Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends in precipitation days in the United States

Changes in precipitation frequency can have a major impact on many different sectors including agriculture, tourism, and recreation. This study investigates trends in precipitation days at first‐order weather stations across the conterminous United States from 1951 to 2015. The Mann‐Kendall test and sliding window correlation analysis are used to examine trends over time. Future precipitation days are forecasted via usage of a stepwise auto‐regressive model. The Mann‐Kendall test found that the majority of the Northeast and Midwestern states show upward trends in precipitation days, while negative trends are located in the Southeast and in clusters throughout the Northwest. Sliding window correlation analysis was used to detect the decade when most of the change in precipitation days occurred. The northeastern United States had more significant changes during the earlier decades whereas the centre part of the country had more significant changes in the later decades. Most stations saw more decades with positive (increasing) trends in precipitation days. Precipitation days are expected to increase for most of the United States into the future.
Multiscale imaging of white matter microstructure

Diffusion Magnetic Resonance Imaging (dMRI) tractography is a technique with great potential to characterize the in vivo anatomical position and integrity of white matter tracts. Tractography, however, remains an estimation of white matter tracts, and false positive and false negative rates are not available. The goal of the present study was to compare post mortem tractography of the dentatorubrothalamic tract (DRTT) by its 3D histological reconstruction, in order to estimate the reliability of the tractography algorithm in this specific tract. Recent studies have shown that the cerebellum is involved in cognitive, language and emotional functions besides its role in motor control. However, the exact working mechanism of the cerebellum is still to be elucidated. As the DRTT is the main output tract, it is of special interest for the neuroscience and clinical community. A post mortem human brain specimen was scanned on a 7T MRI scanner using a Diffusion Weighted Steady State Free Precession sequence. Tractography was performed with PROBTRACKX. The specimen was subsequently serially sectioned and stained for myelin using a modified Heidenhein-Woelke staining. Image registration permitted the 3D reconstruction of the histological sections and comparison with MRI. The spatial concordance between the two modalities was evaluated using ROC analysis and a similarity index (SI). ROC curves showed a high sensitivity and specificity in general. Highest measures were observed in the superior cerebellar peduncle with an SI of 0.72. Less overlap was found in the decussation of the DRTT at the level of the mesencephalon. The study demonstrates high spatial accuracy of post mortem probabilistic tractography of the DRTT when compared to a 3D histological reconstruction. This gives hopeful prospect for studying structure-function correlations in patients with cerebellar disorders using tractography of the DRTT.
Hypersensitivity reactions to small molecule drugs

Drug hypersensitivity reactions induced by small molecule drugs encompass a broad spectrum of adverse drug reactions with heterogeneous clinical presentations and mechanisms. These reactions are classified into allergic drug hypersensitivity reactions and non-allergic drug hypersensitivity reactions. At present, the hapten theory, pharmacological interaction with immune receptors (p-i) concept, altered peptide repertoire model, and altered T-cell receptor (TCR) repertoire model have been proposed to explain how small molecule drugs or their metabolites induce allergic drug hypersensitivity reactions. Meanwhile, direct activation of mast cells, provoking the complement system, stimulating or inhibiting inflammatory reaction-related enzymes, accumulating bradykinin, and/or triggering vascular hyperpermeability are considered as the main factors causing non-allergic drug hypersensitivity reactions. To date, many investigations have been performed to explore the underlying mechanisms involved in drug hypersensitivity reactions and to search for predictive and preventive methods in both clinical and non-clinical trials. However, validated methods for predicting and diagnosing hypersensitivity reactions to small molecule drugs and deeper insight into the relevant underlying mechanisms are still limited.
Object Tracking for Satellite Video based on Kernelized Correlation Filters and Three Frame Difference

Recently, correlation filters have yielded lots of promising results in the field of target tracking. However, when dealing with object tracking in satellite video, KCF tracker achieves poor results, because the size of the target is too small compared with the whole image, and the target and background are exactly similar. So, in this paper, we introduce the KCF tracker to the satellite video and propose the three frame difference algorithm to improve the performance of KCF tracker. For the purpose of reducing the probability of drifting in KCF tracker, a simple but effective target detection method: three frame difference algorithm is utilized to locate the target every once a few frames. Based on combining the KCF tracker and three frame difference algorithm, the proposed tracker achieves outperform top ranking trackers such as Struck and TLD on two datasets.
Hemodynamic indicators of the formation of tandem intracranial aneurysm based on a vascular restoration algorithm

