Differential Technique Research Articles

In-Plane Vibrations of Deep Sandwich Arches with Different End Conditions Based on a Logarithmic Shear Deformation Theory

This paper deals with the vibrational frequencies of deep sandwich arches to enhance their application domain and possibly use them for energy harvesting. The circular arch with porous nanocomposite core and titanium alloy face sheets having different end conditions is numerically analyzed. The middle core of the sandwich arch is made of a six-layered porous aluminum reinforced with graphene nanoplatelets. The kinematic equations are formulated in this study based on the higher-order shear deformation theory using a logarithmic function of radius. The effective properties of the nanocomposite media are modeled by employing the Halpin–Tsai modified rule. The equations of motion are determined by applying the principle of virtual displacement. The partial differential equations are reduced using the generalized differential quadrature technique to solving an algebraic eigenvalue problem. Novel numerical results are given to show the effects of geometrical parameters, material properties, and boundary conditions on the vibrations of deep sandwich arch.

On two new modified tawn copulas

At its core, copula theory focuses on constructing a copula function, which characterizes the structure of dependence between random variables. In particular, the creation of extreme value copulas is crucial because they allow accurate modeling of extreme dependence that traditional copulas can ignore. In this article, we propose theoretical developments on this subject by proposing two new extreme value copulas. They aim to extend the functionalities of the so-called Tawn copula. This is of interest because the Tawn copula is known to be a powerful tool in modeling joint distributions, particularly in capturing asymmetric and upper tail dependences, making it valuable for analyzing extreme events and tail risk. The proposed copulas are designed to go beyond these attractive features. On the mathematical side, they are derived from new Pickands dependence functions; one modifies the Pickands dependence function of the Tawn copula by using a polynomial-exponential function, and the other does the same but by introducing a power function. The proofs are based on diverse differentiation, arrangement, and inequality techniques. Overall, the created copulas are attractive because (i) they possess modulable levels of asymmetry, (ii) they depend on several tuning parameters, making them very flexible in terms of upper tail dependence in particular, and (iii) they benefit from interesting correlation ranges of values. Several figures and value tables support the theoretical findings.

Privacy-preserving cloud-based secure digital locker with differential privacy-based deep learning technique

Privacy-preserving cloud-based secure digital locker with differential privacy-based deep learning technique

Asymptotic numerical method for hyperelasticity and elastoplasticity: a review

The literature about the asymptotic numerical method (ANM) is reviewed in this paper as well as its application to hyperelasticity and elastoplasticity. ANM is a generic continuation method based on the computation of Taylor series for solving nonlinear partial differential equations. Modern techniques of high-order differentiation provide simple tools for computing these power series, the corresponding algorithms for finite strain elasticity and elastoplasticity being summarized here. Taylor series is not only a computation tool, but it contains also useful information about the structure of the considered solution curve. The paper ends with a short historical account about the development of this numerical method.

Challenges in Measurement of Low-Value ESL and ESR of High-Performance PFN Capacitors for Klystron Modulator

In the high voltage line type pulse modulators, Pulse Forming Network (PFN) capacitors are one of the important components. These capacitors operate at peak kilo ampere current range and at repetition rate in the range of a few hundred hertz. The performance of these capacitors is critical w.r.t. overall system performance, and they are required to operate at high power density and low losses with high reliability. The Equivalent Series Inductance (ESL) and Equivalent Series Resistance (ESR) are two critical parameters that affect the performance of these capacitors. PFN modulator demands a capacitor of very low ESL and ESR for reliable operation and generation of high-voltage pulses. Higher ESR value adversely affects the performance of the capacitor by raising its temperature and thus deteriorating its life. ESL value does not directly affect life, but it affects the quality of high voltage pulse. In RRCAT, the PFN capacitors purchased from Indian manufacturers were showing high-temperature rise and failures. Therefore, new capacitors were designed to have lower ESL and ESR values. Measurement of ESL and ESR is important to evaluate the performance of the capacitors. The low value of these parameters makes their measurement a challenging task and requires special techniques. For low values of ESL and ESR (less than 100 mΩ) measurement, a differential measurement technique was used in which modification and different layouts were explored to improve the repetitive accuracy of the measurements. The differential ESR and ESL measurement techniques with more emphasis on the low-value ESR measurement will be discussed in the paper.

