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Abstract Background Advance care planning is an important part of palliative care. Public acceptance is a prerequisite for the widespread development and implementation of advance care planning. However, little is known about the level of public’s acceptance and influencing factors of advance care planning across different life cycles. Methods A cross-sectional study in mainland China was conducted from June 20 to August 31, 2022. We used multi-stage sampling strategy to recruit participators. A stepwise linear regression analysis was used to examine the influencing factors in different life cycles (nonage, mature age, middle age and old age). Results The final sample size was 18,002. The average acceptance score of advance care planning of the public throughout the entire life cycle was 64.03. The average score in nonage was 67.13, which is the highest. The average score in mature age was 63.87, in middle age was 63.51, and in old age was 63.54. Multiple linear stepwise regression results indicated that death education support level, well-being index, neighbor relations, health literacy, family social status, and siblings were influencing factors in nonage. Medical insurance, injury events, multiple properties, death education support level, health literacy, family social status, neighbor relation, social support, family health, media contact, and well-being index were influencing factors in mature age. In middle age, region, living alone, depression, debt, houses, death education support level, health literacy, social support, and family social status were influencing factors. In old age, injury event, death education support level, neighbor relation, well-being index, siblings and children were influencing factors. Conclusions This study is the first to compare the Chinese people with different life cycles. It found that the public’s acceptance and influencing factors of advance care planning varied across different life cycles. Governments and health care personnel should emphasize autonomy and initiate advance care planning based on different life cycles and individual approaches, then introduce appropriate public health policies into newer and broader fields.

Abstract Spinal cord injury (SCI) is a debilitating condition characterized by significant sensory, motor, and autonomic dysfunctions, leading to severe physical, psychological, and financial burdens. The current therapeutic approaches for SCI show limited effectiveness, highlighting the urgent need for innovative treatments. MicroRNAs (miRNAs) like miR-10b-5p are known to play pivotal roles in gene expression regulation and have been implicated in various neurodegenerative diseases, including SCI. Polypyrimidine tract binding protein 1 (PTBP1) has also been associated with neural injury responses and recovery. This study aims to explore the interaction between miR-10b-5p and PTBP1 in the context of SCI, hypothesizing that miR-10b-5p regulates PTBP1 to influence SCI pathogenesis and recovery using a rat model of SCI and lipopolysaccharide (LPS)-induced PC12 cells. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to measure miR-10b-5p levels, revealing its low expression in SCI rats. We then assessed neurological function, histopathological changes, and spinal cord water content. We found that administering the agomiR-10b-5p significantly improved neurological function and decreased the spinal cord water content and normal motor neuron loss in SCI rats. Additionally, we explored the functions of miR-10b-5p in LPS-treated PC12 cells. Our results showed that miR-10b-5p repressed LPS-stimulated apoptosis, inflammation, and oxidative stress in PC12 cells. PTBP1 was predicted as a potential target gene of miR-10b-5p using the TargetScan database. Pulldown and luciferase reporter assays further demonstrated that miR-10b-5p binds to the 3’ untranslated region (UTR) of PTBP1. RT-qPCR revealed that miR-10b-5p negatively modulated PTBP1 expression both in vivo and in vitro. Furthermore, rescue assays indicated that miR-10b-5p alleviated SCI in rats and LPS-triggered injury in PC12 cells by downregulating PTBP1. We also investigated the regulation of miR-10b-5p and PTBP1 on the transforming growth factor-beta 1 (TGF-β1)/small mother against decapentaplegic (Smad3) pathway. We found that miR-10b-5p targeted PTBP1 to repress TGF-β1 decay and facilitated TGF-β1/Smad3 pathway activation. In conclusion, our results demonstrate that miR-10b-5p alleviates SCI by repressing TGF-β1 decay and inducing TGF-β1/Smad3 pathway activation through PTBP1 downregulation. This study provides novel insights into potential targeted therapy plans for SCI.