Background Hemodynamic factors are believed to be closely related to IA growth. However, the underlying pathophysiological mechanism that induces the growth sequence in tandem intracranial aneurysms (IAs) remains unclear. Methods and results This study involved five patients with tandem IAs. Aneurysm models were reconstructed based on image datasets. A novel vascular restoration algorithm was proposed to generate the hypothetical geometry of the healthy parent vessel before each IA formation in the concatenated structure. Detailed hemodynamic patterns and morphological features were revealed under various growth sequences of tandem IAs to investigate the flow-driven mechanism of IA growth. Potential hemodynamic indicators of IA formation were proposed. Results The patient cases were divided into two groups based on the size difference of tandem IAs. In the group with a similar size of tandem IAs, the position of the vortex core was associated with the site of the secondary aneurysm, while in the group with a significant size difference of the IAs, the position with the maximum curvature of the parent vessel plays a significant role in aneurysm formation. Conclusions This study preliminarily revealed key hemodynamic and morphological indicators that determine the formation of tandem IAs. The proposed vascular restoration algorithm that provided the pre-aneurysm vasculature might be useful in investigating the flow-driven mechanism of IA growth, thus contributing to the risk evaluation of secondary aneurysm formation.
Automated model calibration with parallel MCMC: Applications for a cardiovascular system model

Computational physiological models continue to increase in complexity, however, the task of efficiently calibrating the model to available clinical data remains a significant challenge. One part of this challenge is associated with long calibration times, which present a barrier for the routine application of model-based prediction in clinical practice. Another aspect of this challenge is the limited available data for the unique calibration of complex models. Therefore, to calibrate a patient-specific model, it may be beneficial to verify that task-specific model predictions have acceptable uncertainty, rather than requiring all parameters to be uniquely identified. We have developed a pipeline that reduces the set of fitting parameters to make them structurally identifiable and to improve the efficiency of a subsequent Markov Chain Monte Carlo (MCMC) analysis. MCMC was used to find the optimal parameter values and to determine the confidence interval of a task-specific prediction. This approach was demonstrated on numerical experiments where a lumped parameter model of the cardiovascular system was calibrated to brachial artery cuff pressure, echocardiogram volume measurements, and synthetic cerebral blood flow data that approximates what can be obtained from 4D-flow MRI data. This pipeline provides a cerebral arterial pressure prediction that may be useful for determining the risk of hemorrhagic stroke. For a set of three patients, this pipeline successfully reduced the parameter set of a cardiovascular system model from 12 parameters to 8–10 structurally identifiable parameters. This enabled a significant ( > 4 × ) efficiency improvement in determining confidence intervals on predictions of pressure compared to performing a naive MCMC analysis with the full parameter set. This demonstrates the potential that the proposed pipeline has in helping address one of the key challenges preventing clinical application of such models. Additionally, for each patient, the MCMC approach yielded a 95% confidence interval on systolic blood pressure prediction in the middle cerebral artery smaller than ±10 mmHg (±1.3 kPa). The proposed pipeline exploits available high-performance computing parallelism to allow straightforward automation for general models and arbitrary data sets, enabling automated calibration of a parameter set that is specific to the available clinical data with minimal user interaction.
Manipulation of the crosstalk between tumor angiogenesis and immunosuppression in the tumor microenvironment: Insight into the combination therapy of anti-angiogenesis and immune checkpoint blockade

Immunotherapy has been recognized as an effective and important therapeutic modality for multiple types of cancer. Nevertheless, it has been increasing recognized that clinical benefits of immunotherapy are less than expected as evidenced by the fact that only a small population of cancer patients respond favorably to immunotherapy. The structurally and functionally abnormal tumor vasculature is a hallmark of most solid tumors and contributes to an immunosuppressive microenvironment, which poses a major challenge to immunotherapy. In turn, multiple immune cell subsets have profound consequences on promoting neovascularization. Vascular normalization, a promising anti-angiogenic strategy, can enhance vascular perfusion and promote the infiltration of immune effector cells into tumors via correcting aberrant tumor blood vessels, resulting in the potentiation of immunotherapy. More interestingly, immunotherapies are prone to boost the efficacy of various anti-angiogenic therapies and/or promote the morphological and functional alterations in tumor vasculature. Therefore, immune reprograming and vascular normalization appear to be reciprocally regulated. In this review, we mainly summarize how tumor vasculature propels an immunosuppressive phenotype and how innate and adaptive immune cells modulate angiogenesis during tumor progression. We further highlight recent advances of anti-angiogenic immunotherapies in preclinical and clinical settings to solidify the concept that targeting both tumor blood vessels and immune suppressive cells provides an efficacious approach for the treatment of cancer.
Studies of Molecular Dynamics of Fmoc-Alanine-d 3 through Solid State Deuteron Nuclear Magnetic Resonance

