A Smart Card-Based Two-Factor Mutual Authentication Scheme for Efficient Deployment of an IoT-Based Telecare Medical Information System

The integration of the Internet of Things (IoT) and the telecare medical information system (TMIS) enables patients to receive timely and convenient healthcare services regardless of their location or time zone. Since the Internet serves as the key hub for connection and data sharing, its open nature presents security and privacy concerns and should be considered when integrating this technology into the current global healthcare system. Cybercriminals target the TMIS because it holds a lot of sensitive patient data, including medical records, personal information, and financial information. As a result, when developing a trustworthy TMIS, strict security procedures are required to deal with these concerns. Several researchers have proposed smart card-based mutual authentication methods to prevent such security attacks, indicating that this will be the preferred method for TMIS security with the IoT. In the existing literature, such methods are typically developed using computationally expensive procedures, such as bilinear pairing, elliptic curve operations, etc., which are unsuitable for biomedical devices with limited resources. Using the concept of hyperelliptic curve cryptography (HECC), we propose a new solution: a smart card-based two-factor mutual authentication scheme. In this new scheme, HECC's finest properties, such as compact parameters and key sizes, are utilized to enhance the real-time performance of an IoT-based TMIS system. The results of a security analysis indicate that the newly contributed scheme is resistant to a wide variety of cryptographic attacks. A comparison of computation and communication costs demonstrates that the proposed scheme is more cost-effective than existing schemes.

An IoT-Enabled E-Nose for Remote Detection and Monitoring of Airborne Pollution Hazards Using LoRa Network Protocol

Detection and monitoring of airborne hazards using e-noses has been lifesaving and prevented accidents in real-world scenarios. E-noses generate unique signature patterns for various volatile organic compounds (VOCs) and, by leveraging artificial intelligence, detect the presence of various VOCs, gases, and smokes onsite. Widespread monitoring of airborne hazards across many remote locations is possible by creating a network of gas sensors using Internet connectivity, which consumes significant power. Long-range (LoRa)-based wireless networks do not require Internet connectivity while operating independently. Therefore, we propose a networked intelligent gas sensor system (N-IGSS) which uses a LoRa low-power wide-area networking protocol for real-time airborne pollution hazard detection and monitoring. We developed a gas sensor node by using an array of seven cross-selective tin-oxide-based metal-oxide semiconductor (MOX) gas sensor elements interfaced with a low-power microcontroller and a LoRa module. Experimentally, we exposed the sensor node to six classes i.e., five VOCs plus ambient air and as released by burning samples of tobacco, paints, carpets, alcohol, and incense sticks. Using the proposed two-stage analysis space transformation approach, the captured dataset was first preprocessed using the standardized linear discriminant analysis (SLDA) method. Four different classifiers, namely AdaBoost, XGBoost, Random Forest (RF), and Multi-Layer Perceptron (MLP), were then trained and tested in the SLDA transformation space. The proposed N-IGSS achieved "all correct" identification of 30 unknown test samples with a low mean squared error (MSE) of 1.42 × 10^-4 over a distance of 590 m.

NOMA-Based VLC Systems: A Comprehensive Review

The enhanced proliferation of connected entities needs a deployment of innovative technologies for the next generation wireless networks. One of the critical concerns, however, is the spectrum scarcity, due to the unprecedented broadcast penetration rate nowadays. Based on this, visible light communication (VLC) has recently emerged as a viable solution to secure high-speed communications. VLC, a high data rate communication technology, has proven its stature as a promising complementary to its radio frequency (RF) counterpart. VLC is a cost-effective, energy-efficient, and secure technology that exploits the current infrastructure, specifically within indoor and underwater environments. Yet, despite their appealing capabilities, VLC systems face several limitations which constraint their potentials such as LED's limited bandwidth, dimming, flickering, line-of-sight (LOS) requirement, impact of harsh weather conditions, noise, interference, shadowing, transceiver alignment, signal decoding complexity, and mobility issue. Consequently, non-orthogonal multiple access (NOMA) has been considered an effective technique to circumvent these shortcomings. The NOMA scheme has emerged as a revolutionary paradigm to address the shortcomings of VLC systems. The potentials of NOMA are to increase the number of users, system's capacity, massive connectivity, and enhance the spectrum and energy efficiency in future communication scenarios. Motivated by this, the presented study offers an overview of NOMA-based VLC systems. This article provides a broad scope of existing research activities of NOMA-based VLC systems. This article aims to provide firsthand knowledge of the prominence of NOMA and VLC and surveys several NOMA-enabled VLC systems. We briefly highlight the potential and capabilities of NOMA-based VLC systems. In addition, we outline the integration of such systems with several emerging technologies such as intelligent reflecting surfaces (IRS), orthogonal frequency division multiplexing (OFDM), multiple-input and multiple-output (MIMO) and unmanned aerial vehicles (UAVs). Furthermore, we focus on NOMA-based hybrid RF/VLC networks and discuss the role of machine learning (ML) tools and physical layer security (PLS) in this domain. In addition, this study also highlights diverse and significant technical hindrances prevailing in NOMA-based VLC systems. We highlight future research directions, along with provided insights that are envisioned to be helpful towards the effective practical deployment of such systems. In a nutshell, this review highlights the existing and ongoing research activities for NOMA-based VLC systems, which will provide sufficient guidelines for research communities working in this domain and it will pave the way for successful deployment of these systems.

