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Abstract This paper provides convergence analysis of some variants of the hybrid extragradient algorithm (HEA) in Hilbert spaces. We employ the HEA to compute the common solution of the equilibrium problem and split fixed-point problem associated with the finite families of k $\Bbbk $ -demicontractive mappings. We also incorporate appropriate numerical results concerning the viability of the proposed variants with respect to various real-world applications.

In this paper, we examine the convergence analysis of a variant of Tseng's splitting method for monotone inclusion problem and fixed point problem associated with an infinite family of $ \eta $-demimetric mappings in Hilbert spaces. The qualitative results of the proposed variant shows strong convergence characteristics under a suitable set of control conditions. We also provide a numerical example to demonstrate the applicability of the variant with some applications.

Understanding the role of the mitogen-activated protein kinases (MAPKs) signalling pathway is essential in advancing treatments for neurodegenerative disorders like Alzheimer's. In this study, we investigate in-silico techniques involving computer-based methods to extract the MAPK1 sequence. Our applied methods enable us to analyze the protein's structure, evaluate its properties, establish its evolutionary relationships, and assess its prevalence in populations. We also predict epitopes, assess their ability to trigger immune responses, and check for allergenicity using advanced computational tools to understand their immunological properties comprehensively. We apply virtual screening, docking, and structure modelling to identify promising drug candidates, analyze their interactions, and enhance drug design processes. We identified a total of 30 cell-targeting molecules against the MAPK1 protein, where we selected top 10 CTL epitopes (PAGGGPNPG, GGGPNPGSG, SAPAGGGPN, AVSAPAGGG, AGGGPNPGS, ATAAVSAPA, TAAVSAPAG, ENIIGINDI, INDIIRTPT, and NDIIRTPTI) for further evaluation to determine their potential efficacy, safety, and suitability for vaccine design based on strong binding potential. The potential to cover a large portion of the world's population with these vaccines is substantial—88.5 % for one type and 99.99 % for another. In exploring the molecular docking analyses, we examined a library of compounds from the ZINC database. Among them, we identified twelve compounds with the lowest binding energy. Critical residues in the MAPK1 protein, such as VAL48, LYS63, CYS175, ASP176, LYS160, ALA61, LEU165, TYR45, SER162, ARG33, PRO365, PHE363, ILE40, ASN163, and GLU42, are pivotal for interactions with these compounds. Our result suggests that these compounds could influence the protein's behaviour. Moreover, our docking analyses revealed that the predicted peptides have a strong affinity for the MAPK1 protein. These peptides form stable complexes, indicating their potential as potent inhibitors. This study contributes to the identification of new drug compounds and the screening of their desired properties. These compounds could potentially help reduce the excessive activity of MAPK1, which is linked to Alzheimer's disease.

In this paper, we posit a framework for the investigation of the fixed point problems (FPP) involving an infinite family of k-demicontractive operators and the split common null point problems (SCNPP) in Hilbert spaces. We employ an accelerated variant of the hybrid shrinking projection algorithm for the construction of a common solution associated with the FPP and SCNPP. Theoretical results comprise strong convergence characteristics under suitable sets of constraints as well as numerical results are established for the underlying algorithm. Applications to signal processing as well as various abstract problems are also incorporated.

Context-awareness is a pervasive computing enabling technology that allows context-aware applications to respond to multiple contexts such as activity, location, temperature, and so on. When many users attempt to access the same context-aware application, user conflicts may emerge. This issue is emphasized, and a conflict resolution approach is presented to address it. Although there are other conflict resolution approaches in the literature, the one presented here is unique in that it considers the users’ special cases such as their sickness, examinations, and so on when resolving conflicts. The proposed approach is helpful when several users with different special cases try to access the same context-aware application. To demonstrate the usefulness of the proposed approach, a conflict manager is integrated with the UbiREAL simulated context-aware home environment. The integrated conflict manager resolves conflicts by taking users special cases into account and employing either automated, mediated, or hybrid conflict resolution approaches. The evaluation of the proposed approach demonstrates that users are satisfied with it and that it is critical and essential to employ users’ special cases in detecting and resolving users conflicts.

