Search

The management of diabetes involves much compliance, disease awareness, and patient empowerment. Blood glucose levels in people with diabetes are abnormal, resulting in various health problems that affect their kidneys, hearts, and vision. Monitoring the patient's health has the benefit of using the Internet of Things (IoT) and diabetes patient monitoring systems. Because this system uses machine learning to classify data, its value goes beyond patient monitoring. So, this paper proposes a novel deep learning model with an effective feature selection mechanism for diabetes mellitus (DM) prediction in IoT-based healthcare environment. The proposed work starts by collecting the real-time IoT data of the patients from the Pima Indian Diabetes database. The data imbalance problem of the collected dataset is rectified by applying the synthetic minority oversampling technique. Afterward, the balanced dataset is preprocessed by applying missing value imputation and data standardization to improve the classification performance. Then, the hybrid algorithm called k-means clustering-based sailfish optimization is utilized, which performs clustering and optimization to select the essential features from the preprocessed dataset. Finally, the selected features are fed into the kaiming and switan included bidirectional long short-term memory for DM prediction. The proposed system achieves better results than the existing state-of-the-art techniques, which shows its effectiveness in predicting DM in real-time IoT datasets. [ABSTRACT FROM AUTHOR]

The pipe component of a water distribution network (WDN) is sized based on the fixed design demand considering a peak factor and design period. Simulation of the designed network by a hydraulic solver provides nodal pressure head, head loss, velocity, and flow in each pipe as the prime outputs for the design demand, and it can also be used for extended-period simulation for a particular demand pattern over the supply hours. But, in reality, the behavior of the network does not match with such a result in an intermittent water supply (IWS) system due to the fact that all house service connections behave as an uncontrolled orifice. This has made it a challenging task in understanding and in predicting the behavior of the networks by the municipal engineer once the water starts flowing through the house service connections (HSCs). Though the municipal engineer provides the same pipe size for HSCs to all residences, the flow received by each house could vary based on the available pressure head at the ferrule point of the main water supply pipeline. In reality, maintaining constant pressure at each HSC is not feasible due to frictional head loss. Hence, variation in flow at the HSC is inevitable even with a small water supply system. This paper illustrates how to simulate the behavior of an IWS system based on the number of HSCs provided to each pipeline using a hydraulic solver. Hydraulic simulation of the water distribution network that provides IWS to consumers can be implemented easily by adding a fictitious node by assigning an appropriate emitter coefficient to each demand node through a fictitious link having a check valve in it. The method for finding the appropriate value of the emitter coefficient that helps in simulating HSCs is illustrated in the present work. [ABSTRACT FROM AUTHOR]

The range of pipe roughness values in both cases (triangular and trapezoidal) at the 0 HT ht level is the same, i.e., 110 to 130. For example, the minimum and maximum values obtained by the authors for HT ht are 8.88 and HT ht , while Sivakumar et al. ([5]) reported 5.81 and HT ht . Because the range of pipe roughness values at the 0 HT ht level in both triangular and trapezoidal cases is the same, MFs of pipe discharges and nodal heads at the 0 HT ht level should be identical. However, for other HT ht levels, these are different. [Extracted from the article]

In an effective Wireless Network (WN), low latency and reliability are essential to provide adequate infrastructure for better communication. Cooperative Communication is one efficient way to achieve these wireless network goals. In this research, the machine learning-based Decode and Forward (DF) coding was developed in conjunction with the network coding algorithm to improve cooperative communication and system functionality that select relays which will not cause interference in a wireless network. Here, the Interference-Thwarting Relay Selection (ITRS) technique is intended to aid reliable communication while reducing self-interference. It is possible to monitor and measure suitable relays in the communication process with the help of a machine learning system. Thus, the proposed Interference-Thwarting Relay Selection technique is implemented with the parameters like Bit Error Rate (BER) as 10−6, Signal to Noise Ratio (SNR) as 36 dB, Symbol Error Rate (SER) as 10−8 and throughput with the power allocation factors. The simulated Machine Learning-Optimized Relay Selection Method (ML-ORSM) results achieve the improved optimal power allocation with symbol error rate. [ABSTRACT FROM AUTHOR]

Summary. The dynamically rising demand for electricity must be satiated by both conventional and unconventional power sources. PV electricity generation is essential. The installed PV sources are not used to their full potential due to low irradiance and poor weather. The goal of many research publications was to maximize PV power using different MPPT approaches. In order to extract the most power under the aforementioned circumstances, this study introduces a novel notion of using a voltage boosting PV panels. Additional PV panels are used in the suggested way to provide enough voltage and current. Using a voltage-boosting PV panel, a 20 kW panel is examined for low irradiance and unfavorable weather conditions. In a proposed method, results are compared with the previous INC MPPT method using a 20-kW panel. Through the power analysis, the proposed method extracted 1277.5 kW of power per year that is more than the INC MPPT method, and Rs. 10,220 per year was benefited during low irradiation alone. The power extraction and cost benefits are similar in cloudy and misty conditions. With power, cost, and efficiency analyses, the new method is contrasted with the traditional incremental conductance method and perturb and observe methods. Simulations were run using the MATLAB/Simulink programme, and experimental results were assessed using the appropriate hardware setup. [ABSTRACT FROM AUTHOR]

