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This paper explains and applies a numerical technique utilizing the cubic B-spline functions and the mean value theorem (MVT) to solve a general time fractional partial differential equation (FPDE). The MVT for integrals enables us to approximate the time fractional derivatives in an appropriate simple form. We use the cubic B-spline functions to construct the numerical solution and its spatial derivatives. The great advantage of our technique is that it enables us to approximate solutions of many time FPDEs for several choices of F(x, t, u, ux, uxx). Two numerical examples have been included to emphasize the accuracy and efficiency of the method. It is demonstrated that the numerical method is unconditionally stable by employing the Von Neumann method (VNM).

The applications regarding the Internet of Things (IoT) demand lightweight and robust cryptographic solutions to ensure authenticated encryption with associated data (AEAD). Also, the lightweight cryptographic solutions that provide data confidentiality, integrity, and authenticity in a single algorithm are critical. In this regard, the CAESAR and NIST lightweight cryptography (LWC) competitions were concluded in 2019 and recently in 2023, respectively, with Ascon selected as the new LWC standard. Ascon has been evaluated (in the literature) for various characteristics, including some limited efforts on field-programmable gate array (FPGA) devices. A comprehensive evaluation of Ascon’s hardware implementation is still needed. Therefore, this work presents a unified hardware implementation of two variants of Ascon, i.e., Ascon-128 and Ascon-128a, to investigate the performance of the AEAD operation on 7-series FPGA devices up to the post-place and route level. For AEAD computations in our work, an iterative design-level approach with a finite-state machine (FSM)-based dedicated controller is employed. The benchmarking results show that Ascon utilizes 1632, 1497, 1904, and 1756 look-up tables on Virtex, Kintex, Spartan, and Artix 7-series FPGA devices, respectively. The operating frequencies on these devices are 335, 331, 309, and 317 MHz, with power consumptions of 239, 236, 219, and 222 mW. Consequently, our evaluation of Ascon demonstrates higher performance in operating frequency on Kintex-7 FPGA.

We propose a hardware-optimized design that implements a Montgomery Elliptic-curve point multiplication Algorithm over $GF(2^{233})$ using Lopez-Dahab projective coordinates. Moreover, we propose a digit-parallel modular multiplier, which reduces clock cycles and improves throughput. Also, we provided how to use our proposed digit-parallel multiplier for post-quantum cryptography algorithms. In addition, we use the proposed digit-parallel multiplier with the square circuit to implement the Itoh-Tsujii inversion algorithm for modular inversion computation; this permits hardware resource minimization. An efficient finite-state machine controller is implemented for control functionalities. A figure of merit in throughput/area is defined for reasonable comparison to state-of-the-art. We provide implementation results after post-place-and-route on field-programmable gate array devices. On the Virtex-7 device, our design utilizes 3386 slices and requires 7218 clock cycles; it achieves a maximum frequency of 365 MHz and computes one point multiplication in $19.77\mu s$ . The total power consumption of our design is 2027 mW. The calculated values for throughput and figure of merit are 50.58Kbps and 14.93, respectively. Consequently, the implementation results and comparisons reveal our design’s suitability for applications requiring area and throughput-optimized cryptographic implementations.

Abstract In this study, biochar (BC) and hydrochar (HC) composites were synthesized with natural kaolinite clay and their properties, stability, carbon (C) sequestration potential, polycyclic aromatic hydrocarbons (PAHs) toxicity, and impacts on maize germination and growth were explored. Conocarpus waste was pretreated with 0%, 10%, and 20% kaolinite and pyrolyzed to produce BCs (BC, BCK10, and BCK20, respectively), while hydrothermalized to produce HCs (HC, HCK10, and HCK20, respectively). The synthesized materials were characterized using X-ray diffraction, scanning electron microscope analyses, Fourier transform infrared, thermogravimetric analysis, surface area, proximate analyses, and chemical analysis to investigate the distinction in physiochemical and structural characteristics. The BCs showed higher C contents (85.73–92.50%) as compared to HCs (58.81–61.11%). The BCs demonstrated a higher thermal stability, aromaticity, and C sequestration potential than HCs. Kaolinite enriched-BCs showed the highest cation exchange capacity than pristine BC (34.97% higher in BCK10 and 38.04% higher in BCK20 than pristine BC), while surface area was the highest in kaolinite composited HCs (202.8% higher in HCK10 and 190.2% higher in HCK20 than pristine HC). The recalcitrance index (R50) speculated a higher recalcitrance for BC, BCK10, and BCK20 (R50 > 0.7), minimal degradability for HCK10 and HCK20 (0.5

