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Machines operate under increasingly harsher contact conditions, causing significant wear and contact fatigue. Sub-surface stresses are responsible for the premature contact fatigue of rolling element bearings, meshing gears, and cam–follower pairs. Surface protection measures include hard, wear-resistant coatings. Traditionally, contact integrity has been
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Machines operate under increasingly harsher contact conditions, causing significant wear and contact fatigue. Sub-surface stresses are responsible for the premature contact fatigue of rolling element bearings, meshing gears, and cam–follower pairs. Surface protection measures include hard, wear-resistant coatings. Traditionally, contact integrity has been predicted using classical Hertzian contact mechanics. However, the theory is only applicable when the contact between a pair of ellipsoidal solids of revolution may be considered as a rigid indenter penetrating a semi-infinite elastic half-space. Many coatings act as thin bonded elastic layers that undergo considerably higher pressures than those predicted by the classical theory. Furthermore, inelastic deformation of bonded solids can cause plastic flow, work-hardening, and elastoplastic behaviour. This paper presents a comprehensive, integrated contact mechanics analysis that includes induced sub-surface stresses in concentrated counterformal finite line contacts for all the aforementioned cases. Generated pressures and deformation are predicted for hard coated surfaces, for which there is a dearth of relevant analysis. The contact characteristics, which are of particular practical significance, of many hard, wear-resistant advanced coatings are also studied. The paper clearly demonstrates the importance of using efficient semi-analytical, detailed holistic contact mechanics rather than the classical idealised methods or empirical numerical ones such as FEA. The novel approach presented for the finite line contact of thin-layered bonded solids has not hitherto been reported in the open literature.
Full article
Campylobacter jejuni is a zoonotic bacterium with the capacity to invade the epithelial cells during the pathogenic process. Several bacterial factors have been identified to contribute to this process, but our knowledge is still very limited about the response of the host. To
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Campylobacter jejuni is a zoonotic bacterium with the capacity to invade the epithelial cells during the pathogenic process. Several bacterial factors have been identified to contribute to this process, but our knowledge is still very limited about the response of the host. To reveal the major routes of this response, a whole-transcriptome analysis (WTA) was performed where gene expressions were compared between the 1st and the 3rd hours of internalization in INT407 epithelial cells. From the 41,769 human genes tested, altogether, 19,060 genes were shown through WTA to be influenced to different extents. The genes and regulation factors of transcription (296/1052; 28%), signal transduction (215/1052; 21%), apoptosis (153/1052; 15%), immune responses (97/1052; 9%), transmembrane transport (64/1052; 6%), cell–cell signaling (32/1052; 3%), cell–cell adhesions (29/1052; 3%), and carbohydrate metabolism (28/1052; 3%) were the most affected biological functions. A striking feature of the gene expression of this stage of the internalization process is the activation of both immune functions and apoptosis, which convincingly outlines that the invaded cell faces a choice between death and survival. The seemingly balanced status quo between the invader and the host is the result of a complex process that also affects genes known to be associated with postinfectious pathological conditions. The upregulation of TLR3 (3.79×) and CD36 (2.73×), two general tumor markers, and SERPINEB9 (11.37×), FNDC1 (7.58×), and TACR2 (8.84×), three factors of tumorigenesis, confirms the wider pathological significance of this bacterium.
Full article
Effects of mowing on vegetation parameters have been well studied. However, less is known about mowing effects on soil fauna and if soil properties alter this. We investigated earthworm communities in a long-term experiment 14 years after its establishment in 5 dry, fresh
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Effects of mowing on vegetation parameters have been well studied. However, less is known about mowing effects on soil fauna and if soil properties alter this. We investigated earthworm communities in a long-term experiment 14 years after its establishment in 5 dry, fresh and moist grassland plots located in the Natura 2000 site Lainzer Tiergarten near Vienna, Austria (238–402 m a.s.l., 48°10′ N, 16°12′ E). The grasslands were either mowed once a year or every second year, or not mowed since being established. Earthworms were assessed using the non-destructive octet electro-shocking method. Additionally, vegetation composition, soil conductivity, temperature and moisture were assessed. We found 13 earthworm species across all treatments, although their abundance was generally low with 6.1 ± 4.7 worms m−2. The total earthworm abundance and species diversity was higher in dry compared to fresh and moist grasslands but was not affected by mowing frequency. Endogeic earthworms (Aporrectodea caliginosa, Aporrectodea rosea) and epigeics (Lumbricus rubellus) were more tolerant to mowing than anecics (Lumbricus terrestris, Allolobophora longa). Since plant species richness was highest in annually mown grasslands and earthworm species richness was positively related to plant species numbers, we recommend regular, low-input management to promote above- and belowground biodiversity in these grasslands.
