Miracle-dz/UniFAR-FTUs huggingface dataset:
Turbulence energetics in stably stratified geophysical flows: Strong and weak mixing regimes

Traditionally, turbulence energetics is characterised by turbulent kinetic energy (TKE) and modelled using solely the TKE budget equation. In stable stratification, TKE is generated by the velocity shear and expended through viscous dissipation and work against buoyancy forces. The effect of stratification is characterised by the ratio of the buoyancy gradient to squared shear, called the Richardson number, Ri. It is widely believed that at Ri exceeding a critical value, Ric, local shear cannot maintain turbulence, and the flow becomes laminar. We revise this concept by extending the energy analysis to turbulent potential and total energies (TPE, and TTE = TKE + TPE), consider their budget equations, and conclude that TTE is a conservative parameter maintained by shear in any stratification. Hence there is no ‘energetics Ric’, in contrast to the hydrodynamic‐instability threshold, Ric−instability, whose typical values vary from 0.25 to 1. We demonstrate that this interval, 0.25 < Ri < 1, separates two different turbulent regimes: strong mixing and weak mixing rather than the turbulent and the laminar regimes, as the classical concept states. This explains persistent occurrence of turbulence in the free atmosphere and deep ocean at Ri ≫ 1, clarifies the principal difference between turbulent boundary layers and free flows, and provides the basis for improving operational turbulence closure models. Copyright © 2008 Royal Meteorological Society
Multivariate Visualization of Oceanography Data Using Decals

In this paper, we present our results on the 2016 Compute Canada Visualization Contest, which centers around the visualization of multiple oceanographic data attributes. Our goal is to help researchers better understand the correlation between these attributes by providing an integrated data visualization. To accomplish this goal, we combine decals and colormaps in a layered fashion over temperature isosurfaces extracted from an oceanography model. We describe how decals can be deformed and animated over isosurfaces to convey the sense of ﬂow given by the ocean currents. Our visualization design focuses on addressing requirements from experts, tailored for such datasets. The results highlight the potential of our approach towards accessing the tridimensional multivariate nature of such complex data.
A Link Performance-based Failure Recovery Approach in SDN Data Plane

SDN is an innovative network architecture, which makes network programmable. Control plane and data plane are decoupled by southbound interface, and the network management are centralized to the control plane, which enables dynamic allocation of data plane resources to be achieved. Through the northbound interface of managed systems, operators issue commands to control plane to handle network events, such as failures occurred in data plane. However, in most of the failure recovery methods, there are only delay taken into account in the backup path selection, and there is no classification processing for flows. The losses caused by failure to different types of flows are different, thus different recovery strategies for flows need to be deployed. This paper chose several link parameters, designed formula to derive link performance parameters LPFP, and selected backup path based on it. In addition, this paper also designed algorithms to classify flows and designed different failure recovery strategies for them. Simulations show that when selecting backup path based on LPFP, the network throughput after failure recovery is higher, and the losses caused by failure will be smaller if there is classification processing for flows.
Zero Waste Biodiesel : Using Glycerin And Biomass To Create Renewable Energy

Biodiesel production creates glycerin as a byproduct. Although glycerin does have its commercial uses, even the current modest biodiesel production has outstripped US glycerin demand. We have combined this excess waste glycerin with waste biomass to produce combustible pellets as an alternative to coal for energy production. Our pellets produced an energy yield of ≈16 kJ/g, placing their energy content within the expected range for existing fuel pellet infrastructure. The pellets can be viably manufactured using simple manufacturing equipment, and can be combusted as fuel in existing fuel pellet and Coal burning facilities. This will greatly facilitate pellet production and adoption as an alternative fuel source in our increasingly resource-conscious world. F A C U L T Y m e n T o R Kawai Tam Department of Chemical and Environmental Engineering Sean Brady and recent graduates, Gregory Leung and Christopher Salam, are truly an inspiring team of committed, intelligent and professional individuals; it has been a pleasure being their faculty mentor. What started as an inspiration to fuel campus transportation vehicles with biodiesel manufactured from waste oil from food services, led the team to examine other waste streams that exist from the biodiesel process and other biomass waste materials available on campus. This waste stream analysis segued into a project that would investigate a potentially new fuel source of energy derived solely from waste materials. As the capstone senior design instructor and instructor in Green Engineering, I found this idea to be innovative because it featured the accounting of multiple waste streams in various life cycle analyses with a potentially beneficial result with immediate impact. As their faculty mentor, I provided guidance in their experimental design and framework of the project and mentorship as they developed proposals for student design competitions. The idea and work presented here earned recognition at the 2007 WERC environmental design competition with a U.S. Department of Agriculture award for innovative use of agricultural materials and a Phase I award at the 2007-2008 EPA P3 student design competition.
Autonomously and Simultaneously Refining Deep Neural Network Parameters by Generative Adversarial Networks

