Wheat, a component of the staple diet globally, is a common food allergen in children. The symptoms of wheat allergy (WA) range from skin rash to shortness of breath, significantly impairing quality of life. Following initial clinical suspicion, individuals may undergo wheat allergen-specific skin prick test (SPT), blood test for serum immunoglobulin E (sIgE) levels or oral food challenge. Conventional management of WA lies in wheat avoidance, yet accidental consumption may be inevitable owing to the ubiquity of wheat in various food products. This article aims to provide an overview of the immunologic pathway of WA, followed by its novel diagnostic methods, namely alcohol-soluble SPT extracts, component-resolved diagnosis and basophil activation test (BAT). The mechanisms underlying wheat allergen-specific oral immunotherapy (OIT) as well as a summary of the efficacy, tolerability and safety of related clinical trials will then be discussed.

Plant-microbe interactions are essential for ecosystem health and agricultural productivity. Metabolomics has revolutionized our understanding of these interactions by providing powerful methods to decipher the complex chemical signals involved. This review highlights the various metabolomics techniques used to study plant-microbe interactions, such as mass spectrometry, nuclear magnetic resonance spectroscopy, and advanced imaging technologies. We also discuss the role of contemporary bioinformatics tools, extensive databases, and the increasing influence of artificial intelligence and machine learning in the analysis of metabolomics data. Integrating metabolomics with other omics fields, including transcriptomics, proteomics, and metagenomics, allows for a comprehensive understanding of the molecular mechanisms underlying plant-microbe interactions. The review emphasizes the significance of fluxomics in elucidating the dynamic nature of metabolic networks. While there are challenges in data analysis, integration, and interpretation, metabolomics has profoundly expanded our knowledge of the role metabolites play in shaping plant-microbe interactions. As metabolomics technologies advance and integrate further with other omics approaches, we anticipate groundbreaking discoveries that will provide deeper insights into these complex interactions, ultimately leading to innovative strategies for sustainable agriculture and biotechnology.

Global warming poses a threat to plant survival, impacting growth and agricultural yield. Protein turnover, a critical regulatory mechanism balancing protein synthesis and degradation, is crucial for cellular response to environmental changes. We investigated the effects of elevated temperature on proteome dynamics in Arabidopsis thaliana seedlings using 15N-stable isotope labeling and ul-tra-performance liquid chromatography-high resolution mass spectrometry, coupled with the ProteinTurnover algorithm. Analyzing different cellular fractions from plants grown under 22°C and 30°C growth conditions, we found significant changes in the turnover rates of 571 proteins, with a median 1.4-fold increase, indicating accelerated protein dynamics under thermal stress. Notably, soluble root fraction proteins exhibited smaller turnover changes, suggesting tissue-specific adap-tations. Significant turnover alterations occurred with redox signaling, stress response, protein folding, secondary metabolism, and photorespiration, indicating complex responses enhancing plant thermal resilience. Conversely, proteins involved in carbohydrate metabolism and mito-chondrial ATP synthesis showed minimal changes, highlighting their stability. This analysis high-lights the intricate balance between proteome stability and adaptability, advancing our under-standing of plant responses to heat stress and supporting the development of improved thermo-tolerant crops.

The pressing threat of global warming poses significant risks to plant survival, adversely affecting their growth and agricultural productivity. It is crucial to understand how plants react to heat stress at the molecular level to develop crops that can withstand higher temperatures. In our study, we investigated the proteome dynamics of *Arabidopsis thaliana* seedlings under moderate heat stress conditions (30°C) using a combination of 15N-stable isotope labeling and the ProteinTurnover algorithm. This approach allowed us to closely examine the proteomic changes across different cellular compartments. Our findings revealed significant changes in the turnover rates of 571 proteins, with an average increase of 1.4-fold, indicating enhanced protein dynamics under heat stress. Notably, root soluble proteins showed more subtle changes, suggesting tissue-specific responses. We also detected significant turnover variations in proteins involved in redox signaling, stress response, and metabolism, highlighting the complex nature of these adaptive mechanisms. In contrast, proteins related to carbohydrate metabolism and mitochondrial ATP synthesis showed little change, underscoring their stability. This detailed analysis illuminates the proteomic adaptations of *Arabidopsis* seedlings to moderate heat stress, enhancing our understanding of plant thermal resilience and supporting efforts to develop thermotolerant crops.

During their growth, bacteria respond to complex environmental changes through equally com-plex and orderly regulatory mechanisms. sRNA has an important role as a post-transcriptional regulator in the environmental adaptation of Bacillus. In this study, we identified an sRNA Bvs091 located in the intergenic region of the Bacillus velezensis, which is widely present in the genus Bacillus and whose expression is upregulated by salt treatment. The deletion of bvs091 in B. ve-lezensis PEBA20 led to a reduced growth rate and a change in the phenotypes, with simple colony structures and low and easily degradable biofilm. Salt tolerance tests indicated that the deletion of bvs091 results in a reduced salt tolerance. galT2 mRNA is supposed to be a direct target of Bvs091 according to results obtained by using the bioinformatic method and performing qRT-PCR analysis. The microscale thermophoresis (MST) analysis showed that Bvs091 could directly bind 28‒51 bases in front of the promoter of galT2. Subsequently, the deletion of galT2 in B. velezensis resulted in increased salt tolerance. Based on the techniques of double plasmids and a half-life period, sRNA Bvs091 is confirmed as a trans-encoded sRNA that negatively regulates the mRNA expression of galT2. In brief, the trans-encoded sRNA Bvs091 acts by pairing the incomplete complementary bases of galT2 mRNA, reducing galT2 mRNA’s stability and affecting the trans-lation efficiency.

This paper considers the solution of the equations for ruin probabilities in infinite continuous time. Using the Fourier Transform and certain results from the theory of complex functions, these solutions are obtained as com- plex integrals in a form which may be evaluated numerically by means of the inverse Fourier Transform. In addition the relationship between the re- sults obtained for the continuous time cases, and those in the literature, are compared. Closed form ruin probabilities for the heavy tailed distributions: mixed exponential; Gamma (including Erlang); Lognormal; Weillbull; and Pareto, are derived as a result (or computed to any degree of accuracy, and without the use of simulations).

This study aimed to present a systematic meta-analysis examining the association between Helicobacter pylori (H. pylori) infection, hemoglobin A1c levels, and the development of type 1 diabetes mellitus. The initial search identified 451 articles related to the association between H. pylori infection and T1DM. Among them, 14 articles had 2,971 participants meeting the inclusion criteria for advanced meta-analysis. A significant association was observed between H. pylori infection and T1DM, with an odds ratio (OR) of 1.87 (95% confidence interval [CI]: 1.27–2.78, p = 0.002). A subgroup analysis on H. pylori status showed that a longer duration of diabetes diagnosis and higher hemoglobin A1c levels were significantly associated with H. pylori infection (p < 0.001 for both). However, there was no significant association between H. pylori infection and the diagnostic age of diabetes (p = 0.306). These findings contribute to the understanding of the association between H. pylori infection and T1DM, thereby highlighting the potential role of H. pylori in influencing the duration and glycemic control of diabetes.

Aims: A community-based multi-component intervention (increasing awareness of the importance of physical activity in chronic illness management through reading comic books, training regarding warm-up stretching exercises, identifying facilitators and barriers to exercise through photosharing, supporting self-reflection and development of action plans) was developed to promote physical activity (PA) among patients with diabetes and hypertension. This study aimed to evaluate the efficacy of this intervention on health behaviour (walking) and health outcomes. Design: A non-randomized controlled trial with waitlisted control and pre- and post-measures. Setting: Community centres for the elderly. Participants: A total of 204 older adults with diabetes and/or hypertension were recruited. They were assigned to either the intervention group (IG) or waitlisted to the control group (CG). Intervention: Under the supervision of a nurse, six weekly group meetings were arranged in community centres for the elderly in which the participants freely exchanged their views regarding the barriers and facilitators of regular physical activity. Participants were encouraged to take photos in their neighbourhood or at home and brought these photos to share at the group meetings. The photos showed both the barriers and the facilitators to PA. In the last meeting, each participant worked out a plan to perform PA in the coming four weeks. Measures: PA referred to the number of steps taken per day and it was measured by a Garmin Accelerometer at baseline, Week 6 and Week 10. Other measures included the nine-item Self-Efficacy Scale for Exercise - Chinese version (SEE-C), the 23-item Chinese Barriers to Exercise Scale and Senior Fitness Tests. Generalised Estimating Equations (GEE) models compared the outcomes over time between IG and CG. Results: A statistically significant difference in the changes in the average number of steps taken daily between the two groups at Week 10 (mean difference = 965.4; 95% confidence interval: 92.2, 1838.6, p = 0.030) was observed, although the difference at Week 6 was non-significant (mean difference = 777.6; 95% confidence interval: −35.3, 1590.5, p = 0.061). IG participants also showed significant improvements in lower body strength (mean difference = 0.967; 95% confidence interval: 0.029, 1.904, p = 0.043) and lower limb flexibility (mean difference = 2.068; 95% confidence interval: 0.404, 3.731, p = 0.015) at Week 10 compared to CG participants. Conclusion: This multi-component intervention improved the participants’ physical activity level and physical fitness, particularly in lower limb flexibility and body strength.

Temporomandibular disorders (TMD) is a group of orofacial pain conditions which is the most common non-dental pain complaint in the maxillofacial region. Due to the complexity of the etiology and often cyclical nature of the disease, the diagnosis and management of TMD remain a challenge where consensus is still lacking in many aspects. While clinical examination is considered the most important process in the diagnosis of TMD, imaging may serve as a valuable adjunct in selected cases. Depending on the type of TMD, many treatment modalities have been proposed, ranging from conservative options to open surgical procedures. In this review, the authors discuss the present thinking in the etiology and classification of TMD, followed by the diagnostic approach and the current trend and controversies in management.

The speech-to-song illusion is a type of auditory illusion that the repetition of a part of a sentence would change people’s perception tendency from speech-like to song-like. The study aims to examine how pace, emotion, and language tonality affect people’s experience of the speech-to-song illusion. It uses a between-subject (Pace: fast, normal, vs. slow) and within-subject (Emotion: positive, negative, vs. neutral; language tonality: tonal language vs. non-tonal language) design. Sixty Hong Kong college students were randomly assigned to one of the three conditions characterized by pace. They listened to 12 audio stimuli, each with repetitions of a short excerpt, and rated their subjective perception of the presented phrase, whether it sounded like a speech or a song, on a five-point Likert-scale. Paired-sample t-tests and repeated measures ANOVAs were used to analyze the data. The findings reveal that a faster speech pace could strengthen the tendency of the speech-to-song illusion. Neither emotion nor language tonality show a statistically significant influence on the speech-to-song illusion. This study suggests that the perception of sound should be in a continuum and facilitates the understanding of song production in which speech can turn into music by having repetitive phrases and to be played in a relatively fast pace.

Embracing innovative digital technologies within educational systems is essential for overcoming challenges in modern learning environments, especially in the post-COVID-19 era. Teaching sustainability management in higher education institutions with innovative digital tools plays a fundamental role in the transition toward sustainable societies. Suitable game design elements play a significant role in facilitating sustainable learning. This study explored the effectiveness of incorporating business simulation games with project-based learning (PBL) in a flipped classroom setting. This approach was adopted within the context of a university cross-border e-commerce course to prepare students for acquiring 21st -century skills as higher-order thinking skills in a rapidly changing educational landscape. A quasi-experimental method was employed, involving a total of 60 university students from China's Zhejiang Province. Participants completed an online questionnaire designed to assess their learning engagement across three dimensions (cognitive, emotional, and behavioral) as well as their higher-order thinking skills (problem-solving, critical thinking, and creativity). The results show that the business simulation games combined with flipped classroom learning had a significantly positive impact on students’ learning outcomes, enhancing their problem-solving, critical thinking, and creative capabilities. Importantly, this approach also improved student engagement and promoted sustainable practices by applying real-life scenarios in an interactive environment. We conclude that business simulation games integrated with project-based learning (PBL) in flipped classroom settings represent a valuable educational approach. This approach not only enhances learning engagement but also fosters the development of higher-order thinking skills, encouraging students to adopt sustainable learning practices.