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Asphalt pavements are prone to cracking in low-temperature environments, and microwave heating (MH) can heal the cracks effectively. This research mainly investigates the different MH effects on the self-healing properties of asphalt mixtures. With this objective, the three-point splitting test is conducted to
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Asphalt pavements are prone to cracking in low-temperature environments, and microwave heating (MH) can heal the cracks effectively. This research mainly investigates the different MH effects on the self-healing properties of asphalt mixtures. With this objective, the three-point splitting test is conducted to generate the cracks. A microwave oven is employed to heat the samples, and a thermal camera measures the surface temperature. Results indicate that heating power and time show a positive linear correlation with healing efficiency, and the HI of the samples can reach over 80%. The HI of the samples decreases with the heating cycle, but the sample with reasonable power and time still has a HI higher than 70% after 5 cycles. The temperature peaks on thermal images indicate that uneven heating exists during heating, but the heating uniformity is within an acceptable range. The healing efficiency level (HEL) suggests that asphalt mixtures have very low inefficient healing behavior if the heating time is below 45 s, but HEL can reach 86.14% at 700 W after 60 s. Furthermore, although the HI of strength shows ideal results, the recovery of other crack parameters, including stiffness, fracture energy, flexible index, and crack resistance index, are not satisfactory.
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The differences in albumen photographs from vintage photographic studios were identified by energy-dispersive X-ray fluorescence spectroscopy and Fourier transform infrared spectroscopy. The results inspired the concept of finding common features characteristic of a given photographic studio. The obtained measurement data (i.e., positions of
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The differences in albumen photographs from vintage photographic studios were identified by energy-dispersive X-ray fluorescence spectroscopy and Fourier transform infrared spectroscopy. The results inspired the concept of finding common features characteristic of a given photographic studio. The obtained measurement data (i.e., positions of vibrational bands for characteristic groups of albumen and the mass contents of chosen elements) were analyzed chemometrically by employing the Principal Component Analysis (PCA). The PCA technique allowed us to reduce the number of relevant experimental parameters characterizing the unique features of the photographic objects. The two major components were able to distinguish the photographic objects in terms of their authorship and the time to produce a photograph. The method developed was examined for a selected group of photographs consisting of albumen prints from three Polish photographic ateliers. To validate ED-XRF measurements and, consequently, the chemometric findings, reference albumen photo samples were designed and prepared. The empirical functional relationships between the content of photochemically reduced silver particles on the photographic paper and several physicochemical factors, including time of exposure to UV light, AgNO3 concentration in a fixed bath, and concentrations of other additives, were proposed. These results can be used for the prediction of the experimental conditions under which the investigated photographs were developed.
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The recent COVID-19 pandemic effectively concretized the vitality of health expenditure and the economic-growth nexus, and the threat of new pandemics make re-examining this relationship a necessity. Consequently, this paper focuses on this nexus for developed OECD countries, paying particular attention to the
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The recent COVID-19 pandemic effectively concretized the vitality of health expenditure and the economic-growth nexus, and the threat of new pandemics make re-examining this relationship a necessity. Consequently, this paper focuses on this nexus for developed OECD countries, paying particular attention to the effects of the COVID-19 pandemic. The use of stock indices as proxy variables for health expenditure and economic growth enabled the examination of this nexus by using high-frequency data and financial econometric techniques, specifically via rolling correlation and bivariate GARCH analyses. The data span 1170 observations between 15 May 2018 and 11 November 2022. Since the research period overlaps with the outbreak of Ukraine–Russia war, additional insights are obtained regarding the effects of the war as well. It was found that an increase in health expenditure leads to a delayed increase in economic growth even in the short term, and this relationship mainly develops during crises such as epidemics, wars, supply chain breakdowns, etc., for developed OECD countries. Given the aging population of developed countries, which will probably deteriorate the health status of those countries in the near future, the increasing political tensions around the globe and the considerations of a global recession highlight the importance and the inevitability of investments in health capital for developed countries as well.
