Miracle-dz/UniFAR-FTUs huggingface dataset:
A Characterization of Dendritic Cells and Their Role in Immunotherapy in Glioblastoma: From Preclinical Studies to Clinical Trials

Glioblastoma (GBM) is the most common and fatal primary central nervous system malignancy in adults with a median survival of less than 15 months. Surgery, radiation, and chemotherapy are the standard of care and provide modest benefits in survival, but tumor recurrence is inevitable. The poor prognosis of GBM has made the development of novel therapies targeting GBM of paramount importance. Immunotherapy via dendritic cells (DCs) has garnered attention and research as a potential strategy to boost anti-tumor immunity in recent years. As the “professional” antigen processing and presenting cells, DCs play a key role in the initiation of anti-tumor immune responses. Pre-clinical studies in GBM have shown long-term tumor survival and immunological memory in murine models with stimulation of DC activity with various antigens and costimulatory molecules. Phase I and II clinical trials of DC vaccines in GBM have demonstrated some efficacy in improving the median overall survival with minimal to no toxicity with promising initial results from the first Phase III trial. However, there remains no standardization of vaccines in terms of which antigens are used to pulse DCs ex vivo, sites of DC injection, and optimal adjuvant therapies. Future work with DC vaccines aims to elucidate the efficacy of DC-based therapy alone or in combination with other immunotherapy adjuvants in additional Phase III trials.
The Spatial Distribution of O-B5 Stars in the Solar Neighborhood as Measured by Hipparcos

We have developed a method to calculate the fundamental parameters of the vertical structure of the Galaxy in the solar neighborhood from trigonometric parallaxes alone. The method takes into account Lutz-Kelker–type biases in a self-consistent way and has been applied to a sample of O–B5 stars obtained from the Hipparcos catalog. We find that the Sun is located 24.2 ± 1.7 (random) ± 0.4 (systematic) pc above the Galactic plane and that the disk O–B5 stellar population is distributed with a scale height of 34.2 ± 0.8 (random) ± 2.5 (systematic) pc and an integrated surface density of [1.62 ± 0.04 (random) ± 0.14 (systematic)] × 10-3 stars pc-2. A halo component is also detected in the distribution and constitutes at least ≈5% of the total O–B5 population. The O–B5 stellar population within ∼100 pc of the Sun has an anomalous spatial distribution, with a less than average number density. This local disturbance is probably associated with the expansion of the Gould Belt.
Interface decay channel of particle surface plasmon resonance

Surface plasmon polariton resonance in metallic clusters embedded in a matrix is broadened due to the interface decay channel of the plasmon lifetime. This non-classical broadening effect is caused by adsorbate-induced local density of states near the Fermi level of the cluster. We study theoretically the broadening effect for realistic small noble clusters extending Persson's theory for adsorbate-induced damping of the plasmon resonance by taking into account the interband transitions in the dielectric function of the cluster. The broadening of the surface plasmon resonance caused by the interface decay channel is significantly influenced by the interband transitions in the metallic cluster.
Evolution of superclusters in the cosmic web

Aims. We investigate how properties of the ensemble of superclusters in the cosmic web evolve with time. Methods. We performed numerical simulations of the evolution of the cosmic web using the Λ cold dark matter model in box sizes L0 = 1024, 512, 256 h−1 Mpc. We found supercluster ensembles of models for four evolutionary stages, corresponding to the present epoch z = 0, and to redshifts z = 1, z = 3, and z = 10. We calculated fitness diameters of superclusters defined from volumes of superclusters divided by filling factors of over-density regions. Geometrical and fitness diameters of largest superclusters, and the number of superclusters as functions of the threshold density were used as percolation functions to describe geometrical properties of the ensemble of superclusters in the cosmic web. We calculated the distributions of geometrical and fitness diameters and luminosities of superclusters, and followed the time evolution of percolation functions and supercluster distributions. We compared percolation functions and supercluster distributions of models and samples of galaxies of the Sloan Digital Sky Survey (SDSS). Results. Our analysis shows that fitness diameters of superclusters have a minimum at a certain threshold density. Fitness diameters around minima almost do not change with time in co-moving coordinates. Numbers of superclusters have maxima which are approximately constant for all evolutionary epochs. The geometrical diameters of superclusters decrease during the evolution of the cosmic web, and the luminosities of superclusters increase during this evolution. Conclusions. Our study suggests that evolutionary changes occur inside supercluster cells of dynamical influence. The stability of fitness diameters and numbers of superclusters during the evolution is an important property of the cosmic web.
Mouse Extraocular Muscles and the Musculotopic Organization of Their Innervation