In healthcare (HC), Internet of Things (IoT) integrated cloud computing provides various features and real-time applications. However, owing to the nature of IoT architecture, their types, various modes of communication and the density of data transformed in the network, security is currently a critical issue in the IoT healthcare (IoT-HC) field. This paper proposes a deep learning (DL) model, namely Adaptive Swish-based Deep Multi-Layer Perceptron (ASDMLP) that identifies the intrusions or attacks in the IoT healthcare (IoT-HC) platform. The proposed model starts by clustering the patients' sensor devices in the network using the Probability-based Fuzzy C-Means (PFCM) model. After clustering the devices, the cluster heads (CHs) among the cluster members are selected based on the energy, distance and degree of the sensor devices for aggregating the data sensed by the medical sensor devices. The base station (BS) sends the patient's data collected by the CHs to the cloud server (CS). At the cloud end, the proposed model implements an IDS by applying training of the DL model in publicly available databases. The DL approach first performs preprocessing of the data and then selects optimal features from the dataset using the Opposition and Greedy Levy mutation-based Coyotes Optimization Algorithm (OGCOA). The ASDMLP trains these optimal features for the detection of HC data intrusions. The outcomes confirm that the proposed approach works well on real-time IoT datasets for intrusion detection (ID) without compromising the energy consumption (EC) and lifespan of the network. [ABSTRACT FROM AUTHOR]

This document is a closure to a previous paper titled "Analysis of Intermittent Water Distribution Networks Using a Dummy Emitter Device at Each Demand Node." The closure addresses comments and criticisms made by discussers regarding the original paper. It explains the methodology used to analyze intermittent water supply (IWS) and highlights the differences in results obtained by different models. The closure also discusses the applicability of the emitter approach in various scenarios and suggests modifications for specific cases. Overall, the closure provides insights into the analysis of IWS systems and the factors that can affect their performance. [Extracted from the article]

• Ion beams induce band gap changes and can enhance photo-response of zinc tin phosphide films. • Structure, microstructure and morphological changes are large for high energy ion beams. • The changes are strongly related to the electronic energy loss of ion beams. • The changes are opposite for low (60–200 keV) and high (80–100 MeV) energy ion beams. Zinc tin phosphide (ZTP) is a promising low cost light sensing semiconductor material. The present study focuses on the effects of various ion beams having energies in the range of keV to MeV, on the structural, optical, and photo-response properties of ZTP thin films. Low energy ions (100 and 200 keV Al and Cu, 150 keV Fe and 60 keV Au ions) of fluences in the range from 1E13 to 1E16 ions/cm2 and high energy ions (80 MeV Si, 100 MeV Ni and 100 MeV Ag ions) from 1E11 to 6E13 ions/cm2 are used. The energy of ions (low or high) determine the changes in the ion-induced defects, structural disorder and recrystallization effects leading to modification in the structural quality, the evolution of microstructure, variation in the optical band gap (from 1.60 to 1.82 eV), and the photo-responsivity to red light up to 0.66 mA/W. The photo-responsivity of the films enhances for 150 keV Fe, 60 keV Au, 80 MeV Si and 100 MeV Ni ions and reduces for 100 and 200 keV Al and Cu and 100 MeV Ag ions. These changes are strongly correlated with the electronic energy loss of the ions in the films. The study demonstrates the applicability of low and high energy ions to improve the photo-response and also reveals the possibility to estimate the extent of its progress in ZTP and other light-sensing materials relevant for photo-detector and solar cell applications. [ABSTRACT FROM AUTHOR]

Dhivya, Padma, and Santhini ([2]) states that wound dressing is designed to be in contact with the wound, which is different from a bandage that holds the dressing in place. Keywords: Chitosan; hemostatic efficacy; plain gauze; secondary layer; spunlace; wound dressing; ; ; ; ; ; EN Chitosan hemostatic efficacy plain gauze secondary layer spunlace wound dressing ZH 8044 8050 7 11/21/22 20221220 NES 221220 Introduction The selection of fibers and textile structures are very essential for the selection hemostatic wound dressing material (Kubera Sampath Kumar et al. [4]; [6]; [5]). 2020a. Study of wound dressing material coated with natural extracts of Calotropis Gigantean, Eucalyptus Globulus and buds of Syzygium Aromaticum solution enhanced with rhEGF (REGEN-D TM 60). 2017a. Evaluation of antibacterial efficacy and wound healing activity of natural fibre based wound dressing coated with natural extracts of calotropis gigantean, eucalyptus globules and buds of syzygiumaromaticum enhanced with epidermal growth factor. [Extracted from the article]