The choice of parameters, and the design of the network architecture are important factors affecting the performance of deep neural networks. However, there has not been much work on developing an established and systematic way of building the structure and choosing the parameters of a neural network, and this task heavily depends on trial and error and empirical results. Considering that there are many design and parameter choices, such as the number of neurons in each layer, the type of activation function, the choice of using drop out or not, it is very hard to cover every configuration, and find the optimal structure. In this paper, we propose a novel and systematic method that autonomously and simultaneously optimizes multiple parameters of any given deep neural network by using a generative adversarial network (GAN). In our proposed approach, two different models compete and improve each other progressively with a GAN-based strategy. Our proposed approach can be used to autonomously refine the parameters, and improve the accuracy of different deep neural network architectures. Without loss of generality, the proposed method has been tested with three different neural network architectures, and three very different datasets and applications. The results show that the presented approach can simultaneously and successfully optimize multiple neural network parameters, and achieve increased accuracy in all three scenarios.
On undercompressive shocks and flooding in countercurrent two-layer flows

We consider the countercurrent flow of two incompressible immiscible viscous fluids in an inclined channel. This configuration may lead to the phenomena of ‘flooding’, i.e. the transition from a countercurrent regime to a cocurrent regime. This transition is marked by a variety of transient behaviour, such as the development of large-amplitude waves that impede the flow of one of the fluids to the reversal of the flow of the denser fluid. From a lubrication approximation based on the ratio of the channel height to the downstream disturbance wavelength, we derive a nonlinear system of evolution equations that govern the interfacial shape separating the two fluids and the leading-order pressure. This system, which assumes fluids with disparate density and dynamic viscosity ratios, includes the effects of viscosity stratification, inertia, shear and capillarity. Since the experimental constraints for this effective system are unclear, we consider two ways to drive the flow: either by fixing the volumetric flow rate of the gas phase or by fixing the total pressure drop over a downstream length of the channel. The latter forcing results in a single evolution equation whose dynamics depends non-locally on the interfacial shape. From both of these driven systems, admissible criteria for Lax shocks, undercompressive shocks and rarefaction waves are investigated. These criteria, through a numerical verification, do not depend significantly on the inertial effects within the more dense layer. The choice of the local/non-local constraints appears to play a role in the transient growth of undercompressive shocks, and may relate to the phenomena observed near the onset of flooding.
Detecting between-individual differences in hind-foot length in populations of wild mammals

Hind-foot length is a widely used index of skeletal size in population ecology. The accuracy of hind-foot measure- ments, however, has not been estimated. We quantified measurement error in adult hind-foot length in yellow-bellied marmots (Marmota flaviventris (Audubon and Bachman, 1841)), mountain goats (Oreamnos americanus (de Blainville, 1816)), and bighorn sheep (Ovis canadensis Shaw, 1804) from long-term capture-recapture studies. Fitting a linear mixed effect model for each species separately, we found that hind-foot length was significantly repeatable in the three species, but repeatability was low, ranging from 0.30 to 0.47. Measurement error explained 53%-66% of the variance in foot length. Differences of 6, 13, and 27 mm would be indistinguishable from measurement error for marmots, goats, and sheep, respectively. At least 4-6 measures per individual were needed to detect variation in foot length between individuals of a population using a mixed effect model. Researchers should strive to limit measurement errors because inaccurate measures may obscure important biological patterns.
A differential-input, differential-output preamplifier topology for the design of ultra-low noise voltage amplifiers

We propose a simple topology for the realization of ultra low noise differential-input, differential-output preamplifiers. The input devices can be either low noise JFET pairs (for high impedance sources) or low noise BJT pairs (for minimum low frequency voltage noise). Besides the input devices, the circuit requires only two matched low noise BJT transistor pairs (either PNP or NPN, depending on the input device type) and a few excess noise free resistors for consistently obtaining differential gains of 100 (40 dB) with a bandwidth in excess of 100 kHz and an equivalent input noise floor comparable to (or better than) those reported in the literature for similar devices. The preamplifier is to be regarded as an off-the-shelf component that can be employed as a building block for a number of applications in the field of low frequency noise measurements.
Multimodal Light Microscopy Approaches to Reveal Structural and Functional Properties of Promyelocytic Leukemia Nuclear Bodies

