General Applicability Research Articles

Intelligent Trajectory Prediction Algorithm for Hypersonic Vehicle Based on Sparse Associative Structure Model

The Hypersonic Glide Vehicle (HGV) has become a focal point in military competitions among nations. Predicting the real-time trajectory of an HGV is of significant importance for aerospace defense interception and assessing enemy combat intentions. Existing prediction methods are limited by the need for large data samples and poor general applicability. To address these challenges, this paper presents a novel trajectory forecasting approach based on the Sparse Association Structure Model (SASM). The SASM can uncover the relationship among known data, transfer associative relationships to unknown data, and improve the generalization of the model. Firstly, a trajectory database is established for different maneuvering modes based on the six-degree-of-freedom motion equations and models of attack and bank angles of the HGV. Subsequently, three trajectory parameters are selected as prediction variables according to the maneuvering characteristics of the HGV. A parameters prediction model based on the SASM is then constructed to predict trajectory parameters. The SASM model demonstrates high accuracy and generalization in forecasting the trajectories of three different HGV types. Experimental results show a 50.35% reduction in prediction error and a 48.7% decrease in average processing time compared to the LSTM model, highlighting the effectiveness of the proposed method for real-time trajectory forecasting.

Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.

The application of artificial intelligence (AI) to health and health care is rapidly increasing. Several studies have assessed the attitudes of health professionals, but far fewer studies have explored the perspectives of patients or the general public. Studies investigating patient perspectives have focused on somatic issues, including those related to radiology, perinatal health, and general applications. Patient feedback has been elicited in the development of specific mental health care solutions, but broader perspectives toward AI for mental health care have been underexplored. This study aims to understand public perceptions regarding potential benefits of AI, concerns about AI, comfort with AI accomplishing various tasks, and values related to AI, all pertaining to mental health care. We conducted a 1-time cross-sectional survey with a nationally representative sample of 500 US-based adults. Participants provided structured responses on their perceived benefits, concerns, comfort, and values regarding AI for mental health care. They could also add free-text responses to elaborate on their concerns and values. A plurality of participants (245/497, 49.3%) believed AI may be beneficial for mental health care, but this perspective differed based on sociodemographic variables (all P<.05). Specifically, Black participants (odds ratio [OR] 1.76, 95% CI 1.03-3.05) and those with lower health literacy (OR 2.16, 95% CI 1.29-3.78) perceived AI to be more beneficial, and women (OR 0.68, 95% CI 0.46-0.99) perceived AI to be less beneficial. Participants endorsed concerns about accuracy, possible unintended consequences such as misdiagnosis, the confidentiality of their information, and the loss of connection with their health professional when AI is used for mental health care. A majority of participants (80.4%, 402/500) valued being able to understand individual factors driving their risk, confidentiality, and autonomy as it pertained to the use of AI for their mental health. When asked who was responsible for the misdiagnosis of mental health conditions using AI, 81.6% (408/500) of participants found the health professional to be responsible. Qualitative results revealed similar concerns related to the accuracy of AI and how its use may impact the confidentiality of patients' information. Future work involving the use of AI for mental health care should investigate strategies for conveying the level of AI's accuracy, factors that drive patients' mental health risks, and how data are used confidentially so that patients can determine with their health professionals when AI may be beneficial. It will also be important in a mental health care context to ensure the patient-health professional relationship is preserved when AI is used.

Measurement of mid-upper arm circumference to screen for childhood malnutrition: General applicability and use in special populations.

Since the development of consensus-recommended indicators for pediatric malnutrition in 2014, screening and diagnosis of pediatric malnutrition have improved, but the indicators are not always used; malnutrition continues to be underdiagnosed in some community and healthcare settings. In particular, mid-upper arm circumference (MUAC) is underused as a screening indicator for pediatric malnutrition, despite its unique advantages and usefulness in several clinical situations. In December 2022, a scientific roundtable was held to bring together several experts in pediatric malnutrition. One of the goals of the scientific roundtable was to discuss the clinical use of anthropometric measures as screening tools for pediatric malnutrition status, with a focus on the use of MUAC. This article arose from that event and is intended as an educational tool to aid clinicians in implementing MUAC measurements. In addition to describing the use of MUAC as a screening tool, the article discusses several clinical situations in which MUAC is especially useful. Additionally, the article reviews practical aspects of measuring and interpreting MUAC values, provides links to additional educational resources, and briefly reviews areas in which further research is needed regarding the use of MUAC for screening of nutrition status in children.