The retinoblastoma (RB) transcriptional corepressor 1 (RB1) is a critical tumor suppressor gene, governing diverse cellular processes implicated in cancer biology. Dysregulation or deletion in RB1 contributes to the development and progression of various cancers, making it a prime target for therapeutic intervention. RB1's canonical function in cell cycle control and DNA repair mechanisms underscores its significance in restraining aberrant cell growth and maintaining genomic stability. Understanding the complex interplay between RB1 and cellular pathways is beneficial to fully elucidate its tumor-suppressive role across different cancer types and for therapeutic development. As a result, investigating vulnerabilities arising from RB1 deletion-associated mechanisms offers promising avenues for targeted therapy. Recently, several findings highlighted multiple methods as a promising strategy for combating tumor growth driven by RB1 loss, offering potential clinical benefits in various cancer types. This review summarizes the multifaceted role of RB1 in cancer biology and its implications for targeted therapy.

Although Darwin‘s evolutionary mutation theory has been widely accepted, many endeavors have been tried to challenge it. With more and more observation of successful hybridization and hybrids, the sexual isolation between species has become vague. The mechanism of evolution has been expanded from the classical model of evolution to multiple routes of speciation. Furthermore, a fundamental crossbreeding theory has been raised and proved by two lines of evidences: paleopolyploidy and fan-shaped spectrum of species. Ancient genome duplications are widespread throughout eukaryotic lineages, particularly in plants. The genome polyploidization, especially in the somatic cell hybridization, can break through the sexual incompatibility between diploid counterparts to hybridize and produce new species. By comparing characteristics, all species in every taxon, both in the extinct fossil and extant organisms, can be arranged into fan-shaped spectrum according to their similarity: left primitive type-middle advanced type-right primitive type. The species are primitive at the two ends and advanced at the middle. The primitive two species always resemble two types of more primitive species that can be confirmed as their ancestors respectively, and the middle species is half similar to the two ancestors respectively. These suggest that the species in the spectrum come from two different ancestors by crossbreeding and gene combination. As a sum, advanced species originated from crossbreeding of two primitive ancestors, by major method of polyploidization, and proved by results of fan-shaped spectrum of species. Then, sex is the cause, force and opportunity for evolution.

Background: This study aimed to assess the dementia literacy (DL) level of community-dwelling adults in the four cities (Hong Kong, Guangzhou, Macau and Zhuhai) of the Greater Bay Area of China and to determine the preferred mass media for receiving dementia information. Methods: A multi-city cross-sectional study with 788 community-dwelling adults completed the survey. Dementia literacy was indirectly measured by two validated scales, 30-item Alzhiemer’s Disease Knowledge Scale (ADKS) and 20-item Dementia Attitudes Scale (DAS). When the ADKS total score was <15 and DAS total score was <70, it was considered as ‘inadequate dementia literacy’. Participants were also asked to indicate whether they would like to receive dementia information via digital media or traditional media. Chi-square tests and logistic regressions were undertaken. Results: About one-third of the participants had inadequate dementia literacy. Those with young age or secondary education preferred to get dementia information from social media. But people living in public housing would like to get information from government or hospital websites. Middle-aged participants inclined to learn dementia from television or radio. Conclusion: It is worthy to conduct territory-wide public education in dementia and develop strategies according to their preferences in the types of mass media.

Monitoring is an important component of pest management, to prevent or mitigate outbreaks of native pests, and to check for quarantine organisms. Surveys often rely on trapping, especially when the target species respond to semiochemicals. Many traps are available for this purpose, but they are bulky in most cases, which raises transportation and deployment issues, and they are expensive, which limits the size and accuracy of any network. To overpass these difficulties, entomologists have used recycled material, such as modified plastic bottles, producing cheap and reliable traps but at the cost of recurrent handywork, not necessarily possible for all end-users (e.g., for national plant protection organizations). These bottle-traps have allowed very large surveys which would have been impossible with standard commercial traps, and we illustrate this approach with a few examples. Here we present, under a Creative Commons BY-SA License, the blueprint of a fan-trap, a foldable model, laser-cut from a sheet of polypropylene, that can rapidly be produced in large numbers, and could be transported and deployed in the field with very little efforts. Our first field comparisons show that fan-traps are as efficient as bottle-traps, and we describe two cases where they are being used for monitoring.

In thermal power plants equipped with air-cooled condensers, axial cooling fans operate under the influence of ambient flow fields. Under inlet cross-flow conditions, the resultant asymmetric flow field is known to introduce additional harmonic forces to the fan blades. This effect has previously been studied only numerically or using blade mounted strain gauges. For this study, Laser Scanning Vibrometry was used to assess fan blade vibration under inlet cross-flow conditions in an adapted fan test rig inside a wind tunnel test section. Two co-rotating laser beams scanned a low pressure axial fan, resulting in spectral, phase resolved surface vibration patterns of the fan blades. Two distinct operating points were examined, with and without inlet cross-flow influence. While almost identical fan vibration patterns were found for both reference operating points, overall blade vibration increased by 100% at low fan flow rate due to cross-flow, and by 20% at high fan flow rate. While numerically predicted natural frequency modes could be confirmed from experimental data as minor peaks in the vibration amplitude spectrum, they were not excited significantly by cross-flow. Instead, primarily higher rotation rate harmonics were amplified, i.a. a synchronous blade tip flapping was strongly excited at the blade pass frequency.

This study aims to investigate the hydration and strength characteristics of green cementitious mortars with ultrahigh-volume limestone-calcined clay as well as two kinds of Class F fly ash. Using the ASTM C311 strength activity index test method, the effect of different pozzolan replacement levels of cement (0%, 20%, 50%, and 80%, by weight) were investigated. Compressive strength at 3, 7, 14, 28 and 90 days under standard curing was recorded, and hydration heat of the 20% and 80% replacement mixes was studied using iso-thermal calorimetry. It was observed that the effectiveness of the pozzolan in mortars depends on particle size distribution, glassy or amorphous nature, surface area and replacement level. The sum of all these effects can be captured by the strength activity test only if the standard recommended 20% pozzolan mix is substituted with the actual mix composition. The results in this study provide insights into the mix design and applications of ultrahigh-volume pozzolanic cementitious materials specifically made with limestone-calcined clay, and promote greener cement and concrete in construction industry.

This study investigated whether reciprocal collaborative pedagogy significantly impacts Indonesian electrical engineering polytechnic students in reducing reading anxiety and improving self-efficacy in ESP reading comprehension skills. Fifty Polytechnic students were equally assigned to two groups. Control groups learned in the traditional reciprocal teaching method individually. Experimental group engaged in reciprocal collaborative pedagogy. Each group received a 6-week reading strategy training. E-learning platforms were used in this study as a complementary tool to distribute ESP reading materials, announcements, and the experiment details being taught. The quantitative and qualitative results demonstrated that the tasks in reciprocal collaborative pedagogy positively affects Indonesian electrical engineering polytechnic students' learning experience and outcomes. This pedagogy promotes a productive learning environment through peer interaction, active engagement, and peer group discussions of the whole learning activities, reducing feelings of anxiety and building confidence in ESP-specialized text.

On 19 September 2021, La Palma volcano (Canarias Archipelagos) started an eruption that persisted until 13 December 2021. Despite the Volcano Explosive Index (VEI) being estimated equal to 3, corresponding to not so powerful eruption, the long eruption activity posed much scientific in-terest in this natural hazard event. In this paper, we searched for possible effects of this eruption on the atmosphere and ionosphere, investigating the climatological archive and Swarm magnetic satellite data. In particular, we explored Aerosol, Sulphur Dioxide and Carbon Monoxide con-centrations in the atmosphere identifying both the direct emissions from the volcano as well as the plume that drifted toward West-South-West and was reinforced during the eruption period. The vertical profile of temperature from the Saber satellite was analysed to search for the possible presence of acoustic gravity waves induced by volcanic activity. Compared with the year before without eruption in the areas, a lot of Saber profiles present an Energy Potential very much higher than the previous year, proposing the presence of Acoustic Gravity Waves (AGW) induced by volcano eruption activity. We also identified Swarm magnetic disturbances on the day of the eruption and in November. The mechanism of coupling could be different for the latter one, as there is no evidence for AGW. They may be due to a more complex of physical and chemical al-terations that propagate from the lower atmosphere to the upper one into the ionosphere.

In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capabilities in image generation and dimensionality reduction. The combination of VAE and various machine learning frameworks has also worked effectively in different daily life applications, however its possibility and effectiveness in modern game design has seldom been explored nor assessed. The use of its feature extractor for data clustering was minimally discussed in literature neither. This paper first attempts to explore different mathematical properties of the VAE model, in particular, the theoretical framework of the encoding and decoding processes, the possible achievable lower bound and loss functions of different applications; then applies the established VAE model into generating new game levels within two well-known game settings; as well as validating the effectiveness of its data clustering mechanism with the aid of the Modified National Institute of Standards and Technology (MNIST) database. Respective statistical metrics and assessments were also utilized for evaluating the performance of the proposed VAE model in aforementioned case studies. Based on the statistical and spatial results, several potential drawbacks and future enhancement of the established model were outlined, with the aim of maximizing the strengths and advantages of VAE for future game design tasks and relevant industrial missions.

Wearable technology has been proposed as a potential tool to change the way of human life, such as the smart bracelet and the Google Glass. In the wearable technology, the inertial sensor has great significance in tracking the object movements. The paper focused on detecting the movements of user’s finger based on the inertial sensor to give the control signals. Firstly, the attitude matrix, which represented the transformation relation of carrier coordinate system and the navigation coordinate system, was obtained. Secondly, the attitude matrix was expressed based on the quaternions. Thirdly, the finger gesture was processed by the attitude matrix to get the attitude angle. Finally, the robot was controlled by attitude angle to make the moving action. The experimental results showed the detection of the finger movement is effective.

The Schwarzschild metric describes a non-rotating and charge-free celestial body, and it results in things stopping at the event horizon of a black hole and spending infinite time across the event horizon by the observer far away from the black hole. The analysis of the particle’s behavior at the event horizon tells us that this solution predicts an un-expanded black hole which violates the astronomical observations and our knowledge about the black hole. Although some alternative metrics have been proposed, the singularity problem is still unsolved. In this research, the degenerate Fermi electron gas is used to reveal that the Fermi electron gas cannot shrink to a point no matter how large energy it obtains, so the singularity exists at the center very unreasonably. In order to avoid these problems, a finite-size nucleus of the black hole is proposed and reasonably explained by the behaviors of the Fermi electron gas and the Fermi neutron gas there. On the other hand, the Kerr-Newman metric is the one describing the rotating and charged black hole and the equation of the light velocity at each space point can be obtained. It tells us that there are two real and non-imaginary solutions for the radial speed of light at the position larger than the Schwarzschild radius.

This paper is motivated by spatio-temporal pattern in the occurrence of Leishmaniasis in Afghanistan and the relatively high number of zero counts. We hold the view that correlations that arise from spatial and temporal sources are inherently distinct. Our method decouples these two sources of correlations, there are at least two advantages in taking this approach. First, it circumvents the need to inverting a large correlation matrix, which is a commonly encountered problem in spatio-temporal analyses. Second, it simplifies the modelling of complex relationships such as anisotropy, which would have been extremely difficult or impossible if spatio-temporal correlations were simultaneously considered. We identify three challenges in the modelling of a spatio-temporal process: (1) accommodation of covariances that arise from spatial and temporal sources; (2) choosing the correct covariance structure and (3) extending to situations where a covariance is not the natural measure of association. Moreover, because the data covers a period that overlaps with the US invasion of Afghanistan, the high number of zero counts may be the result of no disease incidence or lapse of data collection. To resolve this issue, a model truncated at zero built on a foundation of the generalized estimating equations was proposed.

Retinoic acid receptor-related orphan receptor γ (RORγ) is a transcription factor regulating the expression of the pro-inflammatory cytokine IL-17 in human T helper 17 (Th17) cells. Activating RORγ can induce multiple IL-17-mediated autoimmune diseases but may also be useful for anticancer therapy. Its deep immunological functions make RORɣ an attractive drug target. Over 100 crystal structures have been published describing atomic interactions between RORɣ and agonists and inverse agonists. In this review, we focus on the role of dynamic properties and plasticity of the RORɣ orthosteric and allosteric binding sites by examining structural information from crystal structures and simulated models. We discuss the possible influences of allosteric ligands on the orthosteric binding site. We find that high structural plasticity favors the druggability of RORɣ, especially for allosteric ligands.

