Certain biomarkers in exhaled breath are indicators of diseases in the human body. The non-invasive detection of such biomarkers in human breath increases the demand for simple and cost-effective gas sensors to replace state-of-the-art gas chromatography (GC) machines. The use of metal oxide (MOX) gas sensors based on thin-film structures solves the current limitations of breath detectors. However, the response at high humidity levels, i.e., in the case of exhaled human breath, significantly decreases the sensitivity of MOX sensors, making it difficult to detect small traces of biomarkers. We have introduced, in previous work, the concept of a hybrid gas sensor, in which thin-film-based MOX gas sensors are combined with an ultra-thin (20–30 nm) polymer top layer deposited by solvent-free initiated chemical vapor deposition (iCVD). The hydrophobic top layer enables sensor measurement in high-humidity conditions as well as the precise tuning of selectivity and sensitivity. In this paper, we present a way to increase the hydrogen (H₂) sensitivity of hybrid sensors through chemical modification of the polymer top layer. A poly(1,3,5,7-tetramethyl-tetravinylcyclotetrasiloxane) (PV4D4) thin film, already applied in one of our previous studies, is transformed into a silsesquioxane-containing top layer by a simple heating step. The transformation results in a significant increase in the gas response for H₂ ~709% at an operating temperature of 350 °C, which we investigate based on the underlying sensing mechanism. These results reveal new pathways in the biomedical application field for the analysis of exhaled breath, where H₂ indicates gastrointestinal diseases. Full article

Neuroblastoma (NB), the most common cancer in infants and the most common solid tumor outside the brain in children, grows aggressively and responds poorly to current therapies. We have identified a new drug (opaganib, also known as ABC294640) that modulates sphingolipid metabolism by inhibiting the synthesis of sphingosine 1-phosphate (S1P) by sphingosine kinase-2 and elevating dihydroceramides by inhibition of dihydroceramide desaturase. The present studies sought to determine the potential therapeutic activity of opaganib in cell culture and xenograft models of NB. Cytotoxicity assays demonstrated that NB cells, including cells with amplified MYCN, are effectively killed by opaganib concentrations well below those that accumulate in tumors in vivo. Opaganib was shown to cause dose-dependent decreases in S1P and hexosylceramide levels in Neuro-2a cells, while concurrently elevating levels of dihydroceramides. As with other tumor cells, opaganib reduced c-Myc and Mcl-1 protein levels in Neuro-2a cells, and also reduced the expression of the N-Myc protein. The in vivo growth of xenografts of human SK-N-(BE)2 cells with amplified MYCN was suppressed by oral administration of opaganib at doses that are well tolerated in mice. Combining opaganib with temozolomide plus irinotecan, considered the backbone for therapy of relapsed or refractory NB, resulted in increased antitumor activity in vivo compared with temozolomide plus irinotecan or opaganib alone. Mice did not lose additional weight when opaganib was combined with temozolomide plus irinotecan, indicating that the combination is well tolerated. Opaganib has additive antitumor activity toward Neuro-2a tumors when combined with the checkpoint inhibitor anti-CTLA-4 antibody; however, the combination of opaganib with anti-PD-1 or anti-PD-L1 antibodies did not provide increased antitumor activity over that seen with opaganib alone. Overall, the data demonstrate that opaganib modulates sphingolipid metabolism and intracellular signaling in NB cells and inhibits NB tumor growth alone and in combination with other anticancer drugs. Amplified MYCN does not confer resistance to opaganib, and, in fact, the drug attenuates the expression of both c-Myc and N-Myc. The safety of opaganib has been established in clinical trials with adults with advanced cancer or severe COVID-19, and so opaganib has excellent potential for treating patients with NB, particularly in combination with temozolomide and irinotecan or anti-CTLA-4 antibody. Full article

