Search Results (89)

The leaf surface micromorphology and the size of the stomatal complex of hybrids in the eighth seed generation from the crossing of ×Trititrigia cziczinii × Elymus farctus (f11814) on the wheat-like wheat-wheatgrass hybrid w107 were investigated by performing scanning electron microscopy of frozen samples (cryoSEM). The micromorphological characteristics of the paternal plants (w107) were dominant in the hybrid leaves. Costal long cells with silicified wavy walls, characteristic of w107 but absent in the mother plants f11814 and E. farctus, were observed in all hybrid samples examined. Conversely, shield-shaped prickles, a characteristic feature of E. farctus, were retained only in some hybrids. In addition, the maternal feature of Ω-shaped junctions of long epidermal cells in the intercostal zone was completely absent in hybrids. Quantitative parameters of the stomatal apparatus showed a weak correlation with micromorphological markers. Stomatal density on the adaxial side was inversely correlated with stomatal size, while variation in these parameters on the abaxial side occurred independently. The prevalence of paternal micromorphological traits in the hybrids seems to be a consequence of the elimination of genetic material from E. farctus, analogous to the loss of chromosomes from wild species observed in other distant crosses. Full article

Background: Chronic pain is prevalent among the elderly and significantly affects their quality of life (QoL). Pain intensity scales are crucial tools in evaluating the severity of pain and tailoring management strategies. This study investigates the relationship between various pain intensity scales and QoL among elderly patients with chronic pain, highlighting the implications for nursing practice. Methods: A cross-sectional study was conducted with 150 elderly patients (aged 65 and above) in Riyadh, Saudi Arabia. Participants were assessed using the Numeric Rating Scale (NRS), Visual Analog Scale (VAS), and McGill Pain Questionnaire (MPQ) alongside the 36-Item Short-Form Health Survey (SF-36) to evaluate QoL. Data analysis involved Pearson correlation and multiple regression to explore the association of pain intensity on QoL. Results: All pain scales showed significant negative correlations with QoL. The MPQ exhibited a significant association, suggesting its comprehensive nature captures the multidimensional association of pain more effectively. Regression analysis identified pain intensity, age, and duration of chronic pain as significant predictors of reduced QoL. Conclusions: The findings emphasize the importance of selecting appropriate pain assessment tools that reflect the complex nature of pain in elderly patients. Implementing comprehensive pain assessments like the MPQ can enhance individualized care strategies and potentially improve the QoL in this population. This study underscores the role of nurses in optimizing pain management approaches tailored to the elderly. Full article

This paper investigates the feasibility of downscaling within high-dimensional Lorenz models through the use of machine learning (ML) techniques. This study integrates atmospheric sciences, nonlinear dynamics, and machine learning, focusing on using large-scale atmospheric data to predict small-scale phenomena through ML-based empirical models. The high-dimensional generalized Lorenz model (GLM) was utilized to generate chaotic data across multiple scales, which was subsequently used to train three types of machine learning models: a linear regression model, a feedforward neural network (FFNN)-based model, and a transformer-based model. The linear regression model uses large-scale variables to predict small-scale variables, serving as a foundational approach. The FFNN and transformer-based models add complexity, incorporating multiple hidden layers and self-attention mechanisms, respectively, to enhance prediction accuracy. All three models demonstrated robust performance, with correlation coefficients between the predicted and actual small-scale variables exceeding 0.9. Notably, the transformer-based model, which yielded better results than the others, exhibited strong performance in both control and parallel runs, where sensitive dependence on initial conditions (SDIC) occurs during the validation period. This study highlights several key findings and areas for future research: (1) a set of large-scale variables, analogous to multivariate analysis, which retain memory of their connections to smaller scales, can be effectively leveraged by trained empirical models to estimate irregular, chaotic small-scale variables; (2) modern machine learning techniques, such as FFNN and transformer models, are effective in capturing these downscaling processes; and (3) future research could explore both downscaling and upscaling processes within a triple-scale system (e.g., large-scale tropical waves, medium-scale hurricanes, and small-scale convection processes) to enhance the prediction of multiscale weather and climate systems. Full article

