Dot-Blot Hybridization for Detection of Five Cucurbit Viruses by Digoxigenin-Labelled cDNA Probes

Dot-blot hybridization was applied in this paper to detect five viruses infecting cucurbitaceous crops, Zuccini yellow mosaic virus （ZYMV）, Watermelon mosaic virus （WMV）, Cucumber mosaic virus （CMV）, Papaya ringspot viruswatermelon strain （PRSV-W） and Squash mosaic virus （SqMV）, as a good alternative assay in seed health test and epidemiological and transgenic research. Digoxigenin-labelled cDNA probes of the five viruses were synthesized by PCR with the specific primers and applied in dot-blot hybridization to detect five viruses in crude extraction of the infected leaves. And three SqMV probes of different lengths （0.55, 1.6, and 2.7 kb, respectively） were designed to investigate the effect of hybridization. The results showed that the sensitivity for detecting the crude extraction of infected leaves by ZYMV, WMV, CMV, PRSV-W, and SqMV was down to 1：160, 1：160, 1：320, 1：160, and 1：320, respectively. Three SqMV probes of different length showed no differences on the sensitivity and specificity. The digoxigenin-labelled probes prepared by PCR could be used for accurate and rapid identification of 5 viruses infecting cucurbitaceous crops with good stabilities, sensitivities, specificity, and reproducibilifies.

The Use of the PCR-Based Dot-Blot Hybridization Assay to Detect Resistance Markers to Rifampicin and Streptomycin in Mycobacterium tuberculosis Isolates from the SW Region of Cameroon

Drug sensitivity testing to establish resistance to TB drugs takes many months to arrive at. Public health physicians have difficulties with such an approach due to long wait periods and cannot use it to establish community wide prevalence as a way to understand where resistance may be emerging faster and to limit its spread. The objective of this study was to use the dot-blot hybridization technique in the detection of resistance to rifamycin (RIF) and streptomycin (SM) in South- Western Cameroon and to compare the technique with the routine culture and drug susceptibility testing for detecting resistance in a resource poor country, Cameroon. A hospital-based study was conducted at the Regional hospitals of Buea and Limbe and Tiko Central Clinic. Tuberculosis (TB) patients aged 15 to 50 (mean age: 30.50 ± 8.33 standard deviation) were recruited for the study between December 2006 and April 2007. Cultures from 59 patients were tested for rifampicin and streptomycin sensitivity by the modified proportion method and mutational analysis for rpoB codon 516 and rrs codon 513 was performed by the dot-blot hybridization technique. Of the 59 sputum samples collected (36 were males and 23 were females) came from Buea 19 (32.2%), Limbe 20 (33.9%) and Tiko 20 (33.9%) towns respectively. Amplification for the gene showed that there was (59) 100% amplification with primers used for rpoB genes and 43 (72.9%) amplification with primers used for the rrs gene. Mutational analysis demonstrated that resistance to RIF was common in females (52.1%) than males (41.7%) while 6% of the samples were indeterminate. 12 (20.3%) samples showed phenotypic and genotypic resistance to RIF compared to 34 samples (58.1%) for SM. Phenotypic resistance and genotypic susceptibility were found in 5 (8.5%) RIF and 3 (4.7%) SM compared to phenotypic susceptibility and genotypic resistance that were found in 2 (3.5%) RIF and 3(4.7%) SM. Double mutation on rpoB and rrs genes occurred in 8 (13.6%) DNA samples. Resistance to RIF and SM due to mutations on the rpoB and rrs genes respectively in the SW region was found to be high and comparable to the drug susceptibility testing by 92%, (95% CI: 75.7 - 99.1). The Dot-blot technique will be useful in rapidly assessing the effectiveness of national TB control programs in limiting the spread of resistance strains in Cameroon.

p-d Orbital Hybridization Engineered Single-Atom Catalyst for Electrocatalytic Ammonia Synthesis

The rational design of metal single-atom catalysts(SACs)for electrochemical nitrogen reduction reaction(NRR)is challenging.Two-dimensional metal-organic frameworks(2DMOFs)is a unique class of promising SACs.Up to now,the roles of individual metals,coordination atoms,and their synergy effect on the electroanalytic performance remain unclear.Therefore,in this work,a series of 2DMOFs with different metals and coordinating atoms are systematically investigated as electrocatalysts for ammonia synthesis using density functional theory calculations.For a specific metal,a proper metal-intermediate atoms p-d orbital hybridization interaction strength is found to be a key indicator for their NRR catalytic activities.The hybridization interaction strength can be quantitatively described with the p-/d-band center energy difference(Δd-p),which is found to be a sufficient descriptor for both the p-d hybridization strength and the NRR performance.The maximum free energy change(ΔG_(max))andΔd-p have a volcanic relationship with OsC_(4)(Se)_(4)located at the apex of the volcanic curve,showing the best NRR performance.The asymmetrical coordination environment could regulate the band structure subtly in terms of band overlap and positions.This work may shed new light on the application of orbital engineering in electrocatalytic NRR activity and especially promotes the rational design for SACs.