Translanguaging: Moving away from monolingual ESL classrooms and institutions

Translanguaging, defined as “the deployment of a speaker’s full linguistic repertoire without regard for watchful adherence to the socially and politically defined boundaries of named (and usually national and state) languages” (Otheguy et al., 2015, p. 281), has great potential to play a key role in English as a Second Language (ESL) classrooms and institutions. This article first explores the origins and historical development of the concept of translanguaging before examining more general recent developments and applications of this concept internationally and in Australia. The final section provides suggestions for how to apply some of the principles of translanguaging in the adult ESL classroom, with a particular focus on specific translanguaging practices that have been used with Direct Entry English for Academic Purposes students.

Differential effects of macrophage subtype-specific cytokines on fibroblast proliferation and endothelial cell function in co-culture system.

Macrophages are involved in several critical activities associated with tissue repair and regeneration. Current approaches in regenerative medicine are focusing on leveraging the innate immune response to accelerate tissue regeneration and improve long-term healing outcomes. Of particular interest in this regard are the currently known, four main M2 macrophage subtypes: M2interleukin (IL)-4,IL-13, M2IC, M2IL-10, M2non-selective adenosine receptor agonists (NECA) (M2IL-4,IL-13 → M2NECA). In this study, rat bone marrow-derived macrophages (M0) were polarized to each of the four subtypes M2IL-4,IL-13 → M2NECA and cultured for 72 h in vitro. Luminex assay results highlighted increased production of tissue inhibitor of metalloproteinases-1 (TIMP-1) for M2IL-4,IL-13, higher amounts of transforming growth factor-beta 1 (TGF-β1) for M2IL-10, and elevated vascular endothelial growth factor A (VEGF-A) from M2NECA. Co-culture experiments performed with M2IL-10 macrophages and L929 fibroblasts highlighted the increased production of soluble collagen within the media as well as higher amounts of collagen in the extracellular matrix. Human umbilical vein endothelial cells (HUVECs) were co-cultured with M2NECA macrophages, which demonstrated an increase in intercellular adhesion molecule (ICAM) and platelet endothelial cell adhesion molecule (PECAM), as well as increased formation of endothelial tubes. The findings of this study emphasize a critical demand for further characterization and analyses of distinct M2 subtypes and careful selection of specific macrophage populations for regeneration of specific tissue types. The current, broad classification of "M2" may be sufficient in many general tissue engineering applications, but, as conditions are constantly in flux within the microenvironment in vivo, a higher degree of specificity and control over the initial M2 subtype could result in more consistent long-term outcomes where macrophages are utilized as part of an overall regenerative strategy.

Comparison of estimation limits for quantum two-parameter estimation

Measurement estimation bounds for local quantum multiparameter estimation, which provide lower bounds on possible measurement uncertainties, have so far been formulated in two ways: by extending the classical Cramér-Rao bound (e.g., the quantum Cramér-Rao bound and the Nagaoka Cramér-Rao bound) and by incorporating the parameter estimation framework with the uncertainty principle, as in the Lu-Wang uncertainty relation. In this work, we present a general framework that allows a direct comparison between these different types of estimation limits. Specifically, we compare the attainability of the Nagaoka Cramér-Rao bound and the Lu-Wang uncertainty relation, using analytical and numerical techniques. We show that these two limits can provide different information about the physically attainable precision. We present an example where both limits provide the same attainable precision and an example where the Lu-Wang uncertainty relation is not attainable even for pure states. We further demonstrate that the unattainability in the latter case arises because the figure of merit underpinning the Lu-Wang uncertainty relation (the difference between the quantum and classical Fisher information matrices) does not necessarily agree with the conventionally used figure of merit (mean-squared error). The results offer insights into the general attainability and applicability of the Lu-Wang uncertainty relation. Furthermore, our proposed framework for comparing bounds of different types may prove useful in other settings. Published by the American Physical Society 2024

Standoff-free vaporizing foil actuator welding: Process principle, experimental validation, and mechanisms analysis