In recent years, cooperative communication (CC) technology has emerged as a hotspot for testing wireless communication networks (WCNs), and it will play an important role in the spectrum utilization of future wireless communication systems. Instead of running node transmissions at full capacity, this design will distribute available paths across multiple relay nodes to increase the overall throughput. The modeling WCNs coordination processes, as a recurrent mechanism and recommending a deep learning-based transfer choice, propose a recurrent neural network (RNN) process-based relay selection in this research article. This network is trained according to the joint receiver and transmitter outage likelihood and shared knowledge, and without the use of a model or prior data, the best relay is picked from a set of relay nodes. In this study, we make use of the RNN to do superdimensional (high-layered) processing and increase the rate of learning and also have a neural network (NN) selection testing to study the communication device, find out whether or not it can be used, find out how much the system is capable of, and look at how much energy the network needs. In these simulations, it has been shown that the RNN scheme is more effective on these targets and allows the design to keep converged over a longer period of time. We will compare the accuracy and efficiency of our RNN processed-based relay selection methods with long short-term memory (LSTM), gated recurrent units (GRU), and bidirectional long short-term memory (BLSTM),which are all acronyms for long short-term memory methods. [ABSTRACT FROM AUTHOR]

Due to the unpredictable and stochastic nature of renewables, current power networks confront operational issues as renewable energy sources are more widely used. Frequency stability of modern power systems has been considerably harmed by fast and unpredictable power variations generated by intermittent power generation sources and flexible loads. The main objective of the power system frequency control is to ensure the generation demand balance at all times. In reality, obtaining precise estimates of the imbalance of power in both transmission and distribution systems is challenging, especially when renewable energy penetration is high. Electric vehicles have become a viable tool to reduce the occasional impact of renewable energy sources engaged in frequency regulation mainly because of vehicle-to-grid technologies and the quick output power management of EV batteries. The rapid response of EVs enhances the effectiveness of the LFC system significantly. This research work investigates a deep learning strategy based on a long short-term memory recurrent neural network to identify active power fluctuations in real-time. The new approach assesses power fluctuations from a real-time observed frequency signal precisely and quickly. The observed power fluctuations can be used as a control reference, allowing automatic generation control to maintain better system frequency and ensure optimum generation cost with the use of demand management techniques. To validate the suggested method and compare it with several classical methods, a realistic model of the Indian power system integrated with distributed generation technology is used. The simulation results clearly indicate the importance of power fluctuation identification as well as the benefits of the proposed strategy. The results clearly show a considerable improvement in response performance indices, as the maximum peak overshoot was decreased by 21.25% to 51.2%, and settling time was lowered by about 23.34% to 65.40% for the suggested control technique compared to other controllers. [ABSTRACT FROM AUTHOR]

A passive neutron based assaying system for plutonium bearing solid wastes has been designed and developed. The assaying of the plutonium in the drum containing the wastes is determined by as positioned and by rotating the drum to 180 degree and average counts are obtained. The average counts were used for deriving the counting statistics. This system was calibrated with plutonium typically obtained in fast reactor fuel reprocessing facilities with known isotopic compositions. The minimum detection limit has been estimated to be 35 mg. It has been determined that a γ background of up to 2000 mR/h can be tolerated without loss of accuracy. [ABSTRACT FROM AUTHOR]

Growing electrical demand is to be met dynamically through conventional and nonconventional power sources. PV power generation plays a vital role. Because of low irradiation and overcast weather condition, the installed PV sources are not fully utilized. Many research papers were presented to extract maximum power from PV using various MPPT techniques. This paper presents a new idea of implementing a biased transformer to extract maximum power during the above condition. The proposed method uses three winding transformers to give sufficient biased voltage and current. The biased current and voltage were obtained from the grid that is fed to the primary winding—two of the three winding transformers through the controller. A 10 kW panel is checked for low irradiation and overcast weather condition using the biased MPPT technique. The proposed method is compared with the conventional incremental conductance method with power, cost, and efficiency analysis. Simulation was carried out in MATLAB/Simulink software and experimentally evaluated through a suitable hardware setup. [ABSTRACT FROM AUTHOR]

The article focuses on interface of law and psychiatric problems in the elderly.

Scaling up of biofortified varieties is the key component of food-based approaches in addressing micronutrient deficiency. Orange-fleshed sweet potato varieties rich in β -carotene can address the vitamin A deficiency prevalent in rural and tribal areas. We developed a ‘sweet potato biofortification priority index’ (SPBPI), a strategic planning tool for identifying priority states for implementing biofortification field interventions. A scaling-up intervention ‘Rainbow Diet Campaign’ is being implemented in the ‘high-priority’ states, Meghalaya, Mizoram and Arunachal Pradesh identified by SPBPI. [ABSTRACT FROM AUTHOR]

A similar analysis is not applicable for Case Study 2 because the settings of the HT ht values are 0 for both PSVs and emitters. Hence, the discussers used PSV settings of zero instead of the HT ht values given in Table 2 of the original paper. The probable reason behind the authors' incorrect results for HT ht and 1.5 is that the default value of 0.5 might have been used for the global emitter exponent. [Extracted from the article]