The organization of extraocular muscles (EOMs) and their motor nuclei was investigated in the mouse due to the increased importance of this model for oculomotor research. Mice showed a standard EOM organization pattern, although their eyes are set at the side of the head. They do have more prominent oblique muscles, whose insertion points differ from those of frontal‐eyed species. Retrograde tracers revealed that the motoneuron layout aligns with the general vertebrate plan with respect to nuclei and laterality. The mouse departed in some significant respects from previously studied species. First, more overlap between the distributions of muscle‐specific motoneuronal pools was present in the oculomotor nucleus (III). Furthermore, motoneuron dendrites for each pool filled the entire III and extended beyond the edge of the abducens nucleus (VI). This suggests mouse extraocular motoneuron afferents must target specific pools based on features other than dendritic distribution and nuclear borders. Second, abducens internuclear neurons are located outside the VI. We concluded this because no unlabeled abducens internuclear neurons were observed following lateral rectus muscle injections and because retrograde tracer injections into the III labeled cells immediately ventral and ventrolateral to the VI, not within it. This may provide an anatomical substrate for differential input to motoneurons and internuclear neurons that allows rodents to move their eyes more independently. Finally, while soma size measurements suggested motoneuron subpopulations supplying multiply and singly innervated muscle fibers are present, markers for neurofilaments and perineuronal nets indicated overlap in the size distributions of the two populations. Anat Rec, 302:1865–1885, 2019. © 2019 American Association for Anatomy
Effect of dental bleaching on pulp oxygen saturation in maxillary central incisors - a randomized clinical trial

Abstract Objective To assess pulp oxygen saturation levels (SaO2) in maxillary central incisors after dental bleaching. Materials and Methods 80 participants (160 teeth) were randomly allocated to four groups: G1 In-office bleaching with two applications of 35% hydrogen peroxide (HP) (20 minutes), followed by at-home bleaching with 10% carbamide peroxide (CP) (2 hours/day for 16 days); G2 - Same protocol as G1, plus desensitizing toothpaste; G3 - In-office bleaching with 35% HP and one application of placebo gel (20 minutes), followed by at-home bleaching with 10% CP (2 hours/day for 16 days); and G4 - Same protocol as G3, plus desensitizing toothpaste. Pulp SaO2 levels were measured before (T0) and immediately after (T1) in-office bleaching; on the 5th (T2), 8th (T3), 12th (T4), and 16th days of at-home bleaching (T5); and on the 7th (T6) and 30th (T7) days. Mean (SD) pulp SaO2 levels were compared within groups by generalized estimating equations (GEE) and Student’s t-test (P<0.05). Results Mean pulp SaO2 at T0 was 84.29% in G1, 84.38% in G2, 84.79% in G3, and 85.83% in G4. At T1, these values decreased to 81.96%, 82.06%, 82.19%, and 81.15% in G1, G2, G3, and G4 respectively, with significant difference in G4 (P<0.05). During home bleaching, pulp SaO2 levels varied in all groups, with 86.55%, 86.60%, 85.71%, and 87.15% means at T7 for G1, G2, G3, and G4, respectively; G2 presented significant difference (P<0.05). Conclusions Pulp SaO2 level in maxillary central incisors was similar at baseline, reducing immediately after in-office bleaching, regardless of using desensitizing toothpaste and increasing at 30 days after dental bleaching.
TDE fallback cut-off due to a pre-existing accretion disc