The Duvernay Formation in Canada is one of the major oil and gas source formations in the Western Canadian Sedimentary Basin, located at its deepest point. While it demonstrates promising development potential, challenges arise in the urgent need for integration of geology and engineering models, as well as in optimizing sweet spots, particularly as infill wells and pads become central operational objectives for the shale gas field. A lack of the geomechanical understanding of shale gas reservoirs presents a significant obstacle in addressing these challenges. To overcome this, we implemented data acquisition and prepared historical models and profiles, resulting in an extended high-resolution geological and reservoir property model with a fine grid system. Subsequently, a 3D full-field multi-scale geomechanical model was constructed for the main district by integrating seismic data (100 m), geological structures (km), routine logs (m), core data (cm), and borehole imaging (0.25 m), following a well-designed workflow. The predicted fracturability index (brittleness) ranges from 0.6 to 0.78, and a lower horizontal stress difference (STDIFF) is anticipated in the target formation, Upper Duvernay_D, making it a favorable candidate for hydraulic fracturing treatment. Post-analysis of the multi-disciplinary models and various data types provides guidelines for establishing a specific big database, which serves as the foundation for production performance analysis and aggregate sweet spot analysis. Fourteen geological and geomechanical candidate parameters are selected for the subsequent sweet spot analysis. This study highlights the effectiveness of multi-scale geomechanical modeling as a tool for the integration of multi-disciplinary data sources, providing a bridge between geological understanding and future field development decisions. The workflows also offer a data-driven framework for selecting parameters for sweet spot analysis and production dynamic analysis.

Germline variations in the DNA polymerase genes, POLE and POLD1, can lead to a hereditary cancer syndrome that is characterized by frequent gastrointestinal polyposis and multiple primary malignant tumors. However, because of its rare occurrence, this disorder has not been extensively studied. In this report, we present the case of a 22-year-old female patient who had been diagnosed with gastrointestinal polyposis, breast fibroadenoma, multiple primary colorectal cancers, and glioblastoma (grade IV) within a span of 4 years. Next-generation sequencing analysis revealed a germline variant in POLD1 (c.1816C>A; p.L606M). In silico analysis using protein functional predicting software, including SIFT, Polyphen, GERP++, and CADD, further confirmed the pathogenicity of POLD1 p.L606M (classified as ACMG grade Class 4). In line with polymerase deficiency, both rectal cancer and glioblastoma tissues exhibited a high tumor mutation burden, with 16.9 muts/Mb and 347.1 muts/Mb, respectively. Interestingly, the patient has no family history of cancer, and gene examination of both parents confirms that this is a de novo germline variant. Therefore, molecular screening for POLD1 may be necessary for patients with such a cancer spectrum, regardless of their family history.

Purpose: The driver mutations of gliomas have been identified in cerebrospinal fluid (CSF). Here we compared the concordance between CSF and tumor tissue for integrated diagnosis in gliomas using next-generation sequencing (NGS) to evaluate the feasibility of CSF detection in gliomas.Patients and methods: 27 paired CSF/tumor tissues of glioma patients were sequenced by a customized gene panel based on NGS. All CSF samples were collected through lumbar puncture before surgery. Integrated diagnosis was made by analysis of histology and tumor DNA molecular pathology according to the 2021 WHO classification of the central nervous system tumors.Results: A total of 24 patients had detectable circulating tumor DNA (ctDNA) and 22 had at least one somatic mutation or chromosome alteration in CSF. The ctDNA levels varied significantly across different ages, Ki-67 index, magnetic resonance imaging signal and glioma subtypes (p < 0.05). The concordance between integrated ctDNA diagnosis and the final diagnosis came up to 91.6% (Kappa, 0.800). We reclassified the clinical diagnosis of 3 patients based on the results of CSF ctDNA sequencing, and 4 patients were reassessed depending on tumor DNA. Interestingly, a rare IDH1 R132C was identified in CSF ctDNA, but not in the corresponding tumor sample.Conclusion: This study demonstrates a high concordance between integrated ctDNA diagnosis and the final diagnosis of gliomas, highlighting the practicability of NGS based detection of mutations of CSF in assisting integrated diagnosis of gliomas, especially glioblastoma.