Middle East Respiratory Syndrome (MERS) is a human coronavirus subtype that poses a significant public health concern due to its ability to spread between individuals. This research aims to develop a fractional-order mathematical model to investigate the MERS pandemic and to subsequently develop two numerical methods to solve this model numerically to evaluate and comprehend the analysis results. The fixed-point theorem has been used to demonstrate the existence and uniqueness of the solution to the suggested model. We approximate the solutions of the proposed model using two numerical methods: the mean value theorem and the implicit trapezoidal method. The stability of these numerical methods is studied using various results and primary lemmas. Finally, we compare the results of our methods to demonstrate their efficiency and conduct a numerical simulation of the obtained results. A comparative study based on real data from Riyadh, Saudi Arabia is provided. The study’s conclusions demonstrate the computational efficiency of our approaches in studying nonlinear fractional differential equations that arise in daily life problems.

Kaizen is a very important continuous improvement technique; however, measuring kaizen results/benefits have not been clearly and comprehensively addressed by the literature.

In this paper, we present a highly efficient analytical method that combines the Laplace transform and the residual power series approach to approximate solutions of nonlinear time-fractional partial differential equations (PDEs). First, we derive the analytical method for a general form of fractional partial differential equations. Then, we apply the proposed method to find approximate solutions to the time-fractional coupled Berger equations, the time-fractional coupled Korteweg–de Vries equations and time-fractional Whitham–Broer–Kaup equations. Secondly, we extend the proposed method to solve the two-dimensional time-fractional coupled Navier–Stokes equations. The proposed method is validated through various test problems, measuring quality and efficiency using error norms E2 and E∞, and compared to existing methods.

BackgroundAttenuation of transforming growth factor β by blocking angiotensin II has been shown to reduce emphysema in a murine model. General population studies have demonstrated that the use of angiotensin converting enzyme inhibitors (ACEis) and angiotensin-receptor blockers (ARBs) is associated with reduction of emphysema progression in former smokers and that the use of ACEis is associated with reduction of FEV1 progression in current smokers.Research questionIs use of ACEi and ARB associated with less progression of emphysema and FEV1 decline among individuals with COPD or baseline emphysema?MethodsFormer and current smokers from the Genetic Epidemiology of COPD Study who attended baseline and 5-year follow-up visits, did not change smoking status, and underwent chest CT imaging were included. Adjusted linear mixed models were used to evaluate progression of adjusted lung density (ALD), percent emphysema (%total lung volume

BackgroundSmokers manifest varied phenotypes of pulmonary impairment.Research questionWhich pulmonary phenotypes are associated with coronary artery disease (CAD) in smokers?Study design and methodsWe analyzed data from the University of Pittsburgh COPD Specialized Center for Clinically Oriented Research (SCCOR) cohort (n = 481) and the Genetic Epidemiology of COPD (COPDGene) cohort (n = 2,580). Participants were current and former smokers with > 10 pack-years of tobacco exposure. Data from the two cohorts were analyzed separately because of methodologic differences. Lung hyperinflation was assessed by plethysmography in the SCCOR cohort and by inspiratory and expiratory CT scan lung volumes in the COPDGene cohort. Subclinical CAD was assessed as the coronary artery calcium score, whereas clinical CAD was defined as a self-reported history of CAD or myocardial infarction (MI). Analyses were performed in all smokers and then repeated in those with airflow obstruction (FEV1 to FVC ratio, < 0.70).ResultsPulmonary phenotypes, including airflow limitation, emphysema, lung hyperinflation, diffusion capacity, and radiographic measures of airway remodeling, showed weak to moderate correlations (r < 0.7) with each other. In multivariate models adjusted for pulmonary phenotypes and CAD risk factors, lung hyperinflation was the only phenotype associated with calcium score, history of clinical CAD, or history of MI (per 0.2 higher expiratory and inspiratory CT scan lung volume; coronary calcium: OR, 1.2; 95% CI, 1.1-1.5; P = .02; clinical CAD: OR, 1.6; 95% CI, 1.1-2.3; P = .01; and MI in COPDGene: OR, 1.7; 95% CI, 1.0-2.8; P = .05). FEV1 and emphysema were associated with increased risk of CAD (P < .05) in models adjusted for CAD risk factors; however, these associations were attenuated on adjusting for lung hyperinflation. Results were the same in those with airflow obstruction and were present in both cohorts.InterpretationLung hyperinflation is associated strongly with clinical and subclinical CAD in smokers, including those with airflow obstruction. After lung hyperinflation was accounted for, FEV1 and emphysema no longer were associated with CAD. Subsequent studies should consider measuring lung hyperinflation and examining its mechanistic role in CAD in current and former smokers.

