The increased complexity of modern systems is calling for an integrated and comprehensive approach to system design and development and in particular, a shift towards Model-Based Systems Engineering (MBSE) approaches for system design. The requirements that serve as the foundation for these intricate systems are still primarily expressed in Natural Language (NL), which can contain ambiguities and inconsistencies that hinder their direct translation into models. The colossal developments in the field of Natural Language Processing (NLP) in general and Large Language Models (LLMs) in particular can serve as an enabler for the conversion of NL requirements into semi-machine-readable requirements. This is expected to facilitate their standardization and use in a model-based environment. This paper discusses a two-fold strategy for converting NL requirements into semi-machine-readable requirements using language models. The first approach involves creating a requirements table by extracting information from free-form NL requirements. The second approach is an agile methodology that facilitates the identification of boilerplate templates for different types of requirements based on observed linguistic patterns. For this study, three different LLMs were utilized. Two of these models were fine-tuned versions of Bidirectional Encoder Representations from Transformers (BERT), specifically aeroBERT-NER and aeroBERT-Classifier, which were trained on annotated aerospace corpora. Another LLM, called flair/chunk-english, was utilized to identify sentence chunks present in NL requirements. All three language models were utilized together to achieve the standardization of requirements. To demonstrate the effectiveness of the methodologies, requirements from Parts 23 and 25 of Title 14 Code of Federal Regulations (CFRs) were employed, and a total of two, five, and three boilerplate templates were identified for design, functional, and performance requirements, respectively.

Various renewable energy sources such as wind power and photovoltaic (PV) have been increasingly integrated into the power system through power electronic converters in recent years. However, power electronic converter-driven stability issues under specific circumstances, for instance, modal resonances might deteriorate the dynamic performance of the power systems or even threaten the overall stability. In this paper, the integration impact of a hybrid renewable energy source (HRES) system on modal interaction and converter-driven stability is investigated in an IEEE 16-machine 68-bus power system. Firstly, an HRES system is introduced, which consists of full converter-based wind power generation (FCWG) and full converter-based photovoltaic generation (FCPV). The equivalent dynamic models of FCWG and FCPV are then established, followed by the linearized state-space modeling. On this basis, converter-driven stability analyses are performed to reveal the modal resonance mechanisms of the interconnected power systems and the modal interaction phenomenon. Additionally, time-domain simulations are conducted to verify effectiveness of dynamic models and support the converter-driven stability analysis results. To avoid detrimental modal resonances, an optimization strategy is further proposed by retuning the controller parameters of the HRES system. The overall results demonstrate the modal interaction effect between external AC power system and the HRES system and its various impacts on converter-driven stability.

The goods and services produced by forest vegetation ecosystem are the driving force for the rapid, high-quality and sustainable development of human society. In history, with the increase of population and economic development, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services in a country or a region. To meet the demands, most of the original forest has become farmland, plantation and grass and crops land. As a result, the plant water relationship changed from equilibrium to non-equilibrium, which easily led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the question and realize the sustainable utilization of soil water resources and the high-quality sustainable development of forest, it is necessary to apply the limit theory of plant utilization of soil water resources and the vegetation carrying capacity theory in the critical period of plant-water relationship regulation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit and realize high-quality and sustainable development.

This study explored the correlation between concentrations of phenolic compounds (phenols, tannins, and flavonoids) and the versatility of woody medicinal plants in the Caatinga, a seasonally dry forest region in Brazil. We examined whether these compounds influence the versatility of plants used by populations, given their known therapeutic properties. Plants were categorized as high or low versatility based on their relative importance (RI) values ​​at the regional level. Samples collected in Catimbau National Park, Pernambuco, were analyzed using colorimetric methods: Folin-Ciocalteu reagent for total phenols, casein precipitation for tannins, and aluminum chloride complexation for flavonoids. Contrary to expectations, no significant differences in phenolic compound concentrations were found between the high and low versatility groups. Higher levels of total phenols and tannins were observed in Myracrodruon urundeuva and Anadenanthera colubrina, both highly versatile species. However, less versatile species, such as Mimosa tenuiflora and Schinopsis brasiliensis, also showed high levels. Flavonoid content, notably lower than phenols and tannins, did not show significant variation between groups. Although phenolic compounds contribute to the therapeutic properties of medicinal plants, their concentration alone does not determine the versatility of plants in the Caatinga. Versatility is more likely influenced by ecological conditions, cultural practices, and species availability. This study highlights the need to integrate multiple perspectives in ethnopharmacological research.

The Amazonian shrub Myrciaria dubia (Kunth) McVaugh, known as "camu-camu", produces vitamin C-rich fruits of growing commercial interest. However, sustainable utilization requires assessment and protection of the genetic diversity of the available germplasm. We hypothesized that the ex situ M. dubia germplasm bank assembled from eight river basins across the Peruvian Amazon would harbor substantial genetic diversity and have a genetic population structure. This study aimed to (1) develop new polymorphic microsatellite markers, (2) characterize genetic diversity and validate the hypothesis in the ex situ germplasm, and (3) construct a core subset representing maximum allelic variability. Sixteen polymorphic microsatellite loci were developed using an enrichment approach. The evaluation of 336 genotypes from 43 accessions originating from eight river basins of the germplasm bank corroborated this hypothesis, revealing high gene diversity, with observed heterozygosity ranging from 0.468 to 0.644 and expected heterozygosity from 0.684 to 0.817 at the river basin level. Analysis of molecular variance showed a higher genetic variation within accessions and river basins, at 73% and 86%, respectively, than among accessions and river basins, at 27% and 14 %, respectively. Bayesian clustering detected the presence of ten genetic clusters, with several degrees of admixture among river basins. The Putumayo River basin showed a clear genetic homogeneity. A core collection of 84 genotypes was constructed, thus covering 86.7% of the global allelic diversity. These results have important implications for M. dubia conservation strategies and breeding programs, in demonstrating a need for genetic connectivity between populations but preserving unique genetic resources in isolated basins. These results validate the expected levels of diversity and population subdivision in a crop and stress the need to secure genetically diverse germplasms, underscoring the importance of thorough genetic characterization for ex situ germplasm management.

A two-stage pilot plant study has been completed that evaluated the performance of a reverse osmosis (RO) membrane process for the treatment of a feedwater that consisted of a blend of nanofiltration (NF) concentrate and brackish groundwater. Membrane performance was assessed by monitoring the process operation, collecting water quality data, and documenting the blended feedwater’s impact on fouling due to a combination of, or solely caused by, plugging, scaling, microbiological, or organic means. Fluorescence and biological activity reaction tests were used to identify the types of organics and microorganisms present in the blended feedwater. Additionally, scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDS) were used to analyze suspended matter that collected on the surfaces of cartridge filters used in the pilot’s pretreatment system. SEM and EDS were also used to evaluate solids collected on the surfaces of 0.45-µm silver filter pads after filtering known volumes of NF concentrate and RO feedwater blends. Water quality analyses confirmed that the blended feedwater contained little to no dissolved oxygen, and the blended feedwater was absent of a significant amount of particulate matter as defined by silt density index and turbidity measurements. However, water quality results suggested that the presence of sulfate, sulfide, iron, anaerobic bacteria, and humic acid organics likely contributed to the formation of pyrite observed on some of the membrane surfaces autopsied at the conclusion of pilot operations. It was determined that first-stage membrane productivity was impacted by the location of cartridge filter pretreatment; however, second-stage productivity was maintained with no observed flux decline during the entire pilot operation’s timeline. Study results indicated that the operation of an RO process treating a blend of NF concentrate and brackish groundwater could maintain a sustainable and productive operation that provided a practical zero-discharge process operation while the dilution of RO feedwater salinity would lower overall production costs.

Early disease detection is crucial for maximizingcrop yields and minimizing financial losses in agriculture. Inorder to categorise leaf diseases in pepper, tomato, and potato plants, this study suggests a revolutionary CNN design. The algorithm collects disease-specific features from input photos by using data augmentation techniques to artificially enlarge the training dataset. ReLU-activated convolutional layers gradually capture features at different levels, from low to high, while max pooling layers minimise spatial dimensionality. After thecharacteristics are extracted, a fully-connected layers with a softmax activation function classify them into illness groups. A well chosen dataset containing labelled healthy and sick leaves is used to train and validate the model. Generalizability to untesteddata is ensured via performance evaluation on an independent testing set. The field of deep learning for agricultural applications benefits from this research. This strategy has the ability to rev- olutionise agricultural practices by enabling automated disease identification. This might result in early interventions, better crop health, and eventually sustainable agricultural production.

Aimed to obtain purple garlic varieties, 360 bolting bulbs from the Protected Geographical Indication (PGI) “Las Pedroñeras” were selected for their size, and the presence of abundant external scales. After a further selection, 243 out of the 360 bulbs were discarded due to undesired characteristics, as light purple color, high number of small cloves, cloves affected by Fusarium spp. and mites, among other. It was stablished that each bulb would give rise to a family. Thus, 117 families were planted under a random design during season 2021-2022. Either physiological, morphological and phenological traits were assessed for each family, and the affectations by pest and pathogens were also controlled. After the assessment of this trial, 103 out 117 families remained in the program, and were used for the establishment of a second trial the next season. Unlike the first trial, after the evaluations only 23 families remained in the program. There was observed a high variability for most of traits, with a great influence of families. The phenotypic behavior of families was significative influenced by environment, highlighting the need of their assessment under different environmental conditions. The high variability registered for the target sample, opens the possibility to select new garlic varieties from this PGI.

In recent years, there has been a growing interest in the use of medicinal plants and phytochemicals as potential treatments for acne vulgaris. This condition, characterized by chronic inflammation, predominantly affects adolescents and young adults. Conventional treatment typically targets the key factors contributing to its development: the proliferation of Cutibacterium acnes and the associated inflammation. However, these treatments often involve the use of potent drugs. As a result, the exploration of herbal medicine as a complementary approach has emerged as a promising strategy. By harnessing the therapeutic properties of medicinal plants and phytochemicals, it may be possible to address acne vulgaris while minimizing the reliance on strong drugs. This approach not only offers potential benefits for individuals seeking alternative treatments but also underscores the importance of natural remedies in dermatological care. The primary aim of this study was to assess the antimicrobial, antioxidant, and anti-inflammatory properties of plants and their phytochemical constituents in the management of mild acne vulgaris. A comprehensive search of scientific databases was conducted from 2018 to September 2023. The findings of this review suggest that medicinal plants and their phytochemical components hold promise as treatments for mild acne vulgaris. However, it is crucial to note that further research employing high-quality evidence and standardized methodologies is essential to substantiate their efficacy and safety profiles.

The idea of CUAD (contact unmodified antisense DNA) biotechnology and the use of oligonucleotide insecticides (briefly, olinscides, or DNA insecticides) was proposed on lepidopterans and gradually disseminated on hemipteran pests. As the next-generation platform for creation of insecticides, it has a number of unique characteristics (short unmodified antisense DNA as contact insecticide, insect rRNAs as target, DNA containment as mechanism of action) that distinguish it from existing classes of chemical insecticides. Oligonucleotide insecticides possess low carbon footprint, high safety for non-target organisms, rapid biodegradability, avoidance of target-site resistance, ensuring prosperity for agricultural countries that will implement this innovation. As the next-generation class of insecticides olinscides create opportunities that have never existed before in crop protection. Using flexible CUAD platform, any farmer, botanical garden or pest control company is capable of creating its own unique arsenal of insecticides, well-tailored for a particular population of insect pest. Most technological innovations start out very expensive and don't work well, but eventually start working well and become very cheap. CUAD biotechnology has come a long way for 16 years and is very close to the point to be implemented on a large scale against certain groups of pests. In this article we provide basic knowledge of use of oligonucleotide pesticides and list pests (mainly from suborder Sternorrhyncha, Hemiptera) which were successfully controlled by us recently.

Pinus squamata is one of the most threatened conifer endemic to northeastern Yunnan Province, China, and it is prioritized as one of the Plant Species with Extremely Small Populations (PSESP) for urgent protection in China. However, we lack a comprehensive consideration of the protection effect and the endangered mechanism, especially based on the underground growth status of endangered plants. The integrated study of soil properties and rhizosphere bacteria can assist conservation to understand therequired conditions for the protection and survival of rare and endangered species. In our study, bacterial communities in wild, ex-situ, and reintroduced P. squamata rhizosphere were compared using Illumina sequencing of the V3-V4 region of the 16S rRNA genes. We determined the soil physicochemical properties, analyzed the relationships between the bacterial communities and soil physicochemical factors, and predicted the potential bacterial ecological functions. The reintroduced site Qiaojia (RQ) had the highest richness and diversity. Samples were scattered (R = 0.93, P = 0.001), indicating significant difference between the different conservation sites. Soil total potassium (TK) and available nitrogen (AN) were the main factors driving bacterial community (0.01 < P ≤ 0.05). The low abundance of Plant growth-promoting rhizobacteria (PGPR) may be a biotic factor contributing to the endangerment of P. squamata. This study provides a foundation to assess the effect of conservation based on bacterial diversity and plant growth-promoting rhizobacteria (PGPR) to guide future research into the conservation of P. squamata.

Due to combined climate and biodiversity crisis, the sustainable utilization of phytogenetic resources stands as one-way alternative while nutrient management strategies gain an increasing role in agriculture. Building on previous studies regarding the Endangered local endemic of Crete (Greece) Carlina diae (Asteraceae) with medicinal and ornamental value, this investigation focused on its pilot cultivation and fertilization (foliar or root application). Foliar application included chemical fertilizer (conventional) or integrated nutrient management (INM). Root application consisted of chemical fertilizer, biostimulant, or INM with biostimulant. Above-ground biomass content of nutrients, together with leaf chlorophyll fluorescence and colour parameters (SPAD meter, DA meter, Chroma Meter) were determined. The leaf content of chlorophyll, three key antioxidant compounds and minerals’ titers were also assessed. The fertilization scheme did not influence plant growth and visually perceived quality (leaf color and shape). Notably, foliar INM fertilization increased biomass partitioning to inflorescences (harvestable organ for either medicinal or ornamental purposes), and decreased tissue water content (facilitating processing). Considering all three antioxidants together, INM with biostimulant appeared the optimum scheme, being associated with the highest (carotenoids, phenolics) or the second highest (flavonoid) content. In C. diae, therefore, INM fertilization was optimal for upgrading yield (foliar) and herbal quality in terms of antioxidant profile (INM with biostimulant), which might be embraced as an eco-friendly approach for high quality yields.

