Differential Technique Research Articles

A Pseudo-Spectral Method for Wall Shear Stress Estimation from Doppler Ultrasound Imaging in Coronary Arteries.

The Wall Shear Stress (WSS) is the component tangential to the boundary of the normal stress tensor in an incompressible fluid, and it has been recognized as a quantity of primary importance in predicting possible adverse events in cardiovascular diseases, in general, and in coronary diseases, in particular. The quantification of the WSS in patient-specific settings can be achieved by performing a Computational Fluid Dynamics (CFD) analysis based on patient geometry, or it can be retrieved by a numerical approximation based on blood flow velocity data, e.g., ultrasound (US) Doppler measurements. This paper presents a novel method for WSS quantification from 2D vector Doppler measurements. Images were obtained through unfocused plane waves and transverse oscillation to acquire both in-plane velocity components. These velocity components were processed using pseudo-spectral differentiation techniques based on Fourier approximations of the derivatives to compute the WSS. Our Pseudo-Spectral Method (PSM) is tested in two vessel phantoms, straight and stenotic, where a steady flow of 15mL/min is applied. The method is successfully validated against CFD simulations and compared against current techniques based on the assumption of a parabolic velocity profile. The PSM accurately detected Wall Shear Stress (WSS) variations in geometries differing from straight cylinders, and is less sensitive to measurement noise. In particular, when using synthetic data (noise free, e.g., generated by CFD) on cylindrical geometries, the Poiseuille-based methods and PSM have comparable accuracy; on the contrary, when using the data retrieved from US measures, the average error of the WSS obtained with the PSM turned out to be 3 to 9 times smaller than that obtained by state-of-the-art methods. The pseudo-spectral approach allows controlling the approximation errors in the presence of noisy data. This gives a more accurate alternative to the present standard and a less computationally expensive choice compared to CFD, which also requires high-quality data to reconstruct the vessel geometry.

Bismuth oxide nanoparticles enabled sensitive electrochemical determination of Vitamin B12

The intake and monitoring of vitamin B12 levels are highly essential to maintain a healthy body condition. Herein, we report bismuth oxide nanoparticles (Bi2O3 NPs) facilitated electrochemical sensing of vitamin B12 with admirable sensitivity, selectivity, and low detection limit. A facile hydrothermal method was adopted for synthesizing Bi2O3 NPs and their physico-chemical properties were analyzed using various techniques. The electrochemical sensing of vitamin B12 was validated through cyclic voltammetry and differential pulse voltammetry techniques. The sensing results illustrate that the modified electrode exhibits a wide linear range between 10 nM and 275 nM with a low detection limit value of 3.66 nM. In addition to the enhanced electrocatalytic behavior, the Bi2O3 NPs have also enabled the discrimination of vitamin B12 from various potential interfering molecules (even adding a 5-fold concentration). The developed sensor also exhibits better stability, selectivity, and reproducibility towards the target analyte. Finally, the fabricated electrode was applied for the determination of vitamin B12 in serum, and plasma samples, and the results were highly satisfactory with recovery values of 98.4 % to 99.8 %.

The largest metallicity difference in twin systems: High-precision abundance analysis of the benchmark pair Krios and Kronos