The idea of devising and validating various multi-parameter m odels for intramolecular motion in solid, N-protected amino acid derivatives originates from the desire to quantify side chain molecular motion in proteins. It is well recognized that protein side chain motions play an important role in controlling protein structure and conformation, which directly determines protein function. This structure-function relationship necessitates the quantitative investigation of protein side chain dynamics. In this thesis Fmoc-Alanine-d3 is chosen as the model system . Solid state deuteron quadrupole echo line shape analysis, m easurem ents of Zeem an (Tiz) and quadrupole order (TiQ) relaxation and the associated anisotropies are combined with computer simulations to investigate the methyl group dynamics. Tiz and Tiq were m easured using saturation recovery with quadrupole echo detection (SRQE) and Broadband Jeener Broekaert (BBJB) techniques respectively at 7.06 T between 230K and 330K. And at 17.6 T, Tiz w as also measured using SRQE between 190K and 330K. A smaller methyl deuteron quadrupole coupling constant w as found for FmocAlanine-d3 than for Alanine-d3, indicating the existence of an additional motional process in the Fmoc derivative. The Arrhenius activation energy calculated from the relaxation rates of the horns of the low field quadrupole echo spectra is Ea = 13.6 ± 0.8 k j /m o l . This indicates a less severe sterically crowded environment for the rotating CD3 group than that found in crystalline Alanine-d3, for which Ea = 20k]/m ol. Motional spectral densities are derived from the best-fit simulated R-iz and Riq profiles and compared to the experimental data. The Riz and Riq profiles exhibit unusual orientation dependence, which cannot be adequately reproduced by threefold methyl rotation alone. Therefore, more elaborate m odels are proposed that include motion of the C3v rotation axis of the methyl group. Stochastic Liouville formalism is applied to describe modulation of the threefold methyl rotational jumps by libration of the C3v axis. Approximate agreem ent with experimental data is found for two variants of this formalism, describing the libration either a s two-site angular "jumps" or four-site "wobbling" in a cone respectively. However, the two-site jump model produces a significant non-vanishing asymmetry parameter, which is not observed in equilibrium line shapes, and therefore the more symmetric foursite wobble model is adopted. Finally, activation energies are calculated for the threefold methyl rotation and four-site wobbling based on the Arrhenius plots of the best-fit motional rates k3 and k4. TABLE OF CONTENTS Acknowledgem ents iii List of Tables iv List of Figures v Chapter
Functional Relationships of a Geospatial System for Reforestation of a Territory Using Geographic Information Systems

The analysis presented was carried out in an area of Loja Province, Ecuador, with the objective of determining the functioning of the different geospatial systems for the evaluation of the reforestation of the territory, degraded by different activities that are developed in open sky. It was departed from the running of the model of Hottel, that considering the absence of data series of meteorological variables, theoretical methods were used for the calculation of the insolation variable, in Labview software. Considering the affectations by the presence of cloudiness as well as by the surfaces of shade orographic, this was implemented for a Geographic Information System (GIS) taking advantage of the characteristics of these applications for spatial analyses. The analysis of temperature and precipitation was also included considering the variations in altitude [1] for the realization of the functional analysis of the territory. From the joint analyses of both methods were obtained maps that allowed defining the zones with conditions of dampening and flows of radiation and caloric potentials, whose result will allow the specialists of the biotic part to determine the species for reforestation in the area. The digital elevation model (MDE) of the South Region of Ecuador was obtained and the maps of slopes, orientation of the surfaces and slopes oriented, from which, through analysis of cross-images allowed the determination of the maps of radiation, temperature, and precipitation considering the geomorphologic characteristics. The resulting maps are presented.
Temperature Diffusivity Measurement and Nondestructive Testing Requiring No Extensive Sample Preparation and Using Stepwise Point Heating and IR Thermography

This chapter describes a modification to the laser flash method that allows determining temperature diffusivity and nondestructive testing of materials and construc-tions without cutting samples of predefined geometry. Stepwise local heating of the studied object surface at a small spot around 0.1 mm radius with simultaneous high temporary-spatial resolution infrared (IR) filming of the transient temperature distribution evolution with a thermal camera provides a wide range of possibilities for material characterization and sample testing. In case of isotropic and macroscopic homogeneous materials, the resulting transient temperature distribution is radially symmetric that renders possible to improve temperature measurement accuracy by averaging many pixels of the IR images located at the same distance from the heating spot center. The temperature diffusivity measurement can be conducted either on thin plates or on massive samples. The developed emissivity independent in plain IR thermographic method and mathematical algorithms enable thermal diffusivity measurement for both cases with accuracy around a few per cent for a wide range of materials starting from refractory ceramics to well-conducting metals. To detect defects, the differential algorithm was used. Subtracting averaged radial symmetric temperature distribution from the original one for each frame makes local inhomogeneities in the sample under study clearly discernible. When applied to crack detection in plates, the technique demonstrates good sensitivity to part-through cracks located both at the visible and invisible sides of the studied object.
Book review of the adaptable mind: What neuroplasticity and neural reuse tells us about language and cognition