In this article, it is imperative that an efficient and reliable cooling system is used for the large Uninterrupted Power Supply (UPS) panel in Nuclear Power Plant. While the UPS system can tolerate relatively high temperatures, it is advisable to keep the temperature at 25 °C or below in the room where the UPS is housed. A rule of thumb is that for every 10 °C increase in operating temperature, the expected life of the UPS components would be reduced in half. So it is absolutely necessary to maintain the temperature within the limits prescribed by the designer. The aim of this article is to devise a vastly improved cooling system by streamlining the cool air flow and targeting the hotspots of the UPS components which are particularly vulnerable to damage from high temperature. First, a computational model of the whole setup was made and then, computational fluid dynamics (fluent) technique was used to perform fluid flow and heat transfer analysis of this setup, which showed a dramatic performance increase in the heat exchange process and reduced the effective size of the UPS cabin and cost. [ABSTRACT FROM AUTHOR]

This paper proposes the detection and classifications of weld images for crack detection using image processing techniques. The proposed method consists of preprocessing stage, feature extraction stage, classification stage and crack region segmentation regions. The image enhancement method is used as preprocessing stage and texture and statistical features are extracted from the enhanced weld images. These computed features are then classified into "Excess weld", "Good weld", "No weld" and "Undercut weld", using Adaptive Neuro Fuzzy Inference System (ANFIS) classification method. This proposed method is analyzed in terms of sensitivity, specificity, accuracy, positive predictive value, negative predictive value and precision. The simulation results of the proposed method are compared with other state of the art methods. [ABSTRACT FROM AUTHOR]

This article presents the design, analyses and implementation of the novel routing protocol for energy optimization based on LEACH for WSN. Network Lifetime is the major problem in various routing protocols used in WSN. In order to overcome that problem, our proposed routing protocol is developed, which is a combination of Micro Genetic algorithm with LEACH protocol. Our proposed µGA-LEACH protocol, strengthen the cluster head (CH) selection and also reduce the energy consumption of the network when compared to existing protocols. This paper shows the improvement of network lifetime and energy consumption with the optimal CH selection based on a micro genetic algorithm and also compared the results with an existing hierarchical routing protocol like LEACH, LEACH-C, LEACH GA and GADA LEACH routing protocol with various packet sizes, and initial energy. [ABSTRACT FROM AUTHOR]

The ever-increasing demand for wide channel bandwidth, high-speed information, and spectral-efficient communication links with advanced modulation schemes has led to the evolution of the free space optics (FSO) links. This paper proposes an FSO transmission link based on eight-channel wavelength division multiplexing technique integrating spectral-efficient polarization division multiplexing with a 16-level quadrature amplitude modulation (PDM-16-QAM) scheme, with each channel carrying 160 Gbps of information. The proposed link deploys coherent detection technique and the digital signal processing unit to boost the system efficiency and to compensate for the deterioration of the information signal due to channel fading, atmospheric attenuation and atmospheric turbulence. Using numerical simulations, we demonstrate an effective transmission of 1.28 Tbps data with FSO link range varying from 84 km to 1.95 km depending on the weather conditions with reasonable bit error rate results. We also scrutinize the output of the system with published works and demonstrate a better performance for the proposed FSO system i.e. bit rate and range. The proposed system can be implemented under complex atmospheric conditions to achieve a reliable high-speed transmission of information for fronthaul and backhaul links. [ABSTRACT FROM AUTHOR]

Inter-satellite optical wireless communication (IsOWC) links have been exploited by many researchers as a viable technology to transmit information amongst two or more satellites using optical carrier signals and outer space as the medium of propagation medium. IsOWC links can securely transmit information all over the globe. The present study discusses a spectral-efficient large-speed single-channel IsOWC system using polarization division multiplexed-quadrature phase shift keying (PDM-QPSK) scheme. Coherent detection has been used at the receiver terminal for receiver sensitivity improvement. A digital signal processing (DSP) module to mitigate losses due to nonlinearity effects and for estimating carrier phase has been used at the receiver. We have analyzed the proposed link performance by investigating the required optical signal to noise ratio (OSNR) to achieve a target bit error rate (BER). The reported results show a faithful 160 Gbit/s transmission at 40,000 km with good BER. Also, we numerically investigate the OSNR performance of link for increasing pointing errors. Further, a comparative analysis of the proposed link with previous literature illustrates a better performance in terms of spectral efficiency and figure of merit (maximum transmission range × information transmission rate). The integration of PDM-QPSK with coherent detection and DSP provides a viable platform to develop spectral-efficient IsOWC links. [ABSTRACT FROM AUTHOR]

EPANET 2 software has been widely used among researchers and practitioners from its inception for hydraulic analysis. This technical note presents a method to simulate pressure-dependent volume-based demands in a single extended-period simulation run of EPANET 2. In the proposed method, artificial strings made up of a pipe with a minor loss, pressure-sustaining valve, pipe of negligible resistance, and tank are added to the demand nodes before running the hydraulic analysis. The time required to satisfy a volume-based demand is determined as the time required to fill the artificial tank connected to the demand node for normal and pressure-deficient conditions. All the simulations were carried out using the available functions of the graphical user interface of EPANET 2. The proposed method was applied to a two-source looped network available from the literature and additionally compared with an existing method available in the literature using two example networks. [ABSTRACT FROM AUTHOR]

