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Josephson effect in a Fibonacci quasicrystal

Quasiperiodicity has recently been proposed to enhance superconductivity and its proximity effect. Simultaneously, there has been significant experimental progress in the fabrication of quasiperiodic structures, including in reduced dimensions. Motivated by these developments, we use microscopic tight-binding theory to investigate the DC Josephson effect through a ballistic Fibonacci chain attache

Environmental sustainability from a decoupling point perspective

Combatting climate change is of global importance. The fact that all UN member nations have agreed on the sustainable development goals (SDGs) is testament to this. The manufacturing industry plays a crucial part in meeting these goals. However, if manufacturing firms are to improve in terms of sustainability, such efforts must be reconcilable with their ability to make profit. Hence, sustainabili

Bivalirudin vs Heparin Anticoagulation in STEMI : Confirmation of the BRIGHT-4 Results

Background: In the BRIGHT-4 (Bivalirudin With Prolonged Full-Dose Infusion During Primary PCI Versus Heparin Trial-4), anticoagulation with bivalirudin plus a 2- to 4-hour high-dose infusion after percutaneous coronary intervention (PCI) reduced all-cause mortality and bleeding without increasing reinfarction or stent thrombosis compared with heparin alone in patients with ST-segment elevation myo

Compressive Strength Prediction of Lightweight Concrete : Machine Learning Models

Concrete is the most commonly used construction material. The physical properties of concrete vary with the type of concrete, such as high and ultra-high-strength concrete, fibre-reinforced concrete, polymer-modified concrete, and lightweight concrete. The precise prediction of the properties of concrete is a problem due to the design code, which typically requires specific characteristics. The em

Machine Learning-Based CO2Prediction for Office Room : A Pilot Study

Air pollution is increasing profusely in Indian cities as well as throughout the world, and it poses a major threat to climate as well as the health of all living things. Air pollution is the reason behind degraded indoor air quality (IAQ) in urban buildings. Carbon dioxide (CO2) is the main contributor to indoor pollution as humans themselves are one of the generating sources of this pollutant. T

In situ imaging of precipitate formation in additively manufactured al-alloys by scanning X-ray fluorescence

Al-alloys incorporating Mn, Cr and Zr, tailored for powder bed fusion-laser beam processes with solubilities three times equilibrium have recently been developed that yield a high strength. Mn and Cr-enriched precipitates that form during printing and heat treatment influence the material’s mechanical properties hence making it important to understand their kinetics. In this study, direct imaging

Image restoration using a fuzzy-based median filter and modified firefly optimization algorithm

This paper presented an object restoration approach in which images are influenced by the salt & pepper noise replaced by a median filter based on fuzzy logic. A Modified Firefly Optimization Algorithm (MFOA) is used to restore the images based on the Richardson-Lucy algorithm. Denoising, as well as restoring the image, is effectively demonstrated. Compared to current denoising filtered, PSO (

Composition of Giants 1° North of the Galactic Center : Detailed Abundance Trends for 21 Elements Observed with IGRINS

We report the first high-resolution, detailed abundances of 21 elements for giants in the Galactic bulge/bar within 1° of the Galactic plane, where high extinction has rendered such studies challenging. Our high-signal-to-noise-ratio and high-resolution, near-infrared spectra of seven M giants in the inner bulge, located at (l, b) = (0°, +1°), are observed using the IGRINS spectrograph. We report

Application of Internet of Things in Image Processing

Image processing and IoT technology use various sensors and camera-based sensors for processing image data with help of a variety of IoT applications. So far, the IoT and image processing concepts have been used for our real-life applications. Their individual use in the sphere of industries is possible and has had some success. However, a combination of the two technologies has yet to be develope

An Optimized Neuro-Bee Algorithm Approach to Predict the FRP-Concrete Bond Strength of RC Beams

Over the world, there is growing worry about the corrosion of reinforced concrete structures. Structure repair, rehabilitation, replacement, and new structures all require cost-effective and long-lasting technologies. Fiber Reinforced Polymer (FRP) has been widely employed in both retrofitting existing structures and building new ones. Due to its varied qualities in reinforced concrete and masonry