This paper introduces a novel high-velocity impact welding process: the standoff-free vaporizing foil actuator welding (standoff-free VFAW). This technique employs a new type of driving mechanism, overcoming the geometric placement constraints between the flyer plate and the target plate inherent in conventional impact welding processes. It enables welding without requiring an initial standoff distance between the two plates. The feasibility and general applicability of the proposed process were validated through experiments. The welding performance was evaluated using shear tests, peel tests, and microstructural analysis. The results indicate that the proposed process can successfully weld T2 copper to 304 stainless steel and AA5083-H112 to 304 stainless steel. Additionally, this study verified that the proposed process can achieve progressive welding, making it possible to utilize standoff-free VFAW for large-area metal welding. Furthermore, microanalysis revealed the presence of a typical wavy interface characteristic at the joint. Key parameters influencing the welding results were also explored through experiments and finite element modeling, which suggest that the boundary constraints of the workpiece play a key role in the success of standoff-free VFAW. This implies that the initiation of the small and dynamic gap between the flyer and target plates could be the potential mechanism for the proposed process. In summary, standoff-free VFAW presents simplicity and efficiency as its advantages. Moreover, the insights gained from this technique are not limited solely to vaporizing foil actuator welding (VFAW) but could also provide reference points for other high-velocity impact welding techniques.

User profiles in digitalized healthcare: active, potential, and rejecting — a cross-sectional study using latent class analysis

BackgroundThere is evidence of different use by different groups of people for general health-related applications. Yet, these findings are lacking for digitalized healthcare services. It is also unclear whether typical use patterns can be found and how user types can be characterized.MethodsThe analyses are based on data from 1 821 respondents to the Health Related Beliefs and Health Care Experiences in Germany panel (HeReCa). Digitalized healthcare services, that were used to determine the user types, include for example sick notes before/after examination and disease related training. User types were determined by latent class analysis. Individual groups were characterized using multinomial logistic regressions, taking into account socioeconomic and demographic factors as well as individual attitudes towards digitalization in the healthcare system.ResultsThree types were identified: rejecting (27.9%), potential (53.8%) and active (18.3%). Active participants were less likely to be employed, less likely to be highly educated and less skeptical of digital technologies. Potential users were the youngest, most highly-educated and most frequently employed group, with less skepticism than those who rejected. Rejecters were the oldest group, more likely to be female and of higher socio-economic status.ConclusionsSocio-demographic and socio-economic differences were identified among three user types. It can therefore be assumed that not all population groups will benefit from the trend towards digitalization in healthcare. Steps should be taken to enhance access to innovations and ensure that everyone benefits from them.

Commentary on “Nail surgery: General principles, fundamental techniques, and practical applications”

Commentary on “Nail surgery: General principles, fundamental techniques, and practical applications”

Dynamic Imaging of Electrochemically Induced Transformations in Layered Tin Chalcogenide Catalysts.

Understanding the dynamic transformation processes of electrocatalysts during electrochemical reactions is crucial for the development of advanced materials for energy conversion and storage, yet it remains a challenge. Herein, we report the real-time monitoring of the dynamic transformation of a series of layered Sn chalcogenides during electrochemical reduction using a plasmonic imaging method. Taking SnSe2 as an example, we observed a strong firework-like emission diffusing outward from SnSe2 to the surrounding solution under a negative potential. The diffusion coefficient of the observed species is indicative of Sn nanoclusters rather than smaller ions. This study also extends to SnSe and SnS2 nanosheets, demonstrating the general applicability of plasmonic imaging for probing the stability and transformation mechanism of heterogeneous catalysts in electrocatalytic reactions. These insights provide a foundational understanding for designing more stable and efficient electrocatalysts for industrial applications.

Intrinsically stretchable fully π-conjugated polymer film via fluid conjugated molecular external-plasticizing for flexible light-emitting diodes

Fully π-conjugated polymers with rigid aromatic units are promising for flexible optoelectronic devices, but their inherent brittleness poses a challenge for achieving high-performance, intrinsically stretchable fully π-conjugated polymer. Here, we are establishing an external-plasticizing strategy using semiconductor fluid plasticizers (Z1 and Z2) to enhance the optoelectronic, morphological, and stretchable properties of fully π-conjugated polymer films for flexible light-emitting diodes. The synergistic effect of hierarchical structure and optoelectronic properties of Z1 in poly(9,9-di-n-octylfluorene-alt-benzothiadiazole) (F8BT) films enable excellent stretchable deformability (~25%) and good conductivity. PLEDs based on F8BT/Z1 films show stable electroluminescence and efficiency under 15% stretch and 100 cycles at 10% strain, revealing outstanding stress tolerance. This strategy is also improving the stretchable properties of polymers like poly(9,9-di-n-octylfluorenyl-2,7-diyl) (PFO) and poly(2-methoxy-5(2′-ethyl)hexoxy-phenylenevinylene) (Super Yellow), demonstrating its general applicability. Therefore, this strategy can provide effective guidance for designing high-performance stretchable fully π-conjugated polymers films for flexible electronic devices.