Drought, a crucial abiotic stressor, markedly reduces the growth and yield of tomato crops (Solanum lycopersicum L.). Consequently, adopting drought-resistant cultivars and implementing breeding programs to enhance drought tolerance have emerged as enduring solutions to alleviate the adverse effects of drought in various tomato cultivation regions. In this study, 68 tomato accessions from the United States Department of Agriculture (USDA) were assessed in a controlled greenhouse experiment, encompassing both water deficit treatment and a control group subjected to standard watering conditions. The experiment was arranged in a randomized complete block design with three replications. The results of this study pinpointed four accessions PI 365956, PI 584456, PI 390510, and PI 370091, as drought-tolerant accessions. Additionally, high broad-sense heritability was revealed for leaf wilting, leaf rolling, and SPAD chlorophyll content (total leaf chlorophyll). Furthermore, positive correlations were found among parameters associated with leaf wilting, leaf rolling, and SPAD chlorophyll content. The findings of this study provide valuable insights relevant to tomato breeding initiatives, particularly those aimed at fortifying drought tolerance within the elite cultivars of this essential crop.

The viability, productivity and survival of higher plants under the adverse factors influence are largely determined by the functional activity of the antioxidant system. The aim of our work was to investigate changes in formation of high-molecular (superoxide dismutase and peroxidase) and low-molecular (phenolics, including flavanols and proanthocyanidins) antioxidants in callus culture of Camellia sinensis under influence of phenolic precursors (L-phenylalanine – 3 mM, trans-cinnamic acid – 1 mM, naringenin – 0.5 mM). According to the data obtained, precursors effect on tea callus cultures did not lead to significant increasing of superoxide dismutase and peroxidase activity in most cases. However, it led to the increased accumulation of the total phenolics content, as well as flavanols and proanthocyanidins contents. For C. sinensis callus cultures, the most promising regulator of phenolic compounds was L-phenylalanine, in the presence of which its content increased almost twice. Thus, the exogenous effect of various precursors is possible to use for the targeted regulation of the certain phenolics classes accumulation in plant cells.

Diesel contamination of farming soils is of great concern because hydrocarbons are toxic to all forms of life and can potentially enter the food web through crops or plants used for remediation. Data on plant ability to uptake, translocate and accumulate diesel-derived compounds are controversial not only due to the probable diverse attitude of plant species but also because of the lack of a reliable method to distinguish petrogenic from biogenic compounds in plant tissues. The purpose of this study was to set up a GC-MS-based protocol enabling the determination of diesel-derived hydrocarbons in plants grown in contaminated soil for assessing human and ecological risks, predicting phytoremediation effectiveness and biomass disposal. To this aim two plant species Vicia sativa L. and Secale cereale L., belonging to two diverse vascular plant families, were used as plant models. They were grown in soil spiked with increasing concentrations of diesel fuel and the produced biomass was used to set up the hydrocarbon extraction and GC-MSD analysis. The developed protocol was also applied to the analysis of Typha latifolia L. plants, belonging to a different botanical family and grown in a long-time and highly contaminated natural soil. Results showed the possibility of distinguishing diesel-derived compounds from biogenic hydrocarbons in most terrestrial vascular plants, just considering the total diesel compounds in the n-alkanes carbon range C10-C26, where the interference of biogenic compounds is negligible. Diesel hydrocarbons quantification in plant tissues was strongly correlated (0.92<r2<0.99) to the concentration of diesel in spiked soils, suggesting a general ability of the considered plant species to adsorb and translocate relative low amounts of diesel hydrocarbons and the reliability of the developed protocol.

Pea (Pisum sativum L.), like most legumes, forms mutualistic symbioses with nodule bacteria and arbuscular mycorrhizal (AM) fungi. The positive effect of inoculation is partially determined by the plant genotype, thus, pea varieties with high and low symbiotic responsivity have been described, but the molecular genetic basis of this trait remains unknown. Here, we compare the symbiotically responsive breeding line ‘Triumph’ of grain pea with its parental cultivars ‘Vendevil’ (a donor of high symbiotic responsivity) and ‘Classic’ (a donor of agriculturally valuable traits) using genome and transcriptome sequencing. We show that ‘Triumph’ inherited one-fourth of its genome from ‘Vendevil’, including the genes related to AM and nodule formation, and reveal that under combined inoculation with nodule bacteria and AM fungi, ‘Triumph’ and ‘Vendevil’, in contrast to ‘Classic’, demonstrate similar up-regulation of the genes related to solute transport, hormonal regulation and flavonoid biosynthesis in their roots. We also identify the gene PsGLP2, whose expression pattern distinguishing ‘Triumph’ and ‘Vendevil’ from ‘Classic’ correlates with difference within the promoter region sequence, making it a promising marker for the symbiotic responsivity trait. The results of the study may be helpful for future molecular breeding programs aimed at creation of symbiotically responsive cultivars of pea.

Fungal infection of grape berries (Vitis vinifera) by Botrytis cinerea frequently coincides with harvest, impacting both the yield and quality of grape and wine products. A rapid and non-destructive method for identifying B. cinerea infection in grapes at an early stage prior to harvest is critical to manage loss. In this study, zeolitic imidazolate framework-8 (ZIF-8) crystal was applied as an absorbent material for volatile extraction from B. cinerea-infected and healthy grapes in a vineyard followed by thermal desorption gas chromatography-mass spectrometry. The performance of ZIF-8 to absorb and trap targeted volatiles was evaluated with a standard solution of compounds and with a whole bunch of grapes enclosed in a glass container to maintain standard sampling conditions. Results from sampling methods were then correlated to B. cinerea infection in grapes as measured and determined by Genus specific antigen quantification. Trace levels of targeted compounds reported as markers of grape B. cinerea infection were successfully detected with in-field sampling. Peak area counts for volatiles 3-octanone, 1-octen-3-one, 3-octanol, and 1-octen-3-ol extracted using ZIF-8 were significantly higher than values achieved using Tenax®-TA from field testing and demonstrated good correlation with B. cinerea infection severities determined by B. cinerea antigen detection.

This article introduces ten similarity measures that utilize cosine and cotangent functions to compare (m,n)-rung orthopair fuzzy sets, this a super class of q-rung orthopair fuzzy sets. Further, we applied our established weighted similarity measures to medical diagnosis, pattern recognition,and building material problems and also presented the comparison between established measures with the existing cosine and cotangent measures of q-rung orthopair, pythagorean and intuitionistic fuzzy sets. Lastly, we considered a numerical example that demonstrates the effective and scientific application of these similarity measures in plant leaf disease classification. Furthermore, we present graphical interpretations to demonstrate the effectiveness of our established measures.

According to the eminent scholar, philosopher, and physician Avicenna, "the doctor has three tools: the word, the plant, the knife." The plant kingdom is recognized as humanity's earliest and most ancient healing source, employed for the management and prevention of illnesses. Tracing back through history, the most ancient documented proof of plants' utilization in medicine dates back to a Sumerian clay slab discovered in Nagpur roughly 5000 years ago. This artifact included a compilation of twelve medicinal recipes that involved over 250 diverse plant species. Sumerian healers extracted powders and infusions from plant roots and stems, while also crediting healing properties to pears and figs. Additionally, they utilized dried and ground young shoots of willow and plum trees, pine and fir needles as a component in compresses and poultices. Often, powders from animal and mineral sources were blended with those extracted from dried and crushed plants. Notably, in addition to water, wine and beer served as solvents. Thus, at least 80 centuries ago, people utilized the most uncomplicated medicinal plant-based preparations for treatment [1]. The "Pen T'Sao," an ancient Chinese text on roots and herbs, authored by Emperor Shen Nung approximately 2500 BC, contains descriptions of 900 medicaments (comprising dried components of medicinal plants). Several of these substances are still in use today, including Rhei rhisoma, camphor, Theae folium, Podophyllum, great yellow gentian, ginseng, datura, cinnamon bark, and ephedra [2]. Regarding Kazakh folk medicine, an area that has yet to be fully explicated and substantiated, it can be stated that the traditional medicinal knowledge of the Kazakh people transcends the mere treatment of ailments and rests on robust theoretical underpinnings. Oteiboydak Tleukabyluly (1388-1478), an astute healer and prominent figure in Kazakh folk medicine during the 15th century, comprehensively explicated the secrets of the healing art in his medical and ethnographic work "Medical Narrative," which he composed between 1466 and 1473 at the behest of az-Zhanibek Khan, who held him in high esteem as a great healer. This medical encyclopedia delineates the functions of various organs of the human body and provides a catalogue of the primary diseases associated with them. Furthermore, it includes a meticulous description of the methods used in traditional medicine at present, such as setting bones, listening to the pulse, and incantations. Through practical experimentation and experimentation conducted in the steppe laboratory, the healer formulated a total of 1,108 different medicinal compounds, of which 858 were derived from medicinal plants, 318 were extracted from animal organs, and roughly 60 were sourced from metals. The moniker "Teacher without a teacher" was bestowed on Oteiboydak Tleukabylov, who discovered methods for treating 1,050 different diseases [3]. At present, the employment of phytotherapy has gained widespread acceptance on a global scale. According to the World Health Organization's (WHO) global review of national policies concerning traditional, complementary, and alternative medicine, as well as the regulation of herbal medicines, there is an evident growth in the European and Asian market for herbal medicines [4]. Kazakhstan boasts a natural flora of over 6,000 plant species [5]. The exact number of medicinal plant species present in Kazakhstan remains uncertain, as the list continues to expand annually. More than 150 plant species have been employed in both official and folk medicine for various ailments. This review focuses on a selection of medicinal plants growing within the territory of the Republic of Kazakhstan that have traditionally been used to alleviate skin diseases. In conducting this study (2010-2023), emphasis was placed on the plants' phytochemical composition, with a particular focus on the principal components responsible for their therapeutic effects against inflammatory skin conditions such as dermatitis, atopic dermatitis, and eczema.

The work is devoted to the search for effective solutions to the applied problem of early diagnostics of plant stress in the conditions of smart farming and based on modern explicable artificial intelligence (XAI). The study mostly oriented on the theory and practice of XAI, focused on the use of hyperspectral imagery (HSI) and Thermal Infra-Red (TIR) sensor data at the input of a neural network. The first our goal is to build an XAI neural network, explainable due to its structure, the input of which is a datascientist oriented HSI 'explanator', and the output is a biologist oriented TIR 'explanator'. In the middle is SLP-regressor which solves the universal problem of training HSI pixels to temperatures of plants, needed for early plant stress diagnostic. The result can be considered as prototype of a special XAI explanator which is assigned to transform explanator specialized on area 1 onto explanator specialized on area 2. Using this HSI-TIR explanator we ensured the follows: extend HSI data by TIR attribute; providing TIR data for early diagnostic of plant stress; reducing dimensionality HSI needed for TIR training 25 times (from 204 to 8) preserving the same accuracy of temperature prediction (RMSE=0.2-0.3C). This reducing was achieved without using PCA methods. The constructed model is computationally efficient in training: the average training time is significantly less then 1 min (Intel Core i3-8130U, 2.2 GHz, 4 cores, 4 GB). One of the 8 channels, 820 nm, is the leader in correlation with TIR, what allows building local linear temperature prediction functions.

The soil and groundwater of Bhagobangola I block of Murshidabad district, West Bengal, India is severely arsenic contaminated. A bacterium was isolated from the garden soil of Mahishasthali village, which could tolerate 36.49 mM arsenic (III), 280.44 mM arsenic (V) and 63 mM chromium (III), which makes it arsenic (III & V) and chromium (III) hyper-tolerant bacterium. The growth pattern of this bacterium does not show much alteration in presence of 10 mM arsenic (III) and chromium (III), emphasizing its resistance to these heavy metals. Scanning electron microscopy depicted the size of this bacterium to be ~1.45 µm. 16S rDNA sequencing followed by subsequent phylogenetic analysis established the identity of this bacterium as Microbacterium paraoxydans. The bacterium is capable of bioremediation of arsenic and showed 30.8% & 22.6%, and 35.2% and 30.5% of bioremediation over a period of 24 and 48 hours in 1 mM and 4 mM arsenite, respectively. Microbacterium paraoxydans also exhibit plant growth promoting properties like nitrogen fixation, phosphate solubilization, indole-3-acetic acid production and production of siderophores. Therefore, the heavy metal resistance, bioremediation potential and plant growth promoting potential of the bacterium could be utilized not only for reduction of arsenic toxicity in soil and groundwater but also for plant growth promotion by using it as a biofertilizer.

The National Research Centre’s experimental research station (NRCERS) locates in Wadi El Natrun, Egypt 30°29'54.22"N 30°19'10.94"E. The NRCERS has various crop yields (vegetables, fruits, ornamental, and field crops) for different experimental treatments. It followed conventional agricultural procedures in vegetation, fertilisation, irrigation, and plant protection. Such policies have not been evaluated for their impacts on arthropod diversity and distribution. Thus, this study conclusion aims to sufficiently map the arthropod species (pest/predators) distribution, measure the biodiversity indices, to the NRCERS agricultural policies to be modified to support arthropod diversity.

The identification of floral visitation by pollinators provides an opportunity to improve our understanding of the fine-scale ecological interactions between plants and pollinators, contributing to biodiversity conservation and promoting ecosystem health. In this review we outline the various methods which can be used to identify floral visitation, providing a comparison between molecular and non-molecular methods. We review the literature covering the ways in which DNA metabarcoding has been used to answer ecological questions relating to plant use by pollinators and discuss the findings of this research. We present detailed methodological considerations for each step of the metabarcoding workflow, from sampling through to amplification and finally bioinformatic analysis. Detailed guidance is provided to researchers for utilization of these techniques, emphasizing the importance of standardization of methods and improving the reliability of results. Future opportunities and directions of using molecular methods to analyze plant-pollinator interactions are then discussed.

