Electron-Beam Surface Modification of Boron-Based Diffusion Layers Obtained of the Surface of Steel H21

In recent years the interest in the development of new protective coatings with improved functional properties for machine parts’ surface have been of great fundamental and applied importance. The current study is devoted to the creation of coatings based on boron and aluminium on the surface of alloy steel using a cutting-edge method, combining thermal-chemical treatment (TCT) and subsequent electron beam processing (EBP). TCT was carried out in treatment pastes based on boron carbide and aluminum at 950°C and 1050°C for 2 hours. As a result of processing, diffusion layers with a thickness of up to 120 μm and 580 μm were formed on the steel surface after TCT at 950°C and 1050°C respectively. The subsequent EBP led to a complete transformation of the primary diffusion layer and an increase in its thickness to 1.6 mm. XRD analysis showed significant differences in composition before and after EBP: new compound, such as tungsten borides (WB, W2B9) and iron boride (Fe2B) were detected. In addition, it was determined that the distribution of microhardness and elemental composition (B, Al, W) over the layer thickness after EBP had a more favorable profile without significant fluctuations compared to the sample after TCT. The concentration of Al decreased significantly after EBP. It dropped from 18% after TCT to a low of 1%.

Quantum Computing Memoir: Quantum Mechanics, Architectural Developments and its Future

Quantum computing is a cutting edge method of computing that depends on the study of quantum mechanics and its staggering marvels. It is an excellent blend of physical science, arithmetic, computer science and data hypothesis. It gives high computational force, less energy utilization and remarkable speed over old-style computers by controlling the conduct of little actual articles for example minuscule particles like iotas, electrons, photons, and so forth Here, we present a prologue to the crucial ideas and a few thoughts of quantum computing. To comprehend the true abilities and difficulties of a pragmatic quantum computer that can be dispatched financially, the paper covers the engineering, equipment, programming, plan, types and calculations that are explicitly needed by quantum computers. It reveals the ability of quantum computers that can affect our lives in different perspectives like network safety, traffic enhancement, medications, man-made reasoning and some more. Limited scope quantum computers are being grown as of late. This improvement is going towards an incredible future because of their high possible abilities and headways in continuous exploration. Prior to zeroing in on the meanings of a broadly useful quantum computer and investigating the force of the new emerging innovation, it is smarter to survey the beginning, possibilities, and restrictions of the current conventional computing. This data helps us in understanding the potential difficulties in creating outlandish and serious innovation. It will likewise give us an understanding of the continuous advancement in this field. Keywords: Realtime Systems, Programming Processors, Quantum Theory, Quantum Computing

Structural Connectivity Alterations in Operculo-Insular Epilepsy

Operculo-insular epilepsy (OIE) is an under-recognized condition that can mimic temporal and extratemporal epilepsies. Previous studies have revealed structural connectivity changes in the epileptic network of focal epilepsy. However, most reports use the debated streamline-count to quantify ‘connectivity strength’ and rely on standard tracking algorithms. We propose a sophisticated cutting-edge method that is robust to crossing fibers, optimizes cortical coverage, and assigns an accurate microstructure-reflecting quantitative conectivity marker, namely the COMMIT (Convex Optimization Modeling for Microstructure Informed Tractography)-weight. Using our pipeline, we report the connectivity alterations in OIE. COMMIT-weighted matrices were created in all participants (nine patients with OIE, eight patients with temporal lobe epilepsy (TLE), and 22 healthy controls (HC)). In the OIE group, widespread increases in ‘connectivity strength’ were observed bilaterally. In OIE patients, ‘hyperconnections’ were observed between the insula and the pregenual cingulate gyrus (OIE group vs. HC group) and between insular subregions (OIE vs. TLE). Graph theoretic analyses revealed higher connectivity within insular subregions of OIE patients (OIE vs. TLE). We reveal, for the first time, the structural connectivity distribution in OIE. The observed pattern of connectivity in OIE likely reflects a diffuse epileptic network incorporating insular-connected regions and may represent a structural signature and diagnostic biomarker.