A Survey of Deep Learning Based NOMA: State of the Art, Key Aspects, Open Challenges and Future Trends

Non-Orthogonal Multiple Access (NOMA) has become a promising evolution with the emergence of fifth-generation (5G) and Beyond-5G (B5G) rollouts. The potentials of NOMA are to increase the number of users, the system's capacity, massive connectivity, and enhance the spectrum and energy efficiency in future communication scenarios. However, the practical deployment of NOMA is hindered by the inflexibility caused by the offline design paradigm and non-unified signal processing approaches of different NOMA schemes. The recent innovations and breakthroughs in deep learning (DL) methods have paved the way to adequately address these challenges. The DL-based NOMA can break these fundamental limits of conventional NOMA in several aspects, including throughput, bit-error-rate (BER), low latency, task scheduling, resource allocation, user pairing and other better performance characteristics. This article aims to provide firsthand knowledge of the prominence of NOMA and DL and surveys several DL-enabled NOMA systems. This study emphasizes Successive Interference Cancellation (SIC), Channel State Information (CSI), impulse noise (IN), channel estimation, power allocation, resource allocation, user fairness and transceiver design, and a few other parameters as key performance indicators of NOMA systems. In addition, we outline the integration of DL-based NOMA with several emerging technologies such as intelligent reflecting surfaces (IRS), mobile edge computing (MEC), simultaneous wireless and information power transfer (SWIPT), Orthogonal Frequency Division Multiplexing (OFDM), and multiple-input and multiple-output (MIMO). This study also highlights diverse, significant technical hindrances in DL-based NOMA systems. Finally, we identify some future research directions to shed light on paramount developments needed in existing systems as a probable to invigorate further contributions for DL-based NOMA system.

Inside and outside of virus-like particles HBc and HBc/4M2e: A comprehensive study of the structure

Hepatitis B virus core antigen (HBc) with the insertion of four external domains of the influenza A M2 protein (HBc/4M2e) form virus-like particles whose structure was studied using a combination of molecular modeling and cryo-electron microscopy (cryo-EM). It was also shown that self-assembling of the particles occurs inside bacterial cells, but despite the big inner volume of the core shell particle, purified HBc/4M2e contain an insignificant amount of bacterial proteins. It was shown that a fragment of the M2e corresponding to 4M2e insertion is prone to formation of amyloid-like fibrils. However, as the part of the immunodominant loop, M2e insertion does not show a tendency to intermolecular interaction. A full-atomic HBc-4M2e model with the resolution of about 3 Å (3.13 Å for particles of Т = 4 symmetry, 3.7 Å for particles of Т = 3 symmetry) was obtained by molecular modeling methods based on cryo-EM data.

Zero-Padding and Spatial Augmentation-Based Gas Sensor Node Optimization Approach in Resource-Constrained 6G-IoT Paradigm

Ultra-low-power is a key performance indicator in 6G-IoT ecosystems. Sensor nodes in this eco-system are also capable of running light-weight artificial intelligence (AI) models. In this work, we have achieved high performance in a gas sensor system using Convolutional Neural Network (CNN) with a smaller number of gas sensor elements. We have identified redundant gas sensor elements in a gas sensor array and removed them to reduce the power consumption without significant deviation in the node’s performance. The inevitable variation in the performance due to removing redundant sensor elements has been compensated using specialized data pre-processing (zero-padded virtual sensors and spatial augmentation) and CNN. The experiment is demonstrated to classify and quantify the four hazardous gases, viz., acetone, carbon tetrachloride, ethyl methyl ketone, and xylene. The performance of the unoptimized gas sensor array has been taken as a “baseline” to compare the performance of the optimized gas sensor array. Our proposed approach reduces the power consumption from 10 Watts to 5 Watts; classification performance sustained to 100 percent while quantification performance compensated up to a mean squared error (MSE) of 1.12 × 10⁻². Thus, our power-efficient optimization paves the way to “computation on edge”, even in the resource-constrained 6G-IoT paradigm.