We successfully designed an optimized plenum fan with a three-dimensional, smooth, curved blade. The optimized model revealed that the static pressure in the channel had been increased uniformly and stably, and the flow separation at the leading edge was significantly reduced. To conclude, the three-dimensional blade stabilized the fluid flow, and the flow friction was reduced by suppressing the flow separation as much as possible so that both the static pressure and the static efficiency were clearly improved in comparison with those of the original model. The static efficiency, as a result, was improved by 6% compared with that of the original model.

Two new dimacrolide sesquiterpene pyridine alkaloids (DMSPAs), dimacroregelines A (1) and B (2), were isolated from the stems of Tripterygium regelii. The structures of both compounds were characterized by extensive 1D and 2D NMR spectroscopic analyses, as well as HRESIMS data. Compounds 1 and 2 are two rare DMSPAs possessing unique 2-(3′-carboxybutyl)-3-furanoic acid units forming the second macrocyclic ring, representing the first example of DMSPAs bearing an extra furan ring in their second macrocyclic ring system. Compound 2 showed inhibitory effects on the proliferation of human rheumatoid arthritis synovial fibroblast cell (MH7A) at a concentration of 20 μM.

Object detection is important in many applications, such as autonomous driving. While 2D images are lack of depth information and are sensitive to environmental conditions, 3D point cloud can provide accurate depth information and a more descriptive environment. However, sparsity is always a challenge in single-frame point cloud object detection. This paper introduces a two-stage proposal-based feature fusion method for object detection using multiple frames. The proposed method, called proposal features fusion (PFF), utilizes a cosine-similarity approach to associate proposals from multiple frames and employs an attention weighted fusion module to merge features from these proposals. It allows for feature fusion specific to individual objects and offers lower computational complexity while achieving higher precision. The experimental results on the nuScenes dataset demonstrate the effectiveness of our approach, achieving a mAP of 46.7%, which is 1.3% higher than the state-of-the-art 3D object detection method.

In this paper, spacetime is defined as the absolutely invariant homogeneous "coordinate spacetime" frame and its modulation by the relatively variable non-homogeneous "metric spacetime" under its constraints. This modulation is caused by matter and motion, and carries the function of transmitting interactions, reflecting the diffeomorphism invariance and Lorentz invariance. This inhomogeneous spacetime concept makes the medium nature of spacetime more obvious and avoids the problem of "path dependence" caused by the concept of curved spacetime. In this paper, it is argued that all energy-momentum has internal spatio-temporal properties, and all interactions must be transmitted through spacetime metrics. On this basis, a converging and dispersing cyclic multiverse model is proposed. This model of the universe is inevitable as long as there are two macroscopic manifestations of the matter of the universe, namely, gravitation induced convergence and "explosive" dispersion caused by different factors. The new cosmic model matches the observed accelerated "expansion" of the universe and no longer requires the dark energy hypothesis.

This paper empirically analyzes the relationship between digital inclusive finance and rural income, and demonstrates that digital inclusive finance plays a significant role in promoting rural income, based on the 2012-2018 panel data of 17 cities in Henan Province of China. Further dimensional research unveils that all of its breadth of coverage, depth of use and degree of digitization present significant positive correlation with rural income, and a robustness test was conducted through the sub-sample method. In addition, according to regression analysis on the influencing factors of digital inclusive finance through the Tobit model, the level of economic development, the Internet popularity rate and the urbanization rate have a positive effect on the development of digital inclusive finance in Henan, while the income gap between urban and rural areas and the degree of opening up have a negative effect. Finally, predicated on the analysis of the restrictive factors of Henan’s digital inclusive finance in increasing rural income, the paper puts forward specific policy proposals based on the native state quo.

The global shipping industry faces many uncertainties which impact on how organisations within this sector will perform in the future. Research in the critical success factors which impact global shipping industry in the digital era is lacking. This study plugs the gap in the literature by identifying four key critical success factors which are innovation capability, risk governance capability, leadership and strategic capability and technological capability. In addition, this study also found three organisational performance measures that are useful for senior management teams within the industry, namely, financial performance, operational performance and marketing performance. The findings establish a set of critical success factors and the corresponding relationships between the identified critical success factors and the identified organisational performance measures. The paper also provides managerial insights for industry practitioners for defining, prioritising and allocating resources in order to improve organisational performance.

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. There is evidence that some ligands that bind to the GPCRs activate different downstream signaling pathways. G protein activation or -arrestin biased signaling involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. Molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions between receptors and ligands. Here, we highlight recent simulation studies and methods used to study biased G protein-coupled receptor signaling and their conformational dynamics. We also highlight applications of MD simulations to drug discovery.

The existence of palindrome numbers of arbitrary length greater than 2 that are divisible by the prime number 37 is proven in this paper. The method to construct such a palindrome is also described. It turns out that a palindrome number divisible by 37 is also divisible by 3 and, consequently, divisible by 111.

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

Deterministic-stochastic empirical mode decomposition (EMD) is used to obtain low-frequency (non-diffusive, i.e., background velocity) and high-frequency (diffusive, i.e., eddies) components from a Lagrangian drifter‘s trajectory. Eddy characteristics are determined from the time series of eddy trajectories from individual Lagrangian drifter such as the eddy radial scale, eddy velocity scale, eddy Rossby number, and eddy-background kinetic energy ratio. A long-term dataset of the SOund Fixing And Ranging float time series obtained near the California coast by the Naval Postgraduate School from 1992 to 2004 at depth between 150 and 600 m (http://www.oc.nps.edu/npsRAFOS/) is used as an example to demonstrate the capability of the deterministic-stochastic EMD.

In this paper, some mixed type bounds on the spectral radius $\rho(A\circ B)$ for the Hadamard product of two nonnegative matrices ($A$ and $B$) and the minimum eigenvalue $\tau(C\star D)$ of the Fan product of two $M$-matrices ($C$ and $D$) are researched. These bounds complement some corresponding results on the simple type bounds. In addition, a new lower bound on the minimum eigenvalue of the Fan product of several $M$-matrices is also presented: $$ \tau(A_{1}\star A_{2}\cdots\star A_{m})\geq \min_{1\leq i\leq n}\{\prod^{m}_{k=1}A_{k}(i,i)-\prod^{m}_{k=1}[A_{k}(i,i)^{P_{k}}-\tau(A_{k}^{(P_{k})})]^\frac{1}{P_{k}}\}, $$ where $A_{1},\ldots, A_{k}$ are $n\times n$ $M$-matrices and $P_{1},\ldots, P_{k}>0$ satisfy $\sum^{m}_{k=1}\frac{1}{P_{k}}\geq 1$. Some special cases of the above result and numerical examples show that this new bound improves some existing results.

The concept of smart morphing blades, which can control themselves to reduce or eliminate the need for active control systems, is a highly attractive solution in blade technology. In this paper an innovative passive control system based on Shape Memory Alloys (SMAs) is proposed. On the basis of previous thermal and shape characterization of a single morphing blade for a heavy-duty automotive cooling axial fan, this study deals with the numerical analysis of the aerodynamic loads acting on the fan. By coupling CFD and FEM approaches it is possible to analyze the actual blade shape resulting from both the aerodynamic and centrifugal loads. The numerical results indicate that the polymeric blade structure ensures proper resistance and enables shape variation due to the action of the SMA strips.

Despite the popularity of Zumba in several countries, research is scarce about its impact on older adults. Meanwhile, the integration of cognitive tasks with physical exercises, known as dual-tasking, is an evolving strategy to facilitate activities for older people. This study investigated the perceptions of older adults regarding Zumba and the potential of implementing it in a dual-task program. We conducted a qualitative-descriptive research involving 44 Filipino older adults from August to November 2020. Content analysis was employed to analyze the data. Four themes were identified: moving towards match or mismatch; balancing benefits with burdens; dual-tasking as innovative yet potentially challenging; and overcoming barriers with enablers. While Zumba is an inclusive and beneficial activity, individual and contextual limitations could hinder its suitability for older people. Dual-tasking in Zumba was also recognized as an innovative approach, although challenges should be addressed to promote its utility. Several strategies could support the design of these programs in communities. This is the first study to explore older adults’ perceptions towards Zumba and its potential utilization as a dual-tasking program. Findings could guide the implementation of appropriate Zumba and dual-tasking activities that seek to integrate cognitive and physical training for older adults.

Vitamins are essential compounds obtained through diet that are necessary for normal devel-opment and function in an organism. One of the most important vitamins for human physiology is Vitamin A, a group of retinoid compounds and carotenoids which generally function as a mediator for cell growth, differentiation, immunity, and embryonic development, as well as serving as a key component in the phototransduction cycle in vertebrate retina. For humans, vitamin A is obtained through the diet, where provitamin A carotenoids like β-carotene, or preformed vitamin A such as retinyl esters are absorbed into the body via the small intestine and converted into all-trans retinol within the intestinal enterocytes. Specifically, once absorbed, carotenoids are cleaved by carote-noid cleavage oxygenases (CCOs), such as BCO1, to produce all-trans retinal that subsequently gets converted into all-trans retinol. CRBP2 bound retinol is then converted into retinyl esters (REs) by the enzyme lecithin retinol acyltransferase (LRAT) in the endoplasmic reticulum, which is then packaged into chylomicrons and sent into the bloodstream for storage in hepatic stellate cells in the liver or for functional use in peripheral tissues such as the retina. All-trans retinol also travels through the bloodstream bound to retinol binding protein 4 (RBP4), where it enters cells with the assistance of the transmembrane transporters, stimulated by retinoic acid 6 (STRA6) in peripheral tissues or retinol binding protein receptor 2 (RBPR2) in systemic tissues (e.g. in the retina and the liver respectively). Much is known about the intake, metabolism, storage, and function of vitamin A compounds, especially with regard to its impact on eye development and visual function in the retinoid cycle. However, there is much to learn about the role of vitamin A as a transcription factor in development and cell growth, as well as how peripheral cells signal hepatocytes to secrete all-trans retinol into the blood for peripheral cell use. This article aims to review literature re-garding the major known pathways of vitamin A intake from dietary sources into hepatocytes, vitamin A excretion by hepatocytes, as well as vitamin A usage within the retinoid cycle in the RPE and retina to provide insight on future directions of novel membrane transporters for vitamin A in retinal cell physiology and visual function.

The recent outbreak of coronavirus disease 2019 caused by the new coronavirus, SARS-CoV-2, has become an international emergency. Since there is no effective therapy for the treatment of this disease, drugs or vaccine that can prevent or cure the SARS-CoV-2 infection are urgently needed. The viral 3-chymotrypsin-like cysteine protease (3CLpro), which plays a key role in the replication of coronavirus, is a potential drug target for the development of anti-SARS-CoV-2 drugs. With the crystal structure of 3CLpro, we performed virtual screening from a small chemical library of a Traditional Chinese Medicine recipe- FuFang Zhenzhu Tiaozhi (FTZ). Five compounds with the best scores were screened and could be considered as potential hit compounds to be investigated further with bioassays for their anti-virus effects.

Many parents have difficulty managing childhood asthma. In Hong Kong (HK), while medication is the primary form of treatment, traditional Chinese medicine is another favored option. In addition, HK follows a dual-track healthcare system, which may pose unique experiences for Chinese parents in childhood asthma management. This qualitative descriptive study aimed to explore the experiences of HK Chinese parents in caring for their children with asthma. Methods: Fourteen HK Chinese mothers of children (aged 3-10) suffering from asthma were purposively sampled to participate in individual, semi-structured interviews. A realist approach following conventional content analysis was used to interpret the interviews. Results: The mothers expressed feelings of uncertainty, fear of asthma crises, and searching for ways to cope. These feelings triggered various strategies to control their child’s asthma. As long as the child’s asthma symptoms recurred, the mothers’ distress continued. Their distress was sometimes exacerbated by self-doubt and worries about whether they would receive adequate support from their family and healthcare professionals. Conclusion: Helping parents to understand their limits may help them be more open to varied aspects of their caregiving experiences, and thus to cope better. Psychological interventions together traditional educational training may help to alleviate parents’ psychological difficulties.