The PII protein is an evolutionary highly conserved regulatory protein from bacteria to higher plants. In bacteria it modulates the activity of several enzymes, transporters and regulatory factors by interacting with them and thereby regulating important metabolic hubs like carbon/nitrogen homeostasis. More than two decades ago the PII protein was characterized for the first time in plants, but its physiological role is still not sufficiently resolved. To gain more insights into the function of this protein, we investigated the interaction behaviour of AtPII with candidate proteins by BiFC and FRET/FLIM in planta and with GFP/RFP traps in vitro. In the course of these studies we found that AtPII interacts in chloroplasts with itself as well as with known interactors like NAGK in dot-like aggregates, which we named PII foci. In these novel protein aggregates AtPII interacts also with yet unknown partners, which are known to be involved in plastidic protein degradation. Further studies revealed that the C-terminal part of AtPII is crucial for the formation of PII foci. Altogether, the presented results indicate a novel mode of interaction for PII proteins with other proteins in plants, which may be a new starting point for the elucidation of physiological functions of PII proteins in plants.

Plants are exposed to highly fluctuating effects of light, temperature, weather conditions and many other environmental factors throughout their life. As sessile or-ganisms, unlike animals, they are unable to escape, hide or even change their position. Therefore, the growth and development of plants is largely determined by interaction with the external environment, the success of this interaction depends on the ability of the phenotype plasticity, which is largely determined by epigenetic regulation. In addi-tion to how environmental factors can change the patterns of genes expression, epige-netic regulation determines how genetic expression changes during the differentiation of one cell type into another, and how patterns of gene expression are passed from one cell to its descendants. Thus, one genome can generate many 'epigenomes'. Epigenetic modifications acquire special significance during the formation of gametes and plant reproduction, when epigenetic marks are eliminated during meiosis and early embry-ogenesis and later reappear. However, during asexual plant reproduction, when meio-sis is absent or suspended, epigenetic modifications that have arisen in the parental sporophyte can be transmitted to the next clonal generation practically unchanged. In plants that reproduce sexually and asexually, epigenetic variability has different adap-tive significance. In asexuals, epigenetic regulation is of particular importance for im-parting plasticity to the phenotype, when the genotype remains unchanged for many generations of individuals. Of particular interest is the question of the possibility of transferring acquired epigenetic memory to future generations and its potential role for natural selection and evolution. All these issues will be discussed to some extent in this review. In the last two decades, a lot of data on the epigenetic regulation of plants has appeared, as well as works summarizing the accumulated knowledge (Verhoeven and Preite 2013; Pikaard and Scheid 2014; Gehring 2019; Ono and Kinoshita 2021), nevertheless, many questions remain unclear, and a number of results are contradic-tory. New in this area data is constantly emerging. We tried to take into account and discuss the main findings and conclusions in this field.

Membrane transporters (MTs) are mainly localized at the plasma membrane (PM), tonoplast and vacuolar membrane (VM) of cells in all plant organs. Their work is to maintain the cellular homeostasis by controlling ionic movements across PM channels from roots to upper plant parts, xylem loading and remobilization of sugar molecules from photosynthesis tissues in the leaf (source) to roots, stem and seeds (sink) via phloem loading. The plant’s whole source-to-sink relationship is regulated by multiple transporting proteins in a highly sophisticated manner and driven based on different stages of plant growth and development (PG&D), and environmental changes. The MTs play a pivotal role in PG&D in terms of increased plant height, branches/tiller numbers, enhanced numbers, length and filled panicles per plant, seed yield and grain quality. Dynamic climatic changes disturbed the ionic balance (salt, drought and heavy metals) and sugar supply (cold and heat stress). Due to poor selectivity, some of the MTs also uptake toxic elements in the roots that negatively impact on PG&D, later on also exported to upper parts and then deteriorate the grain quality. As an adaptive strategy, in response to salt and HMs plants activated PM and VM localized MTs that export toxic elements into vacuole, and also translocate in the root’s tips and shoot. However, in case of drought, cold and heat stresses, MTs increased the water and sugar supply to all organs. In this review, we mainly reviewed recent literature from Arabidopsis, halophytes, and major field crops such as rice, wheat, maize and oilseed rape to argue on the global role of MTs in PG&D and abiotic stress tolerance. We also discussed the gene expression level changes and genomic variations within a species as well as within a family in response to developmental and environmental cues.

Phytoremediation, a method of phytomanagement using the plant holobiont to clean up polluted soils, is particularly effective for degrading organic pollutants, such as alkanes and polycyclic aromatic hydrocarbons (PAHS). However, the respective contributions of host plants and their associated microbiota within the holobiont to the efficiency of phytoremediation is poorly understood. Identification of plant-associated bacteria capable of efficiently utilizing these compounds as carbon source while stimulating plant-growth, is a keystone for phytomanagement engineering in order to improve the efficiency of pollutant removal. In this study, we sampled the rhizosphere and the surrounding bulk soil of Salix purpurea and Eleocharis obusta from the site of a former petrochemical plant in Varennes, QC, Canada. Our objectives were to: (i) isolate and identify indigenous bacteria inhabiting these biotopes; (ii) assess the ability of isolated bacteria to utilize alkanes (dodecane and hexadecane) and PAHs (naphthalene, phenanthrene and pyrene) as the sole carbon source, and (iii) determine the plant growth-promoting (PGP) potential of the isolates using five key traits. A total of 438 morphologically different bacterial isolates were obtained, purified, preserved and identified through PCR and 16S rRNA gene sequencing. Identified isolates represent 62 genera, including taxa such as Acinetobacter, Arthrobacter, Bacillus, Enterobacter, Nocardia, Pseudomonas, Rhodococcus, Streptomyces and Variovorax. Approximately, 32% of bacterial isolates, including Arthrobacter, Pseudomonas, Streptomyces, Enterobacter, Nocardia, Acinetobacter and Microbacterium, were able to utilize all five different hydrocarbons compounds. Additionally, 5% of tested isolates belonging to genera Pseudomonas, Acinetobacter, Serratia, Klebsiella, Microbacterium, Bacillus and Stenotrophomonas possessed all five of the tested PGP functional traits. This culture collection of diverse, petroleum-hydrocarbon degrading bacteria, with multiple PGP traits, represents a valuable resource for future use in environmental bio- and phyto-technology applications, including phytoremediation of petroleum hydrocarbons contaminated soils and phytomanagement of anthropized areas.

Mints emit diverse scents that exert specific biological functions and are relevance for applications. The current work strives to develop electronic noses that can electronically discriminate the scents emitted by different species of Mint as alternative to conventional profiling by gas chromatography. Here, 12 different sensing materials including 4 different metal oxide nanoparticle dispersions (AZO, ZnO, SnO2, ITO), one Metal-Organic Frame as Cu(BPDC), and 7 different polymer films including PVA, PEDOT: PSS, PFO, SB, SW, SG, PB were used for functionalizing of QCM sensors. The purpose was to discriminate six economically relevant Mint species (Mentha x piperita, Mentha spicata, Mentha spicata ssp. crispa, Mentha longifolia, Agastache rugosa, and Nepeta cataria). The adsorption and desorption datasets obtained from each modified QCM sensor were processed by three different classification models including Principal Component Analy-sis (PCA), Linear Discriminant Analysis (LDA), and k-Nearest Neighbor Analysis (k-NN). This allowed discriminating the different Mints with classification accuracies of 97.2% (PCA), 100% (LDA), and 99.9% (k-NN), respectively. Prediction accuracies with a repeating test measurement reached up to 90.6% for LDA, and 85.6% for k-NN. These data demonstrate that this electronic nose can discriminate different Mint scents in a reliable and efficient manner.

Soil CO2 efflux (FCO2) plays a dominant role in the terrestrial carbon (C) cycle but interpreting constraints on local observations is impeded by challenges in disentangling belowground CO2 sources. Trees contribute most C to forest soils, so linking aboveground properties to FCO2 could open new avenues to study plant-soil feedbacks and facilitate scaling; furthermore, FCO2 responds dynamically to meteorological conditions, complicating predictions of total FCO2 and forest C balance. We tested for proximity effects of individual Acer saccharum Marsh. trees on FCO2, comparing FCO2 within 1 m of mature stems to background fluxes before and after an intense rainfall event. Wetting significantly increased background FCO2 (6.4±0.3 vs. 8.6±0.6 s.e. μmol CO2 m-2s-1), with a much larger enhancement near tree stems (6.3±0.3 vs. 10.8±0.4 μmol CO2 m-2s-1). FCO2 varied significantly among individual trees and post-rain values increased with tree diameter (with a slope of 0.058 μmol CO2 m-2s-1 cm-1). Post-wetting amplification of FCO2 (the ‘Birch effect’) in root zones often results from the improved mobility of labile carbohydrates and further metabolization of recalcitrant organic matter, which may both occur at higher densities near larger trees. Our results indicate that plant-soil feedbacks change through tree ontogeny and provide evidence for a novel link between whole-system carbon fluxes and forest structure.

Conventional plant breeding methods exploit already existing genomic variation in plants to develop a variety in 8 to 10 years, which can decrease the genetic variability of the plant’s genome. The ever-increasing food demand for cereals crops cannot be met by traditional breeding methods. In order to increase food production in less time, there is a dire need to improve breeding methods. Several conventional and molecular breeding methods are being used to improve the crops traits. Molecular researchers have developed new genome editing tools like CRISPR/Cas9, CRISPR/Cpf1, prime editing, base editing, dcas9 epigenetic modification, and several other transgene-free genomes editing approaches. These genome editing tools can improve the desired traits precisely and efficiently. Moreover, a newly developed breeding method “Speed Breeding” has revolutionized the agriculture by shortening the crop cycle. It can produce 5-6 generations of cereals in a year. In this review, we have summarized all these conventional and molecular breeding approaches to improve cereal crops.

Soybean maturity is a trait of critical importance for the development of new soybean cultivars, nevertheless, its characterization based on visual ratings has many challenges. Unmanned aerial vehicles (UAVs) imagery-based high-throughput phenotyping methodologies have been proposed as an alternative to the traditional visual ratings of pod senescence. However, the lack of scalable and accurate methods to extract the desired information from the images remains a significant bottleneck in breeding programs. The objective of this study was to develop an image-based high-throughput phenotyping system for evaluating soybean maturity in breeding programs. Images were acquired twice a week, starting when the earlier lines began maturation until the latest ones were mature. Two complementary convolutional neural networks (CNN) were developed to predict the maturity date. The first using a single date and the second using the five best image dates identified by the first model. The proposed CNN architecture was validated using more than 15,000 ground truth observations from five trials, including data from three growing seasons and two countries. The trained model showed good generalization capability with a root mean squared error lower than two days in four out of five trials. Four methods of estimating prediction uncertainty showed potential at identifying different sources of errors in the maturity date predictions. The architecture used solves limitations of previous research and can be used at scale in commercial breeding programs.

Post-translational modifications (PTMs) of histone residues shape the landscape of gene expression by modulating the dynamic process of RNAPII transcription. The contribution of particular histone modifications to the definition of distinct RNAPII transcription stages remains poorly characterized in plants. Chromatin Immuno-precipitation combined with next-generation sequencing (ChIP-seq) resolves the genomic distribution of histone modifications. Here, we review histone PTM ChIP-seq data in Arabidopsis thaliana and find support for a Genomic Positioning System (GPS) that guides RNAPII transcription. We review the roles of histone PTM “readers”, “writers” and “erasers”, with a focus on the regulation of gene expression and biological functions in plants. The distinct functions of RNAPII transcription during the plant transcription cycle may in part rely on the characteristic histone PTMs profiles that distinguish transcription stages.

In plant cells the conventional route to the vacuole involves the endoplasmic reticulum, the Golgi and the prevacuolar compartment. However, over the years, unconventional sorting to the vacuole, bypassing the Golgi, has been described, which is the case of the Plant Specific Insert (PSI) of the aspartic proteinase cardosin A. Interestingly, this Golgi-bypass ability is not a characteristic shared by all PSIs, since two related PSIs showed to have different sensitivity to ER-to-Golgi blockage. Given the high sequence similarity between the PSIs domains, we sought to depict the differences in terms of post-translational modifications. In fact, one feature that draws our attention is that one is N-glycosylated and the other one is not. Using site-directed mutagenesis to obtain mutated versions of the two PSIs, with and without the glycosylation motif, we observed that altering the glycosylation pattern interferes with the trafficking of the protein as the non-glycosylated PSI-B, unlike its native glycosylated form, is able to bypass ER-to-Golgi blockage and accumulate in the vacuole. This is also true when the PSI domain is analyzed in the context of the full-length cardosin. Regardless of opening exciting research gaps, the results obtained so far need a more comprehensive study of the mechanisms behind this unconventional direct sorting to the vacuole.

We analyzed the plant-litter-soil continuum to investigate the carbon and nitrogen distribution and ecological stoichiometry of an evergreen broad-leaved forest at Dagangshan Mountain, Jiangxi. The results showed that the average C and N contents and C:N ratios in the leaves and fine roots among 6 different tree species were 401.87g/kg, 21.41g/kg, 19.27 and 348.64g/kg, 15.73g/kg, 23.97, respectively; the average C and N contents and C:N ratios were 323.06 g/kg, 12.76 g/kg, 25.58 respectively in leaf litter, and 16.40 g/kg, 1.09 g/kg, 16.27 respectively for soil. In contrast with the C content, the total N content of the fine roots and litter had a high coefficient of variation and a high spatial heterogeneity. We ranked the six different representative tree species according to total C and N content in leaves and fine roots. The results for each species were generally consistent with each other, showing a positive correlation relationship between total C and N content in the leaves and roots. Among them, S. discolor (Champ. ex Benth.) Muell. plants displayed high carbon and nitrogen storage capacities, and on the other hand, C. fargesii Franch., C. myrsinifolia (Blume) Oersted, A. fortunei (Hemsl.) Makino, and V. fordii (Hemsl.) Airy Shaw showed a high nitrogen transfer rate. Total soil N and C decreased with depth. Soil organic carbon (SOC), soil resistant organic carbon (ROC), total N, alkali nitrogen, NH4+-N and NO3--N contents were all also negative correlated with soil depth, but the contents of the NH4+-N and NO3--N did not change significantly; The spatial distribution of soil NO3--N was significantly heterogeneous. At 0-10 cm soil depth, SOC was positively correlated with alkaline nitrogen, and at 10-20 cm soil depth, SOC was significantly positively correlated with total N. In general, when soil carbon was abundant, nitrogen supply capacity was also high.

