Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Model for the Equilibrium Shape of Raindrops

Abstract The equilibrium shape of raindrops has been determined from Laplace's equation using an internal hydrostatic pressure with an external aerodynamic pressure based on measurements for a sphere but adjusted for the effect of distortion. The drop shape was calculated by integration from the upper pole with the initial curvature determined by iteration on the drop volume. The shape was closed at the lower pole by adjusting either the pressure drag or the drop weight to achieve an overall force balance. Model results provide bounds on the axis ratio of raindrops with an uncertainty of about 1% and very good agreement with extensive wind tunnel measurements for moderate to large water drops. The model yields the peculiar asymmetric shape of raindrops: a singly curved surface with a flattened base and a maximum curvature just below the major axis. A close match was found between model shapes and profiles obtained from photos of water drops for diameters up to 5 mm. Coefficients are provided for computing.
Temperature Measurements in a Gas-Turbine-Combustor Sector Rig Using Swept-Wavelength Absorption Spectroscopy

Gas-temperature measurements in the combustion zone of a high-pressure gas-turbine-combustor sector rig were made with a Fourier-domain mode-locked laser using wavelength-agile absorption-spectroscopy techniques. These measurements are among the first employing broadband high-resolution absorption spectroscopy in gas-turbine-engine environments. Compared with previous measurements in reciprocating engines and shock tubes, signal contamination from thermal emission was stronger in this combustor rig; methods for managing emission during experimental planning and postprocessing are discussed. H 2 O spectra spanning 1330―1380 nm (which includes the ν 1 + ν 3 and 2ν 1 overtone bands) are presented along with a method for calculating gas temperatures from the spectra. The resulting temperatures are reported for a variety of combustor conditions. These tests show promise for simple gas-turbine sensors and potential for more detailed experiments involving tomographic reconstruction or multispecies concentration measurements.
LMI approach to delay-dependent robust stability for uncertain time-delay systems

New stability criteria are provided for a class of uncertain linear time-delay systems with time-varying delays. Based on Lyapunov–Krasovskii functionals combined with LMI techniques, simple and improved delay-dependent robust stability criteria given in terms of quadratic forms of state and LMI are derived. Examples show the performance of the application of the results presented.
Gyrokinetic simulations of ion and impurity transport

A systematic study of turbulent particle and energy transport in both pure and multicomponent plasmas is presented. In this study, gyrokinetic results from the GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] are supplemented with those from the GLF23 [R. E. Waltz, G. M. Staebler, W. Dorland et al., Phys. Plasmas 4, 2482 (1997)] transport model, as well as from quasilinear theory. Various results are obtained. The production of a particle pinch driven by temperature gradients (a thermal pinch) is demonstrated, and further shown to be weakened by finite electron collisionality. Helium transport and the effects of helium density gradient and concentration in a deuterium plasma are examined. Interestingly, it is found that the simple D-v (diffusion versus convective velocity) model of impurity flow is consistent with results obtained from nonlinear gyrokinetic simulations. Also studied is the transport in a 50-50 deuterium-tritium plasma, where a symmetry breaking is observed indicating.
On the number of permutations with constraints on their cycle lengths

We consider the set Sn,R of all permutations of degree n with cycle lengths from a fixed set R. Let an R be the number of elements in 5n,A. We assume that the generating function £ * of the set *€A R has the form P(z}/(\ — z), where P(z) is a polynomial, m is a fixed positive integer, and there exists an integer r such that for any non-negative integer s the set R Π {s + l, . , s -f r} cannot be imbedded in any integer lattice with step not equal to one. Under these conditions the asymptotics of the numbers αη>β is found. It is proved that, as η — » oo, where ρ is the density of the set A in the set of all natural numbers, and Γ is the gamma function.
Transient Behavior of Turbomachineries: Applications to Radial Flow Pump Startups

A theoretical analysis of the fast transients of turbomachineries, based on the study of unsteady and incompressible fluids mechanics equations applied to an impeller, is proposed. It leads to internal torque, internal power, and impeller head of an impeller during transient periods. The equations show that the behavior of a pump impeller is not only depending on the acceleration rate and flow rate, as it is usually admitted, but also on velocity profiles and their evolution during the transient. Some hypotheses on the flow in a radial flow pump are proposed. They are validated by comparison with the experimental results of a single stage, single volute radial flow pump during some fast acceleration periods. The model is also used to analyze the behavior of the pump during a fast startup.
Functional connectivity favors aberrant visual network c-Fos expression accompanied by cortical synapse loss in amyloidosis