Nowadays, the smart grid has demonstrated a great ability to make life easier and more comfortable given recent advances. This paper studies the above issue from the perspective of two important and very useful smart grid applications, i.e., the advanced metering infrastructure and demand response using the instrumentality of a set of well-known scheduling algorithms, e.g., best-channel quality indicator, log rule, round robin, and exponential–proportional fairness to validate the performance. To increase the data transmission bandwidth, a new concept of optical wireless communication known as free-space optical communication (FSO) system based on microring resonator (MRR) with the ability to deliver up to gigabit (line of sight) transmission per second is proposed for the two studied smart grid applications. The range between 374.7 and 374.79 THz frequency band was chosen for the generation of 10 successive-carriers with a free spectral range of 8.87 GHz. The ten multi-carriers were produced through drop port of the MRR. The results show up to 10 times bandwidth improvement over the radius as large as 600 m and maintain receive power higher than the minimum threshold (− 20 dBm) at the controller/users, so the overall system is still able to detect the FSO signal and extract the original data without detection. [ABSTRACT FROM AUTHOR]

A comparative study of the inhibitory effect of various parts of the plant Mimusaps Elangi (ME) extract (leaves, fruits, barks, seeds) on the corrosion of mild steel in 1 N HCl medium was investigated using weight loss method, potentiodynamic polarization and electrochemical impedance spectroscopy techniques. The polarization studies revealed that the plants extract act as mixed type inhibitor. It was found from the weight loss method that the inhibition efficiency of ME extracts increase in concentration dependents manner which was also supported by the results of electrochemical techniques. On comparison, maximum inhibition efficiency was found in ME leaves extracts with 98.50% at 20 ppm concentration. The SEM morphology of the adsorbed protective film on the mild steel surface has confirmed the high performance of inhibitive effect of the plant extract. Surface coverage values were tested graphically for suitable adsorption. Temperature studies revealed decrease in inhibition efficiency with increase temperature which suggests physisorption mechanism. [ABSTRACT FROM AUTHOR]

Five variant groups were isolated from the gut of Blue gourami Trichogaster tricopterus through serial dilution, identified by using biochemical tests and bacteria were Bacillus sp., (G1) Pseudomonas sp., (G2) Enterobacter sp., (G3) Aeromonas sp., (G4) and Escherichia sp., (G5). Based on enzymatic productivity (Amylase, Cellulase, Lipase, and Protease) and antimicrobial activity Bacillus sp., Enterobacter sp., and Aeromonas sp., and mass multiplied using nutrient broth. Four different feeds such as feed I (Control), II (1ml Bacillus sp.,) III (1ml each of Bacillus sp. and Enterobacter sp.) and IV (1ml each of Bacillus sp., Enterobacter sp. and Aeromonas sp.,) were prepared. Feed utilization parameters of blue gourami Trichogaster tricopterus were studied after 21 days of rearing and all feed utilization parameters were higher in feed IV. [ABSTRACT FROM AUTHOR]

A new quinoline-based chemosensor, 1,3-dioxoisoindolin-2-yl quinoline-2-carboxylate (DQC) was synthesized and characterized by ESI-MS, 1H NMR, 13C NMR and FT-IR. The binding ability of DQC towards different metal ions was investigated by UV–visible and fluorescence studies. The chemosensor displayed high selectivity and sensitive "on-off" fluorescence response towards Fe3+ in DMSO/H 2 O solution (8:2, v/v). The binding constant value of DQC with Fe3+ was calculated to be 0.71 × 102 M−1 and 0.77 × 102 M−1 using Benesi-Hildebrand plot by UV–vis and fluorescence spectroscopic methods. The sensor shows excellent linearity with a detection limit of 9.9 × 10−8 M and 16 × 10−8 M from UV–vis and fluorescence titration studies respectively. Job's plot analysis exhibits the 1:1 mode of binding between DQC and Fe3+. Moreover, the binding mechanism of Fe3+ with DQC was confirmed by DFT study. Image 1 • The new quinoline-based chemosensor was synthesized for the detection of Fe3+ ions. • The sensor exhibit selectivity and sensitivity toward Fe3+ ions over other metal ions. • The Fluorescence quenching is due to the binding interaction of the Fe3+ ion with DQC. • 1:1 mode of binding stoichiometry was observed between DQC and Fe3+. [ABSTRACT FROM AUTHOR]

A benzofuran-β-alaninamide based chemosensor, 3-(3-((4-methylbenzyl)amino)propanamido)benzofuran-2-carboxamide (BAA), was designed and synthesized for selective detection of Fe3+ ions. The binding ability of BAA towards Fe3+ in DMSO/H2O solution (9/1, v/v) has been studied by UV-vis absorption and fluorescence spectroscopy. Interestingly, the probe BAA exhibits an excellent "turn-on" fluorescence enhancement at 424 nm with an excitation wavelength of 290 nm. The quantum yield was determined to be 0.248 for BAA and 0.447 for the iron complex. The limit of detection (LOD) was calculated to be 1.3 μM and 0.067 μM by UV-vis absorption and fluorescence methods respectively. These values are much lower than that of US Environmental Protection Agency guidelines for drinking water (5.37 μM). Job's plot measurement evidenced the 2 : 1 binding stoichiometry for the complex formed between BAA and Fe3+. Moreover, the binding interaction of BAA towards Fe3+ was confirmed by density functional theory (DFT) studies. Finally, the real sample analysis proved that the probe BAA was more suitable for the detection of Fe3+. [ABSTRACT FROM AUTHOR]