Dioscorea alata, commonly known as “greater yam”, is a vital crop in tropical and subtropical regions of the world, yet it faces significant threats from anthracnose disease, mainly caused by Colletotrichum gloeosporioides. However, exploring disease resistance genes in this species has been challenging due to the difficulty of genetic mapping resulting from the loss of the flowering trait in many varieties. The receptor-like kinase (RLK) gene family represents essential immune receptors in plants. In this study, genomic analysis revealed 467 RLK genes in D. alata. The identified RLKs were distributed unevenly across chromosomes, likely due to tandem duplication events. However, a considerable number of ancient whole-genome or segmental duplications dating back over 100 million years contributed to the diversity of RLK genes. Phylogenetic analysis unveiled at least 356 ancient RLK lineages in the common ancestor of Dioscoreaceae, which differentially inherited and expanded to form the current RLK profiles of D. alata and its relatives. The analysis of cis-regulatory elements indicated the involvement of RLK genes in diverse stress responses. Transcriptome analysis identified RLKs that were up-regulated in response to C. gloeosporioides infection, suggesting their potential role in resisting anthracnose disease. These findings provide novel insights into the evolution of RLK genes in D. alata and their potential contribution to disease resistance. Full article

Cellular slime molds are excellent model organisms in the field of cell and developmental biology because of their simple developmental patterns. During our studies on the identification of bioactive molecules from secondary metabolites of cellular slime molds toward the development of novel pharmaceuticals, we revealed the structural diversity of secondary metabolites. Cellular slime molds grow by feeding on bacteria, such as Klebsiella aerogenes and Escherichia coli, without using medium components. Although changing the feeding bacteria is expected to affect dramatically the secondary metabolite production, the effect of the feeding bacteria on the production of secondary metabolites is not known. Herein, we report the isolation and structure elucidation of clavapyrone (1) from Dictyostelium clavatum, intermedipyrone (2) from D. magnum, and magnumiol (3) from D. intermedium. These compounds are not obtained from usual cultural conditions with Klebsiella aerogenes but obtained from coincubated conditions with Pseudomonas spp. The results demonstrate the diversity of the secondary metabolites of cellular slime molds and suggest that widening the range of feeding bacteria for cellular slime molds would increase their application potential in drug discovery. Full article

Through the analysis of various typical cases, this study examines whether the establishment of an agro-product regional public brand (ARPB) can effectively boost the revenue of farmers and increase their share in the supply chain. The findings suggest that an early-stage ARPB can command a price premium for products, yet its overall contribution to farmers’ revenue remains limited due to scale constraints. The premium ability of an ARPB is influenced by product characteristics and sales strategies, underscoring the need to enhance control over terminal sales. Although the revenue of all operators in an ARPB supply chain shows an increase compared to that of a non-ARPB supply chain, the ratios of revenue allocated to farmers diminish. The Shapley value method was utilized to optimize the revenue-sharing in the supply chain, indicating a need to increase the share of revenue for farmers. This optimization necessitates the formation of a community of interests between farmers, processing enterprises, and sellers to facilitate the upstream movement of brand premiums. Furthermore, enhancing the government’s mediation and regulatory functions can provide farmers with more opportunities to partake in brand benefits. Full article

Richter transformation is a rare phenomenon characterized by the transformation of cell chronic lymphocytic leukemia (CLL) into a more aggressive lymphoma variant. The early identification of CLLs with a high risk of RT is fundamental. In this field, 2-deoxy-2-[¹⁸F]-fluoro-D-glucose positron emission tomography/computed tomography (2-[¹⁸F]FDG PET/CT) has been shown to be a non-invasive and promising tool, but apparently, unclear data seem to be present in the literature. This systematic review and bivariate meta-analysis aimed to investigate the diagnostic performance of 2-[¹⁸F]FDG PET/CT and its parameters in predicting RT. Between 2006 and 2024, 15 studies were published on this topic, including 1593 CLL patients. Among semiquantitative variables, SUVmax was the most investigated, and the best threshold derived for detecting RT was five. With this cut-off value, a pooled sensitivity of 86.8% (95%CI: 78.5–93.3), a pooled specificity of 48.1% (95%CI: 27–69.9), a pooled negative predictive value of 90.5% (95%CI: 88.4–92.4), a pooled negative likelihood ratio of 0.35 (95%CI: 0.17–0.70), a pooled positive likelihood ratio of 1.8 (95%CI: 1.3–2.4), and a pooled diagnostic odds ratio of 6.7 (3.5–12.5) were obtained. With a higher cut-off (SUVmax = 10), the specificity increased while the sensitivity reduced. The other metabolic features, like metabolic tumor volume, total lesion glycolysis, and radiomic features, were only marginally investigated with controversial evidence. Full article