While Alzheimer’s disease (AD) has been extensively studied with a focus on cognitive networks, sensory network dysfunction has received comparatively less attention despite compelling evidence of its significance in both Alzheimer’s disease patients and mouse models. We recently found that neurons in the primary visual cortex of an amyloid mouse model exhibit an imbalance of postsynaptic structures favoring neuronal hyperactivity alongside increased c-Fos expression, which regulates plasticity and memory. Here, we investigate aberrant visual network and brain-wide c-Fos expression and functional connectivity patterns, network responses to light deprivation, and visual system presynaptic deficits of a mouse model of Alzheimer’s disease. We found that the mouse model of AD exhibits aberrant c-Fos expression and functional connectivity patterns across multiple brain regions, and functional connectivity between brain regions is a significant predictor for aberrant c-Fos expression. We also show that one week of light deprivation increases c-Fos expression across the brain in nonpathological controls but not the AD model, indicating experience-dependent plasticity deficits in multiple brain regions. Using in vivo and ex vivo imaging of presynaptic termini, we found that aberrant visual cortical c-Fos expression is associated with selective loss of excitatory cortical but not inhibitory or subcortical synapses. Our findings reveal novel structural and functional connectivity deficits in the visual network pre-plaque amyloidosis.
The assembly landscape of the complete B-repeat superdomain from Staphylococcus epidermidis strain 1457

The accumulation-associated protein (Aap) is the primary determinant of Staphylococcus epidermidis device-related infections. The B-repeat superdomain is responsible for intercellular adhesion that leads to the development of biofilms occurring in such infections. It was recently demonstrated that Zn-induced B-repeat assembly leads to formation of functional amyloid fibrils, which offer strength and stability to the biofilm. Rigorous biophysical studies of Aap B-repeats from S. epidermidis strain RP62A revealed Zn-induced assembly into a stable, reversible dimer and tetramer, prior to aggregation into amyloid fibrils. Genetic manipulation is not tractable for many S. epidermidis strains, including RP62A; instead, many genetic studies have used strain 1457. Therefore, to better connect findings from biophysical and structural studies of B-repeats to in vivo studies, the B-repeat superdomain from strain 1457 was examined. Differences between the B-repeats from strain RP62A and 1457 include the number of B-repeats, which has been shown to play a critical role in assembly into amyloid fibrils, as well as the distribution of consensus and variant B-repeat subtypes, which differ in assembly competency and thermal stability. Detailed investigation of the Zn-induced assembly of the full B-repeat supderdomain from strain 1457 was conducted using analytical ultracentrifugation. Whereas the previous construct from RP62A (Brpt5.5) formed a stable tetramer prior to aggregation, Brpt6.5 from 1457 forms extremely large stable species on the order of 28- and 32-mers, prior to aggregation into similar amyloid fibrils. Importantly, both assembly pathways proceed through the same mechanism of dimerization and tetramerization, and both conclude with the formation of amyloid-like fibrils. Theoretical discussions of the energy landscape of B-repeats from different strains and of different length are provided with considerations of biological implications. Statement of Significance Staphylococcus epidermidis is a major pathogen responsible for device-related infections. The primary factor responsible for such infections is the accumulation-associated protein, Aap, through its ability to mediate formation of dense surface-adherent communities of bacteria known as biofilms. Our lab recently demonstrated that the B-repeat superdomain of Aap from strain RP62A undergoes Zn-dependent assembly to form functional amyloid fibrils that improve the strength and resilience of biofilms in vitro. These amyloid fibrils may be responsible for the difficulty in treating device-related infections. However, strain 1457 is commonly used for genetic manipulation. In this manuscript, the Zn-dependent assembly of B-repeats from strain 1457 is shown to lead to the same outcome of amyloidogenesis, although it occurs through different intermediate oligomeric states.
Bouts of rest and physical activity in C57BL/6J mice

The objective was to exploit the raw data output from a scalable home cage (type IIL IVC) monitoring (HCM) system (DVC®), to characterize pattern of undisrupted rest and physical activity (PA) of C57BL/6J mice. The system’s tracking algorithm show that mice in isolation spend 67% of the time in bouts of long rest (≥40s) and 59 % of the time was interpreted as sleep. Twenty percent is physical activity (PA), split equally between local movements and locomotion. Decomposition revealed that a day contains ∼6500 discrete bouts of short and long rest, local and locomotor movements. Mice travel ∼330m per day, mainly during the dark hours, while travelling speed is similar through the light-dark cycle. Locomotor bouts are usually <0.2m and <1% are >1m. Tracking revealed also fits of abnormal behaviour. The starting positions of the bouts showed no preference for the rear over the front of the cage floor, while there was a strong bias for the peripheral (75%) over the central floor area. The composition of bouts has a characteristic circadian pattern, however, intrusive husbandry routines increased bout fragmentation by ∼40%. Extracting electrode activations density (EAD) from the raw data yielded results close to those obtained with the tracking algorithm, with 59% of time in long rest (<1 EAD s-1) and 20% in PA. We confirm that EAD correlates closely with movement distance (rs >0.95) and the data agreed in ∼96% of the file time. Thus, albeit EAD being less informative it may serve as a proxy for PA and rest, enabling monitoring group housed mice. The data show that a change in housing density from one to two, and up to three mice had the same effect size on EAD (∼2) with no difference between sexes. The EAD deviated significantly from this stepwise increase with 4 mice per cage, suggesting a crowdedness stress inducing sex specific adaptations. We conclude that informative metrics on rest and PA can be automatically extracted from the raw data flow in near-real time (< 1 hrs). These metrics relay useful longitudinal information to those that use or care for the animals.
Optimization of molecular methods for detection and quantification of specific duckweed-bacteria interactions