Numerous tidal disruption event (TDE) candidates originating from galactic centres have been detected (e.g., by ${\it Swift}$ and ASASSN). Some of their host galaxies show typical characteristics of a weak active galactic nucleus (AGN), indicative of a pre-existing accretion disc around the supermassive black hole (SMBH). In this work, we develop an analytic model to study how a pre-existing accretion disc affects a TDE. We assume the density of the disc $\rho\propto R^{-\lambda}$, $R$ being the radial distance from the SMBH and $\lambda$ varying between $0.5$ and $1.5$. Interactions between the pre-existing accretion disc and the stream of the tidally disrupted star can stall the stream far from the SMBH, causing a sudden drop in the rate of fallback of gas into the SMBH. These interactions could explain the steep cut-off observed in the light curve of some TDE candidates (e.g., ${\it Swift}$ J1644 and ${\it Swift}$ J2058). With our model, it is possible to use the time of this cut-off to constrain some properties pertaining to the pre-existing accretion disc, such as $\lambda$ and the disc viscosity parameter $\alpha$. We demonstrate this by applying our theory to the TDE candidates ${\it Swift}$ J1644, ${\it Swift}$ J2058 and ASASSN-14li. Our analysis favours a disc profile with $\lambda\sim1$ for viscosity parameters $\alpha\sim0.01-0.1$.
Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study

Background Virtually, all organisms on Earth have their own circadian rhythm, and humans are no exception. Circadian rhythms are associated with various human states, especially mood disorders, and disturbance of the circadian rhythm is known to be very closely related. Attempts have also been made to derive clinical implications associated with mood disorders using the vast amounts of digital log that is acquired by digital technologies develop and using computational analysis techniques. Objective This study was conducted to evaluate the mood state or episode, activity, sleep, light exposure, and heart rate during a period of about 2 years by acquiring various digital log data through wearable devices and smartphone apps as well as conventional clinical assessments. We investigated a mood prediction algorithm developed with machine learning using passive data phenotypes based on circadian rhythms. Methods We performed a prospective observational cohort study on 55 patients with mood disorders (major depressive disorder [MDD] and bipolar disorder type 1 [BD I] and 2 [BD II]) for 2 years. A smartphone app for self-recording daily mood scores and detecting light exposure (using the installed sensor) were provided. From daily worn activity trackers, digital log data of activity, sleep, and heart rate were collected. Passive digital phenotypes were processed into 130 features based on circadian rhythms, and a mood prediction algorithm was developed by random forest. Results The mood state prediction accuracies for the next 3 days in all patients, MDD patients, BD I patients, and BD II patients were 65%, 65%, 64%, and 65% with 0.7, 0.69, 0.67, and 0.67 area under the curve (AUC) values, respectively. The accuracies of all patients for no episode (NE), depressive episode (DE), manic episode (ME), and hypomanic episode (HME) were 85.3%, 87%, 94%, and 91.2% with 0.87, 0.87, 0.958, and 0.912 AUC values, respectively. The prediction accuracy in BD II patients was distinctively balanced as high showing 82.6%, 74.4%, and 87.5% of accuracy (with generally good sensitivity and specificity) with 0.919, 0.868, and 0.949 AUC values for NE, DE, and HME, respectively. Conclusions On the basis of the theoretical basis of chronobiology, this study proposed a good model for future research by developing a mood prediction algorithm using machine learning by processing and reclassifying digital log data. In addition to academic value, it is expected that this study will be of practical help to improve the prognosis of patients with mood disorders by making it possible to apply actual clinical application owing to the rapid expansion of digital technology.
Turbulent flow through spacer grids in rod bundles

