Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in the Localization of Polyamine Spermidine in the Rat Retina with Age

Polyamines (PAs) in the nervous system has a key role in regeneration and aging. Therefore, we investigated age-related changes in the expression of PA spermidine (SPD) in the rat retina. Fluorescent immunocytochemistry was used to evaluate the accumulation of SPD in retinae from rats of postnatal days 3, 21, and 120. Glial cells were identified using glutamine synthetase (GS), whereas DAPI, a marker of cell nuclei, was used to differentiate between retinal layers. SPD localization in the retina was strikingly different between neonates and adults. In the neonatal retina (postnatal day 3-P3), SPD is strongly expressed in practically all cell types, including radial glia and neurons. SPD staining showed strong co-localization with the glial marker GS in Müller Cells (MCs) in the outer neuroblast layer. In the weaning period (postnatal day 21-P21), the SPD label was strongly expressed in all MCs, but not in neurons. In early adulthood (postnatal day 120-P120), SPD was localized in MCs only and was co-localized with the glial marker GS. A decline in the expression of PAs in neurons was observed with age while glial cells accumulated SPD after the differentiation stage (P21) and during aging in MC cellular endfoot compartments.
U p -Net: a generic deep learning-based time stepper for parameterized spatio-temporal dynamics

In the age of big data availability, data-driven techniques have been proposed recently to compute the time evolution of spatio-temporal dynamics. Depending on the required a priori knowledge about the underlying processes, a spectrum of black-box end-to-end learning approaches, physics-informed neural networks, and data-informed discrepancy modeling approaches can be identiﬁed. In this work, we propose a purely data-driven approach that uses fully convolutional neural networks to learn spatio-temporal dynamics directly from parameterized datasets of linear spatio-temporal processes. The parameterization allows for data fusion of ﬁeld quantities, domain shapes, and boundary conditions in the proposed U p -Net architecture. Multi-domain U p -Net models, therefore, can generalize to different scenes, initial conditions, domain shapes, and domain sizes without requiring re-training or physical priors. Numerical experiments conducted on a universal and two-dimensional wave equation and the transient heat equation for validation purposes show that the proposed U p -Net outperforms classical U-Net and conventional encoder–decoder architectures of the same complexity. Owing to the scene parameterization, the U p - Net models learn to predict refraction and reﬂections arising from domain inhomogeneities and boundaries. Generalization properties of the model outside the physical training parameter distributions and for unseen domain shapes are analyzed. The deep learning ﬂow map models are employed for long-term predictions in a recursive time-stepping scheme, indicating the potential for data-driven forecasting tasks. This work is accompanied by an open-sourced code.
A new algorithm for the extrinsic calibration of a 2D LIDAR and a camera

In this paper, we propose a new extrinsic calibration algorithm for a camera and a 2D LIght Detection And Ranging sensor (LIDAR). N plane-line correspondences are used to establish geometric constraints for computing the extrinsic parameters. The existing algorithms that use the same constraints either require N ≥ 5 or focus on the minimal solution for N = 3. In contrast, the proposed algorithm is effective for all N ≥ 3. This is made possible by decoupling the initial estimation of rotation from translation and imposing the orthonormal constraints on the computation of rotation. When the rotation matrix is obtained, the estimation of translation is reduced to solving a linear least-squares problem. Then an iterative procedure is followed to refine the initial estimation. This algorithm gives a new minimal solution, which can be used as the hypothesis generator in the RANdom SAmple Consensus (RANSAC) algorithm. Simulation and real experimental results show that the proposed algorithm outperforms the state-of-the-art ones.
Words Similarities on Personalities: A Language-Based Generalization Approach for Personality Factors Recognition

