There has been an increasing awareness of indoor air quality (IAQ) management in green building designs, driven by the need to mitigate potential health risks and create sustainable and healthy indoor environments. The COVID-19 pandemic has further highlighted the critical role of ventilation and IAQ in reducing the risk of indoor airborne transmission. Governments and organisations worldwide have responded to this growing concern by implementing ventilation requirements and updating IAQ standards and guidelines. In the case of Hong Kong, a developed and densely populated city characterised by high-rise buildings, this study aims to provide a strategic framework for non-governmental agencies to address IAQ issues effectively. A comprehensive review of policies, regulations, and guidelines by international bodies and individual governments, along with an examination of the current IAQ management scheme in Hong Kong, has been conducted. Drawing inspiration from successful IAQ management strategies, the study aims to identify insights and potential pathways for the city’s future development of IAQ management strategies. Overall, this research highlights the importance of proactive IAQ management for buildings and offers a roadmap for Hong Kong’s pursuit of healthier indoor environments. Full article

Recent years have seen an increase in the popularity of exploring the correlation between groundwater and tourism as a research topic. Although previous studies have touched on certain aspects of this relationship, none has yet plunged to the heart of the matter. This Bibliometric study examines the literature on the relationship between tourism and groundwater in the overall context of economic development. The bibliometric tools VOS Viewer version 1.6.19 and R Bibliometrix were employed to analyze 104 publications selected via the Preferred Reporting Items for Systematic Reviews and Meta-Analyses diagram. The results suggest a growing interest in the subject and the need for broader and collaborative research, to fully understand these dynamics. Major contributions come from Spanish, American, Chinese, and Mexican authors, focusing on sustainability, anthropogenic impact, physical characteristics, and groundwater quality. In conclusion, this study provides an overview of the current research landscape, identifies trends and gaps, and encourages international collaboration for a better understanding of groundwater issues in the tourism context. Although our work provides very important knowledge, it should be recognized that the analysis is made only based on the Scopus-indexed literature. This restriction highlights the necessity for future research to do a more comprehensive and integrated bibliometric analysis. The array of research sources will thus definitely enhance the joint academic knowledge on that subject and lead to more inclusive and, therefore, higher-quality academic discourse. Full article

An allergy to bites from Culicoides (Diptera: Ceratopogonidae) occurs because of a hypersensitivity reaction caused by the inoculation of insect salivary antigens during the bite, resulting in immune-mediated dermatitis. To the best of our knowledge, no previous studies have focused on allergic dermatitis in donkeys in Brazil. Therefore, this study aimed to describe the epidemiological, clinicopathological, and therapeutic aspects of allergic dermatitis in donkeys and to identify the insects involved in its epidemiology. This study reported the occurrence of dermatitis in 17 animals. The clinical signs were restlessness and severe itching. Skin lesions were found on the head, depigmented areas of the muzzle and cheeks, flanks, pelvic and thoracic limbs, and the scrotal sac. The lesions were characterized by areas of alopecia with crusts accompanied by serosanguineous exudates. Histologically, the lesions were characterized as moderate superficial dermatitis with irregular epidermal acanthosis and pronounced diffuse orthokeratotic hyperkeratosis. In total, 378 Culicoides specimens were collected, with Culicoides ocumarensis Ortiz being the most abundant species. The combined application of copaiba oil and a multivitamin emulsion exhibited potential for topical treatment of allergic dermatitis caused by insect bites in donkeys. Our study revealed an association between allergic dermatitis in donkeys and Culicoides. Full article

