Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunoenhancing Effects of Euglena gracilis on a Cyclophosphamide-Induced Immunosuppressive Mouse Model

In this study, the effects of the immune stimulator Euglena gracilis (Euglena) in cyclophosphamide (CCP)-induced immunocompromised mice were assessed. The key component β-1,3-glucan (paramylon) constitutes 50% of E. gracilis. Mice were orally administered Euglena powder (250 and 500 mg/kg body weight (B.W.)) or β-glucan powder (250 mg/kg B.W.) for 19 days. In a preliminary immunology experiment, ICR mice were intraperitoneally injected with 80 mg of CCP/kg B.W. during the final 3 consecutive days. In the main experiment, BALB/c mice were treated with CCP for the final 5 days. To evaluate the enhancing effects of Euglena on the immune system, mouse B.W. , the spleen index, natural killer (NK) cell activity and mRNA expression in splenocytes lungs and livers were determined. To detect cytokine and receptor expression, splenocytes were treated with 5 µg/ml concanavalin A or 1 µg/ml lipopolysaccharide. The B.W. and spleen index were significantly increased and NK cell activity was slightly enhanced in all the experimental groups compared to the CCP group. In splenocytes, the gene expression levels of tumor necrosis factor-α, interferon-γ, interleukin (IL)-10, IL-6, and IL-12 receptor were increased in the E. gracilis and β-glucan groups compared to the CCP group, but there was no significant difference. Treatment with 500mg of Euglena/kg B.W. significantly upregulated dectin-1 mRNA expression in the lung and liver compared to the CCP group. These results suggest that Euglena may enhance the immune system by strengthening innate immunity through immunosuppression.
Electrical conductivity and impedance spectroscopy studies of cerium based aeschynite type semiconducting oxides: CeTiMO6 (M=Nb or Ta)

Complex ceramic oxides, CeTiMO6 (M=Nb or Ta) having aeschynite type mineral structure were prepared by the conventional ceramic route. Complex impedance analysis in the frequency range 10 Hz–1 MHz over a wide temperature range (30–600 °C) indicates the presence of grain boundary effect along with the bulk contribution and also confirms the presence of non-Debye type of multiple relaxations in the material. The frequency dependent conductivity plots exhibit double power law dependence suggesting three types of conduction mechanisms: low frequency (10 Hz–1 kHz) conductivity owing to long range translational motion of electrons (frequency independent), mid-frequency conductivity (1–10 kHz) due to short-range hopping, and high frequency (10 kHz–1 MHz) conduction due to localized orientation hopping mechanism. The hopping model can explain the nature of the conduction mechanism completely. The electrical conductivity measurements with temperature suggest the negative temperature coefficient of resistance behav.
Impact of dedicated neuro-anesthesia management on clinical outcomes in glioblastoma patients: A single-institution cohort study

Background Glioblastomas are mostly resected under general anesthesia under the supervision of a general anesthesiologist. Currently, it is largely unkown if clinical outcomes of GBM patients can be improved by appointing a neuro-anesthesiologist for their cases. We aimed to evaluate whether the assignment of dedicated neuro-anesthesiologists improves the outcomes of these patients. We also investigated the value of dedicated neuro-oncological surgical teams as an independent variable in both groups. Methods A cohort consisting of 401 GBM patients who had undergone resection was retrospectively investigated. Primary outcomes were postoperative neurological complications, fluid balance, length-of-stay and overall survival. Secondary outcomes were blood loss, anesthesia modality, extent of resection, total admission costs, and duration of surgery. Results 320 versus 81 patients were operated under the anesthesiological supervision of a general anesthesiologist and a dedicated neuro-anesthesiologist, respectively. Dedicated neuro-anesthesiologists yielded significant superior outcomes in 1) postoperative neurological complications (early: p = 0.002, OR = 2.54; late: p = 0.003, OR = 2.24); 2) fluid balance (p<0.0001); 3) length-of-stay (p = 0.0006) and 4) total admission costs (p = 0.0006). In a subanalysis of the GBM resections performed by an oncological neurosurgeon (n = 231), the assignment of a dedicated neuro-anesthesiologist independently improved postoperative neurological complications (early minor: p = 0.0162; early major: p = 0.00780; late minor: p = 0.00250; late major: p = 0.0364). The assignment of a dedicated neuro-oncological team improved extent of resection additionally (p = 0.0416). Conclusion GBM resections with anesthesiological supervision of a dedicated neuro-anesthesiologists are associated with improved patient outcomes. Prospective evidence is needed to further investigate the usefulness of the dedicated neuro-anesthesiologist in different settings.
Estimation of simultaneous equation models with latent dependent variables: a Monte Carlo evaluation

