Pneumonia is an acute respiratory illness caused by viruses or bacteria. Early detection of pneumonia is important to ensure curative treatment and improve survival rates. Pneumonia detection on ...chest X-rays (CXR) is important for early diagnosis, effective treatment, monitoring patient progress, and managing public health concerns. It plays a vital role in ensuring that individuals with pneumonia receive the appropriate care they need while contributing to research and disease surveillance efforts. However, the examination of CXRs is a difficult process and is prone to subjective variabilities. The use of artificial intelligence (AI) and deep learning (DL) models can perform the detection and classification of pneumonia on CXR images. With this motivation, this study introduces a new Chaotic Sea Horse Optimization with Deep Learning Method for Pneumonia Detection and Classification (CSHODL-PDC) technique on CXR images. The main intention of the CSHODL-PDC algorithm lies in the automated detection and classification of pneumonia on CXR images. The CSHODL-PDC method initially designs a Gaussian filtering (GF) based noise eradication approach to eliminate the noise. In addition, the CSHODL-PDC technique employs the NASNetLarge model to produce a set of feature vectors. Moreover, an improved fuzzy deep neural network (FDNN) model is applied for the automated identification and classification of pneumonia. Finally, the CSHO algorithm selects the optimal hyperparameter values of the improved FDNN model, demonstrating the novelty of the work. A series of simulation analyses were performed on the CXR Pneumonia dataset from the Kaggle repository. The experimental values inferred the improved performance of the CSHODL-PDC method over recent models with a maximum accuracy of 99.22%, precision of 98.96%, and recall of 99.22%. Therefore, the proposed model can be employed for accurate and automated pneumonia detection.
The densely packed electronic components in electronic devices emit electromagnetic (EM) radiations, and the interaction of the emitted EM radiations with external EM signals of neighboring ...components leads to device malfunctions and also creates health issues in human beings. Particularly, in aircraft, EM interference is a serious threat that leads to disastrous outcomes. The shielding of electronic components is an ideal way to reduce the pollution of electromagnetic interference (EMI). The mechanism of EMI shielding efficiency is discussed elaborately in this article. The factors associated with the EMI shielding of materials are discussed in detail. The EMI shielding by reflection and absorption are two possible routes to improve the shielding performance of the shielding materials. This article also highlights the EMI shielding mechanisms by reflection and absorption. However, the risk of secondary EM pollution is associated with the reflection of EM waves. This review also outlines the methods to improve the absorption‐based shielding performance of the materials. The significance of the microstructure of the shielding materials in enhancing the absorption‐dominant shielding efficiency is also presented with a detailed analysis. This helps to fabricate the absorption‐dominant EMI shielding materials with suitable microstructures. The EM loss is associated with the magnetic, dielectric, and conduction losses according to EM theory.
Highlights
This article highlights the recent progress in epoxy‐based EMI shielding materials.
EMI shielding mechanisms by reflection and absorption are discussed elaborately.
Reviewed the methods to improve the absorption‐based shielding performance in detail.
Materials with EMI shielding efficiency greater than 30 dB are highly preferable.
Attenuation mechanisms involved in absorption‐based EMI shielding
The leaf extract of
Senna alata
(SA) was employed as a bio-reducing agent to prepare the bioactive Ag-NPs. The FTIR spectrum of Ag-NPs revealed the existence of biomolecules in SA leaf extract. The ...formation of Ag-NPs was confirmed by analyzing their XRD profile. The SPR band at 434 nm in the UV spectrum also supported the formation of Ag-NPs. The grain size was computed as 25 nm by XRD. It was further confirmed using TEM. The morphology of the bioactive Ag-NPs was affirmed as spherical by SEM. The cytotoxicity of bioactive Ag-NPs against brine shrimp was assessed by a lethal toxicity test. The significant antibacterial potential of bioactive Ag-NPs against six pathogenic strains was concluded by disc diffusion assay. The prepared bioactive Ag-NPs exhibited a higher antimicrobial property against
B. subtilis
and
V. cholera
. The anticancer property of the prepared Ag-NPs was also examined against breast cancer cells.
Graphical abstract
Highlights
The bioactive Ag-NPs were prepared by using leaf extract of
Senna alata
.