Novel differential power processing technique for uneven partial shading mitigation in PV systems

Photovoltaic (PV) system output power greatly depends on environmental operating conditions. Partial shaded condition (PSC) operates PV string under mismatch. PV module mismatch has been one of the major causes for reduced amount of output power. Maximizing the amount of energy extraction from PV system under mismatch greatly influenced by conversion efficiency as well as the mismatch mitigation topology used. Differential power processing (DPP) is one of the advanced techniques to deal with mismatch conditions and enhance power output from a PV system. In this paper hybrid modular DPP topology is presented. The proposed technique mitigates the effect of mismatches at submodule and enhance power extraction from PV string. Since in majority shading on a PV module is nonuniform. The conversion efficiency of module level DPP shading mitigation techniques enhanced using submodule level DPP architecture. To demonstrate its applicability simulation study is carried out in MATLAB Simulink and results are compared with traditional bypass method and module level DPP. Simulation results showed the reduction in mismatch loss and improvement in efficiency and power output.

Quasi-Periodic Traveling Waves on an Infinitely Deep Perfect Fluid Under Gravity

We consider the gravity water waves system with a periodic one-dimensional interface in infinite depth and we establish the existence and the linear stability of small amplitude, quasi-periodic in time, traveling waves. This provides the first existence result of quasi-periodic water waves solutions bifurcating from a completely resonant elliptic fixed point. The proof is based on a Nash–Moser scheme, Birkhoff normal form methods and pseudo differential calculus techniques. We deal with the combined problems of small divisors and the fully-nonlinear nature of the equations. The lack of parameters, like the capillarity or the depth of the ocean, demands a refined nonlinear bifurcation analysis involving several nontrivial resonant wave interactions, as the well-known “Benjamin-Feir resonances”. We develop a novel normal form approach to deal with that. Moreover, by making full use of the Hamiltonian structure, we are able to provide the existence of a wide class of solutions which are free from restrictions of parity in the time and space variables.

CXCL10/IgG1 Axis in Multiple Sclerosis as a Potential Predictive Biomarker of Disease Activity.

Multiple sclerosis (MS) is a heterogeneous disease, and its course is difficult to predict. Prediction models can be established by measuring intrathecally synthesized proteins involved in inflammation, glial activation, and CNS injury. To determine how these intrathecal proteins relate to the short-term, i.e., 12 months, disease activity in relapsing-remitting MS (RRMS), we measured the intrathecal synthesis of 46 inflammatory mediators and 14 CNS injury or glial activation markers in matched serum and CSF samples from 47 patients with MS (pwMS), i.e., 23 RRMS and 24 clinically isolated syndrome (CIS), undergoing diagnostic lumbar puncture. Subsequently, all pwMS were followed for ≥12 months in a retrospective follow-up study and ultimately classified into "active", i.e., developing clinical and/or radiologic disease activity, n = 18) or "nonactive", i.e., not having disease activity, n = 29. Disease activity in patients with CIS corresponded to conversion to RRMS. Thus, patients with CIS were subclassified as "converters" or "nonconverters" based on their conversion status at the end of a 12-month follow-up. Twenty-seven patients with noninflammatory neurologic diseases were included as negative controls. Data were subjected to differential expression analysis and modeling techniques to define the connectivity arrangement (network) between neuroinflammation and CNS injury relevant to short-term disease activity in RRMS. Lower age and/or higher CXCL13 levels positively distinguished active/converting vs nonactive/nonconverting patients. Network analysis significantly improved the prediction of short-term disease activity because active/converting patients featured a stronger positive connection between IgG1 and CXCL10. Accordingly, analysis of disease activity-free survival demonstrated that pwMS, both RRMS and CIS, with a lower or negative IgG1-CXCL10 correlation, have a higher probability of activity-free survival than the patients with a significant correlation (p < 0.0001, HR ≥ 2.87). Findings indicate that a significant IgG1-CXCL10 positive correlation predicts the risk of short-term disease activity in patients with RRMS and CIS. Thus, the present results can be used to develop a predictive model for MS activity and conversion to RRMS.