Modified asphalt binders are still considered important in asphalt pavement. However, the comprehensive use of various modifiers is limited due to storage stability issues. Moreover, there is a scarcity of detailed analyses regarding the degree of separation for asphalt binders among each method despite the utilization of various methods to assess the storage stability of binders. Therefore, a comprehensive analysis was conducted to assess the storage stability of asphalt binder modified with a crumb rubber modifier (CRM) and styrene–isoprene–styrene (SIS), utilizing five evaluation factors following the ASTM D7173 guidelines based on four mixing methods (A: high-shear mixing method, B: low-speed agitating method, C: high-shear mixing method + low mixing method, D: low-speed agitating method + low mixing method). To produce the modified asphalt binder, the proportions of the CRM were 5% and 10% for each binder, and 10% SIS was added to all binders. The results in this study convey that (1) the addition of the modifier led to an increase in G*/sin δ with different mixing methods, but using mixing methods (C and D) for a relatively long time resulted in a lower G*/sin δ, indicating suboptimal performance; (2) through the multiple stress creep recovery (MSCR), rheological properties of J_nr and % rec exhibited trends similar to G*/sin δ evaluation, highlighting an improved elastic recovery with a higher modifier content; (3) storage stability assessment revealed consistent trends in high-shear mixing groups (A and C), while low-speed mixing groups (B and D) exhibited an elevated separation index (SI), suggesting a sensitivity to modification conditions; (4) evaluation using the MSCR method indicated that % rec with a 3.2 kPa load is effective for the sensitive assessment of binder storage stability and J_nr showed a limited sensitivity across varying loads, advocating for % rec for precise evaluation; and (5) despite permitting various tests, achieving consistent results remains challenging. Future research should explore diverse modifiers and optimal evaluation methods to enhance knowledge of binder behavior and separation dynamics. Full article

The planar cell polarity (PCP) system is essential for positioning cells in 3D networks to establish the proper morphogenesis, structure, and function of organs during embryonic development. The PCP system uses inter- and intracellular feedback interactions between components of the core PCP, characterized by coordinated planar polarization and asymmetric distribution of cell populations inside the cells. PCP signaling connects the anterior–posterior to left–right embryonic plane polarity through the polarization of cilia in the Kupffer’s vesicle/node in vertebrates. Experimental investigations on various genetic ablation-based models demonstrated the functions of PCP in planar polarization and associated genetic disorders. This review paper aims to provide a comprehensive overview of PCP signaling history, core components of the PCP signaling pathway, molecular mechanisms underlying PCP signaling, interactions with other signaling pathways, and the role of PCP in organ and embryonic development. Moreover, we will delve into the negative feedback regulation of PCP to maintain polarity, human genetic disorders associated with PCP defects, as well as challenges associated with PCP. Full article

The potential of artificial intelligence (AI) and machine learning (ML) in agriculture for improving crop yields and reducing the use of water, fertilizers, and pesticides remains a challenge. The goal of this work was to introduce Hyperfidelis, a geospatial software package that provides a comprehensive workflow that includes imagery visualization, feature extraction, zonal statistics, and modeling of key agricultural traits including chlorophyll content, yield, and leaf area index in a ML framework that can be used to improve food security. The platform combines a user-friendly graphical user interface with cutting-edge machine learning techniques, bridging the gap between plant science, agronomy, remote sensing, and data science without requiring users to possess any coding knowledge. Hyperfidelis offers several data engineering and machine learning algorithms that can be employed without scripting, which will prove essential in the plant science community. Full article

Doubly coupled designs (DCDs) have better space-filling properties between the qualitative and quantitative factors than marginally coupled designs (MCDs) which are suitable for computer experiments with both qualitative and quantitative factors. In this paper, we propose a new class of DCDs, called group doubly coupled designs (GDCDs), and provide methods for constructing two forms of GDCDs, within-group doubly coupled designs and between-group doubly coupled designs. The proposed GDCDs can accommodate more qualitative factors than DCDs, when the subdesigns for the qualitative factors are symmetric. The subdesigns of qualitative factors are not asymmetric in the existing results on DCDs, and in this paper, we construct GDCDs with symmetric and asymmetric designs for the qualitative factors, respectively. Moreover, detailed comparisons with existing MCDs show that GDCDs have better space-filling properties between qualitative and quantitative factors. Finally, the methods are particularly easy to implement. Full article