Much work has been dedicated to the quest to determine the structure–activity relationship in synthetic brassinosteroid (BR) analogs. Recently, it has been reported that analogs with phenyl or benzoate groups in the alkyl chain present activities comparable to those shown by natural BRs, depending on the nature of the substituent in the aromatic ring. However, as it is well known that the activity depends on the structure of the whole molecule, in this work, we have synthesized a series of compounds with the same substituted benzoate in the alkyl chain and a hydroxyl group at C3. The main goal was to compare the activities with analogs with -OH at C2 and C3. Additionally, a molecular-docking study and molecular dynamics simulations were performed to establish a correlation between the experimental and theoretical results. The synthesis of eight new BR analogs was described. All the analogs were fully characterized by spectroscopical methods. The bioactivity of these analogs was assessed using the rice lamina inclination test (RLIT) and the inhibition of the root and hypocotyl elongation of Arabidopsis thaliana. The results of the RLIT indicate that at the lowest tested concentration (1 × 10⁻⁸ M), in the BR analogs in which the aromatic ring was substituted at the para position with methoxy, the I and CN substituents were more active than brassinolide (50–72%) and 2–3 times more active than those analogs in which the substituent group was F, Cl or Br atoms. However, at the highest concentrations, brassinolide was the most active compound, and the structure–activity relationship changed. On the other hand, the results of the A. thaliana root sensitivity assay show that brassinolide and the analogs with I and CN as substituents on the benzoyl group were the most active compounds. These results are in line with those obtained via the RLIT. A comparison of these results with those obtained for similar analogs that had a hydroxyl group at C2 indicates the importance of considering the whole structure. The molecular-docking results indicate that all the analogs adopted a brassinolide-like orientation, while the stabilizing effect of the benzoate group on the interactions with the receptor complex provided energy binding values ranging between −10.17 and −13.17 kcal mol⁻¹, where the analog with a nitrile group was the compound that achieved better contact with the amino acids present in the active site. Full article

Background and Objectives: Migraine is a leading cause of disability worldwide, with complex pathophysiological mechanisms involving oxidative and nitrosative stress. Recent research suggests that Indole-3-Propionic Acid (IPA) may have a neuroprotective role in reducing nitrosative stress. This study aims to elucidate the roles of IPA and nitrosative stress biomarkers in migraine patients, focusing on their potential as therapeutic targets. Materials and Methods: This cross-sectional, case-control study included 57 migraine patients and 30 healthy controls. Patients were categorized into episodic migraine (EM) and chronic migraine (CM) groups. Socio-demographic and clinical characteristics were documented through structured interviews. Validated scales such as the Visual Analog Score (VAS), Headache Impact Test 6 (HIT-6), Migraine Disability Assessment Test (MIDAS), Migraine 24 h Quality of Life Scale (24 h QoL), Mini-Mental State Examination (MMSE), and Migraine Attacks–Subjective Cognitive Impairments Scale (Mig-SCog) were administered. Venous blood samples were collected, and serum levels of IPA, Nitric Oxide (NO), Nitric Oxide Synthase (NOS), and Peroxynitrite (ONOO⁻) were measured using ELISA and spectrophotometric methods. Results: Significant differences in serum IPA and NO levels were observed between migraine patients and controls. Specifically, higher serum IPA levels were found in the EM group, while higher serum NO levels were observed in the CM group. Elevated NO levels correlated with increased migraine attack frequency. Conversely, serum IPA levels showed a negative correlation with attack frequency, suggesting a protective role. Specifically, NO levels were positively correlated with the number of painful days, NSAID usage, VAS scores, HIT-6 scores, and MIDAS scores, while negatively correlated with 24 h QoL scores. Conclusions: The study highlights the significant involvement of IPA and nitrosative stress in migraine pathophysiology. Elevated IPA levels, particularly in EM patients, suggest its potential neuroprotective role. These findings underscore the importance of targeting oxidative and nitrosative stress pathways in developing effective migraine therapies. Full article

Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming and epithelial–mesenchymal transition (EMT) were investigated with explorative shotgun proteomics complemented by a Random Forest (RF) machine-learning approach. Deep and superficial tumor regions and distant-site non-tumor samples from the same patients (n = 16) were analyzed. Among the 2009 proteins analyzed, 91 proteins, including 23 novel potential CRC hallmarks, showed significant quantitative changes. In addition, a 98.4% accurate classification of the three analyzed tissues was obtained by RF using a set of 21 proteins. Subunit E1 of 2-oxoglutarate dehydrogenase (OGDH-E1) was the best classifying factor for the superficial tumor region, while sorting nexin-18 and coatomer-beta protein (beta-COP), implicated in protein trafficking, classified the deep region. Down- and up-regulations of metabolic checkpoints involved different proteins in superficial and deep tumors. Analogously to immune checkpoints affecting the TME, cytoskeleton and extracellular matrix (ECM) dynamics were crucial for EMT. Galectin-3, basigin, S100A9, and fibronectin involved in TME–CRC–ECM crosstalk were found to be differently variated in both tumor regions. Different metabolic strategies appeared to be adopted by the two CRC regions to uncouple the Krebs cycle and cytosolic glucose metabolism, promote lipogenesis, promote amino acid synthesis, down-regulate bioenergetics in mitochondria, and up-regulate oxidative stress. Finally, correlations with the Dukes stage and budding supported the finding of novel potential CRC hallmarks and therapeutic targets. Full article