Manipulating d-d orbital hybridization induced by Mo-doped Co_(9)S_(8) nanorod arrays for high-efficiency water electrolysis

Precisely refining the electronic structure of electrocatalysts represents a powerful approach to further optimize the electrocatalytic performance.Herein,we demonstrate an ingenious d-d orbital hybridization concept to construct Mo-doped Co_(9)S_(8) nanorod arrays aligned on carbon cloth(CC)substrate(abbreviated as Mo-Co_(9)S_(8)@CC hereafter)as a high-efficiency bifunctional electrocatalyst toward water electrolysis.It has experimentally and theoretically validated that the 4d-3d orbital coupling between Mo dopant and Co site can effectively optimize the H_(2)O activation energy and lower H^(*)adsorption energy barrier,thereby leading to enhanced hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)activities.Thanks to the unique electronic and geometrical advantages,the optimized Mo-Co_(9)S_(8)@CC with appropriate Mo content exhibits outstanding bifunctional performance in alkaline solution,with the overpotentials of 75 and 234 mV for the delivery of a current density of 10 mA cm^(-2),small Tafel slopes of 53.8 and 39.9 mV dec~(-1)and long-term stabilities for at least 32 and 30 h for HER and OER,respectively.More impressively,a water splitting electrolylzer assembled by the self-supported Mo-Co_(9)S_(8)@CC electrode requires a low cell voltage of 1.53 V at 10 mA cm^(-2)and shows excellent stability and splendid reversibility,demonstrating a huge potential for affordable and scalable electrochemical H_(2) production.The innovational orbital hybridization strategy for electronic regulation herein provides an inspirable avenue for developing progressive electrocatalysts toward new energy systems.

Morphological and molecular evidence for natural hybridization between Sorbus pohuashanensis and S. discolor (Rosaceae)

In overlapping distribution areas of Sorbus pohuashanensis and S.discolor in North China(Mount Tuoliang,Mount Xiling and Mount Baihua),Sorbus indi-viduals were found with pink fruit,which have never been recorded for the flora of China.Fourteen morphological characters combined with four chloroplast DNA markers and internal transcribed spacer(ITS)were used to analyze the origin of the Sorbus individuals with pink fruits and their relationship to S.pohuashanensis and S.discolor.PCA,SDA and one-way(taxon)ANOVA of morphological characters provided convincing evidence of the hybrid ori-gin of Sorbus individuals with pink fruits based on a novel morphological character and many intermediate characters.Haplotype analysis based on four cpDNA markers showed that either S.pohuashanensis or S.discolor were maternal parents of Sorbus individuals with pink fruits.Incongru-ence of the position of Sorbus individuals with pink fruits between cpDNA and ITS in cluster trees supported by DNA sequence comparative analysis,implying former hybridiza-tion events between S.pohuashanensis and S.discolor.Mul-tiple hybridization events between S.pohuashanensis and S.discolor might have contributed to the generation of Sorbus individuals with pink fruits.This study has provided insights into hybridization between species of the same genus in sympatric areas,which is of great significance for the study of interspecific hybridization.

Cryptic diversity and rampant hybridization in annual gentians on the Qinghai-Tibet Plateau revealed by population genomic analysis

