Miracle-dz/UniFAR-FTUs huggingface dataset:
Real Check RIO: A Real-World Analysis of Nivolumab in First Line Metastatic Melanoma Assessing Efficacy, Safety and Predictive Factors

Simple Summary With the recent advances of immunotherapy in the modern oncology era, the landscape of malignant melanoma has changed. However, it is not clear from the data across the various trials how to design the best therapeutic strategy. Hence, we decided to study the role of potential predictive biomarkers in a real-world, unselected population from Romania and to analyze the results of the single agent Nivolumab as first-line treatment in metastatic melanoma patients. Based on our findings, we believe that further studies could be designed to better map the immune landscape in metastatic melanoma in order to provide further perspectives on treatment options and choice. Abstract We performed a retrospective study on 51 metastatic melanoma patients treated with Nivolumab in first line, at the Regional Institute of Oncology (RIO) Iasi, Romania between April 2017 and December 2019. We studied the efficacy and safety of anti-PD-1 immune checkpoint inhibitor therapy on a treatment-naive population. After a median follow-up of 36 months, the median progression free survival (PFS) was 26 months (95% CI, 15–36) and the median overall survival (OS) was 31 months (95% CI, 20.1–41.8). At 12 months after the initiation of immunotherapy, the percentage of patients alive was 70%, and at 24 months 62.5%. The most common adverse events observed were dermatological (23.5%) and grade ≥3 was identified in 4 (6.8%) patients. Multivariate analysis indicated that the presence of liver metastases (HR 4.42; 95% CI: 1.88–10.4, p = 0.001) and a neutrophils/lymphocytes ratio (NLR) were associated with poor survival (HR 3.21; 95% CI: 1.04–9.87, p = 0.04). Although retrospective data on a small group of patients were analyzed, we can conclude that our results in RIO are similar to those described in clinical trials and other real-world studies. Our study highlights the potential usefulness of liver metastases and NLR as novel predictive factors in clinical decision-making.
Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data

Standard approaches to semiparametric modelling of two-sample survival data are not appropriate when the two survival curves cross. We introduce a two-sample model that accommodates crossing survival curves. The two scalar parameters of the model have the interpretations of being the short-term and long-term hazard ratios respectively. The time-varying hazard ratio is expressed semiparametrically by the two scalar parameters and an unspecified baseline distribution. The new model includes the Cox model and the proportional odds model as submodels. For inference we use a pseudo maximum likelihood approach that can be expressed via some simple estimating equations, analogous to that for the maximum partial likelihood estimator of the Cox model, that provide consistent and asymptotically normal estimators. Simulation studies show that the estimators perform well for moderate sample sizes. We also illustrate the methods with a real-data example. The new model can be extended easily to the regression setting. Copyright 2005, Oxford University Press.
On the interactions of unit roots and exogeneity

The paper considers the impact on estimation and inference of interactions between the existence of unit roots in a data generation process and the presence or absence of weak and strong exogeneity of conditioning variables for the parameters of interest in individual cointegrated linear relationships. The asymptotic distributions of estimators for single equation conditional linear relations are analyzed in conjunction with a Monte Carlo study. The results confirm the important role of weak exogeneity in single equation estimation from integratedcointegrated data; highlight the advantages of using an asymptotic analysis to understand the complicated interactions observed; and reveal the accuracy of the limiting distributions in characterizing finite sample behaviour.
User-defined high impulsive frequency acquisition model for mechanical damage identification

