In this investigation, water-soluble N-Acetyl Cysteine Capped-Cadmium Telluride QDs (NAC/CdTe nanocrystals), utilizing N-acetyl cysteine as a stabilizer, were prepared to assess their potential in differentiating between DNA extracted from pathogenic bacteria (e.g. Escherichia coli isolated from urine specimen) and intact DNA (extracted from blood of healthy individuals) for biomedical sensing prospective. Following the optical characterization of the synthesized QDs, the XRD analysis illustrated the construction of NAC-CdTe-QDs with a grain size of 7.1 nm. The prepared NAC-CdTe-QDs exhibited higher PL emission features at of 550 nm and UV-Vis absorption peak at 300 nm. Additionally, the energy gap quantified via PL and UV–Vis were 2.2 eV and 2.3 eV, respectively. The interconnection between the synthesized QDs and the different types of the extracted genomic DNA (both Escherichia coli and healthy subjects) was analyzed optically. This is resulted in a clear shift in the maximum fluorescence emission intensities (observed at 533 nm for an Escherichia coli DNA and 541 for healthy DNA). Overall, the present study findings suggest that prepared QDs could be employed as probes for the detection of pathogenic bacteria DNA from that of healthy subjects.
Cadmium oxide (CdO) thin films were deposited using the sequencing ion layer adsorption and reaction (SILAR) method. In this study, the effect of the pH value of an aqueous solution of cadmium acetate at a concentration of 0.2 mol of the cadmium oxide film was determined. The solution source for the cadmium oxide film was cadmium ions and an aqueous ammonia solution. The CdO films were deposited on glass substrates at a temperature of 90 ℃. The cadmium oxide film thickness was determined by the weight difference method at pH values (7.2, 8.2). X-ray diffraction (XRD) and scanning electron microscopy (SEM) showed that the size of the crystals increased with the increase in the solution (pH). While the UV-visible spectra of the fil
... Show MoreThe internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreThis abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota
... Show MoreIn every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho
... Show MoreThe purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
... Show MoreIn most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con
... Show MoreThe tight gas is one of the main types of the unconventional gas. Typically the tight gas reservoirs consist of highly heterogeneous low permeability reservoir. The economic evaluation for the production from tight gas production is very challenging task because of prevailing uncertainties associated with key reservoir properties, such as porosity, permeability as well as drainage boundary. However one of the important parameters requiring in this economic evaluation is the equivalent drainage area of the well, which relates the actual volume of fluids (e.g gas) produced or withdrawn from the reservoir at a certain moment that changes with time. It is difficult to predict this equival
Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene
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