Introduction: Fluoride is a double-edged sword. The fluoride produces a dose-dependent effect on the dentition. However, this is not confined to increased caries resistance. Fluoride causes various disorders, together called fluorosis, if accumulated above certain levels in the body. Aim: The aim of the study is to assess the dental fluorosis prevalence among 6–10 year-old school children in Malaysia. Materials and Methods: A total of 100 school children in the age group of 6–16 years were selected for the study and were divided into six age groups. The children were assessed for dental fluorosis according to Dean’s criteria index of fluorosis, and dental caries according to the WHO basic survey guidelines. The overall health status of the child was assessed by DMFT index. Results: The results of the present study revealed that the prevalence of Grade 2 fluorosis was the highest and Grade 5 fluorosis was the lowest in all the age groups. The number of children was highest in the age group between 15 and 16 years followed by the age group between 6 and 7 years. The overall DMFT increased as the age of the children increased in the different age groups. The DMFT increased as the severity of fluorosis increased up to Grade 2 and then decreased from Grade 3 to Grade 5. Conclusion: Our findings showed that the risk of dental fluorosis was significantly higher in this Johor Bahru area which shows more fluoride content in drinking water and to a lesser degree of dental caries in the same area. [ABSTRACT FROM AUTHOR]

To detect the region and bleeding frame in the wireless capsule endoscopy video, an automatic computer-aided technique is highly demanded to reduce the burden of physicians. The wireless capsule endoscopy (WCE), is an imaging technology which is recently established and doesn't require any wired device. This device detects abnormalities in GI tract, i.e. (colon, esophagus, small intestine, and stomach). A WCE video consists of 57,000 images. It is very hard to examine by clinicians. To determine bleeding photos out of fifty-seven thousand WCE images makes the task very hard and expensive. The main goal is to develop an automatic obscure bleeding detection method by using superpixel segmentation and naive Bayes classifier. Naive Bayes and superpixel segmentation are used for this problem. [ABSTRACT FROM AUTHOR]

The sensing-as-a-service concept has been developed to address the challenges that future smart cities would have in managing an enormous number of sensors. Smart cities must find a solution to the enormous difficulty of effectively sharing user-confidential information without sacrificing quality, privacy, or interruption. The development of blockchain technology has the potential to overcome these problems, but the limitations of the current models include large storage, customizable blockchain, high communication overhead, and high processing costs. The proposed average hybrid leader optimization (AHLO)-PrivPresKey Gen model determined a blockchain-based secure information sharing scheme using a smart contract in a smart city. Blockchain-based smart contracts implement a highly complex midway illustration method to reduce the user's clarification burden. The proposed scheme makes utilize of different safety operators, like 3 Data Encryption Standard, segmenting interpolation, passwords, one time password token and etc. Furthermore, the data privacy phase is improved by utilizing various functionalities, such as dyadic product, Chebyshev polynomial, and keys, where the keys are optimally generated using AHLO. The designed AHLO is obtained by the consolidation of average and subtraction based optimizer and hybrid leader-based optimization. The designed model has delivered minimum memory of 30.5 MB, minimum computational time of 28.467 MB, maximum encryption quality of 0.808, maximum detection rate of 0.898, minimum responsiveness of 41.679 and minimum bandwidth of 95 that surpasses the conventional schemes. [ABSTRACT FROM AUTHOR]

The accessibility and enlargement in development of economical, less weight, highly reliable antennas are required for wireless communication, it poses new challenges for the design of antenna in wireless communication. The micro strip patch antenna used for these communication, because they will provide high frequency and less bandwidth. This paper presents a design and simulation of rectangular micro strip patch antenna at 2.5 GHz frequency range for wireless communication that provides a radiation pattern along a wide angle of beam. The circuit is designed with a full custom approach and incorporates 2 novel logic styles: the Multiple-Output Monotonic CMOS (M2CMOS) and the Dynamic Inversion technique (DI).The designing process uses the Rogers RT/duriod 5880 material is used as the substrate and coaxial probe feed method is used to gives the excitation value of the antenna. This antenna has many practical applications like WLAN, WI-FI etc. so the HFSS software will be used to design and implement the antenna. The designed antenna can be implemented in the FPGA controller with LT spice to check the real time applications. [ABSTRACT FROM AUTHOR]