In the realm of digital transformation, effective leadership and motivation are pivotal for organisations navigating the complexities of today’s systems. This study explores the intersection of intrinsic motivation and mental well-being among mature students—an analogy that sheds light on strategies applicable to organisational contexts. In developed nations like the UK, mental health for mature students is increasingly recognised as a crucial component of their educational journey. Mature students, who typically enrol in higher education after an educational gap and upon turning 21, often face specific challenges that can impact their mental well-being while pursuing academic goals. The primary objective of our study was to assess the relationship between intrinsic motivation and the mental well-being of mature students. The study included 248 full-time undergraduate mature students enrolled in private higher education institutions in the UK. These participants were 21 years and older. The research employed two measurement scales: the four-item Intrinsic Motivation Scale, adapted from Jaramillo, and the Warwick–Edinburgh Mental Well-Being Scale. Data collection utilised online Google Forms with multiple choice self-report formatted questions, and our analysis involved both descriptive and inferential statistics. Our research revealed a significant positive correlation between variables of intrinsic motivation and mental well-being. Confirmatory factor analysis (CFA) results confirmed the construct in the model. The results indicated that intrinsic motivation significantly predicts mental well-being among mature students (Cohen’s effect size value, f² = 0.54). Recognising and addressing the unique difficulties individuals encounter and providing appropriate support can enhance their well-being and contribute to the overall success of the higher education community. Full article

The integration of urban agriculture into cityscapes necessitates a comprehensive understanding of multiple engineering and environmental factors, including urban fabric, building configurations, and dynamic energy and material flows. In contrast to rural settings, urban areas introduce complexities such as hygrothermal fluctuations, variable sunlight exposure and shadow patterns, diverse plant dimensions and shapes, and material interception. To address these challenges, this study presents an open-source Digital Twin model based on the use of a geographical information system (GIS) for near-real-time solar radiation mapping. This methodology aims to optimize crop productivity, enhance resilience, and promote environmental sustainability within urban areas and enables the near-time mapping of the salient features of different portions of the city using available open data. The work is structured into two main parts: (i) definition of the GIS-based Digital Twin model for mapping microclimatic variables (in particular solar radiation) to support sustainable urban agriculture design and (ii) application of the model to the city of Milan to verify its replicability and effectiveness. The key findings are connected to the possibility to integrate open data (solar radiation) with measurements in situ (illuminance and data referred to the specific crops, with related conversion coefficient) to develop a set of maps helpful for urban farmers but also for designers dealing with the synergy between buildings and urban farms. Initially tested on a neighborhood of Milan (Italy), the model will be applied in the Singapore context to verify analogies and differences. This correlation facilitates a more practical and straightforward examination of the relationships between solar irradiation and illuminance values of natural sunlight (involving both incident and diffuse light). The consistency of measurements allows for the precise documentation of these fluctuations, thereby enhancing the understanding of the influence of solar radiation on perceived luminance levels, particularly in urban environments characterized by diverse contextual factors such as vegetation, nearby structures, and geographical positioning. Full article

The article approaches ‘landscape architecture’, insisting on the term ‘architecture’ as describing landscape formations accepted as structured systems of composed, perceptual elements presenting organizational and aesthetic value. The central idea of this proposal refers to the key concept that design systems do not copy reality in its full complicated substance; they simply cannot manage to represent and work with the complex totality of the real surrounding world. They rather design abstract formational elements that ‘schematize’ reality and create composing syntactic systems, composing ‘languages’. It was in this context that modern 20th-century garden designers insisted on the comparison of landscape design approaches with architectural abstract building plans or abstract early 20th century-paintings. However, analogous correlations may also be regarded in the opposite orientation. Thus, contemporary architectural projects are often described as ‘landscape formations’ in a period of environmental sensitivity combined with enlarged topological awareness; the latter presents earth bas-relief as a convincing metaphor of topological mathematical transformations in general, associated with computational ‘animate’ design. Nevertheless, the principal aim of the article is firstly to insist on the interchangeable approaches of hard-scape architectural design and green-scape design in terms of analogous abstract and schematized formations. Moreover, the present article intends to propose a possible didactic strategy of landscape design for architects or students in schools of architecture and for attendees already accustomed to building or hard-scape urban design. This design didactic strategy is principally founded on the concept that common abstract ‘schematized’ formations underlie all those practices: landscape design as well as building and urban design. Full article