In large-scale wind farms, the voltage fluctuations caused by the uncertainty of wind speed at the turbine terminals pose a pressing challenge. This article presents a localized voltage control strategy tailored toward rapid adjustments in turbine terminal voltage in wind turbine generators. Based on relative voltage observation, this strategy achieves voltage coordination between the high and low ends of the transformer in wind turbine generators. Firstly, the overall structure of the wind farm and the characteristics of terminal voltage are analyzed. Secondly, the principles and feasibility of the relative voltage control strategy are examined. Finally, the effectiveness of the proposed control strategy is validated through simulation results from a specific wind farm. The results demonstrate its capability to achieve a fast and stable voltage dynamic response within the wind farm based on local information, thus mitigating the risk of voltage out of limit. Full article

The $H_2{O}_2$-assisted oxidation by a peroxidase enzyme takes place to help plants maintain the concentrations of organic compounds at physiological levels. Cells regulate the oxidation rate by inhibiting the action of this enzyme. The cells use two inhibitory processes to regulate the enzyme: a noncompetitive substrate inhibitory process and a competitive substrate inhibitory process. Numerous applications of peroxidase have been developed in clinical biochemistry, enzyme immunoassays, the treatment of waste water containing phenolic compounds, the synthesis of various aromatic chemicals, and the removal of peroxide from industrial wastes. The kinetic mechanism of the Spanish broom peroxidase enzyme is a Ping Pong Bi Bi mechanism with the presence of competitive inhibition by substrates. A mathematical model may help in identifying the key mechanism from amongst a set of competing mechanisms. In this study, we developed a fractional mathematical model to describe the $H_2{O}_2$-supported oxidation by the enzyme Spanish broom peroxidase. Numerical simulations of the model produced results that are consistent with the known behaviour of Spanish broom peroxidase. Finally, some future investigations of the study are briefly indicated as well. Full article

In this paper, an improved complex-valued convolutional neural network (CvCNN) structure to be placed at the received side is proposed for nonlinearity compensation in a coherent optical system. This complex-valued global convolutional kernel-assisted convolutional neural network equalizer (CvGNN) has been verified in terms of Q-factor performance and complexity compared to seven other related nonlinear equalizers based on both the 64 QAM experimental platform and the QPSK numerical platform. The global convolution operation of the proposed CvGNN is more suitable for the calculation process of perturbation coefficients, and the global receptive field can also be more effective at extracting effective information from perturbation feature maps. The introduction of CvCNN can directly focus on the complex-valued perturbation feature maps themselves without separately processing the real and imaginary parts, which is more in line with the waveform-dependent physical characteristics of optical signals. Based on the experimental platform, compared with the real-valued neural network with small convolutional kernel (RvCNNC), the proposed CvGNNC improves the Q-factor by ∼2.95 dB at the optimal transmission power, while reducing the time complexity by ∼44.7%. Full article