Aims. We conducted a high-precision differential abundance analysis of the remarkable binary system HD 240429/30 (Krios and Kronos, respectively), whose difference in metallicity is one of the highest detected to date in systems with similar components (~0.20 dex). A condensation temperature TC trend study was performed to search for possible chemical signatures of planet formation. In addition, other potential scenarios are proposed to explain this disparity. Methods. Fundamental atmospheric parameters (Teff, log g, [Fe/H], υturb) were calculated using the latest version of the FUNDPAR code in conjunction with ATLAS12 model atmospheres and the MOOG code, considering the Sun and then Kronos as references, employing high-resolution MAROON-X spectra. We applied a full line-by-line differential technique to measure the abundances of 26 elements in both stars with equivalent widths and spectral synthesis taking advantage of the non-solar-scaled opacities to achieve the highest precision. Results. We find a difference in metallicity of ~0.230 dex: Kronos is more metal rich than Krios. This result denotes a challenge for the chemical tagging method. The analysis encompassed the examination of the diffusion effect and primordial chemical differences, concluding that the observed chemical discrepancies in the binary system cannot be solely attributed to any of these processes. The results also show a noticeable excess of Li of approximately 0.56 dex in Kronos, and an enhancement of refractories with respect to Krios. A photometric study with TESS data was carried out, without finding any signal of possible transiting planets around the stars. Several potential planet formation scenarios were also explored to account for the observed excess in both metallicity and lithium in Kronos; none was definitively excluded. While planetary engulfment is a plausible explanation, considering the ingestion of an exceptionally high mass, approximately ~27.8 M⊕, no scenario is definitively ruled out. We emphasize the need for further investigations and refinements in modelling; indispensable for a comprehensive understanding of the intricate dynamics within the Krios and Kronos binary system.

KIF1A, R1457Q, and P1688L Mutations Induce Protein Abnormal Aggregation and Autophagy Impairment in iPSC-Derived Motor Neurons.

Mutations in the C-terminal of KIF1A (Kinesin family member 1A) may lead to amyotrophic lateral sclerosis (ALS) through unknown mechanisms that are not yet understood. Using iPSC reprogramming technology and motor neuron differentiation techniques, we generated iPSCs from a healthy donor and two ALS patients with KIF1A mutations (R1457Q and P1688L) and differentiated them into spinal motor neurons (iPSC-MN) to investigate KIF1A-related ALS pathology. Our in vitro iPSC-iMN model faithfully recapitulated specific aspects of the disease, such as neurite fragmentation. Through this model, we observed that these mutations led to KIF1A aggregation at the proximal axon of motor neurons and abnormal accumulation of its transport cargo, LAMP1, resulting in autophagy dysfunction and cell death. RNAseq analysis also indicated that the functions of the extracellular matrix, structure, and cell adhesion were significantly disturbed. Notably, using rapamycin during motor neuron differentiation can effectively prevent motor neuron death.

Stability of phase composition and properties of Zn4+xSb3 medium-temperature thermoelectric material

The phase composition and thermoelectric properties of a β-Zn4Sb3 based material before and after thermocycling tests at 273–723 K have been studied. Specimens with stoichiometric Zn and Sb molar ratios and with additions of different excess Zn quantities have been synthesized by direct component smelting followed by spark plasma sintering. The phase composition and structure of the materials have been studied using X-ray diffraction and transmission electron microscopy. The thermal conductivity and specific heat of the materials have been measured with laser flash and differential scanning calorimetry techniques. The phase composition of the as-synthesized, as-sintered and as-thermocycled Zn4+xSb3 thermoelectric material has been found to vary depending on excess Zn content in the charge. Excess Zn has been shown to dissolve in the β-Zn4Sb3phase upon spark plasma sintering and thermocycling. β-Zn4+xSb3 solid solution depletion of interstitial zinc atoms or ZnSb phase precipitation upon thermocycling increase the thermal conductivity and reduce the thermoelectric efficiency of the material. The Zn4.1Sb3 composition has shown high thermoelectric efficiency, the 715 K ZT being ∼1.23 and 1.18 before and after thermocycling, respectively.

Code-Based Differential GNSS Ranging for Lunar Orbiters: Theoretical Review and Application to the NaviMoon Observables