Berberis vulgaris (L.) has remarkable ethnopharmacological properties and is widely used in traditional medicine. The present study investigated B. vulgaris stem bark (Berberidis cortex) by extraction with 50% ethanol. The main secondary metabolites were quantified, resulting in a polyphenols content of 17.6780 ± 3.9320 mg Eq tannic acid/100 g extract, phenolic acids amount of 3.3886 ± 0.3481 mg Eq chlorogenic acid/100 g extract and 78.95 µg/g berberine. The dried hydro-ethanolic extract (BVE) was thoroughly analyzed using Ultra-High-Performance Liquid Chromatography coupled with High-Resolution Mass Spectrometry (UHPLC–HRMS/MS) and HPLC, and 40 bioactive phenolic constituents were identified. Then, the antioxidant potential of BVE was evaluated using three methods. Our results could explain the protective effects of Berberidis cortex EC₅₀FRAP = 0.1398 mg/mL, IC₅₀ABTS = 0.0442 mg/mL, IC₅₀DPPH = 0.2610 mg/mL compared to ascorbic acid (IC₅₀ = 0.0165 mg/mL). Next, the acute toxicity and teratogenicity of BVE and berberine—berberine sulfate hydrate (BS)—investigated on Daphnia sp. revealed significant BS toxicity after 24 h, while BVE revealed considerable toxicity after 48 h and induced embryonic developmental delays. Finally, the anticancer effects of BVE and BS were evaluated in different tumor cell lines after 24 and 48 h of treatments. The MTS assay evidenced dose- and time-dependent antiproliferative activity, which was higher for BS than BVE. The strongest diminution of tumor cell viability was recorded in the breast (MDA-MB-231), colon (LoVo) cancer, and OSCC (PE/CA-PJ49) cell lines after 48 h of exposure (IC₅₀ < 100 µg/mL). However, no cytotoxicity was reported in the normal epithelial cells (HUVEC) and hepatocellular carcinoma (HT-29) cell lines. Extensive data analysis supports our results, showing a significant correlation between the BVE concentration, phenolic compounds content, antioxidant activity, exposure time, and the viability rate of various normal cells and cancer cell lines. Full article

The energy revolution in Saudi Arabia has accelerated significantly since 2016, driven by the National Vision 2030. Significant changes to energy subsidies took place, and the renewable energy sector has seen rapid growth. The paper presents an empirical analysis of the Saudi energy transition by emphasizing the drivers of fuel consumption in KSA. It primarily attempts to explore the long-run (LR) connection between oil consumption and several economic variables such as economic growth, crude oil prices, investment, and the labor force in Saudi Arabia (KSA) from 1991 up to 2021. The paper implemented the vector error correction model (VECM) and performed different diagnostic tests to provide more evidence about the validity and robustness of the tests. The empirical findings highlighted how important the labor force, savings, GDP, and crude oil price are in determining oil consumption for KSA. The law of demand is significantly present, which negatively affects oil consumption for KSA as an oil exporting country. The results also supported the existence of a long-term direct correlation between the variables and oil consumption. Furthermore, the short-term estimation highlighted that only saving has a negative impact on oil consumption for a single lagged period. Our findings provide governments and regulators with further incentive to slow the expansion in oil consumption, as a larger labor force is demanding more oil to attain the target, faster economic growth, and increased savings are all contributing factors. Our findings are significant because they can assist policymakers, investors, and regulators in generating more efficient oil substitutes and making them affordable for the economy. Full article

This paper focuses on the current application of machine learning (ML) in enhanced oil recovery (EOR) through CO₂ injection, which exhibits promising economic and environmental benefits for climate-change mitigation strategies. Our comprehensive review explores the diverse use cases of ML techniques in CO₂-EOR, including aspects such as minimum miscible pressure (MMP) prediction, well location optimization, oil production and recovery factor prediction, multi-objective optimization, Pressure–Volume–Temperature (PVT) property estimation, Water Alternating Gas (WAG) analysis, and CO₂-foam EOR, from 101 reviewed papers. We catalog relative information, including the input parameters, objectives, data sources, train/test/validate information, results, evaluation, and rating score for each area based on criteria such as data quality, ML-building process, and the analysis of results. We also briefly summarized the benefits and limitations of ML methods in petroleum industry applications. Our detailed and extensive study could serve as an invaluable reference for employing ML techniques in the petroleum industry. Based on the review, we found that ML techniques offer great potential in solving problems in the majority of CO₂-EOR areas involving prediction and regression. With the generation of massive amounts of data in the everyday oil and gas industry, machine learning techniques can provide efficient and reliable preliminary results for the industry. Full article

