User-generated passwords often pose a security risk in authentication systems. However, providing a comparative substitute poses a challenge, given the common tradeoff between security and user experience. This paper integrates cryptographic methods (both asymmetric and symmetric), steganography, and a combination of physiological and behavioural biometrics to construct a prototype for a passwordless authentication system. We demonstrate the feasibility of scalable passwordless authentication while maintaining a balance between usability and security. We employ threat modeling techniques to pinpoint the security prerequisites for the system, along with choosing appropriate cryptographic protocols. In addition, a comparative analysis is conducted, examining the security impacts of the proposed system in contrast to that of traditional password-based systems. The results from the prototype indicate that authentication is possible within a timeframe similar to passwords (within 2 s), without imposing additional hardware costs on users to enhance security or compromising usability. Given the scalable nature of the system design and the elimination of shared secrets, the financial and efficiency burdens associated with password resets are alleviated. Furthermore, the risk of breaches is mitigated as there is no longer a need to store passwords and/or their hashes. Differing from prior research, our study presents a pragmatic design and prototype that deserves consideration as a viable alternative for both password-based and passwordless authentication systems. Full article

This paper proposes a quadrotor system control scheme using an intelligent–proportional–integral–differential control (I-PID)-based controller augmented with a radial basis neural network (RBF neural network) and the proposed adaptive robust term. The I-PID controller, similar to the widely utilized PID controller in quadrotor systems, demonstrates notable robustness. To enhance this robustness further, the time-delay estimation error was compensated with an RBF neural network. Additionally, an adaptive robust term was proposed to address the shortcomings of the neural network system, thereby constructing a more robust controller. This supplementary control input integrated an adaptation term to address significant signal changes and was amalgamated with a reverse saturation filter to remove unnecessary control input during a steady state. The adaptive law of the proposed controller was designed based on Lyapunov stability to satisfy control system stability. To verify the control system, simulations were conducted on a quadrotor system maneuvering along a spiral path in a disturbed environment. The simulation results demonstrate that the proposed controller achieves high tracking performance across all six axes. Therefore, the controller proposed in this paper can be configured similarly to the previous PID controller and shows satisfactory performance. Full article

Companies are increasingly focusing on sustainable business practices. Internal and external stakeholders’ expectations manifest in legal requirements, national and international standards, and market and customer expectations, among other things, must be considered. In addition to profit maximization, which is the usual target for corporate management, management must consider environmental sustainability aspects such as resource efficiency, greenhouse gas intensity, and a company’s emissions behavior. In addition, social aspects related to the company’s employees, the immediate urban environment, the situation in the supply chain, and effects on the market environment must increasingly be considered. Specifically, companies are faced with the challenge of dealing with conflicting objectives regarding the various aspects of sustainability and, if necessary, weighing them up against each other. These trade-offs must be made against the company’s socio-economic and ecological environment, corporate strategy, and sustainability goals. This paper provides an overview of current approaches and research gaps on this topic through a literature review. It highlights the lack of methods and frameworks to specifically deal with trade-offs and conflicts between goals. Full article

Efficiency in stock markets is essential for economic stability and growth. This study investigates the efficiency and herding behavior of the stock markets from the top economies of the world (known as G20 countries). We classify stock market indices using MSCI classification for the developed and emerging markets to provide a comparative examination using the latest data and by employing the robust multifractal detrended fluctuation (MFDFA) method. In addition to the full sample, the analysis uses sub-sample periods to reveal the hidden features and efficiencies of the G20 markets during the Russia–Ukraine War and COVID-19 for the first time. The findings show the availability of varied multifractality among all G20 stock markets during the overall and crisis periods, exhibit long-range correlations, and may support the fractal market hypothesis. In addition, Italy remains the least efficient, while Germany remains the most efficient stock market. The sub-sample results further reveal unevenness in the local fluctuations and resultant higher inefficiency considering the sheer magnitude and impact of crises on the G20 stock markets. However, the efficiency of developed stock markets performed better as compared to emerging markets. The study of G20 stock markets is useful and provides several implications for a wider audience. Full article