In the near future, international space agencies have planned to achieve significant milestones in investigating the utilization of Global Navigation Satellite Systems (GNSS) within and beyond the current space service volume up to their application to lunar missions. These initiatives aim to demonstrate the feasibility of GNSS navigation at lunar altitudes. Based on the outcomes of such demonstrations, dozens of lunar missions will likely be equipped with a GNSS receiver to support autonomous navigation in the lunar proximity. Relying on non-invasive, consolidated differential techniques, GNSS will enable baseline estimation, thus supporting a number of potential applications to lunar orbiters such as collaborative navigation, formation flight, orbital manoeuvers, remote sensing, augmentation systems and beyond. Unfortunately, the large dynamics and the geometry of such differential GNSS scenarios set them apart from current terrestrial and low-earth orbit use cases. These characteristics result in an increased sensitivity to measurements time misalignment among orbiters. Hence, this paper offers a review of baseline estimation methods and characterizes the divergences and limitations w.r.t. to terrestrial applications. The study showcases the estimation of the baseline length between a lunar CubeSat mission, VMMO, and the communication relay Lunar Pathfinder mission. Notably, real GNSS measurements generated by an Engineering Model of the NaviMoon receiver in the European Space Agency (ESA/ESTEC) Radio Navigation Laboratory are utilized. A radio-frequency constellation simulator is used to generate the GNSS signals in these hardware-in-the-loop tests. The performed analyses showed the invalidity of common terrestrial differential GNSS ranging techniques for space scenarios due to the introduction of significant biases. Improved ranging algorithms were proposed and their potential to cancel ranging errors common to both receivers involved was confirmed.

Stability analysis of sandwich double nanobeam-system with varying cross-section interconnected by Kerr-type three-parameter elastic layer

In this study, the endurable buckling load of the elastically connected parallel sandwich nano-beams with varying cross-sections is assessed. In this regard, a layered beam system consisting of two parallel axially loaded tapered sandwich nanobeams that are interconnected via a Kerr-type three-parameter elastic foundation is considered. The geometric properties are assumed to be changed exponentially along the length of the beam element. The governing equilibrium equations of the system are described by a set of three coupled homogeneous differential equations, which originates in the context of Eringen's non-local elasticity theory and Euler beam model. Then, the numerical differential quadrature technique is used to estimate the endurable axial critical loads. Eventually, a comprehensive parameterization research is performed to investigate the sensitivity of linear buckling resistance to tapering ratio, nonlocal parameter, stiffness of elastic connections, volume fraction exponent, and thickness ratio. The research work of the present study is novel, and the attained numerical outcomes can be used as benchmarks for future researches in this field.

Tweeting environmental pollution: Analyzing twitter language to uncover its correlation with county-level obesity rates in the United States

BackgroundEnvironmental pollution has been linked to obesogenic tendencies. Using environmental-related posts from Twitter (now known as X) from U.S. counties, we aim to uncover the association between Twitter linguistic data and U.S. county-level obesity rates. MethodsAnalyzing nearly 300 thousand tweets from January 2020 to December 2020 across 207 U.S. counties, using an innovative Differential Language Analysis technique and drawing county-level obesity data from the 2020 Food Environment Atlas to identify distinct linguistic features in Twitter relating to environmental-related posts correlated with socioeconomic status (SES) index indicators, obesity rates, and obesity rates controlled for SES index indicators. We also employed predictive modeling to estimate Twitter language's predictive capacity for obesity rates. ResultsResults revealed a negative correlation between environmental-related tweets and obesity rates, both before and after adjusting for SES. Contrarily, non-environmental-related tweets showed a positive association with higher county-level obesity rates, indicating that individuals living in counties with lower obesity rates tend to tweet environmental-related language more frequently than those living in counties with higher obesity rates. The findings suggest that linguistic patterns and expressions employed in discussing environmental-related themes on Twitter can offer unique insights into the prevailing cross-sectional patterns of obesity rates. ConclusionsAlthough Twitter users are a subset of the general population, incorporating environmental-related tweets and county-level obesity rates and using a novel language analysis technique make this study unique. Our results indicated that Twitter users engaging in more active dialog about environmental concerns might exhibit healthier lifestyle practices, contributing to reduced obesity rates.