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate the tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) the tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving the tour routes, the transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city’s tourism service function.

Because Newton's gravity and Einstein's general theory of relativity are macroscopic gravitational theories, therefore, this paper attempts to establish a set of quantum gravity theory of the microscopic expression of Newton's and Einstein's theory of gravity to make up for the shortcomings of the existing macro-gravity theory at the micro level, and further develop the macroscopic gravity theory into the microscopic field. Based on the cognition of the field theory model, from the general assumption, space-time is further regarded as an ideal fluid, from the perspective of the distribution of ideal fluid density, this paper derives the Newton's universal gravitational equation and Einstein's general relativity equation. On the micro level, the gravitational field is further interpreted as a gradient field of space-time density; the Newtonian potential is further interpreted as the density of an object at the micro level; gravity is further interpreted as the potential pressure(space-time pressure) exhibited by the gradient of the density of the object at the micro level; flection space-time is further interpreted as the embodiment of the gradient distribution of the ideal fluid (space-time) density at the micro level. Based on a modified gravitational model, it explains the dynamics of the stars' rotation and revolution.

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

Because of an often complicated and difficult-to-access care system, help-seeking for people with suspected dementia can be stressful. Difficulty in help-seeking may contribute to carer burden, in addition to other known stressors in dementia care. This study examined the relationship between perceived help-seeking difficulty and carer burden, and the barriers contributing to perceived difficulty. We interviewed 110 carers accessing a community-based dementia assessment service for suspected dementia of a family member for their perceived difficulty, delays, and barriers in help-seeking, and carers burden in terms of role strain, self-criticism, and negative emotions. Linear regression models showed that perceived help-seeking difficulty is associated with carer self-criticism, while carer role strain and negative emotions are associated with symptom severity of the person with dementia but not help-seeking difficulty. Inadequate knowledge about symptoms, service accessibility, and affordability together explained more than half of the variance in perceived help-seeking difficulty (Nagelkerke R2 = .56). Public awareness about symptoms, support in navigating service, and financial support may reduce perceived difficulty in help-seeking, which in turn may reduce carer self-criticism during the early course of illness.

Moso bamboo is famous for fast growing and biomass accumulation, as well as high annual output for timber and bamboo shoots. These high outputs require high nutrient inputs to maintain and improve stand productivity. Soil nitrogen (N), phosphorus (P) and potassium (K) are important micronutrients for plant growth and productivity. Due to high variability of soils, analysing spatial patterns of soil N, P and K stocks is necessary for scientific nutrient management in Moso bamboo forests. In this study, soils were sampled from 138 locations across Yong’an City and ordinary kriging was applied for spatial interpolation of soil N, P and K stocks. Soil N stock showed a strong spatial dependence while soil N and P stocks presented a moderate spatial dependence, indicating soil N was mainly controlled by intrinsic factors while soil N and P stocks were controlled by both intrinsic and extrinsic factors. Different spatial patterns were observed for soil N, P and K stocks across the whole study area, indicating that fertilizations with different ratios of N:P:K should be applied for different sites to maintain and improve stand productivity. The total soil N, P and K stocks within 0-60 cm were 0.624, 0.020 and 0.583 Tg, respectively.

This research delves into the realm of predictive modeling within artificial intelligence (AI) and introduces an innovative ensemble approach designed to enhance prognostic precision. The proposed methodology, characterized by its ebullient nature, leverages the collective wisdom of diverse predictive models, synthesizing a comprehensive and robust framework. The pursuit of parsimony are paramount, underscoring the need for efficient model architectures that balance predictive acuracy and computational efficiency. Our study meticulously explores the amalgamation of diverse algorithms, encapsulating the intrinsic complexity of real-world phenomena. We navigate the intricate landscape of feature selection, algorithmic diversity, and model combination, fostering a holistic understanding of the prognostic process. The ebullient ensemble emerges as a dynamic solution, harnessing the synergy of constituent models while mitigating the risk of overfitting. To validate the efficacy of our approach, extensive experiments are conducted on diverse datasets, spanning domains such as healthcare, finance, and natural language processing. Comparative analyses demonstrate the superior predictive performance of our ensemble model in comparison to individual algorithms and traditional ensemble methods. Additionally, we delve into interpretability aspects, elucidating the underlying mechanisms that contribute to the model's prognostic prowess. Our research advances the frontier of predictive modeling in AI, offering a nuanced and sophisticated paradigm for prognostication. The ebullient ensemble approach stands as a testament to the synergy achievable through the amalgamation of diverse predictive models, providing a pragmatic and parsimonious avenue for enhanced prognostic acuracy in artificial intelligence applications.

This article focuses on artificial intelligence in educational technology, starting with an introduction to educational technology, an interdisciplinary field of study that covers the design, development, utilization, and evaluation of technology and digital tools in educational Settings. A detailed description of its definition in an academic context - a multidisciplinary field of computer science and cognitive science that deals with the development of computational systems that exhibit intelligent behaviour, describing its areas of coverage and scope of application. It then introduces the benefits of AI in education technology, specifically addressing personalized learning, adaptive learning systems, automated scoring and feedback, virtual tutors and chatbots, data analytics, as well as content recommendations and natural language processing, accessibility and inclusion. Then it introduces the main concepts of AI personalized learning: AI personalized learning uses the power of artificial intelligence to meet the unique needs and preferences of individual learners, as well as its key principles and main characteristics. Adaptive learning systems harness the power of artificial intelligence and data analytics to tailor the learning experience to each student's needs and abilities, as well as its core principles and strengths. It also introduces the main operating principles of automated grading and feedback: it uses artificial intelligence and computer algorithms to evaluate and evaluate student assignments, tests and exams without the direct involvement of human graders, and its associated benefits. Secondly, the main concepts of virtual tutor are introduced: Virtual tutor is a computer-based system that uses artificial intelligence and machine learning algorithms to provide students with personalized and interactive educational support and its key characteristics and main advantages, and then the nature and benefits of chatbots and help in the field of education. The final conclusion summarizes the benefits and future challenges of integrating AI into educational technology.

In this paper, the filtering method of biomedical image denoising is described comprehensively. Firstly, it introduces the biomedical image denoising, describes the relationship between biomedical image denoising and medical care, introduces the filtering methods, the filtering methods of biomedical image denoising, the challenges encountered by the current filtering methods, and other application fields of filtering methods. Firstly, the background of biomedical image denoising is introduced. Biomedical image denoising is a challenge. Different imaging modes have different noise characteristics, and noise levels can vary greatly depending on the specific application. Secondly, it describes that biomedical image denoising plays an important role in medical care, and the biomedical image directly affects the patient's diagnosis, treatment plan and the overall quality of medical care service. Then the filtering method is introduced in detail, describing the core concepts and related features of linear filtering, nonlinear filtering and frequency domain filtering, and then focusing on the adaptive filtering method, describing the characteristics, conditions of use, common algorithms and advantages of adaptive filtering method. Then the filter methods of biomedical image denoising are introduced, and the core concepts of Gaussian filter, median filter, total variation denoising and Wiener filter are introduced respectively. Then, the challenges encountered by filtering methods are described, such as the accurate selection of filters, the balance between noise reduction and image detail preservation are introduced. Finally, the application of filtering method in other fields is mentioned, such as audio processing, speech recognition and so on. In summary, this paper comprehensively expounds the denoising and filtering methods of biomedical images, the filtering methods of medical image denoising, the relationship between medical image denoising and medical care, and the challenges encountered by filtering methods.

Misinformation research has grown to become a critical topic in all disciplines. Since the expanding of online media, misinformation has been spreading rapidly across the globe through social media and other information systems. Paralleling the rise of academic interest in misinformation, is the emergence of online education scholarship. Interest in the online educational implications of misinformation and its impact attracts an increase in scholarship on misinformation. This article presents the results of a review of 1172 publications with “Misinformation” across disciplines and a subset of 174 misinformation literature in online education that were published between 2009 and 2021. This review answers three questions: (1) What is the overall distribution of publication activity with "misinformation" publications? (2) What methodologies have scholars used to investigate misinformation involving online education? (3) What have scholars reported about the results of studies involving misinformation in online education? The review reveals that various methodologies were used in literature focusing on misinformation online education with leading numbers of content analysis and quantitative studies. This systematic review is particularly relevant to those online educators in various disciplines who are interested in learning what scholars from their own academic disciplines are writing about misinformation.

Classical mechanics describes the laws of motion in the macroscopic material world, while quantum mechanics describes the laws of motion in the microscopic material world that classical mechanics cannot explain, and achieves a highly accurate mathematical representation of the laws of microscopic physical motion. But even with such a successful theory, there is confusion about the probability wave. Therefore, this paper attempts to improve the physical definition of the conceptual basis of quantum mechanics, thus solving the confusion of quantum mechanical probability waves, and finally surprisingly discovered another feasible interpretation of the principle of cosmic redshift and the invariance of the speed of light.

Toshiba devised the bladeless fan (or Air Multiplier) concept in 1981. Researchers like James Dyson and Jafari et al. further developed it. Bladeless fans are more energy-efficient, safer due to the hidden blades, easier to clean, and more adjustable than conventional fans. From a performance point of view, bladeless fans are better because they multiply mass flow rate, eliminate buffeting, consume less power, and are quieter. This paper investigates the influence of the airfoil’s outlet slit thickness on the discharge ratio by varying the outlet slit thickness of an Eppler 473 airfoil from 1.2 mm to 2 mm in intervals of 0.2 mm. Results indicated that smaller slits showed higher discharge ratios. The airfoil with a 1.2 mm slit thickness showed a discharge ratio of 18.78, a 24% increase from the discharge ratio of the 2 mm slit. The effect of outlet angle on the pressure drop across the airfoil was also studied. Outlet angles were varied from 16∘ to 26∘ by an interval of 2∘. The airfoil profile with a 24∘ outlet angle showed a maximum pressure difference of 965 Pa between the slit and leading edge. In contrast, the 16∘ outlet angle showed the least pressure difference of 355 Pa. Parameters such as average velocity, turbulent kinetic energy, the standard deviation of velocity and outlet velocity magnitude was used to assess the performance of airfoil profiles used in bladeless fan.

Concerning fan systems with an air pipe connecting air intake and a closed outlet, aerodynamic noise cannot be directly transmitted from the fan inlet and outlet to the outside. At this moment, the volute vibrational radiation noise induced casing surface vibration is the major noise component. The main factors affecting the fan vibrational noise are analyzed through theoretical derivation, then a vibrational noise optimization control method for the volute casing is proposed that considered the influence of vibro-acoustic coupling, taking the panel thickness of the volute (front-panel thickness [FT], side-panel thickness [ST], and back-panel thickness [BT]) as design variables, and the acoustical power of the volute surface and the total mass of the volute as the optimal target function. The optimization method is mainly divided into three main parts: the first was based on the simulation of unsteady flow of the fan to obtain the vibrational noise source; the second, using the design of experimental (DOE) method and the proposed numerical simulation of fluid-structure-acoustic coupling method to obtain the designing space, then the radical-based function (RBF) method is used to construct the approximate surrogate model instead of the simulation model previously mentioned, which was used to provide the basic mathematical model for the optimization of the next part; the third part, implementing the low vibrational noise optimization for the fan volute, applied the single-target (taking volute radiated acoustical power as the target function) and the multi-target (taking the volute radiated acoustical power and volute total mass as the target function) methods. In addition, the fan aerodynamic performance, volute casing surface fluctuations, and vibration response were validated by experiments, showing good agreement. It is of utmost importance that the dynamic pressure measurements and vibrational tests on the volute casing verify the accuracy of the numerical calculation. The optimization results showed that the vibrational noise optimization method proposed in this study can effectively reduce the vibration noise of the fan, obtaining a maximum value of noise reduction of 7.3 dB. The optimization identified in this paper provides a significant reference for the design of a low-vibrational-noise volute.