Understanding the evolutionary and ecological processes involved in population differentiation and speciation provides critical insights into biodiversity formation. In this study, we employed 29,865 single nucleotide polymorphisms(SNPs) and complete plastomes to examine genomic divergence and hybridization in Gentiana aristata, which is endemic to the Qinghai-Tibet Plateau(QTP) region. Genetic clustering revealed that G. aristata is characterized by geographic genetic structures with five clusters(West, East, Central, South and North). The West cluster has a specific morphological character(i.e., blue corolla) and higher values of FSTcompared to the remaining clusters, likely the result of the geological barrier formed by the Yangtze River. The West cluster diverged from the other clusters in the Early Pliocene;these remaining clusters diverged from one another in the Early Quaternary. Phylogenetic reconstructions based on SNPs and plastid data revealed substantial cyto-nuclear conflicts. Genetic clustering and D-statistics demonstrated rampant hybridization between the Central and North clusters,along the Bayankala Mountains, which form the geological barrier between the Central and North clusters. Species distribution modeling demonstrated the range of G. aristata expanded since the Last Interglacial period. Our findings provide genetic and morphological evidence of cryptic diversity in G. aristata, and identified rampant hybridization between genetic clusters along a geological barrier.These findings suggest that geological barriers and climatic fluctuations have an important role in triggering diversification as well as hybridization, indicating that cryptic diversity and hybridization are essential factors in biodiversity formation within the QTP region.

Enhanced and asymmetric signatures of hybridization at climatic margins: Evidence from closely related dioecious fig species

Hybridization plays a significant role in biological evolution. However, it is not clear whether ecological contingency differentially influences likelihood of hybridization, particularly at ecological margins where parental species may exhibit reduced fitnesses. Moreover, it is unknown whether future ecosystem change will increase the prevalence of hybridization. Ficus heterostyla and F. squamosa are closely related species co-distributed from southern Thailand to southwest China where hybridization, yielding viable seeds, has been documented. As a robust test of ecological factors driving hybridization, we investigated spatial hybridization signatures based on nuclear microsatellites from extensive population sampling across a widespread contact range. Both species showed high population differentiation and strong patterns of isolation by distance. Admixture estimates exposed asymmetric interspecific gene flow.Signatures of hybridization increase significantly towards higher latitude zones, peaking at the northern climatic margins. Geographic variation in reproductive phenology combined with ecologically challenging marginal habitats may promote this phenomenon. Our work is a first systematic evaluation of such patterns in a comprehensive, latitudinally-based clinal context, and indicates that tendency to hybridize appears strongly influenced by environmental conditions. Moreover, that future climate change scenarios will likely alter and possibly augment cases of hybridization at ecosystem scales.

Cryptic divergences and repeated hybridizations within the endangered “living fossil” dove tree(Davidia involucrata) revealed by whole genome resequencing

The identification and understanding of cryptic intraspecific evolutionary units(lineages) are crucial for planning effective conservation strategies aimed at preserving genetic diversity in endangered species.However, the factors driving the evolution and maintenance of these intraspecific lineages in most endangered species remain poorly understood. In this study, we conducted resequencing of 77 individuals from 22 natural populations of Davidia involucrata, a “living fossil” dove tree endemic to central and southwest China. Our analysis revealed the presence of three distinct local lineages within this endangered species, which emerged approximately 3.09 and 0.32 million years ago. These divergence events align well with the geographic and climatic oscillations that occurred across the distributional range.Additionally, we observed frequent hybridization events between the three lineages, resulting in the formation of hybrid populations in their adjacent as well as disjunct regions. These hybridizations likely arose from climate-driven population expansion and/or long-distance gene flow. Furthermore, we identified numerous environment-correlated gene variants across the total and many other genes that exhibited signals of positive evolution during the maintenance of two major local lineages. Our findings shed light on the highly dynamic evolution underlying the remarkably similar phenotype of this endangered species. Importantly, these results not only provide guidance for the development of conservation plans but also enhance our understanding of evolutionary past for this and other endangered species with similar histories.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Asymmetric orbital hybridization in Zn-doped antiperovskite Cu_(1-x)Zn_(x)NMn_(3)enables highly efficient electrocatalytic hydrogen production

Rational design of efficient and robust earth-abundant alkaline hydrogen evolution reaction(HER)catalysts is a key factor for developing energy conversion technologies.Currently,antiperovskite nitride CuNMn_(3)has garnered significant interest due to its remarkable properties such as negative/zero thermal expansion and magnetocaloric effects.However,when utilized as hydrogen evolution catalysts,it encounters large challenge resulting from excessively strong/weak interactions with adsorbed H on Mn/Cu active sites,which leads to low HER activity.In this study,we introduce an asymmetric orbital hybridization strategy in Zn-doped Cu_(1-x)Zn_(x)NMn_(3)by leveraging the localization of Zn electronic states to reconfigure the electronic structures of Cu and Mn,thereby reducing the energy barrier for water dissociation and optimizing Cu and Mn active sites for hydrogen adsorption and H_(2)production.Electrochemical evaluations reveal that Cu_(0.85)Zn_(0.15)NMn_(3)with x=0.15 demonstrates exceptional electrocatalytic activity in alkaline electrolytes.A low overpotential of 52 mV at 10 mA cm^(-2)and outstanding stability over a 150-h test period are achieved,surpassing commercial Pt/C.This research offers a novel strategy for enhancing HER performance by modulating asymmetric hybridization of electron orbitals between multiple metal atoms within a material structure.