Plastics offer many advantages and are widely used in various fields. Nevertheless, most plastics derived from petroleum are slow to degrade due to their stable polymer structure, posing serious threats to organisms and ecosystems. Thus, developing environmentally friendly and biodegradable plastics is imperative. In this study, biodegradable cellulose/multi-walled carbon nanotube (MCNT) hybrid gels and films with improved ultraviolet-shielding properties were successfully prepared using cotton textile waste as a resource. It was proven that MCNTs can be dispersed evenly in cellulose without any chemical or physical pretreatment. It was found that the contents of MCNTs had obvious effects on the structures and properties of hybrid films. Particularly, the averaged transmittance of cellulose/MCNT composite films in the range of 320–400 nm (T_320–400) and 290–320 nm (T_290–320) can be as low as 19.91% and 16.09%, when the content of MCNTs was 4.0%, much lower than those of pure cellulose films (T_320–400: 84.12% and T_290–320: 80.03%). Meanwhile, the water contact angles of the cellulose/MCNT films were increased by increasing the content of MCNTs. Most importantly, the mechanical performance of cellulose/MCNT films could be controlled by the additives of glycerol and MCNTs. The tensile strength of the cellulose/MCNT films was able to reach as high as 20.58 MPa, while the elongation at break was about 31.35%. To summarize, transparent cellulose/MCNT composites with enhanced ultraviolet-shielding properties can be manufactured successfully from low-cost cotton textile waste, which is beneficial not only in terms of environmental protection, but also the utilization of natural resources. Full article

Background: Physical activity contributes to both physiological and psychosocial benefits for children and adolescents with disabilities. However, the prevalence of physical inactivity is notably higher among disabled young people compared to their healthy peers. Despite this, there is a lack of constructed knowledge structure, evolutionary path, research hotspots, and frontiers in studies related to physical activity in young people with disabilities.Methods: The literature related to the research of physical activity in children and adolescents with disabilities was retrieved from the core collection of the Web of Science. The annual publication numbers and the timing, frequency, and centrality of the co-occurrence network with respect to journals, countries, institutions, authors, references, and keywords were analyzed. Additionally, clustering analysis and burst analysis were performed on the references and keywords. All analyses were conducted using CiteSpace. Results: A total of 1308 related articles were included. The knowledge structure of research on the physical activity of disabled children and adolescents, including annual publication numbers, influencing journals, countries, institutions, authors, references, and keywords along with their respective collaborative networks, has been constructed. Furthermore, the research foundation, current hot topics, and research frontiers have been identified by analyzing references and keywords. Conclusions: Current research hotspots include interventions, therapies, and programs aimed at enhancing specific skills, as well as addressing the satisfaction of competence to improve motivation and the effectiveness of physical activity. There is also a focus on the development of scales for quantitative studies. Future directions may be toward personalized interventions or programs to enhance physical activity levels among youth with disabilities. Full article

Systemic inflammation and coronary microvascular endothelial dysfunction are essential pathophysiological factors in heart failure (HF) with preserved ejection fraction (HFpEF) that support the use of statins. The pleiotropic properties of statins, such as anti-inflammatory, antihypertrophic, antifibrotic, and antioxidant effects, are generally accepted and may be beneficial in HF, especially in HFpEF. Numerous observational clinical trials have consistently shown a beneficial prognostic effect of statins in patients with HFpEF, while the results of two larger trials in patients with HFrEF have been controversial. Such differences may be related to a more pronounced impact of the pleiotropic properties of statins on the pathophysiology of HFpEF and pro-inflammatory comorbidities (arterial hypertension, diabetes mellitus, obesity, chronic kidney disease) that are more common in HFpEF. This review discusses the potential mechanisms of statin action that may be beneficial for patients with HFpEF, as well as clinical trials that have evaluated the statin effects on left ventricular diastolic function and clinical outcomes in patients with HFpEF. Full article