The present review focuses on the recent studies carried out in passive micromixers for understanding the hydrodynamics and transport phenomena of miscible liquid–liquid (LL) systems in terms of pressure drop and mixing indices. First, the passive micromixers have been categorized based on the type of complexity in shape, size, and configuration. It is observed that the use of different aspect ratios of the microchannel width, presence of obstructions, flow and operating conditions, and fluid properties majorly affect the mixing characteristics and pressure drop in passive micromixers. A regime map for the micromixer selection based on optimization of mixing index (MI) and pressure drop has been identified based on the literature data for the Reynolds number (Re) range (1 ≤ Re ≤ 100). The map comprehensively summarizes the favorable, moderately favorable, or non-operable regimes of a micromixer. Further, regions for special applications of complex micromixer shapes and micromixers operating at low Re have been identified. Similarly, the operable limits for a micromixer based on pressure drop for Re range 0.1 < Re < 100,000 have been identified. A comparison of measured pressure drop with fundamentally derived analytical expressions show that Category 3 and 4 micromixers mostly have higher pressure drops, except for a few efficient ones. An MI regime map comprising diffusion, chaotic advection, and mixed advection-dominated zones has also been devised. An empirical correlation for pressure drop as a function of Reynolds number has been developed and a corresponding friction factor has been obtained. Predictions on heat and mass transfer based on analogies in micromixers have also been proposed. Full article

In the period 2022–2023, an analysis of fourteen phenotypic traits was conducted across 192 maize accessions in the Aral region of Xinjiang. The Shannon–Wiener diversity index was employed to quantify the phenotypic diversity among the accessions. Subsequently, a comprehensive evaluation of the index was performed utilizing correlation analysis, principal component analysis (PCA) and cluster analysis. The results highlighted significant findings: (1) A pronounced diversity was evident across the 192 maize accessions, accompanied by complex interrelationships among the traits. (2) The 14 phenotypic traits were transformed into 3 independent indicators through principal component analysis: spike factor, leaf width factor, and number of spikes per plant. (3) The 192 materials were divided into three groups using cluster analysis. The phenotypes in Group III exhibited the best performance, followed by those in Group I, and finally Group II. The selection of the three groups can vary depending on the breeding objectives. This study analysed the diversity of phenotypic traits in maize germplasm resources. Maize germplasm was categorised based on similar phenotypes. These findings provide theoretical insights for the study of maize accessions under analogous climatic conditions in Alar City, which lay the groundwork for the efficient utilization of existing germplasm as well as the development and selection of new varieties. Full article

This paper leverages turbulence theory from physics to examine the similarities and differences between financial market volatility and turbulent phenomena on a statistical physics level. By drawing analogies between the dynamics of financial markets and fluid turbulence, an innovative analytical framework has been developed to enhance our understanding of the complexity inherent in financial markets. The research methodology involves a comparative analysis of several national stock market indices and simulated turbulent velocity time series, with a particular focus on key statistical properties such as probability distributions, correlation structures, and power spectral densities. Furthermore, a financial market capital flow model has been established, and corresponding solutions have been proposed. Through computational simulations and data analysis, it was discovered that financial market volatility shares some statistical characteristics with turbulence, yet there are significant differences in the shape of probability distributions and the timescales of correlations. This indicates that although financial markets exhibit patterns similar to turbulence, as a multivariate-driven complex system, their behavioral patterns do not completely correspond to natural turbulence phenomena, highlighting the limitations of directly applying turbulence theory to financial market analysis. Additionally, the study explores the use of Bézier curves to simulate market volatility and, based on these analyses, formulates trading strategies that demonstrate practical applications in risk management. This research provides fresh perspectives for the fields of financial market theory and econophysics, offering new insights into the complexity of financial markets and the prevention and management of financial risks. Full article