New Media User Privacy Protection Mechanism Based on Differential Privacy and Data Anonymization

With the rapid development of new media, user privacy issues have become increasingly important. New media platforms, such as TikTok, Twitter, and WhatsApp, process vast amounts of user data daily, including personal information, behavioral data, and social relationships. The extensive collection and use of this data present numerous privacy protection challenges. Many users are not fully aware of how their data is collected and used when using new media platforms, lacking informed consent regarding data collection. Consequently, relying on users to take proactive privacy measures to prevent the disclosure of critical information is difficult to achieve. To address this issue, this paper proposes a privacy protection mechanism that combines differential privacy and data anonymization. The mechanism protects query results through differential privacy techniques and hides user identity information using data anonymization techniques, thereby ensuring user privacy during data analysis and processing. This paper conducts necessary experimental analysis on the proposed method, and the results demonstrate its usability and effectiveness.

Energy-safety balanced composites of attractive cyclic nitramines with polyaniline

Composite microcrystals of the cyclic nitramines 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (ε-CL-20), 1,3,5-trinitro-1,3,5-triazinane(RDX), 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (β-HMX), and cis-1,3,4,6-tetranitrooctahydroimidazo-[4,5-d]imidazole (BCHMX) with polyaniline (PANi) have been prepared and thoroughly characterized in terms of morphology and phase purity. PANi outperformed other conducting polymers in terms of selectivity towards NAs due to its better interaction with NAs, low production cost, and ease of preparation. The bonding of nitramines with the polymeric PANi chain has been examined by means of Fourier transform infrared (FTIR), Raman spectroscopy methods, and fluorescence quenching; the Raman spectrum has shown the laser sensitivity of these microcrystals. Powder X-ray diffraction results have shown changes in polymorph modifications in CL20 (from ɛ to β) and HMX (from β to α) during the preparation of the composites, which have also been confirmed by spectral and differential thermal analysis techniques. The structural orientations found in these composites significantly stabilize nitramines against impact; their detonation properties have slightly deteriorated, but the PANi electrical conductivity has strongly increased their electric-spark sensitivity. The above properties of the prepared composites determine their potential use mainly as parts of the electric or laser impulse initiators, having “a green character”, for various charges.

Sea surface Fresnel reflections difference driven de-glint algorithm for airborne optical images.

This paper presents a glint correction algorithm for high spatial resolution optical remote sensing imagery captured by the ER-2 Airborne Visual Infrared Imaging Spectrometer (AVIRIS). The algorithm employs linear and differential techniques to mitigate sun glint and sky glint effects, encompassing statistical glint reflections resulting from variations in imaging angles within strips and inter-strip variations due to Fresnel reflectance disparities. It aims to diminish Fresnel reflectance diversity on water surfaces and mitigate the distortions induced by glint reflectance during spectral and ocean color inversion. A comparative analysis of spectral and ocean color information in AVIRIS images before and after correction reveals enhanced accuracy following the glint correction. By systematically addressing multiple glint reflections and their ramifications, this method offers a valuable framework for correcting water surface glint in diverse high spatial resolution optical imagery.

Profiling Bioactive Compounds in the Bark of Cinchona officinalis L. and Anti-arthritic Properties Thereof