Three methods can be used to estimate simultaneous equation models with latent dependent variables: two-stage, minimum distance (MD) and full-information maximum likelihood. Theoretically all the three methods provide asymptotically consistent estimates, but the performance of these estimators in finite samples cannot be determined in theory. This letter evaluates the performance of these estimators in finite samples using Monte Carlo simulation. The results show that the MD estimator performs very poorly; overall the full information maximum likelihood estimator performs better than the other two estimators.
Precipitation of Au nanoclusters in SrTiO3 by ion implantation

Gold nanoclusters dispersed in single-crystal SrTiO3 (STO) (001) have been prepared by ion implantation at both 300 and 975 K followed by annealing at 1275 K for 10 h. High-resolution transmission electron microscopy (TEM), high-angle annular dark-field imaging in an aberration-corrected dedicated scanning TEM, and image simulations were used to study the morphology, size, and crystallographic orientation of the Au nanoclusters with respect to the STO matrix, as well as the interface structure between the Au nanoclusters and STO. Gold ion implantation at 300 K leads to amorphization of the STO surface layer, which is corrugated to form bumps and valleys on the surface. Annealing at 1275 K for 10 h leads to epitaxial recrystallization of the amorphized layer within which Au clusters of several nanometers and a narrow size distribution were formed. Implantation at 975 K and subsequent annealing produces much larger Au clusters ∼50 nm in diameter and a very wide size distribution. The precipitated Au cluster.
Quantitative assessment of depolarization by the retinal pigment epithelium in healthy and glaucoma subjects measured over a large field of view

We present measurements of depolarization introduced by the retinal pigment epithelium (RPE) over a 45° field of view using polarization sensitive optical coherence tomography. A detailed spatial distribution analysis of depolarization caused by the RPE is presented in a total of 153 subjects including both healthy and diseased eyes. Age and sex related differences in the depolarizing character of the RPE are investigated.
Structural and electrical properties of beryllium metal to 66 GPa studied using designer diamond anvils

The structural and electrical properties of alkaline-earth metal beryllium were studied to 66 GPa using designer diamond anvils. The ambient pressure hexagonal close-packed phase was found to be stable to the highest pressure of 66 GPa and the measured static equation of state differs substantially from the one derived from the existing shock wave data. The electrical resistance data at high pressure shows a gradual decrease in resistance to pressure up to 25 GPa followed by a slight increase to 53 GPa. The axial ratio (cla) remains strongly nonideal with e/a = 1.562 at V/V 0 =0.708, indicating that deviations from nearly free electron behavior are still dominant at high compressions.
Recursive Particle Swarm Optimization Application for the Radial Basis Function Networks Modeling System

A Recursive Particle Swarm Optimization (RPSO) is proposed to solve dynamic optimization problems where the data is obtained not once but one by one. The position of each particle swarm is updated recursively based on the continuous data and the historical knowledge. The experiment results indicate that RPSO-based radial basis function networks needs fewer radial basis functions and gives more accurate results than traditional PSO in solving dynamic problems.
Light-meson leptonic decay rates in lattice 
QCD+QED