Abstract In this paper, we compute a common solution of the fixed point problem (FPP) and the generalized split common null point problem (GSCNPP) via the inertial hybrid shrinking approximants in Hilbert spaces. We show that the approximants can be easily adapted to various extensively analyzed theoretical problems in this framework. Finally, we furnish a numerical experiment to analyze the viability of the approximants in comparison with the results presented in (Reich and Tuyen in Rev. R. Acad. Cienc. Exactas Fís. Nat., Ser. A Mat. 114:180, 2020).

This paper provides iterative solutions, via some variants of the extragradient approximants, associated with the pseudomonotone equilibrium problem (EP) and the fixed point problem (FPP) for a finite family of η-demimetric operators in Hilbert spaces. The classical extragradient algorithm is embedded with the inertial extrapolation technique, the parallel hybrid projection technique and the Halpern iterative methods for the variants. The analysis of the approximants is performed under suitable set of constraints and supported with an appropriate numerical experiment for the viability of the approximants.

Many complex systems have been modelled and analyzed as complex networks. These systems are huge and complex in terms of number of interconnecting components. In this research, we have analyzed the co-authorship network of Sindh university authors on science direct to understand the connectivity pattern of authors who published their articles over time. This research has found that the connectivity pattern of the authors is highly heterogonous due to the emergence of hubs in this system. Further, this network has shown highly clustered behavior with small world effect. These findings based on network analysis suggests that the co-authorship system is depending on few authors frequently publishing multiple papers in this network.

Abstract This paper provides iterative construction of a common solution associated with the classes of equilibrium problems (EP) and split convex feasibility problems. In particular, we are interested in the EP defined with respect to the pseudomonotone bifunction, the fixed point problem (FPP) for a finite family of -demicontractive operators, and the split null point problem. From the numerical standpoint, combining various classical iterative algorithms to study two or more abstract problems is a fascinating field of research. We, therefore, propose an iterative algorithm that combines the parallel hybrid extragradient algorithm with the inertial extrapolation technique. The analysis of the proposed algorithm comprises theoretical results concerning strong convergence under a suitable set of constraints and numerical results.

Abstract In this paper, we develop an iterative algorithm whose architecture comprises a modified version of the forward–backward splitting algorithm and the hybrid shrinking projection algorithm. We provide theoretical results concerning weak and strong convergence of the proposed algorithm towards a common solution of the fixed point problem associated to a finite family of demicontractive operators, the split equilibrium problem and the monotone inclusion problem in Hilbert spaces. Moreover, we compute a numerical experiment to show the efficiency of the proposed algorithm. As a consequence, our results improve various existing results in the current literature.

Abstract In this paper, we study a modified extragradient method for computing a common solution to the split equilibrium problem and fixed point problem of a nonexpansive semigroup in real Hilbert spaces. The weak and strong convergence characteristics of the proposed algorithm are investigated by employing suitable control conditions in such a setting of spaces. As a consequence, we provide a simplified analysis of various existing results concerning the extragradient method in the current literature. We also provide a numerical example to strengthen the theoretical results and the applicability of the proposed algorithm.

Abstract Iterative algorithms are widely applied to solve convex optimization problems under a suitable set of constraints. In this paper, we develop an iterative algorithm whose architecture comprises a modified version of the forward-backward splitting algorithm and the hybrid shrinking projection algorithm. We provide theoretical results concerning weak and strong convergence of the proposed algorithm towards a common solution of the monotone inclusion problem and the split mixed equilibrium problem in Hilbert spaces. Moreover, numerical experiments compare favorably the efficiency of the proposed algorithm with the existing algorithms. As a consequence, our results improve various existing results in the current literature.

Due to the rapid growth of small and smart hand-held devices, mobile ad hoc networks (MANets) are becoming very common nowadays. MANets may consist of a number of small hand-held devices having limited resources in terms of memory, battery and processing power. In order to provide services to the users, these devices are capable of communicating with each other through some radio technology, such as WiFi, Bluetooth or Infrared. Since radio channels are inherently vulnerable to various security threats, it requires that devices in MANets must establish a secure association amongst themselves before exchanging any sensitive information or data. The process of establishing a secure channel between two devices is referred to as device pairing or device association. Device pairing do not rely on traditional mechanisms for security due to the impulsive and ad hoc interactions among the devices. Due to this, researchers have proposed many schemes/protocols to deal with this issue; however, the issue of group pairing (i.e. secure association of more than two devices) is less addressed issue in the literature yet. There could be many scenarios (such as confidential office meetings, paring of group of home appliances in smart-homes, etc) of MANets, where secure group communications is desired. Consequently, this research focuses on this issue and proposes a QR (quick response) code based scheme to establish a secure channel between a numbers of devices. The proposed system is implemented and tested on modern hand-held devices and a usability study of the implemented system is also carried out.