Clearing and successfully characterizing ecosystem service flow paths has become a key bottleneck restricting in-depth research on the supply and demand relationships of ecosystem services. At present, although some explorations have been performed using water ecosystem services as a pioneer, the nature of its network and the fact that ecological base flow needs to be eliminated have been ignored. This study used InVEST and network models to consider ecological base flow, quantifying the supply, demand, and flow paths of freshwater ecosystem services in the Xiangjiang River Basin. The results showed that the overall distribution of the water supply in the Xiangjiang River Basin from 2000 to 2020 shows a pattern of higher supply in the south and lower supply in the north. The distribution of water demand shows higher levels in the north and lower levels in the south. The network density remains at its maximum level. The results of this study have provided a scientific basis for water resource management in river basins and improving ecological compensation mechanisms. Full article

Hemp (Cannabis sativa L.) has experienced a significant resurgence in popularity, and global interest in diversifying its use in various industries, including the food industry, is growing. Therefore, due to their exceptional nutritional value, hemp seeds have recently gained increasing interest as a valuable ingredient for obtaining high-quality foods and dietary supplements. Hemp seeds stand out for their remarkable content of quality proteins, including edestin and albumin, two distinct types of proteins that contribute to exceptional nutritional value. Hemp seeds are also rich in healthy lipids with a high content of polyunsaturated fatty acids, such as linoleic acid (omega-6), alpha-linolenic acid (omega-3), and some vitamins (vitamins E, D, and A). Polyphenols and terpenoids, in particular, present in hemp seeds, provide antimicrobial, antioxidant, and anti-inflammatory properties. This review examines the scientific literature regarding hemp seeds’ physicochemical and nutritional characteristics. The focus is on those characteristics that allow for their use in the food industry, aiming to transform ordinary food products into functional foods, offering additional benefits for the body’s health. Innovating opportunities to develop healthy, nutritionally superior food products are explored by integrating hemp seeds into food processes, promoting a balanced and sustainable diet. Full article

Safety is essential for sustainable aviation fuels (SAFs). However, evaluating SAFs’ impacts on aero-engine safety is challenging because it involves multiple space scales and the strongly coupled relationships of aero-engine components. Aiming at addressing this problem, a model-based approach is proposed to establish the relationship between the fuel-level physical properties and engine-level safety parameters. Firstly, a unified modeling criterion is proposed to consider the interrelations of aero-engine components. Under this criterion, aero-engine secondary air system (SAS) components are included in SAF safety assessment, since they have non-neglectable influences on aero-engine safety. Secondly, this paper proposes a surrogate-based iteration strategy to embed the combustor’s high-dimensional computational fluid dynamics (CFD) model into the aero-engine flow network model. Then, the proposed model-based safety assessment approach is applied to a Fischer–Tropsch hydro-processed synthesized paraffinic kerosine (F-T SPK) safety assessment case. The effects of fuel flow and blending ratio are considered. The results indicate the necessity to evaluate SAFs’ safety at the aero-engine level and consider the influences of SAS components. The proposed model-based approach may provide a preliminary screening before SAFs’ certification tests. This convenience may be beneficial for reducing the cost and accelerating SAFs’ application. Full article

Ensuring security in electronic examination systems represents a significant challenge, particularly when practical considerations dictate that most involved parties cannot be fully trusted due to self-interest. To enhance the security, we introduce auditability to e-exam systems, enabling an auditing authority to verify the system integrity. This auditability not only ensures system robustness but also creates an opportunity to grant communication between candidates and examiners, allowing for clarification on unclear questions during exams. Additionally, the implementation of attribute-based certifications ensures anonymity for both candidates and examiners throughout all stages of the exam, with the option for revocation in case of audit-detected fraud. Full article