The evaluation of personality traits allows the study of human behavior in different environments, but it is not a trivial task. In this sense, the Five-Factor Model (FFM) allows, in a global way, the assessment of personality traits of individuals using textual data. However, there is a scarcity of lexical resources for languages other than English, which generated the main research question of this work: “Can models trained to predict FFM personality traits using English textual data show satisfactory results when applied to textual data in other languages? ”. Therefore, this work aims to answer: (i) Whether Word Embeddings techniques could be used to solve low resources languages problems in FFM personality traits prediction; and (ii) Whether is feasible to train a traditional Machine Learning algorithm with English language textual data and evaluate its performance with Brazilian Portuguese language textual data for FFM personality traits prediction. Thus, the work aims to present an approach in which the models can be used to learn the highest level of abstraction. As results, was observed that the difference in performance between the models trained for personality recognition in English is minimal when used to predict FFM personality traits in Brazilian Portuguese texts. In this task, the Stochastic Gradient Descent model presented the best average results among the FFM personality traits of the models analyzed.
Atomic disorder effects on half-metallicity of the full-Heusler alloys Co 2 ( Cr 1 − x Fe x ) Al : A first-principles study

We investigate the atomic disorder effects on the half-metallicity of the full-Heusler alloy ${\mathrm{Co}}_{2}({\mathrm{Cr}}_{1\ensuremath{-}x}{\mathrm{Fe}}_{x})\mathrm{Al}$ from first principles by using the Korringa-Kohn-Rostoker method with the coherent potential approximation. Our results show that disorder between Cr and Al does not significantly reduce the spin polarization of the parent alloy ${\mathrm{Co}}_{2}\mathrm{CrAl},$ while disorder between Co and Cr makes a considerable reduction of the spin polarization. It is observed that the spin polarization of ${\mathrm{Co}}_{2}({\mathrm{Cr}}_{1\ensuremath{-}x}{\mathrm{Fe}}_{x})\mathrm{Al}$ decreases with increasing Fe concentration x in both the ordered ${L2}_{1}$ and the disordered $B2$ structures, and that the effects of the disorder on the spin polarization is significant at low Fe concentrations. The results suggest that a highly spin-polarized ferromagnet with high Curie temperature will be obtained if a ${\mathrm{Co}}_{2}({\mathrm{Cr}}_{1\ensuremath{-}x}{\mathrm{Fe}}_{x})\mathrm{Al}$ with the ordered ${L2}_{1}$ structure can be fabricated at low Fe concentrations.
Gravity Currents Produced by Sudden Release of a Fixed Volume of Heavy Fluid

In this paper we study various aspects of gravity (or density) currents arising from instantaneous releases of heavy fluids in a rectangular channel with a horizontal bottom. It is shown, by means of a scaling argument, that these plane currents can be successfully modeled by a two-by-two system in conservation form together with a pair of algebraic relations. A number of numerical experiments are carried out using this “weak stratification” model to elicit information concerning the behavior of gravity currents. A weakly nonlinear analysis is employed to clarify some aspects that were uncovered by the numerical experimentation.
UTILITY MAXIMIZATION IN A PURE JUMP MODEL WITH PARTIAL OBSERVATION

This article considers the asset price movements in a financial market when risky asset prices are modeled by marked point processes. Their dynamics depend on an underlying event arrivals process—a marked point process having common jump times with the risky asset price process. The problem of utility maximization of terminal wealth is dealt with when the underlying event arrivals process is assumed to be unobserved by the market agents using, as the main tool, backward stochastic differential equations. The dual problem is studied. Explicit solutions in a particular case are given.
Preventing Wormhole Attacks in Wireless Mesh Networks

In a wireless mesh network, the need for cooperation among wireless nodes to relay each others packets exposes the network to a wide range of security threats. A particularly devastating type of threats is the so-called wormhole attacks. In order to defense against the attack, a type of wormhole attack model and a watch nodes-based wormhole attack detection scheme were presented in this paper. The scheme that is based on the combination of a number of techniques, such as distributed voting, watch nodes based detection and identity-based cryptosystem. Qualitative analysis and simulation show that the wormhole attack detection scheme is more advantageous over the some of the previous schemes in terms of performance and cost.
A Survey of Trusted Computing Solutions Using FPGAs