The Gurney flap (GF) is a miniature lift-enhancement device and is usually mounted at the trailing edge of an airfoil. The GF and has been successfully applied to isolated airfoils, multi-element airfoils, and aircraft wings as well as helicopter rotor due to its attractive features of simplicity, cost-effective and separation control. The GF also has aroused the attention of researchers in the turbomachinery industry. However, limited studies are currently available on the application of a GF to an axial fan.Hence, in this paper, we conduct a wind tunnel and computational fluid dynamic (CFD) investigation on an axial fan profiled with a NACA 65-(12)10 airfoil to evaluate the effect of the GF on the performance of the fan. We also present the detailed flow features of the fan with and without the GF after validating the simulation results with the experimental results. The experimental results show that as the GF is installed higher on the fan blade, it can produce a higher total pressure rise accompanied with a greater loss of efficiency. The installation of the GF also enlarges the work capacity of the fan. Detailed flow field analysis, including the surface pressure distribution, vorticity distribution at the trailing edge and streamline distribution of the fan, is carried out to understand the mechanisms of the effect of the GF on the performance of the fan.

This study examines the unique circumstances surrounding state-owned equity participation in non-state-controlled enterprises in China. Specifically, this study examines the impact of state-owned equity participation on the environmental, social, and governance (ESG) performance of non-state-controlled enterprises. Focusing on A-share listed firms on the Shanghai and Shenzhen Stock Exchanges and using data from 2013 to 2021, empirical testing shows that state-owned equity participation can significantly improve the ESG performance of non-state-controlled enterprises, with this conclusion remaining reliable after a series of robustness tests. Top management incentives is a mediating mechanism for state-owned equity participation in enhancing ESG performance. This study also finds that when state-owned equity participates in large enterprises or companies with a high degree of digital transformation, the effect on ESG performance is greater than that of small to medium-sized enterprises (SMEs) or enterprises with a low level of digital transformation. The findings of this study add to the current body of the existing field of research on the factors influencing corporate ESG performance and the impact of state-owned equity on corporate non-financial performance.

The cytoskeleton is a master organizer of cell cortex, organelles positioning and membrane trafficking. Therefore, playing a decisive role in establishment of apico-basal polarity. Septins are critical cytoskeleton components which function in apico-basal polarity remain weakly investigated. Here, using 3D culture system, we demonstrate that septin9 localizes at basolateral membrane (BM). Its depletion induces an inverted polarity phenotype, decreasing -catenin at BM and increasing the expression of the transforming growth factor (TGF) and the epithelial-to-mesenchymal transition (EMT) markers. Similar effects were observed upon deleting its two polybasic domains, and the mutant become cytoplasmic and apical. The cysts with an inverted polarity phenotype display an invasive phenotype, with src and cortactin accumulating at the peripheric membrane. Inhibition of TGF-receptor and RhoA rescues the polarized phenotype. Although the cysts from overexpressed-septin 9, overgrowth and present a filled lumen. Both phenotypes correspond to tumor features. This suggests that septin 9 expression and assembly through the two PB domains are essential for establishing and maintaining apico-basal polarity against tumor development through a mechanism involving TGF-dependent EMT and RhoA activity.

In this research, the other reasonable explanations for the cosmic microwave background radiation is revealed. Due to the microwave resolution, it very roughly shows the image of galaxies in the universe. Moreover, the intensity measurement on each pixel of the image is the sum of the incident microwaves from different directions, so the microwave image cannot represent the microwave sources clearly far away from the Earth. Hence, we propose a simulation after removing several strongest microwave sources, the remaining microwave radiation sources can establish a very uniform intensity distribution over a range of several ten light years. On the other hand, Sloan Digital Sky Survey reveals 200 million galaxies in the universe and, in fact, only to eliminate the contributions of all galaxies from the microwave image is impossible. The way to further obtain the fine-scale structure by only removing the few strongest microwave sources as the foreground effect will keep the other contributions from all the rest galaxies and stars. Therefore, the Cosmic Microwave Background cannot be uniquely explained the radiation which was left after the initial formation of the universe. Moreover, it is the mainly residual radiation from the un-calculated galaxies and inaccurate estimation of the microwave source strength.

Multi-view stereo (MVS) employs multi-point photography for image point positioning and three-dimensional reconstruction technology. Recently, this technology has been introduced into the monitoring of road slopes due to advances in photography and computing technology. In general, the various phases of post-image processing procedures are applied to various photographic data. In this study a novel, automated image-monitoring system is proposed to improve the ability of automatic processing. First, an Internet of things (IoT)-based digital photography system architecture was constructed to provide automatic control of camera photography and real-time transmission of image data. In addition, a visual SfM-MVS 3D reconstruction technique was used to develop related software and hardware interfaces based on the built-in Python computing framework of Photoscan Pro. The software integrates fully automatic photography, image transmission, monitoring of data processing and product release programs. The experimental results show that the system architecture can be applied to fully automatic three-dimensional monitoring of road slopes.

Purpose: This study aimed to focus on the design and development of low-cost DIY air purifiers, using a ventilating fan, air pump, water pump, and an ultrasonic generator, with regard to filtration efficacy and also cost-effectiveness that can be used during the COVID-19 pandemic and haze pollution. Methods: Six types of household air purifiers, incorporating a HEPA filter, a HEPA filter & electrostatic fiber, an air pump, an air pump & ultrasonic wave, a water pump, and a water pump & ultrasonic wave, were fabricated. The amount of particulate matter (PM) and CO₂ levels were recorded at 0, 10, 20, 30, and 60 min, then, repeated 3 times. After 10 min of the 3^rd experiment of each study, the last measurement of air pollution would be recorded. Results: At 60 min, the HEPA filter & electrostatic fiber showed the best performance regarding reduction of PM and CO₂ levels. The highest PM reduction rate had occurred at 30 min using an air pump procedure (99.330 to 100%). The CO₂ levels of all experiments had fluctuated at different times. After 10 min of a closed machine, HEPA filter & electrostatic fiber revealed the highest rate of PM elevation, while PM levels of all water-based purifier systems were decreased. A water pump and air pump were the cheapest air cleaners, when taking into account maintenance expenses and electricity charges. Conclusion: An air pump is the optimum method for reducing particulate matter at minimum cost but without the benefit of reduced humidity, while the HEPA filter & electrostatic fiber is the best system to decrease PM levels, but this requires an enclosed structure at the inlet to prevent dust coming back into the room. As filtration efficiency is increased by the use of filters & electrostatic fiber mechanisms, the more expensive the system becomes.

L-Theanine, a unique non-protein amino acid, is an important bioactive component of green tea. Previous studies have shown that L-theanine has many potent health benefits, such as anti-anxiety effect, regulation of immune response, relaxing neural tension, reducing oxidative damage. However, little is known concerning whether L-theanine can improve the clearance of mitochondrial DNA (mtDNA) damage in organisms. Here, we reported that L-theanine treatment increased ATP production and improved mitochondrial morphology to extend the lifespan of UVC-exposed nematodes. Mechanistic investigations showed that L-theanine treatment enhanced the removal of mtDNA damage and extended lifespan by activating autophagy, mitophagy, mitochondrial dynamics, and mitochondrial unfolded protein response (UPRmt) in UVC-exposed nematodes. In addition, L-theanine treatment also up-regulated the expression of genes related to mitochondrial energy metabolism in UVC-exposed nematodes. Our study provided a theoretical basis for the possibility that tea drinking may prevent mitochondrial related diseases.

Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are fast becoming the most common chronic liver disease and are often preventable with healthy dietary habits and weight management. Sugar-sweetened beverage (SSB) consumption is associated with obesity and NAFLD. However, the impact of different types of SSB, including artificially sweetened beverages (ASB), is not clear after controlling for total sugar intake and total caloric intake. In this study, we examined the association between different SSB consumption and the risk of NAFLD and NASH. A total of 3,739 US adults aged ≥20 years old who had completed 24-hour dietary recall interviews and measurements, including dietary, SSB, smoking, physical activity, and liver stiffness measurement, using the National Health and Nutrition Examination Survey 2017-2020 surveys were included in this study. Chi-square tests, t-tests, and weighted logistic regression models were utilized for analyses. The prevalence of NASH was 20.5%, and NAFLD (defined without NASH) was 32.7% of .S.U.S. adults. We observed a higher prevalence of NASH/NAFLD in men, Mexican-Americans, sugar intake from SSB, light-moderate alcohol use, individuals with lower physical activity levels, higher energy intake, obesity, and medical comorbidities. Heavy sugar consumption through SSB was significantly associated with NAFLD (aOR=1.60, 95% CI=1.05-2.45). In addition, intake of ASB only (compared to non-SSB category) was significantly associated with NAFLD (aOR=1.78, 95% CI=1.04-3.05), after adjusting for demographic, risk behaviors, and body mass index. Higher sugar intake from SSB and exclusive ASB intake are both associated with the risk of NAFLD.

Background: Clinical trails have revealed that patients with depression generally accompanied with learning and memory impairment, which critically impact on individual’s health and development. Danggui-Shaoyao-San (DSS), a famous Chinese complex prescription, significantly overcame depression and relieved cognitive disorder based on previous research and publication. However, its effectsand potential mechanism against chronic restraint stress (CRS) remained unknown. Methods: CRS animal model was established and mice were divided to six groups while they were oral administrated with Danggui-Shaoyao-San at doses of 1.25, 2.5 and 5 g/kg for 14 days. Emotional and cognitive performances were detected by behavior tests, meanwhile neural plasticity and its molecular mechanism were examined by Dil staining, western blot and immunofluorescence. Results: DSS treatment dose-dependently improved locomotion ability in open filed test, overcame depression behavior in forced swimming test and elevated plus maze test, enhanced learning and memory ability in Morris water maze test. CRS decreased number of total spines and mushroom spines, while DSS treatment dose-dependently restored these by Dil staining. Expression of BDNF and GluR1 were significantly down-regulated in CRS group, which were significantly normalized by DSS. Conclusions: DSS treatment dose-dependently reversed CRS-induced cognitive impairments by inducing structural remodeling of neurons.

Attribute reduction is a core technique in the rough set domain and an important step in data preprocessing. Researchers have proposed numerous innovative methods to enhance the capability of attribute reduction, such as the emergence of multi-granularity rough set models, which can effectively process distributed and multi-granularity data. However, these innovative methods still have many shortcomings, such as how to deal with complex constraints and how to perform multi-angle effectiveness evaluations. Based on the multi-granularity model, this study proposes a new method of attribute reduction, namely using multi-granularity neighborhood information gain ratio as the measurement criterion. This method combines both supervised and unsupervised perspectives, and by integrating multi-granularity technology with neighborhood rough set theory, constructs a model that can adapt to multi-level data features. This model can select the optimal granularity level or attribute set according to the requirements. Finally, the proposed method is experimented with on 15 UCI datasets against six other attribute reduction algorithms. The experimental outcomes, upon analysis and comparative review, substantiate the reliability and consistency of the attribute reduction approach introduced in this study.

Large-scale volumetric fracturing is generally used during shale gas development. The return rate of fracturing fluid is low, and a large amount of slickwater will be retained in the reservoir. The adsorption and desorption of partially hydrolyzed polyacrylamide (HPAM), an additive commonly used in slickwater, on the surface of shale was studied using Longmaxi Shale from the Sichuan Basin. The experimental results showed that the mass ratio of the HPAM solution to shale reached saturation adsorption at 20:1 when the concentration of HPAM solution was 1000 mg/L and 25:1 when the concentration of HPAM solution was 500 mg/L. The mass ratio of the HPAM solution to shale was fixed at 25:1, and the adsorption equilibrium was reached at a HPAM concentration of 1000 mg/L when the aqueous solution temperature was 30°C and 800 mg/L when the aqueous solution temperature was 60°C. The Langmuir adsorption model yielded a better fit than the Freundlich adsorption model. The adsorption equilibrium time at 30°C was at 60 min for a HPAM concentration of 500 mg/L, while for a concentration of 1000 mg/L, it was at 90 min. The adsorption equilibrium time at 60°C was 40 min for a HPAM concentration of 500 mg/L, whereas it was 60 min for a HPAM concentration at 1000 mg/L. The pseudo-second order kinetics model yielded better fits than the pseudo-first order kinetics model. The adsorption of HPAM on shale was strong, and the adsorbed HPAM resembled cobwebs adhering to the shale surface. HPAM on the surface of shale after adsorption could resist the desorption capacity of water. However, when the amount of adsorbed HPAM on shale increased significantly, the amount of residual HPAM on the surface of the shale decreased rapidly during desorption in deionized water. The desorption of HPAM on the shale surface followed a modified desorption model. The higher the concentration of HPAM adsorbed on the shale surface was, the easier it was to desorb, the easier it was to be removed from the shale.