Electrospark coatings alloyed with MoS₂ have been studied. The coatings were obtained by the following two strategies: the first consisted of pre-applying molybdenum disulfide to the treated surface and alloying with a molybdenum electrode (Mo + MoS₂ coating); the second consisted of applying a paste with a sulfur content of 33.3% to the treated surface and alloying with a molybdenum electrode (Mo + S coating). The structure, phase composition, and tribological properties of the coatings were investigated. The coatings have a complex structure consisting of an upper soft layer, a hardened white layer, a diffusion zone, and a substrate. Element analysis and cross-sectional hardness changes indicated that element diffusion occurred at the coating/substrate interface. The phase composition of the coatings is represented by BCC and FCC solid solutions on Fe, and MoS₂ is also detected. In Mo + S coatings, the molybdenum disulfide on the surface is about 8%; in Mo + MoS₂ coatings, it is 27%–46%. The obtained coatings show very good tribological properties compared to molybdenum ESA coatings. The frictional forces and coefficients are reduced by a factor of 10 and 40, depending on the test conditions. Full article

The rapid advancement of deep learning and large-scale AI models has simplified the creation and manipulation of deepfake technologies, which generate, edit, and replace faces in images and videos. This gradual ease of use has turned the malicious application of forged faces into a significant threat, complicating the task of deepfake detection. Despite the notable success of current deepfake detection methods, which predominantly employ data-driven CNN classification models, these methods exhibit limited generalization capabilities and insufficient robustness against novel data unseen during training. To tackle these challenges, this paper introduces a novel detection framework, ReLAF-Net. This framework employs a restricted self-attention mechanism that applies self-attention to deep CNN features flexibly, facilitating the learning of local relationships and inter-regional dependencies at both fine-grained and global levels. This attention mechanism has a modular design that can be seamlessly integrated into CNN networks to improve overall detection performance. Additionally, we propose an adaptive local frequency feature extraction algorithm that decomposes RGB images into fine-grained frequency domains in a data-driven manner, effectively isolating fake indicators in the frequency space. Moreover, an attention-based channel fusion strategy is developed to amalgamate RGB and frequency information, achieving a comprehensive facial representation. Tested on the high-quality version of the FaceForensics++ dataset, our method attained a detection accuracy of 97.92%, outperforming other approaches. Cross-dataset validation on Celeb-DF, DFDC, and DFD confirms the robust generalizability, offering a new solution for detecting high-quality deepfake videos. Full article

Multiscale nano/micro-structured surfaces with superhydrophobicity are abundantly observed in nature such as lotus leaves, rose petals and butterfly wings, where microstructures typically reinforce mechanical stability, while nanostructures predominantly govern wettability. To emulate such hierarchical structures in nature, various methods have been widely applied in the past few decades to the manufacture of multiscale structures which can be applied to functionalities ranging from anti-icing and water–oil separation to self-cleaning. In this review, we highlight recent advances in nano/micro-structured superhydrophobic surfaces, with particular focus on non-metallic materials as they are widely used in daily life due to their lightweight, abrasion resistance and ease of processing properties. This review is organized into three sections. First, fabrication methods of multiscale hierarchical structures are introduced with their strengths and weaknesses. Second, four main application areas of anti-icing, water–oil separation, anti-fog and self-cleaning are overviewed by assessing how and why multiscale structures need to be incorporated to carry out their performances. Finally, future directions and challenges for nano/micro-structured surfaces are presented. Full article

In recent years, research on the preservation of historical architecture has gained significant attention, where the effectiveness of semantic segmentation is particularly crucial for subsequent repair, protection, and 3D reconstruction. Given the sparse and uneven nature of large-scale historical building point cloud scenes, most semantic segmentation methods opt to sample representative subsets of points, often leading to the loss of key features and insufficient segmentation accuracy of architectural components. Moreover, the geometric feature information at the junctions of components is cluttered and dense, resulting in poor edge segmentation. Based on this, this paper proposes a unique semantic segmentation network design called MSFA-Net. To obtain multiscale features and suppress irrelevant information, a double attention aggregation module is first introduced. Then, to enhance the model’s robustness and generalization capabilities, a contextual feature enhancement and edge interactive classifier module are proposed to train edge features and fuse the context data. Finally, to evaluate the performance of the proposed model, experiments were conducted on a self-curated ancient building dataset and the S3DIS dataset, achieving OA values of 95.2% and 88.7%, as well as mIoU values of 86.2% and 71.6%, respectively, further confirming the effectiveness and superiority of the proposed method. Full article