McFine: python-based Monte-Carlo multi-component hyperfine structure fitting

Abstract Modelling complex line emission in the interstellar medium (ISM) is a degenerate, high-dimensional problem. Here, we present McFine, a tool for automated multi-component fitting of emission lines with complex hyperfine structure, in a fully automated way. We use Markov chain Monte Carlo (MCMC) to efficiently explore the complex parameter space, allowing for characterising model denegeracies. This tool allows for both local thermodynamic equilibrium (LTE) and radiative-transfer (RT) models. McFine can fit individual spectra and data cubes, and for cubes encourage spatial coherence between neighbouring pixels. It is also built to fit the minimum number of distinct components, to avoid overfitting. We have carried out tests on synthetic spectra, where in around 90 per cent of cases it fits the correct number of components, otherwise slightly fewer components. Typically, Tex is overestimated and τ underestimated, but accurate within the estimated uncertainties. The velocity and line widths are recovered with extremely high accuracy, however. We verify McFine by applying to a large Atacama Large Millimeter/submillimeter Array (ALMA) N2H+ mosaic of an high-mass star forming region, G316.75-00.00. We find a similar quality of fit to our synthetic tests, aside from in the active regions forming O-stars, where the assumptions of Gaussian line profiles or LTE may break down. To show the general applicability of this code, we fit CO(J = 2-1) observations of NGC 3627, a nearby star-forming galaxy, again obtaining excellent fit quality. McFine provides a fully automated way to analyse rich datasets from interferometric observations, is open source, and pip-installable.

A pH-Responsive Protein Assembly through Clustering of a Charge-Tunable Single Amino Acid Repeat.

Specific targeting of tumor cells is a key to achieving high therapeutic efficacy while minimizing off-target side effects. As a general approach to targeting diverse tumor cells, considerable attention has been paid to the tumor microenvironment, particularly its slightly acidic pH (6.5-6.8). However, existing pH-sensitive nanomaterials, based on organic polymers and proteins, often lack sufficient pH sensitivity and specificity. Here, we demonstrate a strategy to construct a pH-responsive protein assembly through clustering of a single amino acid repeat as a charge-tunable moiety. As a proof of concept, a histidine peptide with varying lengths was displayed on the surface of a ferritin assembly composed of 24 subunits by genetic fusion to a subunit. The resulting self-assembled ferritin particles, termed "pHerricle (pH-responsive ferritin particle)", were shown to exhibit a specific binding to tumor cells in response to pH changes through cooperative effects of histidine peptides. Increasing the histidine peptide length from 0 to 12 residues increased the pHerricle's cell-binding capacity by 21-fold and allowed modulation of the targetable pH range. General applicability as a tumor cell-targeting platform was shown by specific delivery of a cytotoxic cargo by the pHerricle into tumor cells of various origins in a pH-dependent manner.

Functional carbon nanodots enhance tomato tolerance to zinc deficient soils: Mechanisms and structure-function relationships

Zinc (Zn) deficiency is a global problem disorder affecting both crops and humans. Herein, modified functional carbon nanodots (MFCNs) with various structures and characteristics were developed to regulate tomato yields and Zn migration in plant–soil systems affected by Zn deficiency through structure–function relationships. Sulfur-doped FCNs (S-FCNs), nitrogen-doped FCNs (N-FCNs), and nitrogen‑sulfur co-doped FCNs (N,S-FCNs) were hydrothermally modified using FCNs as precursors. Their regulatory effects on tomatoes growing in Zn-deficient alkaline soils were studied in pot culture experiments. Specifically, 8 mg kg−1 of FCNs and S-FCNs improved tomato yields by 132 % and 108 %, respectively, compared with the control. However, N-FCNs and N,S-FCNs showed no significant effect on yield compared with the control (P < 0.05). Moreover, the application of FCNs or S-FCNs significantly improved fruit quality and nutritional value, including Zn content (by 26.3 % and 22.0 %, respectively) and naturally occurring antioxidants (by 3.37- and 2.08-fold for lycopene, 1.31- and 1.18-fold for flavonoids, and 2.28- and 1.89-fold for phenolics, respectively; P < 0.05). Although N-FCNs and N,S-FCNs increased Zn contents, they inhibited the synthesis of naturally occurring antioxidants in fruits. Zn bioaccessibility, uptake, and transportation in plant-soil systems were regulated by MFCNs through both direct and indirect mechanisms, including ionic reactions, plant physiology, and environmental effects. MFCNs regulated plant tolerance to Zn deficiency not only by affecting root activity, redox homeostasis, micronutrient balance, chelator synthesis, genetic expression, and plant photosynthesis but also by influencing rhizosphere soil properties and the microbial environment. Based on their dual role as “plant growth regulators” and “soil conditioners”, MFCNs may have general applicability in agriculture. This study highlights the behavior of MFCNs in plant-soil systems, providing innovative nanotools for enhancing Zn availability, crop stress resistance and environmental preservation in sustainable agriculture.