Caught red handed: modeling and confirmation of the myeloperoxidase ceruloplasmin alpha-thrombin complex

The work is devoted to the study of the structural characteristics of the myeloperoxidase-ceruloplasmin-thrombin complex using small-angle neutron scattering methods in combination with computer modeling, as well as surface plasmon resonance and solid-phase enzyme assay. We have previously shown that the functioning of active myeloperoxidase during inflammation, despite the presence in the blood of an excess of ceruloplasmin which inhibits its activity, is possible due to the partial proteolysis of ceruloplasmin by thrombin. In this study, the myeloperoxidase-ceruloplasmin-thrombin heterohexamer was obtained in vitro. The building of a heterohexamer full-atomic model in silico, considering the glycosylation of the constituent proteins, confirmed the absence of steric barriers for the formation of protein-protein contacts. It was shown that the partial proteolysis of ceruloplasmin does not affect its ability to bind to myeloperoxidase, and a structural model of the heterohexamer was obtained using the small-angle neutron scattering method.

Cold and distant: structural features of the nucleoprotein complex of a cold-adapted influenza A virus strain

Two influenza A nucleoprotein variants (wild-type: G102R; and mutant: G102R and E292G) were studied with regard to macro-molecular interactions in oligomeric form (24-mers). The E292G mutation has been previously shown to provide cold adaptation. Molecular dynamics simulations of these complexes and trajectory analysis showed that the most significant difference between the obtained models was distance between nucleoprotein complex strands. The isolated complexes of two ribonucleoprotein variants were characterized by transmission electron microscopy and differential scanning fluorimetry (DSF). Presence of the E292G substitution was shown by DSF to affect nucleoprotein complex melting temperature. In the filament interface peptide model, it was shown that the peptide corresponding in primary structure to the wild-type NP (SGYDFEREGYS) is prone to temperature-dependent self-association, unlike the peptide corresponding to E292G substitution (SGYDFGREGYS). It was also shown that the SGYDFEREGYS peptide is capable of interacting with a monomeric nucleoprotein (wild type); this interaction's equilibrium dissociation constant is five orders of magnitude lower than for the SGYDFGREGYS peptide. Using small-angle neutron scattering (SANS), the supramolecular structures of isolated complexes of these proteins were studied at temperatures of 15, 32, and 37 °C. SANS data show that the structures of the studied complexes at elevated temperature differ from the rod-like particle model and react differently to temperature changes. The data suggest that the mechanism behind cold adaptation with E292G is associated with a weakening of the interaction between strands of the ribonucleoprotein complex and, as a result, the appearance of inter-chain interface flexibility necessary for complex function at low temperature.Communicated by Ramaswamy H. Sarma.

A double-edged sword: supramolecular complexes of triazavirine display multicenter binding effects which influence aggregate formation

Communicated by Ramaswamy H. Sarma.

Triazavirine supramolecular complexes as modifiers of the peptide oligomeric structure

In this study, we present molecular dynamics simulations of the antiviral drug triazavirine, that affects formation of amyloid-like fibrils of the model peptide (SI). According to our simulations, triazavirine is able to form linear supramolecular structures which can act as shields and prevent interactions between SI monomers. This model, as validated by simulations, provides an adequate explanation of triazavirine's mechanism of action as it pertains to SI peptide fibril formation.

Partially Assembled Nucleosome Structures at Atomic Detail

The evidence is now overwhelming that partially assembled nucleosome states (PANS) are as important as the canonical nucleosome structure for the understanding of how accessibility to genomic DNA is regulated in cells. We use a combination of molecular dynamics simulation and atomic force microscopy to deliver, in atomic detail, structural models of three key PANS: the hexasome (H2A·H2B)·(H3·H4)₂, the tetrasome (H3·H4)₂, and the disome (H3·H4). Despite fluctuations of the conformation of the free DNA in these structures, regions of protected DNA in close contact with the histone core remain stable, thus establishing the basis for the understanding of the role of PANS in DNA accessibility regulation. On average, the length of protected DNA in each structure is roughly 18 basepairs per histone protein. Atomistically detailed PANS are used to explain experimental observations; specifically, we discuss interpretation of atomic force microscopy, Förster resonance energy transfer, and small-angle x-ray scattering data obtained under conditions when PANS are expected to exist. Further, we suggest an alternative interpretation of a recent genome-wide study of DNA protection in active chromatin of fruit fly, leading to a conclusion that the three PANS are present in actively transcribing regions in a substantial amount. The presence of PANS may not only be a consequence, but also a prerequisite for fast transcription in vivo.