The current investigations were aimed at the determination of the hydrolytic and oxidative stability of commercial pomegranate seed oils provided by four different producers, and to assess the oils’ primary quality parameters. During storage, many changes occur in oils that can significantly affect their quality. The oils were tested for acid and peroxide values, fatty acid profile, and their distribution between the sn-1,3 and sn-2 positions of triacylglycerols. The oxidative stability was also determined, and melting curves were plotted for the oils. The analyzed oils were stored for one month in a dark place at refrigerator temperature. Based on the obtained results, it was found that the acid values for most oils did not exceed the permissible level determined by the Codex Alimentarius. However, in all oils, the peroxide value exceeded the permissible level set by the standard EN ISO 3960:2017-03 and the Codex Alimentarius after the one-month storage period. The examined pomegranate seed oils were found to be valuable sources of polyunsaturated fatty acids, especially punicic acid, which was the most abundant fatty acid present in these oils. In all analyzed oils, linoleic acid predominated in the sn-2 position of the triacylglycerols. Pomegranate seed oils did not exhibit good oxidative stability, as the oxidation induction times for all tested oils were very short. The storage period significantly affected the content of the primary oxidation products and oxidative stability of the oils. Full article

The building and construction industry consumes a significant amount of natural resources alongside contributing to the generation of waste materials. Addressing the dual challenge of waste management and recycling in this sector is imperative. This study begins with a bibliometric assessment to identify waste materials used as insulation in building and construction systems. The assessment of 2627 publications revealed mattress waste materials were seldom considered. The aim of this research focuses on exploring alternative methods for repurposing mattress materials in construction, aiming to mitigate waste generation. While various materials are being recycled for building applications, this research emphasises the potential of incorporating recycled polyurethane foam (PUF) from mattresses as insulation products. A transient plane source (TPS) was employed to determine the thermal conductivity of waste mattress PUF obtained from a recycling plant in Victoria, Australia. The results exhibited promising thermal resistance, with a mean value of 0.053 Wm/K. However, optimal thermal performance was observed with increased thickness, suggesting that a thickness of 215mm aligns with industry standards for building fabric systems. Further research is required to comprehensively analyse moisture resistance and fire retardation of waste mattress materials. This paper presents key findings of current trends, limitations, and future research directions to the use of waste mattress PUF as an insulation material. Full article

Abnormal melanogenesis can lead to hyperpigmentation. Tyrosinase (TYR), a key rate-limiting enzyme in melanin production, is an important therapeutic target for these disorders. We investigated the TYR inhibitory activity of hydrolysates extracted from the muscle tissue of Takifugu flavidus (TFMH). We used computer-aided virtual screening to identify a novel peptide that potently inhibited melanin synthesis, simulated its binding mode to TYR, and evaluated functional efficacy in vitro and in vivo. TFMH inhibited the diphenolase activities of mTYR, reducing TYR substrate binding activity and effectively inhibiting melanin synthesis. TFMH indirectly reduced cAMP response element-binding protein phosphorylation in vitro by downregulating melanocortin 1 receptor expression, thereby inhibiting expression of the microphthalmia-associated transcription factor, further decreasing TYR, tyrosinase related protein 1, and dopachrome tautomerase expression and ultimately impeding melanin synthesis. In zebrafish, TFMH significantly reduced black spot formation. TFMH (200 μg/mL) decreased zebrafish TYR activity by 43% and melanin content by 52%. Molecular dynamics simulations over 100 ns revealed that the FGFRSP (T-6) peptide stably binds mushroom TYR via hydrogen bonds and ionic interactions. T-6 (400 μmol/L) reduced melanin content in B16F10 melanoma cells by 71% and TYR activity by 79%. In zebrafish, T-6 (200 μmol/L) inhibited melanin production by 64%. TFMH and T-6 exhibit good potential for the development of natural skin-whitening cosmetic products. Full article

Zika virus (ZIKV) is an emerging flavivirus that represents significant public health challenges, particularly in the Americas, and is a substantial risk to other parts of the world due to its rapid expansion and its established association with neurological disorders, including Guillain–Barré syndrome and an intrauterine fetal infection that can cause microcephaly, blindness, and other congenital neurological complications. To date, no vaccine to prevent ZIKV infections has been approved. Therefore, developing a safe and effective vaccine against this virus is a global health priority. This review analyzes the ZIKV outbreaks, as well as associated neurological complications, its genome, and immunological responses. The current vaccines in development have reported results from preclinical and clinical trials about novel approaches to obtain safer and more effective vaccines and the challenges faced by ZIKV vaccine development. Full article