Abstract We developed a curcumin-based chemosensor (DCD) for selective and efficient detection of Picric acid (PA). The developed chemosensor DCD exhibit a broad emission band at 516 nm and shows green colour fluorescence in DMSO/H 2 O solution (8:2, v/v) due to the more conjugations of its double bonds. Upon binding with PA, the fluorescence intensity of DCD was dramatically quenched in the presence of other aromatic nitro compounds due to the disruption of conjugation. Using Benesi-Hildebrand plot, the binding constant value of DCD with PA was calculated to be 4 × 10−2 M. The chemosensor DCD shows perfect linearity up to 250 μM with a detection limit of 11 × 10−8 M. The binding stoichiometry ratio between DCD and PA was calculated to be 1:1 by Job's plot analysis. In addition, the DFT study also confirms the binding mechanism of DCD with PA. Graphical abstract Image 1 Highlights • The Curcumin-based chemosensor was developed for sensing Picric acid. • The sensor display excellent fluorescence intensity at 516 nm. • The sensor exhibit high selectivity and sensitivity towards Picric acid. • The strong fluorescence quenching of DCD was due to the disruption of conjugation. • The detection limit of DCD to PA was calculated to be 11 × 10−8 M. [ABSTRACT FROM AUTHOR]

Multimetallic nanostructure spinels composed of nickel, cobalt, and manganese ions were synthesized and their bifunctional catalytic activity towards oxygen evolution and oxygen reduction reaction in alkaline pH is reported. Three different compositions, namely, NiCoMnO 4, Ni 1.5 Co 0.75 Mn 0.75 O 4, and Ni 2 Co 0.5 Mn 0.5 O 4 were prepared by a simple template-free hydrothermal route followed by a thermal treatment in air at 600 °C. The ORR/OER activity and the stability of these ternary metal oxides strongly depend on the composition of transition metals. The best performing Ni 1.5 Co 0.75 Mn 0.75 O 4 catalyst exhibits modest OER and ORR activity with an overpotential difference (ΔE = E ORR -E OER) of 0.79 V vs. RHE between two reactions in alkaline solution, comparable to expensive and supported IrO 2, Pt catalysts. Electrochemical studies and extensive physical characterizations indicated that amount of nickel substituted in the crystal lattice influence the bifunctional catalytic activity of the studied ternary metal oxide compositions. • Hydortothermal synthesis of Ni.Mn,Co mixed spinel oxides. • Compositional effect on electrocatalyic activity is reported. • The ternary metal oxides exhibited intriguing OER and modest ORR activity. [ABSTRACT FROM AUTHOR]

This project presents a replacement three-phase converter supported the Cuk converter. The principal feature of the planned topology is that the energy storage parts, like inductors and capacitors, is reduced therefore on boost the trustworthiness, and reduce the size and total value. The buck-boost inherent characteristic of the Cuk device, reckoning on the time-varying duty magnitude relation, provides flexibility for stand alone and grid-connected applications once the required output ac voltage is lower or larger than the dc aspect voltage. Average large and little signal models are accustomed to studying the Cuk converter's nonlinear operation. The essential structure, management vogue, and MATLAB/SIMULINK results are given. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The new pyridine-pyrazole based chemosensor was designed, synthesized and characterized for the detection of Fe3+ ions. • The PPPC exhibits high selectivity and sensitivity toward Fe3+ ions over other metal ions. • Fluorescence quenching mechanism is due to the binding interaction of the Fe3+ ion with PPPC. • Fe3+ ion inhibits the ICT process by forming a complex with PPPC. Abstract A novel pyridine-pyrazole based "turn-off" fluorescent chemosensor namely, 5-N-(pyridine-2-yl)-3-(pyridine-4-yl)-1H-pyrazole-5-carboxamide (PPPC) was designed, synthesized and well characterized by NMR, ESI-MS and FT-IR spectroscopic techniques. UV–vis absorption and fluorescence spectroscopic studies show that PPPC exhibits high selectivity and sensitivity towards Fe3+ ion in DMSO/H 2 O solution (9:1, v/v) over other metal ions. The binding constant (K) of PPPC with Fe3+ was calculated to be 5.1 × 10−2 M and 6.1 × 10−2 M from Benesi-Hildebrand plot using UV–vis and fluorescence spectrophotometer respectively. The detection limit of PPPC for Fe3+ was further determined as 57 nM and 88 nM by UV–vis and fluorescence titrations. Moreover, the binding mechanism of Fe3+ with PPPC was confirmed by DFT study. [ABSTRACT FROM AUTHOR]

In this paper, we will focus on the problem of modeling global or die-to-die variation in semiconductor devices. We will demonstrate that the process corner-based approach for modeling global variation, which has been the dominant approach for design validation, has fundamental limitations in predicting the circuit performance variation. We will then show how a full statistical model of variation can accurately predict circuit behavior and discuss some of the challenges in moving from a corner-based design to statistical simulations. [ABSTRACT FROM AUTHOR]