A B S T R A C T Genital herpes disease is caused mainly by herpes simplex virus type 2 (HSV-2), which is sexually transmitted with a high prevalence in both developed and developing countries. No vaccine is currently available against genital herpes. In this study, we introduced and expressed two genes encoding HSV-2 glycoprotein D (gD) and VP16 protein and a GFP marker gene (control) in tobacco seedlings. Positive plant infection was assessed through characteristic tobacco mosaic virus disease symptoms on leaves and by monitoring the fluorescence emitted by the expressed GFP protein. Expression of the HSV-gD2 and VP16 antigens was verified by RT-PCR, ELISA and Western blot. As a proof of concept, the immunogenicity and the protection ability of the plant produced gD antigen was tested in a mouse model of genital herpes and compared to gD antigen produced in a mammalian expression system. This showed that the plant-gD preparation, when used in combination with a CpG oligodeoxynucleotide as adjuvant, was highly immunogenic and capable of inducing complete immunity to lethal vaginal HSV-2 challenge in mice. Thus, the data presented here may have implications for the development of a production system for highly immunogenic plant-based HSV-2 vaccine antigens.

Among the plant nutrients potassium (K) is one of the vital elements required for plant growth and physiology. Potassium is not only a constituent of plant structure but also plays regulatory function in several biochemical processes related to protein synthesis, carbohydrate metabolism, enzyme activation. There are several physiological processes like stomatal regulation and photosynthesis are dependent on K. In the recent decades K was found to provide abiotic stress tolerance. Under salt stress, K helps in maintaining ion homeostasis and regulation of osmotic balance. Under drought stress condition K regulates the stomatal opening and makes the plants adaptive to water deficit. Many reports provided the notion that K enhances the antioxidant defense in plants and therefore, protects the plants from oxidative stress under various environmental adversities. Also, it provides some cellular signaling alone or in association with other signaling molecules and phytohormones. Although a considerable progress in understanding K-induced abiotic stress tolerance in plants has been achieved the exact molecular mechanisms of such protections are still under research. In this review, we summarized the recent literature on the biological functions of K, its uptake, and translocation and its role in plant abiotic stress tolerance.

The chemical industry is an integral part of the world economy and a substantial income source for developing countries. However, existing regulations or the enforcement of these regulations, on controlling atmospheric pollutants sometimes may be insufficient, leading to the deterioration of surrounding ecosystems and to a quality decrease of the atmospheric environment. Previous works in this domain fail to generate executable solutions for inspection agencies due to practical challenges. In addressing these challenges, we introduce a so-called Chemical Plant Environment Protection Game (CPEP) to generate reasonable schedules of high-accuracy air quality monitoring stations for inspection agencies. First, Stackelberg Security Games (SSGs) are incorporated together with source estimation methods into this research. Second, high-accuracy air quality monitoring stations as well as gas sensors are modeled into the CPEP. Third, simplified data analysis on the regularly discharging of chemical plants is utilized to construct the CPEP. Finally, an illustrative case study is used to investigate the effectiveness of the CPEP Game, and a realistic case study is conducted to illustrate how the models and algorithms being proposed in this paper, work. Results show that playing a CPEP Game can reduce operational costs of high-accuracy air quality monitoring stations; moreover, playing the game leads to more compliance from the chemical plants towards the inspection agencies.

There is a balanced plant-water relationship in the primary vegetation of desert area. With the increase of population and social development in desert areas, people’s need for forest vegetation ecosystem’s goods and service have been changed. To meet the growing demand for plant community goods and services, more original vegetation has been changed into non-native vegetation such as in China loess plateau. However, with the plant growth, sometime soil drying happens and then becomes gradually serious with times in most of desert regions. Serious drying of soil eventually result in soil degradation, vegetation decline and agriculture failure，which influence the produce and supply of forest vegetation goods and service in market in dry year or waste of soil water resources in wet year, which wastes precious nature resources. In order to solve these problems, the soil water resources have to be used in sustainable way and plant-water relationship have to be regulated on Carrying Capacity of Soil Water for Vegetation in the key period of plant water relationship regulation, to carry out sustainable use of nature resources, high-quality and sustainable development of forest and grass or high-quality produce of fruit and crop in desert re-gions.

Traditional thermal insulation panels consume large amounts of energy during production and emits pollutants into the environment. To mitigate this impact, the development of bio-based materials is an attractive alternative. In this context, the characteristics of the Eucalyptus fiber bark (EGFB) make it a candidate for insulation applications. However, more knowledge about the manufacturing process and in-service performance is needed. The present study characterized the properties that determinate the in-service behaviour of the EGFB insulation panel. The assessment involved two different manufacturing process. The results indicated that the hot plates and the saturated steam injection manufacturing system can produce panels with similar theoretical and bulk density. The thermal conductivity fluctuated between 0.064 and 0.077 W/m.K, which indicated good insulation. Furthermore, the values obtained for thermal diffusivity and water vapor transmission properties are comparable with other commercially available panels. To guarantee a good in-service performance, the panels need to be treated with flame retardant and antifungal additive. The good performance of the panel is relevant because bio-based Eucalyptus bark panels generate less CO2 eq and require less energy consumption compared to traditional alternatives, contributing to the sustainability of the forestry and the construction industry.

The task of automatically and intelligently diagnosing faults in marine equipment is of great significance due to the numerous duties that shipboard professionals must handle. Incorporating automated and intelligent systems on ships allows for more efficient equipment monitoring and better decision-making. This approach has attracted considerable interest in both academia and industry because of its potential for economic savings and improved safety. Several fault diagnosis methods are documented in the literature, often involving mathematical and control theory models. However, due to the inherent complexity of some processes, not all characteristics are precisely known, making mathematical modeling highly challenging. As a result, fault diagnosis often depends on data or heuristic information. Fuzzy logic theory is particularly well-suited for processing this type of information. Therefore, this paper employs fuzzy models to diagnose faults in a marine pneumatic servo-actuated valve. The proposed fault diagnosis framework analyzes the discrepancy signals between the outputs of the fuzzy models and the actual process outputs. These discrepancies, known as residuals, help in detecting and isolating equipment faults. The fault isolation process uses an intelligent decision-making approach to determine the specific fault in the system. This method is applied to diagnose abrupt faults in a marine pneumatic servo-actuated valve.

Cannabidiol (CBD), a non-psychotropic main component of the Cannabis plant, is approved as a drug in the European Union (EU) under the name “Epidyolex”. However, the approval process as a food ingredient under the Novel Food Regulation was paused by the European Food Safety Authority (EFSA) due to a lack of safety data. Nevertheless, there is a growing, unregulated market in which CBD is advertised with various health claims and different dosage instructions. Of particular concern is its toxic effect on the liver and possible reproductive toxicity in humans. Studies suitable for calculating a benchmark dose were identified from the available data. Animal studies yielded a Benchmark Dose Lower Confidence Limit (BMDL) of 43 mg/kg bw/day, which translates into a safe human dose of approximately 15 mg/day. Only a Lowest Observed Adverse Effect Level (LOAEL) of 4.3 mg/kg bw/day could be identified from the human data. This updated risk assessment confirmed the Health-based Guidance Value (HBGV) of 10 mg/day based on human LOAEL. Despite existing data gaps, preliminary regulation appears advisable as the current form of the gray CBD market is unacceptable from the standpoint of consumer safety and protection.

Ever since the discovery of dendritic cells by Ralph Steinman and Zanvil Cohn in 1973, it is increasingly evident that dendritic cells are integral for adaptive immune responses, and there is an undeniable focus on them for vaccines development. Fungal infections, often thought in-nocuous, are becoming significant threats due to increased immunocompromised or im-mune-suppressed population and climate change. Further, the recent COVID-19 pandemic unraveled the wrath of fungal infections and devastating outcomes. Invasive fungal infections cause significant case fatality rates ranging from 20% to 90%. Regrettably, no licensed fungal vaccines exist, and there is an urgent need for preventive and therapeutic purposes. In this re-view, we discuss the ontogeny, subsets, tissue distribution, and functions of lung dendritic cells. In the latter part, we summarize and discuss the studies on the DC-based vaccines against pulmonary fungal infections. Finally, we highlight some emerging potential avenues that can be incorporated for DC-based vaccines against fungal infections.

This study presents extended Immunity Agent-Based Model (IABM) simulations to evaluate vaccination strategies in controlling the spread of infectious diseases. The application of IABM in the analysis of vaccination configurations is innovative, as a vaccinated individual can be infected depending on how their immune system acts against the invading pathogen, without a pre-established infection rate. Analysis at the microscopic level demonstrates the impact of vaccination on individual immune responses and infection outcomes, providing a more realistic representation of how the humoral response caused by vaccination affects the individual’s immune defense. At the macroscopic level, the effects of different population-wide vaccination strategies are explored, including random vaccination, targeted vaccination of specific demographic groups, and spatially focused vaccination. The results indicate that increased vaccination rates are correlated with decreased infection and mortality rates, highlighting the importance of achieving herd immunity. Furthermore, strategies focused on vulnerable populations or densely populated regions prove to be more effective in reducing disease transmission compared to randomly distributed vaccination. The results presented in this work show that vaccination strategies focused on highly crowded regions are more efficient in controlling epidemics and outbreaks. Results suggest that applying vaccination only in the densest region resulted in the suppression of infection in that region, with less intense viral spread in areas with lower population densities. Strategies focused on specific regions, in addition to being more efficient in reducing the number of infected and dead people, reduce costs related to transportation, storage, and distribution of doses compared to the random vaccination strategy. Considering that, despite scientific efforts to consolidate the use of mass vaccination, the accessibility, affordability, and acceptability of vaccines are problems that persist, investing in the study of strategies that mitigate such issues is crucial in the development and application of government policies that make immunization systems more efficient and robust.

Bacillus Calmette-Guérin (BCG) immunotherapy has been a cornerstone treatment for non-muscle invasive bladder cancer for decades and still faces challenges, such as severe immune adverse reactions, which reduce its use as a first-line treatment. This review examines BCG therapy’s history, mechanisms, and current status, highlighting how nanotechnology and bioengineering are revitalizing its application. We discuss novel nanocarrier systems aimed at enhancing BCG's efficacy while mitigating specific side effects. These approaches promise improved tumor targeting, better drug loading, and enhanced stimulation of anti-tumor immune responses. Key strategies involve using functional BCG cell wall components and co-delivering BCG with chemotherapeutics to achieve synergistic effects. While most studies remain experimental, this research direction offers hope for overcoming BCG's limitations and advancing bladder cancer immunotherapy. Further elucidation of BCG's mechanisms and rigorous safety evaluations of new delivery systems will be crucial for translating these innovations into clinical practice.

The marketing industry is rapidly evolving, necessitating educational programs to adapt and equip graduates with relevant skills and knowledge. This systematic literature review with bibliometric analysis (SLRBA) explores the integration of Problem-Based Learning (PBL) in marketing education. PBL is an instructional strategy that empowers students to solve real-life problems by integrating theory and practice, thus fostering critical thinking and decision-making skills. Our review synthesizes data from 71 sources, highlighting the definition of PBL, strategies to promote its implementation in marketing education, and the benefits and challenges associated with this approach. The findings indicate that PBL enhances student engagement, provides hands-on experience, and prepares students for real-world marketing challenges. Strategies such as using social media, serious games, e-learning, and feedback mechanisms are discussed for their effectiveness in promoting active learning and student participation. Despite its advantages, PBL faces challenges such as resource intensiveness, student resistance, and information integrity issues. This review underscores the importance of PBL in bridging the gap between theoretical knowledge and practical application, ultimately preparing marketing students to meet the demands of the industry. The paper concludes with recommendations for future research and best practices for implementing PBL in marketing education.

Coastal zones experience increasing climatic and human pressures, which lead to growing risks and tipping points (TPs) under future scenarios and natural resource scarcity. To avoid crossing TPs with irreversible coastal losses, this paper proposes the development of adaptation pathways based on advanced coastal oceanography and engineering knowledge that enables an objective assessment of evolving coastal risks. These pathways feature sequential interventions, combining conventional engineering works with nature-based solutions (NbS), steered by simulations and observations as a function of available coastal resources (space and sediment) and risks for infrastructure and socioeconomic assets. Such an adaptation has been developed for urban and peri-urban Mediterranean beaches, considering conventional coastal engineering together with NbS. Both types of interventions are assessed in terms of key physical variables, which serve to evaluate performance and estimate TPs. This analysis supports the new coastal protection and management plan promoted by the local government and the coastal adaptation plan of the central government. The approach and results illustrate the potential of adaptation pathways for beach sustainability, enhancing the compatibility between short/long-term coastal protection objectives under present/future climate and management scenarios. The adaptation pathways development underpins an increasing stakeholder cooperation to achieve shared decisions for coastal sustainability.

This paper aims to examine the potential for ecotourism development in the Pulicat Lake, a proposed Ramsar site situated in the Indian states of Andhra Pradesh and Tamil Nadu. Pulicat Lake has enormous potential for tourism and recreation; however, it is inevitable to ensure sustainable development in the region. The data for the study was collected using various methods, including case study techniques, qualitative interviews, observations, and information obtained from secondary sources. The study aimed to identify the sustainability dimensions of the location, including economic impact and income generation potentials through employment opportunities like field guides and travel companions. It is also examined the social impact on the local community and the development efforts made to reduce environmental pressures while conserving the flora and fauna. Additionally, the study discusses the possibilities and strategies for ornithological ecotourism at Pulicat Lake.