With the continuous advancement of autonomous driving and monitoring technologies, there is increasing attention on non-intrusive target monitoring and recognition. This paper proposes an ArcFace SE-attention model-agnostic meta-learning approach (AS-MAML) by integrating attention mechanisms into residual networks for pedestrian gait recognition using frequency-modulated continuous-wave (FMCW) millimeter-wave radar through meta-learning. We enhance the feature extraction capability of the base network using channel attention mechanisms and integrate the additive angular margin loss function (ArcFace loss) into the inner loop of MAML to constrain inner loop optimization and improve radar discrimination. Then, this network is used to classify small-sample micro-Doppler images obtained from millimeter-wave radar as the data source for pose recognition. Experimental tests were conducted on pose estimation and image classification tasks. The results demonstrate significant detection and recognition performance, with an accuracy of 94.5%, accompanied by a 95% confidence interval. Additionally, on the open-source dataset DIAT-μRadHAR, which is specially processed to increase classification difficulty, the network achieves a classification accuracy of 85.9%. Full article

Reproductive success is an important aspect of marine mammals’ population health, as it is an indicator of the trajectory for the population into the future. The aim of this study is to provide additional relevant data on fetus–maternal ultrasonographic monitoring in sea lion species, in order to evaluate possible fetal distress or abnormalities. From 2018 to 2023, serial ultrasonographic scans of two healthy California sea lion females (16 ± 4 years old), kept under human care, were performed over the course of two pregnancies for each female. Animals were monitored from the ovulation to the delivery. Ultrasonography was performed weekly, and, during the last month, daily images were recorded using Logiq Versana Active, General Electric, with a 2–5 MHz curvilinear transducer, and Logiq V2, General Electric, with a 2–5 MHz curvilinear transducer. Right and left lateral recumbencies have been used during the examination. To the author’s knowledge, this is the first study describing in detail the sea lion organogenesis and their correlation with the stage of pregnancy. Full article

I deduce an exact and analytic Bianchi type I solution of Einstein’s field equations, which generalizes the isotropic ΛCDM universe model to a corresponding model with anisotropic expansion. The main point of the article is to present the anisotropic generalization of the ΛCDM universe model in a way suitable for investigating how anisotropic expansion modifies observable properties of the ΛCDM universe model. Although such generalizations of the isotropic ΛCDM universe model have been considered earlier, they have never been presented in this form before. Several physical properties of the model are pointed out and compared with properties of special cases, such as the isotropic ΛCDM universe model. The solution is then used to investigate the Hubble tension. It has recently been suggested that the cosmic large-scale anisotropy may solve the Hubble tension. I consider those earlier suggestions and find that the formulae of these papers lead to the result that the anisotropy of the cosmic expansion is too small to solve the Hubble tension. Then, I investigate the problem in a new way, using the exact solution of the field equations. This gives the result that the cosmic expansion anisotropy is still too small to solve the Hubble tension in the general Bianchi type I universe with dust and LIVE (Lorentz Invariant Vacuum Energy with a constant energy density, which is represented by the cosmological constant) and anisotropic expansion in all three directions—even if one neglects the constraints coming from the requirement that the anisotropy should be sufficiently small so that it does not have any significant effect upon the results coming from the calculations of the comic nucleosynthesis during the first ten minutes of the universe. If this constraint is taken into account, the cosmic expansion anisotropy is much too small to solve the Hubble tension. Full article

This article aims to provide a comprehensive review of the latest advancements in numerical methods and practical implementations in the field of fractional stochastic partial differential equations (FSPDEs). This type of equation integrates fractional calculus, stochastic processes, and differential equations to model complex dynamical systems characterized by memory and randomness. It introduces the foundational concepts and definitions essential for understanding FSPDEs, followed by a comprehensive review of the diverse numerical methods and analytical techniques developed to tackle these equations. Then, this article highlights the significant expansion in numerical methods, such as spectral and finite element methods, aimed at solving FSPDEs, underscoring their potential for innovative applications across various disciplines. Full article