Enhanced Redox Electrocatalysis in High‑Entropy Perovskite Fluorides by Tailoring d–p Hybridization

High-entropy catalysts featuring exceptional properties are,in no doubt,playing an increasingly significant role in aprotic lithium-oxygen batteries.Despite extensive effort devoted to tracing the origin of their unparalleled performance,the relationships between multiple active sites and reaction intermediates are still obscure.Here,enlightened by theoretical screening,we tailor a high-entropy perovskite fluoride(KCoMnNiMgZnF_(3)-HEC)with various active sites to overcome the limitations of conventional catalysts in redox process.The entropy effect modulates the d-band center and d orbital occupancy of active centers,which optimizes the d–p hybridization between catalytic sites and key intermediates,enabling a moderate adsorption of LiO_(2)and thus reinforcing the reaction kinetics.As a result,the Li–O2 battery with KCoMnNiMgZnF_(3)-HEC catalyst delivers a minimal discharge/charge polarization and long-term cycle stability,preceding majority of traditional catalysts reported.These encouraging results provide inspiring insights into the electron manipulation and d orbital structure optimization for advanced electrocatalyst.

Aqueous Supercapacitors With Wide Operative Voltage Window and Long Cycling Life Enabled by Electrolyte Hybridization Effect

Developing supercapacitors(SCs)with long cycling life and wide operative voltage window is a significant topic in the field of aqueous electrolytes.Although the design of water in salt(WIS)electrolytes has pushed the development of aqueous electrolytes to a new height,the WIS electrolytes with an operative voltage window of up to 2.5 V is still very scarce.Herein,in order to enrich the type of aqueous electrolyte with high operative voltage,tetramethylammonium trifluoromethanesulfonate(TMAOTf)based WIS electrolyte was used as a model to construct WIS based hybrid electrolyte with acetonitrile(ACN)co-solvent and LiTFSI co-solute.In view of the coordination effect of ACN and Lit on free water in TMAOTf based WIS electrolyte,the TMAt-Lit-AWIS electrolyte has the electrochemical stabilization window of up to 3.35 V.Further coupled with the commercial YP-50F electrodes,TMAt-Lit-AWIS based SCs exhibited wide operative voltage window(2.5 V),long cycling life(45,000 cycles)and good low-temperature performance(99.99%capacitance retention after 2000 cycles at20℃).The design of this hybrid electrolyte will enrich the types of aqueous hybrid electrolytes with long cycling life and wide operative voltage window.

Enhancing ^(*)CO coverage on Sm-Cu_(2)O via 4f-3d orbital hybridization for highly efficient electrochemical CO_(2) reduction to C_(2)H_(4)

The electrocatalytic conversion of CO_(2) into valuable chemical feedstocks using renewable electricity offers a compelling strategy for closing the carbon loop.While copper-based materials are effective in catalyzing CO_(2) to C_(2+)products,the instability of Cu^(+)species,which tend to reduce to Cu~0 at cathodic potentials during CO_(2) reduction,poses a significant challenge.Here,we report the development of SmCu_(2)O and investigate the influence of f-d orbital hybridization on the CO_(2) reduction reaction (CO_(2)RR).Supported by density functional theory (DFT) calculations,our experimental results demonstrate that hybridization between Sm^(3+)4f and Cu^(+)3d orbitals not only improves the adsorption of *CO intermediates and increases CO coverage to stabilize Cu^(+) but also facilitates CO_(2) activation and lowers the energy barriers for CAC coupling.Notably,Sm-Cu_(2)O achieves a Faradaic efficiency for C_(2)H_(4) that is 38%higher than that of undoped Cu_(2)O.Additionally,it sustains its catalytic activity over an extended operational period exceeding 7 h,compared to merely 2 h for the undoped sample.This research highlights the potential of fd orbital hybridization in enhancing the efficacy of copper-based catalysts for CO_(2)RR,pointing towards a promising direction for the development of durable,high-performance electrocatalysts for sustainable chemical synthesis.