The promyelocytic leukemia (pml) gene product PML is a tumor suppressor localized mainly in the nucleus of mammalian cells. In the cell nucleus, PML seeds the formation of macromolecular multiprotein complexes, known as PML nuclear bodies (PML NBs). While PML NBs have been implicated in many cellular functions including cell cycle regulation, survival and apoptosis their role as signaling hubs along major genome maintenance pathways emerged more clearly. However, despite extensive research over the past decades, the precise biochemical function of PML in these pathways is still elusive. It remains a big challenge to unify all the different previously suggested cellular functions of PML NBs into one mechanistic model. With the advent of genetically encoded fluorescent proteins it became possible to trace protein function in living specimens. In parallel, a variety of fluorescence fluctuation microscopy (FFM) approaches have been developed which allow precise determination of the biophysical and interaction properties of cellular factors at the single molecule level in living cells. In this report, we summarize the current knowledge on PML nuclear bodies and describe several fluorescence imaging, manipulation, FFM, and super-resolution techniques suitable to analyze PML body assembly and function. These include fluorescence redistribution after photobleaching, fluorescence resonance energy transfer, fluorescence correlation spectroscopy, raster image correlation spectroscopy, ultraviolet laser microbeam-induced DNA damage, erythrocyte-mediated force application, and super-resolution microscopy approaches. Since most if not all of the microscopic equipment to perform these techniques may be available in an institutional or nearby facility, we hope to encourage more researches to exploit sophisticated imaging tools for their research in cancer biology.
Male Gametophyte Development and Evolution in Extant Gymnosperms

The male gametophytes of gymnosperms are characterized by the diversities in pollen morphology, cellular composition and pattern of cell division, pollen tube morphology, sperm delivery, growth pattern through the ovule and nucellus, and pollen tube wall composition both within and among the four living orders, i.e., Cycadales, Ginkgoales, Coniferales, and Gnetales. At dehiscence, gymnosperm pollen grains contain a variable number of cells yet none have sperm at this stage. Pollen germination in the ovule usually occurs within a few hours or days in gnetophytes, about a week or so in conifers and Ginkgo, or after several months in cycads. Complete development of the male gametophytes typically involves two to five mitotic divisions. Evolution of the male gametophyte appears to have involved a reduction of its component cells with prothallial cells being among those reduced or eliminated. There is a shift in the site of sperm discharge from a proximal position in pollen grains of cycads and Ginkgo to distal in conifers and gnetophytes. Two methods of sperm delivery occur in gymnosperms: zooidogamy, defined by pollen tubes with motile sperm as exhibited in cycads and Ginkgo, and siphonogamy, defined by pollen tubes with non-motile sperm which are directly delivered into the egg as exhibited in conifers and gnetophytes. Different pollen tube morphologies occur in the nucellus, i.e., branched and haustorial in cycads and Ginkgo, and unbranched and non-haustorial in conifers and gnetophytes. Pollen tubes form heterotrophic relationships with the nucellus, but it is only in cycads that intracellular penetration results in significant destruction of the nucellus. Pollen tube walls of gymnosperms contain cellulose and arabinogalactan proteins; however, pectins are prevalent in cycads and mixed -glucan in Ginkgo. A standard terminology to describe the cellular composition of the male gametophytes in gymnosperms is proposed. _____________________________________________________________________________________________________________
Visualizing electrocardiographic information on a patient specific model of the heart

The treatment of atrial tachycardia by radio-frequency ablation is a complex and minimally invasive procedure. In most cases the surgeon uses fluoroscopic imaging to guide catheters into the atria. After recording activation potentials from the electrodes on the catheter, which has to be done for different catheter positions, the physiologist has to fuse both the activation times derived from the potentials with the fluoroscopic images and extract from these a 3D anatomical model of the atrium. This model will provide him with the necessary information to locate the ablation regions. To alleviate the problem of mentally reconstructing these different sources of information, we propose a virtual environment that has the ability to visualize the electrodes information onto a patient specific model of the atria. This 3D atrium surface model is derived from pre-operatively taken MR-images. Within the system this model is visualized in 3 different ways: two views correspond to the 2 fluoroscopes images, which are shown registred in the background while the third one can be freely manipulated by the physiologist. The system allows to annotate measurements onto the 3D model. Since the heart is not a static organ, tools are provided to modify previous annotations interactively. The information contained in the measurements can than be dispersed across the heart after extrapolation and interpolation and subsequently visualized by color coding the surface model. Preliminary clinical evaluation on 30 patients indicates that the combined representation of the activation times and the heart model provides a thorough and more accurate insight into the possible causes and solutions to the tachycardia than would be obtained using solely the fluoroscopes images and mental reconstruction. Unlike other tachycardia visualization software, our approach starts with a patient specific surface model which in itself provides extra insight into the problem. Furthermore it can be used very interactively by the physiologist as a kind of 3D sketchbook where he can enter, delete, . different measurements, tissue types. Finally, the system can visualize at any stage of the surgery a model containing all information at hand. In this paper we present a system to represent electrocardiographic information that allows the physiologist to mark measurements which can than be visualized on a patient specific atrium model by color coding. First clinical evaluation indicates that this approach offers a considerable amount of added value.
Inter and intra-observer reliability in histologic evaluation of necrosis rate induced by neo-adjuvant chemotherapy for osteosarcoma