Catalytic studies for hydrogen production via steam reforming of ethanol (SRE) are essential for process optimization. Likewise, selecting the ideal support for the active phase can be critical to achieve high conversion rates during the catalytic steam reforming. In this work, copper-based catalysts were synthesized using two different supports, NaY zeolite and Nb2O5/Al2O3 mixed oxides. The materials were prepared using wet impregnation and characterized for their physicochemical properties using different analytical techniques. Differences in catalyst morphologies were readily attributed to the characteristics of the support. The Cu/NaY catalyst showed better textural properties than Cu/Nb2O5/Al2O3, resulting in a homogeneous metal dispersion over the support surface. Both catalytic systems were active in SRE, but Cu/NaY resulted in higher ethanol conversions compared to Cu/Nb2O5/Al2O3. Hence, the performance of copper-based catalysts was influenced significantly by the textural properties of the support.

Seroconversion surveys of anti-SARS-CoV-2 antibodies provide accurate estimates of the SARS-CoV-2 infection. This nationwide population-based cross-sectional serosurvey aimed to evaluate the prevalence of SARS-CoV-2 antibodies among residents in Gabon and compare the estimated cumulative number of COVID-19 cases with the officially registered number of laboratory-confirmed cases up to December 2021. Households in each province were randomly selected. Twenty-eight localities including 16 urban and 12 rural, were randomly selected to participate in the study. Whole blood samples were collected in dry tubes from all study participants around the country within 15 days. Serum samples were used to measure the total Immunoglobulin antibodies. Overall, data of 1672 households were analyzed. Out of the 3659 participants, 3175 were found positive for SARS-CoV-2 antibodies, resulting in a crude seroprevalence of 86.77%. Stratification of study participants by age group has shown highest seroprevalences in 20–29 and 40-49 age groups with 91.78% (95% CI:89.5–93.6) and 91.42% (95% CI:88.7–93.5), respectively. Nyanga province had the lowest prevalence (72,8%), and Estuaire and Ogoué-Lolo provinces had the highest prevalence (90 and 92%, respectively). Our results suggest a high transmission rate in the Gabonese population, 21 months after the first SARS-CoV-2 case in the country. This high seroprevalence estimate could indicate that the applied infection control measures may not have been adequately implemented or appropriately adhered to by the population.

With its unique properties and potential applications, nanoparticle-based delivery platforms for vac-cines have gained significant attention in recent years. Nanoparticles have the advantages of enhancing immunogenicity, targeting delivery and improving stability, providing a new solution for drug and vaccine delivery. And in some clinical studies, a variety of nanoparticle delivery platforms have been gradually applied to a wide range of vaccine applications. Current research priorities are exploring various types of nanoparticles as vaccine delivery system to enhance vaccine stability and immunogen-icity. Lipid nanoparticles have shown promising potential in preclinical and clinical studies to efficiently deliver antigens to immune cells. Moreover, lipid nanoparticles (LNPs) and other nanoparticles as nu-cleic acids especially mRNA delivery system, have shown vast potential for vaccine development. In this review, we present various vaccine platforms with an emphasis on nanoparticles for mRNA nano-vaccine delivery vehicles. We introduce several novel nanoparticles delivery platforms for mRNA vac-cine such as lipid, polymer, protein-based nanoparticle and so on. In addition, we overview the an-ti-tumor immunity of nanovaccine against different tumors in cancer immunotherapy. Finally, we give an outlook future perspectives and remaining challenges for this promising technolo-gy-nanoparticle-based delivery platforms for vaccines.

Proper Post-Activation Performance Enhancement helps to improve athletic performance. This study aimed to investigate the effects of two different velocity loss (VL), 10%VL and 20%VL, on post-activation performance enhancement (PAPE) in 20m sprint performance among sprint athletes. Twenty-four male sprint athletes (100m sprint time: 10.96±0.15 s) were recruited. A randomized crossover experimental design was used for traditional group (TG), 10%VL, and 20%VL interventions. Sprint tests were conducted at the 4th, 8th, 12th, and 16th minutes after the intervention. Two-way repeated measures ANOVA revealed an interaction effect between group and time on 20m sprint performance (F=2.817, p=0.037, partial η²=0.585). Simple effect analyses showed significant differences compared to baseline at the 4th minute for the 20%VL group (P&lt;0.05). Cohen's d values indicated improvement in 10m sprint times at the 8th minute of the rest interval for all three intervention groups (TG: ES=-0.270, 10%VL: ES=-0.038, 20%VL: ES=-0.279). Improvement in 20m sprint times was observed at the 4th minute for the 20%VL group (ES=-0.296) and at the 16th minute for the 10%VL group (ES=-0.276). Compared to traditional PAPE schemes based on 1RM, PAPE schemes based on velocity loss (20%VL) can better induce PAPE effects in sprint athletes.

Sewage surveillance can be used as an effective complementary tool for detecting pathogens in local communities, providing insights into emerging threats and aiding in the monitoring of outbreaks. In this study using qPCR and whole genomic sewage surveillance, we detected Mpox virus along with other viruses, in municipal and hospital wastewaters in Belo Horizonte, Brazil over a 9 months period (from July 2022 till March 2023). MPXV DNA detection rates varied in our study, with 19.6% (11 out of 56 samples) detected through the hybrid capture method of whole genome sequencing and 20% (12 out of 60 samples) through qPCR. In hospital wastewaters, the detection rate was higher at 40% (12 out of 30 samples), compared to 13.3%(4 out of 30 samples) in municipal wastewaters. This variation could be attributed to the relatively low number of MPXV cases reported in the city, which ranged from 106 to 341 cases during the study period, and to dilution effects, given that each of the two wastewater treatment plants (WWTP) investigated serves approximately 1.1 million inhabitants. Additionally, nine other virus families were identified in both hospitals and municipal wastewaters including Adenoviridade, Astroviridae, Caliciviridae, Picornaviridade, Polyomaviridae, Coronaviridae (which includes SARS-CoV-2), Herspesviridae, Papillomaviridae and Flaviviridae (notably including Dengue). These findings underscore the potential of genomic sewage surveillance as a robust public health tool for monitoring a wide range of viruses circulating in both community and hospitals environments including MPXV.

Despite its growing importance as a dry beneficiation method, there is a lack of studies exploring the fundamentals aspects of dry jigging. In this sense, this study focuses on explore some essential aspects of density-based separation in dry jigs, like pulse profile, energy consumption and, especially, stratification over time, also exploring an innovative operational strategy here called “transient pulsation”. The tests were carried out using density tracers distributed across 11 density ranges (0.4-2.4 g/cm³) and employing a base bed (gravel) to analyze their segregation in a pilot-scale dry jig. Pressure drop and active power data were acquired to measure the pulse characteristics and energy consumption. The findings suggest that establishing the dry jigging cycle is more complex than in hydraulic jigs due to the compressibility of air. Stationary pulsation tests revealed an unstable behavior of stratification over time, contrasting with traditional hydraulic jigs, while transient pulsation tests unveiled varied trends in separation quality. Energy consumption analysis underscored the significant role of the blower drive. These insights have the potential to inform operational enhancements in dry jigging.

We construct a Bayesian estimator for the dilution of a wastewater sample. When wastewater is diluted by rainwater an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows (CSOs) and wastewater storage tanks, which divert wastewater away from treatment plants when the flow is excessive. However, we also have proxies for the flow from various chemical markers (e.g.\ phosphate, ammonium, electrical conductivity), whose level per unit of population is fixed. The new flow estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

Glioblastoma (GBM) is the most common malignant brain tumor in adults. Despite advancements in treatment, the prognosis for patients with GBM remains poor due to its aggressive nature and resistance to therapy. CRISPR-based genetic screening has emerged as a powerful tool for identifying genes crucial for tumor progression and treatment resistance, offering promising targets for tumor therapy. In this review, we provide an overview of the recent advancements in CRISPR-based genetic screening approaches and their applications in GBM. We highlight how these approaches have been used to uncover genetic determinants of GBM progression and susceptibility to various therapies. Furthermore, we discuss ongoing challenges and future directions of CRISPR-based screening methods in advancing GBM research.

Using UAV-based multispectral images for quickly and accurately monitoring chlorophyll content is critical for field management and yield estimation. However, the lower model accuracy and the poor robustness of the estimation models are still preventing the widespread application of UAV-based multispectral images. We carried out two field trials at various experimental sites to further enhance the precision and applicability of the model used to estimate the chlorophyll content of potato plants. Firstly, the texture features and vegetation indices derived from multispectral images were screened using the Pearson correlation coefficient method, and Normalized difference red edge (NDRE) performed the best over the two growth periods. Secondly, principal component analysis (PCA) was applied to recombine five bands of multispectral images, and third PCA results (PCA3) was selected to combined with NDRE according to the construction principle of NDRE, and the newly constructed parameter was named improved NDRE (INDRE). Finally, INDRE was used to establish a chlorophyll content estimation model of potato plants, and compared with some traditional parameters. The results demonstrated that the INDRE had the maximum accuracy (R2 = 0.7865, RMSE = 2.1378), and corresponding R2 increased by 0.1481 and RMSE decreased by 1.2994 than NDRE. Additionally, the model was validated using independent data from Experiment 2, and INDRE considerably increased estimation accuracy compared to other factors. In conclusions, the INDRE suggested in this study significantly enhances the accuracy and applicability of the chlorophyll content inversion model and can serve as an additional reference for fertilization management.

The escalating levels of atmospheric carbon dioxide (CO₂) due to anthropogenic activities have raised significant concerns regarding their far-reaching consequences, including potential impacts on human brain function. This study employs Agent-Based Modeling (ABM) and a comprehensive literature review to comprehensively examine the effects of varying atmospheric CO₂ concentrations on human brain activity. Historical and projected CO₂concentration data, along with neuroscientific insights, were integrated into the ABM framework to simulate brain activity responses under different CO₂ scenarios. The simulations revealed that elevated CO₂ levels disrupt neural activity and alter neurotransmitter profiles, indicating potential cognitive consequences. Sensitivity analysis emphasized the importance of accurate parameterization for robust simulations. The findings underscore the urgent need to address global CO₂ emissions to preserve cognitive health. Further research is essential to validate and refine the model, incorporating additional factors for a comprehensive understanding of the cognitive repercussions of rising CO₂ levels, crucial for informed policy-making and public awareness campaigns.

Among the various types of gas sensors, the chemoresistive gas sensors based on metal oxides are considered the most attractive ones due to their simple operation, low costs and miniaturization. Thin films of V2O5 undoped and doped with TiO2 were studied as nitrogen dioxide, methane and hydrogen sensors. The experimental kinetics of the electrical conductivity changes due to introduction and removal of gas on metal oxide gas sensors were successfully explained in terms of the Langmuir adsorption theory.

Background: Recent research suggests a concerning trend of non-suicidal self-injury (NSSI) and suicidal behaviors emerging at younger ages (as early as age 12). Early onset of NSSI is linked to more severe outcomes. While universal school-based prevention programs have shown promise in addressing suicidal behaviors, there's limited research on their effectiveness in preventing NSSI onset among adolescents. This study aims to evaluate the efficacy of a universal prevention program in schools for NSSI and mental complaints while enhancing resilience and mental health in 11-14-year-old adolescents. Methods: In total, 329 Flemish secondary school students (55.6% female), aged 11 to 14 years, participated in a 4-hour classroom universal prevention, with a focus on emotion regulation, mental health, and specific strategies to prevent NSSI and reduce stigma. For both the intervention and control group (N = 124), a pre-, post- and one-month follow-up questionnaire was administered, containing reliable and valid measures for NSSI and suicidality, emotion regulation, help-seeking behaviors, well-being, and psychological distress. Results: The prevention program effectively reduced NSSI and psychological distress, particularly for adolescents with a history of NSSI. Conclusions: These findings support previous research on the effectiveness of school-based programs in reducing mental complaints and suggest promising outcomes for NSSI prevention.

System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these issues, we present an Agent-Based Model (ABM) for SoS evolution in the Internet of Vehicles (IoV) , serving as a quantitative analysis tool for SoS research. By integrating multiple complex and rational behaviors of individuals, we aim to simulate real-world scenarios as accurately as possible. To simulate the SoS evolution process, our model employs multiple agents with autonomous interactions and incorporates external environmental variables. Furthermore, we propose three evaluation metrics: evolutionary time, degree of variation, and evolutionary cost, to assess the performance of SoS evolution. Our study demonstrates that enhanced information transparency significantly improves the evolutionary performance of distributed SoS. Conversely, the adoption of uniform standards only brings limited performance enhancement to distributed SoSs. Although our proposed model has limitations, it stands out from other approaches that utilize Agent-Based Modeling to analyze SoS theories. Our model focuses on realistic problem contexts and simulates realistic interaction behaviors. This study enhances the comprehension of SoS evolution processes and provides valuable insights for the formulation of effective evolutionary strategies.

