Using Selective Electron Beam Melting to Enhance the High-Temperature Strength and Creep Resistance of NiAl–28Cr–6Mo In Situ Composites

By increasing the density of interfaces in NiAl–CrMo in situ composites, the mechanical properties can be significantly improved compared to conventionally cast material. The refined microstructure is achieved by manufacturing through electron beam powder bed fusion (PBF-EB). By varying the process parameters, an equiaxed or columnar cell morphology can be obtained, exhibiting a plate-like or an interconnected network of the (Cr,Mo) reinforcement phase which is embedded in a NiAl matrix. The microstructure of the different cell morphologies is investigated in detail using scanning electron microscope, transmission electron microscopy, and atom probe tomography. For both morphologies, the mechanical properties at elevated temperatures are analyzed by compression and creep experiments parallel and perpendicular to the building direction. In comparison to cast NiAl and NiAl–(Cr, Mo), the yield strength of the PBF-EB fabricated specimens is significantly improved at temperatures up to 1,027 °C. While the columnar morphology exhibits the best improved mechanical properties at high temperatures, the equiaxial morphology shows nearly ideal isotropic mechanical behavior, which is a substantial advantage over directionally solidified material.     

Modeling and Analysis of UAV-Assisted Mobile Network with Imperfect Beam Alignment

With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed according to Poisson Cluster Process (PCP) around base stations, in particular, Thomas Cluster Process (TCP). Using this model, the impact of beam alignment errors on the coverage probability was investigated. Initially, the Probability Density Function (PDF) of directional antenna gain between the user and its serving base station was obtained. Then, association probability with each tier was achieved. A tractable expression was derived for coverage probability in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) condition links. Numerical results demonstrated that at low UAVs altitude, beam alignment errors significantly degrade coverage performance. Moreover, for a small cluster size, alignment errors do not necessarily affect the coverage performance.     

Optimal Deep Learning Model Enabled Secure UAV Classification forIndustry 4.0

Emerging technologies such as edge computing, Internet of Things (IoT), 5G networks, big data, Artificial Intelligence (AI), and Unmanned Aerial Vehicles (UAVs) empower, Industry 4.0, with a progressive production methodology that shows attention to the interaction between machine and human beings. In the literature, various authors have focused on resolving security problems in UAV communication to provide safety for vital applications. The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification (CSODL-SUAVC) model for Industry 4.0 environment. The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification. Primarily, the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation (ML-DWT), CSO-related Optimal Pixel Selection (CSO-OPS), and signcryption-based encryption. The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images. The secret images, encrypted by signcryption technique, are embedded into cover images. Besides, the image classification process includes three components namely, Super-Resolution using Convolution Neural Network (SRCNN), Adam optimizer, and softmax classifier. The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication. The proposed CSODL-SUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects. The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.     

WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service (QoS). SDN having an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance. To implement WiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator. The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30% and enhances the throughput by 20%–50%, hence maintaining user fairness and accommodating more wireless devices and traffic load in the network, when compared to traditional client-driven (CD) approach and state of the art Wi-Balance approach.     

Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and beef with different concentrations (10%–50% v/v). Principal component analysis (PCA) and partial least square (PLS) were used to develop a calibration model at 800–3500 cm⁻¹. Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken, lamb, and beef samples. The corresponding FTIR peaks for the lard have been observed at 1159.6, 1743.4, 2853.1, and 2922.5 cm⁻¹, which differentiate chicken, lamb, and beef samples. The wavenumbers offer the highest determination coefficient R² value of 0.846 and lowest root mean square error of calibration (RMSEC) and root mean square error prediction (RMSEP) with an accuracy of 84.6%. Even the tiniest fat adulteration up to 10% can be reliably discovered using this methodology.     

Classification of Electroencephalogram Signals Using LSTM and SVM Based on Fast Walsh-Hadamard Transform

Classification of electroencephalogram (EEG) signals for humans can be achieved via artificial intelligence (AI) techniques. Especially, the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic regions. From this perspective, an automated AI technique with a digital processing method can be used to improve these signals. This paper proposes two classifiers: long short-term memory (LSTM) and support vector machine (SVM) for the classification of seizure and non-seizure EEG signals. These classifiers are applied to a public dataset, namely the University of Bonn, which consists of 2 classes –seizure and non-seizure. In addition, a fast Walsh-Hadamard Transform (FWHT) technique is implemented to analyze the EEG signals within the recurrence space of the brain. Thus, Hadamard coefficients of the EEG signals are obtained via the FWHT. Moreover, the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG recordings. Also, a k-fold cross-validation technique is applied to validate the performance of the proposed classifiers. The LSTM classifier provides the best performance, with a testing accuracy of 99.00%. The training and testing loss rates for the LSTM are 0.0029 and 0.0602, respectively, while the weighted average precision, recall, and F1-score for the LSTM are 99.00%. The results of the SVM classifier in terms of accuracy, sensitivity, and specificity reached 91%, 93.52%, and 91.3%, respectively. The computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s, respectively. The results show that the LSTM classifier provides better performance than SVM in the classification of EEG signals. Eventually, the proposed classifiers provide high classification accuracy compared to previously published classifiers.     

