Multiple Peaks Research Articles

Machine learning chain models for multi-response prediction of electrical equipment in substation subjected to earthquakes

Engineering structures often exhibit multiple potential vulnerable positions during strong earthquakes, such as porcelain insulators and connection flanges of electrical equipment in substations. This paper proposes two types of machine learning (ML) chain models, where multiple individual models are linked end to end, to predict multiple peak seismic responses of substation equipment at the same time using intensity measures (IMs). One is a simple chain where the next input is the previous output, while in another one, the next input is combined by IMs and the previous output. The training mechanisms of ML chain models are presented by means of bio-inspired multi-objective optimization techniques for the hyperparameters of multiple individual ML models. A case study on a 1100 kV transformer bushing is then conducted. Artificial neural network-gradient boosting regression and artificial neural network-kernel ridge regression chain models are respectively established for predicting the peak stresses at two most vulnerable positions. Both the evaluation indicators and shaking table tests show enough prediction accuracy of the two ML chain models. Such chain models are qualified for identifying the initial damage to equipment, which can be employed for assisting post-earthquake rapid judgement and relief.

Green synthesis of silver nanoparticles using Osbeckia leschenaultiana DC extract: Optimization of synthesis, biological activities, larvicidal activity and toxicity analysis

Presently the Osbeckia leschenaultiana DC leaf - extract was used to synthesis the silver nanoparticles and the green synthesized AgNPs were characterized by UV–vis spectrophotometer, FTIR, XRD, DLS, Zeta potential and SEM. Absorbance at 405 nm was obtained in UV–vis spectrophotometer and multiple peaks emerged in FTIR analyses that represent the presence of some interesting functional groups. XRD results proved that the synthesised AgNPs were face-centered cubic and crystalline in nature. SEM revealed the particles are Cuboid and irregular forms; the particle size ranged between 70 nm and 100 nm. And the antibacterial and antioxidant characterization of green synthesized silver nanoparticles Osbeckia leschenaultiana DC leaf − extract against. Methicillin-resistant Staphylococcus aureus, Vibrio cholerae, Bacillus subtilis and Escherichia coli, revealed the potential antibacterial efficiency against gram positive bacteria Methicillin-resistant Staphylococcus aureus (23.0 ± 1.0) and Bacillus subtilis (22.0 ± 1.0) and they showed 60–70 % high antioxidant activity compared to Osbeckia leaf extract. AgNPs showed the highest mortality against Aedes aegypti with LC50 value of 49.17 µg/mL, followed by the Osbeckia leaf extract have LC50 value of 85.95 µg/mL. The toxicity profile analyzed using non-target organism Artemia salina exhibited less toxicity. The results revealed that the Osbeckia leschenaultiana DC mediated AgNPs had multifaceted antibacterial, antioxidant and larvicidal potential.

Dynamics of Airyprime beams with higher-order spectral phase modulation in the fractional Schrödinger equation

In this paper, the effects of spectral phase modulation on propagation characteristics of Airyprime beams modeled by fractional Schrödinger equation are studied, and the propagation dynamics of Airyprime beams are analyzed. It is found that the second and third-order spectral phase modulation significantly affect the beams dynamics. For the second-order spectral phase modulation, an increase in the Lévy index leads to a forward shift of the peak position, and the peak intensity increases for the positive spectral modulation coefficient, while the opposite tendency of the peak intensity is found for the negative spectral modulation coefficient. In addition, the appearance of multiple peaks depends on the positive modulation coefficient. For the third-order spectral phase modulation, the peak intensity increases under the larger spectral phase modulation coefficient with the backward shift of the maximum peak position, and an increase of the Lévy index results in the forward shift of the focusing position. The results show potential applications of Airyprime beams in various fields such as optical controlling and manipulation.