In the past few decades, time–frequency (TF) methods have become increasingly popular in the field of modal identification and structural health monitoring. The general and significant shortfalls of the TF models are the distributed and vague frequency components as an output. To overcome the cons of the initial TF technique, segregation of the modes incorporated within the affected vibration signatures evolved eventually. The most utilized and preferred technique can be named empirical mode decomposition (EMD) and its variants. However, these variants, along with the basic framework, possess the multi-mode tendency, which further compels the extension of the whole damage identification procedure. This work presents the development of a temporally evolved, generalized and high impulsive frequency acquisition model for structural damage identification. To meet the said outcome, variational mode decomposition (VMD) is considered an optimization-based signal decomposition tool that utilizes the contents of the generated modal responses. This work also aims to investigate the applicability of VMD for the purpose of structural damage identification for the following situations: the old ADA steel bridge under vehicle-induced vibration for various damage scenarios; a three-story shear frame building model. Along with the said validation of the proposed condition monitoring model, this paper addresses the need of stable and reliable novel damage indicator (DI) as a statistical alteration of the extracted instantaneous outputs. The proposed DI as the mean of the ratio of the instantaneous outputs collectively indicates the relative capacity of the structure to produce a stable response. The selected outputs are instantaneous frequency, phase and energy, taken into consideration to depict the physical alterations in the measured response. The proposed DI evidently explains the physical relation of the involved factors with the degradation causes in the considered structure. The DI also reflects the remaining usefulness of the system and provides the measurements in safety aspects to the operators. The results so obtained are well competent for real bridge structures under the influence of dynamic loading conditions induced by vehicle movements.
Uncertainty evaluation of displacement gradients measured by electronic speckle pattern shearing interferometry (ESPSI)

Electronic speckle pattern shearing interferometry (ESPSI), also known as shearography, is a whole-field optical technique used to generate phase fringe patterns that allow us to evaluate displacement gradients. In this work, we report on a Monte Carlo computer simulation to calculate the standard uncertainties associated with the displacement gradients obtained from the experimental data yielded by ESPSI. The displacements were induced by applying tensile load to a metallic sheet sample. At each point of the illuminated area, the standard uncertainty of the gradient was taken as the standard deviation of the series of outcomes obtained by a large number of gradient evaluations. These evaluations were performed by using sets of values generated according to the probability density functions (PDFs) that we assigned to the experimental data. The reported method to evaluate the uncertainties of the displacement gradients agrees with international recommendations.
Identification of parameters in systems of ordinary differential equations using quasilinearization and data perturbation

Given a set of observed data for a particular physical phenomenon, the problem of computing the “best fit” parameters for the mathematical model describing the phenomenon is a common problem in process or reaction mechanism identification. If the mathematical model comprises a set of non-linear ordinary differential equations, this leads to a non-linear boundary value problem. A very powerful way of attacking this class of problem uses an adaptation of the Newton-Raphson-Kantorovich procedure, called quasilinearization, which regards the non-linear problem as the limit of a sequence of linear problems. Starting from an initial trial solution, convergence if it does occur, occurs rapidly; further, convergence is assured if the initial guess is “close enough” to the true solution. The difficulty of making a good initial guess, a serious limitation of the method in the past, can in principle be overcome by the algorithm proposed. When a given vector may not be within the domain of convergence of the original problem, it must be within the domain of convergence of some other derived problem. The latter may then be perturbed towards the original problem in a finite number of steps. In the case of process identification, new data points are derived; these are subsequently adjusted until they coincide with the original data. The algorithm has been successfully applied to several examples from recent chemical engineering literature. Si l'on a en main une serie de resultats d'observation pour un phenomene physique particulier, un probleme courant est de calculer les parametres qui conviennent le mieux au modele mathematique qui serf a decrire le phenomene, lors de l'identification du mecanisme d'un procede ou d'une reaction. Si le modele mathematique comprend une serie d'equationg differentielles ordinaires et non-lineaires, il s'agit d'un probleme de valeur-limite non-lineaire et l'un des meilleurs moyens de l'attaquer est la quasi-linearisation, une adaptation du procede de Newton, Raphson et Kantorovich, ou l'on considere le probleme non-lineaire comme la limite d'une serie de probleme lineaires. Si l'on part d'une solution initiate d'essai, la convergence, si elle se produit, survient rapidement; en outre, la convergence est certaine, si l'estimation initiale est assez proche de la solution reelle. On peut surmonter par l'algorithme propose la difficulte eprouvee a faire une bonne estimation initiale, ce qui a limite serieusement l'emploi de la methode dans le passe. Lorsqu'un vecteur d'essai donne n'entre pas dans le domaine de convergence du probleme original, il doit entrer dans celui d'un autre probleme qui en derive; on peut alors ramener ce dernier au probleme original dans un nombre d'etapes defini. Dans le cas de l'identification d'un procede, on en deduit de nouveaux points de repere, qu'on ajuste subsequemment jusqu'a ce qu'ils coincident avec les resultats originaux. On a applique l'algorithme avec succes a plusieurs exemples provenant des travaux recents en genie chimique.
The Impact of Real Geometries on Three-Dimensional Separations in Compressors