This paper develops two numerical methods for solving a system of fractional differential equations based on hybrid shifted orthonormal Bernstein polynomials with generalized block-pulse functions (HSOBBPFs) and hybrid shifted orthonormal Legendre polynomials with generalized block-pulse functions (HSOLBPFs). Using these hybrid bases and the operational matrices method, the system of fractional differential equations is reduced to a system of algebraic equations. Error analysis is performed and some simulation examples are provided to demonstrate the efficacy of the proposed techniques. The numerical results of the proposed methods are compared to those of the existing numerical methods. These approaches are distinguished by their ability to work on the wide interval 0,a, as well as their high accuracy and rapid convergence, demonstrating the utility of the proposed approaches over other numerical methods.

This article proposes a collocation approach based on a redefined quintic B-spline basis for solving the time-fractional Whitham-Broer-Kaup equations. The presented method involves discretizing the time-fractional derivatives using an L1-approximation scheme and then approximating the spatial derivatives using the redefined quintic B-spline basis. The von Neumann technique has been used to demonstrate that the proposed method is unconditionally stable. The error estimates are discussed and show that the proposed method is third-order convergent. The results demonstrate the potential of the proposed method as a reliable tool for solving fractional differential equations.

This paper investigates the global asymptotic stability problem for a class of Takagi-Sugeno fuzzy Clifford-valued delayed neural networks with impulsive effects and leakage delays using the system decomposition method. By applying Takagi-Sugeno fuzzy theory, we first consider a general form of Takagi-Sugeno fuzzy Clifford-valued delayed neural networks. Then, we decompose the considered -dimensional Clifford-valued systems into -dimensional real-valued systems in order to avoid the inconvenience caused by the non-commutativity of the multiplication of Clifford numbers. By using Lyapunov-Krasovskii functionals and integral inequalities, we derive new sufficient criteria to guarantee the global asymptotic stability for the considered neural networks. Further, the results of this paper are presented in terms of real-valued linear matrix inequalities, which can be directly solved using the MATLAB LMI toolbox. Finally, a numerical example is provided with their simulations to demonstrate the validity of the theoretical analysis.

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year longitudinal chest imaging, spirometry, and molecular data, is a rich resource for relating COPD phenotypes to underlying genetic and molecular mechanisms. In this article, we place COPDGene clustering studies in context with other highly cited COPD clustering studies, and summarize the main COPD subtype findings from COPDGene. First, most manifestations of COPD occur along a continuum, which explains why continuous aspects of COPD or disease axes may be more accurate and reproducible than subtypes identified through clustering methods. Second, continuous COPD-related measures can be used to create subgroups through the use of predictive models to define cut-points, and we review COPDGene research on blood eosinophil count thresholds as a specific example. Third, COPD phenotypes identified or prioritized through machine learning methods have led to novel biological discoveries, including novel emphysema genetic risk variants and systemic inflammatory subtypes of COPD. Fourth, trajectory-based COPD subtyping captures differences in the longitudinal evolution of COPD, addressing a major limitation of clustering analyses that are confounded by disease severity. Ongoing longitudinal characterization of subjects in COPDGene will provide useful insights about the relationship between lung imaging parameters, molecular markers, and COPD progression that will enable the identification of subtypes based on underlying disease processes and distinct patterns of disease progression, with the potential to improve the clinical relevance and reproducibility of COPD subtypes.

Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P

Block ciphers are widely used for securing data and are known for their resistance to various types of attacks. The strength of a block cipher against these attacks often depends on the S-boxes used in the cipher. There are many chaotic map-based techniques in the literature for constructing the dynamic S-Boxes. While chaos-based approaches have certain attractive properties for this purpose, they also have some inherent weaknesses, including finite precision effect, dynamical degradation of chaotic systems, non-uniform distribution, discontinuity in chaotic sequences. These weaknesses can limit the effectiveness of chaotic map-based substitution boxes. In this paper, we propose an innovative approach for constructing dynamic S-boxes using Gaussian distribution-based pseudo-random sequences. The proposed technique overcomes the weaknesses of existing chaos-based S-box techniques by leveraging the strength of pseudo-randomness sequences. However, one of the main drawbacks of using Gaussian distribution-based pseudo-random sequences is the low nonlinearity of the resulting S-boxes. To address this limitation, we introduce the use of genetic algorithms (GA) to optimize the nonlinearity of Gaussian distribution-based S-boxes while preserving a high level of randomness. The proposed technique is evaluated using standard S-box performance criteria, including nonlinearity, bit independence criterion (BIC), linear approximation probability (LP), strict avalanche criterion (SAC), and differential approximation probability (DP). Results demonstrate that the proposed technique achieves a maximum nonlinearity of 112, which is comparable to the ASE algorithm.