GaN thickness dependence of GaN/AlN superlattices on face-to-face-annealed sputter-deposited AlN templates

Recently, deep-ultraviolet (DUV) light-emitting devices have attracted attention for various applications. GaN/AlN superlattices have emerged as a promising alternative for achieving high-efficiency DUV emission. To fabricate superlattices with high crystal quality and abrupt interfaces, we have utilized face-to-face-annealed sputter-deposited AlN template substrates characterized by a flat surface and low dislocation density. Furthermore, radio-frequency plasma-assisted molecular beam epitaxy with in situ reflection high-energy electron diffraction monitoring was employed for the growth process. The growth of the superlattices follows a specific sequence. Step 1: AlN growth, Step 2: conversion of Al droplets to AlN, Step 3: GaN growth, and Step 4: evaporation of Ga droplets. This study explored the impact of GaN thickness on the GaN/AlN superlattice. The GaN thickness was linearly controlled by changing the duration of Step 3. This approach allowed for the growth of a flat GaN layer up to 1 monolayer (ML) and achieved superlattices with abrupt interfaces. Single-peak cathodoluminescence (CL) emission at 240–245 nm was observed from the superlattices, with the peak shift toward longer wavelengths as the GaN thickness increased. In contrast, quantum dot-like GaN islands were generated with a thickness of over 1 ML, induced by compressive strain. Superlattices with thicker GaN exhibited broad CL emission with multiple peaks. However, the AlN barrier layer reduced the surface roughness and maintained abrupt interfaces within the superlattices. Therefore, to obtain sharp single-peak UV emission from GaN/AlN superlattices, the growth sequence should be controlled to obtain flat GaN layers without dots.

Advancing soil property prediction with encoder-decoder structures integrating traditional deep learning methods in Vis-NIR spectroscopy

The technology for estimating soil properties using visible and near-infrared spectroscopy has been maturing, with corresponding advances and breakthroughs in deep learning models. In this study, based on the large soil spectral library LUCAS, we explore the potential of encoder-decoder structures to improve convolutional neural network regression predictions. By introducing an encoder-decoder structure into the feature channels of a six-layer CNN model (TRNN model), we significantly enhanced the performance of shallow CNN models and successfully carried out regression predictions for seven soil properties. We employed IntegratedGradients, DeepLift, GradientShap, and DeepLiftShap methods to interpret the output of the TRNN model. Our TRNN model, built on raw spectra, demonstrated high accuracy in predicting multiple soil properties, outperforming residual architectures, LSTMs, various CNN architectures, and other traditional machine learning methods proposed in previous studies. We also investigated the impact of multi-task output structures (TRNN 1-M and TRNN M−M) and single-task output structures (TRNN 1-1) on model performance. For the TRNN model with an encoder-decoder structure, multi-task output structures resulted in a reduction in performance. The TRNN showed outstanding results in regression analysis of the seven soil properties selected in this study (cation exchange capacity, organic carbon content, calcium carbonate content, pH, clay content, silt content, and sand content), with R2 values exceeding 0.93 for all seven properties. Different soil characteristics correspond to different wavelengths, with multiple characteristic peaks commonly observed. This research convincingly demonstrates the enormous potential of combining large model architectures with traditional deep learning approaches for predicting soil properties, which could significantly advance precision agriculture.

Combined Effects of Local and Regional Drivers on Oyster Spat Density and Growth in Eastern Australia

Up to 85% of shellfish reefs have been lost worldwide, resulting in declining ecosystem services, and increasing restoration demand. However, more information regarding the conditions which maximise oyster settlement and growth is required to optimise restoration. We deployed oyster settlement tiles at 21 intertidal sites throughout Moreton Bay, Australia; a region where > 96% of rock oyster reefs are lost and demand for restoration is high. We quantified effects of variables describing the spatial (from GIS), local habitat (using quadrats and water quality measures), and oyster predator (using underwater videography) characteristics of sites on oyster density and size on tiles. Oyster density was highest at sites with intermediate predator abundance and temperature, highest nearby invertebrate cover, and low and high values of turbidity and nearby rock and algae cover. Conversely, oyster size was highest at sites with intermediate predator density, higher fish species richness and turbidity, and lowest temperatures. Together, this showed that optimal restoration requires sites with 22 to 23 °C average water temperatures, between 10 and 15 oyster predators, and either low (< 2 NTU) or high (> 6 NTU) turbidity levels. Notably, we observed multiple peaks for several variables, suggesting the potential presence of multiple cryptic oyster species on settlement tiles. We found that oysters shared preferred environmental conditions with polychaetes, coralline algae, and tunicates, and were more prevalent and abundant at sites with lower turf algae, barnacle, and mussel cover. Identifying environmental variables influencing oyster population distribution, settlement, and growth can guide the selection and approach of oyster restoration sites.