In this study, a commercial sodium butyrate protected by a new buffer salt solution (NSB) was tested to determine whether it can be used as an antibiotic alternative in broiler production. A total of 192 1-day-old broilers were randomly allocated to three dietary treatments: soybean meal diet (CON), antibiotic diet (ANT, basal diet + 100 mg/kg aureomycin), and NSB (basal diet + 800 mg/kg NSB). The growth performance, serum anti-inflammatory cytokines, intestinal morphology, gut barrier function, antioxidative parameters, SCFAs’ content, and cecal microbiota were analyzed. The result showed that NSB significantly improved ADFI and ADG (p < 0.01), and decreased FCR (p < 0.01). Serum anti-inflammatory cytokine IL-10 was up-regulated (p < 0.01), and pro-inflammatory TNF-α was down-regulated (p < 0.05) by NSB supplementation. H&E results showed that VH and the VH/CD ratio significantly increased (p < 0.05) in the jejunum and ileum in the NSB group. Furthermore, ZO-1 (p < 0.01), claudin-1 (p < 0.01), and occludin (p < 0.05) in the jejunum and claudin-1 (p < 0.01) and mucin-2 (p < 0.05) in the ileum were significantly up-regulated in the NSB group. Additionally, SOD (p < 0.05) and the T-AOC/MDA ratio (p < 0.01) in the jejunum and SOD in the ileum were significantly increased (p < 0.05) in the NSB group. The MDA level also significantly increased (p < 0.01) in the ANT group in the jejunum. Propionic acid (p < 0.05) and butyric acid (p < 0.01) content significantly increased in the NSB group in the jejunum and ileum segments. The 16S rRNA sequencing results showed no significant difference (p > 0.05) in alpha and beta diversity among the groups. LEFSe analysis also indicated that Peptostreptococcaceae, Colidextribacter, Firmicutes, Oscillospira, and Erysipelatoclostridiaceae, which promote SCFA production (p < 0.05), were identified as dominant taxon-enriched bacterial genera in the NSB group. The Spearman correlation analysis revealed that Colidextribacter with ADFI, ADG, VH, claudin-1 (p < 0.05), and unclassified_f__Peptostreptococcaceae with ADFI, IL-10, and ZO-1 were positively correlated (p < 0.05). Furthermore, ADFI and ADG with IL-10, claudin-1, SOD, T-AOC, and butyric acid (p < 0.05), and similarly, ADG with VH (p < 0.05), showed a positive correlation. In conclusion, NSB enhanced the growth performance by improving jejunum and ileum morphology, and serum anti-inflammatory cytokines, and by regulating the intestinal barrier function and antioxidant capacity, SCFAs’ content, and cecum microbiota, showing its potential use as an alternative to antibiotics in poultry nutrition. Full article