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Persistent HPV infections may cause cervical and vaginal intraepithelial neoplasia (CIN and VaIN). Traditional methods might destroy the structure and function of the cervix. 5-aminolevulinic acid photodynamic therapy (ALA-PDT) is a non-invasive targeted therapy. This study aims to evaluate the efficacy and safety
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Persistent HPV infections may cause cervical and vaginal intraepithelial neoplasia (CIN and VaIN). Traditional methods might destroy the structure and function of the cervix. 5-aminolevulinic acid photodynamic therapy (ALA-PDT) is a non-invasive targeted therapy. This study aims to evaluate the efficacy and safety of ALA-PDT for CIN and VaIN and the clearance of HPV. A retrospective study of 303 patients who confirmed CIN or VaIN and received ALA-PDT was conducted. All the patients were followed up at six and twelve months after treatment and then annually thereafter. The effect was evaluated through HPV genotyping, a cytology test, and colposcopy-directed biopsy if necessary. After ALA-PDT, the remission rates for CIN 2, CIN 3, VaIN 2, and VaIN 3 were 90.6%, 88.5%, 87.3%, and 77.8%. For CIN 1, the remission rate at the six-month follow-up was 93.1%. The total HPV clearance rates were 72.5% at the six-month follow-up and 85.7% at the 12-month follow-up. The most common adverse event was vaginal discharge. No severe adverse effect was observed. ALA-PDT is an effective and safe treatment for all grades of CIN and VaIN and is helpful in clearing HPV with minimal side effects. This treatment may not influence fertility and delivery.
Full article
Airborne particulate matter (PM) is of great concern in the modern-day atmosphere owing to its association with a variety of health impacts, such as respiratory and cardiovascular diseases. Of the various size fractions of PM, it is the finer fractions that are most
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Airborne particulate matter (PM) is of great concern in the modern-day atmosphere owing to its association with a variety of health impacts, such as respiratory and cardiovascular diseases. Of the various size fractions of PM, it is the finer fractions that are most harmful to health, in particular ultrafine particles (PM0.1; UFPs), with an aerodynamic diameter ≤ 100 nm. The smaller size fractions, of ≤2.5 µm (PM2.5; fine particles) and ≤0.1 µm (PM0.1; ultrafine particles), have been shown to have numerous linkages to negative health effects; however, their collection/sampling remains challenging. This review paper employed a comprehensive literature review methodology; 200 studies were evaluated based on the rigor of their methodologies, including the validity of experimental designs, data collection methods, and statistical analyses. Studies with robust methodologies were prioritised for inclusion. This review paper critically assesses the health risks associated with fine and ultrafine particles, highlighting vehicular emissions as the most significant source of particulate-related health effects. While coal combustion, diesel exhaust, household wood combustors’ emissions, and Earth’s crust dust also pose health risks, evidence suggests that exposure to particulates from vehicular emissions has the greatest impact on human health due to their widespread distribution and contribution to air pollution-related diseases. This article comprehensively examines current sampling technologies, specifically focusing on the collection and sampling of ultrafine particles (UFP) from ambient air to facilitate toxicological and physiochemical characterisation efforts. This article discusses diverse approaches to collect fine and ultrafine particulates, along with experimental endeavours to assess ultrafine particle concentrations across various microenvironments. Following meticulous evaluation of sampling techniques, high-volume air samplers such as the Chem Vol Model 2400 High Volume Cascade Impactor and low-volume samplers like the Personal Cascade Impactor Sampler (PCIS) emerge as effective methods. These techniques offer advantages in particle size fractionation, collection efficiency, and adaptability to different sampling environments, positioning them as valuable tools for precise characterisation of particulate matter in air quality research and environmental monitoring.
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With the increasing dissemination of the Internet of Things and 5G, mobile edge computing has become a novel scheme to assist terminal devices in executing computation tasks. To elevate the coverage and computation capability of edge computing, a collaborative computation offloading and resource
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With the increasing dissemination of the Internet of Things and 5G, mobile edge computing has become a novel scheme to assist terminal devices in executing computation tasks. To elevate the coverage and computation capability of edge computing, a collaborative computation offloading and resource management architecture was proposed in space–air–ground integrated networking (SAGIN). In this manuscript, we established a novel model considering the computation offloading cost constraints of the communication, computing and cache model in the SAGIN. To be specific, the joint optimization problem of collaborative computation offloading and resource management was modeled as a mixed integer nonlinear programming problem. To address this issue, this paper proposed a computation offloading and resource allocation strategy based on deep reinforcement learning (DRL). Differing from traditional methods, DRL does not need a well-established formulation or previous information, and it is capable of revising the strategy adaptively according to the environment. The simulation results demonstrate the proposed approach can achieve the optimal reward values in the case of different terminal device numbers. Furthermore, this manuscript provided the analysis with variant parameters of the proposed approach.