Ensuring the security and privacy of computation and data management in the cloud and edge is an ever-important requirement. There are several working solutions today for trusted computing with general purpose processors, for instance, Intel SGX and ARM TrustZone. However, with the widespread commercial adoption of specialized hardware accelerators in the cloud and at the edge, most importantly FPGAs, two questions emerge: 1) How secure are they against threats? and 2) How could FPGAs be utilized for more efficient trusted computing? In this survey, we investigate these two questions precisely. Even though there have been numerous surveys in the past on the security of FPGAs, we believe it is timely to study the space of related work again, given the large number of data-centric applications aimed at targeting trusted execution environments that have recently appeared. Therefore, in addition to presenting an overview of state of the art, we also highlight some opportunities for FPGAs in the context of providing efficient trusted computation.
A micromechanical constitutive model for porous ferromagnetic shape memory alloys under magneto-mechanical coupling

Porous Ferromagnetic Shape Memory Alloys (FSMAs) have excellent magneto- mechanical properties, such as distinctive magnetic shape memory effect, pseudoelasticity, and porous characteristics. In this work, based on the Eshebly equivalent inclusion theory and Mori–Tanaka method, a three-phase micromechanical constitutive model for porous FSMAs under magneto-mechanical coupling is given. Numerical results of dense FSMAs are compared with the experimental data to verify the validity of the model. Then, the mechanical behaviors for porous FSMAs under magneto-mechanical coupling with different conditions are discussed. The results show that porous FSMAs variants with different reorientations have good pseudoelastic property, and the stress–strain and magnetic field-strain responses for porous FSMAs can be influenced significantly under different pore volume fractions. Besides, several other properties for porous FSMAs are also proposed, which will provide a reliable theoretical basis for the future research of these functional materials in practical applications. Graphical abstract
Linking the Intrinsic Electrical Response of Ferroelectric Devices to Material Properties by Means of Impedance Spectroscopy

Ferroelectric devices have gained attention in recent years as a potential solution for ultra-low power computing due to their ability to act as memory units and synaptic weights in brain-inspired architectures. One way to study the behavior of these devices under different conditions, particularly the influence of material composition and charge trapping on ferroelectric switching, is through impedance spectroscopy. However, the parasitic impedance of the metal lines that contact the electrodes of the device can affect the measured response and interpretation of the results. In this study, we examined the frequency response of ferroelectric tunnel junctions (FTJs) with a metal-dielectric-ferroelectric-metal (MDFM) stack at various voltages, starting from the analysis of single layer capacitors (MFM and MDM) to better interpret FTJ’s results. To accurately assess the intrinsic response of the device, we developed a method that estimates and removes the parasitic access impedance contribution, which was validated by means of physics-based simulations. This method allows quantifying the intrinsic device-level variability of FTJs and, for the first time, to investigate the relation between the thickness of the dielectric layer, the equivalent phase composition of the ferroelectric material, and the magnitude of the peak in the frequency response, often assumed to be related to charge trapping only.
Daily Microwave-Derived Surface Temperature over Canada/Alaska

Abstract The land surface temperature variation over northern high latitudes in response to the increase in greenhouse gases is challenging because of the lack of meteorological stations. A new method to derive the surface temperature from satellite microwave measurements that improves the frequency of measurements relative to that of infrared data is presented. The daily Special Sensor Microwave Imager 25 km × 25 km Equal-Area Scalable Earth Grid (EASE-Grid) dataset provided by the National Snow and Ice Data Center in Boulder, Colorado, is processed to derive the surface temperature using the method proposed by Fily et al. A normalization approach based on the 40-yr ECMWF reanalysis (ERA-40; 2.5°) temperature diurnal cycle fitted for each pixel is applied to overcome the time acquisition variation of measurements as well as to interpolate missing data. An adaptive mask for discriminating between ice-free pixels and snow-free pixels is also applied. The resulting database is thus a new consistent hourly s.
Three Varieties of Grape Pomace, with Distinctive Extractable:Non-Extractable Polyphenol Ratios, Differentially Reduce Obesity and Its Complications in Rats Fed a High-Fat High-Fructose Diet