The bark samples of C. officinalis were collected from The Nilgiris district of Tamil Nadu. The collected samples were processed and extracted using methanol solvent. The extracts showed high yield of secondary metabolites especially alkaloids, phenols, flavonoids, steroids, terpenoids, sterols, quinones and tannins. Alkaloid content was very high in C.officinalis followed by phenol, flavonoid, steroid and Tannin. The secondary metabolites present in C. officinalis (Bark) were isolated, purified, identified and characterized using differential Chromatographic techniques such as TLC, HPLC and GC-MS/ MS. The compounds identified using High Performance Liquid Chromatography (HPLC) technique in bark of C. officinalis in the retention times of 1.750, 2.250, 4.016 and 7.266 minutes were quinine, isoquinidine and cinchonidine. The compounds were then characterized using GC- MS/ MS technique with reference to NIST library. The compounds were eluted from the bark of C. officinalis in the retention time of 9.569, 10.488, 11.814, 13.593, 14.282, 16.542, 16.967, 23.494, 24.954, 25.151, 25.988, 26.752, 26.982, 27.906, 28.277, 31.454, 33.604, and 35.744 minutes. By correlating the retention times with (NIST) mass spectral library the eluted compounds were confirmed as Phthalic acid, Hexadecanoic acid,1,2,3,5-Cyclohexanetetrol, Cinchonab-9-one, 9,12-Octadecadienoic acid (Z,Z)-, Heptadecanoic acid, Quinine, Cinchonine, Cinchonidine, Phenol, Quinine, and gamma.-Sitosterol. The phytochemicals present in the C. officinalis (Bark) samples were evaluated for their biological properties viz., anti-inflammatory activity and anti-arthritic activity in in-vitro conditions. Anti- inflammatory properties of plant samples were tested by protein denaturation method using diclofenac (75 mg/ ml concentration) as positive control. The methanol extract of C.officinalis (Bark) showed anti- inflammatory properties of range between 17.0 and 57.3%. Anti- arthritic activity of bark extract of C. officinalis (75 mg/ ml concentration) was evaluated by albumin denaturation method using diclofenac (75 mg/ ml concentration) as positive control. The methanol extract of C.officinalis (Bark) showed anti- arthritic properties of range between 18.4 and 58.5%. From the study it is understood that the alkaloids and polyphenols present in the methanolic extract of bark of C. officinalis were responsible for their biological properties. Hence, C. officinalis can serve as an alternative to synthetic drugs available in the market to treat arthritis subject to safety (toxicity) studies in humans. Based on the In vitro results, it was confirmed that the bark of C.officinalis possesses comparatively high biological values. Thus an herbal aerosol for arthritis may be formulated using the bark extract of C.officinalis as key ingredient and the therapeutic product will be of cost effective, easy to use and pocket friendly.

Rapid identification of bloodstream infection pathogens and drug resistance using Raman spectroscopy enhanced by convolutional neural networks.

Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can be markedly improved through the prompt identification of the causative pathogens and their susceptibility to antibiotics and antimicrobial agents. Traditional BSI diagnosis via blood culture is often hindered by its lengthy incubation period and its limitations in detecting pathogenic bacteria and their resistance profiles. Surface-enhanced Raman scattering (SERS) has recently gained prominence as a rapid and effective technique for identifying pathogenic bacteria and assessing drug resistance. This method offers molecular fingerprinting with benefits such as rapidity, sensitivity, and non-destructiveness. The objective of this study was to integrate deep learning (DL) with SERS for the rapid identification of common pathogens and their resistance to drugs in BSIs. To assess the feasibility of combining DL with SERS for direct detection, erythrocyte lysis and differential centrifugation were employed to isolate bacteria from blood samples with positive blood cultures. A total of 12,046 and 11,968 SERS spectra were collected from the two methods using Raman spectroscopy and subsequently analyzed using DL algorithms. The findings reveal that convolutional neural networks (CNNs) exhibit considerable potential in identifying prevalent pathogens and their drug-resistant strains. The differential centrifugation technique outperformed erythrocyte lysis in bacterial isolation from blood, achieving a detection accuracy of 98.68% for pathogenic bacteria and an impressive 99.85% accuracy in identifying carbapenem-resistant Klebsiella pneumoniae. In summary, this research successfully developed an innovative approach by combining DL with SERS for the swift identification of pathogenic bacteria and their drug resistance in BSIs. This novel method holds the promise of significantly improving patient prognoses and optimizing healthcare efficiency. Its potential impact could be profound, potentially transforming the diagnostic and therapeutic landscape of BSIs.

