MicroRNA Cross-Involvement in Acne Vulgaris and Hidradenitis Suppurativa: A Literature Review

Acne Vulgaris (AV) and Hidradenitis suppurativa (HS) are common chronic inflammatory skin conditions that affect the follicular units that often coexist or are involved in differential diagnoses. Inflammation in both these diseases may result from shared pathways, which may partially explain their frequent coexistence. MicroRNAs (miRNAs) are a class of endogenous, short, non-protein coding, gene-silencing or promoting RNAs that may promote various inflammatory diseases. This narrative review investigates the current knowledge regarding miRNAs and their link to AV and HS. The aim is to examine the role of these molecules in the pathogenesis of AV and HS and to identify possible common miRNAs that could explain the similar characteristics of these two diseases. Five miRNA (miR-155 miR-223-, miR-21, and miRNA-146a) levels were found to be altered in both HS and AV. These miRNAs are related to pathogenetic aspects common to both pathologies, such as the regulation of the innate immune response, regulation of the Th1/Th17 axis, and fibrosis processes that induce scar formation. This review provides a starting point for further studies aimed at investigating the role of miRNAs in AV and HS for their possible use as diagnostic-therapeutic targets.     

Absorption coefficient of bulk and thin film Cu2O

The optical absorption coefficient of thin film and bulk Cu₂O at room temperature is obtained from an accurate analysis of their transmittance and reflectance spectra. These absorption spectra are modeled, together with the low temperature data reported in the literature, using an analytical expression to assess and quantify the role of the different absorption mechanisms. The results suggest that direct forbidden transitions and indirect transitions play an almost equally relevant role. A table of the optical constants of Cu₂O single crystal is given for reference.     

On the efficiency of quantization-based integration methods for building simulation

Models describing energy consumption, heating, and cooling of buildings usually impose difficulties to the numerical integration algorithms used to simulate them. Stiffness and the presence of frequent discontinuities are among the main causes of those difficulties, that become critical when the models grow in size. Quantized State Systems (QSS) methods are a family of numerical integration algorithms that can efficiently handle discontinuities and stiffness in large models. For this reason, they are promising candidates for overcoming the mentioned problems. Based on this observation, this article studies the performance of QSS methods in some systems that are relevant to the field of building simulation. The study includes a performance comparison of different QSS algorithms against state-of-the-art classic numerical solvers, showing that the former can be more than one order of magnitude faster.     

Assessment of intradialysis calcium mass balance by a single pool variable‐volume calcium kinetic model

Introduction: A reliable method of intradialysis calcium mass balance quantification is far from been established. We herein investigated the use of a single‐pool variable‐volume Calcium kinetic model to assess calcium mass balance in chronic and stable dialysis patients. Methods: Thirty‐four patients on thrice‐weekly HD were studied during 240 dialysis sessions. All patients were dialyzed with a nominal total calcium concentration of 1.50 mmol/L. The main assumption of the model is that the calcium distribution volume is equal to the extracellular volume during dialysis. This hypothesis is assumed valid if measured and predicted end dialysis plasma water ionized calcium concentrations are equal. A difference between predicted and measured end‐dialysis ionized plasma water calcium concentration is a deviation on our main hypothesis, meaning that a substantial amount of calcium is exchanged between the extracellular volume and a nonmodeled compartment. Findings: The difference between predicted and measured values was 0.02 mmol/L (range ?0.08:0.16 mmol/L). With a mean ionized dialysate calcium concentration of 1.25 mmol/L, calcium mass balance was on average negative (mean ± SD ?0.84 ± 1.33 mmol, range ?5.42:2.75). Predialysis ionized plasma water concentration and total ultrafiltrate were the most important predictors of calcium mass balance. A significant mobilization of calcium from the extracellular pool to a nonmodeled pool was calculated in a group of patients. Discussion: The proposed single pool variable‐volume Calcium kinetic model is adequate for prediction and quantification of intradialysis calcium mass balance, it can evaluate the eventual calcium transfer outside the extracellular pool in clinical practice.     