The success of viscoelastic-surfactant (VES) acid in heterogeneous carbonate reservoirs depends on the wormholes propagation and diverting performance of acid. However, with the continuous propagation of wormholes in the high-permeability zone, the highly viscous spent acid enters the low-permeability zone under the pressure difference, thus affecting the wormholes propagation and diverting performance of acid in the low-permeability zone, which has been neglected in recent studies. Therefore, in this paper, the rheological model of acid is modified by considering the velocity of VES acid viscosity increase, and a two-scale continuous model was established. Based on this model, the diverting process is described, and reservoir connectivity, permeability contrast, and velocity of acid viscosity increase are used to investigate the influence of spent acid on wormholes propagation and diverting performance of acid in the low-permeability zone. The results show that the formation of wormholes in the high-permeability zone makes a pressure difference between the high-permeability zone and the low-permeability zone. The high viscous spent acid flows from the high permeability layer to the low permeability layer under the pressure difference, thus inhibiting the wormholes propagation and diverting performance of acid in the low-permeability zone of heterogeneous carbonate reservoirs. The influence degree of spent acid is 30.6% when the permeability contrast is 3, and the influence degree decreases with the enhancement of heterogeneity. At permeability contrasts greater than 10, there is almost no effect. The velocity of acid viscosity increase affects the diverting performance of acid, and the faster the viscosity increase, the farther the highly viscous zone formed in a short time, the better its diverting performance. In the VES acid system commonly used in carbonate acidizing, the maximum difference of diverting performance is 4.25 times. The parallel coreflood experiments overestimate the diverting performance of VES acid by about 20%. When selecting the diverting technology for acidizing treatment, the diverting acid system with higher diverting performance in the laboratory experiments or diverting technology with stronger diverting performance can be appropriately selected. In addition, the velocity of spent VES acid viscosity increase is a significant parameter affecting the acid diverting performance. In the low calcite content reservoir or dolomite reservoir, the spent acid viscosity increases relatively slowly due to the slower reaction rate, which will reduce the diverting performance in the reservoir.

Abstract Radial drilling‐fracturing is an innovative fracturing technology that achieves superior stimulation effects. This paper develops a model for radial drilling‐fracturing in shale reservoirs, which can predict fracture initiation pressure and failure mode of shale. Compared with published models, this model additionally considers shale hydration and inclinations of boreholes and reservoir. Then, the influences of 7 factors are studied and main conclusions are as follows. First, with the angle between radial borehole and formation strike increasing, matrix failure pressure declines only around 90° and 270°. Bedding tensile failure pressure ascends and then falls back. Bedding shear failure pressure rapidly descends, then reaches a plateau, and finally rebounds. A small or large angle is favorable for bedding tensile failure. Shale tends to crack with bedding shear failure under a moderate angle and with matrix failure only at 90° and 270°. Second, with the enlargement of azimuth difference between the radial borehole and main wellbore, matrix failure pressure periodically fluctuates, forming an inverted W‐shape curve. Bedding tensile failure pressure and bedding shear failure pressure both ascend, then slide downward, and finally rise again. Besides, a small azimuth difference inclines shale to bedding shear failure, and the other failure modes tend to occur when azimuth difference is around 90°. Third, pressures required for all failure modes descend as the dip of shale formation increases. However, the difference in descending rate leads to that the increase of dip angle can incline shale to bedding shear failure. Besides, pressures required for bedding tensile failure and matrix failure decline linearly with the increasing reservoir temperature. Temperature has no impact on bedding shear failure. Hence, matrix failure and bedding tensile failure are more prone to occur in the high‐temperature reservoir. The research provides a reference for field applications of radial drilling‐fracturing in the shale reservoir.

Using current Embedded Discrete Fracture Models (EDFM) to predict the productivity of fractured wells has some drawbacks, such as not supporting corner grid, low precision in the near wellbore zone, and disregarding the heterogeneity of conductivity brought by non-uniform sand concentration. An EDFM is developed based on the corner grid, which enables high efficient calculation of the transmissibility between the embedded fractures and matrix grids, and calculation of the permeability of each polygon in the embedded fractures by the lattice data of the artificial fracture aperture. On this basis, a coupling method of local grid refinement (LGR) and embedded discrete fracture model is designed, which is verified by comparing the calculation results with the Discrete Fracture Network (DFN) method and fitting the actual production data of the first hydraulically fractured well in Iraq. By using this method and orthogonal experimental design, the optimization of the parameters of the first multi-stage fractured horizontal well in the same block is completed. The results show the proposed method has theoretical and practical significance for improving the adaptability of EDFM and the accuracy of productivity prediction of fractured wells, and enables the coupling of fracture modeling and numerical productivity simulation at reservoir scale. Key words: hydraulic fracturing, grid refinement, embedded discrete fracture method, reservoir numerical simulation, productivity prediction, parameters optimization