The leading electromagnetic (e.m.) and strong isospin-breaking corrections to the $\pi^+ \to \mu^+ \nu[\gamma]$ and $K^+ \to \mu^+ \nu[\gamma]$ leptonic decay rates are evaluated for the first time on the lattice. The results are obtained using gauge ensembles produced by the European Twisted Mass Collaboration with $N_f = 2 + 1 + 1$ dynamical quarks. The relative leading-order e.m. and strong isospin-breaking corrections to the decay rates are 1.53(19) % for $\pi_{\mu 2}$ decays and 0.24(10) % for $K_{\mu 2}$ decays. Using the experimental values of the $\pi_{\mu 2}$ and $K_{\mu 2}$ decay rates and updated lattice QCD results for the pion and kaon decay constants in isosymmetric QCD, we find that the Cabibbo-Kobayashi-Maskawa matrix element $\vert V_{us}\vert = 0.22538(38)$, reducing by a factor of about $1.8$ the corresponding uncertainty in the PDG review. Our calculation of $|V_{us}|$ allows also an accurate determination of the first-row CKM unitarity relation $\vert V_{ud}\vert^2 + \vert V_{us}\vert^2 + \vert V_{ub}\vert^2 = 0.99988(44)$. Theoretical developments in this paper include a detailed discussion of how QCD can be defined in the full QCD+QED theory and an improved renormalisation procedure in which the bare lattice operators are renormalised non-perturbatively into the RI$^\prime$-MOM scheme and subsequently matched pertubatively at $O(\alpha_{em}\alpha_s(M_W))$ into the W-regularisation scheme appropriate for these calculations.
Non invasive blood flow assessment in diabetic foot ulcer using laser speckle contrast imaging technique

Measuring microcirculatory tissue blood perfusion is of interest for both clinicians and researchers in a wide range of applications and can provide essential information of the progress of treatment of certain diseases which causes either an increased or decreased blood flow. Diabetic ulcer associated with alterations in tissue blood flow is the most common cause of non-traumatic lower extremity amputations. A technique which can detect the onset of ulcer and provide essential information on the progress of the treatment of ulcer would be of great help to the clinicians. A noninvasive, noncontact and whole field laser speckle contrast imaging (LSCI) technique has been described in this paper which is used to assess the changes in blood flow in diabetic ulcer affected areas of the foot. The blood flow assessment at the wound site can provide critical information on the efficiency and progress of the treatment given to the diabetic ulcer subjects. The technique may also potentially fulfill a significant need in diabetic foot ulcer screening and management.
Implementation and validation of a new prognostic large‐scale cloud and precipitation scheme for climate and data‐assimilation purposes

A large‐scale condensation scheme, able to treat separately both atmospheric cloud condensate and precipitation content in a prognostic way, has been implemented and validated in Météo‐France's operational global model, ARPEGE. The proposed scheme can be used for climate simulations and short‐range numerical weather prediction, although it was originally designed for the future variational assimilation of cloud and precipitation observations.
Temperature tuning of polarization mode dispersion in single-core and two-core photonic liquid crystal fibers

In this paper we present numerical and experimental results of propagation and polarization properties of the photonic liquid crystal fibers (PLCFs) in which only selected micro holes were filled with nematic liquid crystal (LC) guest materials. As a host photonic crystal fiber (PCF) structure, we used a commercially available highly birefringent PCF (Blazephotonics, UK). A tunable laser operated at infrared has powered the PLCFs under investigation infiltrated by the 1550 nematic LC synthesized at the Military University of Technology. Temperature induced changes of the polarization mode dispersion (PMD) as well switching between fundamental and higher order modes and also single-core and two-core propagation were successfully demonstrated.
Multiple optical tweezers for micro Raman spectroscopy

The goal of our study is to develop a setup that combines multi-trapping and manipulation with micro Raman spectroscopy of microns size particles. Multiple trapping, in 2D or 3D (two or three dimensional) configurations, is obtained in an inverted microscope scheme by shaping the trapping beam (1064 nm) with diffractive optical elements implemented on a spatial light modulator (SLM). Manipulation of multiple particles, directly trapped by the beam, can be achieved using the dynamic displaying of the SLM. Indirect trapping and manipulation of the sample can be obtained surrounding it with trapped micro beads that are manipulated by the optical tweezers. Laser light is not directly focused on the sample but is distributed on the beads and therefore the photo-induced damaging of biological samples is reduced. This technique offers also other advantages: the sample can be kept in a stable position during the spectroscopic investigation or can be moved in x-y-z to get spatial resolved information in a scanning mode measurement and the shape of a deformable sample can be changed in a controlled manner during the measurement. Sample's excitation and Raman signal collection are accomplished with a separate laser beam (514.5 nm) in a non-inverted microscope coupled with the spectrometer. Some experimental results showing multi trapping and indirect manipulation of human red blood cells are presented and discussed.
Reciprocity properties of one-way propagators