Characterization of the cleaved edge cross section of the heterostructures with GaMnAs layer by the confocal micro-Raman spectroscopy

Confocal micro-Raman spectroscopy was used to measure cross-section linescans of the cleaved edge of heterostructures involving a GaMnAs layer. The investigations revealed a shift of the TO mode in the compressed GaMnAs layer to high frequencies relative to the TO GaAs mode in the substrate and to low frequencies in the tensile GaMnAs layers. These results are in agreement with the different manifestations of the anomalous Hall effect in the GaMnAs layers, with either compressive or tensile strains. It is shown that Raman spectroscopy is an appropriate method for the investigation of cross-sectional semiconductor heterostructures whose total thickness is comparable to the size of the analyzing laser spot.

Effects of Experimental Coma on the Expression of Bcl-2 Protein and Caspases 3 and 9 in Rat Brain

We performed immunohistochemical analysis of the expression of caspases 3, 9 and bcl-2 protein in rat brain at various terms after administration of LD50 of sodium thiopental. Expression of the specified apoptosis markers was found in the sensorimotor cortex and hippocampus (dentate gyrus and CA2 region).

Structure of RecX protein complex with the presynaptic RecA filament: Molecular dynamics simulations and small angle neutron scattering

Using molecular modeling techniques we have built the full atomic structure and performed molecular dynamics simulations for the complexes formed by Escherichia coli RecX protein with a single-stranded oligonucleotide and with RecA presynaptic filament. Based on the modeling and SANS experimental data a sandwich-like filament structure formed two chains of RecX monomers bound to the opposite sides of the single stranded DNA is proposed for RecX::ssDNA complex. The model for RecX::RecA::ssDNA include RecX binding into the grove of RecA::ssDNA filament that occurs mainly via Coulomb interactions between RecX and ssDNA. Formation of RecX::RecA::ssDNA filaments in solution was confirmed by SANS measurements which were in agreement with the spectra computed from the molecular dynamics simulations.

[On epigenetic regulation of process of formation of long-term memory]

The review summarizes current concepts on role of several covalent posttranslation chromatin modifications in the process of memory formation in vertebrate and invertebrate animals. There is described a chain of intracellular events from activation of receptors and signal pathways to change of the functional state of genome.

[The morphological basis of conditioned reflex in the honeybee Apis mellifera L]

A review. Works related to research into the neuroanatomical basis of associative learning in the honeybee (proboscis extension reflex) are summarized. Data on the brain organization of the honeybee are presented. The parallel neural pathways of conditioned and unconditioned stimuli are shown. Contribution of different brain structures and identified neurons (VUMmx1, PE1) in the formation of the proboscis extension reflex are discussed.

[Changing of filamentation dynamics of RecA protein, induced by D112R amino acid substitution or ATP to dATP replacement, results in filament steadiness TO THE RecX protein action]

It is known that RecX is a negative regulator of RecA protein. We found that the mutant RecA D112R protein exhibits increased resistance to RecX protein comparatively to wild-type RecA protein in vitro and in vivo. Using molecular modeling we showed, that amino acid located in position 112 can not approach RecX closer than 25-28 angstroms. Thus, direct contact between amino acid and RecX is impossible. RecA D112R protein more actively competes with SSB protein for the binding sites on ssDNA and, therefore, differs from the wild-type RecA protein by dynamics of filamentation on ssDNA. On the other hand, after the replacement of ATP by dATP, the wild-type RecA protein, changing the dynamics of filamentation on ssDNA, also becomes more resistant to RecX. Based on these data it is concluded that the dynamics of filamentation has a great, if not dominant role in the stability of RecA filament to RecX relative to the role of RecA-RecX protein-protein interactions discussed earlier. We also propose an improved model of regulation of RecA by RecX protein, where RecA filament elongation along ssDNA is blocked by RecX protein on the ssDNA region, located outside the filament.

[The effect of point amino acid substitutions in an internal alpha-helix on thermostability of Aspergillus awamori X100 glucoamylase]

Conformational flexibility of alpha-helices in glucoamylase of the fungus Aspergillus awamori was studied by molecular dynamics methods. Several amino acid substitutions (G127A, P128A, I136L, G137A, and G139A) optimizing intrinsic interactions in one of the alpha-helices (D) within the hydrophobic core of this protein were constructed and studied. It was found that these point mutations had different effects on the glucoamylase thermal inactivation constant. Unlike amino acid substitution P128A and substitutions G137A and A246C, I136L and G139A displayed a pronounced additive thermostabilizing effect.