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Given its detrimental effect on the brain, alcoholism is a severe disorder that can produce a variety of cognitive, emotional, and behavioral issues. Alcoholism is typically diagnosed using the CAGE assessment approach, which has drawbacks such as being lengthy, prone to mistakes, and
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Given its detrimental effect on the brain, alcoholism is a severe disorder that can produce a variety of cognitive, emotional, and behavioral issues. Alcoholism is typically diagnosed using the CAGE assessment approach, which has drawbacks such as being lengthy, prone to mistakes, and biased. To overcome these issues, this paper introduces a novel paradigm for identifying alcoholism by employing electroencephalogram (EEG) signals. The proposed framework is divided into various steps. To begin, interference and artifacts in the EEG data are removed using a multiscale principal component analysis procedure. This cleaning procedure contributes to information quality improvement. Second, an innovative graphical technique based on fast fractional Fourier transform coefficients is devised to visualize the chaotic character and complexities of the EEG signals. This elucidates the properties of regular and alcoholic EEG signals. Third, thirty-four graphical features are extracted to interpret the EEG signals’ haphazard behavior and differentiate between regular and alcoholic trends. Fourth, we propose an ensembled feature selection method for obtaining an effective and reliable feature group. Following that, we study many neural network classifiers to choose the optimal classifier for building an efficient framework. The experimental findings show that the suggested method obtains the best classification performance by employing a recurrent neural network (RNN), with 97.5% accuracy, 96.7% sensitivity, and 98.3% specificity for the sixteen selected features. The proposed framework can aid physicians, businesses, and product designers to develop a real-time system.
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This study introduces the concept of urban rainwater system vulnerability and identifies the indicator factors that affect the vulnerability of rainwater systems. Using the analytic hierarchy process (AHP), an index system for the vulnerability assessment of the rainwater system was established, and a
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This study introduces the concept of urban rainwater system vulnerability and identifies the indicator factors that affect the vulnerability of rainwater systems. Using the analytic hierarchy process (AHP), an index system for the vulnerability assessment of the rainwater system was established, and a vulnerability assessment model for the rainwater system was constructed. By integrating vulnerability degree, recurrence period, and water depth of ponding, a vulnerability assessment framework for urban rainwater systems was developed. Taking a newly developed urban area in the Suzhou High-Tech Zone as an example, we calculated the vulnerability degree of the urban rainwater system in this area to be 0.6497, indicating a high level of vulnerability and poor system safety. When encountering rainfall with a recurrence period p > 5 years, the city is likely to experience severe waterlogging. Through the analysis and evaluation of the rainwater system’s vulnerability, while clarifying the current state of the rainwater system, it can provide a scientific reference basis for the system’s upgrade, transformation, and optimized operation and management. Although the selection of factors may not be entirely comprehensive, this method allows for adjustments based on the composition and operation of different rainwater systems.
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This paper discusses the development of rapid, reliable, and accurate polymerase chain reaction (PCR) assays for detecting opium poppy (Papaver somniferum L.) in food. Endpoint, quantitative, and digital PCRs were compared based on the amplification of a newly developed DNA marker targeting
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This paper discusses the development of rapid, reliable, and accurate polymerase chain reaction (PCR) assays for detecting opium poppy (Papaver somniferum L.) in food. Endpoint, quantitative, and digital PCRs were compared based on the amplification of a newly developed DNA marker targeting the NADPH-dependent codeinone reductase (COR) gene. Designed assays were shown to be highly specific and sensitive in discriminating opium poppy from other plant species, even in heat-treated and food samples. Digital PCR was the most sensitive, with a detection limit of up to 5 copies, i.e., approximately 14 pg of target DNA per reaction. Quantitative and digital PCR further allowed the quantification of opium poppy in up to 1.5 ng and 42 pg (15 copies) of target DNA in a sample, respectively. In addition, two duplex PCRs have been developed for the simultaneous detection of opium poppy DNA and representatives of (i) the Papaveraceae family or (ii) the Plantae kingdom. Finally, all designed assays were successfully applied for analysis of 15 commercial foodstuffs; two were suspected of being adulterated. The study results have an important impact on addressing food fraud and ensuring the safety and authenticity of food products. Beyond food adulteration, the study may also have significant implications for forensics and law enforcement.