Objective: The aim of this in vitro study was to evaluate the accuracy of resin-based fixed dental restorations, namely veneers, single crowns, and four-unit fixed partial dental prosthesis (FPDs) using two different 3D printers and polymer-based materials. Materials and Methods: A standard maxillary polyurethane jaw model containing prepared teeth was scanned using an intraoral scanner. The generated STL data were used to design the restorations virtually using CAD software. Two 3D printers were utilized for the provisional digital light processing and stereolithography for the castable resin patterns. Each printer produced 10 specimens of each type of restoration, for a total of 80 restorations. The 3d-printed restorations were then 3D scanned using the same intraoral scanner and evaluated for external and internal dimensional accuracy in terms of trueness and precision. A one-way ANOVA and Two-sample T-Test were implemented to compute the precision (variability between groups) and trueness (with the designed CAD model). A level of statistical significance of p-Value

Agriculture is an important sector of European Union in societal , economic and environmental dimensions. Sustainability of the sector require improvements in its key operations. Weeding is one of the crucial operation having impact on farms’ productivity, safety for farmers, food security and environmental state. To achieve EU policy goals of sustainable agriculture there are needed new technical and organizational solutions. One of the advanced techniques are laser based weeding technique. It is important to understand well the impacts of introduction of these tech-niques to the markets and agricultural practice in sustainability context. For that reason Social Life Cycle Assessment was performed. The method was based on participatory approach. The as-sessment was carried in three perspectives: general society, farmers, and business perspective re-lated to agriculture. Expert interviews based on questionnaires and workshops were realized to get the opinions on the impacts of a new laser technique on particular aspects of its implementation. The results show generally positive impact in all perspectives, especially in the perspective of farmers.

Background: This study aimed to develop and evaluate a dietary self-care promotion program for hemodialysis patients based on Hurley's self-efficacy model. Methods: The needs of hemodialysis patients were identified, and an online community-based dietary self-care promotion program was developed with expert evaluations. 44 hemodialysis patients were randomly assigned to an experimental group (n=22) and a control group (n=22). The program was applied to the experimental group for four weeks. Before and after the intervention, as well as four weeks after the intervention, dietary self-efficacy, dietary self-care behavior, interdialytic weight gain, serum phosphorus, and serum potassium were assessed in both groups. Results: Significant differences over time and between groups were observed in dietary self-efficacy, interdialytic weight gain, serum phosphorus, and serum potassium. The interaction between time and group was also significant. While no significant differences were found over time in dietary self-care behavior, significant group differences and interaction effects between time and group were identified. Conclusions: The results indicate that the dietary self-care promotion program using an online community for hemodialysis patients is more effective in enhancing dietary self-efficacy and dietary self-care behavior compared to conventional treatment. This suggests the clinical applicability of the proposed dietary self-care promotion program.

Treatment wetlands (TWs) are Nature-Based Solutions increasingly used worldwide for wastewater (WW) treatment able to remove mineral and organic pollutants through both physical and biochemical process. Besides the reusable effluent, the TWs produce as main output plant biomass that need to be harvested and disposed at least once a year with significant management costs and TW temporary out of service. This study aims (i) to evaluate the potential of TWs biomass for local energy production and (ii) to understand TW hydraulic conductivity (Ks) effects on the biomass biomethane yield. Specifically, it was addressed by determining the Biochemical Methane Potential of common reed (CR) (Phragmites australis) samples collected at three harvest times from the 10-years-old horizontal subsurface treatment wetland (HSTW) used as a secondary WW treatment system for the IKEA® store located in Catania (Eastern Sicily, Italy). Furthermore, the falling head test was conducted to assess the hydraulic conductivity (Ks) variation in the HSTW, in order to understand the influence on the CR biomethane production. Average methane content values were 130.57 Nm3CH4/tVS (±24.29), 212.70 Nm3CH4/tVS (±50.62) and 72.83 Nm3CH4/tVS (±23.19) in August, September, October 2022, respectively. Ks was correlated with both dry matter (R2 = 0.58) and fiber content (R2 = 0.74) and, consequently, affected the biomethane yield that increased at the Ks increases (R2 = 0.30 in August, R2 = 0.57 in September). In the framework of a circular economy, results showed the successfully possibility of integrating the bioenergy production into TWs. The research could contribute (i) to encourage plant operators to reuse biomass from TWs for local energy production and (ii) to help plant operators to understand Ks effects on the biomass biomethane yield, in order to increase the sustainability of the system and to reduce the maintenance costs.

Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based architecture to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a use case of pedestrians at the Festival of Lights, Lyon, France. Pedestrian outflow data is extracted from video recordings of exiting crowds at the festival. The hybrid model is calibrated and validated using a genetic algorithm that optimizes the match between simulated and observed outflow data. Additionally, a local sensitivity analysis is then conducted to identify the most sensitive parameters in the model. Finally, the performance of the hybrid model is compared to different models in terms of density map and computation time. The results demonstrate that the hybrid model has the capacity to effectively simulate pedestrians across varied density scenarios while optimizing computational performance compared to other models.

In an IoT system, the sheer volume of data generated by numerous sensing devices necessitates a well-designed scheme for storing and retrieving data efficiently, enabling streamlined data processing and analytics. One promising storage architecture involves utilizing solid-state drives (SSDs) to cache data from hard disk drives (HDDs), thereby creating an SSD-based caching storage system. To further enhance access performance, it is possible to employ readahead techniques to minimize data access latency. However, the existing Linux readahead scheme falls short in fully leveraging SSD-based caching storage systems. We address this limitation by introducing a novel cross-layered readahead architecture that effectively communicates with the VFS layer, the file system layer, and the block I/O layer. This communication facilitates the acquisition of readahead timing, readahead data continuity, and readahead data location, respectively. To guide prefetching decisions, our architecture analyzes the degree of data access sequentiality, the performance model of the target storage device, and the access patterns of the I/O workload on the corresponding storage device. The implementation of this new architecture in the Linux kernel yields promising experimental results, demonstrating its robustness by consistently outperforming the stock Linux kernel. Notably, our architecture reduces the total execution time of the stock Linux kernel by up to 49%, except in cases of random workloads where both the stock Linux kernel and our architecture exhibit similar performance.

Plantation-based farmer cooperatives play an important role in promoting agricultural modernization and increasing farmer income, and the management of business risks of such cooperatives not only influences the development of the cooperatives themselves, but also concerns the interests of farmers. Based on the survey data of 226 sample cooperatives from Guizhou province, this article uses factor analysis to measure business risks of plantation-based farmer cooperatives and carries out empirical tests on influence factors of business risks through structural equation model. According to the research results, the ordering of business risks of plantation-based farmer cooperative based on their significance is as follows: market risk > policy risk > natural risk > technical risk > management risk. Influence factors including policy environment, economic environment, social service environment, technical environment, resource endowment of the cooperative and manager characteristics have significant positive influence on the cooperative, with economic environment and manager characteristics generating relatively stronger influence and social service environment generating relatively weaker influence. Through this research, several policy implications on driving high-quality development of plantation-based farmer cooperative are made, including specifying supportive policies of plantation-based farmer cooperative, improving economic environment of agricultural market, upgrading agricultural infrastructure, depending reform of land transfer system, and enhancing internal management of the cooperative.

The objective of this study is to evaluate how two varying amounts of sepiolite-based powder, infused with indigo extract, affect the appearance and durability of a water-based white primer. To examine the influence of this eco-friendly pigment on the coatings' overall appearance, assessments were performed for color, gloss, and surface roughness. Additionally, the coatings were investigated through optical and electron microscopic observations, to evaluate the distribution of the pigment within the polymer matrix. The effect of the pigment on the coating's durability was assessed through accelerated tests, including exposure in a salt spray chamber and a UV-B chamber. These tests aimed to evaluate the emergence of defects and changes in the appearance of the samples over time. Furthermore, the impact of different quantities of sepiolite-based powder on the coating's ability to act as a barrier was assessed using liquid resistance tests and contact angle measurements. These evaluations aimed to understand how the coating responded to various liquids and its surface properties concerning repellency or absorption. In essence, this study underscores the considerable influence of the eco-friendly pigment, demonstrating its capacity to introduce unique color and texture variations to the paint. Moreover, the inclusion of the pigment has enhanced the coating's color stability, its ability to act as a barrier, and overall durability when exposed to harsh environments.

In this research, we present the first steps taken towards a data-driven agent-based model (ABM) specifically designed for simulating infectious disease dynamics in Greece. Amidst the ongoing COVID-19 pandemic caused by SARS-CoV-2, this research holds significant importance as it can offer valuable insights into disease transmission patterns and assist in devising effective intervention strategies. To the best of our knowledge, no similar study has been conducted in Greece. We constructed a prototype ABM that utilizes publicly accessible data to accurately represent the complex interactions and dynamics of disease spread in the Greek population. By incorporating demographic information and behavioral patterns, our model captures the specific characteristics of Greece, enabling accurate and context-specific simulations. By using our proposed ABM, we aim to assist policymakers in making informed decisions regarding disease control and prevention. Through the use of simulations, policymakers have the opportunity to explore different scenarios and predict the possible results of various intervention measures. These may include strategies like testing approaches, contact tracing, vaccination campaigns, and social distancing measures. Through these simulations, policymakers can assess the effectiveness and feasibility of these interventions, leading to the development of well-informed strategies aimed at reducing the impact of infectious diseases on the Greek population. This study is an initial exploration toward understanding disease transmission patterns and a first step towards formulating effective intervention strategies for Greece.

Rapid haemostasis during surgery is essential when one wants to reduce the duration of opera-tions, reduce the need for transfusions, and above all when one wants to achieve better patient management. The use of haemostatic agents, sealants and adhesives improves the haemostatic process by offering several advantages, especially in vascular surgery. These agents vary widely in their mechanism of action, composition, ease of application, adhesion to wet or dry tissue, im-munogenicity and cost. The most used are cyanoacrylate-based glues (Glubran 2) or polysaccharide hydrogel-microsphere powder (AristaTMAH). This work is based on a retrospective study carried out on a sample of patients with different vascular diseases (FAV, pseudoaneurysm and PICC application) in which two different haemostatic sealants were used. The aim was to assess the safety, the advantages and the ability of both sealants to activate the haemostatic process at the affected site, also in relation to their chemical-physical characteristics. The obtained results showed that the application of Glubran 2 and AristaTMAH as surgical wound closure systems is effective and safe as the success achieved was ≥94% on anastomoses of FAV; 100% on stabilization of Picc catheters; ≤95% on pseudoaneurysms.

3D printing with earth-based mortar is still under development and faces challenges. Optimizing the mortar mixture, improving structural strength, determining the relationship between printing speed and the amount of extruded material, and ensuring long-term durability are areas that are still being refined. Additionally, regulatory and certification issues must also be considered to ensure the safety and compliance of 3D printed structures. This paper presents for discussion the records, analyses, studies, and considerations regarding the initial initiatives involving 3D printing with the extrusion of earth-based mortar developed at the Faculty of Engineering of the University of Porto - FEUP. Through this work, it is possible to strengthen and reaffirm that 3D printing with earth-based mortar has significant potential in the construction industry and that the incorporation of dispersed kraft paper fibres from the recycling of cement bags is an excellent resource to achieve good constructability in 3D printing with earth-based mortar.

This paper presents an approach to teacher identity heritage as result of the implementation of a research device created through Arts-based Research (ABR) methods, specifically with video elicitation and video essay used as research tools. Two main objectives were raised. The first one, to establish the real relevance of focusing performance on teacher identity. The second one, testing a new methodological proposal specifically designed for this purpose, but still useful in other contexts where heritage identity is as present as in teaching. The device, Body-camera, involves a process that allows new ways to understand the creation of identities using video to encourage the production of new meanings by visual and oral data. The participants were teachers in training during their internship period. Some notions about teachers' identity heritage were revealed, and also preserved, firstly, through personal perspectives by video elicitations and secondly, through collective perspectives by video essays. Both are video structures used in ABR which mix creative experience, memories, life experiences, relationships and links that shape the teachers’ professional identity.

LR004 is a novel chimeric (human/mouse) monoclonal antibody developed for the treatment of advanced colorectal carcinoma with detectable epidermal growth factor receptor (EGFR) expression. We aimed to investigate the preclinical pharmacokinetics (PK) and in vivo biodistribution of LR004. The PK profiles of LR004 were initially established in rhesus monkeys. Subsequently, 125I radionuclide-labeled LR004 was developed and its binding activity to the EGFR antigen were evaluated. Furthermore, the biodistribution, autoradiography, and NanoSPECT/CT of 125I-LR004 in xenograft mice bearing A431 tumors were examined. The PK data revealed a prolonged half-life and nonlinear PK characteristics of LR004 within the dose range of 6–54 mg/kg. The radiochemical purity of 125I-LR004 was approximately 98.54%, and iodination of LR004 did not affect its specific binding activity to the EGFR antigen. In a classical biodistribution study, 125I-LR004 exhibited higher uptake in highly perfused organs than in poorly perfused organs. Prolonged retention properties of 125I-LR004 in tumors were observed at 4 and 10 days. Autoradiography and NanoSPECT/CT confirmed the significant accumulation and sustained retention of 125I-LR004 at the tumor site in xenograft mice. These findings demonstrated the adequate tumor targeting capabilities of 125I-LR004 in EGFR-positive tumors, which may improve dosing strategies and future drug development.

Since sensor-based perception systems are used in autonomous vehicle applications, validating such systems is imperative to guarantee the robustness of the systems before they are being put to use. In this study, a comprehensive corruption-related simulation-based robustness verification and enhancement process for sensor-based perception systems is proposed. Firstly, we present a methodology and scenario-based corruption generation tools for creating diverse simulated test scenarios that can analogously represent real-world traffic environments, especially considering corruption types related to safety concern. Then, an effective corruption similarity filtering algorithm is proposed to remove corruption types with high similarity and identify the representative corruption types to represent all considered corruption types. As a result, we can generate efficient corruption-related robustness test scenarios with less testing time and good scenario coverage. Subsequently, we perform the vulnerability analysis of object detection models to identify model weaknesses and construct an effective training dataset for model vulnerability enhancement. This enhances the tolerance of object detection models to weather and noise-related corruptions, ultimately improving the robustness of the perception system. We employ case studies to demonstrate the feasibility and effectiveness of the proposed robustness verification and enhancement procedures. Additionally, we explore the impact of different "similarity overlap threshold" parameter settings on scenario coverage, effectiveness, scenario complexity (size of training and testing datasets), and time costs.

