Miracle-dz/UniFAR-FTUs huggingface dataset:
Multispacecraft Measurement of Anisotropic Correlation Functions in Solar Wind Turbulence

Multispacecraft measurements in the solar wind are used to determine the field-aligned anisotropy of magnetohydrodynamic inertial range turbulence. The ratio of the parallel to perpendicular correlation lengths is measured by using time-lagged two-point correlations to construct a spatial autocorrelation function. The mean ratio obtained, 1.79 ± 0.36, is significantly greater than unity and therefore consistent with solar wind fluctuations being anisotropic with energy predominantly in wavevectors perpendicular to the large-scale mean magnetic field. In analyzing eight 40-60 minute intervals of multipoint magnetic field data from the four Cluster spacecraft, the degree of variation in the ratio of the parallel to perpendicular correlation lengths about the mean was larger than expected. This variation does not appear to be correlated with the solar wind velocity or the plasma beta. The ratio of parallel to perpendicular correlation lengths was also uncorrelated between different field components.
Monitoring intra-cellular lipid metabolism in macrophages by Raman- and CARS-microscopy

Monocyte-derived macrophages play a key role in lipid metabolism in vessel wall tissues. Macrophages can take up lipids by various mechanisms. As phagocytes, macrophages are important for the decomposition of lipid plaques within arterial walls that contribute to arteriosclerosis. Of special interest are uptake dynamics and intra-cellular fate of different individual types of lipids as, for example, fatty acids, triglycerides or free and esterified cholesterol. Here we utilize Raman microscopy to image the metabolism of such lipids and follow subsequent storage or degradation patterns. The combination of optical microscopy with Raman spectroscopy allows visualization at the diffraction limit of the employed laser light and biochemical characterization through the associated spectral information. Relatively long measuring times, due to the weakness of Raman scattering can be overcome by non-linear effects such as coherent anti-Stokes Raman scattering (CARS). With this contribution we introduce first results to monitor the incorporation of lipid components into individual cells employing Raman and CARS microscopy.
The Contribution of Orographically Driven Banded Precipitation to the Rainfall Climatology of a Mediterranean Region

Studies carried out worldwide show that topography influences rainfall climatology. As in most western Mediterranean regions, the mountainous Cevennes-Vivarais area in France regularly experiences extreme precipitation that may lead to devastating flash floods. Global warming could further aggravate this situation, but this possibility cannot be confirmed without first improving the understanding of the role of topography in the regional climate and, in particular, for extreme rainfall events. This paper focuses on organized banded rainfall and evaluates its contribution to the rainfall climatology of this region. Stationary rainfall systems made up of such bands are triggered and enhanced by small-scale interactions between the atmospheric flow and the relief. Rainbands are associated with shallow convection and are also present in deep-convection events for specific flux directions. Such precipitation patterns are difficult to observe both with operational weather radar networks, which are not designed to observe low-level convection within complex terrain, and with rain gauge networks, for which gauge spacing is typically larger than the bandwidth. A weather class of banded orographic shallow-convection events is identified, and the contribution of such events to annual or seasonal precipitation over the region is assessed. Moreover, a method is also proposed to quantify the contribution of banded convection during specific deep-convection events. It is shown that even though these orographically driven banded precipitation events produce moderate precipitation intensities they have long durations and therefore represent a significant amount of the rainfall climatology of the region, producing up to 40% of long-term total precipitation at certain locations.
Additive Manufactured Strain Sensor Using Stereolithography Method with Photopolymer Material

As a result of the developments in additive manufacturing (AM) technology, 3D printing is transforming from a method used only in rapid prototyping to a technique used to produce large-scale equipment. This study presents the fabrication and experimental studies of a 3D-printed strain sensor that can be used directly in soft applications. Photopolymer-based conductive and flexible ultraviolet (UV) resin materials are used in the fabrication of the sensor. A Stereolithography (SLA)-based printer is preferred for 3D fabrication. The bottom base of the sensor, which consists of two parts, is produced from flexible UV resin, while the channels that should be conductive are produced from conductive UV resin. In total, a strain sensor with a thickness of 2 mm was produced. Experimental studies were carried out under loading and unloading conditions to observe the hysteresis effect of the sensor. The results showed a close linear relationship between the strain sensor and the measured resistance value. In addition, tensile test specimens were produced to observe the behavior of conductive and non-conductive materials. The tensile strength values obtained from the test results will provide information about the sensor placement. In addition, the flexible structure of the strain sensor will ensure its usability in many soft applications.
Hadronic Contributions for TeV Gamma-Ray Emission from Young Supernova Remnants