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Nikolaos Polyzos, Beatriz H. Paschoalinotto, Tânia C. S. P. Pires, Mikel Añibarro-Ortega, Ricardo Calhelha, Isabel C. F. R. Ferreira, Maria Inês Dias, Lillian Barros and Spyridon A. Petropoulos
Horticulturae2024, 10(5), 479; https://doi.org/10.3390/horticulturae10050479 (registering DOI) - 07 May 2024
In the current study, the effects of drought stress on the growth and phytochemical profile of Scolymus hispanicus L. (a.k.a. golden thistle) were evaluated. Plants were treated with three irrigation regimes, e.g., plants that received only rainwater (Control; C), deficit irrigation (I1; 50%
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In the current study, the effects of drought stress on the growth and phytochemical profile of Scolymus hispanicus L. (a.k.a. golden thistle) were evaluated. Plants were treated with three irrigation regimes, e.g., plants that received only rainwater (Control; C), deficit irrigation (I1; 50% of field capacity (FC)), and full irrigation (Ι2; 100% of FC). The fresh weight of the rosette of leaves was not negatively impacted by deficit irrigation, whereas root development was severely restrained compared to control and I2 treatments. Drought stress conditions had a positive effect on the nutritional properties of the golden thistle since the treatments of control and deficit irrigation showed the highest content of macronutrients and energy. Oxalic acid was the richest organic acid, especially under the I1 regime. Similarly, α-tocopherol was the only identified vitamin E isoform, whose content was also doubled in I1 treatment. Raffinose, glucose, and sucrose were the most abundant free sugars in amounts that varied among the irrigation treatments, while the total and distinct free sugar content was the highest for the I1 treatment. The most abundant detected fatty acid compounds were α-linolenic acid, followed by palmitic and linoleic acid, with the highest amount being detected in C, I1, and I2 treatments, respectively. Flavonoids were the only class of polyphenols detected in golden thistle leaves, including mostly kaempferol and quercetin derivatives. The greatest antioxidant potency was shown for the control and I1 treatments (for OxHLIA and TBARS methods, respectively). The evaluated leaf samples recorded a varied antimicrobial effect for the different bacterial strains and fungi, whereas no cytotoxic, hepatotoxic, and anti-inflammatory effects against the tested cell lines were recorded. Finally, the mineral content of leaves was significantly affected by the irrigation regime, with Ca, Mg, Cu, and Zn being the highest for the I1 treatment, while the I2 treatment had the highest content of K, Fe, and Mn and the lowest Na content. In conclusion, deficit irrigation showed promising results since it improved the phytochemical content without compromising the fresh weight of leaves, and thus it could be suggested as a sustainable agronomic practice for producing high-added value products without significant constraints in growth development and yield parameters of golden thistle.
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In this work, we formalize the effect of mechanical shaking by using various forms of an externally exerted force, which may be constant or may be position-dependent, and we examine the changes in the potential energy surfaces that quantify the chemical reaction. We
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In this work, we formalize the effect of mechanical shaking by using various forms of an externally exerted force, which may be constant or may be position-dependent, and we examine the changes in the potential energy surfaces that quantify the chemical reaction. We use a simple toy model to model the potential energy surfaces of a chemical reaction, and we study the effect of a constant or position-dependent externally exerted force for various forms of the force. As we demonstrate, the effect of the force can be quite dramatic on the potential energy surfaces, which acquire new stationary points and new Newton trajectories that are distinct from the original ones that were obtained in the absence of mechanochemical effects. We also introduce a new approach to mechanochemical interactions, using a dynamical systems approach for the Newton trajectories. As we show, the dynamical system attractor properties of the trajectories in the phase space are identical to the stationary points of the potential energy surfaces, but the phase space contains much more information regarding the possible evolution of the chemical reaction—information that is quantified by the existence of unstable or saddle fixed points in the phase space. We also discuss how an experimental method for a suitable symmetric liquid solution substance might formalize the effect of shaking via various forms of external force, even in the form of an extended coordinate-dependent force matrix. This approach may experimentally quantify the Epstein effect of shaking in chemical solutions via mechanochemistry methods.