Background: The world has been suffering from the Coronavirus Disease-2019 (COVID-19) pandemic since the end of 2019. The COVID-19-infected patients differ in the severity of the infection and the treatment response. Several studies have been conducted to explore the factors that affect the severity of COVID-19 infection. One of these factors is the polymorphism of the angiotensin converting enzyme 2 (ACE-2) and the type 2 transmembrane serine protease (TMPRSS2) genes since these two proteins have a role in the entry of the virus into the cell. Also, the ACE-1 regulates the ACE-2 expression, so it is speculated to influence the COVID-19 severity.Objective: This study investigates the relationship between the ACE-1, ACE-2, and TMPRSS2 genes single nucleotide polymorphism (SNPs) and the COVID-19 disease severity, treatment response, need for hospitalization, and ICU admission in Egyptian patients.Patients and Methods: The current study is an observational prospective, cohort study, in which 109 total COVID-19 patients and 20 healthy volunteers were enrolled. Of those 109 patients, 51 patients were infected with the non-severe disease and were treated in an outpatient setting, and 58 suffered from severe disease and required hospitalization and were admitted to the ICU. All 109 COVID-19 patients received the treatment according to the Egyptian treatment protocol.Results: Genotypes and allele frequencies among severe and non-severe patients were determined for ACE-1 rs4343, TMPRSS2 rs12329760, and ACE-2 rs908004. The GG genotype and the wild allele of the ACE-2 rs908004 and the mutant allele of the ACE-1 rs4343 were significantly more predominant in severe patients. In contrast, no significant association existed between the TMPRSS2 rs12329760 genotypes or alleles and the disease severity.Conclusion: The results of this study show that the ACE-1 and ACE-2 SNPs can be used as severity predictors for COVID-19 infection since also they have an effect on length of hospitalization.

Abstract Sources and levels of heavy metals (HMs) in soil and dust of urban and suburban areas in Riyadh (industrial city) and Mahad AD’Dahab (mining area) cities in Saudi Arabia were reported in this study. Additionally, the concentrations of HMs in different soil particle size fractions (> 250, 63–250 and 2). The hazard index values of dust and soil ( 1, suggesting non-carcinogenic risk. Therefore, the dust and soil samples from the mined area of Mahad AD’Dahab had a higher pollution levels, as well as ecological and human health risks than those from Riyadh. Hence, the pollution of such residential environments with HMs (especially Cd, Cu, Zn, and Pb) needs to be monitored.

Middle East Respiratory Syndrome (MERS) is a human coronavirus subtype that poses a significant public health concern due to its ability to spread between individuals. This research aims to develop a fractional-order mathematical model to investigate the MERS pandemic and to subsequently develop two numerical methods to solve this model numerically to evaluate and comprehend the analysis results. The fixed-point theorem has been used to demonstrate the existence and uniqueness of the solution to the suggested model. We approximate the solutions of the proposed model using two numerical methods: the mean value theorem and the implicit trapezoidal method. The stability of these numerical methods is studied using various results and primary lemmas. Finally, we compare the results of our methods to demonstrate their efficiency and conduct a numerical simulation of the obtained results. A comparative study based on real data from Riyadh, Saudi Arabia is provided. The study's conclusions demonstrate the computational efficiency of our approaches in studying nonlinear fractional differential equations that arise in daily life problems. [ABSTRACT FROM AUTHOR]

This article proposes a flexible hardware accelerator optimized from a throughput and area point of view for the computationally intensive part of elliptic curve cryptography. The target binary fields, defined by the National Institute of Standards and Technology, are GF(2163), GF(2233), GF(2283), GF(2409), and GF(2571). For the optimization of throughput, the proposed accelerator employs a digit-parallel multiplier. The size of the digit is 41 bits. The proposed accelerator has reused the multiplication and squaring circuit for area optimization to compute modular inversions. Flexibility is included using three additional buffers on top of the proposed accelerator architecture to load different input parameters. Finally, a dedicated controller is used to optimize control signal handling. The architecture is modeled using Verilog and implemented up to the post-place-and-route level on a Xilinx Virtex-7 field-programmable gate array. The area utilization of our accelerator in slices is 1479, 1998, 2573, 3271, and 4469 for m=163 to 571. The time needed to perform one-point multiplication is 7.15, 10.60, 13.26, 20.96, and 30.42 μs. Similarly, the throughput over area figures for the same key lengths are 94.56, 47.21, 29.30, 14.58, and 7.35. Consequently, achieved results and a comprehensive performance comparison show the suitability of the proposed design for constrained environments that demand throughput/area-efficient implementations.