This paper considers the effect of small variations in leading edge geometry, leading edge roughness, leading edge fillet, and blade fillet geometry on the three-dimensional separations found in compressor blade rows. The detrimental effects of these separations have historically been predicted by correlations based on global flow parameters, such as blade loading, inlet boundary layer skew, etc., and thus ignoring small deviations such as those highlighted above. In this paper it is shown that this may not be the case and that certain, engine representative geometry deviations can have an effect equivalent to an increase in blade loading of 10%. Experiments were performed at the stator hub of a low-speed, single-stage compressor. The results show that any deviation which causes suction surface transition to move to the leading edge over the first 30% of span will cause a large growth in the size of the hub separation, doubling its impact on loss. The geometry deviations that caused this, and are thus of greatest concern to a designer, are changes in leading edge quality and roughness around the leading edge, which are characteristic of an eroded blade.
EXPONENTIALLY FITTED INTERPOLATION FORMULAS INVOLVING FIRST AND HIGHER-ORDER DERIVATIVES

We construct exponentially fitted interpolation formulas using the values of the ! -dependent function f as well as its derivatives up to the nth order at a finite number of nodes on a closed interval Ω: The function f is of the form, f (x) = f1(x) cos(! x) + f2(x) sin(! x);x 2 Ω; where f1 and f2 are smooth enough to be approximated by polynomials on Ω: Some properties of the formulas are newly found. The properties are numerically investigated and reexamined by producing some figures.
INSIGHTS INTO THE HIGH-ENERGY γ-RAY EMISSION OF MARKARIAN 501 FROM EXTENSIVE MULTIFREQUENCY OBSERVATIONS IN THE FERMI ERA

We report on the γ-ray activity of the blazar Mrk 501 during the first 480 days of Fermi operation. We find that the average Large Area Telescope (LAT) γ-ray spectrum of Mrk 501 can be well described by a single power-law function with a photon index of 1.78 ± 0.03. While we observe relatively mild flux variations with the Fermi-LAT (within less than a factor of two), we detect remarkable spectral variability where the hardest observed spectral index within the LAT energy range is 1.52 ± 0.14, and the softest one is 2.51 ± 0.20. These unexpected spectral changes do not correlate with the measured flux variations above 0.3 GeV. In this paper, we also present the first results from the 4.5 month long multifrequency campaign (2009 March 15—August 1) on Mrk 501, which included the Very Long Baseline Array (VLBA), Swift, RXTE, MAGIC, and VERITAS, the F-GAMMA, GASP-WEBT, and other collaborations and instruments which provided excellent temporal and energy coverage of the source throughout the entire campaign. The extensive radio to TeV data set from this campaign provides us with the most detailed spectral energy distribution yet collected for this source during its relatively low activity. The average spectral energy distribution of Mrk 501 is well described by the standard one-zone synchrotron self-Compton (SSC) model. In the framework of this model, we find that the dominant emission region is characterized by a size ≲0.1 pc (comparable within a factor of few to the size of the partially resolved VLBA core at 15–43 GHz), and that the total jet power (≃1044 erg s−1) constitutes only a small fraction (∼10−3) of the Eddington luminosity. The energy distribution of the freshly accelerated radiating electrons required to fit the time-averaged data has a broken power-law form in the energy range 0.3 GeV–10 TeV, with spectral indices 2.2 and 2.7 below and above the break energy of 20 GeV. We argue that such a form is consistent with a scenario in which the bulk of the energy dissipation within the dominant emission zone of Mrk 501 is due to relativistic, proton-mediated shocks. We find that the ultrarelativistic electrons and mildly relativistic protons within the blazar zone, if comparable in number, are in approximate energy equipartition, with their energy dominating the jet magnetic field energy by about two orders of magnitude.
Mean, median, mode