Development of correlation to predict the efficiency of a hydro machine under different operating conditions

The global energy demand is increasing due to an increase in economic growth and urbanization which is set to rise by 4.6% in 2021. A major part of this increasing energy demand is accomplished by fossil fuels which create environmental pollution. Hydropower is the most mature, reliable, and cost-effective source of energy. However, the operation and maintenance (O&M) of hydro turbines is the

Prediction of FRCM–Concrete Bond Strength with Machine Learning Approach

Fibre-reinforced cement mortar (FRCM) has been widely utilised for the repair and restora-tion of building structures. The bond strength between FRCM and concrete typically takes precedence over the mechanical parameters. However, the bond behaviour of the FRCM–concrete interface is complex. Due to several failure modes, the prediction of bond strength is difficult to forecast. In this paper, effe

Modified median filter for image denoising

The retrieval of the original image quality is always a challenging task in the area of image processing. A huge number of techniques were used to denoising the image. A new approach is proposed for eliminating salt and paper noise. The methodology suggested is based on a different median filter applied. This paper describe the methodology and logical notations of purposed technique and finally im

Dimensions of Internet of Things : Technological Taxonomy Architecture Applications and Open Challenges-A Systematic Review

We are traversing the growing emerging technology paradigms in today's advanced technological world. In this present era, the Internet of Things (IoT) is extensively used in all sectors. IoT is the ecosystem of smart devices which contains sensors, smart objects, networking, and processing units. These integrated devices provide better services to the end user. IoT is impacting our environment and

Identification of Cardiac Patients Based on the Medical Conditions Using Machine Learning Models

Chronic diseases are the most severe health concern today, and heart disease is one of them. Coronary artery disease (CAD) affects blood flow to the heart, and it is the most common type of heart disease which causes a heart attack. High blood pressure, high cholesterol, and smoking significantly increase the risk of heart disease. To estimate the risk of heart disease is a complex process because

Security issues and challenges in cloud of things-based applications for industrial automation

Due to the COVID-19 outbreak, industries have gained a thrust on contactless processing for computing technologies and industrial automation. Cloud of Things (CoT) is one of the emerging computing technologies for such applications. CoT combines the most emerging cloud computing and the Internet of Things. The development in industrial automation made them highly interdependent because the cloud c

Prognosis of compressive strength of fly-ash-based geopolymer-modified sustainable concrete with ML algorithms

Sustainable concrete is the demand of the present era to reduce carbon emissions. Fly-ash-based geopolymer (FLAG) concrete has been used in the construction industry for more than one and a half decades. The compressive strength (CS) of concrete plays a crucial role in the mechanical properties of concrete. Laboratory experiments take a huge amount of time and cost to estimate the CS of concrete.

Enhancing Sustainability of Corroded RC Structures : Estimating Steel-to-Concrete Bond Strength with ANN and SVM Algorithms

The bond strength between concrete and corroded steel reinforcement bar is one of the main responsible factors that affect the ultimate load-carrying capacity of reinforced concrete (RC) structures. Therefore, the prediction of accurate bond strength has become an important parameter for the safety measurements of RC structures. However, the analytical models are not enough to estimate the bond st

Systemically administered zoledronic acid activates locally implanted synthetic hydroxyapatite particles enhancing peri-implant bone formation : A regenerative medicine approach to improve fracture fixation

Fracture fixation in an ageing population is challenging and fixation failure increases mortality and societal costs. We report a novel fracture fixation treatment by applying a hydroxyapatite (HA) based biomaterial at the bone-implant interface and biologically activating the biomaterial by systemic administration of a bisphosphonate (zoledronic acid, ZA). We first used an animal model of implant

Fine tuning of the innate and adaptive immune responses by Interleukin-2

Novel immunotherapies for cancer and other diseases aim to trigger the immune system to produce durable responses, while overcoming the immunosuppression that may contribute to disease severity, and in parallel considering immunosafety aspects. Interleukin-2 (IL-2) was one of the first cytokines that the FDA approved as a cancer-targeting immunotherapy. However, in the past years, IL-2 immunothera