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Anna Michalska-Ciechanowska, Jessica Brzezowska, Krzysztof Lech, Klaudia Masztalerz, Malgorzata Korzeniowska, Aleksandra Zambrowicz and Marek Szoltysik
Foods2024, 13(10), 1433; https://doi.org/10.3390/foods13101433 (registering DOI) - 07 May 2024
The management of side streams from the food industry, especially oil and dairy by-products, has become an important issue linked to the European Commission’s recommendations for a circular economy. This study aimed to obtain sustainable food additives in the form of soluble-type powders
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The management of side streams from the food industry, especially oil and dairy by-products, has become an important issue linked to the European Commission’s recommendations for a circular economy. This study aimed to obtain sustainable food additives in the form of soluble-type powders composed of whey and recovered phenolics originating from sunflower seed cake. In order to valorise these di-blend products, the powders were characterised in terms of their physical, chemical, and sensory attributes. Based on the study findings, the addition of sunflower seed cake washouts (SSCWs) to whey (Wh) decreased the dry matter in the feed that affected the viscosity and drying yield. The addition of SSCWs did not have a significant effect on the physical properties of powders, except for colour. By-product management proposed in the study resulted in the production of nutritious and ready-to-use products in powder form with improved functional properties in terms of phenolic compounds and antioxidant capacity. The powders were sensorially appealing with a tangy sourness entwined with a delicate interplay of sweet and salty flavours, which can be easily incorporated into different types of foodstuffs.
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Energy efficiency is a principle of architectural design that reduces environmental impact. Generative design can offer alternative options to improve energy efficiency in buildings, but significant gaps exist in the application due to accessing complex knowledge. This study aimed to explore publications on
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Energy efficiency is a principle of architectural design that reduces environmental impact. Generative design can offer alternative options to improve energy efficiency in buildings, but significant gaps exist in the application due to accessing complex knowledge. This study aimed to explore publications on generative design and energy efficiency in buildings and identify generative methods for energy efficiency topics. This study conducted a systematic review using the PRISMA methodology in December 2023 by searching publications from databases including Scopus, Google Scholar, and Thai Journals Online. Descriptive analysis examined 34 articles, showing the publication year, source, and citations. Comparative qualitative and descriptive analysis identified generative methods. Publications are increasing over time, and further growth is expected related to the accessibility of computational design and practical applications. Tools and frameworks demonstrated reduced energy usage compared to prototypes or traditional design approaches. The most studied is thermal performance, which was reduced by 28%. Energy performance achieved up to a 23.30% reduction, followed by others and daylighting. In addition to single-topic studies, there are also studies with multiple topics. Evolutionary algorithms are standard. Parametric search strategies have increased. Exploration reveals rule-based and mixed methods. Machine learning and AI garner attention.
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To effectively reduce building energy consumption, a novel full fresh air system with a heat source tower (HST) and a borehole heat exchanger (BHE) was proposed for space cooling and dehumidification in this paper. The cooling system only adopts geothermal energy to produce
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To effectively reduce building energy consumption, a novel full fresh air system with a heat source tower (HST) and a borehole heat exchanger (BHE) was proposed for space cooling and dehumidification in this paper. The cooling system only adopts geothermal energy to produce dry and cold fresh air for space cooling and dehumidification through the BHE and HST, which has the advantage of non-condensate water compared to BHE systems integrated with a fan coil or chilled beam. Based on the established mathematical model of the cooling system, this paper analyzed the system characteristics, feasibility, operation strategy, energy performance, and cost-effectiveness of the proposed model in detail. The results show that the mathematical model has less than 10% error in estimating the system performance compared to the practical HST−BHE experimental set up. Under the specific boundary conditions, the cooling and dehumidification capacity of this system increases with the decrease in the air temperature, air moisture content, and inlet water temperature of the HST. The optimal cooling capacity and the system COP can be achieved when the air–water flow ratio is at 4:3. A case study was conducted in a residential building in Shenyang with an area of about 1800 m2. It was found that this system can fully meet the cooling and dehumidification demand in such a residential building. The operation strategy of the cooling system can be optimized by adjusting the air–water flow ratio from 4:3 to 3:2 during the early cooling season (7 June–1 July) and end cooling season (3 August–1 September). As a result, the average COP of the cooling system during the whole cooling season can be improved from 6.1 to 8.7. Compared with the air source heat pump (ASHP) and the ground source heat pump (GSHP) for space cooling, the proposed cooling system can achieve an energy saving rate of 123% and 26%, respectively. Considering that the BHE of the GSHP can be part of the proposed HST−BHE cooling system, the integration of the HST and GHSP for space cooling (and heating) is strongly recommended in actual applications.