Summary This note is an attempt to avoid doing the same search for the third time. It happened twice in my life that I wished to prove that the median is located between mean and mode for certain B-distributions: first in 1953, next in 1976. For arbitrary distributions the result is sometimes referred to as Fechner's theorem. Of course it does not hold in general. In order to prove the result for particular distributions one can often use an elegant theorem of Timerding. There is a nice relationship with the standardized third central moment.
Multiobjective Bayesian Optimization for Aeroengine Using Multiple Information Sources

Aeroengine performance optimization rem- ains significant for both efficiency and safety during specific operating conditions. Previous works usually solve this optimization problem under a single-objective optimization framework, while multiple objectives need to be optimized simultaneously. Besides, the underlying optimization process requires a variety of function evaluations, and the evaluation cost for an aeroengine is expensive. In reality, the aeroengine model has multiple information sources with different costs and accuracy. The different costs and accuracy of the multiple information sources should be traded off to guide the search for the optimal in a cost-efficient way. Therefore, we propose a multi-information-source framework for enabling efficient multiobjective Bayesian optimization. We construct the surrogate model with a multifidelity Gaussian process and choose the location–source pair with a modified acquisition function. Finally, we apply the proposed method to improve the performance indexes of the aeroengine, which confirms the efficiency of the proposed algorithm.
Effects of Stroke Rehabilitation Using Gait Robot-Assisted Training and Person-Centered Goal Setting: A Single Blinded Pilot Study

Many stroke survivors have difficulties due to the mobility and activities required in daily living. A walking impairment negatively affects the independent lifestyle of stroke patients, requiring intensive post-stroke rehabilitation. Therefore, the purpose of this study was to examine the effects of stroke rehabilitation using gait robot-assisted training and person-centered goal setting on mobility, the activities of daily living, stroke self-efficacy, and health-related QoL in stroke patients with hemiplegia. An assessor-blinded quasi-experimental study with a pre-posttest nonequivalent control group was used. Participants who were admitted to the hospital with a gait robot-assisted training system were assigned to the experimental group, and those without gait robots were assigned to the control group. Sixty stroke patients with hemiplegia from two hospitals specialized in post-stroke rehabilitation participated. Stroke rehabilitation using gait robot-assisted training and person-centered goal setting for stroke patients with hemiplegia was conducted for a total of six weeks. There were significant differences between the experimental group and control group in the Functional Ambulation Category (t = 2.89, p = 0.005), balance (t = 3.73, p < 0.001), Timed Up and Go (t = −2.27, p = 0.027), Korean Modified Barthel Index (t = 2.58, p = 0.012), 10 m Walking test (t = −2.27, p = 0.040), stroke self-efficacy (t = 2.23, p = 0.030), and health-related quality of life (t = 4.90, p < 0.001). A gait robot-assisted rehabilitation using goal setting for stroke patients with hemiplegia improved gait ability, balance ability, stroke self-efficacy, and health-related quality of life in stroke patients.
Long-Term Olfactory Memory in African Elephants