The bioactive Ag-NPs exhibited significant antimicrobial activity against six pathogenic strains.
The anticancer potential of bioactive Ag-NPs was also examined against the MCF-7 cell line.
A novel fluorescent polyimide (PI) made up of perylenetetracarboxylic dianhydride (PTCDAH) and p-phenylenediamine (PPDA) was prepared with or without Ag and V2O5 nanoparticles at 160 °C for 5 h under ...N2 atmosphere with vigorous stirring. The influence of nanomaterials on the rate of polymerization (Rp) was determined. The synthesized PI and PI nanocomposites were characterized to analyse their chemical functionality (FT-IR), surface morphology (FE-SEM) and thermal properties (DSC and TGA). The catalytic reduction of Cr (VI), p-nitrophenol (NP) and rhodamine6G (R6G) dye was analysed using the prepared PI and PI nanocomposites as a catalyst. It was found that the Rp of PI nanocomposites was higher than pristine PI system. The PI/Ag nanocomposite system exhibited higher degradation temperature (Td) and apparent rate constant (kapp) values towards the reduction of R6G dye.
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•The PI/Ag nanocomposite system yielded higher Td value.•The PI/V2O5 system produced the cage like structure.•The PI/Ag nanocomposite system produced higher kapp value towards the reduction of NP and R6G.•The PI/ V2O5 nanocomposite system exhibited higher kapp value for the reduction of Cr(VI).
The bioactive silver nanoparticles (SNPs) were synthesized using leaf extract of
Leucas zeylanica
(LZ) as a bioreductant. The polyphenols of LZ extract were involved in stabilizing bioactive SNPs. ...The biomolecules of LZ were acting as capping and stabilizing agents. The physical interaction of SNPs with the biomolecules of LZ was concluded by FTIR. The structure of SNPs was affirmed by XRD, and the particle size was obtained as 46 nm using Scherer’s equation. The UV–Visible analysis revealed that the SPR peak appeared at 422 nm only after the bio-reduction of Ag
+
ions into SNPs. The LZ-capped SNPs were also investigated to evaluate their anticancer activity against MCF7 cells. The prepared SNPs induced cell death of 91% at a concentration of 1000 µg/ml. The antimicrobial potential of SNPs was evaluated against four foodborne pathogenic strains by the disk diffusion method. The bioactive SNPs exhibited the highest inhibition zone of 42 mm against
S. aureus
. The brine shrimp was employed as a bioassay to assess the cytotoxicity of the LZ-mediated colloidal SNPs.
Graphical abstract
Highlights
The LZ-capped SNPs were prepared by using leaf extract of
Leucas zeylanica
.
The LZ-capped SNPs exhibited promising antimicrobial activity against four pathogenic strains.
The anticancer potential of LZ-capped SNPs was investigated against the MCF-7 cell line.
The cytotoxicity of LZ-capped SNPs against brine shrimp was found to be dose-dependent.
Nanofluids (NFs) are technologically important heat transfer fluids that are prepared by suspending nanoparticles (NPs) of size less than 100 nm in the base fluids. NFs have been employed in heat ...transfer applications such as solar heat exchangers, radiators, heat sinks, refrigeration systems, heat pipes, solar collectors and thermal energy storage, owing to their remarkable thermo-physical properties over conventional heat transfer fluids. However, the efficiency of the NFs primarily depends on the suspension stability. The development of NFs with excellent stability is important to bridge the gap between research and commercialization. This article is a review of one-step methods developed for the preparation of NFs with enhanced stability as compared with NFs prepared by the two-step method. This review also discusses the various analytical tools which are used to conclude the structure-property relation, particle size, thermal conductivity, stability and viscosity of the NFs. This article also highlights the determination of the thermal conductivity of HNFs by various thermal conductivity models.