Grape pomace is a commonly discarded by-product characterized by high extractable (EPP) and non-extractable (NEPP) polyphenol contents which exhibits anti-obesogenic effects. However, the relevance of each fraction needs to be elucidated. In this work, we examined the effects of three pomaces with different concentrations of EPPs and NEPPs on metabolic alterations associated with obesity. The NEPP:EPP ratio of the grape pomaces was 1.48 for Malbec, 1.10 for Garnacha, and 5.76 for Syrah grape varieties. Rats fed a high-fat high-fructose diet supplemented with Malbec grape pomace (HFFD + MAL) Syrah grape pomace (HFFD + SYR) or Garnacha grape pomace (HFFD + GAR) showed significantly less weight gain: 20%, 15%, and 12% less, respectively, compared to HFFD controls. The adiposity index was also significantly decreased by 20% in the HFFD + MAL and HFFD + SYR groups, and by 13% in the HFFD + GAR group. Serum triglycerides were significantly decreased by 46% in the HFFD + MAL group and by 31% in the HFFD + GAR group, compared to the HFFD group, but not in the HFFD + SYR group. All pomace supplementations regulated postprandial glucose in an oral glucose tolerance test. Therefore, grape pomaces containing both EPPs and NEPPs exert beneficial effects on body weight and glucose homeostasis, while EPPs seem to control triglyceride levels more effectively.
On the Performance of the Fluctuation Test for Structural Change

Abstract We discuss the performance of “closed-end” fluctuation tests, used to detect changes in the structural stability of a model, in the case where the time horizon is large and the observations do not possess high enough moments. It is demonstrated via a simulation study that, in the latter case, the choice of the boundary function should take into account the number of moments existing; otherwise the actual size of the test may exceed the nominal level. We suggest an alternative “open-end” fluctuation procedure and study its asymptotic behavior. It turns out that if an improper boundary function is chosen, then the null hypothesis may be rejected even if it is true. This means that an appropriate choice of the boundary function requires some prior information about the tail heaviness of the observations. This is different from the cumulative sum-based monitoring schemes suggested by Chu et al. (1996) and further studied by Horváth et al. (2004).
Gravity-driven flows in a turbulent fluid

The formation and destruction of a gravity current in a turbulent fluid is examined in laboratory experiments. The gravity current is produced by lock exchange and the fluid is kept turbulent by bubbling air from the base of the tank. When the lock is released the buoyancy forces associated with the reduced gravity g′ between the fluid on the two sides of the lock drives a counterflow, with the dense fluid slumping underneath the less-dense fluid, and a gravity current is formed. The current has a sharp density front at its leading edge, and a stable density stratification is established behind the front. The turbulence, characterized by a longitudinal turbulent diffusion coefficient K, tends to mix this stable stratification. Once the fluid is vertically mixed the gravity current front is destroyed, and the density varies smoothly with horizontal distance over a zone whose length increases with time owing to the continuing longitudinal turbulent diffusion and buoyancy driving. It is found that the gravity current propagates over a distance L1 before it is destroyed, where L1/H ≈ 0.08(g′H)½ H/K, and H is the fluid depth. At this point turbulent dissipation balances the buoyancy driving and frontogenesis is inhibited. The turbulent dispersion coefficient is found to increase with the buoyancy driving with K∞ Ri½, where Ri = g′H/q2 and q is the r.m.s. turbulence velocity fluctuations. It is also shown that when the turbulence level is reduced nonlinearities in the horizontal density gradient can sharpen up to form a front. The implications of these frontogenetical processes to the sea-breeze front and fronts in shallow seas is discussed.
Optimizing Cardiac Wireless Implant Communication: A Feasibility Study on Selecting the Frequency and Matching Medium