(1) Introduction: Despite documented clinical and pain discrepancies between male and female osteoarthritis (OA) patients, the underlying mechanisms remain unclear. Synovial myofibroblasts, implicated in synovial fibrosis and OA-related pain, offer a potential explanation for these sex differences. Additionally, interleukin-24 (IL24), known for its role in autoimmune disorders and potential myofibroblast production, adds complexity to understanding sex-specific variations in OA. We investigate its role in OA and its contribution to observed sex differences. (2) Methods: To assess gender-specific variations, we analyzed myofibroblast marker expression and IL24 levels in synovial tissue samples from propensity-matched male and female OA patients (each n = 34). Gene expression was quantified using quantitative polymerase chain reaction (qPCR). The association between IL24 expression levels and pain severity, measured by a visual analog scale (VAS), was examined to understand the link between IL24 and OA pain. Synovial fibroblast subsets, including CD45-CD31-CD39- (fibroblast) and CD45-CD31-CD39+ (myofibroblast), were magnetically isolated from female patients (n = 5), and IL24 expression was compared between these subsets. (3) Results: Females exhibited significantly higher expression of myofibroblast markers (MYH11, ET1, ENTPD2) and IL24 compared to males. IL24 expression positively correlated with pain severity in females, while no correlation was observed in males. Further exploration revealed that the myofibroblast fraction highly expressed IL24 compared to the fibroblast fraction in both male and female samples. There was no difference in the myofibroblast fraction between males and females. (4) Conclusions: Our study highlights the gender-specific role of myofibroblasts and IL24 in OA pathogenesis. Elevated IL24 levels in females, correlating with pain severity, suggest its involvement in OA pain experiences. The potential therapeutic implications of IL24, demonstrated in autoimmune disorders, open avenues for targeted interventions. Notwithstanding the limitations of the study, our findings contribute to understanding OA’s multifaceted nature and advocate for future research exploring mechanistic underpinnings and clinical applications of IL24 in synovial myofibroblasts. Additionally, future research directions should focus on elucidating the precise mechanisms by which IL24 contributes to OA pathology and exploring its potential as a therapeutic target for personalized medicine approaches. Full article

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates quantum spiking neural networks (QSNN) and quantum long short-term memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conducted a comparative analysis of our model against existing quantum models, including quantum neural networks (QNNs), QLSTM, QSNN and their classical counterparts, elucidating its unique contributions. Through empirical results, we demonstrated the effectiveness of utilizing quantum models inspired by the brain, which outperform the classical approaches and other quantum models in optimizing energy use case. Specifically, in terms of average, best and worst total reward, test reward, robustness, and learning curve. Full article

Background: Patients with complex proximal tibial plateau fractures (TPFs) tend to overestimate the prognosis of their injury, potentially due to factors such as a limited understanding, optimism, and the influence of the pain intensity. Understanding the reasons behind this misperception is crucial for healthcare providers to effectively communicate with patients and establish realistic expectations for treatment outcomes. The purpose of this study was to analyze the outcomes of TPFs, with a particular focus on patient-reported outcome measures concerning functional recovery, pain levels, and overall satisfaction with treatment. The authors aim to provide valuable insights into the realistic expectations and potential limitations that patients may encounter during their recovery journey. Methods: In this retrospective single-center study, all surgically treated TPFs between January 2014 and December 2019 with a minimum follow-up of 12 months were included. Several patient-reported outcome measures were obtained, including the International Knee documentation Committee Score (IKDC), Lyholm score, Tegner score, and visual analog scale (VAS) for pain. Fractures were classified according to Schatzker, and then subgrouped into simple (Schatzker I–III) and complex (Schatzker IV–VI) fractures. Results: A total of 54 patients (mean age 51.1 ± 11.9 years, 59.3% female) with a mean follow-up time of 3.9 years were included. Schatzker II fractures were present in 48% (n = 26) of the cases, with Schatzker III in 6% (n = 3), Schatzker IV fractures in 6% (n = 3), and Schatker VI fractures in 41% (n = 22) of the cases. All outcome scores showed a significant improvement between the first year after surgery and the last follow-up (mean: 3.9 years). Simple fractures showed significantly lower patient-reported outcomes when compared to the preinjury state; however, good to excellent results were observed. Patient-reported outcomes of complex fractures showed no significant changes in the study period with good to excellent results. When it comes to the Lysholm score, there were no significant differences in the outcome between simple and complex fractures. Furthermore, there was a return-to-sports rate of 100%, with high rates of changing sporting activity in 25% (simple fractures) and 45% in complex fractures. Conclusions: The data from this study showed that both simple and complex tibial plateau fractures show favorable outcomes at the midterm follow-up, and that injury severity does not correlate with worse results. While patients may tend to overestimate the recovery speed, this research highlights the importance of long-term follow-up, demonstrating a substantial improvement between one year post-surgery and the final evaluation. Return-to-sports rates were high, with adjustments needed for certain activities. However, patients should recognize the need to shift to lower-impact sports and the lengthy recovery process. Full article