate the pitch angle for the camera is provided in the proposed solution. The advantage of the intrinsic parameters based method is that the algorithm is computationally efficient to meet the real time requirements of the system. In addition to this, it takes into account the system requirements, in the sense, that instead of estimating point to point distance between the camera and the target pedestrian, the vertical distance is estimated with the help of vertical and pitch angles. Practical issues like pixel density per distance value shrinkage at higher distances, lens distortion and jitters are addressed and solutions to them are provided. In multiple experimental tests under real world driving conditions, it has been confirmed that the proposed solution works effectively with a minimal percentage mean error rate.