From the works of Noam Chomsky to Jerry Fodor, the modularity of mind has been deeply rooted in cognitive science. From the “modular” perspective, cognition consists of functionally and anatomically isolable subsystems. Therefore, it is reasonable to assume a language module or a hardwired language organ that is functionally and anatomically different from the other cognitive modules (e.g., vision, olfaction, motor). However, evidence from neuroscience casts doubt on this modular hypothesis. It has been shown that many brain regions are likely to be reused and recycled by various neural communities in order to serve various cognitive functions. If this is the case, language and other cognitive faculties should not be considered modules, since they cannot be realized in special-purpose, special-structure regions. Therefore, it is time to change our understanding of our brains.
Leveraging multiple data types to estimate the size of the Zika epidemic in the Americas

Several hundred thousand Zika cases have been reported across the Americas since 2015. Incidence of infection was likely much higher, however, due to a high frequency of asymptomatic infection and other challenges that surveillance systems faced. Using a hierarchical Bayesian model with empirically-informed priors, we leveraged multiple types of Zika case data from 15 countries to estimate subnational reporting probabilities and infection attack rates (IARs). Zika IAR estimates ranged from 0.084 (95% CrI: 0.067–0.096) in Peru to 0.361 (95% CrI: 0.214–0.514) in Ecuador, with significant subnational variability in every country. Totaling infection estimates across these and 33 other countries and territories, our results suggest that 132.3 million (95% CrI: 111.3-170.2 million) people in the Americas had been infected by the end of 2018. These estimates represent the most extensive attempt to determine the size of the Zika epidemic in the Americas, offering a baseline for assessing the risk of future Zika epidemics in this region.
Uncertainty in satellite estimates of global mean sea-level changes, trend and acceleration

Abstract. Satellite altimetry missions now provide more than 25 years of accurate, continuous and quasi-global measurements of sea level along the reference ground track of TOPEX/Poseidon. These measurements are used by different groups to build the Global Mean Sea Level (GMSL) record, an essential climate change indicator. Estimating a realistic uncertainty in the GMSL record is of crucial importance for climate studies, such as assessing precisely the current rate and acceleration of sea level, analysing the closure of the sea-level budget, understanding the causes of sea-level rise, detecting and attributing the response of sea level to anthropogenic activity, or calculating the Earth's energy imbalance. Previous authors have estimated the uncertainty in the GMSL trend over the period 1993–2014 by thoroughly analysing the error budget of the satellite altimeters and have shown that it amounts to ±0.5 mm yr−1 (90 % confidence level). In this study, we extend our previous results, providing a comprehensive description of the uncertainties in the satellite GMSL record. We analysed 25 years of satellite altimetry data and provided for the first time the error variance–covariance matrix for the GMSL record with a time resolution of 10 days. Three types of errors have been modelled (drifts, biases, noises) and combined together to derive a realistic estimate of the GMSL error variance–covariance matrix. From the latter, we derived a 90 % confidence envelope of the GMSL record on a 10 d basis. Then we used a least squared approach and the error variance–covariance matrix to assess the GMSL trend and acceleration uncertainties over any 5-year time periods and longer in between October 1992 and December 2017. Over 1993–2017, we have found a GMSL trend of 3.35±0.4 mm yr−1 within a 90 % confidence level (CL) and a GMSL acceleration of 0.12±0.07 mm yr−2 (90 % CL). This is in agreement (within error bars) with previous studies. The full GMSL error variance–covariance matrix is freely available online: https://doi.org/10.17882/58344 (Ablain et al., 2018).
Simulation of the Energy Efficiency Dependence on Threshold Voltage in the CMOS Inverter

In this work, we show the CMOS inverter sensitivity of the threshold voltage on the channel doping in dynamic mode. Simulated transient response of the inverter determines the propagation delays for the high-low and low-high transitions. Current emissions at the time of switching were reduced by optimizing the channel impurities. According to the simulation results, it is possible to estimate the efficiency of energy saving depending on the threshold voltages of NMOS and PMOS transistors in the CMOS inverter.