Poor sleep quality, a global public health concern, poses a significant burden on individuals, particularly health care university students facing intense academic stress. A three-center cross-sectional study was conducted at the Higher Institute of Nursing and Health Sciences in Tetouan (Morocco), Faculty of Medicine in Tangier (Morocco) and Faculty of Nursing in Valencia (Spain). We collected various data using a sociodemographic questionnaire, the Pittsburgh sleep quality questionnaire, the international physical activity questionnaire (IPAQ) and the smartphone addiction questionnaire short-version (SAS-SV). A total of 1210 students were included in our study (mean age 20.4 years, 67.2% female, nursing students (66.2%) and medical students (33.8%), 76.1% students from Morocco and 33.9% from Spain). Analysis revealed a higher prevalence of poor sleep quality among Moroccans students compared to Spanish ones (p < 0.001), that nursing students showed less favorable sleep quality than medical students (p < 0.011) and that living with a chronic disease was linked to less favorable sleep quality (p < 0.001). Lastly, intense or weak physical activity and smartphone addiction were correlated with poor sleep quality (p < 0.001). In the multivariate analysis, an association persisted between poor sleep quality and factors such as the country of study (Odds ratio (OR): 6.25 [95% Confidence Interval (CI): 4.34–9.09]), involvement in nursing studies (OR: 3.50 [95% CI: 2.36–5.27]), and the presence of chronic diseases (OR: 2.70 [95% CI: 1.72–4.16]), (p < 0.01 each). Our findings highlight the multifaceted factors affecting sleep quality in young university students. The implications underscore the imperative of interventions tailored to this demographic group. Full article

Myocardial protection has become an essential adjunctive procedure in veterinary cardiac surgery. Del Nido cardioplegia is a good alternative to the traditional St. Thomas II (ST) cardioplegia in open heart surgery in humans. This study aims to compare intra- and postoperative results between ST cardioplegia and modified del Nido (mDN) cardioplegia in mitral valve surgery in dogs with myxomatous mitral valve disease (MMVD). This retrospective study was conducted using clinical records of 16 MMVD dogs that underwent either ST or mDN cardioplegia. We measured cardiopulmonary bypass (CPB) time, aortic cross-clamp (ACC) time, total operation time, the number of cardioplegia doses, total amount of cardioplegia, required defibrillations, in-hospital mortality and pre- and one-month postoperative echocardiographic variables. CPB (159.4 ± 16.1 vs. 210.1 ± 34.0 min), ACC (101.4 ± 7.0 vs. 136.0 ± 24.8 min) and total operation time (262.3 ± 13.1 vs. 327.0 ± 45.4 min) were significantly shorter in the mDN group (p < 0.05). The number of cardioplegia doses (3.25 ± 0.4 vs. 6.25 ± 1.2) and total amount of cardioplegia (161.3 ± 51.5 vs. 405.0 ± 185.9 mL) in the mDN group were also significantly smaller than the ST group (p < 0.05). No difference was observed in the requirement of defibrillation, in-hospital mortality and pre- and postoperative echocardiographic variables. The utilization of mDN cardioplegia was associated with shorter operative time in mitral valve surgery in dogs. Full article

This study investigates the application of steganography for enhancing network security by detecting and promptly eliminating malicious packets to prevent flooding and consequent denial of service attacks while also identifying malicious equipment. The paper discusses foundational concepts such as the prisoner’s dilemma, covert channels, qualitative metrics, and existing steganography techniques in computer communications. An architecture was developed to assess the effectiveness of this solution, and experiments were conducted, with their results presented. This contribution leverages established steganographic principles and seamlessly integrates with widely adopted IPsec protocols, offering a solution to improve covert communication within computer networks. Full article