Royal Crown Shaped Polarization Insensitive Perfect Metamaterial Absorber for C-, X-, and Ku-Band Applications

This study proposed a new royal crown-shaped polarisation insensitive double negative triple band microwave range electromagnetic metamaterial absorber (MA). The primary purpose of this study is to utilise the exotic characteristics of this perfect metamaterial absorber (PMA) for microwave wireless communications. The fundamental unit cell of the proposed MA consists of two pentagonal-shaped resonators and two inverse C-shaped metallic components surrounded by a split ring resonator (SRR). The bottom thin copper deposit and upper metallic resonator surface are disjoined by an FR-4 dielectric substrate with 1.6 mm thickness. The CST MW studio, a high-frequency electromagnetic simulator has been deployed for numerical simulation of the unit cell in the frequency range of 4 to 14 GHz. In the TE mode, the offered MA structure demonstrated three different absorption peaks at 6.85 GHz (C-band), 8.87 GHz (X-band), and 12.03 GHz (Ku-band), with 96.82%, 99.24%, and 99.43% absorptivity, respectively. The electric field, magnetic field, and surface current distribution were analysed using Maxwell’s-Curl equations, whereas the angle sensitivity was investigated to comprehend the absorption mechanism of the proposed absorber. The numerical results were verified using the Ansys HFSS (high-frequency structure simulator) and ADS (advanced design system) for equivalent circuit models. Moreover, the proposed MA is polarisation and incident angle independent. Hence, the application of this MA can be extended to a great extent, including airborne radar applications, defence, and stealth-coating technology.     

Net interaction between different forms of short-term synaptic plasticity and slow-IPSPs in the hippocampus and auditory cortex

Paired-pulse plasticity is typically used to study the mechanisms underlying synaptic transmission and modulation. An important question relates to whether, under physiological conditions in which various opposing synaptic properties are acting in parallel, the net effect is facilitatory or depressive, that is, whether cells further or closer to threshold. For example, does the net sum of paired-pulse facilitation (PPF) of excitatory postsynaptic potentials (EPSPs), paired-pulse depression (PPD) of inhibitory postsynaptic potentials (IPSPs), and the hyperpolarizing slow IPSP result in depression or facilitation? Here we examine how different time-dependent properties act in parallel and examine the contribution of gamma-aminobutyric acid-B (GABAB) receptors that mediate two opposing processes, the slow IPSP and PPD of the fast IPSP. Using intracellular recordings from rat CA3 hippocampal neurons and L-II/III auditory cortex neurons, we examined the postsynaptic responses to paired-pulse stimulation (with intervals between 50 and 400 ms) of the Schaffer collaterals and white matter, respectively. Changes in the amplitude, time-to-peak (TTP), and slope of each EPSP were analyzed before and after application of the GABAB antagonist CGP-55845. In both CA3 and L-II/III neurons the peak amplitude of the second EPSP was generally depressed (further from threshold) compared with the first at the longer intervals; however, these EPSPs were generally broader and exhibited a longer TTP that could result in facilitation by enhancing temporal summation. At the short intervals CA3 neurons exhibited facilitation of the peak EPSP amplitude in the absence and presence of CGP-55845. In contrast, on average L-II/III cells did not exhibit facilitation at any interval, in the absence or presence of CGP-55845. CGP-55845 generally "erased" short-term plasticity, equalizing the peak amplitude and TTP of the first and second EPSPs at longer intervals in the hippocampus and auditory cortex. These results show that it is necessary to consider all time-dependent properties to determine whether facilitation or depression will dominate under intact pharmacological conditions. Furthermore our results suggest that GABAB-dependent properties may be the major contributor to short-term plasticity on the time scale of a few hundred milliseconds and are consistent with the hypothesis that the balance of different time-dependent processes can modulate the state of networks in a complex manner and could contribute to the generation of temporally sensitive neural responses.     

A point of view: why point-of-care places are not free marketplaces

Current wisdom holds that health care is a business and "as such must abide by market principles." Most nurses are not well enough versed in economic theories to credibly critique health care delivery decisions based on economic theories. The relationship of market principles to health care realities is described in basic terms to encourage nurses to "optimize patient care and influence health care policy." Physicians, who control all access points to the health care system, have enjoyed a 40-year market dominance that is "rapidly being replaced by insurance companies and for-profit investors." Providers' decisions to treat or not to treat are strongly influenced by whether the patient is in a fee-for-service or capitated payment environment.     

Ristocetin- and thrombin-induced platelet aggregation at physiological shear rates: differential roles for GPIb and GPIIb-IIIa receptor

We recently reported that washed platelets (WP) activated with ADP and expressing surface-bound vWF aggregated in flow through small tubes or in a cylindrical couette device at physiological shear rates of G = 300 s(-1)-1000 s(-1) in the absence of exogenous ligands, with GPIb-vWF partially, and activated GPIIb-IIIa totally required for the aggregation. We have now extended these studies to aggregation of platelets "activated" with ristocetin or thrombin. Washed platelet suspensions with added soluble vWF and ristocetin (0.3-0.75 mg/ml), or activated with thrombin (0.01-0.5 U/ml) but no added ligand, were sheared in a coaxial cylinder device at uniform shear rate, G = 1000 s(-1). The collision capture efficiency (alphaG) with which small aggregates form (= experimental/calculated initial rates of aggregation) was correlated with vWF platelet binding assessed by flow cytometry. The vWF-GPIb interaction was exclusively able to support ristocetin-mediated shear aggregation of metabolically active platelets, with very few vWF monomer equivalents bound per platelet (representing < or = 10 molecules of 10 million Da) required to yield high capture efficiencies (alphaG = 0.38+/-.02; n = 11), suggesting rapid and stable bond formations between vWF and GPIb. However, platelet surface-expressed vWF, generated by addition of thrombin to washed platelets, was found to mediate platelet aggregation with alphaG = 0.08+/-.01 (n = 6), surprisingly comparable to that previously reported for WP and ADP activation. Blocking the GPIIb-Illa receptor decreased alphaG by 95+/-3% (n =3), while a monoclonal antibody to the vWF site on GPIb caused a 49+/-7% (n = 8) decrease in alphaG. The partial role for GPIb thus appears to reflect a facilitative function for increasing contact time between flowing platelets, and allowing engagement of the GPIIb-IIa receptor to yield stable attachment.