Bacterial colonization dynamics of plants can differ between phylogenetically similar bacterial strains as well as in the context of complex bacterial communities. Quantitative studies that can resolve closely related bacteria within complex communities can lead to a better understanding of plant-microbe interactions. However, current methods lack the specificity to differentiate phylogenetically similar bacterial strains. In this study, we describe molecular strategies to study specific duckweed-bacteria interactions. We first systematically optimized a bead-beating protocol to co-isolate nucleic acids simultaneously from duckweed and bacteria. We then developed a generic fingerprinting assay to detect bacteria present in duckweed samples. To detect specific duckweed-bacteria interactions, we developed a genomics-based computational pipeline to generate bacterial strain-specific primers. These strain-specific primers differentiated bacterial strains from the same genus and enabled the detection of specific duckweed-bacteria interactions present in a community context. Moreover, we used these strain-specific primers to quantify the bacterial colonization of duckweed by normalization to a plant reference gene and revealed differences in colonization levels between strains from the same genus. Lastly, confocal microscopy of inoculated duckweed further supported our PCR results and showed bacterial colonization of the duckweed root-frond interface and root interior. The molecular methods introduced in this work should enable the tracking and quantification of specific plant-microbe interactions within plant-microbial communities.
The neuron mixer and its impact on human brain dynamics

A signal mixer made of a transistor or a diode facilitates rich computation, which has been the building block of modern telecommunications. The mixing produces new signals at the sum and difference frequencies of the input, thereby enabling powerful operations such as frequency conversion (aka heterodyning), phase detection, and multiplexing. Here, we report that a neural cell is also a signal mixer. We found through ex-vivo and in-vivo whole-cell measurements that neurons mix exogenous (controlled) and endogenous (spontaneous) subthreshold membrane potential oscillations, producing new oscillation frequencies. We show, using pharmacological manipulation, that the neural mixing originates in the voltage-gated ion channels. Furthermore, we demonstrate that the neural mixing dynamic is evident in human brain activity and is associated with cognitive functions. We found that the human electroencephalogram (EEG) displays distinct clusters of local and inter-region mixing interactions. By quantifying the strength of these interactions before a task, we show that converting the salient posterior alpha-beta oscillations into gamma-band oscillations regulates the visual attention state. Neural circuit oscillations have been observed in nearly every cognitive domain and species, and abnormal spectra of neural oscillations have been found in almost all brain disorders. Signal mixing enables individual neurons to actively sculpt the spectrum of their circuit oscillations and utilize them for computational operations, which have only been seen in modern telecommunication until now.
Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks

Primates can recognize objects despite 3D geometric variations such as in-depth rotations. The computational mechanisms that give rise to such invariances are yet to be fully understood. A curious case of partial invariance occurs in the macaque face-patch AL and in fully connected layers of deep convolutional networks in which neurons respond similarly to mirror-symmetric views (e.g., left and right profiles). Why does this tuning develop? Here, we propose a simple learning-driven explanation for mirror-symmetric viewpoint tuning. We show that mirror-symmetric viewpoint tuning for faces emerges in the fully connected layers of convolutional deep neural networks trained on object recognition tasks, even when the training dataset does not include faces. First, using 3D objects rendered from multiple views as test stimuli, we demonstrate that mirror-symmetric viewpoint tuning in convolutional neural network models is not unique to faces: it emerges for multiple object categories with bilateral symmetry. Second, we show why this invariance emerges in the models. Learning to discriminate among bilaterally symmetric object categories induces reflection-equivariant intermediate representations. AL-like mirror-symmetric tuning is achieved when such equivariant responses are spatially pooled by downstream units with sufficiently large receptive fields. These results explain how mirror-symmetric viewpoint tuning can emerge in neural networks, providing a theory of how they might emerge in the primate brain. Our theory predicts that mirror-symmetric viewpoint tuning can emerge as a consequence of exposure to bilaterally symmetric objects beyond the category of faces, and that it can generalize beyond previously experienced object categories.
Detection of tumor-derived extracellular vesicles interactions with immune cells is dependent on EV-labelling methods