The aim of the study was to recover copper and lead metal from waste printed circuit boards (PCBs). The electrowinning method is found to be an effective recycling process to recover copper and lead metal from printed circuit board wastes. In order to simplify the process with affordable equipment, a simple ammonical leaching operation method was adopted. The selected PCBs were incinerated into fine ash powder at 500°C for 1 hour in the pyrolysis reactor. Then, the fine ash powder was subjected to acid-leaching process to recover the metals with varying conditions like acid-base concentration, electrode combination, and leaching time. The relative electrolysis solution of 0.1 M lead nitrate for lead and 0.1 M copper sulphate for copper was used to extract metals from PCBs at room temperature. The amount of lead and copper extracted from the process was determined by an atomic absorption spectrophotometer, and results found were 73.29% and 82.17%, respectively. Further, the optimum conditions for the recovery of metals were determined by using RSM software. The results showed that the percentage of lead and copper recovery were 78.25% and 89.1% should be 4 hrs 10 A/dm2. [ABSTRACT FROM AUTHOR]

Hepatitis B is the most serious type of viral hepatitis. The hepatitis B viral transmission occurs in the dental setting mainly due to the improper use of the safety measure by the dentists. This review is to evaluate the hepatitis B infection-related awareness among the dental students. There is a need for improving the knowledge among the students regarding the spread of the infection through the saliva contact. The most serious complication of hepatitis is fulminant hepatitis, and it can also cause hepatocellular carcinoma. The awareness and importance regarding the hepatitis B vaccination are reviewed under this topic. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis, is the second leading infectious cause of death in world. The aim of this study was to evaluate the ADRs to anti tubercular drugs in tuberculosis patients. It was prospective observational study 300 patients were included and were monitored for ADRs. Out of 300 patients, 110 (36.66%) developed ADR. The incidence of ADRs were found to be more in females (77.27%) as compared to males (22.72%). Incidence of ADRs were maximum in the age group 21-40 years (63.63%). Majority of ADRs were Increased liver enzyme transaminase (23.12%) and followed by gastritis (19.90%). As a pharmacist we have the liability to support the patients during the period of antitubercular treatment. These ADR may steer the patient to make a judgment for stopping the medications and finally the occurrence of drug resistance and an amplified health care cost. If a proper educational system is implemented, most of the patient may report their ADR and thereby we can improve the patient adherence and therapeutic outcome. [ABSTRACT FROM AUTHOR]

The ability to transfer crude oil through pipelines from wellhead to refinery without any complication is dealt with midstream flow assurance. Crude oil deposits are found in reservoir under high temperature and pressure which when extracted and transported through pipelines results in drastic changes in their process condition thereby leading to several problems. Conventional methods like electric, emulsification and thermal insulation are highly expensive and often require regular pigging in crude pipelines. Here, Pour Point Depressant (PPD) plays a significant role in reducing the problems faced in pipeline transportation in midstream sector. One of the advanced and recent methods of using PPD is gaining importance over conventional methods due to the ease in handling the different types of crudes. To make this possible, different types of PPDs are employed to encounter various problems. This review discusses the necessity and importance of PPDs, their types, mechanism, nature, advantages etc. in detail. It also touches upon the conventional and a few other techniques applied. [ABSTRACT FROM AUTHOR]

The title salt (I), C6H8N+⋅C20H17O8-, comprises a 2-methylpyridinium cation and a 2,3-bis(4-methylbenzoyloxy)succinate mono-anion while the salt (II), 2C6H8N+⋅2C20H17O8-⋅5H2O, consists of a pair of 4-methylpyridinium cations and 2,3-bis(4-methylbenzo-yloxy)succinate mono-anions and five water molecules of solvation in the asymmetric unit. In (I), the dihedral angle between the aromatic rings of the anion is 40.41 (15)°, comparing with 43.0 (3) and 85.7 (2)° in the conformationally dissimilar anion molecules in (II). The pyridine ring of the cation in (I) is inclined at 23.64 (16) and 42.69 (17)° to the two benzene moieties of the anion. In (II), these comparative values are 4.7 (3), 43.5 (3)° and 43.5 (3), 73.1 (3)° for the two associated cation and anion pairs. The crystal packing of (I) is stabilized by inter-ionic N--H⋯O, O--H⋯O and C--H⋯O hydrogen bonds as well as weak C--H⋯π interactions, linking the ions into infinite chains along [100]. In the crystal packing of (II), the anions and cations are also linked by N--H⋯O and O--H⋯O hydrogen bonds involving also the water molecules, giving a two-dimensional network across (001). The crystal structure is also stabilized by weak C--H⋯O and C--H⋯π interactions. [ABSTRACT FROM AUTHOR]

Brain tumor and brain stroke are two important causes of death in and around the world. The abnormalities in brain cell leads to brain stroke and obstruction in blood flow to brain cells leads to brain stroke. In this article, a computer aided automatic methodology is proposed to detect and segment ischemic stroke in brain MRI images using Adaptive Neuro Fuzzy Inference (ANFIS) classifier. The proposed method consists of preprocessing, feature extraction and classification. The brain image is enhanced using Heuristic histogram equalization technique. Then, texture and morphological features are extracted from the preprocessed image. These features are optimized using Genetic Algorithm and trained and classified using ANFIS classifier. The performance of the proposed ischemic stroke detection system is analyzed in terms of sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and Mathew's correlation coefficient. [ABSTRACT FROM AUTHOR]