Unconventional Field Dependence of Magnetoresistance of (TMTSF)2ClO4 Studied by 46-T Pulsed Magnetic Field System

A new TTP donor, Me-DH-TTP (2-methyl-5-(1,3-dithiolan-2-yliden)-1,3,4,6-tetrathiapentalene), was designed to realize a system with large on-site Coulomb repulsion as compared with the previously known bis-fused type TTP donors. Probably as a consequence, (Me-DH-TTP)₂AsF₆ exhibits semiconducting behavior from room temperature to liquid helium temperature. By increasing pressure, metallic behavior appears below 300 K, and with distinct metal-insulator (M-I) transition up to 2.2 GPa. This M-I transition suddenly disappears beyond 2.5 GPa, and metallic state is stabilized down to 2.6 K. We discuss the possibility of quantum critical point around 2.4 GPa.     

Calibration of the Density-Gradient model by using the multidimensional effective-mass Schrödinger equation

A calibration method is developed for the electron effective mass in the Density-Gradient model. This method uses the two- and three-dimensional effective-mass Schrödinger equations, which are solved for bounded quantum systems. The electron effective mass is computed by fitting the electron concentration computed by using the Density-Gradient model to the electron concentration computed by using the Schrödinger equation. Results for strongly confined silicon system with (100), (110), and (111) crystallographic orientations are presented. It is shown that the effective mass varies with the shape and dimensions of the quantum box. In device simulations, one should use the value of m_n that corresponds to the right shape and dimensions of the confinement region in the device.     

Creating and Rendering Convolution Surfaces

Implicit surfaces obtained by convolution of multi-dimensional primitives with some potential function, are a generalisation of popular implicit surface models: blobs, metaballs and soft objects. These models differ in their choice of potential function but agree upon the use of underlying modelling primitives, namely, points. In this paper a method is described for modelling and rendering implicit surfaces built upon an expanded set of skeletal primitives: points, line segments, polygons, arcs and planes. An analytical solution to the convolution is described. This solution offers a more accurate and robust representation of the resultant implicit surface than previous methods. An algorithm for ray-tracing the surfaces formed through convolution of any combination of these primitives is also outlined.     

About the Collatz conjecture

This paper refers to the Collatz conjecture. The origin and the formalization of the Collatz problem are presented in the first section, named “Introduction”. In the second section, entitled “Properties of the Collatz function”, we treat mainly the bijectivity of the Collatz function. Using the obtained results, we construct a (set of) binary tree(s) which “simulate(s)”– in a way that will be specified – the computations of the values of the Collatz function. In the third section, we give an “efficient” algorithm for computing the number of iterations (recursive calls) of the Collatz function. A comparison between our algorithm and the standard one is also presented, the first being at least 2.25 “faster” (3.00 in medium). Finally, we describe a class of natural numbers for which the conjecture is true. Received 28 April 1997 / 10 June 1997     

Redundant Sensor Calibration Monitoring Using Independent Component Analysis and Principal Component Analysis

This paper presents a comparison of methods for industrial on-line sensor calibration monitoring for redundant sensors. Principal component analysis (PCA) and independent component analysis (ICA) techniques are developed and compared using both simulated data and data sets from an operating nuclear power plant. The performance is dependent on the types of noise sources; however, under most conditions ICA outperforms PCA, based on the bias and variance of their respective parameter estimates. A case study is included to demonstrate the usefulness of both techniques for the early detection of sensor drift.     

Cardiac Toxicity Associated with Immune Checkpoint Inhibitors: A Systematic Review

Immune checkpoint inhibitors (ICIs) are an important advancement in the field of cancer treatment, significantly improving the survival of patients with a series of advanced malignancies, like melanoma, non-small cell lung cancer (NSCLC), hepatocellular carcinoma (HCC), renal cell carcinoma (RCC), and Hodgkin lymphoma. ICIs act upon T lymphocytes and antigen-presenting cells, targeting programmed cell death protein 1 (PD1), programmed cell death protein ligand 1 (PD-L1), and cytotoxic T-lymphocyte antigen 4 (CTLA-4), breaking the immune tolerance of the T cells against malignant cells and enhancing the body’s own immune response. A variety of cardiac-adverse effects are associated with ICI-based treatment, including pericarditis, arrhythmias, cardiomyopathy, and acute coronary syndrome, with myocarditis being the most studied due to its often-unexpected onset and severity. Overall, Myocarditis is rare but presents an immune-related adverse event (irAE) that has a high fatality rate. Considering the rising number of oncological patients treated with ICIs and the severity of their potential adverse effects, a good understanding and continuous investigation of cardiac irAEs is of the utmost importance. This systematic review aimed to revise recent publications (between 2016–2022) on ICI-induced cardiac toxicities and highlight the therapeutical approach and evolution in the selected cases.     

Circulating Small EVs miRNAs as Predictors of Pathological Response to Neo-Adjuvant Therapy in Breast Cancer Patients

Neo-adjuvant therapy (NAT) is increasingly used in the clinic for the treatment of breast cancer (BC). Pathological response to NAT has been associated with improved patients’ survival; however, the current techniques employed for assessing the tumor response have significant limitations. Small EVs (sEVs)-encapsulated miRNAs have emerged as promising new biomarkers for diagnosis and prediction. Therefore, our study aims to explore the predictive value of these miRNAs for the pathological response to NAT in BC. By employing bioinformatic tools, we selected a set of miRNAs and evaluated their expression in plasma sEVs and BC biopsies. Twelve miRNAs were identified in sEVs, of which, miR-21-5p, 221-3p, 146a-5p and 26a-5p were significantly associated with the Miller–Payne (MP) pathological response to NAT. Moreover, miR-21-5p, 146a-5p, 26a-5p and miR-24-3p were independent as predictors of MP response to NAT. However, the expression of these miRNAs showed no correlation between sEVs and tissue samples, indicating that the mechanisms of miRNA sorting into sEVs still needs to be elucidated. Functional analysis of miRNA target genes and drug interactions revealed that candidate miRNAs and their targets, can be regulated by different NAT regimens. This evidence supports their role in governing the patients’ therapy response and highlights their potential use as prediction biomarkers.     

Graph structure in the Web

The study of the Web as a graph is not only fascinating in its own right, but also yields valuable insight into Web algorithms for crawling, searching and community discovery, and the sociological phenomena which characterize its evolution. We report on experiments on local and global properties of the Web graph using two AltaVista crawls each with over 200 million pages and 1.5 billion links. Our study indicates that the macroscopic structure of the Web is considerably more intricate than suggested by earlier experiments on a smaller scale.     

Design of ruthenium-zeolite nanocomposites for enhanced hydrocarbon synthesis from syngas

The purpose of this work is the design of metal-zeolite nanocomposite catalysts for Fischer–Tropsch synthesis, containing ruthenium nanoparticles, uniformly distributed in the hierarchical BEA zeolites. The use of ruthenium avoids the formation of inert hardly reducible inert metal silicates and metal aluminates. Carbon nanotubes with supported metal oxide nanoparticles play the role of sacrificial template, which allows creating mesoporosity and bringing metallic functionality inside the zeolite matrix. Both mesoporosity and larger micropores of the BEA zeolite facilitate the localization of metal nanoparticles within the zeolite structure and diffusion of the reacting molecules. Compared to the conventional zeolite supported metal catalysts, the synthesized hierarchical ruthenium-zeolites exhibited much higher activity and lower methane selectivity in Fischer–Tropsch synthesis.