Acoustic reciprocity is a fundamental property of the wave equation for the total acoustic wavefield (Rayleigh, 1878). In its most elementary form the reciprocity principle states that an acoustic response remains the same when the source and receiver are interchanged. In terms of Green’s functions this reciprocity principle reads G(r2, r1) = G(r1, r2), with r = (x, y, z). For more general expressions and their seismic applications, see Fokkema and van den Berg (1993).
Efficient Calculation of 3D Fast Multipole Method (FMM) Phase Integrals using an Analytical Method

The fast multipole method (FMM) was originally developed to reduce the computation time and memory required to calculate the scattering problems such as obtaining radar cross section (RCS) of a large object. In the FMM, it is necessary to integrate the phase of each basis region multiplied by its current basis function. However, the phase value is not a linear function, and hence its integration should be performed with care. Integrations of this type have generally been carried out numerically due to lack of an analytical solution. In this paper, we present an analytical method for the phase integral and show that this method can reduce the calculation time compared to the numerical method when a Rao-Wilton-Glisson (RWG) basis function is used as the current basis function set.
Photon-assisted breakdown, negative resistance, and switching in a quantum-well transistor laser

Data are presented on the transistor laser with collector bias and photon-assisted tunneling causing, under the constraints IE+IB+IC=0 (α=ΔIC∕ΔIE) and α→1, breakdown and negative resistance effects in the IC-VCE characteristics. Collector bias, aided by photon-assisted tunneling (Franz—Keldysh absorption), supplies holes to the n-p-n transistor base by tunneling escape of electrons (ΔIB=0), “feeding” quantum-well recombination radiation (generation and regeneration, ΔIE=ΔIC=ΔIhv) and yielding the negative resistance/switching condition α→1 (α=ΔIC∕ΔIE, ΔIC=ΔIE, ΔIB=0, IE+IB+IC=0), and, as a consequence, corners, negative resistance, switching, vertical collector current (ΔVCE≈0), spectral change, and mode hopping effects in the IC-VCE characteristics.
Computationally efficient methods in spatial statistics : Applications in environmental modeling

In this thesis, computationally efficient statistical models for large spatial environmental data sets are constructed. In the first part of the thesis, a method for estimating spatially dependent temporal trends is developed. A space-varying regression model, where the regression coefficients for the spatial locations are dependent, is used. The spatial dependence structure is specified by a Gaussian Markov Random Field model, and the model parameters are estimated using the Expectation Maximization algorithm, which allows for feasible computation times for relatively large data sets. The model is used to analyze temporal trends in vegetation data from the African Sahel, and the results indicate a substantial gain in accuracy compared with methods based on independent ordinary least squares regressions for the individual pixels in the data set. In the second part of the thesis, explicit computationally efficient wavelet Markov approximations of Gaussian Matern fields are derived using Hilbert space approximations. Using a simulation-based study, the wavelet approximations are compared with two of the most popular methods for efficient covariance approximations. The study indicates that, for a given computational cost, the wavelet Markov methods have a substantial gain in accuracy compared with the other methods. Finally, a new class of stochastic field models is constructed using nested Stochastic Partial Differential Equations (SPDEs). The model class is computationally efficient, applicable to data on general smooth manifolds, and includes both the Gaussian Matern fields and a wide family of fields with oscillating covariance functions. Non-stationary covariance models are obtained by spatially varying the parameters in the SPDEs, and the model parameters are estimated using direct numerical optimization, which is more efficient than standard Markov Chain Monte Carlo procedures. As examples of areas of application, the model class is used to approximate popular models in random ocean wave theory, and applied to a large data set of global Total Column Ozone (TCO) data. The TCO data set contains approximately 180 000 measurements, showing that the models allow for efficient inference, even for large environmental data sets. (Less)
Evaluation of Instagram Social Media Marketing to Plan New Strategy Formulation in Menantea