In recent years, there has been a lot of research interest in analyzing chaotic constructions and their associated cryptographic structures. Compared with the essential combination of encryption and signature, the signcryption scheme has a more realistic solution for achieving message confidentiality and authentication simultaneously. However, the security of a signcryption scheme is questionable when deployed in modern safety-critical systems, especially as billions of sensitive user information is transmitted over open communication channels. In order to address this problem, a lightweight, provably secure certificateless technique that uses Fractional Chaotic Maps (FCM) for group-oriented signcryption (CGST) is proposed. The main feature of the CGST-FCM technique is that any group signcrypter may encrypt data/information with the group manager (GM) and have it sent to the verifier seamlessly. This implies the legitimacy of the signcrypted information/data is verifiable using the public conditions of the group, but they cannot link it to the conforming signcrypter. In this scenario, valid signcrypted information/data cannot be produced by the GM or any signcrypter in that category alone. However, the GM is allowed to reveal the identity of the signcrypter when there is a legal conflict to restrict repudiation of the signature. Generally, the CGST-FCM technique is protected from the indistinguishably chosen ciphertext attack (IND-CCA). Additionally, the computationally difficult Diffie-Hellman (DH) problems have been used to build unlinkability, untraceability, unforgeability, and robustness of the projected CGST-FCM scheme. Finally, the security investigation of the presented CGST-FCM technique shows appreciable consistency and high efficiency when applied in real-time security applications.

BACKGROUND:Eosinophilic airway inflammation in patients with chronic obstructive pulmonary disease (COPD) is associated with exacerbations and responsivity to steroids, suggesting potential shared mechanisms with eosinophilic asthma. However, there is no consistent blood eosinophil count that has been used to define the increased exacerbation risk. OBJECTIVE:We sought to investigate blood eosinophil counts associated with exacerbation risk in patients with COPD. METHODS:Blood eosinophil counts and exacerbation risk were analyzed in patients with moderate-to-severe COPD by using 2 independent studies of former and current smokers with longitudinal data. The Genetic Epidemiology of COPD (COPDGene) study was analyzed for discovery (n = 1,553), and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study was analyzed for validation (n = 1,895). A subset of the ECLIPSE study subjects were used to assess the stability of blood eosinophil counts over time. RESULTS:COPD exacerbation risk increased with higher eosinophil counts. An eosinophil count threshold of 300 cells/μL or greater showed adjusted incidence rate ratios for exacerbations of 1.32 in the COPDGene study (95% CI, 1.10-1.63). The cutoff of 300 cells/μL or greater was validated for prospective risk of exacerbation in the ECLIPSE study, with adjusted incidence rate ratios of 1.22 (95% CI, 1.06-1.41) using 3-year follow-up data. Stratified analysis confirmed that the increased exacerbation risk associated with an eosinophil count of 300 cells/μL or greater was driven by subjects with a history of frequent exacerbations in both the COPDGene and ECLIPSE studies. CONCLUSIONS:Patients with moderate-to-severe COPD and blood eosinophil counts of 300 cells/μL or greater had an increased risk exacerbations in the COPDGene study, which was prospectively validated in the ECLIPSE study.

In this paper, we show how to approximate the solution to the generalized time-fractional Huxley-Burgers’ equation by a numerical method based on the cubic B-spline collocation method and the mean value theorem for integrals. We use the mean value theorem for integrals to replace the time-fractional derivative with a suitable approximation. The approximate solution is constructed by the cubic B-spline. The stability of the proposed method is discussed by applying the von Neumann technique. The proposed method is shown to be conditionally stable. Several numerical examples are introduced to show the efficiency and accuracy of the method.

Abstract The internet has become one of the main sources of news spread as it unleashed the information dissemination space, where the news websites express opinions on entities while also reporting on recent or unusual security risks. Recently, many research studies have focused on sentimental reflection on the views and impressions of people utilising natural language processing and analytical linguistics. Therefore, we have collected corpus from popular Arabic websites that publish articles related to recent security issues, and we provide light weight preprocessing techniques where data is term matrix is transformed. We also present an intensive lexical‐driven data analysis with visualised data views, as our topic modelling technique can effectively extract significant topics from all the collected text from different websites. Our experiments validate the k‐means clustering algorithm with and without the latent Dirichlet allocation topic modelling method, and we adopted various validation techniques to measure the topic clustering internally and externally. As shown in the experiments' results, our proposed combined method has a high round index rate of 87.2%, with a large number of topics and clusters.