Combining Ability and Heterotic Effects in Newly Developed Early Maturing and High-Yielding Maize Hybrids under Low and Recommended Nitrogen Conditions

Nitrogen (N) is a crucial nutrient vital for the growth and productivity of maize. However, excessive nitrogen application can result in numerous environmental and ecological problems, such as water pollution, biodiversity loss, and greenhouse gas emissions. Therefore, breeding maize hybrids resilient to low nitrogen conditions is crucial for sustainable agriculture, especially under low nitrogen conditions. Consequently, this study aimed to evaluate the combining ability and heterosis of maize lines, recognize promising hybrids, and study gene action controlling key traits under low and recommended N stress conditions. The half-diallel mating design hybridized seven maize inbreds, resulting in 21 F1 hybrids. These hybrids, along with two high-yielding commercial hybrids (SC10 and TWC310), were evaluated in field trials under recommended (290 kg/ha) and low N (166 kg N/ha) conditions. Significant variations were observed among assessed hybrids for all measured traits, with non-additive gene action being predominant for grain yield and its related characteristics under recommended and low N conditions. Inbred lines P105 and P106 were recognized as effective combiners for earliness, with P105 also excelling in shorter plant height and lower ear placement. In addition, P101, P102, and P104 were identified as good combiners for increasing grain yield and related attributes under low N conditions. The crosses P105 × P106 and P106 × P107 demonstrated outstanding heterotic effects for earliness, while hybrids P101 × P102 and P102 × P104 exhibited remarkable heterotic effects for grain yield low nitrogen stress conditions. These promising hybrids could be considered for commercial use after further evaluation. Strong positive correlations were found between grain yield and ear height, plant height, number of kernels per row, and 1000-grain weight, highlighting their importance for indirect selection to enhance the grain yield of maize under low N stress conditions.

Ternary Hybrid Nanofluid with First and Second Order Velocity Slips: Dual Solutions with Stability Analysis

Modeling the boundary layer flow of ternary hybrid nanofluids is important for understanding and optimizing their thermal performance,particularly in applications where enhanced heat transfer and fluid dynamics are essential.This study numerically investigates the boundary layer flow of alumina-copper-silver/water nanofluid over a permeable stretching/shrinking sheet,incorporating both first and second-order velocity slip.The mathematical model is solved in MATLAB facilitated by the bvp4c function that employs the finite difference scheme and Lobatto IIIa formula.The solver successfully generates dual solutions for the model,and further analysis is conducted to assess their stability.The findings reported that only one of the solutions is stable.For the shrinking sheet case,increasing the first-order velocity slip delays boundary layer separation and enhances heat transfer,while,when the sheet is stretched,the second-order velocity slip accelerates separation and improves heat transfer.Boundary layer separation is most likely to occur when the sheet is shrinking;however,this can be controlled by adjusting the velocity slip with the inclusion of boundary layer suction.

Multi-Objective Hybrid Sailfish Optimization Algorithm for Planetary Gearbox and Mechanical Engineering Design Optimization Problems

This paper introduces a hybrid multi-objective optimization algorithm,designated HMODESFO,which amalgamates the exploratory prowess of Differential Evolution(DE)with the rapid convergence attributes of the Sailfish Optimization(SFO)algorithm.The primary objective is to address multi-objective optimization challenges within mechanical engineering,with a specific emphasis on planetary gearbox optimization.The algorithm is equipped with the ability to dynamically select the optimal mutation operator,contingent upon an adaptive normalized population spacing parameter.The efficacy of HMODESFO has been substantiated through rigorous validation against estab-lished industry benchmarks,including a suite of Zitzler-Deb-Thiele(ZDT)and Zeb-Thiele-Laumanns-Zitzler(DTLZ)problems,where it exhibited superior performance.The outcomes underscore the algorithm’s markedly enhanced optimization capabilities relative to existing methods,particularly in tackling highly intricate multi-objective planetary gearbox optimization problems.Additionally,the performance of HMODESFO is evaluated against selected well-known mechanical engineering test problems,further accentuating its adeptness in resolving complex optimization challenges within this domain.