Leucokinins (LKs) constitute a neuropeptide family first discovered in a cockroach and later identified in numerous insects and several other invertebrates. The LK receptors are only distantly related to other known receptors. Among insects, there are many examples of species where genes encoding LKs and their receptors are absent. Furthermore, genomics has revealed that LK signaling is lacking in several of the invertebrate phyla and in vertebrates. In insects, the number and complexity of LK expressing neurons vary, from the simple pattern in the larva of Drosophila where the entire CNS has 20 neurons of three main types, to cockroaches with about 250 of many different types. Common to all studied insects is the presence or 1-3 pairs of LK-expressing neurosecretory cells in each abdominal neuromere of the ventral nerve cord, that, at least in some insects, regulate secretion in Malpighian tubules. This review summarizes the diverse functional roles of LK signaling in insects, as well as other arthropods and mollusks. These functions include regulation of ion and water homeostasis, feeding, sleep-metabolism interactions, state-dependent memory formation, as well as modulation of gustatory sensitivity and nociception. Other functions are implied by the neuronal distribution of LK, but remain to be investigated.

Activities in the digital economy driven by information technology have rapidly increased in scope and speed in the aftermath of COVID-19. Meanwhile, social isolation accelerated by quarantine measures has increased concerns about individuals’ mental health. However, little is known about the specific consequences of online interactions, especially when applied in online fan community-based relationships where loyal community members are prevalent. Therefore, we examined whether a sense of virtual community (SOVC) can link fans’ online activities with their mental well-being and behavioral loyalty to the platform. For this purpose, we focus on BTS fandom “Adorable Representative MC for Youth” (ARMY) behaviors and attitudes on the fan community platform Weverse. With 202 valid data samples acquired from global ARMY, this study conducted a partial least squares–structural equation modeling analysis. The empirical findings reveal that SOVC in Weverse is significantly influenced by the intensity of online interactions with other fans and parasocial relationships with celebrities. SOVC is found to be the direct predictor of fans’ behavioral loyalty and mental well-being. When considering fans’ perceptions of other social media platforms, dissatisfaction with previous online fan communities enhances the intensity of online interactions with other fans in Weverse.

In order to balance the conflicts among mass flow rate, total pressure ratio, adiabatic efficiency and stall margin in a low-bypass transonic fan, the optimization of the rotor blade is implemented in this study. An advanced 3D optimization design system is adopted, and flow diagnostic methods based on vorticity dynamics are employed to discuss the flow field. Results indicate that by controlling the blade camber line curvature, significant improvements in the aerodynamic performance for the fan stage are achieved, the total pressure ratio is increased by 1.90%, while the adiabatic efficiency and mass flow rate are increased by 4.45% and 5.82%, respectively. Vorticity diagnosis suggest that there exists a close link between performance parameters and vorticity parameters in the axial fan/compressor, both azimuthal vorticity and boundary vortex flux have significant influences on the stage performance. Moreover, the boundary layer separation is accompanied by the spike of entropy and static pressure, while the derivation/gradient of these flow parameters would also suffer drastic changes under the effect of shock wave. The vorticity parameters could provide detailed flow information about the on-wall flow with high accuracy, which provides the researchers with a novel method for the turbomachinery aerodynamic design and analysis.

New innovative green concepts in electrified vertical take-off and landing vehicles currently emerge as a revolution to urban mobility going into the third dimension (vertically). The high population density of cities makes the market share highly attractive while posing an extraordinary challenge for community acceptance due to the increasing and possibly noisier commuter traffic. In addition to passenger transport, package deliveries to customers by drones may enter the market. The new challenges associated with this increasing transportation need in urban, rural and populated areas pose challenges for established companies and startups to deliver low-noise emission products. The article's objective is to revisit the benefits and drawbacks of an affordable acoustic measurement campaign focused on early prototyping. In the very early phase of product development, often considerably limited resources are available. With this in mind, the article discusses the sound power results using the enveloping surface method in a typically available low-reflection room with a reflecting floor according to DIN EN ISO 3744:2011-02. The method is applied to a subsonic electric ducted fan (EDF) unit of a 1:2 scaled electrified vertical take-off and landing vehicle. The results show that considerable information at low costs can be gained for the early prototyping stage, despite this easy-to-use, easy-to-realize, and not fine-tuned measurement setup. Furthermore, the limitations and improvements to a possible experimental setup are presented to discuss a potentially more ideal measurement environment. Measurements at discrete operating points and transient measurements across the total operating range were conducted to provide complete information on the EDF's acoustic behavior. The rotor-self noise and the rotor-stator interaction were identified as primary tonal sound sources, along with the highest broadband noise sources located on the rotor. Based on engineering experience, a first acoustic improvement treatment is also quantified with a sound power level reduction of 4dB(A). In conclusion, the presented method is a beneficial first measurement campaign to quantify the acoustic properties of an electric ducted fan unit at minimal resources in a reasonable time of several weeks when starting from scratch.

Topography represented by high resolution digital elevation models are able to inform past and present morphological process on the terrain. High resolution LiDAR data taken by the General Directorate of Map at the surroundings of the Bergama city shows great opportunities to understand the morphological process on alluvial fan on which the city is located and the flood plain of Bakırçay river near the alluvial fan. In this paper the LiDAR data collected in 2015 have been used to create DEM’s to understand the geomorphological evolution of the alluvial fan and the flood plain around it. Since the proximal roots and medial parts of the alluvial fan have been the scene for a long human settlement most topographical traces of the morphological process have been distorted. Nevertheless, the traces of past and present morphological process at the distal fan which consist the contact zone with the flood plain are very clear on the DEM created from LiDAR data. The levees and some old courses of Bergama and Bakırçay rivers have been shown on the maps which are also important to understand the ancient roads which follows these levees.

In this perspective article, we ponder topographical enhancements of artificial neural networks. In our recent paper in JMLR, we proved a quasi-equivalence between the network width and depth and also discussed the power of intra-links, which can be viewed as network height. In 1982, Hopfield published a network to model human associative memory, which contains many loops for dynamic evolution toward fixed points. Based on noising-denoising loops, diffusion models are recently developed to enable Bayesian modeling and inference with big data. Furthermore, we envision development of multi-AI-agent systems through “netware” engineering as a quantum leap of software engineering for emergent behaviors and autonomous AI at individual and population levels. We believe that the novel use of links and loops in space and time via multi-scale coupling would catalyze the next-generation neural networks.

Air passenger traffic prediction is crucial for the effective operation of civil aviation airports. Despite some progress in this field, the prediction accuracy and methods need further improvement. This paper proposes an integrated approach to the prediction of air passenger index as follows. Firstly, the air passenger index is defined and classified by the K-means clustering method. Based on the mutual information (MI) principle, the information entropy is used to analyze and select the key influencing factors of air passenger travel. By incorporating the MI principle into the support vector regression (SVR) framework, this paper presents an innovative MI-SVR machine learning model used to predict the air passenger index. Finally, the proposed model is validated by passenger throughput data of the Shanghai Pudong International Airport, China. The experimental results prove the model feasibility and effectiveness by comparing them with conventional methods, such as ARIMA, LSTM, and other machine learning models, outperformed by the MI-SVR model. Besides, it is shown that the prediction effect of each model could be improved by introducing influencing factors based on mutual information. The main findings are considered instrumental to the airport operation and air traffic optimization.

Air passenger traffic prediction is crucial for the effective operation of civil aviation airports. Despite some progress in this field, the prediction accuracy and methods need further improvement. This paper proposes an integrated approach to the prediction of air passenger index as follows. Firstly, the air passenger index is defined and classified by the K-means clustering method. Based on the mutual information (MI) principle, the information entropy is used to analyze and select the key influencing factors of air passenger travel. By incorporating the MI principle into the support vector regression (SVR) framework, this paper presents an innovative MI-SVR machine learning model used to predict the air passenger index. Finally, the proposed model is validated by passenger throughput data of the Shanghai Pudong International Airport, China. The experimental results prove the model feasibility and effectiveness by comparing them with conventional methods, such as ARIMA, LSTM, and other machine learning models, outperformed by the MI-SVR model. Besides, it is shown that the prediction effect of each model could be improved by introducing influencing factors based on mutual information. The main findings are considered instrumental to the airport operation and air traffic optimization.

The cuttlebone-like structure is a complex porous bionic structure with asymmetric sinusoidal S-shaped wall structure connecting laminar septa, and studies have shown that the cuttlebone-like structure has light weight, high strength and excellent energy absorption capability. It has become an important research to investigate the mechanical mechanism of cuttlebone-like structure and to design a bionic structure beyond nature structure based on it. In order to investigate the mechanical properties of the static compression and shearing processes of the cuttlebone-like structure, this paper establishes theoretical formulas and analyzes the influence of dimensionless parameters such as height-to-thickness ratio $\lambda$, period-to-thickness ratio $\xi$ and amplitude to period ratio $\eta$ on the compression and shearing processes with the help of ABAQUS finite element software.The parameter sensitivity analysis method was used to compare the important influence degree of each dimensionless parameter on the mechanical properties of the structure and to determine the relative optimal parameters of the structural mechanical properties under compression and shearing. Based on the relatively optimal parameter of the cuttlebone-like structure, the cross-sectional geometry of the structure is improved to build a new cuttlebone-like structure.The experimental results showed that the new cuttlebone-like structure with revised cross-section improved the mechanical properties of the cuttlebone-like structure.The study results are of theoretical guidance to enhance the mechanical properties and geometric design of cuttlebone-like structures.

A Systemic Lupus Erythematosus (SLE) is a prototypical systemic autoimmune disease characterized by a complex interplay of genetic, molecular, and cellular factors. It is considered a multifactorial disorder influenced by genetic susceptibility, environmental triggers, and dysregulated immune responses. Understanding the molecular and cellular mechanisms driving SLE pathogenesis has been instrumental in developing targeted therapies to manage the disease and improve patient outcomes. In this essay, we will delve into the intricate molecular and cellular processes underlying SLE and examine the key lessons learned from human therapies.

Murine herpesvirus-68 (MHV-68) productively infects the mouse lungs, exhibiting a complex pathology characteristic of both acute viral infections and chronic respiratory diseases. We sought to discover proteins differentially expressed in bronchoalveolar lavage (BAL) from mice infected with MHV-68. Mice were infected intranasally with MHV-68. After 9 days, as the lytic phase of infection resolved, differential BAL proteins were identified by 2D electrophoresis and mass spectrometry. Of 23 unique proteins, acute phase proteins, vitamin A transport, and oxidative stress response factors Pdx6 and EC-SOD (Sod3) were enriched. Correspondingly, iNOS2 was induced in lung tissue by 7 days post infection. Oxidative stress was partly a direct result of MHV-68 infection, as reactive oxygen species (ROS) were induced in cultured murine NIH3T3 fibroblasts and human lung A549 cells infected with MHV-68. Finally, mice were infected with a recombinant MHV-68 co-expressing inflammatory cytokine murine interleukin 6 (IL6) showed exacerbated oxidative stress and soluble type I collagen characteristic of tissue recovery. Thus, oxidative stress appears to be a salient feature of MHV-68 pathogenesis, in part caused by lytic replication of virus and IL6. Proteins and small molecules in lung oxidative stress networks therefore may provide new therapeutic targets to ameliorate respiratory virus infections.