This study explores the potential of aluminum wine bottles as a sustainable alternative to traditional glass bottles, emphasizing their recyclability and environmental advantages. It reviews the potential use of Al-Mn-Mg 3xxx alloys in beverage can bodies and examines various applications of aluminum containers in packaging, including recyclable beverage containers. The manufacturing processes for aluminum bottles, including casting, rolling, punching, and deformation techniques, are discussed in detail, with a particular focus on their impact on mechanical properties and microstructure. The preference for 1xxx aluminum alloys in impact extrusion is explained, highlighting their lower flow stress and higher formability compared to 3xxx alloys, and the microstructural changes induced by various processing steps are analyzed. Challenges related to using recycled aluminum and their effects on mechanical properties and microstructure during aluminum bottle production are also addressed. One objective is to increase the proportion of recycled alloyed material used in aluminum bottle manufacturing. Depending on the technique employed, the fraction of alloyed recycled material can vary. The percentage of recycled alloyed material (3xxx series Al alloys) in cold backward impact extrusion could be raised by 60%. High-speed blow forming could facilitate the production of aluminum bottles with a recycled alloyed material ranging from 50 to 100% of the 3xxx series aluminum can body alloys. The high-speed drawing and ironing (DWI) process can produce large-format aluminum bottles (up to 750 mL), utilizing at least 90% of the recycled 3xxx series can body stock. Furthermore, the paper discusses the importance of optimized heat treatment designs in enhancing mechanical properties and controlling microstructural evolution in alloyed aluminum materials, such as 3xxx series alloys. The study concludes with a need for further research to deepen our understanding of the metallurgical aspects of aluminum bottle manufacturing and to optimize the use of recycled aluminum in packaging solutions, with a specific focus on improving mechanical properties and microstructural integrity. This comprehensive review aims to contribute to the development of more sustainable packaging practices in the beverage industry by providing insights into the interplay between manufacturing processes, mechanical properties, and microstructure of aluminum bottles. Full article

Welding stands as a critical focus for the intelligent and digital transformation of the machinery industry, with automated laser welding playing a pivotal role in the sector’s technological advancement. The management of welding deformation in such operations is fundamental, relying on advanced analysis and prediction methods. The endeavor to accurately analyze welding deformation in practical applications is compounded by the interplay of numerous variables, a pronounced coupling effect among these factors, and a reliance on expert intuition. Thus, effective deformation control in automated laser welding operations necessitates the gathering of pre-test laser welding data to develop a predictive approach that accurately reflects real-world conditions and is characterized by improved reliability and stability. To address the technological evolution in automated laser welding, a predictive model based on neural network technology is proposed to map the intricate relationship between process variables and the resulting deformation. At the heart of this approach is the formulation of a predictive model utilizing a back-propagation neural network (BP), with an emphasis on four essential welding parameters: speed, peak power, duty cycle, and defocusing amount. The model’s predictive accuracy is then honed through the application of the whale optimization algorithm (WOA) and the differential evolutionary (DE) algorithm. Finally, extensive testing in an automated laser welding experimental setup is conducted to validate the accuracy and reliability of the proposed prediction model. It is demonstrated through these experiments that the deformation prediction model, enhanced by the DEWOA-BP neural network, accurately forecasts the relationship between laser welding parameters and the induced deformation, maintaining a prediction error margin of ±0.1mm. The model is employed to fulfill the requirements for a pre-welding quality evaluation, thereby facilitating a more calculated and informed approach to welding operations. This method of intelligent prediction is not only crucial for the intelligent transformation of laser welding but also holds significant implications for traditional machining technologies such as milling, grinding, and spraying. It offers innovative ideas and methods that are pivotal for the industrial revolution and technological advancement of the traditional machining industry. Full article

Platelets play an important role in hemostasis, and a low platelet count usually increases the risk of bleeding. Conditions in which thrombosis occurs despite low platelet counts are referred to as thrombosis with thrombocytopenia syndrome, including heparin-induced thrombocytopenia, vaccine-induced immune thrombotic thrombocytopenia, paroxysmal nocturnal hemoglobinuria, antiphospholipid syndrome, thrombotic microangiopathy (TMA), and disseminated intravascular coagulation. TMA includes thrombotic thrombocytopenic purpura, Shiga toxin-producing Escherichia coli-associated hemolytic uremic syndrome (HUS), and atypical HUS. Patients with these pathologies present with thrombosis and consumptive thrombocytopenia associated with the activation of platelets and the coagulation system. Treatment varies from disease to disease, and many diseases have direct impacts on mortality and organ prognosis if therapeutic interventions are not promptly implemented. Underlying diseases and the results of physical examinations and general laboratory tests as part of a thorough workup for patients should promptly lead to therapeutic intervention before definitive diagnosis. For some diseases, the diagnosis and initial treatment must proceed in parallel. Utilization of not only laboratory tests but also various scoring systems is important for validating therapeutic interventions based on clinical information. Full article