Purpose: Tumor necrosis rate following neo-adjuvant chemotherapy is one of the most important prognostic factors for patients with osteosarcoma, and it also provides the basis for selection of postoperative adjuvant chemotherapy. However, reported necrosis rates for the same tumors can vary among pathologists, complicating decision making for further treatment. Methods: Ten H&E stained pathology slides from 10 osteosarcoma patients treated with neo-adjuvant chemotherapy were randomly selected. Six expert pathologists were assigned to analyze the slides for tumor necrosis rate at four time points, with an interval of 3 weeks. Intraclass and interclass correlation coefficients (IntraCC & InterCC) and 95% confidence intervals (CI) were calculated. Results: The overall InterCC among the 6 observers was 0.652 (95% CI 0.294-0.820) for tumor necrosis rate (range: 0-100%), suggesting good reliability. IntraCCs were 0.799, 0.788, 0.867, 0.935, 0.962, and 0.947 respectively. The interCC among higher careers and lower careers were 0.603 (95% CI.: 0.387-0.843) and 0.696 (95% C.I.: 0.487-0.919), respectively, which was not significantly different. Major differences in tumor necrosis estimation were due to interpretation of areas with isolated atypical cells in fibrotic stroma. Conclusion: Low inter-observer and relatively high intra-observer reliability were observed in the histologic evaluation of necrosis rate after neo-adjuvant chemotherapy. The interCCs between the higher career and lower career groups did not vary. These findings suggest that a valid measurement protocol for tumor necrosis rate evaluation after chemotherapy is required to improve the clinical relevance of the quantification of response to neo-adjuvant therapy.
Thoughts on object detection using convolutional neural networks for forward-looking sonar

This work reviews the problem of detection in Forward-Looking Sonar images. In the underwater realm, most of the imaging is done by acoustic means, i.e. sonar. The Forward-Looking Sonar usually has a very low Signal to Noise Ratio therefore object detection in Forward-Looking Sonar images is still an open issue. The article will introduce our database and some conclusions that were gathered from working with it. It will also show results from a Convolutional Neural Network designed for Forward-Looking Sonar Images.
Endogenous Sunk-Costs Technology and Home Market Effects

Sutton (1991, 1998) proves that the home market effects would reverse with the assumption of the labor requirements with endogenous sunk costs. Departing from the original Helpman-Krugman modeling assumptions, we introduce the endogenous sunk costs of production to trading partners, and show that home market effects will be offset but not reverse, a result opposite of Sutton (1991, 1998).
The Data Readiness Problem for Relational Databases

We consider the problem of determining whether organizations facing a new data-transformation task can avoid building a new transformation procedure from scratch by reusing their stored procedures. Because it can be difficult to obtain exact descriptions of what stored procedures do, our framework abstracts data-transforming tools as black-box procedures, in which a procedure description indicates the parts of the database that might be modified by the procedure and constraints on the states of the database that must hold before and after the application of this procedure. In this paper we present our framework and study the problem of determining, given a database and a set of procedures, whether there is a sequence of procedures from this set such that their application to the database results in the satisfaction of a boolean query. This data readiness problem is undecidable in general, but we show decidability for a broad and realistic class of procedures.
Apparatus to search for optical flashes of extragalactic origin

An apparatus is described to search for optical, point-like flashes in the sky at the time scale of seconds. Such flashes are expected to accompany gamma ray bursts (GRB) observed routinely by satellites and proven to be of extragalactic origin. So far only one such flash has been recorded shortly after the GRB, because standard methods of observational astronomy are not suitable for the time scale of seconds. In this paper, a novel approach is proposed based on experience from particle physics experiments. An apparatus is described which monitors the sky continuously. The large data stream is analysed on-line and potentially interesting events are selected by a multilevel trigger system. In the first phase of the project the apparatus consists of two CCD cameras, especially designed for this project and a robotic mount used to scan interesting regions of the sky. In the second phase the experiment will consist of two sets of 16 cameras on fixed mounts, covering almost all visible sky.
Conical open mapping theorems and regularity

Suppose $T$ is a continuous linear operator between two Hilbert spaces $X$ and $Y$ and let $K$ be a closed convex nonempty cone in $X$. We investigate the possible existence of $\delta > 0$ such that $\delta B_Y \cap T(K) \subseteq T(B_X \cap K)$, where $B_X,B_Y$ denote the closed unit balls in $X$ and $Y$ respectively. This property, which we call openness relative to $K$, is a generalization of the classical openness of linear operators. We relate relative openness to Jameson's property~(G), to the strong conical hull intersection property, to bounded linear regularity, and to metric regularity. Our results allow a simple construction of two closed convex cones that have the strong conical hull intersection property but fail to be boundedly linearly regular.