Recent advances in differential topology single out four-dimensions as being special, allowing for vast varieties of exotic smoothness (differential) structures, distinguished by their handlebody decompositions, even as the coarser algebraic topology is fixed. Should the spacetime we reside in takes up one of the more exotic choices, and there is no obvious reason why it shouldn't, apparent pathologies would inevitably plague calculus-based physical theories assuming the standard vanilla structure, due to the non-existence of a diffeomorphism and the consequent lack of a suitable portal through which to transfer the complete information regarding the exotic physical dynamics into the vanilla theories. An obvious plausible consequence of this deficiency would be the uncertainty permeating our attempted description of the microscopic world. We tentatively argue here, that a re-inspection of the key ingredients of the phenomenological particle models, from the perspective of exotica, could possibly yield interesting insights. Our short and rudimentary discussion is qualitative and speculative, because the necessary mathematical tools have only just began to be developed.

It is well known but under-appreciated in astrophysical applications, that it is possible for gravity to take on a life of its own in the form of Weyl-curvature-only metrics (note we are referring to the Weyl-only solutions of ordinary General Relativity, we are not considering Weyl conformal gravity or any other modified gravity theories), as numerous examples demonstrate the existence of gravitational fields not being sourced by any matter. In the weak field limit, such autonomous gravitational contents of our universe manifest as solutions to the homogeneous Poisson's equation. In this note, we tentatively explore the possibility that they may perhaps account for some phenomenologies commonly attributed to dark matter. Specifically, we show that a very simple solution of this kind exists that can be utilized to describe the rising tails seen in many galaxy rotation curves, which had been difficult to reconcile within the cold dark matter or modified Newtonian dynamics frameworks. This solution may also help explain the universal $\sim 1$Gyr rotation periods of galaxies in the local universe.

Semantic communication is not obsessed with improving the accuracy of transmitted symbols, but is concerned with expressing the desired meaning that the symbol sequence exactly carried. However, the generation and measurement of semantic messages are still an open problem. Expansion combines simple things into complex systems and even generates intelligence, which is consistent with the evolution of the human language system. We apply this idea to semantic communication system, quantifying and transmitting semantics by symbol sequences, and investigate the semantic information system in a similar way as Shannon did for digital communication systems. This work was the first to propose the concept of semantic expansion and knowledge collision, which may provide a new paradigm for semantic communications. We believe that expansion and collision will be the cornerstone of semantic information theory.

In foggy weather scenarios, the scattering and absorption of light by water droplets and particulate matter cause object features in images to become blurred or lost, presenting a significant challenge for target detection in autonomous driving vehicles. To tackle this problem, this study proposes a foggy weather detection method, YOLOv5s-Fog, based on the YOLOv5s framework. The model enhances the feature extraction and expression capabilities of YOLOv5s by introducing a novel target detection layer, SwinFocus. Additionally, this research incorporates decoupled head into the model and replaces the conventional non-maximum suppression method with Soft-NMS. Experimental results demonstrate that these improvements effectively enhance the detection performance for blurry objects and small targets in foggy weather conditions. Compared to the baseline model YOLOv5s, YOLOv5s-Fog achieves a 5.4% increase in mAP on the RTTS dataset, reaching 73.4%. This method provides technical support for rapid and accurate target detection in adverse weather conditions, such as foggy weather, for autonomous driving vehicles.

We live in extraordinary times, where COVID-19 pandemic has brought the whole world to a screeching halt. Tensions and contradictions that surround the pandemic ridden world include the availability, and the lack thereof, various facial protection measures to mitigate the viral spread. Here, we comprehensively explore the different type of facial protection measures, including masks, needed both for the pubic and the health care workers (HCW). We discuss the anatomy, the critical issues of disinfection and reusability of masks, the alternative equipment available for the protection of the facial region from airborne diseases, such as face shields and powered air purifying respirators (PAPR), and the skin-health impact of prolonged wearing of facial protection by HCW. Clearly, facial protection, either in the form of masks or alternates, appears to have mitigated the pandemic as seen from the minimal COVID-19 spread in countries where public mask wearing is strictly enforced. On the contrary, the healthcare systems, that appear to have been unprepared for emergencies of this nature, should be appropriately geared to handle the imbalance of supply and demand of personal protective equipment including face masks. These are two crucial lessons we can learn from this tragic experience.

In this tutorial review, we compare and contrast the chemical mechanisms of electrophile/oxidant sensing, and the molecular mechanisms of signal propagation. We critically analyze biological systems in which these different pathways are believed to be manifest and what the data really mean. Finally, we discuss applications of this knowledge to disease treatment and drug development.

Sphalerite has been recognized as the most important carrier of critical metal of Indium (In) due to that In mainly exists in the sphalerite lattice by isomorphic substitution. There are two significant replacing schemes for In entry into sphalerite, these are, Ag++In3+→2Zn2+ and Cu++In3+→2Zn2+. In order to understand the reaction process and constraints of the two substitution schemes, this paper uses first-principles methods to calculate In and Ag, Cu replacing Zn in sphalerite. According to the substitution schemes of Ag++In3+→2Zn2+ and Cu++In3+→2Zn2+, two doped sphalerite systems of Zn30InAgS32 and Zn30InCuS32 were constructed using 2×2×2 supercell model of sphalerite. Firstly, the pressure is controlled to 30MPa, and the temperature is set from 20-40MPa to simulate the response of the two doped sphalerite systems to temperature; Then, the control temperature was unchanged to 600K, and the pressure was set from 20-40MPa to investigate the pressure control of the two doped sphalerite systems. The lattice parameters, substitution energy, electronic structure, and population analysis of the designed models before and after replacement have been critically compared. The main conclusions can be drawn that it is more stable for In to enter sphalerite via the coupled substitution scheme Cu++In3+→2Zn2+, and the conditions that the two substitution schemes most likely to occur are 650K and 40MPa. This study not only reveals the physical and chemical properties of In-rich sphalerite formed by the two reaction processes of Ag++In3+→2Zn2+ and Cu++In3+→2Zn2+, but also has a certain enlightenment effect on the search for indium in sphalerite, and promotes the application of first principles in mineralization analysis.

An energy model that correlates fan airflow, head, speed, and system power input is essential to detect device faults and optimize control strategies in fan systems. Since the application of variable frequency drives (VFDs) makes the motor efficiency data published by manufacturers inapplicable, the fan efficiency and drive (belt-motor-VFD) efficiency must be identified for each individual system to obtain accurate energy models. The objectives of this paper are to identify an energy model of existing VFD-motor-fan systems using available experimental data and demonstrate its applications in loose belt fault detection and virtual airflow meter development for optimal control. First, an approach is developed to identify the fan head, fan efficiency and drive efficiency curves using available fan head, speed, and system power input as well as temporarily measured airflow rate without measuring shaft power. Then the energy model is identified for an existing VFD-motor-fan system. Finally, the identified model is applied to detect the slipped belt faults and develop the virtual airflow meter. The experiment results reveal that the developed approach can effectively obtain the energy model of VFD-motor-fan systems and the model can be applied to effectively detect slipped belt faults and accurately calculate the fan airflow rate.

Drug nanosuspensions offer a promising approach to improve bioavailability for poorly soluble drug candidates. Such formulations often necessitate the inclusion of an excipient to stabilize the drug nanoparticles. However, a rationale to choose the correct excipient for a given drug candidate remains unclear. To gain molecular insight into formulation design, this work first utilizes molecular dynamics simulation to computationally investigate drug-excipient interactions for a number of combinations that have been previously studied experimentally. We find that hydrophobic interactions drive excipient adsorption to drug nanoparticles, and that the fraction of polar surface area serves as a predictor for experimental measurements of nanosuspension stability. To test these ideas prospectively, we applied our model to an uncharacterized drug compound, GDC-0810. Our simulations predicted that salt forms of GDC-0810 would lead to more stable nanosuspensions than the neutral form; therefore, we tested the stability of salt GDC-0810 nanosuspensions and found that the salt form readily formed nanosuspensions even without excipient. To avoid computationally expensive simulations in the future, we extended our model by showing that simple, two-dimensional properties of the single drug molecule can be used to rationalize nanosuspension design without simulation. In all, our work demonstrates how computational tools can provide molecular insight into drug-excipient interactions, and aid in rational formulation design.

Prediction of protein-ligand binding affinities is crucial for computational drug discovery. A number of deep learning approaches have been developed in recent years to improve the accuracy of such affinity prediction. While the predicting power of these systems have advanced to some degrees depending on the dataset used for model training and testing, the effects of the quality and quantity of the underlying data have not been thoroughly examined. In this study, we employed erroneous datasets and data subsets of different sizes, created from one of the largest databases of experimental binding affinities, to train and evaluate a deep learning system based on convolutional neural networks. Our results show that data quality and quantity do have significant impacts on the prediction performance of trained models. Depending on the variations in data quality and quantity, the performance discrepancies could be comparable to or even larger than those observed among different deep learning approaches. In particular, the presence of proteins during model training leads to a dramatic increase in prediction accuracy. This implies that continued accumulation of high-quality affinity data, especially for new protein targets, is indispensable for improving deep learning models to better predict protein-ligand binding affinities.

Cooling fans are one of the critical components of air-forced (AF) dry-type transformers for regulating internal temperatures. Therefore, effective malfunction detection is crucial to maintain the transformer temperature within an acceptable range and prevent overheating. Regular maintenance occurs periodically and issues with cooling fans may arise between maintenance periods, leading to prolonged operation under malfunctioning conditions and potential failures. In addition, utilities typically have online information about whether a fan works or not without providing information about cooling fan malfunctioning circumstances. To address these challenges, this study proposes learning-based online monitoring techniques to detect malfunctions in AF transformer cooling fans. Random forests (RFs) and convolutional neural networks (CNNs) are developed to classify the audio signals from cooling fans into normal and malfunctioning classes. Unlike RFs, which require separate feature extraction, CNNs are trained based on spectrogram images derived from audio signals. Thus, various time-frequency techniques are utilized for feature extraction in RFs. Besides, multiple data augmentation techniques are employed to enhance the dataset size and diversity. Algorithmic performance is optimized through hyperparameter tuning and classifier threshold adjustment. Simulations reveal that CNNs outperform RFs, whereas the latter provides superior interpretability of acoustic features compared to the former.

This survey of research literature is an overview of the current state of science addressing DSM-5 diagnostic criteria as it relates to identifying Autism Spectrum Disorder (ASD) in young children. Selected sources are of high quality and have been published since 2020 in peer-reviewed journals relevant to children’s health. The narrative is organized from the earliest to the most recent publications and is divided into sections around categories and themes that highlight the main arguments, findings, and controversies identified by researchers. There are indications in the literature that while ASD can be identified and differentiated from other developmental disorders in young children, doing so requires that clinicians who have relied on the DSM-5 should also use multiple measures, including other formalized screening tools as assessments that gather observational input from parents and caregivers, as well as findings from physical examinations, laboratory investigations, and magnetic resonance imagining (MRI). This high level of corroboration points to an emerging diagnosis paradigm through which transdiagnostic approaches to early diagnosis and intervention may exist.

Temper embrittlement is a major challenge encountered during the heat treatment of high-performance steels for large forgings. This study investigates the microstructural evolution and mechanical properties of Cr-Ni-Mo-V thick-walled steel, designed for new large forgings with a tensile strength of 1500 MPa, under different tempering cooling rates. Optical microscopy (OM), scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD) were employed to analyze the microstructural features. The results demonstrate that the embrittlement occurring during air cooling after tempering is attributed to the concentration of impurities near Fe3C at the grain boundaries. The low-temperature impact toughness at -40°C after water quenching reaches 29 J due to the accelerated cooling rate during tempering, which slows down the diffusion of impurity elements towards the grain boundaries, resulting in reduced concentration and dislocation density, and increased stability of the grain boundaries, thereby enhancing toughness. the bainite content decreases and the interface between martensite and bainite undergoes changes after water quenching during tempering. These alterations influence the crack propagation direction within the two-phase microstructure, further modifying the toughness. These findings contribute to the understanding of temper embrittlement and provide valuable guidance for optimizing heat treatment processes to enhance the performance of high-performance steels in large forgings.

A novel indole, microindolinone A (1), was isolated from a deep-sea-derived actinomycete Microbacterium sp. MCCC 1A11207, together with 18 known compounds (2–19). By detailed analysis of the ¹H, ¹³C, HSQC, COSY, HMBC, HRESIMS, and CD data, the absolute configuration of 1 was elucidated as 5R-hydroxy-4,5,6,7-tetrahydroindole-4-one. Noteworthily, 1 is the second example of a saturated indole isolated from nature.