Polysaccharide Conjugates' contribution to mellow and thick taste of Pu-erh ripe tea, besides Theabrownin

Mellow and thick taste (MTT) is considered to be a typical taste characteristic of high-quality Pu-erh ripe tea. However, the role of polysaccharide conjugates remains unclear. In this study, the infusion of different grades of Pu-erh ripe tea was isolated to fractions by sensory-guided ultrafiltration technology and the key taste substances of MTT in Pu-erh ripe tea were identified and confirmed in the sensory reconstruction experiment. Further separation, purification and structural identification of the polysaccharide conjugates were carried out. Involving in aggregation morphology, the ultrafiltration fraction exhibited obvious MTT than other fractions. The main MTT compound (PRTPS-5), mainly composed of the rhamnose, galactose, arabinose and mannose, had a molecular weight of 22.93 kDa. The main chain of PRTPS-5 comprised α-L-Araf-(1→, →2,4)-α-L-Rhap-(1→, →2)-α-L-Rhap-(1→, α-D-Galp-(1→, →4)-α-D-GalpA-6-OMe-(1→, →4)-α-D-Manp-(1→, →3,6)-β-D-Galp-(1 → and →5)-α-L-Araf-(1 → and contained multiple pectic characteristic peaks. This result had scientific guiding significance for the quality enhancement of Pu-erh ripe tea.

Multiexcitation Peaks and Multicolor Emission Nanoassemblies for Transmembrane Cell Imaging and Photoresponsivity Antibacterial.

Nanomaterials with photoresponsivity have garnered attention due to their fluorescence imaging, photodynamic, and photothermal therapeutic properties. In this study, a photoresponsivity nanoassembly was developed by using photosensitizers and carbon dots (CDs). Due to their multiple excitation peaks and multicolor fluorescence emission, especially their membrane-permeating properties, these nanoassemblies can label cells with multiple colors and track cell imaging in real time. Additionally, the incorporation of photosensitizers and CDs provides the nanoassemblies with the potential for photodynamic therapy (PDT) and photothermal therapy (PTT). The nanoassemblies effectively suppressed the activity of Escherichia coli and Staphylococcus aureus through PDT and PTT. Moreover, the nanoassemblies exhibited a high affinity for E. coli and S. aureus. These distinct features confer broad-spectrum antibacterial properties to the nanoassemblies. As a photoresponsivity nanoplatform, these nanoassemblies have demonstrated potential applications in the fields of bioimaging and antimicrobial.

Pharmacokinetic Simulation and Area under the Curve Estimation of Drugs Subject to Enterohepatic Circulation.

Enterohepatic circulation (EHC) is a complex process where drugs undergo secretion and reabsorption from the intestinal lumen multiple times, resulting in pharmacokinetic profiles with multiple peaks. The impact of EHC on area under the curve (AUC) has been a topic of extensive debate, questioning the suitability of conventional AUC estimation methods. Moreover, a universal model for accurately estimating AUC in EHC scenarios is lacking. To address this gap, we conducted a simulation study evaluating five empirical models under various sampling strategies to assess their performance in AUC estimation. Our results identify the most suitable model for EHC scenarios and underscore the critical role of meal-based sampling strategies in accurate AUC estimation. Additionally, we demonstrate that while the trapezoidal method performs comparably to other models with a large number of samples, alternative models are essential when sample numbers are limited. These findings not only illuminate how EHC influences AUC but also pave the way for the application of empirical models in real-world drug studies.

Dispersion-Selective Band Engineering in an Artificial Kagome Superlattice.

The relentless pursuit of band structure engineering continues to be a fundamental aspect in solid-state research. Here, we meticulously construct an artificial kagome potential to generate and control multiple Dirac bands of graphene. This unique high-order potential harbors natural multiperiodic components, enabling the reconstruction of band structures through different potential contributions. As a result, the band components, each characterized by distinct dispersions, shift in energy at different velocities in response to the variation of artificial potential. Thereby, we observe a significant spectral weight redistribution of the multiple Dirac peaks. Furthermore, the magnetic field can effectively weaken the superlattice effect and reactivate the intrinsic Dirac band. Overall, we achieve actively dispersion-selective band engineering, a functionality that would substantially increase the freedom in band design.