Palm kernel cake (PKC), a byproduct of palm oil extraction, serves an important role in Ecuador’s animal feed industry. The emergence of yellow-orange fungal growth in PKC on some cattle farms in Ecuador sparked concerns within the cattle industry regarding a potential mycotoxin-producing fungus on this substrate. Due to the limited availability of analytical chemistry techniques in Ecuador for mycotoxin detection, we chose to isolate and identify the fungus to determine its association with mycotoxin-producing genera. Through molecular identification via ITS region sequencing, we identified the yellow-orange fungus as the yeast Candida ethanolica. Furthermore, we isolated two other fungi—the yeast Pichia kudriavzevii, and the fungus Geotrichum candidum. Molecular identification confirmed that all three species are not classified as mycotoxin-producing fungi but in contrast, the literature indicates that all three have demonstrated antifungal activity against Aspergillus and Penicillium species, genera associated with mycotoxin production. This suggests their potential use in biocontrol to counter the colonization of harmful fungi. We discuss preventive measures against the fungal invasion of PKC and emphasize the importance of promptly identifying fungi on this substrate. Rapid recognition of mycotoxin-producing and pathogenic genera holds the promise of mitigating cattle intoxication and the dissemination of mycotoxins throughout the food chain. Full article

Managing cellular networks in the Beyond 5G (B5G) era is a complex and challenging task requiring advanced deep learning approaches. Traditional models focusing on internet traffic (INT) analysis often fail to capture the rich temporal and spatial contexts essential for accurate INT predictions. Furthermore, these models do not account for the influence of external factors such as weather, news, and social trends. This study proposes a multi-source CNN-RNN (MSCR) model that leverages a rich dataset, including periodic, weather, news, and social data to address these limitations. This model enables the capture and fusion of diverse data sources for improved INT prediction accuracy. An advanced deep learning model, the transformer-enhanced CNN-RNN (TE-CNN-RNN), has been introduced. This model is specifically designed to predict INT data only. This model demonstrates the effectiveness of transformers in extracting detailed temporal-spatial features, outperforming conventional CNN-RNN models. The experimental results demonstrate that the proposed MSCR and TE-CNN-RNN models outperform existing state-of-the-art models for traffic forecasting. These findings underscore the transformative power of transformers for capturing intricate temporal-spatial features and the importance of multi-source data and deep learning techniques for optimizing cell site management in the B5G era. Full article

Leasing has proven to be a business model that is perfectly suited to the circular economy. It significantly contributes to sustainable development by enabling the reuse of machinery and equipment after each lease period and by including preventive maintenance and overhauls within and between lease terms. This helps to extend the life cycle of equipment, promote value recovery, and reduce waste. This paper examines an imperfect preventive maintenance (PM) strategy applied to equipment rented under the terms of “free leasing.” In free leasing, the lessor makes the equipment available to the customer for a specified period of time without charging rent. In return, the customer is required to purchase the equipment’s consumables exclusively from the lessor. The lessor is also responsible for the maintenance of the equipment at the customer’s premises. The greater the quantity of consumables used by the customer, the more the equipment will deteriorate. Consequently, the lessor must be able to determine the most effective approach to preventive maintenance, ensuring that it aligns with the customer’s planned usage rate while maximizing profit. This work proposes a PM strategy to be adopted by the lessor during the free lease period. This strategy involves the performance of imperfect PM actions just before the start of the lease period and then periodically. Different packages of preventive actions can be applied each time, with each package having a different cost depending on the level of effectiveness in terms of rejuvenating the equipment. Minimal repairs are performed in the event of equipment failure. The decision variables are the PM period to be adopted and the maintenance efficiency level to be chosen for each preventive intervention. The objective is to determine, for a given customer with an estimated consumption rate profile of consumables, the optimal values of these decision variables so that the lessor maximizes their profit. A mathematical model is developed to express the lessor’s average profit over each lease period. A solution procedure is developed for small instances of the problem, and an Artificial Bee Colony algorithm is implemented for larger instances. A numerical example and a sensitivity analysis are presented. Full article