Cell-cell communication within the complex tumor microenvironment is critical to cancer progression. Tumor-derived extracellular vesicles (TD-EVs) are key players in this process. They can interact with immune cells and modulate their activity, either suppressing or activating the immune system. Understanding the interactions between TD-EVs and immune cells is essential for understanding immune modulation by cancer cells. Fluorescent labelling of TD-EVs is a method of choice to study such interaction. This work aims to determine the impact of EV labelling methods on the detection of EV interaction and capture by the different immune cell types within human Peripheral Blood Mononuclear Cells (PBMCs), analyzed by imaging flow cytometry and multicolor spectral flow cytometry. EVs released by the triple-negative breast carcinoma cell line MDA-MB-231 were labeled either with the lipophilic dye MemGlow-488 (MG-488), with Carboxyfluorescein diacetate, succinimidyl ester (CFDA-SE), or through expression of a MyrPalm-superFolder GFP (sfGFP) that incorporates into EVs during their biogenesis using a genetically engineered cell line. Our results showed that these different labeling strategies, although analyzed with the same techniques, led to diverging results. While MG-488-labelled EVs incorporate in all cell types, CFSE-labelled EVs are restricted to a minor subset of cells and sfGFP-labelled EVs are mainly detected in CD14+ monocytes which are the main uptakers of EVs and other particles, regardless of the labeling method. Moreover, MG-488-labeled liposomes behaved similarly to MG-488 EVs, highlighting the predominant role of the labelling strategy on the visualization and analysis of TD-EVs uptake by immune cell types. Consequently, the use of different EV labeling methods has to be considered as they can provide complementary information on various types of EV-cell interaction and EV fate.
Measurement of bulk photovoltaic and photorefractive characteristics of iron doped LiNbO3

Birefringence changes induced in LiNbO3:Fe by a light beam have been measured to determine the photovoltaic characteristics such as the saturation value of space charge field, dielectric relaxation time, the probability φ of creating a free electron by an absorbed photon and the mean migration length L of the electron. These quantities are determined for different wavelengths covering the region 400–600 nm. The product φL that determines the photorefractive sensitivity of the material increases with decreasing wavelength. This increase is largely due to the increase of φ, the variation of the migration length being relatively small.
Assessing the Performance of an Ensemble Forecast System in Predicting the Magnitude and the Spectrum of Analysis and Forecast Uncertainties

AbstractThe ability of an ensemble to capture the magnitude and spectrum of uncertainty in a local linear space spanned by the ensemble perturbations is assessed. Numerical experiments are carried out with a reduced resolution 2004 version of the model component of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). The local ensemble transform Kalman filter (LETKF) data assimilation system is used to assimilate observations in three steps, gradually adding more realistic features to the observing network. In the first experiment, randomly placed, noisy, simulated vertical soundings, which provide 10% coverage of horizontal model grid points, are assimilated. Next, the impact of an inhomogeneous observing system is introduced by assimilating simulated observations in the locations of real observations of the atmosphere. Finally, observations of the real atmosphere are assimilated.The most important findings of this study are the following: predicting the magnitude of the.
Moment of momentum equation for curvilinear free-surface flow

The control volume approach in fluid mechanics relies upon the conservation of energy, momentum and angular momentum. However, open channel flows are typically related to only conservation of energy and momentum. Thus, for flows of non-uniform velocity and non-hydrostatic pressure distributions, the number of unknowns is larger than that of equations for depth-averaged models. This gap resulted in semi-empirical approaches either using momentum or using energy conservation. However, a more fundamental depth-averaged model may be developed by accounting for angular momentum balance. This basic approach was largely overlooked in hydraulic practice. The generalized form of the control volume conservation laws in curvilinear flow are presented herein, including the angular momentum balance. The development is used to prove that the classical Boussinesq-type solution does not satisfy the angular momentum balance. A more general Boussinesq approach is considered and applied to the 2D free overfall, indicating its ability to reproduce the salient flow features.
Performance Evaluation of Event-Triggered Model Predictive Control for Boost Converter

This paper evaluates the performance of an event-triggered model predictive control (MPC) for a DC-DC boost converter. Event-triggered MPC is used to enhance the computational performance of an enumeration-based MPC controlled boost converter by triggering the optimal control problem (OCP) only when an event is triggered as opposed to solving the OCP at every time step. Accordingly, the event-trigger threshold significantly impacts the number of times the OCP is solved. This paper numerically investigates such impact by evaluating various threshold values. The results of this study provide a general guidance to the selection of the threshold value to meet specific system criteria, e.g., balance between computation performance and control performance.