Differential Fault and Algebraic Equation Combined Analysis on PICO

In modern information technology, research on block cipher security is imperative. Concerning the ultra lightweight block cipher PICO, there has been only one study focused on recovering its complete master key, with a large search space of 264, and no fault analysis yet. This paper proposes a new fault analysis approach, combining differential fault and algebraic equation techniques. It achieved the recovery of PICO’s entire master key with 40 faults in an average time of 0.57 h. S-box decomposition was utilized to optimize our approach, reducing the time by a remarkable 75.83% under the identical 40-fault condition. Furthermore, PICO’s complete master key could be recovered with 28 faults in an average time of 0.78 h, indicating a significant 237 reduction in its search space compared to the previous study. This marks the first fault analysis on PICO. Compared to conventional fault analysis methods DFA (differential fault analysis) and AFA (algebraic fault analysis), our approach outperforms in recovering PICO’s entire master key, highlighting the cruciality of key expansion complexity in block cipher security. Therefore, our approach could serve to recover master keys of block ciphers with comparably complicated key expansions, and production of more secure block ciphers could result.

DFT and electrochemical determination of Hg2+ and Pb2+ in water using polyaniline–quinoxaline composite modified GCE electrode

In this study, we designed and synthesized a new class of donor–acceptor conjugated polymers containing the polyaniline-quinoxaline [Acenaptho [1, 2 -b] quinoxalin-9-amine] (PAni-QUA) composite, and we subsequently utilized it as an electrochemical sensor to detect Hg2+ and Pb2+ ions with good selectivity and sensitivity. Energy dispersive X-ray analysis spectroscopy (EDAX), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), and UV–Vis spectroscopy (UV–Vis) were employed to analyze the structural and morphological characteristics of the resulting composite. The electrochemical characteristics of the electrode modifiers were analyzed using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Several sensitivity-influencing factors, including chemical and electrochemical parameters like pH and the impact of the supporting electrolyte medium, were also identified to improve the efficiency of the developed sensor. In the presence of different hazardous metal ion species, the interference ability of the proposed sensor was also examined. They were also used to conduct individual and simultaneous sensing studies of various metal ions in different supportive electrolyte media utilizing the differential pulse voltammetry technique (DPV). The PAni-QUA composite modified GCE sensor shows remarkable selectivity and sensitivity towards Hg2+ and Pb2+ ions over the other heavy metal ions in 1 to 20 µM ranges, respectively. The detection limits (3σ/m) were 1.28 nM and 5.91 nM for Hg2+ and Pb2+ ions. Density Functional Theory (DFT) was used in the present study to accomplish the adsorption mechanism of the suggested sensors. The DFT calculation demonstrated that the PAni-QUA composite was formed with a lower band gap energy than QUA and DD PAni. These results showed that the suggested sensor (PAni-QUA) had the lowest detection limit in the acetate buffer medium compared to the specified electrolyte media. Based on these findings, it is possible to use this technology to identify harmful metal ions (Hg2+ and Pb2+) with high sensitivity in real water samples.

Portfolio-consumption choice problem with voluntary retirement and consumption constraints

We study the investment–consumption choice problem with voluntary retirement and upside/downside consumption constraints in infinite horizon, which can be formulated as a two-phase mixed stochastic control problem including stopping time coupled with controls. By verification theorem, we show the strong solution of a fully nonlinear differential variational inequality, satisfying some special properties, is the value function of this problem. Then we eliminate the nonlinearity through Legendre transformation, and obtain the closed-form formulas of the optimal investment–consumption feedback strategy, the optimal retirement strategy and the value function by solving the dual equation. Since the introduction of consumption constraints, these formulas are both segmented and semi-explicit, and bring certain difficulties to the analysis of the properties of the optimal strategies and the value function. The regularity of the feedback strategy and the value function are obtained, as well as their monotonicity or non-monotonicity with respect to various parameters are discussed by some stochastic analysis methods and differential equation techniques.