In this study, we investigated the catalytic properties of mono- and bimetallic palladium (Pd) and platinum (Pt) nanoparticles deposited via supercritical fluid reactive deposition (SFRD) on titanium dioxide (TiO₂) powder. Transmission electron microscopy analyses verified that SFRD experiments performed at 353 K and 15.6 MPa enabled the deposition of uniform mono- and bimetallic nanoparticles smaller than 3 nm on TiO₂. Electron-dispersive X-ray spectroscopy demonstrated the formation of alloy-type structures for the bimetallic PdPt nanoparticles. H₂O₂ is an excellent oxidizing reagent for the production of fine and bulk chemicals. However, until today, the design and preparation of catalysts with high H₂O₂ selectivity and productivity remain a great challenge. The focus of this study was on answering the questions of (a) whether the catalysts produced are suitable for the direct synthesis of hydrogen peroxide (H₂O₂) in the liquid phase and (b) how the metal type affects the catalytic properties. It was found that the metal type (Pd or Pt) influenced the catalytic performance strongly; the mean productivity of the mono- and bimetallic catalysts decreased in the following order: Pd > PdPt > Pt. Furthermore, all catalysts prepared by SFRD showed a significantly higher mean productivity compared to the catalyst prepared by incipient wetness impregnation. Full article

To explore the impact of shade treatment on grape berries, ‘Marselan’ grape berries were bagged under different light transmission rates (100% (CK), 75% (A), 50% (B), 25% (C), 0% (D)). It was observed that this treatment delayed the ripening of the grape berries. The individual weight of the grape berries, as well as the content of fructose, glucose, soluble sugars, and organic acids in the berries, was measured at 90, 100, and 125 days after flowering (DAF90, DAF100, DAF125). The results revealed that shading treatment reduced the sugar content in grape berries; the levels of fructose and glucose were higher in the CK treatment compared to the other treatments, and they increased with the duration of the shading treatment. Conversely, the sucrose content exhibited the opposite trend. Additionally, as the weight of the grape berries increased, the content of soluble solids and soluble sugars in the berries also increased, while the titratable acidity decreased. Furthermore, 16 differentially expressed genes (DEGs) were identified in the photosynthesis-antenna protein pathway from the transcriptome sequencing data. Correlation analysis revealed that the expression levels of genes VIT_08s0007g02190 (Lhcb4) and VIT_15s0024g00040 (Lhca3) were positively correlated with sugar content in the berries at DAF100, but negatively correlated at DAF125. qRT-PCR results confirmed the correlation analysis. This indicates that shading grape clusters inhibits the expression of genes in the photosynthesis-antenna protein pathway in the grape berries, leading to a decrease in sugar content. This finding contributes to a deeper understanding of the impact mechanisms of grape cluster shading on berry quality, providing important scientific grounds for improving grape berry quality. Full article

For the most popular method of scan formation in Optical Coherence Tomography (OCT) based on plane-parallel scanning of the illuminating beam, we present a compact but rigorous K-space description in which the spectral representation is used to describe both the axial and lateral structure of the illuminating/received OCT signals. Along with the majority of descriptions of OCT-image formation, the discussed approach relies on the basic principle of OCT operation, in which ballistic backscattering of the illuminating light is assumed. This single-scattering assumption is the main limitation, whereas in other aspects, the presented approach is rather general. In particular, it is applicable to arbitrary beam shapes without the need for paraxial approximation or the assumption of Gaussian beams. The main result of this study is the use of the proposed K-space description to analytically derive a filtering function that allows one to digitally transform the initial 3D set of complex-valued OCT data into a desired (target) dataset of a rather general form. An essential feature of the proposed filtering procedures is the utilization of both phase and amplitude transformations, unlike conventionally discussed phase-only transformations. To illustrate the efficiency and generality of the proposed filtering function, the latter is applied to the mutual transformation of non-Gaussian beams and to the digital elimination of arbitrary aberrations at the illuminating/receiving aperture. As another example, in addition to the conventionally discussed digital refocusing enabling depth-independent lateral resolution the same as in the physical focus, we use the derived filtering function to perform digital “super-refocusing.” The latter does not yet overcome the diffraction limit but readily enables lateral resolution several times better than in the initial physical focus. Full article