Preparation, Quality control and Standardization of a Destructive Distillate &lt;i&gt;Swasakasa Nei&lt;/i&gt; (SKN), A Traditional Siddha Herbal Pharmaceutic for &lt;i&gt;Swasakasam&lt;/i&gt; (Bronchial Asthma)

Standardization is essential to ensure the quality and reliability of traditional medicines. This study aimed to collect, authenticate and purification of raw materials, preparation of &lt;i&gt;Swasakasa Nei&lt;/i&gt; (SKN) according to SOP, and Quality evaluation and Standardization procedures following Pharmacopoeial Laboratory of Indian Medicine (PLIM) guidelines. SKN, prepared as &lt;i&gt;Kuzhithylam&lt;/i&gt;, is used to treat &lt;i&gt;Swasakasam&lt;/i&gt; (Bronchial Asthma) in the Siddha system of medicine. The organoleptic characters of &lt;i&gt;Swasakasa Nei&lt;/i&gt; reveal that SKN was a black, thick semisolid with a smoky odour, greasy consistency, and free-flowing nature drug. Physicochemical analysis showed values for Saponification Value (202.19), Iodine Value (30), Acid Value (7.25%), Peroxide Value (0.58%), Refractive Index (1.462), Specific Gravity (0.9131 g/ml), Loss on Drying (34.17%), Total Fatty Matter (60.18%), Free Fatty Acids (1.06%), and Unsaponifiable Matter (0.98%). The congealing point was 19°C, with no mineral oil and definite oxidation on rancidity. HPTLC fingerprint analysis revealed multiple prominent peaks at various wavelengths. Microbial contamination tests showed no specific microbes, and aflatoxin assays confirmed SKN was free from Aflatoxins B1, B2, G1, and G2. Pesticide residue analysis detected no organochlorine, organophosphorus, or pyrethroids, and heavy metal analysis showed no trace elements or heavy metals. These standards affirm the authenticity, genuineness, and safety of SKN, contributing to its scientific validation.

Multi-axis stress sensing of bending and torsion using nano-diamond NVC fixed on a Si cantilever

In this study, we developed a cantilever-type force probe with a nano-diamond nitrogen vacancy color center (NVC) fixed on Si surface by sputtered SiO2 layer. We explored the correlation between the optically detected magnetic resonance (ODMR) spectrum’s peak shift and the stress intensity caused by the cantilever’s vibration. By adjusting the crystal axis of the nano-diamond and the static magnetic field, we assessed the peak shift’s dependency on these variables. Our results indicated that the peak shift could effectively detect uniaxial stress from standard vibration. Moreover, with increasing vibration amplitude, the peak shift proportionally intensified, consistent with theoretical expectations. For multi-axial vibration involving torsion, we noted multiple peak shifts in positive direction, suggesting stress along the axis. These findings confirm the potential of nano-diamonds on cantilevers to measure multiaxial stress.

Responses of sap flow in Larix principis-rupprechtii to environment under different weather conditions.

This study was conducted in Liupanshan Forest Ecological Positioning Station of the National Forestry and Grassland Administration. We monitored sap flow of Larix principis-rupprechtii plantation in the Xiangshui River sub-basin throughout the 2019 growing season (from May 17 to October 12), as well as the meteorological conditions and soil environment (soil temperature and soil water content), to analyze the comprehensive environmental responses of sap flow in L. principis-rupprechtii under different weather conditions. The results showed that sap flow rate increased and then decreased on the daily scale, with the highest rate on sunny days, followed by overcast days and then rainy days. Sap flow rate had a single peak on sunny days and multiple peaks on overcast and rainy days. Sunny days had earlier and longer sap flow compared to overcast and rainy days. Dominant factors driving sap flow differed across different weather. Vapor pressure deficit was the dominant factor influencing sap flow in sunny and overcast days, while solar radiation was dominant one in rainy days. The contribution rates of main factors to sap flow on sunny, overcast and rainy days were 31.1%, 27.4% and 40.1%, respectively. Results of the principal component analysis showed the factors affecting sap flow on sunny days could be classified into hydrothermal complex factors (air temperature, soil temperature, and volumetric soil moisture), water vapor transpiration factors (relative humidity and vapor pressure deficit), and radiation factor (solar radiation). The factors affecting sap flow on overcast and rainy days were combined into transpiration (relative humidity, solar radiation, and vapor pressure deficit), heat (air temperature and soil temperature), and soil water factor volumetric (volumetric soil moisture). On sunny days, sap flow reached the peak value 110, 80, 70 min after the hydrothermal, water vapor transpiration, and radiation factors, respectively. On overcast and rainy days, sap flow reached its peak in 10, 20, 30 min and 140, 60, 150 min, respectively before the peaks of transpiration, heat, and soil water factors.