Investigations on magnesium ion conducting gellan gum-based biopolymer blend electrolytes for energy storage applications

The economical and ecological polymer electrolytes are essential for energy storage devices. The key problem we are trying to resolve is how to improve ionic conductivity and safety in polymer electrolytes, which are essential for energy storage devices to operate effectively. We have prepared biopolymer blend electrolytes with different concentrations of magnesium chloride (MgCl2) by solution casting technique and the prepared electrolytes are investigated. Increase of amorphous nature of the polymer membranes is confirmed by X-ray diffraction analysis. Fourier transform infrared (FTIR) spectroscopy used to define complex formation between salt and polymers. Thermal properties of the electrolytes are confirmed by differential scanning calorimetry technique. The higher ionic conductivity of 1.04 × 10−5 S/cm has been achieved for 8 wt.% MgCl2 mixed gellan gum: polyvinyl alcohol (PVA) polymer blend at the room temperature. The present work highlights the preparation and characterization of gellan gum: PVA: MgCl2 polymer blend electrolytes with enhanced ionic conductivity and safety. The optimized polymer electrolyte is applied for energy storage devices.

Infinite time blow‐up with arbitrary initial energy for a damped plate equation

AbstractThis paper deals with the infinite blow‐up phenomena for a class of damped plate equations with logarithmic nonlinearity under the Navier boundary condition. Combining potential well method and modified differential inequality technique, we establish the infinite blow‐up result of solutions with arbitrary initial energy. In particular, it is not necessary to suppose that the initial velocity and the initial displacement should have the same sign in the sense of the L2 inner product, that is, the solution may blow up at infinity even , more precisely, .

Square impossible differential attack and security of AES in known plaintext scenario

In this work, we examine the security of the 8-round AES, under the known plaintext attack scenario, a type of cryptographic attack in which an attacker has access to the plaintext and corresponding ciphertext pairs. We present an innovative impossible differential (ID) attack technique, which utilizes a specific ID characteristic, to perform the first known plaintext attack on the 8-round AES with a 256-bit key. Additionally, we propose a new attack methodology, known as the Square Impossible Differential (SID) attack, to enhance the effectiveness of the ID attacks on AES in chosen ciphertext or plaintext scenarios. The SID attack is a combination of a square attack and an ID attack. Our methodology introduces various new approaches, including the key indicator vectors, eliminating the key candidate through the Meet-in-The-Middle technique and mounting the guess and determine attack through the hash tables for the two-round decryption of one column of AES while determining the subkeys constituting the impossible differential characteristic for a given plaintext/ciphertext difference pair. Our approach demonstrates lower computational complexity compared to previous methods, and our analysis shows that the complexities of our known plaintext attack and SID attack are estimated to be 2220 and 2209, respectively.

Synthesis and characterization of N-MPG/CuS flower-like/MXene to modify a screen-printed carbon electrode for electrochemical determination of nalbuphine

Nalbuphine (NAL) is a drug with narcotic properties and analgesic effects, and its use has side effects such as drowsiness, nausea, and headache. Excessive use of this drug leads to death. Measuring NAL is important to ensure that the correct dose is administered to the patient and to avoid overdose or underdose. It is also important to monitor the patient's response to the medication and adjust the dosage if necessary. Additionally, measuring nalbuphine levels may be important in cases of suspected overdose or toxicity. In the present research, a very simple and cheap method based on screen-printed carbon electrodes coated with CuS flower-like and N-doped mesoporous graphene and MXene was constructed for the measurement of NAL. At first, the modifier was analyzed by SEM, EDS, and TEM methods. Then, the NAL measurement was done by cyclic and differential pulse voltammetry techniques. Results showed a good ability of the prepared sensor for measurement of NAL in the span of 5–150 μM, which reached a detection limit of 1.6 μM. The prepared sensor showed the capability of NAL measurement in real samples.

