Constraints on CD4 recovery postchemotherapy in adults: thymic insufficiency and apoptotic decline of expanded peripheral CD4 cells

To examine the mechanisms of CD4 reconstitution in an adult population, lymphocyte repopulation was assessed following dose-intense chemotherapy in 25 breast cancer patients, ages 33 to 69 years. Chemotherapy resulted in a greater than 60% reduction in total CD4 T cells and, in particular, a greater than 90% loss of the CD45RA+ CD4 cells. CD4 recovery was protracted, achieving less than 50% of pretreatment levels after 12 to 14 months. Two facets of the CD4 recovery were notable. First, generation of CD45RA+ CD4 cells played only a minor role in the first year, suggesting that thymic production was not the main route of CD4 regeneration. Indeed, recovery of CD45RA+ CD4 cell levels remained limited in half of the patients even after 2 years. Second, expansion of the mature peripheral CD4 cells (CD45RO+) remaining after chemotherapy was the main source of early CD4 repopulation, peaking at 3 to 6 months postchemotherapy. This expansion was limited in duration, however, and was followed by a secondary decline, such that the total CD45RO+ CD4 levels at 9 to 12 months were lower than at 6 months. When stimulated by mitogens, an increased susceptibility to apoptosis was observed in postchemotherapy CD4 cells as compared with those from normal donors. The elevated expression of markers such as HLA-DR during chemotherapy and for several months postchemotherapy is consistent with the presence of an activated T-cell population. CD4 apoptotic frequency correlated with the frequency of HLA-DR expression on T cells. Thus, CD4 recovery is constrained in adults by a limited thymic regenerative capacity and by an increased susceptibility to apoptosis within the expanding peripheral CD4 population.     

Energy inefficiency diagnosis in industrial process through one-class machine learning techniques

In the era of Industry 4.0, the ease of access to precise measurements in real-time and the existence of machine-learning (ML) techniques will play a vital role in building practical tools to isolate inefficiencies in energy-intensive processes. This paper aims at developing an abnormal event diagnosis (AED) tool based on ML techniques for monitoring the operation of industrial processes. This tool makes it easier for operators to accomplish their tasks and to make quick and accurate decisions to ensure highly efficient processes. One of the most popular ML techniques for AED is the multivariate statistical control (MSC) method; it only requires the dataset of the normal operating conditions (NOC) to detect and identify the variables that contribute to abnormal events (AEs). Despite the popularity of MSC, it is challenging to select the appropriate method for detecting and isolating all possible abnormalities a complex industrial process can experience. To address this limitation and improve efficiency, we have developed a generic methodology that integrates different ML techniques into a unified multiagent based approach, the selected ML techniques are supposed to be built using only the normal operating condition. For the sake of demonstration, we chose a combination of two ML methods: principal component analysis and k-nearest neighbors (k-NN). The k-NN was integrated into the proposed multiagent to take into account the nonlinearity and multimodality that frequently occur in industrial processes. In addition, we modified a k-NN method proposed in the literature to reduce computation time during real-time detection and isolation. Finally, the proposed methodology was successfully validated to monitor the energy efficiency of a reboiler located in a thermomechanical pulp mill.

     

Effect of the percentage carbon equivalent on the nodule characteristics,density and modulus of elasticity of ductile cast iron

Successful melting and Mg treatment were conducted using a vortex unit which produced spheroidal graphite (SG) Fe ingots having a percentage carbon equivalent (%CE) ranging from 3.782 to 5.240. Microstructure examination revealed graphite nodules embedded in a white matrix (unetched condition). The variation of %CE proved to have a pronounced effect on the nodule characteristics. The nodule count showed a maximum value at %CE of 4.613. For metal-mould ingots it reached a value of 1584 nodules mm^–2, while for sand-mould ingots it reached a value of 970 nodules mm^–2. Nodule size was found to be inversely proportional to the nodule count for both sand- and metal-mould ingots. The nodularity of all ingots was, in general, higher than 95%. The density of SG Fe was found to decrease gradually (at %CE=3.782) from 7242 to 6969 kg m^–3. The modulus of elasticity (E) showed a boat-like curve having minimum values of 189 and 192 GPa for the sand and metal moulds, respectively.     

Cryptanalysis of an embedded systems’ image encryption

Multimedia Tools and Applications - Recently, a new image encryption-scheme for embedded systems based on continuous third-order hyperbolic sine chaotic system, has been proposed. The...     

A multiprocessor based heuristic for multi-dimensional multiple-choice knapsack problem

This paper presents a multiprocessor based heuristic algorithm for the Multi-dimensional Multiple Choice Knapsack Problem (MMKP). MMKP is a variant of the classical 0–1 knapsack problem, where items having a value and a number of resource requirements are divided into groups. Exactly one item has to be picked up from each group to achieve a maximum total value without exceeding the resource constraint of each type. MMKP has many real world applications including admission control in adaptive multimedia server system. Exact solution to this problem is NP-Hard, and hence is not feasible for real time applications like admission control. Therefore, heuristic solutions have been developed to solve the MMKP. M-HEU is one such heuristic, which solves the MMKP achieving a reasonable percentage of optimality. In this paper, we present a multiprocessor algorithm based on M-HEU, which runs in O(T/p+s(p)) time, where T is the time required by the algorithm using single processor, p is the number of processors and s(p), a function of p, is the synchronization overhead. We also present the worst-case analysis of our algorithm, the computation of the optimal number of processors as well as the lower bound of the total value that can be achieved by the heuristic.     

On the effects of oxygen cross-sections in the fast neutron fluence analysis for a reactor pressure vessel scraping test

Studies in support of the assessment of aging structural materials in pressurized water reactors are being performed at the Paul Scherrer Institut. To that aim, a state-of-the-art methodology based on applying a CASMO-4/SIMULATE-3/MCNPX calculation scheme has been developed. In the frame of the methodology validation, an investigation is currently reported pertaining to the sensitivity of the calculated results, for a specific reactor pressure vessel scraping test, to the nuclear data used with the Monte Carlo code. Thus, the MCNPX-2.4.0 calculations have been carried out using three different data libraries, based on JEF-2.2, ENDF/B-VI.8 and JENDL-3.3 evaluations, respectively.     

Correction to: Security analysis of an audio data encryption scheme based on key chaining and DNA encoding

Multimedia Tools and Applications - A Correction to this paper has been published: https://doi.org/10.1007/s11042-021-10592-x     

High Dielectric Breakdown Strength Nanoplatelet-Based Multilayer Thin Films

Dielectric materials that can withstand high voltages are of great interest due to the growing need for high-performance insulation systems in electronics. Polymer nanocomposites have gained popularity as electrical insulators due to their processability, high operating voltage, and tortuous paths for current flow created by the nanoparticles in the polymer matrix. The dielectric breakdown strength of a relatively thick multilayer thin film containing polyethylenimine (PEI) and vermiculite clay (VMT), thickened with tris(hydroxymethyl)aminomethane (tris), is evaluated as a function of bilayers (BL) deposited. The resulting nanobrick wall structure of this clay-based assembly is ideal for protective insulation. An 8 BL PEI+tris/VMT film achieves a dielectric breakdown strength of 245 kV mm⁻¹, with a thickness of 5 µm. With increasing bilayers, the breakdown strength gradually decreases, but 20 BL of PEI+tris/VMT achieves a breakdown voltage of 2.36 kV. This nanoplatelet-based system is the first “thick growing” layer-by-layer deposited film to be used as an insulating layer. Its unusually high breakdown strength can be useful for the protection of various high voltage electronics.