Various patients with complete bilateral cleft lip and palate present with a protruded premaxilla. Several techniques have been described for correctional repair of the projection with a plethora of unsatisfactory outcomes. This poses a challenge not only for the cleft team providing care but also for the patients and their respective families. Multiple patients suffer from residual deformities after inadequate primary repair, which increase surgical, financial, and psychological burden. Premaxillary setback with posterior vomerine ostectomy and complete bilateral cleft lip repair can promote alignment of the premaxilla with the maxillary prominences. To effectively address this challenging deformity, we describe a single-stage surgical technique that includes vomerine ostectomy posterior to the vomero–premaxillary suture, bilateral gingivoperiosteoplasties with complete bilateral cleft lip repair, and primary cleft rhinoplasty. Careful surgical planning is essential for adequate matching between the length of the protruded premaxilla and the extent of ostectomy. The described technique offers several advantages for the management of complete bilateral cleft lip with a projected premaxilla. It can be applied anywhere around the world and is most beneficial in underprivileged areas where patients suffer from restricted access to healthcare, absence of presurgical orthodontics and lack of sufficient resources. Full article

Category level 6D object pose estimation aims to predict the rotation, translation and size of object instances in any scene. In current research methods, global average pooling (first-order) is usually used to explore geometric features, which can only capture the first-order statistical information of the features and do not fully utilize the potential of the network. In this work, we propose a new high-order pose estimation network (HoPENet), which enhances feature representation by collecting high-order statistics to model high-order geometric features at each stage of the network. HoPENet introduces a global high-order enhancement module and utilizes global high-order pooling operations to capture the correlation between features and fuse global information. In addition, this module can capture long-term statistical correlations and make full use of contextual information. The entire network finally obtains a more discriminative feature representation. Experiments on two benchmarks, the virtual dataset CAMERA25 and the real dataset REAL275, demonstrate the effectiveness of HoPENet, achieving state-of-the-art (SOTA) pose estimation performance. Full article

Electroosmotic experiments obtain the electroosmotic pressure coefficient of a rock sample by measuring the excitation voltage at both ends of the sample and the pressure difference caused by the excitation voltage. The electroosmotic pressure is very weak and buried in the background noise, which is the most difficult signal to measure in the dynamic-electric coupling experiment, so it is necessary to improve its signal-to-noise ratio. In this paper, for the low signal-to-noise ratio of electroosmotic pressure, the dual pressure sensor method is proposed, i.e., two pressure sensors of the same type are used to measure electroosmotic pressure. Two different data extraction methods, Fast Fourier Transform and Locked Amplification, are utilized to compare the dual pressure sensor method of this paper with the existing single pressure sensor method. The relationship between the electroosmotic pressure coefficient and the excitation frequency, mineralization, permeability, and porosity is analyzed and discussed. Full article

The burgeoning significance of environmental, social, and governance (ESG) metrics in realms such as investment decision making, corporate reporting, and risk management underscores the imperative for a robust, comprehensive solution capable of effectively capturing, representing, and analysing the multifaceted and intricate ESG data landscape. Facing the challenge of aligning with diverse standards and utilising complex datasets, organisations require robust systems for the integration of ESG metrics with traditional financial reporting. Amidst this, the evolving regulatory landscape and the demand for transparency and stakeholder engagement present significant challenges, given the lack of standardized ESG metrics in certain areas. Recently, the use of ontology-driven architectures has gained attention for their ability to encapsulate domain knowledge and facilitate integration with decision-support systems. This paper proposes a knowledge graph in the ESG metric domain to assist corporations in cataloguing and navigating ESG reporting requirements, standards, and associated data. Employing a design science methodology, we developed an ontology that serves as both a conceptual foundation and a semantic layer, fostering the creation of an interoperable ESG Metrics Knowledge Graph (ESGMKG) and its integration within operational layers. This ontology-driven approach promises seamless integration with diverse ESG data sources and reporting frameworks, while addressing the critical challenges of metric selection, alignment, and data verification, supporting the dynamic nature of ESG metrics. The utility and effectiveness of the proposed ontology were demonstrated through a case study centred on the International Financial Reporting Standards (IFRS) framework that is widely used within the banking industry. Full article

Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to the kinematics principle of the pump-controlled pitch system, the relationship between the pitch angular velocity and acceleration limit and the displacement of the hydraulic cylinder is established. Through the method of theoretical analysis, the nonlinear relationship expression between pitch angle and hydraulic cylinder displacement is obtained, and the linearization of pitch angular velocity control is realized; the formula for b₀ (the estimated value of the input gain of the system) of the pump-controlled pitch system is obtained by the method of modeling and analysis, b₀ is the key parameter for the design of the ADRC; the stability of the controller parameters is proved through the stability analysis and simulation analysis, and the design of the self-immobilizing controller with pitch angular velocity and acceleration limitation is the completed ADRC design. Finally, a joint simulation platform of AMESim and MATLAB as well as a physical experiment platform of electro-hydraulic servo pump-controlled pitch control is constructed, and the effectiveness of the proposed control method is verified through simulation and experiment. The results show that compared with the unrestricted ADRC and PID, the velocity-acceleration-limited ADRC can effectively improve the control effect of the angular velocity and acceleration of the paddle, smooth the startup process, improve the safety of the system, and have better position control accuracy and anti-jamming ability. Full article

Pisha sandstone (PS) is a special interbedded rock in the middle reaches of the Yellow River that experiences severe weathering and is loose and broken. Due to severe multiple erosion events, the Pisha sandstone region is called “the most severe water loss and soil erosion in the world” and “the ecological cancer of the earth”. As a special pozzolanic mineral, PS has the potential to be used as precursors for the synthesis of green and low-carbon geopolymer gel materials and applied in ecological restoration. This paper aims to undertake a phase review of the precursors for geopolymer gel materials. The genesis and distribution, physical and chemical characterization, erosion characteristics, and advances in the ecological restoration of PS are all summarized. Furthermore, current advances in the use of PS for the synthesis of geopolymer gel materials in terms of mechanical properties and durability are discussed. The production of Pisha sandstone geopolymer gels through the binder jetting technique and 3D printing techniques is prospected. Meanwhile, the prospects for the resource application of PS in mine rehabilitation and sustainable ecology are discussed. In the future, multifactor-driven comprehensive measures should be further investigated in order to achieve ecological restoration of the Pisha sandstone region and promote high-quality development of the Yellow River Basin. Full article

In this article, we address the problem of synchronizing multiple analog-to-digital converter (ADC) and digital-to-analog converter (DAC) chains in a multi-channel system, which is constrained by the sampling frequency and inconsistencies among the components during system integration. To evaluate and compensate for the synchronization differences, we propose a pulse compression shape-based algorithm to measure the entire delay parameter of the ADC/DAC chain, which achieves sub-sampling resolution by mapping the shape of the discrete pulse compression peak to the signal propagation delay. Moreover, owing to the matched filtering in the pulse compression process, the algorithm exhibits good noise performance and is suitable for wireless scenarios. Experiments verified that the algorithm can achieve precise measurements with sub-sampling resolution in scenarios where the signal-to-noise ratio (SNR) is greater than −10 dB. Full article

The proliferation of invasive plant species poses a significant ecological threat, necessitating effective mapping strategies for control and conservation efforts. Existing studies employing unmanned aerial vehicles (UAVs) and multispectral (MS) sensors in complex natural environments have predominantly relied on classical machine learning (ML) models for mapping plant species in natural environments. However, a critical gap exists in the literature regarding the use of deep learning (DL) techniques that integrate MS data and vegetation indices (VIs) with different feature extraction techniques to map invasive species in complex natural environments. This research addresses this gap by focusing on mapping the distribution of the Broad-leaved pepper (BLP) along the coastal strip in the Sunshine Coast region of Southern Queensland in Australia. The methodology employs a dual approach, utilising classical ML models including Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) in conjunction with the U-Net DL model. This comparative analysis allows for an in-depth evaluation of the performance and effectiveness of both classical ML and advanced DL techniques in mapping the distribution of BLP along the coastal strip. Results indicate that the DL U-Net model outperforms classical ML models, achieving a precision of 83%, recall of 81%, and F1–score of 82% for BLP classification during training and validation. The DL U-Net model attains a precision of 86%, recall of 76%, and F1–score of 81% for BLP classification, along with an Intersection over Union (IoU) of 68% on the separate test dataset not used for training. These findings contribute valuable insights to environmental conservation efforts, emphasising the significance of integrating MS data with DL techniques for the accurate mapping of invasive plant species. Full article