Tough gel with extreme temperature tolerance is a class of soft materials having potential applications in the specific fields that require excellent integrated properties under subzero temperature. Herein, physically crosslinked Europium (Eu)-alginate/polyvinyl alcohol (PVA) organohydrogels that do not freeze at far below 0°C, while retention of high stress and stretchability is demonstrated. These organohydrogels are synthesized through displacement of water swollen in polymer networks of hydrogel to cryoprotectants (e.g., ethylene glycol, glycerol, and d-sorbitol). The organohydrogels swollen water-cryoprotectant binary systems can be recovered to their original shapes when be bent, folded and even twisted after being cooled down to a temperature as low as −20 and −45°C, due to lower vapor pressure and ice-inhibition of cryoprotectants. The physical organohydrogels exhibit the maximum stress (5.62 ± 0.41 MPa) and strain (7.63 ± 0.02), which is about 10 and 2 times of their original hydrogel, due to the synergistic effect of multiple hydrogen bonds, coordination bonds and dense polymer networks. Based on these features, such physically crosslinked organohydrogels with extreme toughness and wide temperature tolerance is a promising soft material expanding the applications of gels in more specific and harsh conditions.

Emerging evidence indicates that many microRNAs (miRNAs) are indispensable regulators of osteoblast differentiation and bone formation. However, the role of miRNAs in mechanotransduction of osteoblasts remains to be elucidated. This study aimed to identify a mechanosensitive miRNA that regulates Activin A receptor type I (ACVR1)-induced osteogenic differentiation. After 4 weeks of hindlimb unloading (HLU) suspension of 6-month-old male C57BL/6J mice, femurs and tibias were harvested to extract total bone RNAs. Elevated levels of miR-208a-3p correlated with a lower degree of bone formation in whole-bone samples of HLU mice. However, in vitro overexpression of miR-208a-3p inhibited osteoblast differentiation, whereas silencing of miR-208a-3p by antagomiR-208a-3p promoted expression of osteoblast activity, bone formation marker genes, and matrix mineralization under mechanical unloading condition. Bioinformatics analysis and a luciferase assay revealed that ACVR1 is a target gene of miR-208a-3p that negatively regulates osteoblast differentiation under mechanical unloading environment. Further, this study also demonstrates that in vivo pre-treatment with antagomiR-208a-3p led to an increase in bone formation and trabecular microarchitecture and partly rescued the bone loss caused by mechanical unloading. Collectively, these results suggest that in vivo, inhibition of miRNA-208a-3p by antagomiR-208a-3p may be a potential therapeutic strategy for ameliorating bone loss.

Pervasive devices such as mobile phones and PDAs (Personal Digital Assistants) come with different wireless communication capabilities, for example, WiFi (Wireless Fidelity), Bluetooth, IrDA (Infrared), etc. In order for pervasive devices to interact with each other, they need to have matching (alike) communication capabilities, otherwise such heterogeneous devices would not be able to interact with each other. In this paper we address this issue and propose a system that makes devices with heterogeneous wireless communication capabilities communicate with each other. The proposed system supports adaptation of wireless communication protocols through a proxy, which sits between a client and a server, and supports adaptation of wireless communication protocols. Its functionality involves intercepting a request made by a client with a different wireless communication capability (e.g. Bluetooth) from what the server has (e.g. WiFi), connecting to the server and then sending results back to the client. We have tested the system by implementing a messaging service application and running it on the system. The proxy supports all Bluetooth protocols, i.e. OBEX (Object Exchange), L2CAP (Logical Link Control and Adaptation Protocol), RFCOM (Radio Frequency Communication) and WiFi protocol and can run on (J2MW (Java 2 Micro Edition) enabled mobile phones which support both Bluetooth and WiFi capabilities