The effects of the spacer grids with mixing vanes in rod bundles on the turbulent structure were investigated experimentally. The detailed hydraulic characteristics in subchannels of a 5 X 5 rod bundle with mixing spacer grids were measured upstream and downstream of the spacer grid by using a one component LDV (Laser Doppler Velocimetry). Axial velocity and turbulent intensity, skewness factor, and flatness factor were measured. The turbulence decay behind spacer grids was obtained from measured data. The trend of turbulence decay behaves in a similar vay as turbulent flow through mesh grids or screens. Pressure drop measurements were also performed to evaluate the loss coefficient for the spacer grid and the friction factor for a rod bundle
Quality of a climate reconstruction for the CADSES regions

We used the regional climate model CCLM 4 to reconstruct the climate over the CADSES regions for the period 1961-2000. This most recent model version is currently still in a test phase. The simulation quality for this part of the entire simulation area is exemplarily analyzed by using a small but representative subset of model variables. Mean sea level pressure is chosen as an indicator for the behavior of the near-surface dynamics. Furthermore, the two regional variables 2 m temperature and precipitation are evaluated, which are of relevance for hydrological applications. For additional analyses to identify sources of uncertainty, we used soil moisture and cloudiness. Altogether, the accuracy of the simulation results can be judged as being in good agreement with the results of similar simulations by other regional climate models over Europe. Area-averaged monthly mean 2 m temperatures during winter show a cold bias of about -2 K. The simulated mean sea level pressure is with a bias of about 2 hPa slightly too high compared to the used reference data set. Although cloud cover evaluation hints at insufficiencies in the corresponding parameterization, further analyses are required to unambiguously identify the causes for this cold bias. During summer, higher 2 m temperatures linked to reduced precipitation are identified in nearly identical regions over southern and south-eastern Europe. Further analyses of soil moisture evolution and cloud cover give evidence for a source of uncertainty in the surface hydrological scheme. Altogether, the detected differences do not exceed the typical ranges of uncertainty in comparable regional climate simulations over Europe. For input in hydrological applications, however, the uncertainties produced by the CCLM simulation described here have to be reduced in the medium term.
Principal Congruence Subgroups of the Hecke Groups

Abstract Let q be an odd integer >3 and let Gq be the Hecke group associated to q. Let (τ) be a prime ideal of Z [λq] and G(q, τ) the principal congruence subgroup of Gq associated to τ. We give a formula for [Gq : G(q, τ)], the index of the principal congruence subgroup G(q, τ) in Gq. We also give formulae for the indices [G1(q, τ), G(q, τ)] and [G0(q, τ), G1(q, τ)]. Finally, we give a formula for the geometric invariants of G(q, τ) when q is a rational prime.
OSCILLATORY AND VANISHING RESISTANCE STATES IN MICROWAVE IRRADIATED 2D ELECTRON SYSTEMS

Giant-amplitude oscillations in dc magnetoresistance of a high-mobility two-dimensional electron system can be induced by millimeterwave irradiations, leading to zero-resistance states at the oscillation minima. Following a brief overview of the now well-known phenomenon, this paper reports on aspects of more recent experiments on the subject. These are: new zero-resistance states associated with multi-photon processes; suppression of Shubnikov-de Haas oscillations by high-frequency microwaves; and microwave photoconductivity of a high-mobility two-dimensional hole system.
Clouds effect on the atmospheric total column carbon dioxide retrieval by space orbiting Argus 1000 micro-spectrometer: introductory study

Carbon Dioxide (CO2) is one of the most important greenhouse gases after water vapor (H2O) which plays significant role in the climate process. Accurate space-based measurement of CO2 is of great significance in inferring the location of CO2 sources and sinks. Uncertainties in greenhouse gases (GHG) retrieval process must be minimized to accurately infer the actual amount of the atmospheric species. Clouds pose a large uncertainty in CO2 spacebased retrieval process leading, mostly, to an underestimation in the CO2 absorption amount above the cloud layer provided that photons do not perform multiple paths. In this paper, three different cases of data collected over cloudy and clear skies by Argus 1000 micro-spectrometer were analyzed. Findings show that the CO2 absorption in the absence of clouds is approximately 4.5% higher than when clouds are present.
Restricted Boltzmann machine learning for solving strongly correlated quantum systems