Sub-6GHz Assisted mmWave Hybrid Beamforming with Self-Supervised Learning

In this paper,we propose a sub-6GHz channel assisted hybrid beamforming(HBF)for mmWave system under both line-of-sight(LOS)and non-line-of-sight(NLOS)scenarios without mmWave channel estimation.Meanwhile,we resort to the selfsupervised approach to eliminate the need for labels,thus avoiding the accompanied high cost of data collection and annotation.We first construct the dense connection network(DCnet)with three modules:the feature extraction module for extracting channel characteristic from a large amount of channel data,the feature fusion module for combining multidimensional features,and the prediction module for generating the HBF matrices.Next,we establish a lightweight network architecture,named as LDnet,to reduce the number of model parameters and computational complexity.The proposed sub-6GHz assisted approach eliminates mmWave pilot resources compared to the method using mmWave channel information directly.The simulation results indicate that the proposed DCnet and LDnet can achieve the spectral efficiency that is superior to the traditional orthogonal matching pursuit(OMP)algorithm by 13.66% and 10.44% under LOS scenarios and by 32.35% and 27.75% under NLOS scenarios,respectively.Moreover,the LDnet achieves 98.52% reduction in the number of model parameters and 22.93% reduction in computational complexity compared to DCnet.

Enhancing Evapotranspiration Estimation: A Bibliometric and Systematic Review of Hybrid Neural Networks in Water Resource Management

Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET estimation.The findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological processes.These hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET estimation.The growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional methods.Despite the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data scarcity.Future research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder trust.Additionally,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world applications.Approaches such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these challenges.This study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable regions.By integrating CNNs for automatic feature extraction and leveraging hybrid architectures,HANNs offer considerable advantages for optimizing water management,particularly agriculture.Addressing challenges related to interpretability and scalability will be vital to ensuring the widespread deployment and operational success of HANNs in global water resource management.

A Novel Control Strategy Based onπ-VSG for Inter-Face Converter in Hybrid Microgrid

The rapid development of new energy power generation technology and the transformation of power electronics in the core equipment of source-grid-load drives the power system towards the“double-high”development pattern of“high proportion of renewable energy”and“high proportion of power electronic equipment”.To enhance the transient performance of AC/DC hybrid microgrid(HMG)in the context of“double-high,”aπtype virtual synchronous generator(π-VSG)control strategy is applied to bidirectional interface converter(BIC)to address the issues of lacking inertia and poor disturbance immunity caused by the high penetration rate of power electronic equipment and new energy.Firstly,the virtual synchronous generator mechanical motion equations and virtual capacitance equations are used to introduce the virtual inertia control equations that consider the transient performance of HMG;based on the equations,theπ-type equivalent control model of the BIC is established.Next,the inertia power is actively transferred through the BIC according to the load fluctuation to compensate for the system’s inertia deficit.Secondly,theπ-VSG control utilizes small-signal analysis to investigate howthe fundamental parameters affect the overall stability of the HMG and incorporates power step response curves to reveal the relationship between the control’s virtual parameters and transient performance.Finally,the PSCAD/EMTDC simulation results show that theπ-VSG control effectively improves the immunity of AC frequency and DC voltage in the HMG system under the load fluctuation condition,increases the stability of the HMG system and satisfies the power-sharing control objective between the AC and DC subgrids.

Blood-based magnetohydrodynamic Casson hybrid nanofluid flow on convectively heated bi-directional porous stretching sheet with variable porosity and slip constraints

Fluid flow through porous spaces with variable porosity has wide-range applications,notably in biomedical and thermal engineering,where it plays a vital role in comprehending blood flow dynamics within cardiovascular systems,heat transfer and thermal management systems improve efficiency using porous materials with variable porosity.Keeping these important applications in view,in current study blood-based hybrid nanofluid flow has considered on a convectively heated sheet.The sheet exhibits the properties of a porous medium with variable porosity and extends in both the x and y directions.Blood has used as base fluid in which the nanoparticles of Cu and Cu O have been mixed.Thermal radiation,space-dependent,and thermal-dependent heat sources have been incorporated into the energy equation,while magnetic effects have been integrated into the momentum equations.Dimensionless variables have employed to transform the modeled equations into dimensionless form and facilitating their solution using bvp4c approach.It has concluded in this study that,both the primary and secondary velocities augmented with upsurge in variable porous factor and declined with escalation in stretching ratio,Casson,magnetic,and slip factors along x-and y-axes.Thermal distribution has grown up with upsurge in Casson factor,magnetic factor,thermal Biot number,and thermal/space-dependent heat sources while has retarded with growth in variable porous and stretching ratio factors.The findings of this investigation have been compared with the existing literature,revealing a strong agreement among present and established results that ensured the validation of the model and method used in this work.