WSNs (Wireless Sensor Networks) comprise a large number of small, inexpensive, low power and memory constrained sensing devices (called sensor nodes) that are densely deployed to measure a given physical phenomenon. Since WSNs are commonly deployed in a hostile and unattended environment, it is easy for an adversary to physically capture one or more legitimate sensor nodes, re-program and redeploy them in the network. As a result, the adversary becomes able to deploy several identical copies of physically captured nodes in the network in order to perform illegitimate activities. This type of attack is referred to as Node Replication Attack or Clone Node Attack. By launching node replication attack, an adversary can easily get control on the network which consequently is the biggest threat to confidentiality, integrity and availability of data and services. Thus, detection and prevention of node replication attack in WSNs has become an active area of research and to date more than two dozen schemes have been proposed, which address this issue. In this paper, we present a comprehensive review, classification and comparative analysis of twenty five of these schemes which help to detect and/or prevent node replication attack in WSNs

Prolonged periods of skeletal muscle inactivity or mechanical unloading (bed rest, hindlimb unloading, immobilization, spaceflight and reduced step) can result in a significant loss of musculoskeletal mass, size and strength which ultimately lead to muscle atrophy. With advancement in understanding of the molecular and cellular mechanisms involved in disuse skeletal muscle atrophy, several different signaling pathways have been studied to understand their regulatory role in this process. However, substantial gaps exist in our understanding of the regulatory mechanisms involved, as well as their functional significance. This review aims to update the current state of knowledge and the underlying cellular mechanisms related to skeletal muscle loss during a variety of unloading conditions, both in humans and animals. Recent advancements in understanding of cellular and molecular mechanisms, including IGF1-Akt-mTOR, MuRF1/MAFbx, FOXO, and potential triggers of disuse atrophy, such as calcium overload and ROS overproduction, as well as their role in skeletal muscle protein adaptation to disuse is emphasized. We have also elaborated potential therapeutic countermeasures that have shown promising results in preventing and restoring disuse-induced muscle loss. Finally, identified are the key challenges in this field as well as some future prospectives.

Imidacloprid (IC) is a systemic insecticide related to the tobacco toxin nicotine. IC is a toxic substance frequently used into combat insects, rodents and plants pests and other creatures that can pose problems for agriculture. We, therefore, planned this study to assess risk factors, biochemical and histological alterations associated with hepatotoxicity and nephrotoxicity. Forty-eight adult male albino mice were divided into four groups of 12 animals each. All the animals were given standard synthetic pellet diet. One group served as control, and the other three were served as experimental groups. Decrease in the body weight of the high dose group was observed at 15 mg/kg/day, and no mortality occurred during the treatment period. High dose of imidacloprid caused a significant elevation of serum clinical chemistry parameters, serum glutamic oxaloacetic transaminase (SGOT), serum glutamic pyruvate kinase (SGPT), alkaline phosphatase (ALP) and total bilirubin (TBIL). Histology of liver and kidney indicates hepatotoxicity and nephrotoxicity at a high dose of imidacloprid. Based on the morphological, biochemical and histopathological analysis, it is evident that imidacloprid induced toxicological effects at 15 mg/kg/day to mice. The results of the present study demonstrate that IC had significant effects on body weight, liver functions and kidney (p < 0.05) at a dose of 15 mg/kg body weight. IC treatment 5 and 10 mg/kg/day may be considered as no observed adverse effect level (NOAEL) for mice. It was concluded that IC can cause hepatotoxicity and nephrotoxicity at a dose much lower than the LD50 (131 mg/kg body weight) in mice.

Long noncoding RNAs (lncRNAs), which form a diverse class of RNAs, remain the least understood type of noncoding RNAs in terms of their nature and identification. Emerging evidence has revealed that a small number of newly discovered lncRNAs perform important and complex biological functions such as dosage compensation, chromatin regulation, genomic imprinting, and nuclear organization. However, understanding the wide range of functions of lncRNAs related to various processes of cellular networks remains a great experimental challenge. Structural versatility is critical for RNAs to perform various functions and provides new insights into probing the functions of lncRNAs. In recent years, the computational method of RNA structure prediction has been developed to analyze the structure of lncRNAs. This novel methodology has provided basic but indispensable information for the rapid, large-scale and in-depth research of lncRNAs. This review focuses on mainstream RNA structure prediction methods at the secondary and tertiary levels to offer an additional approach to investigating the functions of lncRNAs.