Abstract In this paper, we present a new structure of the n-dimensional trigonometric cubic B-spline collocation algorithm, which we show in three different formats: one-, two-, and three-dimensional. These constructs are critical for solving mathematical models in different fields. We illustrate the efficiency and accuracy of the proposed method by its application to a few two- and three-dimensional test problems. We use other numerical methods available in the literature to make comparisons.

Abstract This paper proposes two numerical approaches for solving the coupled nonlinear time-fractional Burgers’ equations with initial or boundary conditions on the interval [ 0 , L ] $[0, L]$ . The first method is the non-polynomial B-spline method based on L1-approximation and the finite difference approximations for spatial derivatives. The method has been shown to be unconditionally stable by using the Von-Neumann technique. The second method is the shifted Jacobi spectral collocation method based on an operational matrix of fractional derivatives. The proposed algorithms’ main feature is that when solving the original problem it is converted into a nonlinear system of algebraic equations. The efficiency of these methods is demonstrated by applying several examples in time-fractional coupled Burgers equations. The error norms and figures show the effectiveness and reasonable accuracy of the proposed methods.

Abstract Background Microalgae and nanoparticles are currently considered promising tools for numerous agricultural and biotechnological applications. The green microalga Chlorella sp. MF1 and its biosynthesized silver nanoparticles (AgNPs) were used in this study as biofortification agents to enhance glucosinolate and kaempferol levels in Eruca sativa. UV–visible spectroscopy, XRD, FTIR and TEM were comprehensively used for characterizing Chlorella-based AgNPs. Results The biosynthesized AgNPs were found to be spherical in shape, with size ranging from 1.45 to 5.08 nm. According to FTIR measurements, silver ions were reduced to AgNPs by functional groups such as amide, hydroxyl and carboxylate. Different experimental treatments were conducted, including either soaking seeds of E. sativa or foliar spray with various concentrations of Chlorella suspension (1, 2, 3 and 4 g L−1) and AgNPs (5, 10, 20 and 40 mg L−1). Expression levels of five key genes in the biosynthetic pathway of glucosinolates (MAM1, SUR1, MYB34 and MYB51) and kaempferol (CHS) were assessed using qRT-PCR. The results indicated an upregulation in the gene expression levels in all treatments compared to control, recording the highest level at 40 mg L−1 AgNPs and 4 g L−1 Chlorella suspension. In addition, high glucosinolates and kaempferol content was detected in plants whose leaves were sprayed with AgNPs and Chlorella suspension (40 mg L−1 and 4 g L−1) based on HPLC analysis. Sequence analysis of amplified CHS fragments from E. sativa plants treated with AgNPs (40 mg L−1) showed high sequence similarity to A. thaliana CHS gene. However, there were several CHS regions with sequence polymorphism (SNPs and Indels) in foliar sprayed plants. Conclusions Results of this study evidenced that the application of AgNPs and Chlorella suspension increased glucosinolates and kaempferol content in E. sativa through upregulation of key genes in their biosynthetic pathway.

This paper proposes a novel hardware design for a compact crypto processor devoted to elliptic-curve point multiplication over GF(2233). We focus on minimizing hardware usage, which we obtain using an iterative bit–serial finite field modular multiplier for polynomial coefficient multiplication. The same multiplier is also used for modular squares and inversion computations, further optimizing the hardware footprint. Our design offers flexibility by permitting users to load different curve parameters and secret keys while keeping a low-area hardware design. To efficiently generate the control signals, we utilize a finite-state-machine-based controller. We have implemented the proposed crypto processor on Virtex-6 and Virtex-7 FPGA devices, and we have evaluated its performance at clock frequencies of 100, 50, and 10 MHz. Specifically, for one point multiplication computation on Virtex-7 FPGA, our crypto processor uses 391 slices, attains a maximum frequency of 161 MHz, has a latency of 4.45 ms, and consumes 77 mW of power. These results, along with a comparison to state-of-the-art designs, clearly demonstrate the practicality of our crypto processor for applications requiring efficient and compact cryptographic computations.