Abstract The oil reservoir of Mishrif Formation is of strong heterogeneity vertically and laterally, and its single‐well production rate after conventional acidizing is low and declines fast. Therefore, we intend to carry out the pilot test on diverting acid fracturing so as to improve the stimulation effect of acid fracturing by enlarging the lateral and vertical stimulation range. In this paper, a series of experimental studies (eg, rock mechanics, acid rheology, acid‐rock reaction kinetics, and full‐diameter core etching diversion) were carried out to deal with the reservoir characteristics and stimulation demand of Mishrif Formation, the principal oil reservoir in Halfaya Oilfield in Iraq, the Middle East. It is shown that calcite content of Mishrif Formation reservoir is higher than 95%, indicating the strong acid dissolution. As for rock mechanics, the characteristics of “low Young's modulus and high Poisson's ratio” are presented, and the stress‐strain curves show certain elastic‐plastic characteristics. Additionally, a large number of wormholes appear on the surface of the full‐diameter cores after acid etching, so it is necessary to consider the serious filtration of acidizing fluid near the wellbore. The mechanical strength of rock plates decreases after acid etching, so it is recommended to adopt and optimize the closed acidizing technology so as to avoid excessive etching. Furthermore, the self‐support flow conductivity of etched fractures is weak, so it is recommended to adopt the sand fracturing or the combined stimulation technology of acid fracturing + sand fracturing to improve the reservoir stimulation effects.

AbstractRadial drilling-fracturing, the combination of radial drilling and hydraulic fracturing, can guide fractures toward the target area and effectively enhance the recovery of the low permeable reservoir. In this paper, based on the stress superposition principle, we establish an analytical model to predict fracture initiation pressure (FIP) and the shale failure mode for radial drilling-fracturing applied in shale formations. In contrast with the former studies, this model can additionally consider the failure from shale beddings and is more applicable in the shale reservoir. The model classifies the shale failure into three modes and, respectively, gives the criterion for each failure mode. Then, a series of sensitivity analyses is conducted by examining effects of various parameters. By analyzing the variation characteristic of the initiation pressures required for three failure modes, the main conclusions are as follows. Firstly, matrix failure and shear failure along bedding tend to take place when the azimuth of radial borehole is moderate. Small and large azimuths are favorable for the occurrence of tensile failure along bedding. Secondly, a high ratio of horizontal in situ stress predisposes shale to generate matrix failure, and bedding tensile failure and bedding shear failure are apt to occur when the ratio of horizontal in situ stress is low. Thirdly, with the increasing intersection angle of the radial borehole wall and bedding plane, the failure mode apt to occur changes from bedding tensile failure to bedding shear failure and then to matrix failure. Fourthly, shale prefers to yield bedding shear failure under a small Biot coefficient and generate the other two failure modes when Biot coefficient is large. Fifthly, permeability coefficient virtually has no influence on the failure mode of shale. The research clarifies the fracture initiation characteristics of radial drilling-fracturing in shale formations and provides a reference for the field application of radial drilling-fracturing.

Radial drilling-fracturing, the combination of the hydraulic fracturing and radial borehole, is a technology that can guide the hydraulic fractures to directionally propagate and efficiently develop low permeability reservoir. In this paper, an analytical model of two radial boreholes (a basic research unit) is established to predict fracture initiation pressure (FIP) from one particular radial borehole and the interference between radial boreholes when the hydraulic fracturing is guided by multi-radial boreholes. The model is based on the stress superposition principle and the maximum tensile stress criterion. The effects of in situ stress, wellbore pressure, and fracturing fluid percolation are considered. Then, sensitivity analysis is performed by examining the impact of the intersection angle between radial boreholes, the depth difference between radial boreholes, the radius of radial boreholes, Biot coefficient, and the number of radial boreholes. The results show that FIP declines with the increase of radial boreholes number and the decrease of intersection angle and depth difference between radial boreholes. Meanwhile, the increase of radial borehole number and the reduction of intersection angle and depth difference strengthen the interference between radial boreholes, which conduce to the formation of the fracture network connecting radial boreholes. Besides, FIP declines with the increase of radial borehole radius and the decrease of Biot coefficient. Large radius and low Biot coefficient can enlarge the influence range of additional stress field produced by radial boreholes, enhance the mutual interference between radial boreholes, and guide fracture growth between radial boreholes. In hydraulic fracturing design, in order to reduce FIP and strengthen the interference between radial boreholes, the optimization design can be carried out by lowering intersection angle, increasing radius and number of boreholes, and reducing the depth difference between boreholes when the conditions permit. The research clarifies the interference between radial boreholes and provides the theoretical basis for optimizing radial boreholes layout in hydraulic fracturing guided by multi-radial boreholes.