Ischemic stroke is one of the most disabling diseases and a leading cause of death globally. Despite advances in medical care, the global burden of stroke continues to grow, as no effective treatments to limit or reverse ischemic injury to the brain are available. However, recent preclinical findings have revealed the potential role of transient receptor potential cation 6 (TRPC6) channels as endogenous protectors of neuronal tissue. Activating TRPC6 in various cerebral ischemia models has been found to prevent neuronal death, whereas blocking TRPC6 enhances sensitivity to ischemia. Evidence has shown that Ca2+ influx through TRPC6 activates cAMP response element-binding protein (CREB), an important transcription factor linked to neuronal survival. Additionally, TRPC6 activation may counter excitotoxic damage resulting from glutamate release by attenuating the activity of NMDA receptors of neurons by posttranslational means. Unresolved though, are the roles of TRPC6 channels in non-neuronal cells such as astrocytes and endothelial cells. Moreover, TRPC6 channels may have detrimental effects on the blood-brain barrier, although their exact role in neurovascular coupling requires further investigation. This review discusses evidence-based cell-specific aspects of TRPC6 in the brain to assess the potential targets for ischemic stroke management.

Proteases or peptidases are hydrolases that catalyze the breakdown of polypeptide chains into smaller peptide subunits. Proteases exist in all life forms, including archaea, bacteria, protozoa, insects, animals, and plants, due to their vital functions in cellular processing and regulation. There are several classes of proteases in the MEROPS database based on their catalytic mecha-nisms. This review focuses on the post-proline cleaving enzymes (PPCEs), especially the prolyl endoprotease/oligopeptidase (PEP/POP). To date, most PPCEs studied are of microbial and ani-mal origins. Recently, there are reports of new plant PPCEs. The most common PEP/POP are members of the S9 family that comprise two conserved domains. The substrate-limiting β-propeller domain prevents unwanted digestion, while the α/β hydrolase catalyzes reaction at the carboxyl-terminal of proline residues. PPCEs have diverse applications, are widely used in the beer brewing industry, and have potential as therapeutic agents for Alzheimer’s disease and celiac disease by targeting proline-rich substrates. Protein engineering via mutagenesis has been performed to improve heat resistance, pepsin-resistant capability, specificity, and protein turno-ver of PPCEs for pharmacological applications. This is the first comprehensive review to cover the biotechnological applications of PPCEs and discuss the unique prolyl cleaving activity of dif-ferent enzymes based on the recent structure-function studies from diverse taxa.

The aim of this study was to assess the best timing to perform arthrocentesis in the management of temporomandibular disorders with regards to conservative treatment. A systematic search based on PRISMA guidelines, including a computer search with specific keywords, reference list search, and manual search was done. Relevant articles were selected after 3 search rounds for final review based on 6 predefined inclusion criteria, followed by a round of critical appraisal. Eleven publications, including 5 randomized controlled trials and 6 prospective clinical studies informed this review. The studies were divided into 3 groups based on the timing of arthrocentesis: 1). Arthrocentesis as the initial treatment, 2). Early arthrocentesis, and 3). Late arthrocentesis. Meta-analyses compared the efficacy of improvement in mouth opening and pain reduction in the 3 groups. The results were statistically significant and favoured early arthrocentesis, followed by late arthrocentesis in terms of both improvements in mouth opening and pain reduction. All 3 groups showed improvement in mouth opening and pain reduction. We conclude that early arthrocentesis may be able to produce the best clinical results, while arthrocentesis before attempting conservative treatment may produce less favourable outcomes.

This communication investigates possible anomalies in the lithosphere atmosphere and ionosphere on the occasion of the ML=3.3 earthquake that occurred on 1st January 2023 close to Guidonia Montecelio (Rome, Italy). This earthquake followed another event on 23 December 2022 of magnitude ML=3.1 with a very close epicentre (distance less than 1km). Seismological investigations clearly show an acceleration of seismicity in the last six months in the area. Two solutions of fitting time to failure power law on the Cumulative Benioff strain curve are the more likelihood: the ML3.3 of 1 January is the mainshock of seismic sequence or incoming earthquakes of a magnitude of about 4.1 provides a slightly better fit of the seismic data. Further investigation are necessary to assess if the accumulated stress have been totally released or not. No atmospheric anomalies related to this seismic activity have been identified even if some SO2 emissions could come from tectonic or volcanic sources in the South-Tyrrhenian Sea. Swarm satellites' magnetic data shows an anomalous track on 16 December 2022, which is temporally compatible with the seismic acceleration but other sources for the anomalous signal are also possible.

Over the past few decades, phototherapy, encompassing the utilization of both natural and artificial light, has emerged as a dependable and non-invasive strategy for addressing a diverse range of illnesses, diseases, and infections. This therapeutic approach, primarily known for its efficacy in treating skin infections such as herpes and acne lesions, involves the synergistic use of specific light wavelengths and photosensitizers like methylene blue. Photodynamic therapy, as it is termed, relies on the generation of antimicrobial reactive oxygen species (ROS) through the interaction between light and externally applied photosensitizers. Recent research, however, has highlighted the intrinsic antimicrobial properties of light itself, marking a paradigm shift in focus from exogenous agents to the inherent photosensitivity of molecules found naturally within pathogens. Chemical analyses have identified specific organic molecular structures and systems, including porphyrins and conjugated C=C bonds, as pivotal components in molecular photosensitivity. Given the prevalence of these systems in organic life forms, there is an urgent need to investigate the potential impact of phototherapy on individual molecules expressed within pathogens and discern their contributions to the antimicrobial effects of light. This review delves into the recently unveiled key molecular targets of phototherapy, offering insights into their potential downstream implications and therapeutic applications. By shedding light on these fundamental molecular mechanisms, we aim to advance our understanding of phototherapy's broader therapeutic potential and contribute to the development of innovative treatments for a wide array of microbial infections and diseases.

Design guidelines and the Design Review Panel (DRP) are crucial components in ensuring consistent and high-quality design within masterplan sites. This study focuses on New Zealand, examining the challenges faced by industry partners in adapting to masterplanned design guidelines. The case study centers on Hobsonville Point, the largest Government lead masterplan community in New Zealand, which promotes sustainable and higher-density living—an uncommon concept in the country. We conducted interviews with 18 key stakeholders involved in the development of Hobsonville Point. The results show that the DRP provides flexible judgments and insightful information that better accommodates individual development characteristics than the strict numerical standards specified in design guidelines. This study underscores the importance of DRP in producing good design outcomes, especially when they are involved at the very beginning of the design process. Additionally, we took note of stakeholder concerns about DRP members' expertise and the possible effects of high turnover rates on the design process. To strive for continual improvement, future empirical studies on the DRP process are encouraged to enhance proficiency and dependability. Design guidance should be prioritised to ensure climate-related design is implemented to promote sustainable urban development.

When an aircraft malfunctions, quickly and accurately identifying the faulty unit is essential for ensuring normal operation. Unfortunately, maintenance engineers often struggle to acquire the necessary fault-related knowledge due to poor management and utilization of aircraft fault documents. To address this issue, we introduce knowledge graph technology into the field of aircraft fault diagnosis, exploring its construction and application for effective knowledge management. Our work starts by analyzing the critical knowledge elements required for aircraft fault diagnosis and designing a schema layer for fault knowledge graphs. We then we then combine deep learning and heuristic rules to extract fault knowledge from both structured and unstructured data, enabling the construction of aircraft fault knowledge graphs. Finally, we develop a fault question-answering system based on fault knowledge graphs that can accurately give solutions to questions posed by maintenance engineers. Our practice demonstrates that knowledge graphs provide an effective means of managing aircraft fault knowledge, assisting engineers in locating fault reasons accurately and quickly.

To determine the fracture rate of ceramic crowns and causes of ceramic crown failure, this study used keywords—namely “endocrown,” “veneered fixed dental prosthesis,” “monolithic lithium disilicate (LS2),” and “all-ceramic single crown”—to search for articles published in English from 2005 to 2023 in the PubMed electronic database. Rather than using the Boolean logic algorithm between MESH terms and keywords, we accurately calculated the numbers of final clinically tracked cases with crown fractures from the contents of articles. The titles and abstracts of many related articles focused on implant or abutment fracture, while crown fracture was investigated and mentioned only in the main texts of the articles. Our studies included those crowns as well as having more complete data collection. Our search yielded 228, 93, 404, and 358 articles for the keywords “endocrown,” “veneered fixed dental prosthesis,” “monolithic lithium disilicate (LS2),” and “all-ceramic single crown,” respectively. We used the Newcastle–Ottawa Scale (NOS) to assess article quality, and our inclusion criteria were randomized controlled trials (RCT) and cohort study articles involving more than 3 years of follow-up and more than 20 cases. After reviewing, 16 high-quality articles were selected for analysis. The 4.4% crown fracture rate recommended on the basis of most clinical results was achieved in only 6 of the 16 articles. In these 6 articles, the researchers concluded the following reasons that may cause the crown fractures: the thickness of the veneer ceramic material; the connector dimensions; pontic span of the fixed prosthesis; the type of cement; the treatment of the ceramic surface before luting. Other articles inferred that the computer-aided design libraries that were insufficient for the creation of appropriate anatomically supported frameworks for prostheses with ceramic veneers; the thermal expansion coefficient and fracture toughness of the framework material did not match those of the veneer ceramic, resulting in an insufficient area supporting the ceramic veneer then leads to premature crown failure after a long period chewing. The future prospective for material developing could focus on solving those problems and have better clinical results.

Since the 21st century, China's urbanization process has been rapid development, the concept and function of urban public space in the city has been gradually paid attention to. In order to guarantee life and water, most urban construction relies on rivers, and Bridges are the most important way to communicate between urban areas. The main functional part of the bridge is the span structure, that is, the bearing structure of the bridge, and the lower part of the "gray" space formed by the bridge structure. Considering the social level, with the economic growth and urbanization development, people have brought a better living environment and quality of life, and also improved the requirements for urban public environment. In the increasingly tense urban space, how to use and transform the space under the bridge is a problem that needs to be considered and solved. In view of this problem, in this study, we try to solve the micro-transformation of space under Bridges in cities through public art from the perspective of "regional culture" and "art for all". This paper analyzes the micro-transformation of space art under Bridges in two large cities of Shanghai and Foshan, namely, the space under Bridges under Songhong Road in Shanghai, the space under Bridges under Central Of Suzhou River and the space under Bridges under Pingsheng Bridge in Foshan. This paper discusses the cultural intervention of "regional culture" in the micro-transformation of the space under the bridge, and the influence and effect of "art for all" on the public art space under the bridge after the transformation to the community and the public.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

A pilot study regarding the transplantation of 100 specimens of the critically endangered Pinna nobilis took place in summer of 2019 in Maliakos Gulf (Central Aegean, Greece). In this study we present the relationships between total height (HT, in cm), unburied length (UL, in cm), and shell width (SW, in cm) for P. nobilis and the relationship between HT and net weight (W, in g). Length-length relationships were all linear for all cases: r2 > 0.900), whereas the relationship between HT and W was exponential with the value of the exponent b being allometric. "Ecology, Conservation and Restoration of Threatened Animal"

As the first time, 0D-1D-3D and fully 3D steady-state aero-thermo-fluid simulations of a structural oil-to-air Fan Outlet Guide Vane Cooler (FOGVC) in a jet engine are presented. Using the commercial softwares Ansys Fluent, the thermo-mechanical module of Ansys and the 1D fluid solver Flownex, 5 simulation types (3D fully conjugate heat transfer with and without a thin wall model, 3D with a thin wall model, 1D-3D coupled, 1D and 0D) corresponding to 4 levels of simplification in 3 possible domains (oil, oil-metal and oil-metal-air) have been compared to provide selection criteria when a determined level of accuracy in the simulations without prohibited computational times is desired. The methodologies are applied to two different oil internal cavities: an inverted U with rectangular cross section and a coil internal cavity with a circular cross section. The obtained results show that depending on the scope of the research (outlet oil temperature, dissipated heat rate or oil pressure drop) and the accuracy of the results, one method or the other may be used. Experimental data would be needed to validate the numerical results by all employed methodologies and geometries.