In this paper, we present a highly efficient analytical method that combines the Laplace transform and the residual power series approach to approximate solutions of nonlinear time-fractional partial differential equations (PDEs). First, we derive the analytical method for a general form of fractional partial differential equations. Then, we apply the proposed method to find approximate solutions to the time-fractional coupled Berger equations, the time-fractional coupled Korteweg–de Vries equations and time-fractional Whitham–Broer–Kaup equations. Secondly, we extend the proposed method to solve the two-dimensional time-fractional coupled Navier–Stokes equations. The proposed method is validated through various test problems, measuring quality and efficiency using error norms E 2 and E ∞ , and compared to existing methods. [ABSTRACT FROM AUTHOR]

Many encryption algorithms are designed to decrease the probability of cyberattacks by assuring data security as well as system and participant authentication. However, in the development of computer resources cryptanalytical techniques have been developed and performed competitively in information security with good results. In this paper, we reported security flaws in the recently offered encryption technique based on a chaotic map for Internet of Health Things (IoHT) security. The scheme was based on a new chaotic map, modified Mandelbrot set, and conditional shift algorithm asserting the encryption algorithm is secure. We have performed some cryptographic attacks to retrieve the key from the understudy cryptosystem. The key was retrieved in little computation by using a chosen-plaintext attack and one known plaintext ciphertext pair. The minimum execution time of performed attacks indicates the vulnerability of the diffusion-based encryption algorithm. To enhance the security of the understudy cryptographic algorithm, we have also suggested certain improvements.

The fifth-generation (5G) wireless network is commercialized. The need to integrate massive devices in 5G and wireless sensor networks (WSN) to provide several convenient services for network users becomes imperative. However, there are growing concerns that 5G-WSNs pose new security threats to sensitive user information. User authentication and key agreement have been provided for secure end-to-end communication. However, stricter security techniques are required as billions of massive devices are being networked to collect and process complex user data in real-time. Therefore, anonymous authentication and authorization are highly coveted for privacy preservation and prevention of unlawful exploitation of user data. However, guaranteeing data integrity, authentication, and non-repudiation require special-purpose identity-based signature techniques that are quite difficult to design in practice. In order to address this problem, this paper proposes a lightweight, provably secure identity-based online/offline signature technique (IBOOST) and its extension for massive devices in 5G-WSNs using fractional chaotic maps. The IBOOST scheme achieves multi-time use of offline storage at a lower processing time. Therefore, the signer can reuse the offline pre-stored information in a polynomial time. This makes our IBOOST superior to the existing online/offline signature techniques that allow only a single signature. Additionally, the new technique enables the pre-registration process with a secret key, and no secret key is required in the offline stage. Also, the proposed IBOOST proves to be secure in the random oracle unforgeability under the chosen message attack (UF-IBS-CMA). Finally, the IBOOST and its enhanced version (A-IBOOST) give the lowest computational costs compared to several contending techniques. Therefore, the proposed IBOOST shows superior security and performance with better computational overhead than the preliminary techniques.

Transmission of multimedia data such as images, videos, and audio over the Internet is risky due to cyberattacks. To overcome the security issues, several encryption schemes are proposed over the last few decades which also possess few vulnerabilities such as time inefficiency and weak security. In this research, to provide the highest level of security to the digital data, chaos is incorporated for the scrambling of rows and columns of the plaintext image. Further, a noisy image is generated based on the chaotic logistic map and the suitable initial conditions which are selected based on the analysis performed. For the reduction of the encryption computational time, a Discrete Wavelet Transform (DWT) is used in which only low-frequency bands are encrypted because most of the plaintext information lies in such frequency bands. To gauge the performance of the proposed encryption scheme, several security tests such as entropy, correlation, energy, peak signal to noise ratio, mean square error, keyspace, and key sensitivity analysis, noise-resistant, and cropping attack analyses are performed. From the cropping and noise attack analysis, we have found that the proposed encryption algorithm can decrypt the plaintext image with negligible loss of information but the content of the plaintext image can be visualized.

In this article, we present an encryption technique that can encrypt any digital data. The proposed scheme basically depends on a substitution-permutation network. Two separate bijective maps are used in the proposed algorithm. Firstly, the substitution boxes are used to perform the substitution process. This technique uses elliptic curves (ECs) to create several substitution boxes with good cryptographic properties. The generated substitution boxes are utilized to replace the arrange data that produces the most uncertainty in the plain image data. Further, we used the permutation process to generate strong randomness in the proposed technique. For the evaluation of the stability of the proposed algorithm; nonlinearity, linear approximation probability, bit independence criterion, strict avalanche criterion and differential approximation probability were performed on the substitution boxes. Differential attacks (Number of Changing Pixel Rate (NPCR), Uniform Average Change Intensity (UACI)) and statistical tests (Entropy, Correlation) were performed on the encrypted images to check their resistance against different attacks. The execution and image analysis reveals that the proposed scheme attains good encryption results while requiring minimal computing ability and has efficient potential in real-time image encryption applications.