Cardiac wireless implantable medical devices (CWIMD) have brought a paradigm shift in monitoring and treating various cardiac conditions, including heart failure, arrhythmias, and hypertension. One of the key elements in CWIMD is the implant antenna which uses radio frequency (RF) technology to wirelessly communicate and transmit data to external devices. However, wireless communication with a deeply implanted antenna using RF can be challenging due to the significant loss of electromagnetic (EM) signal at the air–skin interface, and second, due to the propagation and reflection of EM waves from different tissue boundaries. The air–skin interface loss of the EM wave is pronounced due to the absence of a matching medium. This paper investigates the EM propagation losses in the human body and presents a choice of optimal frequency for the design of the cardiac implant antenna and the dielectric properties of the matching medium. First, the dielectric properties of all tissues present in the human thorax including skin, fat, muscle, cartilage, and heart are analyzed as a function of frequency to study the EM wave absorption at different frequencies. Second, the penetration of EM waves inside the biological tissues is analyzed as a function of frequency. Third, a transmission line (TL) formalism approach is adopted to examine the optimal frequency band for designing a cardiac implant antenna and the matching medium for the air–skin interface. Finally, experimental validation is performed at two ISM frequencies, 433 MHz and 915 MHz, selected from the optimal frequency band (0.4–1.5 GHz) suggested by our analytical investigation. For experimental validation, two off-the-shelf flexible dipole antennas operating at selected ISM frequencies were used. The numerical and experimental findings suggested that for the specific application of a cardiac implant with a penetration depth of 7–17 cm, the most effective frequency range for operation is within 0.4–1.5 GHz. The findings based on the dielectric properties of thorax tissues, the penetration depth of EM waves, and the optimal frequency band have provided valuable information on developing and optimizing CWIMDs for cardiac care applications.
Experimental and numerical investigation of thermal effects in end-pumped Cr/sup 4+/:forsterite lasers near room temperature

The results of a study which employs both experimental and theoretical methods to investigate the role of thermal effects in room-temperature Cr/sup 4+/:forsterite lasers are presented. A novel model was developed to calculate the incident threshold pump power required to attain oscillation by taking into account absorption saturation and pump-induced thermal loading in the gain medium. Experimentally, the incident threshold pump power was measured as a function of the crystal boundary temperature for three Cr/sup 4+/:forsterite laser crystals with different small-signal differential absorption coefficients /spl alpha//sub p0/ and/or cross-sectional areas. Excellent agreement was obtained between theory and experiment for values of the stimulated emission cross section comparable to those from previously reported data. The model was then used to numerically determine the optimum value of /spl alpha//sub p0/ which minimizes the incident threshold pump power in room-temperature Cr/sup 4+/:forsterite lasers. At a crystal boundary temperature of 15/spl deg/C, the optimum value of /spl alpha//sub p0/ was determined to be 0.64 cm/sup -1/ for a 2-cm-long Cr/sup 4+/:forsterite crystal, corresponding to an unsaturated absorption of 72%. The use of crystals with an optimum absorption coefficient should lead to the realization of highly efficient CW Cr/sup 4+/:forsterite lasers at room temperature.
Performance evaluation of redundant OPC UA architecture for process control

Classical control applications with a centralized logic and distributed input/output system are being replaced by dynamic environments of cooperating components. Thus, the OPC (Object Linking and Embedding for Process Control) UA (Unified Architecture) is becoming more popular, because the OPC Data Access substandard is not well suited for distributed systems. Moreover, in many production systems, redundant data servers are preferred, for financial and legal reasons. Providing performance evaluation gives an estimate of the time required (and data samples lost) to switch to a backup data source for redundant OPC UA architecture, depending on the failure detection method, number of variables and redundancy mode.