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Concerns over sustainability have recently drawn more attention in a post-COVID-19 environment, particularly from developing countries. This heightened global awareness of sustainability highlights the importance of comprehending consumer behavior in purchasing green products. This study utilized an extended theory of planned behavior (TPB)
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Concerns over sustainability have recently drawn more attention in a post-COVID-19 environment, particularly from developing countries. This heightened global awareness of sustainability highlights the importance of comprehending consumer behavior in purchasing green products. This study utilized an extended theory of planned behavior (TPB) called the sustainability theory of planned behavior (STPB) to holistically assess the behavioral intention among green consumers in a particular developing country: the Philippines. Convenience sampling was used with 500 participants, and 54 modified questions were distributed online. Different factors, such as perceived environmental concern, perceived economic concern, perceived authority support, subjective norm, attitude, perceived behavioral control, customer perceived value, and purchasing intention, were assessed concurrently through the structural equation modeling (SEM) approach. Through this, it was discovered that all the STPB predictors were significant drivers affecting the consumers’ purchasing intention, with customer perceived value having the highest direct effect. Moreover, it was found that the relationship between perceived economic concern on subjective norms and perceived behavioral control was insignificant. Further implications and comparisons were made based on the results of the study. The study’s findings can be utilized to help policymakers and marketers devise strategies that will effectively encourage sustainability through targeted interventions and increased product awareness. The study has validated the integration of new constructs into the TPB, enhancing the predictive power of the proposed model for assessing the behavioral intention to purchase green products. Thus, the model construct can be applied and utilized to investigate other topics regarding sustainability.
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This study addresses the field of X-ray security screening and focuses on synthesising realistic X-ray images using advanced generative models. Insufficient training data in this area pose a major challenge, which we address through innovative data augmentation techniques. We utilise the power of
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This study addresses the field of X-ray security screening and focuses on synthesising realistic X-ray images using advanced generative models. Insufficient training data in this area pose a major challenge, which we address through innovative data augmentation techniques. We utilise the power of generative adversarial networks (GANs) and conditional GANs (cGANs), in particular the Pix2Pix and Pix2PixHD models, to investigate the generation of X-ray images from various inputs such as masks and edges. Our experiments conducted on a Korean dataset containing dangerous objects relevant to security screening show the effectiveness of these models in improving the quality and realism of image synthesis. Quantitative evaluations based on metrics such as PSNR, SSIM, LPIPS, FID, and FSIM, with scores of 19.93, 0.71, 0.12, 29.36, and 0.54, respectively, show the superiority of our strategy, especially when integrated with hybrid inputs containing both edges and masks. Overall, our results highlight the potential of advanced generative models to overcome the challenges of data scarcity in X-ray security screening and pave the way for more efficient and accurate inspection systems.
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The post-harvest phase of potato tuber dormancy and sprouting are essential in determining the economic value. The intricate transition from dormancy to active growth is influenced by multiple factors, including environmental factors, carbohydrate metabolism, and hormonal regulation. Well-established environmental factors such as temperature,
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The post-harvest phase of potato tuber dormancy and sprouting are essential in determining the economic value. The intricate transition from dormancy to active growth is influenced by multiple factors, including environmental factors, carbohydrate metabolism, and hormonal regulation. Well-established environmental factors such as temperature, humidity, and light play pivotal roles in these processes. However, recent research has expanded our understanding to encompass other novel influences such as magnetic fields, cold plasma treatment, and UV-C irradiation. Hormones like abscisic acid (ABA), gibberellic acid (GA), cytokinins (CK), auxin, and ethylene (ETH) act as crucial messengers, while brassinosteroids (BRs) have emerged as key modulators of potato tuber sprouting. In addition, jasmonates (JAs), strigolactones (SLs), and salicylic acid (SA) also regulate potato dormancy and sprouting. This review article delves into the intricate study of potato dormancy and sprouting, emphasizing the impact of environmental conditions, carbohydrate metabolism, and hormonal regulation. It explores how various environmental factors affect dormancy and sprouting processes. Additionally, it highlights the role of carbohydrates in potato tuber sprouting and the intricate hormonal interplay, particularly the role of BRs. This review underscores the complexity of these interactions and their importance in optimizing potato dormancy and sprouting for agricultural practices.
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One of the key driving factors for achieving the goal of sustainable economic development is to ensure decent employment opportunities. This article explores the relationship between industrial intelligence and sustainable development in China from the perspective of employment. Based on interprovincial panel data
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One of the key driving factors for achieving the goal of sustainable economic development is to ensure decent employment opportunities. This article explores the relationship between industrial intelligence and sustainable development in China from the perspective of employment. Based on interprovincial panel data from 2006 to 2019, using the fixed-effect regression model and mediating-effect regression model, this study empirically tests the impact of industrial intelligence on sustainable employment in China. The following conclusions are drawn: (1) Industrial intelligence has a significant positive impact on the overall scale of employment. Industrial intelligence has promoted the optimization and upgrading of employment skill structure and industrial structure. Industrial intelligence will reduce the employment proportion of low-skilled labor and increase the employment proportion of medium-skilled labor and high-skilled labor. Industrial intelligence significantly reduces the employment share of the manufacturing sector and increases the employment share of the service sector. (2) Industrial intelligence reduces employment levels through capital deepening effects. Industrial intelligence has significantly improved regional labor productivity and significantly improved employment levels through productivity effects. (3) The results of regional heterogeneity show that industrial intelligence has promoted the improvement of employment level and the upgrading of employment structure in the eastern region but has not had a significant positive impact on other regions.