We develop a machine learning method to construct accurate ground-state wave functions of strongly interacting and entangled quantum spin as well as fermionic models on lattices. A restricted Boltzmann machine algorithm in the form of an artificial neural network is combined with a conventional variational Monte Carlo method with pair product (geminal) wave functions and quantum number projections. The combination allows an application of the machine learning scheme to interacting fermionic systems. The combined method substantially improves the accuracy beyond that ever achieved by each method separately, in the Heisenberg as well as Hubbard models on square lattices, thus proving its power as a highly accurate quantum many-body solver.
A split‐step Padé solution for the parabolic equation method

A split‐step Pade solution is derived for the parabolic equation (PE) method. Higher‐order Pade approximations are used to reduce both numerical errors and asymptotic errors (e.g., phase errors due to wide‐angle propagation). This approach is approximately two orders of magnitude faster than solutions based on Pade approximations that account for asymptotic errors but not numerical errors. In contrast to the split‐step Fourier solution, which achieves similar efficiency for some problems, the split‐step Pade solution is valid for problems involving very wide propagation angles, large depth variations in the properties of the waveguide, and elastic ocean bottoms. The split‐step Pade solution is practical for global‐scale problems.
Preheated Advection-dominated Accretion Flow

The advection-dominated accretion flow (ADAF) has been quite successful in explaining a wide variety of accretion-powered astronomical sources. The physical characteristics of ADAF complement the classical thin disk flow quite nicely, and extensive work has been done on it. However, all high-temperature accretion solutions including ADAF are physically thick, so outgoing radiation interacts with the incoming flow. Thus, ADAF solutions share as much or more resemblance with classical spherical accretion flows as with disk flows. This interaction, which has been neglected by most authors, is primarily through the Compton heating process that will typically limit the steady solutions to L ≲ 10-2LEdd, where LEdd is the Eddington luminosity. We examine this interaction for the popular ADAF case, but similar conclusions, we expect, would apply for other high-temperature, geometrically thick disks as well. We study the global thermal nature of the flow, with special consideration given to various cooling and, especially, preheating by Comptonizing hot photons produced at smaller radii. We find that without allowance for Compton preheating a very restricted domain of ADAF solution is permitted and with Compton preheating included a new high-temperature PADAF branch appears in the solution space. In the absence of preheating, high-temperature flows do not exist when the mass accretion rate ≡ c2/LEdd ≳ 10-1.5. Below this mass accretion rate, a roughly conical region around the hole cannot sustain high-temperature ions and electrons for all flows having ≳ 10-4, which may lead to a funnel possibly filled with a tenuous hot outgoing wind. If the flow starts at large radii with the usual equilibrium temperature ~104 K, the critical mass accretion rate is much lower, ~ 10-3.7, above which level no self-consistent ADAF (without preheating) can exist. However, above this critical mass accretion rate, the flow can be self-consistently maintained at high temperature if Compton preheating is considered. These solutions constitute a new branch of solutions as in spherical accretion flows. High-temperature PADAF flows can exist above the critical mass accretion rate in addition to the usual cold thin disk solutions. We also find solutions where the flow near the equatorial plane accretes normally while the flow near the pole is overheated by Compton preheating, possibly becoming a polar wind, solutions which we designate WADAF.
A Numerical Study in Three Space Dimensions of Bénard Convection in a Rotating Fluid

Abstract The primitive, nonlinear, Boussinesq equations of motion, continuity and thermodynamic energy are integrated numerically in three space dimensions and time to study convection driven by unstable vertical density gradients and subject to Coriolis forces. Parameter values are chosen to permit quantitative comparison with data from laboratory experiments for rotating Benard convection in water. The model realistically simulates the structure of the convection cells, their horizontal scale, and the mean vertical heat transport. The experimentally observed phenomenon of a non-monotone dependence of heat transport on rotation rate is reproduced and shown to be a consequence of the rotational constraint on the wavelength of the cells.