Review of Opportunities and Challenges for Additive Manufacturing of Steels in the Construction Industry

Abstract Additive manufacturing (AM), or 3-D printing, encompasses a range of technologies that “print” material layer by layer to create the final part. Though there is significant interest in the AM of concrete in the construction sector, opportunities for the AM of steel still need to be explored. This review focuses on the AM of low-alloy steels, stainless steels, duplex stainless steels (DSSs), precipitation-hardened (PH) stainless steels, and tool steels, highlighting the challenges and opportunities of employing AM technology for construction applications. Fusion-based AM technologies, such as wire arc additive manufacturing (WAAM), laser powder bed fusion (LPBF), and laser-directed energy deposition (LDED), are the core technologies that have been tested in the industry so far. WAAM has seen the most exploration for construction applications because of its higher deposition rate, larger build volume, and lower cost than other AM technologies. The mechanical performance of low-alloy steel, stainless steel, and tool steel shows increased tensile strengths after AM processing compared with wrought counterparts. Although AM is not economical for geometrically simple metal components or geometries, there is potential for AM to fabricate unique structural connections or joints, optimized load-bearing columns, and even entire bridges, as highlighted in this paper. AM’s digital nature (i.e., using computer-aided design (CAD) to create G-code paths for printing) can increase structural efficiency if coupled with topology optimization methods and high-strength alloys. Currently, however, general applications of AM in the industry are limited because of barriers with structural codes and standards not incorporating AM parts and AM technology barriers (i.e., limited build volumes).

Rosetta stone for the population dynamics of spiking neuron networks.

Populations of spiking neuron models have densities of their microscopic variables (e.g., single-cell membrane potentials) whose evolution fully capture the collective dynamics of biological networks, even outside equilibrium. Despite its general applicability, the Fokker-Planck equationgoverning such evolution is mainly studied within the borders of the linear response theory, although alternative spectral expansion approaches offer some advantages in the study of the out-of-equilibrium dynamics. This is mainly due to the difficulty in computing the state-dependent coefficients of the expanded system of differential equations. Here, we address this issue by deriving analytic expressions for such coefficients by pairing perturbative solutions of the Fokker-Planck approach with their counterparts from the spectral expansion. A tight relationship emerges between several of these coefficients and the Laplace transform of the interspike interval density (i.e., the distribution of first-passage times). "Coefficients" like the current-to-rate gain function, the eigenvalues of the Fokker-Planck operator and its eigenfunctions at the boundaries are derived without resorting to integral expressions. For the leaky integrate-and-fire neurons, the coupling terms between stationary and nonstationary modes are also worked out paving the way to accurately characterize the critical points and the relaxation timescales in networks of interacting populations.

Evaluation of whether commonly used risk assessment tools are applicable to women in forensic psychiatric institutions

ObjectiveBy providing a structured assessment of specific risk factors, risk assessment tools allow statements to be made about the likelihood of future recidivism in people who have committed a crime. These tools were originally developed for and primarily tested in men and are mainly based on the usual criminological background of men. Despite significant progress in the last decade, there is still a lack of empirical research on female offenders, especially female forensic psychiatric inpatients. To improve prognosis in female offenders, we performed a retrospective study to compare the predictive quality of the following risk assessment tools: PCL-R, LSI-R, HCR-20 v3, FAM, and VRAG-R. MethodData were collected from the information available in the medical files of 525 female patients who had been discharged between 2001 and 2017. We examined the ability of the tools to predict general and violent recidivism by comparing the predictions with information from the Federal Central Criminal Register. ResultsOverall, the prediction instruments had moderate to good predictive performance, and the study confirmed their general applicability to female forensic psychiatric patients. ConclusionThe LSI-R proved to be particularly valid for general recidivism, and both, LSI-R and HCR-20 v3, for violent recidivism.