Simple Summary African elephants are known for their long memory; this is also valid for their olfactory sense and their ability to discriminate scents. This feature is highly important for these mammals to maintain their family bonds and to differentiate between familiar and unfamiliar individuals. Thus far, scientific data only testify to an olfactory memory of up to one year for African elephants. This study investigated the long-term olfactory memory of two mother-daughter pairs that were separated for 2 and 12 years, respectively. Results showed that all four elephants were able to recognize their separated relatives just by the scent of feces, thereby giving the empirical implication of olfactory memory in African elephants of up to 12 years. Abstract African elephants are capable of discriminating scents up to a single changed molecule and show the largest reported repertoire of olfactory receptor genes. Olfaction plays an important role in family bonding. However, to the best of our knowledge, no empirical data exist on their ability to remember familiar scents long-term. In an ethological experiment, two mother-daughter pairs were presented with feces of absent kin, absent non-kin, and present non-kin. Video recordings showed reactions of elephants recognizing kin after long-term separation but only minor reactions to non-kin. Results give the empirical implication that elephants have an olfactory memory longer than 1 year and up to 12 years and can distinguish between kin and non-kin just by scent. These findings confirm the significance of scent for family bonds in African elephants.
An analog+digital phase-frequency detector for phase locking of a diode laser to an optical frequency comb

Optical phase locking of a diode laser to a mode of a femtosecond optical comb has been achieved with a system that combines the advantages of analog and digital phase detectors. Low noise and fast response are combined with a broad phase range and lock reliability. Details of the circuit are illustrated, and properties of different phase detectors in view of optical frequency measurements are discussed.
Reliable N-Glycan Analysis–Removal of Frequently Occurring Oligosaccharide Impurities by Enzymatic Degradation

Glycosylation, especially N-glycosylation, is one of the most common protein modifications, with immense importance at the molecular, cellular, and organismal level. Thus, accurate and reliable N-glycan analysis is essential in many areas of pharmaceutical and food industry, medicine, and science. However, due to the complexity of the cellular glycosylation process, in-depth glycoanalysis is still a highly challenging endeavor. Contamination of samples with oligosaccharide impurities (OSIs), typically linear glucose homo-oligomers, can cause further complications. Due to their physicochemical similarity to N-glycans, OSIs produce potentially overlapping signals, which can remain unnoticed. If recognized, suspected OSI signals are usually excluded in data evaluation. However, in both cases, interpretation of results can be impaired. Alternatively, sample preparation can be repeated to include an OSI removal step from samples. However, this significantly increases sample amount, time, and effort necessary. To overcome these issues, we investigated the option to enzymatically degrade and thereby remove interfering OSIs as a final sample preparation step. Therefore, we screened ten commercially available enzymes concerning their potential to efficiently degrade maltodextrins and dextrans as most frequently found OSIs. Of these enzymes, only dextranase from Chaetomium erraticum and glucoamylase P from Hormoconis resinae enabled a degradation of OSIs within only 30 min that is free of side reactions with N-glycans. Finally, we applied the straightforward enzymatic degradation of OSIs to N-glycan samples derived from different standard glycoproteins and various stem cell lysates.
The potential for artificial intelligence in healthcare

Artificial intelligence (AI) is emerging as a promising technology for transforming the healthcare industry. The potential of AI lies in its ability to analyze vast amounts of data and identify patterns that can lead to better diagnosis, treatment, and patient outcomes. This abstract explores the potential for artificial intelligence in healthcare. The study highlights the various applications of AI in healthcare, such as medical imaging analysis, drug discovery, and personalized medicine. The study reviews the benefits of AI in healthcare, such as increased efficiency, accuracy, and cost savings. The study also examines the challenges of implementing AI in healthcare, such as data security and privacy concerns and regulatory barriers. The study concludes that artificial intelligence has the potential to revolutionize the healthcare industry, enabling more accurate diagnoses, personalized treatments, and improved patient outcomes. As the technology continues to advance, the healthcare industry will need to address the challenges of implementing AI while maintaining patient privacy and regulatory compliance. Despite these challenges, the benefits of AI in healthcare are clear, and the technology is poised to transform the industry in the coming years.