Water scarcity challenges have necessitated the adoption of water-saving techniques in protected and nom-protected farming. This study aimed to assess the performance of a water-saving soil-less cultivation technique and to compare it with conventional soil-based cultivation in protected farming. The soilless technique used local gravel and a mixture of peat-moss, humin-substrate, and perlite in ratios of 4:3:1.5. Three irrigation regimes were imposed using emitters 8Lh-1 design discharge (D1) emitters with 6Lh-1 design discharge (D0.75) and 4Lh-1 de-sign discharge (D0.5) for the two cultivation methods during the growth cycle of tomato by drip irrigation. The vegetative growth, fruit yield and water consumption were measured and water productivity was determined. Moreover, an economic assessment was carried out by estimating and comparing economic coefficients for the two cultivation methods. Estimated coefficients include revenues, net profit, benefit-cost ratio, break-even levels of production and prices, revenues over variable cost, and revenues on investment. The tomato fruit yield under soil-based cultivation overtopped the yield under soilless cultivation. The water productivity under the soilless cultivation was almost twice that (24.3 kg m-3) of the soil-based cultivation (15.5 kg m-3). The soilless cultivation saved 50% of irrigation water applied by the conventional soil-based method, saving energy and soil from deterioration. Revenues and net profits stimulated by higher yield coupled with lower variable cos supported the soil-based cultivation. The economic assessment showed that both cultivation methods were economically viable. However, the soil-based cultivation method was more profitable due to its higher fruit yield. Overall, the results of this study suggest that the soilless cultivation technique is a viable option for wa-ter-saving cultivation. However, the soil-based cultivation method is still more profitable due to its higher fruit yield

This work introduces an innovative approach that unites a PIDND2N2 controller and the balanced arithmetic optimization algorithm (b-AOA) to enhance the stability of an automatic voltage regulator (AVR) system. The PIDND2N2 controller, tailored for precision, stability, and responsiveness, mitigates the limitations of conventional methods. The b-AOA optimizer is obtained through integration of pattern search and elite opposition-based learning strategies into the arithmetic optimization algorithm. This integration optimizes the controller parameters and the AVR system's response, harmonizing exploration and exploitation. Extensive assessments, including evaluations on 23 classical benchmark functions, demonstrate the efficacy of the b-AOA. It consistently achieves accurate solutions, exhibits robustness in addressing a wide range of optimization problems, and stands out as a promising choice for various applications. In terms of AVR system, comparative analyses highlight the superiority of the proposed approach in transient response characteristics, with the shortest rise and settling times and zero overshoot. Additionally, the b-AOA approach excels in frequency response, ensuring robust stability and a broader bandwidth. Furthermore, the proposed approach is compared with various state-of-the-art control methods for the AVR system, showcasing impressive performance. These important results underscore the significance of this work, setting a new benchmark for AVR control by advancing stability, responsiveness, and reliability in power systems.

3D human pose estimation has made significant advancements through the integration of deep learning techniques. This survey provides a comprehensive review of recent 3D human pose estimation methods, with a focus on monocular images, videos, and multi-view cameras. Our approach stands out through a systematic literature review methodology, ensuring an up-to-date and meticulous overview. Unlike many existing surveys that categorize approaches based on learning paradigms, our survey offers a fresh perspective, delving deeper into the subject. For image-based approaches, we not only follow existing categorizations but also introduce and compare significant 2D models. Additionally, we provide a comparative analysis of these methods, enhancing the understanding of image-based pose estimation techniques. In the realm of video-based approaches, we categorize them based on the types of models used to capture inter-frame information. Furthermore, in the context of multi-person pose estimation, our survey uniquely differentiates between approaches focusing on relative poses and those addressing absolute poses. Our survey aims to serve as a pivotal resource for researchers, highlighting state-of-the-art deep learning strategies and identifying promising directions for future exploration in 3D human pose estimation.

This study aims to evaluate the combined assimilation of AGRI infrared radiance and ground-based MWR (Microwave Radiometer) data for predicting short-duration heavy rainfall. The WRFDA 4.3 framework is utilized to establish the data assimilation interface. The structural characteristics of this joint assimilation approach are analyzed using a typical heavy rainfall event in the Kaifeng region of Central China. The findings indicate the following: (1) The joint assimilation of FY-4A AGRI and ground-based MWR data effectively corrects the initial moisture content in model simulations. Data assimilation significantly improves the simulation of 24-hour accumulated rainfall. Furthermore, the joint assimilation of AGRI radiance and MWR data outperforms assimilating either of them individually; (2) In the heavy rainfall stage, from the low level to the high level, strong upward movement occurs in the center of the rainstorm. The water vapor in the process of this rainstorm mainly comes from the westward air transport in front of the high trough. The water vapor is continuously transported to the heavy rainfall belt through this channel, providing sufficient water vapor for the maintenance of the rainstorm; (3) The combination of the interaction between high and low level vorticity and divergence in the atmosphere and the vertical upward movement, the emergence of low level jet and the generation of unstable energy in the atmospheric environment jointly lead to the occurrence of the rainstorm process; and (4) The terrain-sensitive experiment results show that, the existence of the topography of Taihang Mountain changes the precipitation in Kaifeng area, and reducing the terrain height will lead to a 50%-60% decrease in the overall precipitation of the precipitation center, and the precipitation range will also be greatly reduced. An increase of more than 50% in terrain height will lead to an increase in precipitation center, precipitation range and precipitation intensity, and an increase of 10%-20% in overall precipitation; An increase of more than 75% in the terrain height will cause the rain belt to shift eastward by about 0.5°E, and the precipitation center will shift significantly eastward. When the terrain height increased by more than 100%, the precipitation did not continue to increase, which was basically the same as the control test. This paper provides a valuable basis for further improving the application of FY-4A AGRI radiance and ground-based microwave radiometer in numerical weather models.

Women's attitudes towards domestic violence play an important role in shaping the social acceptance of domestic violence, acting as both a known predictor of victimization and an indicator of disclosure and help-seeking behavior. Therefore, the study objectives were 1) to conduct a nationwide analysis to explore the factors associated with the acceptance of domestic violence among Iraqi women according to the social-ecological framework, and 2) to identify the most vulnerable women according to the spatial distribution of Iraqi governorates. This cross-sectional study was conducted using secondary data analysis from the 2018 Iraq Multiple Indicator Cluster Survey (MICS 6), which included 19,443 married Iraqi women. Logistic regression was employed to examine the factors associated with acceptance of domestic violence. In this study, the analyses were performed according to the Social Ecological Model (SEM). This study revealed that 48.4% of married Iraqi women accepted domestic violence. Yet, women living in South/Central regions of Iraq showed a higher prevalence of domestic violence acceptance namely Anbar, Salahaddin Thiqar, and Misan where the prevalence was (62%-73%). Several factors across the social-ecological model were associated with a higher likelihood of women accepting such behavior, including experiencing functional difficulty, having lower educational attainment, being married to a blood-related husband, and being married to a husband who has multiple wives/partners, living in poverty, residing in rural areas, living in the south and central regions of Iraq, and feeling unsafe in the neighborhood. Conversely, factors that were associated with a lower likelihood of women accepting such behavior were owning a mobile phone and using a computer or tablet. This study provides policymakers with valuable insights to comprehensively assess indicators of attitudes toward domestic violence against women. It also addresses the scarcity of information on the acceptance of domestic violence in Iraq on national and governorate levels, emphasizing the need for urgent national-level policy discussions to achieve key Sustainable Development Goals related to gender equity and good health and well-being.

Coseismic landslides pose significant threats, causing widespread destruction of buildings, roads, pipelines, and leading to numerous casualties. In recent years, the frequency of earthquakes has increased, prompting a growing interest in regional-scale assessment techniques for coseismic landslides. The infinite slope model proposed by Newmark is widely used to evaluate coseismic landslide hazard. However, the infinite slope model fails to reflect the impact of rock mass structure on the stability of slopes. This paper proposes a novel approach for mapping the hazards of coseismic landslides by considering the roughness of the potential slide surfaces in the inner slope. The proposed method is validated using data from the 2013 Lushan earthquake. The datasets, including geological units, peak ground acceleration (PGA), and high-resolution digital elevation models of topography, are rasterized at a grid spacing of 30 meters. They are then combined within an infinite slope model based on Newmark permanent-deformation analysis, enabling the estimation of coseismic landslide displacement in each grid area resulting from the Lushan earthquake. The modeled displacements are compared with the inventory of landslides triggered by the Lushan earthquake, allowing the derivation of a confidence level function that relates predicted displacement to the spatial variation of coseismic landslides. Ultimately, a hazard map of coseismic landslides is generated based on the established confidence level function. This map serves as a valuable tool for predicting the hazard zone of seismic regions and offers essential insights for decision-making related to infrastructure development and post-earthquake construction.

Cyber-Physical Systems (CPS) play an essential role in today’s production processes, leveraging Artificial Intelligence (AI) to enhance operations such as optimization, anomaly detection, and predictive maintenance. This article reviews a cognitive architecture for artificial intelligence, which has been developed to establish a standard framework for integrating AI solutions into existing production processes. Given that machines in these processes continuously generate large streams of data, Online Machine Learning (OML) was identified as a crucial extension to the existing architecture. To substantiate this claim, real-world experiments using a slitting machine were conducted to compare the performance of OML with traditional Batch Machine Learning. The evaluations clearly indicate that OML adds significant value to CPS and is strongly recommeded as an extension of related architectures such as the cognitive architecture for AI discussed in this article. Additionally, surrogate model-based optimization is employed to determine the optimal hyperparameter settings for the corresponding OML algorithms, aiming to achieve peak performance in their respective tasks.

Within an amplicon-based metagenomic study of Archaea, Fungi, and Bacteria in Livingston Island, Maritime Antarctica, in many of the samples antagonisms between these three super kingdoms were observed under the form of an inversely proportional dependence of the richnesses of the three types of microorganisms. This was quantified - based on the observed numbers of the total tags and the numbers of the operational taxonomic units (OTUs), as well as based on four alpha diversity parameters – the Shannon, the Simpson, the Chao1, and the ACE indices. We found that the most discriminative results in the antagonism measuring were observed in the comparison of the numbers of the OTUs and the ACE community richness estimator. The antagonism between Archaea and Fungi was strongest, followed by that of Archaea and Bacteria. The Fungi-Bacteria antagonism was slightly detectable. Pearson and Spearman correlation analysis also showed a statistically significant negative correlation between the fungal and archaeal effective tags, while the correlation between archaeal and bacterial diversity was positive. Indications of the order of primary microbial succession in barren ecological niches were also observed, demonstrating that Archaea and Bacteria are the pioneers, followed by Fungi which in time would displace Archaea.

Background: The target volume for post-mastectomy radiation therapy (PMRT) in breast cancer patients with reconstruction has been a subject of debate. This study aimed to assess the radiation dose distribution and treatment outcomes associated with different chest wall (CW) delineation according to ESTRO ACROP guideline for patients underwent implant-based reconstruction. Methods: We conducted a retrospective review of breast cancer patients who underwent mastectomy followed by two-stage implant-based breast reconstruction and adjuvant radiation therapy (RT) between 2007 and 2022. The expanders/implants were positioned retropectorally. The chest wall target volumes were categorized into two groups: the prepectoral group, which excluded the deep lymphatic plexus, and the whole expander group. Results: The study included 26 patients, 15 in prepectoral group and 11 in whole expander group. No significant differences were observed in normal organs exposure between the two groups. There was a trend toward a lower ipsilateral lung mean dose in the prepectoral group (10.2 vs. 11.1 Gy, p=0.06). Both groups exhibited limited instances of reconstruction failure and local recurrence. Conclusions: For patients undergoing two-stage expander-implant retropectoral breast reconstruction and PMRT, our data have provided comparable outcomes and normal organs exposure for those omitting the deep lymphatic plexus.

This study assesses the impact of incorporating an adaptive learning mechanism into an agent-based model (ABMS) simulating behavior on a university campus during the course of a pandemic outbreak, with a particular case on the COVID-19 pandemic. The aim is to reduce overcrowding and infections on campus through the use of Reinforcement Learning (RL). Our findings indicate that RL is a viable approach for effectively representing agents’ behavior within this context. The results reveal specific temporal patterns of overcrowding violations. While our study successfully mitigated campus crowding, it had limited influence on altering the course of the epidemic. This highlights the necessity for comprehensive epidemic control strategies that consider the role of individual decision-making influenced by adaptive learning, along with the implementation of targeted interventions. This research significantly contributes to our understanding of adaptive learning within complex systems and offers valuable insights for shaping future public health policies in similar community settings. Future research directions encompass exploring various parameter settings and updating representations of the disease’s natural history.

The growing population with changing consumption patterns in developing countries is causing significant challenges with regards to solid waste management. Plastic wastes are particularly problematic, with single-use plastics leaking into the environment, including the marine environment, at an unprecedented rate. Approximately 80 percent of ocean plastics come from land-based sources or about 8 million tons are dumped into the ocean every year. Thailand was identified as one of the top 10 countries ranked by mass of mismanaged plastic wastes, with more than 60,000 tons per year entering the ocean through multiple outlets, including rivers. In the environment, plastic wastes can be degraded into small sizes (less than 5 mm), called microplastics (MPs), which could contaminate the ecosystems and the food chain, including foodstuffs and water supply. Tap water samples collected from a water supply treatment plant and Academic Institutions 1 and 2 in central Thailand were found to contain MPs about 304 ±90, 270 ±109 and 386 ±102 particles/L, respectively. In addition, MPs concentrations of 211 ±70 and 122 ±60 particles/L were also found in drinking water samples collected from commercial bottled water and membrane filtration water, respectively. The MPs sizes of 0-50 µm were most abundant in both the tap and drinking water samples whose shapes were mainly fragments and fiber. These data indicated potential health risks to the people who consume these water sources, and recommendations for health impacts minimization were proposed.

Following on from work already carried out in our laboratory on a new biomass-derived green solvent, eucalyptol, we are now turning our attention to sabinene as a new green solvent. Sabinene is also derived from biomass. We have shown that it can be used as such or distilled to synthesize thiazolo[5,4-b]pyridine heterocycles by thermal or microwave activation. This new solvent was compared with various conventional and green solvents. The conditions were optimized to enable us to carry out the syntheses in good yields, and we were able to show that sabinene, a natural bicyclic monoterpene, could be used effectively as a solvent.