Ransomware encrypts victim’s files or locks users out of the system. Victims will have to pay the attacker a ransom to decrypt and regain access to the user files. Petya targets individuals and companies through email attachments and download links. NotPetya has worm-like capabilities and exploits EternalBlue and EternalRomance vulnerabilities. Protection methods include vaccination, applying patches, et cetera. Challenges faced to combat ransomware includesocial engineering, outdated infrastructures, technological advancements, backup issues, and conflicts of standards. ThreeLevel Security (3LS) is a solution to ransomware that utilizes virtual machines along with browser extensions to perform ascan, on any files that the user wishes to download from the Internet. The downloaded files would be sent over a cloud server relay to a virtual machine by a browser extension. Any changes to the virtual machine after downloading the file would be observed, and if there were a malfunction in the virtual machine, the file would not be retrieved to the user’s system.

Individual tree segmentation is essential for many applications in city management and urban ecology. Light Detection and Ranging (LiDAR) system acquires accurate point clouds in a fast and environmentally-friendly manner, which enables single tree detection. However, the large number of object categories and occlusion from nearby objects in complex environment pose great challenges in urban tree inventory, resulting in omission or commission errors. Therefore, this paper addresses these challenges and increases the accuracy of individual tree segmentation by proposing an automated method for instance recognition urban roadside trees. The proposed algorithm was implemented of unmanned aerial vehicles laser scanning (UAV-LS) data. First, an improved filtering algorithm was developed to identify ground and non-ground points. Second, we extracted tree-like objects via labeling on non-ground points using a deep learning model with a few smaller modifications. Unlike only concentrating on the global features in previous method, the proposed method revises a pointwise semantic learning network to capture both the global and local information at multiple scales, significantly avoiding the information loss in local neighborhoods and reducing useless convolutional computations. Afterwards, the semantic representation is fed into a graph-structured optimization model, which obtains globally optimal classification results by constructing a weighted indirect graph and solving the optimization problem with graph-cuts. The segmented tree points were extracted and consolidated through a series of operations, and they were finally recognized by combining graph embedding learning with a structure-aware loss function and a supervoxel-based normalized cut segmentation method. Experimental results on two public datasets demonstrated that our framework achieved better performance in terms of classification accuracy and recognition ratio of tree.

As artificial intelligence (AI) advances rapidly, it has been incorporated into formal education to facilitate subject-based learning. Integration of AI technologies to support learning requires teachers to intentionally design AI-assisted learning. However, there have been a limited number of empirical studies investigating teachers' behavioural intentions to design AI-assisted learning. To explore the predictors of teachers' behavioural intentions to design AI-assisted learning and examine the structural relationships among these factors, the authors constructed a structural model of AI literacy, Technological Pedagogical Content Knowledge (TPACK), technostress, school support, teacher agency, teacher autonomy and behavioural intentions. Data from 312 K-12 in-service teachers in China were analysed. The results suggest that TPACK, school support, teacher agency and teacher autonomy positively predict teachers' behavioural intentions to design AI-assisted learning. However, AI literacy and technostress were not statistically associated with teachers' behavioural intentions. On the other hand, TPACK significantly mediated AI literacy and teachers' behavioural intentions.

While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs about computer programming at middle school level. Second, the study aimed to understand how students' epistemic beliefs predict their computational thinking disposition and computer programming self-efficacy. A total of 406 middle school students completed a survey consisting of three research instruments: the Computer Programming Epistemic Belief Inventory (CPEBI), the Computational Thinking Scale (CTS), and the Computer Programming Self-Efficacy Scale (CPSES). The results indicated that the epistemic belief of "uncertainty" was a significant and positive predictor of the "abstraction" and "generalization" dimensions of computational thinking dispositions. In addition, the belief of "complexity" was an antecedent to three dimensions of computational thinking, namely, "algorithmic thinking," "evaluation," and "generalization." Only the "evaluation" dimension of CT disposition had significant and positive relationships with "programming self-efficacy." The roles of "uncertainty" and "complexity" of computer programming epistemic beliefs are discussed. Implications and suggestions for future computer programming education, especially for young students, are provided.