An overpressure monitoring system based on PVDF integrated Electronic sensor with enhanced noise attenuation capability

The measurement of shockwave overpressure is of great significance for the safe use of explosives. The traditional overpressure monitoring systems are based on Integrated Electronics Piezo-Electric (IEPE) ceramic sensors. However, the brittleness of piezoelectric ceramic limits the application of overpressure monitoring system in high impact overpressure testing. Herein, a novel overpressure monitoring system based on Integrated Electronic Poly (vinylidene fluoride) (PVDF) (PFIE) sensor with electromagnetic interference shielding capability and parasitic vibration noise elimination function was designed for intense overpressure acquiring. PVDF, as a polymer, can endure much higher impact pressures compared to piezoelectric ceramics. However, its larger internal resistance makes it more prone to electromagnetic interference. To address this, an electromagnetic shielding structure was designed, incorporating an impedance matching circuit that effectively reduces the sensor's output impedance. Additionally, to mitigate excessive vibration noise during overpressure testing, the differential noise reduction technique has been implemented. Both the laboratory testing and the real blast testing with 10 kg trinitrotoluene were performed to validate the PFIE overpressure monitoring system. The result shows that the electromagnetic noise suppression ability of the PFIE overpressure sensors developed for the monitoring system was improved by 45 dB, and the parasitic vibration noise could be attenuated from 30 % to 1 %, what’s more the RMS errors of the overpressure dynamic parameters obtained by the monitoring system were below 10 %. This work has successfully addressed the noise sensitivity issue inherent in PVDF when used as a pressure sensor, capitalizing on its robust impact resistance. This approach has provided a viable solution for measuring overpressure in scenarios involving intense shock pressures, leveraging the strengths of PVDF in such demanding applications.

ELM combined with differential Raman spectroscopy for the detection of microplastics in organisms

Aiming at the problems of low extraction efficiency, high false detection rate, weak Raman signal and serious interference by fluorescence signal in the detection of microplastics in marine organisms, this paper establishes a set of rapid detection methods for microplastics in organisms, including confocal Raman spectroscopy, fluorescence imaging, differential Raman spectroscopy, and rapid identification of microplastics based on the ELM modeling assistance. Firstly, to address the problem of low extraction efficiency of microplastics, we explored and optimized the digestion method of tissues, which effectively improved the digestion effect of fish tissues and excluded the influence of tissues on microplastics detection. Aiming at the problems of high misdetection rate and low pre-screening efficiency of microplastics, fluorescence imaging technology is adopted to realize the visualization and detection of microplastics, which effectively improves the detection efficiency and precision of microplastics. Based on the confocal microscopy Raman spectroscopy detection system built independently in the laboratory, using 784/785 nm as the excitation light, the differential Raman spectroscopy technique effectively excludes the interference of fluorescence signals in the Raman spectra, and improves the signal-to-noise ratio of the Raman spectra, and the recovery rate of the Raman characteristic peaks in the differential Raman spectroscopy reaches 100 % compared to the traditional baseline correction method, which is 33.3 % higher than that of the baseline correction method. Finally, a microplastic identification model is constructed based on ELM to assist in realizing the rapid and accurate identification of microplastics. The more complete detection method of microplastics in marine organisms proposed in this paper can realize the rapid and nondestructive, efficient and accurate detection of microplastics in fish, which can help to further promote the development of marine microplastics monitoring technology.

Bismuth sulfide micro flowers decorated nickel foam as a promising electrochemical sensor for quantitative analysis of melamine in bottled milk samples

Here, we demonstrate hydrothermally grown bismuth sulfide (Bi2S3) micro flowers decorated nickel foam (NF) for electrochemical detection of melamine in bottled milk samples. The orthorhombic phase of hydrothermally grown Bi2S3 is confirmed by the detailed characterization of x-ray diffraction and its high surface area micro flowers-like morphology is investigated via field emission scanning electron microscope. Furthermore, the surface chemical oxidation state and binding energy of Bi2S3/NF micro flowers is analyzed by x-ray photoelectron spectroscopy studies. The sensor exhibits a wide linear range of detection from 10 ng l−1 to 1 mg l−1 and a superior sensitivity of 3.4 mA cm−2 to melamine using differential pulse voltammetry technique, with a lower limit of detection (7.1 ng l−1). The as-fabricated sensor is highly selective against interfering species of p-phenylenediamine (PPDA), cyanuric acid (CA), aniline, ascorbic acid, glucose (Glu), and calcium ion (Ca2+). Real-time analysis done in milk by the standard addition method shows an excellent recovery percentage of ̴ 98%. The sensor’s electrochemical mechanism studies reveal that the high surface area bismuth sulfide micro flowers surface interacts strongly with melamine molecules through hydrogen bonding and van der Waals forces, resulting in a significant change in the sensor’s electrical properties while 3D skeletal Nickel foam as a substrate provides stability, enhances its catalytic activity by providing a more number /of active sites and facilitates rapid electron transfer. The work presented here confirms Bi2S3/NF as a high-performance electrode that can be used for the detection of other biomolecules used in clinical diagnosis and biomedical research.