A gradient-based strategy to construct efficient heat conduction path for arbitrary configurations

The heat conduction optimization problem is a widely investigated abstraction of various heat dissipation problems in industry and electronics cooling. This paper studies the optimization strategy that produces optimized heat conduction path made of high thermal conductivity materials, with the objective of lowering the hot spot temperature or improving temperature uniformity. The automatic differentiation (AD) technique is a general-purpose method to calculate the partial derivatives of any continuous function composed by elementary functions with respect to multiple independent variables. It is introduced to calculate the gradient of the objective function with respect to the thermal conductivity field, so that the optimization procedure can be guided directly towards the minimization of the desired objective function. This paper investigated the configurations of both continuous-value thermal conductivity and discrete-value thermal conductivity. Results indicate that the present optimization strategy is able to handle various types of boundary conditions and objective functions. The present method is compared with the iterative method based on variational principle (Var), showing that the AD method performs better than the Var method in most situations.

Genuine differential voltammetry

A novel form of differential voltammetry is proposed, developed through the implicit anodic and cathodic current components of the experimentally accessible conventional net current measured in a voltammetric experiment. By employing basic mathematical modelling of an electrode reaction of a dissolved redox couple at a conventional, macroscopic electrode within the framework of the Butler-Volmer electrode kinetic model, the implicit anodic and cathodic current components of the net conventional current are clearly defined and can be estimated. Consequently, a novel form of differential current, calculated as the difference between anodic and cathodic implicit current components associated with a single potential of the voltammetric experiment, can be established. This differential current demonstrates remarkable characteristics in terms of electrode kinetics and analytical performance, particularly in cases involving fast, seemingly electrochemically reversible electrode processes. It holds promise to be analytically superior to the best-known differential voltammetric techniques so far (e.g., square-wave voltammetry), as well as provides a means for estimating the rate constants of very fast, apparently reversible electrode processes at macroscopic electrodes under mild experimental conditions (i.e., studied at slow potential scan rates). The practical implication of the novel methodology is significant: a simple linear sweep voltammogram of a quasi-reversible electrode reaction with unknown electrode kinetic parameters can be readily transformed into the novel type of differential voltammogram through a convolution procedure of the conventional net current, paving a new way for studying electrode processes by voltammetry.

Advancements in differentiation between sperm cells and epithelial cells for efficient forensic DNA analysis in sexual assault cases.

Most of the sexual assault casework samples are of mixed sources. Forensic DNA laboratories are always in the requirement of a precise technique for the efficient separation of sperm and non-sperm DNA from mixed samples. Since the introduction of the differential extraction technique in 1985, it has seen significant advancements in the form of either chemicals used or modification of incubation times. Several automated and semi-automated techniques have also adopted the fundamentals of conventional differential extraction techniques. However, lengthy incubation, several manual steps, and carryover over non-sperm material in sperm fraction are some of the major limitations of this technique. Advanced cell separation techniques have shown huge promise in separating sperm cells from a mixture based on their size, shape, composition, and membrane structure and antigens present on sperm membranes. Such advanced techniques such as DEParray, ADE, FACS, LCM, HOT and their respective pros and cons have been discussed in this article. As current-day forensic techniques should be as per the line of Olympic slogan i.e., faster, higher, stronger, the advanced cell separation techniques show a huge potential to be implemented in the casework samples.

Preparation of pyridoxine-based polyurethane modified sensors and their use in simultaneous determination of Cu(II) – Co(II) ions