We model a time-dependent nonthermal particle and photon spectra for young SNRs by assuming diffusive shock acceleration of the nonthermal particles and address a possible hadronic contribution of TeV γ-ray emission. In this model, the nonthermal electron and proton spectra, and then multiwavelength photon spectra that originated from both the electrons and the protons at different ages of the SNRs, are calculated respectively; the photon spectrum from radio to X-ray bands is dominated by synchrotron radiation of the relativistic electrons, and TeV γ-rays are produced by electron bremsstrahlung, inverse Compton scattering, and the π0 decay due to the relativistic protons colliding with ambient medium. Our results indicate that the relative importance of the hadronic origin of TeV γ-rays depends on the ratio of accelerated electrons to protons at the source, and the hadronic origin of TeV γ-rays can dominate the bremsstrahlung and inverse Compton processes of the relativistic electrons for young SNRs when a reasonable value of the ratio of the electrons to the protons at the source is used. The model is applied to three young SNRs, RX J1713.7-3946, SN 1006, and RX J0852.0-4622; our model results can explain the multiwavelength photon spectra for the three SNRs and show that the high-energy γ-rays from RX J1713.7-3946 and RX J0852.0-4622 may have hadronic origins.
A two-stage robust generation expansion planning framework for regional integrated energy systems with carbon growth constraints

After proposing the carbon peaking and carbon neutrality target, China further proposed a series of specific carbon emission growth limit sub-targets. How to decarbonize the energy system to ensure the realization of the carbon growth limit sub-targets is a meaningful topic. At present, generation expansion planning of renewable energy in integrated energy systems has been well studied. However, few of the existing studies consider specific carbon emission growth targets. To address this research gap, a two-stage robust generation expansion planning framework for regional integrated energy systems with carbon growth constraints is proposed in this paper, which takes into account multiple uncertainties. In this framework, the objective function is to minimize the total operation cost and wind turbine investment cost. The first stage is the decision-making level of the wind turbine capacity configuration scheme. The second stage is the optimal economic dispatching in the worst-case scenario, which is a bi-level problem of max-min form. Thus, the two-stage robust optimization framework constitutes a problem of min-max-min form, which is pretty hard to solve directly with a commercial solver. Therefore, a nested column-and-constraint generation algorithm is adopted and nested iterations are performed to solve the complex problem. Finally, case studies are carried out on a regional electric-gas integrated energy system. The MATLAB/YALMIP simulation platform with the Gurobi solver is used to verify the effectiveness and superiority of the proposed framework. Compared with other four cases, 5,000 Monte Carlo scheduling tests demonstrate that the proposed framework can ensure the system carbon emission to be controlled within a certain limit even in the worst scenario. Due to the consideration of multiple uncertainties, the proposed framework planning results are both robust and economical for investment. This study can provide theoretical support for the actual regional integrated energy system to achieve a certain carbon growth target.
On local constraints and regularity of PDE in electromagnetics. Applications to hybrid imaging inverse problems

The first contribution of this thesis is a new regularity theorem for time harmonic Maxwell’s equations with less than Lipschitz complex anisotropic coefficients. By using the $L^p$ theory for elliptic equations, it is possible to prove $H^1$ and Holder regularity results, provided that the coefficients are $W^{1,p}$ for some p > 3. This improves previous regularity results, where the assumption $W^{1,\infty}$ for the coefficients was believed to be optimal. The method can be easily extended to the case of bi-anisotropic materials, for which a separate approach turns out to be unnecessary. The second focus of this work is the boundary control of the Helmholtz and Maxwell equations to enforce local constraints inside the domain. More precisely, we look for suitable boundary conditions such that the corresponding solutions and their derivatives satisfy certain local non-zero constraints. Complex geometric optics solutions can be used to construct such illuminations, but are impractical for several reasons. We propose a constructive approach to this problem based on the use of multiple frequencies. The suitable boundary conditions are explicitly constructed and give the desired constraints, provided that a finite number of frequencies, given a priori, are chosen in a fixed range. This method is based on the holomorphicity of the solutions with respect to the frequency and on the regularity theory for the PDE under consideration. This theory finds applications to several hybrid imaging inverse problems, where the unknown coefficients have to be imaged from internal measurements. In order to perform the reconstruction, we often need to find suitable boundary conditions such that the corresponding solutions satisfy certain non-zero constraints, depending on the particular problem under consideration. The multiple frequency approach introduced in this thesis represents a valid alternative to the use of complex geometric optics solutions to construct such boundary conditions. Several examples are discussed.
Bacterial Culture-Negative Acute Infective Endocarditis With Vegetation in Native Bicuspid Aortic Valve