A DFT study of the CaMg2As2 material for photovoltaic applications

The research focused on investigating the structural, elastic, electronic, optical, and thermoelectric characteristics of the CaMg2As2 compound. To inspect these properties, the density functional theory (DFT) method has been applied via the Wien2K code. The electronic analysis revealed that the CaMg2As2 compound demonstrates semiconductor behavior with an indirect band gap of 1.781 eV. Additionally, its elastic properties were examined, revealing a 1.980 % AVR, indicating a variation in elasticity depending on the direction of load or stress applied. We have also studied various optical properties of CaMg2As2, including the refractive index, extinction coefficient, electron energy loss, dielectric tensor, and optical conductivity. the absorption coefficient value is zero for energy levels below 2.60 eV, meaning there is no energy absorption by the material at lower energy levels. However, as the energy surpasses 2.60 eV, the absorption coefficient increases and shows multiple peaks. This signifies that as the incident radiation's energy increases, the material starts absorbing more energy at specific energy levels. In addition, one significant finding is that the thermal conductivity of the lattice (κL) in CaMg2As2 decreases exponentially as the temperature rises. This means that as the material gets hotter, its ability to conduct heat becomes less effective. In simple terms, the material becomes less efficient at transferring heat at higher temperatures. These findings suggest that CaMg2As2 has potential as a thermoelectric material with interesting properties that deserve further investigation.

Physicochemical, morphological, and charge carrier mobility range dielectric evaluations of Yb-doped BaCo2 W-type hexagonal ferrites for high-frequency applications

Microwave absorption materials have attracted attention due to their extensive applications in different fields. Herein, ytterbium-doped BaCo2 W-type hexaferrite nanocrystallites with a nominal composition of BaCo2YbxFe16−xO27 (x = 0.00, 0.03, 0.06, 0.09, and 0.12) were synthesized via the sol–gel method, and their physicochemical and dielectric characteristics were estimated. XRD plots revealed the pure phase structure of each prepared hexaferrite sample. The lattice constant and unit cell volume were affected by changes in the Yb concentration. The crystallite size was measured by the Debye–Scherrer formula, revealing intense crystals typically in the 18–33 nm range. FTIR spectroscopy showed multiple absorption bands from 430 to 3000 cm−1, and Raman spectroscopy revealed multiple peaks between 200 and 1000 cm−1, displaying the allocated polyhedra and symmetry. XPS spectroscopy confirmed the existence of all metal ions in the required valence state. The dielectric measurements were evaluated at frequencies from 1 to 6 GHz for all the synthesized compositions, and the material behavior was explained using the Maxwell–Wagner and Koop theories. The conduction mechanism in the hexagonal ferrites was assessed using Cole–Cole analysis. Reflection loss measurements were also conducted: the samples at x = 0.03 and x = 0.12 yielded minimal reflection losses of −60.06 and −51.69 dB at 5.5 GHz, respectively. The results demonstrate the suitability of the samples for use in microwave and high-frequency absorption applications.