"Research Findings": This study incorporates teacher vitality, efficacy, and engagement with lesson design practice in which teachers can particularly encounter challenges from technology integration that calls for design thinking. Using a structural equation modeling approach, this study explores the relationships among teachers' design thinking engagement (DTE), efficacy in two types of technological pedagogical content knowledge (TPACK) called pedagogical content knowledge (PCK) and technological pedagogical content knowledge (TPCK), and design vitality (DV). A survey containing measurements for teachers' DTE, PCK efficacy, TPCK efficacy, and DV was delivered to 408 Chinese early childhood teachers. Reliability and validity of the instruments were attained through confirmatory factor analysis. Results indicated that teachers' DTE was statistically significant in explaining teachers' perceived PCK and TPCK efficacy, as well as perceived DV. Teachers' perceived TPCK efficacy significantly predicts DV. However, no significant prediction was found for teachers' perceived PCK efficacy to DV. "Practice or Policy": To ensure teachers with character strength as designers who face technology integration challenges, it is important for teacher development program to highlight teachers' proximal processes as designers structured with emotional, cognitive, and behavioral processes that can be manifested through design activities of "Empathize", "Define", "Ideate", "Prototype", and "Test".

The purposes of this study were to explore students' learning performance, knowledge construction, and behavioral patterns in computer-supported collaborative learning (CSCL) online discussions with/without using Form+Theme+Context (FTC) model guidance scaffolding in visual imagery education. In the online learning activities, the control group did not use the FTC model guidance scaffolding, while the experimental group did. This study employed quantitative content analysis and sequential analysis to investigate the discussion content and behavioral patterns of 63 students from a private university in Taiwan during online discussion learning activities. Results showed that the learning performance of the students in the experimental group outperformed that of students in the control group. Moreover, the study revealed that the two groups of students were primarily sharing or comparing information during discussion. More behaviors of exploring opinions and concepts and communicating or constructing knowledge among group members were observed in the experimental group. Secondly, students in the experimental group participated more in knowledge construction than did students in the control group, and their behavioral patterns were more diverse. Accordingly, this study shows that incorporating the FTC model into learning with sufficient guidance from the instructor could be useful for improving students' visual imagery analysis abilities.

The molecular structure of the title compound, [Sn2(C10H13)4(C14H20)Cl2], is a binuclear centrosymmetric complex, in which the Sn atoms are four-coordinated by three C atoms and one Cl atom in a distorted tetrahedral geometry.

Arbuscular mycorrhizal fungi (AMF) and rhizobia play a pivotal role in enhancing crop productivity, shaping microbial community structure, and improving soil quality, making them key components for sustainable ecosystem development. The symbiotic relationship between AMF and rhizobia is crucial for facilitating efficient biological nitrogen fixation and nutrient absorption, thereby reducing the dependence on chemical fertilizers and promoting sustainable agricultural practices. The findings of various studies, however, indicate that soil environment can impede the symbiotic relationship between AMF and rhizobia. We conducted a comprehensive meta-analysis of 158 articles from 1980 to 2022 to explore the synergistic interactions in legume–AMF–rhizobium systems and the potential mechanisms underlying this synergism. Our findings revealed that the inoculation with AMF and/or rhizobia significantly (p < 0.001) increased legume plant nitrogen content, phosphorus content, shoot biomass, yield, AMF colonization rate, and the number and weight of nodules compared to uninoculated controls (effect size d > 0). Moreover, there was a substantial synergistic effect between AMF and rhizobia (p < 0.001). Nevertheless, soil salinity stress, drought stress, and pH stress could hinder the positive effects of inoculation treatments, possibly due to the plant trade-off strategies under abiotic stress conditions. This research may potentially lead to new solutions for sustainable agricultural systems amidst the challenges posed by global climate change. [ABSTRACT FROM AUTHOR]