The Dromedary camel (Camelus dromedaries) is an important species because of its ability to produce good quality meat, milk, and fibers under harsh environmental conditions. Camels are also crucial for transportation, racing, and as draft animals in agriculture. Therefore, dromedary camels play a critical role in the economy for millions of people living in the arid part of the world. The inherent capability of camels to produce meat and milk is highly correlated with their reproductive performance. Compared with other domestic species, the reproductive efficiency in camelids is low. Although recent reproductive technologies such as in vitro fertilization (IVF) and somatic cell nuclear transfer (SCNT) have been successfully applied to camelids and the birth of live offspring following these technologies has been reported; in vitro embryo production (IVP) has lagged in this species. The development of the IVP system for dromedary camels may be a useful tool for the genetic improvement of this species. IVP in farm animals includes three main steps; in vitro maturation (IVM) of an oocyte, IVF of a matured oocyte, and in vitro culture (IVC) of fertilized oocyte up to the blastocyst stage. This review aims to summarize various factors that influence oocyte quality, IVM, and in vitro embryo development in dromedary camel.

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving cryptosystem is necessary. Such a solution relies on chaos encryption algorithms over standard cryptographic methods that possess multistage encryption levels, including high speed, high security, low compute overheads, and procedural power, among other characteristics. In this work, a secure image encryption scheme is proposed using linear feedback shift register (LFSR) and chaos-based quantum chaotic map. The focus of the scheme is mainly dependent on the secret keys from the input of the algorithm. The threat landscape, the statistical test analysis, along critical comparisons with other schemes indicate that the presented algorithm is significantly secure and is resistant to a wide range of different attacks such as differential and statistical attacks. The proposed method has sufficiently higher sensitivity and security when compared to existing encryption algorithms. Several security parameters validated the security of proposed work such as correlation coefficient analyses among the neighboring pixels, entropy, the number of pixels change rate (NPCR), unified average change intensity (UACI), mean square error (MSE), brute force, key sensitivity, and peak signal to noise ratio (PSNR) analyses. The randomness of the ciphers produced by the proposed technique is also passed through NIST-800-22. The results of NIST indicate that the ciphers are highly random and do not produce any type of periodicity or pattern.

This article presents a throughput/area accelerator for elliptic-curve point multiplication over GF(2571). To optimize the throughput, we proposed an efficient hardware accelerator architecture for a fully recursive Karatsuba multiplier to perform polynomial multiplications in one clock cycle. To minimize the hardware resources, we have utilized the proposed Karatsuba multiplier for modular square implementations. Moreover, the Itoh-Tsujii algorithm for modular inverse computation is operated using multiplier resources. These strategies permit us to reduce the hardware resources of our implemented accelerator over a large field size of 571 bits. A controller is implemented to provide control functionalities. Our throughput/area accelerator is implemented in Verilog HDL using the Vivado IDE tool. The results after the place-and-route are given on Xilinx Virtex-6 and Virtex-7 devices. The utilized slices on Virtex-6 and Virtex-7 devices are 6107 and 5683, respectively. For the same FPGA devices, our accelerator can operate at a maximum of 319 MHz and 361 MHz. The latency values for Virtex-6 and Virtex-7 devices are 28.73 μs and 25.38 μs. The comparison to the state-of-the-art shows that the proposed architecture outperforms in throughput/area values. Thus, our accelerator architecture is suitable for cryptographic applications that demand a throughput and area simultaneously.

This article presents a latency-optimized implementation of the SIMECK lightweight block cipher on a field-programmable-gate-array (FPGA) platform with a block and key lengths of 32 and 64 bits. The critical features of our architecture include parallelism, pipelining, and a dedicated controller. Parallelism splits the digits of the key and data blocks into smaller segments. Then, we use each segmented key and data block in parallel for encryption and decryption computations. Splitting key and data blocks helps reduce the required clock cycles. A two-stage pipelining is used to shorten the critical path and to improve the clock frequency. A dedicated controller is implemented to provide control functionalities. For the performance evaluation of our design, we report implementation results for two different cases on Xilinx 7-series FPGA devices. For our case one, the proposed architecture can operate on 382, 379, and 388 MHz frequencies for Kintex-7, Virtex-7, and Artix-7 devices. On the same Kintex-7, Virtex-7, and Artix-7 devices, the utilized Slices are 49, 51, and 50. For one encryption and decryption computation, our design takes 16 clock cycles. The minimum power consumption is 172 mW on the Kintex-7 device. For the second case, we targeted the same circuit frequency of 50 MHz for synthesis on Kintex-7, Virtex-7, and Artix-7 devices. With minimum hardware resource utilization (51 Slices), the least consumed power of 13.203 mW is obtained for the Kintex-7 device. For proof-of-concept, the proposed SIMECK design is validated on the NEXYS 4 FPGA with the Artix-7 device. Consequently, the implementation results reveal that the proposed architecture is suitable for many resource-constrained cryptographic applications.