VCPNET: A new dataset to benchmark vegetation carbon phenology metrics

Shifts in plant phenology associated with climate change have received unprecedented attention from land managers, policymakers, and the scientific community, with important implications for the structure and function of the biosphere. Eddy covariance (EC) has been used to measure carbon exchange between the land surface and atmosphere, which provides an opportunity to describe the seasonality of ecosystem processes. Using BASE flux products provided by the AmeriFlux network and a non-linear modeling approach, this study developed a vegetation carbon phenology (VCP) dataset, which we termed VCPNET (version 1.0). VCPNET was developed with fine spatial and temporal scales for a total of 87 EC sites (2820 site-years of data) across North America, including nine vegetation types. We extracted phenology metrics by site to provide long-term VCP metrics across these ecosystems. Analyses revealed significant differences in photosynthetic capacity and respiration rate-derived VCP metrics across the landscape, as well as differences associated with whether daily cumulative or half-hourly maximum measurements were used. Daily carbon fluxes may be more consistent in simulating phenology behavior than 30-min maximum fluxes across all vegetation types, except in sites classified as Grassland. Overall vegetation types, the seasonality of photosynthetic capacity may exert a larger control on the net carbon uptake of the ecosystem compared to the respiration rate. Thus, model-estimated photosynthesis-activated seasons may better represent true phenology, particularly the development of above- and below-ground plant biomass in tree-covered areas, which is crucial in forecasting ecosystem carbon sequestration. In addition, a nonlinear model can robustly capture day-to-day variation in carbon flux; however, precise simulation of phenological patterns with multiple peaks, typically observed in disturbed ecosystems, must be addressed during model optimization. The cross-ecosystem phenology metrics provided by VCPNET could be utilized for regional-global analysis and calibration of satellite-based vegetation indices, which accurately scale land surface phenology. Our findings provide a prospective tool for a deeper understanding of ecosystem function, allowing a direction and foundation for optimizing phenology models and algorithms and ultimately contributing to developing new ecological theories and practices in response to climate change.

Water-Stable Ln-MOF as a multi-emitting luminescent sensor for the detection of metal ions and pharmaceuticals

The development of innovative multi-emission sensors for the rapid and accurate detection of contaminants is both vital and challenging. In this study, utilizing two rigid ligands (H3ICA and H4BTEC), a series of water-stable bimetallic organic frameworks (EuTb-MOFs) were synthesized. Luminescent investigations have revealed that EuTb-MOF-1 exhibits prominent multiple emission peaks, attributed to the distinctive fluorescence characteristics of Eu(III) and Tb(III) ions. Therefore, EuTb-MOF-1 efficiently recognized various metal ions and pharmaceutical compounds through 2D decoded maps. Fe3+ and Pb2+ exhibited significant quenching effects on the luminescence of EuTb-MOF-1, which were attributed to the internal filtering effect and the interaction between Lewis basic sites within EuTb-MOF-1 and Pb2+ ions, respectively. Furthermore, EuTb-MOF-1 demonstrated high sensitivity to sulfonamide antibiotics, with detection limits of 0.037 μM for SMZ and 0.041 μM for SDZ, respectively. In addition, EuTb-MOF-1 was immobilized to prepare MOF-based test strips, enabling direct visual detection of sulfonamides as a portable sensor. With excellent water stability, multi-responsive recognition capabilities, and high sensitivity to specific analytes, EuTb-MOF-1 is a promising candidate for environmental contaminant detection in aquatic systems.

Guided Mode Evolution and Ionization Injection in Meter-Scale Multi-GeV Laser Wakefield Accelerators.

We show that multi-GeV laser wakefield electron accelerators in meter-scale, low density hydrodynamic plasma waveguides operate in a new nonlinear propagation regime dominated by sustained beating of lowest order modes of the ponderomotively modified channel; this occurs whether or not the injected pulse is linearly matched to the guide. For a continuously doped gas jet, this emergent mode beating effect leads to axially modulated enhancement of ionization injection and a multi-GeV energy spectrum of multiple quasimonoenergetic peaks; the same process in a locally doped jet produces single multi-GeV peaks with <10% energy spread. A three-stage model of drive laser pulse evolution and ionization injection characterizes the beating effect and explains our experimental results.