Metabolic Profiling Indicates Diversity in the Metabolic Physiologies Associated With Maternal Postpartum Depressive Symptoms

Background: Postpartum depression (PPD) is a devastating disease requiring improvements in diagnosis and prevention. Blood metabolomics identifies biological markers discriminatory between women with and those without antenatal depressive symptoms. Whether this cutting-edge method can be applied to postpartum depressive symptoms merits further investigation.Methods: As a substudy within the Biology, Affect, Stress, Imagine and Cognition Study, 24 women with PPD symptom (PPDS) assessment at 6 weeks postpartum were included. Controls were selected as having a score of ≤ 6 and PPDS cases as ≥12 on the Edinburgh Postnatal Depression Scale. Blood plasma was collected at 10 weeks postpartum and analyzed with gas chromatography–mass spectrometry metabolomics.Results: Variations of metabolomic profiles within the PPDS samples were identified. One cluster showed altered kidney function, whereas the other, a metabolic syndrome profile, both previously associated with depression. Five metabolites (glycerol, threonine, 2-hydroxybutanoic acid, erythritol, and phenylalanine) showed higher abundance among women with PPDSs, indicating perturbations in the serine/threonine and glycerol lipid metabolism, suggesting oxidative stress conditions.Conclusions: Alterations in certain metabolites were associated with depressive pathophysiology postpartum, whereas diversity in PPDS physiologies was revealed. Hence, plasma metabolic profiling could be considered in diagnosis and pathophysiological investigation of PPD toward providing clues for treatment. Future studies require standardization of various subgroups with respect to symptom onset, lifestyle, and comorbidities.

Time-Variant Front-End Read-Out Electronics for High-Data-Rate Detectors

The foreseen incremental luminosity for near-future high-energy physics experiments demands evolution for the read-out electronics in terms of event data-rate. However, the filtering necessary to reject noise and meet the signal-to-noise-ratio requirements imposes a restriction on the operational speed of the conventional read-out electronics. The stringent trade-off between signal-to-noise-ratio and the event data-rate originates from the time-invariant behavior of the conventional systems. In this paper, the cases of time-variant systems are addressed, studying a benchmark with the RC-CR shaping function used in time-over-threshold methods. It was demonstrated that the time-variant systems enable a higher data-rate for the given noise performance. Moreover, taking advantage of time-variant systems, the proposed rising-edge method enables further data-rate enhancement with respect to the traditional time-over-threshold technique by reading the data from the rising edge of the analog output waveform. A comparison between the conventional time-invariant time-over-threshold technique, its time-variant equivalent and rising-edge method confirms the better performance of the latter one in terms of data-rate enhancement for a target noise performance. Moreover, design challenges for time-variant systems are briefly discussed, considering the ATLAS Monitored Drift Tube detector as a design case.

AN IOT-BASED WEATHER MONITORING SYSTEM

The framework proposed in this paper is a cutting-edge method for tracking weather conditions in a specific location and making the data available to everyone, anywhere in the world. The Internet of Things (IoT) is the technology behind this, which is a cutting-edge and cost-effective approach for connecting things to the internet and connecting the whole universe of things in a network. Things could go either way here.

A Design Method of Tele-Rehabilitation Platforms for Post-Stroke Patients Based on Consumer Technology

Background: Telerehabilitation represents a new cutting-edge method in the treatment of patients suffering from motor and cognitive disorders caused by stroke. Even if there exist dedicated devices able to track patients’ movements to evaluate the performed rehabilitation exercises, they require specific settings necessary for a correct and simple use at the patient’s home. If we consider the recent pandemic situation and the lockdown condition, which made difficult the access to these products, post stroke patients may be not able to perform home rehabilitation. Objectives: the goal of this work is the design of a specific method to develop a tele-rehabilitation platform for post-stroke patients using consumer technologies without involving ad-hoc devices. Method: Open-source tools have been investigated for speeding up the development starting with the medical knowledge. Results: a group of four healthcare technologies engineering students with no specific skills about computer science has developed a platform in four months using the design method. Conclusion: the presented method allowed the development of a clinical knowledge-based web platform for post-stroke patients totally based on consumer technology.

Presenting a Semi-Automatic, Statistically-Based Approach to Assess the Sharpness Level of Optical Images from Natural Targets via the Edge Method. Case Study: The Landsat 8 OLI–L1T Data

Developing reliable methodologies of data quality assessment is of paramount importance for maximizing the exploitation of Earth observation (EO) products. Among the different factors influencing EO optical image quality, sharpness has a relevant role. When implementing on-orbit approaches of sharpness assessment, such as the edge method, a crucial step that strongly affects the final results is the selection of suitable edges to use for the analysis. Within this context, this paper aims at proposing a semi-automatic, statistically-based edge method (SaSbEM) that exploits edges extracted from natural targets easily and largely available on Earth: agricultural fields. For each image that is analyzed, SaSbEM detects numerous suitable edges (e.g., dozens-hundreds) characterized by specific geometrical and statistical criteria. This guarantees the repeatability and reliability of the analysis. Then, it implements a standard edge method to assess the sharpness level of each edge. Finally, it performs a statistical analysis of the results to have a robust characterization of the image sharpness level and its uncertainty. The method was validated by using Landsat 8 L1T products. Results proved that: SaSbEM is capable of performing a reliable and repeatable sharpness assessment; Landsat 8 L1T data are characterized by very good sharpness performance.