The recording and measurement of the electric events of the brain utilizing an electroencephalogram (EEG) has turned out to be a prominent equipment among the plethora of devices used for the ...analysis of neural ailments in the previous few years, especially for seizure detection. It is condemnatory to ascertain if the state of an epilepsy patient’s brain is symptomatic of a plausible seizure beginning; hence, EEG signals aid with the provision of significant information regarding the epileptogenic networks which is meant to be scrutinized and comprehended prior the commencement of therapeutic proceedings. And so relevant alarm or treatment could be provided in time. Desirable seizure prognosis depends on the ability to appropriately distinguish the preictal phase from the interictal phase of ictal in EEG. The pre-programmed seizure indication system can efficiently aid physicians to diagnose and proctor epilepsy which also decreases their amount of work. Various different remarkable studies are found to give great outcomes in the complication two-class seizure diagnosis, but the majority of the feature extraction techniques are contingent on manual techniques. This work nominates a start to end seizure indication structure that is automatic and whose methodology is grounded on deep learning. To achieve this, EEG signals from CHB-MIT Scalp EEG database. The Deep convolutional variational autoencoder (DCVAE) was utilized to study the expressed seizure features from EEG data and The tunable Q-factor wavelet transform (TQWT) was utilized for pre-processing. Later, these vigorous EEG characteristics relevant to seizures are provided as the input to the stacked bi-directional long short-term memory (SB-LSTM) model for the automatic detection of epileptic seizures. One of the best models, achieved an accuracy of 99.6%, sensitivity of 98.85%, and specificity values of 99.8%, respectively.
2-aminopyridinium adipate monoadipic acid dihydrate (2APA) single crystal was grown by the slow evaporation solution growth technique. Single crystal X-ray and Powder X-ray diffraction analysis ...confirmed the lattice cell parameters and crystallinity of 2APA crystal. Fourier Transform–Infrared (FT-IR), Fourier Transform-Raman (FT-R), and Nuclear Magnetic Resonance spectral studies have been used to confirm the functional group and structure of 2APA single crystal. The UV–Visible spectral analysis found the 2APA single crystal transparency (60%), cut-off wavelength (298), and band gap (E
g
= 4.1 eV). Vicker’s microhardness study analyzed the mechanical strength of a 2APA single crystal. The laser damage threshold value of 2APA is 2.1 GW/cm
2
using Nd: YAG laser. The third-order NLO susceptibility of 2APA single crystal is 4.81 × 10
–6
esu, estimated by the Z-scan technique.
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Recently, The conservation of energy in these nodes is of utmost importance for Internet of Things (IoT) systems used in monitoring patients. The significant factors that cause power ...consumption in an Internet of Healthcare Things (IoHT) network. Hence, a novel MAC resource allocation protocol called Centralized Dynamic Time Scheduling (CDTS) is designed to overcome these issues. The CDTS system helps to avoid congestion and network traffic in the IoHT network. This proposed approach is compared with a fuzzy-based technique to measure efficiency. It is observed that our proposed technique reduced power consumption by up to 20% and is suitable for real-time healthcare applications.
•The conservation energy in IoHT network is cited as major concern.•To avoid congestion and network traffic in the IoHT network.•A novel CDTS resource allocation protocol is designed to increase network lifetime.•A new dynamic feedback loop method reduces the total bit error rate in the network.•Our proposed method power consumption by up to 20%.
Due to the limited energy source in the sensor nodes, the conservation of energy in these nodes is of utmost importance for Internet of Things (IoT) systems used in monitoring patients. The significant factors that cause power consumption in an Internet of Healthcare Things (IoHT) network are network interference, resource allocation, and time spent idly by body sensors. Moreover, complex encoding, decoding, and encryption processes could increase the processing time in both Media Access Control (MAC) and Physical (PHY) layers. Hence, a novel MAC resource allocation protocol called Centralized Dynamic Time Scheduling (CDTS) is designed to overcome these issues. The CDTS system helps to avoid congestion and network traffic in the IoHT network. The main objective of this algorithm is to reduce the active time of each sensor in the network. We also reduced the total bit error rate in the network by introducing a dynamic bit interleaving method with a feedback loop. It is known that In the PHY layer, encoding and decoding are implemented with the help of a passive modulation scheme to reduce the delay in the network. In the encryption process, the Elliptic curve cryptography(ECC) method is used, which reduces the number of iterations required for encrypting the data. This proposed approach is compared with a fuzzy-based technique to measure efficiency. It is observed that our proposed technique reduced power consumption by up to 20% and is suitable for real-time healthcare applications.