In this study, pyridoxine-based polyurethane-modified electrodes were prepared to simultaneously and sensitively measure copper (Cu(II)) and cobalt (Co(II)) ions in complex matrix samples. For the production of the electrodes, firstly, the synthesis of pyridoxine-based polyurethane structures was carried out. In these syntheses, the polymer structure was diversified by using different isocyanates. Polyethyleneglycol-200 (PEG), pyridoxine (B6), and β-cyclodextrin (β-CD) groups were used as the source of polyol. The synthesized polyurethane structures were characterized by different instrumental techniques and used in gold electrode surface modification. Modified sensor surfaces were examined by scanning electron microscopy and atomic force microscopy techniques. The prepared modified sensors were used for the simultaneous detection of Cu(II) and Co(II) ions using the differential pulse voltammetry technique. The limit of detection (LOD), limit of quantitation (LOQ), and R2 values for Cu(II) ions were calculated as 8.81 μM, 29.4 μM, and 0.993, respectively. LOD, LOQ, and R2 values for Co(II) ions were calculated as 9.84 μM, 32.8 μM, and 0.9935, respectively. For repeatability, the relative standard deviation (RSD %) of the prepared simultaneous sensors was determined as 1.54 and 1.71 for Cu(II) and Co(II), respectively. As a result, Cu(II) and Co(II) ions were measured independently and simultaneously with high sensitivity. According to these results, it is predicted that pyridoxine-based polyurethane-modified sensors may be suitable for the simultaneous detection of Cu(II) and Co(II) in medical, food, and agricultural samples.

A privacy-preserving federated graph learning framework for threat detection in IoT trigger-action programming

Trigger-Action Programming (TAP) is a common user-programming paradigm in Internet of Things (IoT) smart home platforms, allowing users to create customized automation rules to match IoT devices and network services. However, the potential security threats associated with TAP rules are often overlooked or underestimated by users. To address this issue, we propose PFTAP, a novel federated graph learning framework for threat detection of TAP rules while simultaneously protecting user data and privacy. First, we propose a hierarchical graph attention network. This network comprises intra-rule attention and inter-rule attention modules, which enable the learning of comprehensive feature representations for triggers and actions. By capturing the intricate relationships between different rules, the network enhances the detection accuracy of risky TAP rules. Moreover, our framework is based on federated learning and integrates symmetric encryption and local differential privacy techniques, aiming to safeguard user privacy from unauthorized access or tampering. To evaluate the effectiveness of our framework, we conduct experiments using an extensive dataset of IFTTT rules. The experimental results convincingly demonstrate that PFTAP outperforms state-of-the-art methods in terms of threat detection performance.

On the terminal conditions of the two cutters and a fugitive ship differential game with non-zero capture radius and different players’ speed ratio

We study a pursuit-evasion differential game in which three agents move with simple motion on the Euclidean plane. Two of them, the cutters (pursuers), aim to capture a fugitive ship (the evader) as soon as possible. Having an opposite goal, the fugitive ship seeks to avoid capture for as long as possible. The game ends when the distance between the fugitive and at least one of the cutters is smaller than a given value. We have divided the game into two cases: case 1, when all players have the same speed, and case 2, when the evader is faster than the pursuers. Unlike previous work, our main innovations are as follows. For case 1, we present a solution obtained using exclusively differential game techniques. The game of kind is solved by establishing a study of the barrier that defines the winner of the game. In addition, we obtained time-optimal strategies for all players, proving that they do not switch controls. For case 2, we obtain the primary solution and exhibit an example showing the existence of control switches.

Performance Analysis of Interconnection and Differential Power Processing Techniques under Partial Shading Conditions

Partial shading conditions can cause low output power, hotspots, and a reduced lifespan in photovoltaic arrays. Interconnection (IC) and differential power processing (DPP) can be used to mitigate these effects. When individually applied to an array, these techniques can significantly increase the generated power. A few authors studied the combined use of these schemes under specific conditions such as large-scale arrays or a complex combination of several techniques, making it difficult to identify the individual contribution of each technique. Here, we aimed to determine whether the combined use of a switching-inductor DPP circuit and a total-cross-tied interconnection scheme presents better performance than each standalone technique, using a small-scale photovoltaic array. An array was tested using IC, DPP, and a combination of both techniques, and the array was subjected to 13 shading patterns and two irradiance levels. The performance in each case was assessed using maximum output power, performance ratio, mismatch power loss, and power enhancement indicators. The results showed that a standalone differential power processing circuit presents better performance than when it is combined with an interconnection. The DPP showed performance ratio values of up to 97%, mismatch power losses lower than 36.9%, and a power enhancement of up to 95.9%. The standalone interconnection shows the worst performance among the three techniques.