A distributed command governor based on graph colorability theory

In this paper, a distributed command governor (CG) strategy is introduced that, by the use of graph colorability theory, improves the scalability property and the performance of recently introduced distributed noncooperative sequential CG strategies. The latter are characterized by the fact that only 1 agent at a decision time is allowed to update its command, whereas all the others keep applying their previously computed commands. The scalability of these early CG distributed schemes and their performance are limited because the structure of the constraints is not taken into account in their implementation. Here, by exploiting the idea that agents that are not directly coupled by the constraints can simultaneously update their control actions, the agents in the network are grouped into particular subsets (turns). At each time instant, on the basis of a round‐robin policy, all agents belonging to a turn are allowed to update simultaneously their commands, whereas agents in other turns keep applying their previous commands. Then, a turn‐based distributed CG strategy is proposed and its main properties are analyzed. Graph colorability theory is used to determine the minimal number of turns and to distribute each agent in at least a turn. A novel graph colorability problem that allows one to maximize the frequency at which agents can update their commands is proposed and discussed. A final example is presented to illustrate the effectiveness of the proposed strategy.     

Photoluminescence and photoluminescence excitation studies in 80 MeV Ni ion irradiated MOCVD grown GaN

We report damage creation and annihilation under energetic ion bombardment at a fixed fluence. MOCVD grown GaN thin films were irradiated with 80 MeV Ni ions at a fluence of 1 × 10¹³ ions/cm². Irradiated GaN thin films were subjected to rapid thermal annealing for 60 s in nitrogen atmosphere to anneal out the defects. The effects of defects on luminescence were explored with photoluminescence measurements. Room temperature photoluminescence spectra from pristine sample revealed presence of band to band transition besides unwanted yellow luminescence. Irradiated GaN does not show any band to band transition but there is a strong peak at 450 nm which is attributed to ion induced defect blue luminescence. However, irradiated and subsequently annealed samples show improved band to band transitions and a significant decrease in yellow luminescence intensity due to annihilation of defects which were created during irradiation. Irradiation induced effects on yellow and blue emissions are discussed.     

Optimization of a dynamic uncertain causality graph for fault diagnosis in nuclear power plant

Fault diagnostics is important for safe operation of nuclear power plants (NPPs).In recent years,data-driven approaches have been proposed and implemented to tackle the problem,e.g.,neural networks,fuzzy and neurofuzzy approaches,support vector machine,K-nearest neighbor classifiers and inference methodologies.Among these methods,dynamic uncertain causality graph (DUCG) has been proved effective in many practical cases.However,the causal graph construction behind the DUCG is complicate and,in many cases,results redundant on the symptoms needed to correctly classify the fault.In this paper,we propose a method to simplify causal graph construction in an automatic way.The method consists in transforming the expert knowledge-based DCUG into a fuzzy decision tree (FDT) by extracting from the DUCG a fuzzy rule base that resumes the used symptoms at the basis of the FDT.Genetic algorithm (GA) is,then,used for the optimization of the FDT,by performing a wrapper search around the FDT:the set of symptoms selected during the iterative search are taken as the best set of symptoms for the diagnosis of the faults that can occur in the system.The effectiveness of the approach is shown with respect to a DUCG model initially built to diagnose 23 faults originally using 262 symptoms of Unit-1 in the Ningde NPP of the China Guangdong Nuclear Power Corporation.The results show that the FDT,with GA-optimized symptoms and diagnosis strategy,can drive the construction of DUCG and lower the computational burden without loss of accuracy in diagnosis.     

Coded transmissions for space links affected by solar scintillation: Baseband analysis

A thorough analysis of the behavior of error‐correcting codes over space links affected by solar scintillation is presented. The relevant channel parameters are fixed through the development of a model based on real missions' data. Both telecommand and telemetry links are considered in fast and slow fading conditions. Besides classical coherent modulation schemes, the possibility to use noncoherent modulation schemes is considered, to eliminate the problem of phase tracking. For the case of channels with very slow fading, the use of external interleavers or erasure coding is proposed to cope with error bursts.