Rationally designed BCR-ABL kinase inhibitors for improved leukemia treatment via covalent and pro-/dual-drug targeting strategies

BackgroundChronic Myeloid Leukemia (CML) is a blood cancer that remains challenging to cure due to drug resistance and side effects from current BCR-ABL inhibitors. There is an urgent need for novel and more effective BCR-ABL targeting inhibitors and therapeutic strategies to combat this deadly disease. MethodWe disclose an “OH-implant” strategy to improve a noncovalent BCR-ABL inhibitor, PPY-A, by adding a hydroxyl group to its scaffold. By taking advantage of this OH “hot spot”, we designed a panel of irreversible covalent kinase inhibitors and hypoxia-responsive pro-/dual-drugs, and their biological activities were studied in vitro, in cellulo and in vivo. ResultThe resulting compound B1 showed enhanced solubility and biological activity. B4 achieved sustained BCR-ABL inhibition by forming a stable covalent bond with ABL kinase. Hypoxia-responsive prodrug P1 and dual-drugs D1/D2/D3 demonstrated significant anti-tumor effects under hypoxic conditions. The in vivo studies using K562-xenografted mice showed that B1 displayed superior antitumor activity than PPY-A, while P1 and D3 offered better safety profiles alongside significant tumor control. ConclusionWe have successfully developed a chemical biology approach to convert a known noncovalent BCR-ABL inhibitor into more potent and safer inhibitors through covalent and pro-/dual-drug targeting strategies. Our “OH-implant” approach and the resulting drug design strategies have general applicability and hold promise for improvement the performance of various other reported drugs/drug candidates, thereby providing advanced medicines for disease treatment.

Synchrotron polarization with a partially random magnetic field: General approach and application to X-ray polarization from supernova remnants

Context. Diagnostics based on the polarization properties of the synchrotron emission can provide precious information on both the ordered structure and the random level of the magnetic field. While this issue has already been analyzed in the radio band, the polarization data recently obtained by the mission IXPE have shown the need to extend this analysis to the X-ray band. Aims. While our immediate targets are young supernova remnants, the scope of this analysis is wider. Our aim is to extend the analysis to particle energy distributions more complex than a power law, and to investigate a wider range of cases involving a composition of ordered and random magnetic fields. Methods. Since an analytical approach is only possible in a limited number of cases, we devised for this purpose an optimized numerical scheme, and we directly used it to investigate particle energy distributions in the form of a power law with an exponential or super-exponential cutoff. We also considered a general combination of an ordered field plus an anisotropic random component. Results. We show that the previously derived analytic formulae, valid for power-law distributions, may also be good approximations of the polarization degree in the more general case with a cutoff, as typically seen in X-rays. We explicitly analyzed the young supernova remnants SN 1006, Tycho, and Cas A. In particular, for SN 1006 we proved the consistency between the radio and X-ray polarization degrees, favoring the case of a predominantly random field with an anisotropic distribution. In addition, for the power-law case we investigated the effect of a compression on ordered and on random magnetic field components, aimed at describing the mid-age radio supernova remnants. Conclusions. This work allows a more efficient exploitation of radio and X-ray measurements of the synchrotron polarization, and is addressed to present observations with IXPE and to future projects.

Growth-Promoting Bacteria and Salicylic Acid Improve Essential Oil, Flower Yield, And Compatible Osmolyte Content of Common Yarrow (Achillea millefolium L.) Under Drought Stress

Drought is one of the major constraints on agricultural productivity in arid and semiarid regions. Coping with drought stress involves several adaptations and mitigation strategies such as the use of plant-growth promoting bacteria and salicylic acid, which was examined in this study under two levels of water regimes (well-watered as control and drought stress) in southwest Iran in 2018 and 2020 on common yarrow (Achillea millefolium). Catalase levels significantly increased in response to drought stress and salicylic acid application. Salicylic acid and combined application treatment of both bacteria also resulted in a significant increase in proline compared with the control. Different bacteria strains also resulted in a significant increase in peroxidase and superoxide dismutase when compared with the control. Drought stress, salicylic acid application, and different bacteria strains significantly reduced total protein. The use of salicylic acid and the combined application of both bacteria significantly increased the percentage of essential oil compared with the control. Moreover, 41 compounds were isolated, accounting for 92.08% of the essential oil, with more than 90.00% being volatile terpenes. The main components of yarrow essential oil were borneol (16.79%), flanderin (15.92%), cineole (14.32%), camphor (9.77%), and alpha-pinene (3.44%). In general, growth-promoting bacteria and salicylic acid application constitute an advantageous management practice for the commercial production of Achillea millefolium, increasing the nutraceutical and medicinal values of this species.