In the field of video quality assessment for object recognition tasks, accurately predicting the impact of different quality factors on recognition algorithms remains a significant challenge. Our study introduces a novel evaluation framework designed to address this gap by focussing on machine vision rather than human perceptual quality metrics. We used advanced machine learning models and custom Video Quality Indicators to enhance the predictive accuracy of object recognition performance under various conditions. Our results indicate a model performance, achieving a mean square error (MSE) of 672.4 and a correlation coefficient of 0.77, which underscores the effectiveness of our approach in real-world scenarios. These findings highlight not only the robustness of our methodology but also its potential applicability in critical areas such as surveillance and telemedicine. Full article

Microbial communities are not only an important indicator of soil status but also a determinant of plant nutrition and health levels. Loss of microbial community ecosystem control can directly lead to microbial disease occurrence. During the process of Yuanyang Nanqi wild imitation planting, root rot diseases frequently occur, seriously affecting their yield and quality. Via amplicon sequencing, this study mainly compared the microbial community composition between the rhizosphere soil and roots of healthy and diseased Yuanyang Nanqi with root rot. The α-diversity showed that the microbial community diversity and abundance in the roots of diseased Yuanyang Nanqi were much lower than those of those in healthy specimens, while no significant difference was found in the rhizosphere soil. The β－diversity showed that the bacterial community in the Gejiu region and the fungal community in the Honghe region were significantly different from those in other regions. The species relative abundance map showed that there was no obvious difference in microbial community composition between the rhizosphere soil and roots of healthy and diseased Nanqi, but in diseased specimens with root rot, the proportions of Pseudomonas and Fusarium increased. Based on a functional prediction analysis of FUNGuild, the results showed that the Nanqi roots were mainly pathological saprophytic type and that their rhizosphere soil was mainly saprophytic type. The microorganisms in the roots of Yuanyang Nanqi tubers with root rot were also isolated and identified through the use of the culture method. The possible pathogenic strains were tested via anti－inoculation, and Fusarium oxysporum was identified as one of the main pathogenic fungi of Nanqi root rot, which was consistent with the amplicon sequencing results. These results will help us understand the change trend of microbial communities in healthy and diseased plants and analyze the pathogens involved, the pathogenesis, and the beneficial microorganisms, which would provide a theoretical basis for effective biological control. Full article

Active mounting systems have become more prevalent in recent years to effectively mitigate structure-induced vibration across the automobile chassis. This trend is particularly evident in engine mounts. Considerable research has been dedicated to this approach owing to its potential to enhance the quietness and travel comfort of automobiles. However, prior research has concentrated on a limited spectrum of specific vibrations and noise control or has been restricted to vertical vibration control. This article describes the modeling, analysis, and control of a source structure employing a multidirectional active mounting system designed to closely simulate the position and direction of an actual automobile engine mount. A piezoelectric stack actuator is connected in series to an elastic (rubber) mount to form an active mount. The calculation of the secondary force required for each active mount is achieved through the application of harmonic excitation forces. The control signal can also reduce vibrations caused by destructive interference with the input signal. Furthermore, horizontal oscillations can be mitigated by manipulating the parameters via dynamic interconnections of the source structure. We specifically examined the level of vibration reduction performance in the absence of a vertical active element operation and determined whether the control is feasible. Simulation outcomes demonstrate that this active mount, which operates in both the vertical and horizontal directions, effectively mitigates excitation vibrations. Furthermore, a simulation was conducted to mitigate the vibrations caused by complex signals (AM and FM signals) and noise. This was achieved by monitoring the system response using an adaptive filter NLMS algorithm. Adaptive filter simulations demonstrate that the control efficacy degrades in response to complex signals and noise, although the overall relaxation trend remains unchanged. Full article