Social media allows marketers to connect and engage potential customers. This led many marketing professionals to refocus on their social media marketing strategy. Menantea Toko is one of the most talked Food and Beverage Brand in 2021. Their existence surprised the public because they gained 100k followers in just 3 days. The purpose of this research is to determine how to evaluate the usage of social media Instagram Menantea and to propose a social media marketing strategy for Menantea. This form of research is taken as descriptive quantitative research. The research population is followers of Instagram Menantea. This study used a non-probability sample approach known as purposive sampling, with the minimal sampling size obtained using the slovin formula. Methods for gathering data include in-depth interviews, surveys, and Forum Group Discussions (FGD). Pearson's product moment validity test and the Cronbach's Alpha formula were used to evaluate the questionnaire's reliability. The results demonstrated that social media marketing on Instagram Menantea was effective and generated a positive response from followers.
Deuxième microlocalisation sur les sous-variétés isotropes

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Stability and dissipativity theory for nonnegative dynamical systems: a thermodynamic framework for biological and physiological systems

Nonnegative dynamical system models are derived from mass and energy balance considerations that involve dynamic states whose values are nonnegative. These models are widespread in biological, physiological, and ecological sciences and play a key role in the understanding of these processes. In this paper we develop several results on stability, dissipativity, and stability of feedback interconnections of linear and nonlinear nonnegative dynamical systems. Specifically, using linear Lyapunov functions we develop necessary and sufficient conditions for Lyapunov stability, semistability, and asymptotic stability for nonnegative systems. In addition, using linear storage functions and linear supply rates we develop, new notions of dissipativity theory for nonnegative dynamical systems. Finally, these results are used to develop general stability criteria for feedback.
Semi-signed prioritized neural fitting for surface reconstruction from unoriented point clouds

Reconstructing 3D geometry from \emph{unoriented} point clouds can benefit many downstream tasks. Recent shape modeling methods mostly adopt implicit neural representation to fit a signed distance field (SDF) and optimize the network by \emph{unsigned} supervision. However, these methods occasionally have difficulty in finding the coarse shape for complicated objects, especially suffering from the ``ghost'' surfaces (\ie, fake surfaces that should not exist). To guide the network quickly fit the coarse shape, we propose to utilize the signed supervision in regions that are obviously outside the object and can be easily determined, resulting in our semi-signed supervision. To better recover high-fidelity details, a novel importance sampling based on tracked region losses and a progressive positional encoding (PE) prioritize the optimization towards underfitting and complicated regions. Specifically, we voxelize and partition the object space into \emph{sign-known} and \emph{sign-uncertain} regions, in which different supervisions are applied. Besides, we adaptively adjust the sampling rate of each voxel according to the tracked reconstruction loss, so that the network can focus more on the complicated under-fitting regions. To this end, we propose our semi-signed prioritized (SSP) neural fitting, and conduct extensive experiments to demonstrate that SSP achieves state-of-the-art performance on multiple datasets including the ABC subset and various challenging data. The code will be released upon the publication.
Further characterizations of integral input-to-state stability for hybrid systems

In this work we present further characterizations of integral input-to-state stability (iISS) for hybrid systems. In particular, the equivalence between 0-input uniform global asymptotic stability (0-UGAS) plus uniform bounded energy bounded state (UBEBS) and iISS is examined. In order to show this equivalence, some necessary conditions for 0-UGAS and UBEBS are provided. In addition, a non-smooth Lyapunov characterization for hybrid systems is proposed and proven. With the help of the aforementioned equivalence, the combination of local iISS and practical iISS, which are defined in this work, is also shown to be equivalent to iISS under one condition on the local and practical quantifiers.