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Improving agricultural production relies on the decisions and actions of farmers and land managers, highlighting the importance of efficient soil monitoring techniques for better resource management and reduced environmental impacts. Despite considerable advancements in soil sensors, their traditional bulky counterparts cause difficulty in
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Improving agricultural production relies on the decisions and actions of farmers and land managers, highlighting the importance of efficient soil monitoring techniques for better resource management and reduced environmental impacts. Despite considerable advancements in soil sensors, their traditional bulky counterparts cause difficulty in widespread adoption and large-scale deployment. Printed electronics emerge as a promising technology, offering flexibility in device design, cost-effectiveness for mass production, and a compact footprint suitable for versatile deployment platforms. This review overviews how printed sensors are used in monitoring soil parameters through electrochemical sensing mechanisms, enabling direct measurement of nutrients, moisture content, pH value, and others. Notably, printed sensors address scalability and cost concerns in fabrication, making them suitable for deployment across large crop fields. Additionally, seamlessly integrating printed sensors with printed antenna units or traditional integrated circuits can facilitate comprehensive functionality for real-time data collection and communication. This real-time information empowers informed decision-making, optimizes resource management, and enhances crop yield. This review aims to provide a comprehensive overview of recent work related to printed electrochemical soil sensors, ultimately providing insight into future research directions that can enable widespread adoption of precision agriculture technologies.
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Alireza Jorkesh, Sylvia Rothenberger, Laura Baldassar, Birute Grybaite, Povilas Kavaliauskas, Vytautas Mickevicius, Monica Dettin, Filippo Vascon, Laura Cendron and Antonella Pasquato
Int. J. Mol. Sci.2024, 25(10), 5079; https://doi.org/10.3390/ijms25105079 (registering DOI) - 07 May 2024
SARS-CoV-2 is the pathogen responsible for the most recent global pandemic, which has claimed hundreds of thousands of victims worldwide. Despite remarkable efforts to develop an effective vaccine, concerns have been raised about the actual protection against novel variants. Thus, researchers are eager
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SARS-CoV-2 is the pathogen responsible for the most recent global pandemic, which has claimed hundreds of thousands of victims worldwide. Despite remarkable efforts to develop an effective vaccine, concerns have been raised about the actual protection against novel variants. Thus, researchers are eager to identify alternative strategies to fight against this pathogen. Like other opportunistic entities, a key step in the SARS-CoV-2 lifecycle is the maturation of the envelope glycoprotein at the RARR685↓ motif by the cellular enzyme Furin. Inhibition of this cleavage greatly affects viral propagation, thus representing an ideal drug target to contain infection. Importantly, no Furin-escape variants have ever been detected, suggesting that the pathogen cannot replace this protease by any means. Here, we designed a novel fluorogenic SARS-CoV-2-derived substrate to screen commercially available and custom-made libraries of small molecules for the identification of new Furin inhibitors. We found that a peptide substrate mimicking the cleavage site of the envelope glycoprotein of the Omicron variant (QTQTKSHRRAR-AMC) is a superior tool for screening Furin activity when compared to the commercially available Pyr-RTKR-AMC substrate. Using this setting, we identified promising novel compounds able to modulate Furin activity in vitro and suitable for interfering with SARS-CoV-2 maturation. In particular, we showed that 3-((5-((5-bromothiophen-2-yl)methylene)-4-oxo-4,5 dihydrothiazol-2-yl)(3-chloro-4-methylphenyl)amino)propanoic acid (P3, IC50 = 35 μM) may represent an attractive chemical scaffold for the development of more effective antiviral drugs via a mechanism of action that possibly implies the targeting of Furin secondary sites (exosites) rather than its canonical catalytic pocket. Overall, a SARS-CoV-2-derived peptide was investigated as a new substrate for in vitro high-throughput screening (HTS) of Furin inhibitors and allowed the identification of compound P3 as a promising hit with an innovative chemical scaffold. Given the key role of Furin in infection and the lack of any Food and Drug Administration (FDA)-approved Furin inhibitor, P3 represents an interesting antiviral candidate
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