We designed a bidirectional reflection distribution function (BRDF) measurement system to research the characteristics of space target materials. This system measures the BRDF data of an aluminum plate and gold foil. A hybrid biogeography-based optimization-firefly (BBO-Firefly) algorithm was proposed to optimize the five-parameter BRDF model. To check the performance of the hybrid BBO-Firefly algorithm, we set up a contrast experiment to optimize the BRDF parameters using the BBO algorithm, Firefly algorithm, and hybrid BBO-Firefly algorithm. The experimental results prove that the hybrid BBO-Firefly algorithm surpasses the BBO algorithm and Firefly algorithm in convergence speed and precision in the same situation and has a better optimization effect. Finally, we substitute the optimization results of the hybrid BPO-Firefly algorithm into the BRDF model to analyze the reflection characteristics of an aluminum plate and gold foil.

The scope of this paper is to compare different dental sealants and flow materials indicated for sealing pit and fissures considering their chemical formula. The narrative review aims to address the questions: What is the essence of different dental sealants’ activity, how their chemical formula affects their mechanisms of caries prevention and what makes a dental sealant efficient mean of caries prevention. Another vital issue is whether the sealants which contain fluoride, or any other additions have potentially increased antimicrobial properties. Methods: An electronic search of the PubMed, Cochrane, Web of Science and Scopus databases was performed. The following keywords were used: (dental sealants) AND (chemical composition). Additionally, information about composition and indications for clinical use provided by manufacturers were utilized. The review aims are to find crucial elements of sealants’ composition which affect their cariostatic mechanisms.

Self-adaptive systems are capable of reconfiguring themselves while in use to reduce the risks forced by environments for which they may not have been specifically designed. Run-time validation techniques are required because complex Self-adaptive systems must consistently offer acceptable behavior for important services. The run-time testing can offer further confidence that a Self-adaptive system will continue to act as intended even when operating in unknowable circumstances. This article introduces an evolutionary framework that supports adaptive testing for Self-adaptive systems. To ensure that the adaptive systems continue to operate following its requirements and that both test plans and test cases continuously stay relevant to shifting operational conditions. The proposed approach using the SPEA2 algorithm facilitates both the execution and adaptation of run-time testing operations.

The notion that ‘Stock-G’ humpback whales off western South America are primarily deep oceanic migrators is poorly supported. We documented 66 land-based sightings from Pucusana, Lima Sur: 18 incidental (2002–2023) and 48 dedicated sightings during the northbound winter migration (June-July 2023), covering respectively 38 and 105 individual whales, despite a mean daily observer effort of only 58.7 min. Estimated distances from shore ranged 20–7,000 m (mean= 2,729 m) at depths 25–99 m, while 50% migrated at < 2,500 m (median) from shore. Several groups skirted the coastline from headland to headland. Of five southbound migrating groups, four included an adult with neonate; no northbound groups enclosed a neonate. Two cases of single juvenile/subadult whales moving multidirectionally and closely associated with large seabird feeding frenzies, were considered foraging also. In 2023, 94% of all northbound nearshore sightings occurred from 14 June-11 July, signalling the maximum threat period for interactions with coastal fisheries off metropolitan Lima. If migration is temporally and spatially predictable, effective mitigating measures should be feasible.

Survivors of sexual and gender-based violence (SGBV) are often hindered in their quest to access quality healthcare. This could complicate the achievement of the laudable SDG Target 3.7. The study used an ethnographic approach to solicit information from health providers, adolescents, and young women (AYW) in 10 communities from Lagos and Ibadan; two major cities in Nigeria. Findings indicated that the structural system of services provided in the health services at the primary healthcare level was limited, which posed a great challenge in AYW’s utilization of services for sexual and gender-based violence (SGBV). Some of the challenges identified by health providers included non-existing counseling services, rehabilitation centers, referral problems, and a lack of training for health providers in handling victims of SGBV. The study provided the context of the health providers’ inadequacy and structural problem of health services in providing comprehensive support services to victims of SGBV like adolescents and young women in the slum setting. This poses a barrier to the utilization of services by the survivors. Necessary inclusive services that will meet the need of the victims of SGBV should be in place at primary healthcare centers close to the people in the community for accessibility.

This study investigates the influence of the porous structure, on the density and the mechanical behaviour of new foam concretes incorporating hemp shives. A total of eight batches of foam concretes were manufactured and tested, made with a protein-based foam agent, containing cement, ground granulated blast furnace slag and Metakaolin as binder and hemp shives as natural aggregate. The effect of several parameters is studied, elaboration method (direct and preformed), amount of pozzolanic additions (0% and 30%) and incorporation of hemp shives (5 and 15 vol%) on the resulting physical properties, microstructure, porous structure and mechanical behaviour of the concretes. Hemp shives incorporation results in increased concrete porosity and air bubble radius, decreased uniformity and mechanical strength, and lower cohesion with the cement matrix compared to standard concretes.

This work aimed to develop an easy-to-use smartphone-based electrochemical biosensor to quickly assess coffee blend's total polyphenol (Phs) content at industrial and individual level. The device is based on a commercial carbon-based screen-printed electrode (SPE) modified with multi-walled carbon nanotubes (CNTs) and gold nanoparticles (GNPs). At the same time, the biotransducer, Laccase from Trametes versicolor, TvLac, was immobilized on the sensor surface by using glutaraldehyde (GA) as cross-linking agent. The platform was electrochemically characterized to ascertain the influence of the SPE surface modification on its performance. The working electrode (WE) surface morphology characterization was obtained by scanning electron microscopy (SEM) and Fourier-transform infrared (FT-IR) imaging. All the measurements were carried out with a micro-potentiostat Sensit Smart by PalmSens connected to a smartphone. The developed biosensor provided a sensitivity of 0.12 μA/μM, a linear response ranging from 5 to 70 μM, and a lower detection limit (LOD) of 2.99 μM. Afterwards, the biosensor was tested for quantifying the total Phs content in coffee blends, evaluating the influence of both the variety and the roasting degree. The smartphone-based electrochemical biosensor performance has been validated though the Folin-Ciocâlteu standard method.

Cells are influenced by several biomechanical aspects of their microenvironment, such as substrate geometry. According to the literature, substrate geometry influences the behavior of muscle cells; in particular, the curvature feature improves cell proliferation. However, the effect of the substrate geometry on the myogenic differentiation process is not clear and needs to be further investigated. Here, we show that the 3D co-printing technique allows the realization of substrates. To test the influence of the co-printing technique on cellular behavior we realized linear polycaprolactone substrates with channels in which a fibrinogen-based hydrogel loaded with C2C12 cells was deposited. Cell viability and differentiation were investigated up to 21 days in culture. The results suggest that this technology significantly improves the differentiation at 14 days. Therefore, we investigate the substrate geometry influence by comparing three different co-printed geometries – linear, circular, and hybrid structures (linear and circular features combined). Based on our results, all structures exhibit optimal cell viability (&gt; 94%) but the linear pattern allows to increase the in-vitro cell differentiation, in particular after 14 days of culture. This study proposes an endorsed approach for creating artificial muscles for future skeletal muscle tissue engineering applications.

All solar thermal systems, due to their thermal nature, can be hybridised or operated with both fossil fuel and solar energy. By enhancing availability and dispatch ability, hybridization has the potential to boost the value of concentrating solar thermal technology. Hybrid photovoltaic thermal systems (PV/T) offer a solution to improve on the limited capacity growth seen with standard solar panels. The analysis focuses on the creation of alternative structural and design so-lutions that may be used to boost lacking efficiency that was previously hampered by limited spectrum absorption of sun light. As a result, the spectrum is separated into two spectrum ranges, one that directly matches the bandgap of PV materials and the other that is absorbed for thermal absorption outputs. Most two channel systems are used to capture or reflect sunlight, with the layer specifically located right above the PV cell. Another layer of nanofluid is employed to evacuate heat from the PV cell, acting as the second channel, to specifically eliminate overheating difficulties. To address concerns that have arisen as a result of years of observation, the most recent study involves nano-particle-based fluids employed in PV/T, which uses a cooling medium to provide an alternate heat transfer option. Aside from nanofluids, there are phase change materials, channel alterations that result in a higher flow rate and hence improve overall performance.

Evidence-based data for endometriosis management are limited. Experiments are excluded without adequate animal models. Data are limited to symptomatic women and occasional observations. Hormonal medical therapy cannot be blinded if recognised by the patient. Randomised controlled trials are not realistic for surgery since a variable disease with low numbers. Each diagnosis and treatment is an experiment with an outcome and experience is Bayesian updating from the past. If the experience of many is similar, this has more value than an opinion. The combined experience of a group of endometriosis surgeons was used to discuss problems in the management of endometriosis. Considering endometriosis as several genetically/epigenetically different diseases is important for medical therapy. Imaging cannot exclude endometriosis and diagnostic accuracy is limited for superficial lesions, deep lesions, and cystic corpora lutea. Surgery should not be avoided for emotional reasons. Shifting infertility treatment to IVF without considering fertility surgery is questionable. The concept of complete excision should be reconsidered. Surgeons should introduce quality control and teaching should move to explain why it is done. The perception of information has a personal bias. These are the major problems in the management of endometriosis identified by the combined experience of endometriosis surgeons.

There is an international concern for reducing energy consumption and protecting the environment in the construction industry. The energy efficiency of a building depends on the thermal resistance of concrete, and utilizing concrete products with elevated thermal resistance can enhance this aspect. This study analyzes the impact of perlite, as an addition, on the physico-mechanical properties of concrete, with the aim of identifying perlite concrete products that will respond to the improvement of the heat transfer resistance of the building envelope. The study examines the effect of replacing different amounts of concrete aggregates with perlite in percentages of 10%, 20%, 30%, and 100%. The results show that substituting sand with perlite improves the thermal performance of concrete, but its mechanical properties are negatively affected. The research carried out highlighted that perlite can be successfully introduced in the production of concrete blocks used for external non-bearing wall panels, the outstanding feature being the reduction of energy consumption in buildings. Overall, the paper identifies an efficient and environmentally friendly way of using perlite in the construction industry, enhancing the energy efficiency of buildings while minimizing the environmental footprint caused by the construction industry.

Animal welfare assessment protocols are important for identifying welfare problems in conservation programs. This study aimed to develop a baseline welfare protocol for the assessment of welfare in huemul (Hippocamelus bisulcus) in conservation centers. This protocol is based on the Welfare Quality® (WQ) framework for cattle, considering the available literature on the behaviours, ecology, conservation plans, captive management of this species, and welfare assessment protocols for other ungulate species. As a result, the protocol was specifically developed for huemuls and included four principles, 12 criteria, and 23 animal- and resource-based indicators. The 12 criteria of the WQ protocol were reduced to nine, and three new criteria were added because they were both feasible and essential for welfare assessment in captive huemuls. This protocol is mainly intended to identify welfare problems in endangered species in the context of conservation centers (reproduction, rescue, rehabilitation, or treatment centers). Thus, aggregation of different measures to obtain a global score has not been proposed. However, a scoring system that assigns a value on a 0-2 scale (0= No welfare concern; 1= welfare concern; 2= urgent welfare concern) is proposed for each category. Although further research is still needed to fully validate the protocol, this is the first development of a completed protocol for huemul welfare assessment.

High-precision ground point cloud data has a wide range of applications in various fields, and the separation of ground points from non-ground points is a crucial preprocessing step. Therefore, designing an efficient, accurate, and stable ground extraction algorithm is of great significance for improving the processing efficiency and analysis accuracy of point cloud data. The study area in this article was a Park in Guilin, Guangxi, China. The point cloud was obtained by utilizing the UAV platform. In order to improve the stability and accuracy of the Filter algorithm, this article proposed a triangular grid filter based on Slope Filter, found violation points by the spatial position relationship within each point in the triangulation network, improved KD-Tree-Based Euclidean Clustering, and applied it to the non-ground points extraction, this method has good accuracy, stability and achieves good results in separating ground points from non-ground points. At first, using Slope Filter to remove some non-ground points, to reduce the error of taking ground points as non-ground points; Secondly, established a triangular grid based on the triangular relationship between each point, the violation-triangle can determin through the grid, and then the corresponding violation points were found in the violation-triangle; Thirdly, according to the three-point collinear method to extract the regular points, used these points to extract the regular landmarks by KD-Tree-Based Euclidean Clustering and Convex Hull Algorithm; Finally, removed disperse points and irregular landmarks by Clustering Algorithm. In order to confirm the superiority of this algorithm, this article compared the filter effects of various algorithms on the study area and filtered the 15 sample data provided by ISPRS, and obtained an average error of 3. 46%. The results showed that the algorithm in this article have a high processing efficiency and accuracy, which can greatly improve the processing efficiency of point cloud data in practical applications.

Nanotechnology and polymer engineering are steering towards a new development to invade deleterious mysteries. In the last few decades, polymer engineering has grabbed researchers’ attention and similarly, polymeric network-engineered structures have been vastly studied. Prior to therapeutic application, early and quick detection analyses are critical. Therefore, developing nanoscale sensors to manage the acute expression of feeble states and malignancies to draw therapeutic lines demands advanced nanoengineering. In spite of nano-therapeutics have emerged as an alternative approach to tackling strenuous diseases. Also, studies have shown highly biocompatible biomedical engineering has emerged with sheer progression. Moreover, hydrogels have emerged as a three-dimensional (3D) polymeric network that consists of hydrophilic natural or synthetic polymers. The resemblance of hydrogels with tissue structure makes it more unique to study inquisitively. Preceding studies have shown a vast spectrum of synthetic and natural polymer deployment in the field of biotechnology and molecular diagnostics. This review explores recent studies on synthetic and natural polymer engineered hydrogel-based biosensors and their applications in multipurpose diagnostics and therapeutics. We reviewed the latest studies on hydrogel-engineered biosensors, exclusively DNA-based and DNA hydrogels fabricated biosensors.