A 51-year-old male with a past medical history of bicuspid aortic valve, hypertension, and anterior cerebral artery stroke of unclear etiology three months earlier, presented to the Emergency Department with progressive shortness of breath, hemoptysis, and night sweats. The patient's echocardiogram revealed a mobile mass greater than 1.0 cm in diameter on the bicuspid aortic valve, which was not present on the echocardiogram three months prior, during his stroke workup. Per modified Duke's criteria, this patient was found to have 'definite' infective endocarditis despite persistently negative blood cultures. The patient underwent urgent surgical aortic valve replacement and a ventricular septal defect was noted that was not seen on prior imaging. The patient was discharged on intravenous antibiotics and warfarin. The patient was able to return to his normal functional status weeks after surgery, and is continuing to exercise without limitation. This case provides an example of patients with bicuspid aortic valves having an increased propensity for developing infective endocarditis. While also highlighting the interesting intra-operative images and presentation of acute culture-negative endocarditis with vegetation, and the subsequent repair, treatment, and recovery.
Mean-variance portfolio selection via LQ optimal control

Concerns the problem of mean-variance portfolio selection in an incomplete market. Asset prices are solutions of stochastic differential equations and the parameters in these equations may be random. We approach this problem from the perspective of linear-quadratic (LQ) optimal control and backward stochastic differential equations (BSDEs); that is, we focus on the so-called stochastic Riccati equation (SRE) associated with the problem. Excepting certain special cases, solvability of the SRE remains an open question. Our primary theoretical contribution is a proof of existence and uniqueness of solutions of the SRE associated with the mean-variance problem. In addition, we derive closed form expressions for the optimal portfolios and efficient frontier in terms of the solution of the SRE. A generalization of the Mutual Fund Theorem and financial interpretations of the SRE are also obtained.
Key Factors to Foster Academic Performance in Online Learning Environment: Evidence From Indonesia During COVID-19 Pandemic

Abstract The unprecedented COVID-19 pandemic has changed many aspects of society, including education. While online learning aims to avoid the transmission of viruses, however, what causes the success or failure of online learning needs to be investigated. This study tries to answer the question by analyzing how self-regulated learning, digital literacy, and the mediation of course satisfaction influence students’ academic performance in online learning situations caused by the COVID-19 pandemic in Indonesia. We employed Partial Least Square Structural Equation Modelling (PLS-SEM) on 358 respondents gathered from an online survey questionnaire completed by undergraduate students during the pandemic. The study finds that self-regulated learning is the key factor, followed by digital literacy. Course satisfaction also proved to mediate self-regulated learning and digital literacy on academic performance.
ON THE DECOMPOSITION OF SWITCHING FUNCTIONS

Abstract : A given switching function of n variables can frequently be decomposed into a composite function of several essentially simpler switching functions. Such decompositions lead to designs of more economical switching circuits to realize the given switching function. Ashenhurst's chart method is generalized to nondisjunctive decompositions by means of the don't care conditions. This extension provides an effective method of constructing all decompositions of switching functions. (Author)
Designing Follow-Up Times

Studies of time-to-event are often conducted using follow-up sessions with subjects at risk. When these sessions must be widely spaced, their timing can significantly affect the efficiency of a study design. In this article we analyze the optimal timing of follow-up from a Bayesian decision theoretic standpoint. The article has two goals: (1) to develop the necessary distributional theory and computational approaches to determine optimal sequential and nonsequential follow-up schedules in the exponential case and (2) to demonstrate that unusually large gains in efficiency (more than threefold over the standard approach in the examples considered) can be achieved using our group sequential timing of follow-up. We hope that this striking illustration will encourage more systematic consideration of followup times in study designs. Specifically, we consider time-independent hazard rates. We derive posterior and predictive distributions in three scenarios: single follow-up time for the estimation of a single hazard rate, group-specific follow-up time for the comparison of hazard rates in two treatment groups or cohorts, and multiple follow-up times for a single hazard rate. We encounter a novel family of mixtures of gamma functions and characterize its moments, which play a critical role in the determination of optima. We then provide a solution to the optimal follow-up time in the single follow-up problem. We develop a practical and accurate approximation to the optimal solution as a function of prior hyperparameters that can be used to implement real time calculations and more complex sequential strategies. Finally, we consider the sequential choice of follow-up times. We discuss the general dynamic programming solution and illustrate it in the setting of a two-stage design.
Can Bayesian Models of Cognition Show That We Are (Epistemically) Rational?