A revised stratigraphic model for the ∼ 1910–1835 Ma Tanami Group, the Northern Territory, Australia: Implications for exploration targeting

The Paleoproterozoic Tanami Group of the Granites—Tanami Orogen hosts a known endowment of > 20 Moz of gold mineralization across numerous deposits. Throughout the region, host lithologies impart a first-order control on the style, grade and endowment of mineralization. However, the genetic relationship and regional distribution of three regionally correlative formations (the Dead Bullock, Mount Charles and Stubbins formations) remains enigmatic. Here, we combine lithostratigraphic analysis, lithogeochemistry, detrital zircon geochronology and geophysical observations to propose a new evolutionary model for the Tanami Group. We find that the Tanami Group was deposited in a continental back-arc basin setting and developed in four stages. Package A marked the onset of the rifting of the continental Archean basement. Sedimentary rocks within Package A are dominantly felsic in composition and display a unimodal detrital zircon age population at ∼ 2530 Ma. Package B marks the onset of mafic volcanism; consequently, volcaniclastic and sedimentary rocks within Package B display a distinct mafic geochemical signature. Detritus shed from an Archean basement persisted throughout this period, and a unimodal detrital age component at ∼ 2530 Ma persists. Package C marked the waning stages of voluminous mafic volcanism across the Tanami Basin. Sedimentary volcaniclastic rocks within Package C display a mixed mafic and felsic composition. Detrital zircon age spectra record multiple peaks at ∼ 2500, 3000 and 3350 Ma, which may reflect erosion of older Archean basement domains or changes in paleo-drainage. Package D marked a significant change in the source of detritus entering the basin from dominantly Archean to Paleoproterozoic, with dominant detrital age peaks at ∼ 1860 Ma. Despite significant lithofacies variations, the presented model highlights multiple correlations between the Dead Bullock and Mount Charles formations. The Mount Charles Formation likely represents a volcanic source-proximal, high-energy depocenter. In contrast, the Dead Bullock Formation was deposited in a lower energy setting, distal to volcanic centers. These observations are important to mineral exploration. Notably, the Mount Charles Formation is distributed over a significantly greater area than previously thought, and the under-represented Hangingwall and Footwall sequences of this formation are interpreted to host significant gold mineralization at the Oberon and Groundrush deposits.

An efficient spider wasp optimizer-based tracker for enhancing the harvested power from thermoelectric generation sources

The distribution of heat at the cold and hot sides of a thermoelectric generator (TEG) is essential to its operation. Due to the inhomogeneous pattern, the TEG power-voltage (P–V) curve exhibits multiple peaks, which pose significant consequences for TEG generation. In order to increase the system conversion efficiency at this point, tracking global peak power (GPP) using a maximum power point tracker (MPPT) is crucial. The peak generation from TEG devices cannot be harvested by traditional algorithms such as hill climbing (HC) because they fall in local peaks. Therefore, the spider wasp optimizer (SWO), a new metaheristic-based tracker, is proposed in this paper to monitor the global power from TEG system operating at inhomogeneous heat distribution. In SWO, the iterative process of changing the population length aids in avoiding local solutions. The suggested SWO-based tracker is responsible for regulating the dc-dc boost converter linked to the TEG array terminals by giving its MOSFET the proper duty cycle. Seven inhomogeneous heat distributions are examined for two TEG arrays: symmetric 9 × 9 and asymmetric 10 × 15. These heat distributions are uneven row, uneven column, diagonal, outer, center, and random. The proposed approach is compared to artificial gorilla troops optimizer (GTO), gold rush optimizer (GRO), walrus optimization algorithm (WaOA), particle swarm optimizer (PSO), chef-based optimization approach (CBOA), cuckoo search (CS), Jellyfish search approach (JS), seagull optimization approach (SOA), and sine cosine approach (SCA). With regard to 9 × 9 array, the suggested SWO-tracker performed better than the published GTO method since it increased the generated power in the following scenarios: uneven row, uneven column, SN, diagonal, outer, center, and random patterns by 1.225 W, 0.4083 W, 19.5838 W, 2.4596 W, 1.394 W, and 2.4463 W, respectively. In asymmetric array, the suggested SWO performed better than all others, obtaining the least errors in relation to the Simulink GPPs of 0.016 W, 0.0822 W, 0.3615 W, 0.0603 W, 0.0569 W, 0.0081 W, and 0.0089 W. The obtained outcomes validated the proficiency and dependability of the suggested SWO-tracker in all examined cases.