Mueller matrix-based characterization of cervical tissue sections: a quantitative comparison of polar and differential decomposition methods.

Quantitative optical polarimetry has received considerable recent attention owing to its potential for being an efficient diagnosis and characterizing tool with potential applications in biomedical research and various other disciplines. In this regard, it is crucial to validate various Mueller matrix (MM) decomposition methods, which are utilized to extract and quantify the intrinsic individual polarization anisotropy properties of various complex optical media. To quantitatively compare the performance of both polar and differential MM decomposition methods for probing the structural and morphological changes in complex optical media through analyzing their intrinsic individual polarization parameters, which are extracted using the respective decomposition algorithms. We also intend to utilize the decomposition-derived anisotropy parameters to distinguish among the cervical tissues with different grades of cervical intraepithelial neoplasia (CIN) and to characterize the healing efficiency of an organic crystal. Polarization MM of the cervical tissues with different grades of CIN and the different stages of the self-healing crystal are recorded with a home-built MM imaging setup in the transmission detection geometry with a spatial resolution of . The measured MMs are then processed with both the polar and differential MM decomposition methods to extract the individual polarization parameters of the respective samples. The derived polarization parameters are further analyzed to validate and compare the performance of both the MM decomposition methods for probing and characterizing the structural changes in the respective investigated optical media through their decomposition-derived intrinsic individual polarization properties. Pronounced differences in the decomposed-derived polarization anisotropy parameters are observed for cervical tissue sections with different grades of CIN. While a significant increase in the depolarization parameter is obtained with the increment of CIN stages for both the polar [ for CIN grade one (CIN-I) and for CIN grade two (CIN-II))] and differential ( for CIN-I and for CIN-II) decomposition methods, a trend reversal is seen for the linear diattenuation parameter , indicating the structural distortion in the cervical morphology due to the CIN disease. More importantly, with the differential decomposition algorithm, the magnitude of the derived parameter decreases from 0.26 to 0.19 with the progression of CIN, which was not being probed by the polar decomposition method. Our results demonstrate that the differential decomposition of MM holds certain advantages over the polar decomposition method to characterize and probe the structural changes in the cervical tissues with different grades of CIN. Although the quantified individual polarization parameters obtained through both the MM decomposition methods can be used as useful metrics to characterize various optical media, in case of complex turbid media such as biological tissues, incorporation of the differential decomposition technique may yield more efficient information. Also, the study highlights the utilization of MM polarimetry with an appropriate decomposition technique as an efficient diagnostic and characterizing tool in the realm of biomedical clinical research, and various other disciplines.

Joint optimization of utility and privacy in mobile edge computing

In mainstream research on Mobile Edge Computing (MEC), considerations for user privacy are often overlooked. This paper introduces Differential Privacy techniques to MEC, which obfuscate specific parameter values when transmitting user data, preventing leakage of sensitive information. Simultaneously, privacy, latency, and energy are incorporated as components of the utility function. We model the task offloading process using a deep reinforcement learning model and propose the use of the Deep Deterministic Policy Gradient (DDPG) algorithm in conjunction with a Laplacian privacy budget for joint optimization of privacy and utility during offloading. After sufficient training, the DDPG model can effectively approximate the optimal solution. Compared to traditional work, the optimized framework gives ample consideration to user privacy needs and outputs the optimal task offloading ratio solution with relatively low time complexity. This approach effectively safeguards user privacy while also considering the efficiency of task offloading.