Abstract “According to [Bayesian] models” in cognitive neuroscience, says a recent textbook, “the human mind behaves like a capable data scientist. ” Do they? That is, do such models show we are rational? I argue that Bayesian models of cognition, perhaps surprisingly, don’t and indeed can’t show that we are Bayes-rational. The key reason is that they appeal to approximations, a fact that carries significant implications. After outlining the argument, I critique two responses, seen in recent cognitive neuroscience. One says that the mind can be seen as approximately Bayes-rational, while the other reconceives norms of rationality.
Adaptive synchronization for nonlinear FitzHugh–Nagumo neurons in external electrical stimulation

This paper investigates the synchronization problem for FitzHugh–Nagumo (FHN) neurons in external electrical stimulations. Using the sliding mode control technique, an adaptive control law is established that guarantees synchronization even when the parameters of the master and slave FHN neurons are fully unknown. A proportional‐integral switching surface is introduced to simplify the task of assigning the stability of the closed‐loop error system in the sliding mode. Furthermore, the proposed synchronization scheme is then applied to a secure communication system. Computer simulations are provided to verify the effectiveness of the proposed adaptive synchronization scheme. Copyright © 2007 John Wiley & Sons, Ltd.
RVB phase of hydrogen at high pressure: towards the first ab-initio Molecular Dynamics by Quantum Monte Carlo

3 To myself 4 I want acknowledge: Sandro Sorella for his patience with me. In these years he taught many things but I spent enough time to understand them (especially his QMC code); Irina Yegorova: My sweet ljubimaja, she corrected my thesis, and promised to listen to my presentation, poor girl; Lorenzo Stella: My personal " contarolo " , since he helped me many many times. It's unbelievable, but he always has an answer to any question. I don't know if I have to thank him for his sense of humor, for sure, this halved the scientific production in our room; Michele Casula: Because he was always ready to help me, and because I had a good collaboration with him (I'm not sure he will think the same), but I want to complain one thing about him: He speaks too little, and also his girlfriend agrees with me! Tania Zykova Timan: Because she is whimsical, wayward and full of glee for the life. She often made me happy in bad moments. Hamed Seyed Allaei: A very good friend patient and wise. He taught me English, and he is still continuing to do it at this moment. I want to complain about him that he never cut his beard. Joachim Almergrin: Because he is always happy (I don't know how) even when he was fired, and because he was a master in knowing new girls and new friends. Vittoria Colizza: My dear " amichetta " , I was lucky to live with her two times during this PhD, and I hope we will be always friends, I will never forget her strong character. Sara Bertocco: My second " mamma " , she always took care of me and helped in difficult moments. Fabio Affinito: for nice internet chatting during these years. Davide Ceresoli and Ugo Tartaglino: For the clarity and simplicity of their explanations, and for all the lunches together. Erio Tosatti: For useful discussions, probably I should have discussed more with him. many others for good weekends spent in Rome. 5 My family, my sister and my brother: they always were close to me in these years.
Alleviation of cognitive deficits in a rat model of glutamate-induced excitotoxicity, using an N-type voltage-gated calcium channel ligand, extracted from Agelena labyrinthica crude venom

Excitotoxicity is a common pathological process in Alzheimer’s disease (AD) which is caused by the over-activity of N-Methyl-D-Aspartate receptors (NMDARs). The release of neurotransmitters depends on the activity of voltage-gated calcium channels (VGCCs). Hyper-stimulation of NMDARs can enhance the releasement of neurotransmitters through the VGCCs. This malfunction of channels can be blocked by selective and potent N-type VGCCs ligand. Under excitotoxicity condition, glutamate has negative effects on the pyramidal cells of the hippocampus, which ends in synaptic loss and elimination of these cells. These events leads to learning and memory elimination through the hippocampus circuit’s dysfunction. A suitable ligand has a high affinity to receptor or channel and is selective for its target. The bioactive small proteins of venom have these characteristics. Therefore, peptides and small proteins of animal venom are precious sources for pharmacological applications. The omega-agatoxin-Aa2a was purified, and identified from Agelena labyrinthica specimens, as an N-type VGCCs ligand for this study. The effect of the omega-agatoxin-Aa2a on the glutamate-induced excitotoxicity in rats was evaluated through behavioral tests including Morris Water Maze, and Passive avoidance. The syntaxin1A (SY1A), synaptotagmin1 (SYT1), and synaptophysin (SYN) genes expression were measured via Real-Time PCR. The local expression of synaptosomal-associated protein, 25 k Da (SNAP-25) was visualized using an immunofluorescence assay for synaptic quantification. Electrophysiological amplitude of field excitatory postsynaptic potentials (fEPSPs) in the input–output and LTP curves of mossy fiber were recorded. The cresyl violet staining of hippocampus sections was performed for the groups. Our results demonstrated that the omega-agatoxin-Aa2a treatment could recover the learning, and memory impairment caused by NMDA-induced excitotoxicity in rat hippocampus.