The aging ability of dry white wines has been increasingly recognised. The present work aimed to understand which sensory factors drive their quality evaluation by experienced tasters. Individuals assessed several aesthetic, synthetic, and analytic flavour attributes, using dark tasting glasses. Wines originated from the grape varieties Alvarinho, Arinto, Sauvignon Blanc and Pinot Bianco with a wide range of ages. Basic physical-chemical analysis, browning (Abs 420 nm), elemental composition and a partial volatile fraction were also determined. The overall quality scores were a function of complexity and balance and were negatively influenced by the perception of faultiness. The different ages could be associated with a continuous sensory space characterised by a decreasing perception of freshness and an increase in the mellowed flavours. All wines shared an austere in-mouth perception elicited by their acidity, saltiness, bitterness, smoothness and dryness. Nevertheless, quality scores were similar from the youngest to the oldest-tasted wines (17 years old). The exception was a Sauvignon Blanc wine from a recent vintage that was judged as faulty due to the perception of earthiness. Overall, the tasted wines displayed an unexpected aging ability as demonstrated by the difference between the predicted and real wine ages. To improve the recognition of old wines, the metaphor “mellowed by age” is proposed to describe flavours resulting from beneficial aging instead of “oxidised by age”.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Plant cells' ability to withstand abiotic stress is strongly linked to modifications in their mechanical characteristics. Nevertheless, the lack of a workable method for consistently tracking plant cell mechanical properties severely restricts our comprehension of the mechanical alterations in plant cells under stress. With Polyethylene Glycol (PEG6000), we created a drought-like environment, and we used the Double Resonator Piezoelectric Cytometry (DRPC) method to dynamically and non-invasively track changes in the stress (ΔS) created and viscoelasticity (storage modulus G' and loss modulus G") of protoplasts and suspension cells of rice during drought stress. The findings demonstrate that, rice suspension cells and protoplasts react mechanically differently to 5%–15% PEG6000 stress, implying distinct resistance mechanisms. However, neither of them can withstand 25% PEG6000 stress, they respond mechanically similarly to 25% PEG6000 stress. The results of DRPC are further corroborated by the morphological alterations of rice cells and protoplasts observed under an optical microscope. To sum up, the DRPC technique functions as a precise cellular mechanical sensor and offers novel research tools for the evaluation of plant cell adversity and differentiating between the mechanical reactions of cells and protoplasts under abiotic stress.

The popular appreciation of dry white wines is most frequently directed to young wines. However, present consumption trends comprise the valorisation of aged dry white wines. Therefore, the present work was aimed at the sensory analysis of these wines with different ages to define their sensory space and to understand which factors drive their quality evaluation by experienced tasters (critics, oenologists and students). Individuals were asked to evaluate several synthetic and aesthetic attributes and to characterise the analytic sensory profile through a Check-All-That-Apply (CATA) methodology. The quality evaluations were differently correlated with wine synthetic parameters according to the taster group. For both critics and oenologists, overall quality scores were driven by persistence and complexity. Moreover, quality was also highly correlated with power for critics and with balance for oenologists. Quality scores were highly correlated with wine browning (absorbance at 420 nm) for critics. The tasting panel showed a homogeneous analytic description of aroma, taste and mouthfeel consistent with wine age. The different ages could be associated to a continuous sensory space characterised by a decreasing perception of freshness and increase in mature and mellowed descriptors. All wines shared an austere in-mouth perception elicited by their acidity, saltiness, bitterness, smoothness and dryness. The age prediction showed that most tasters failed to guess the age wines with more than roughly 13 years old, indicating that tasters were not familiar with the sensory features of white wines with 17 to 46 years old. In conclusion, experienced tasters consistently described the sensory space and recognised the high quality of aged dry white wines. Education programs may use the defined sensory spaces according to aging and to expand the range of quality perception by consumers.

A two-year experiment was conducted with a local maize hybrid under full irrigation (F), deficit irrigation (D) and rainfed conditions (R) to estimate maize evapotranspiration in Bosnia and Herzegovina. Three approaches (Allen & Pereira (A&P), SIMDualKc (SD), and Vegetation Index (VI)) were used to estimate the actual crop coefficient (Kc act), actual basal crop coefficient (Kcb act), and actual crop evapotranspiration (ETc act) were applied with the dual crop coefficient method and remote sensing (RS) data. While Kcb act from all approaches matched FAO56 tabulated values, SD showed differences, in comparison to A&P, of up to 0.24 in D and R conditions, especially in initial and mid-season stages. VI demonstrated very good performance in all treatments. In F, the obtained Kc act for all approaches during the initial and end stages were higher than the tabulated values, ranging from 0.71-0.87 for Kc ini act and from 0.80-1.06 for Kc end act, while the mid-season period showed very good agreement with the literature. Maize crop evapotranspiration range is 769-813 mm, 480-752 mm, and 332-618 mm for F, D and R, respectively. The results confirmed the suitability of both approaches (SD and VI) to estimate maize crop evapotranspiration under F, with the VI approach demonstrating an advantage in calculating Kcb act, Kc act, and ETc act values under water stress conditions. The 67.6% increase in grain yields with irrigation emphasizes the need to transition from rainfed to irrigation-dependent agriculture, even for drought-resistant crops like maize.

Climate change related increases in frequency and intensity of heatwaves affect viticulture, leading to losses in yield and grape quality. We assessed whether canopy architecture manipulation mitigates the effects of summer stress in a Mediterranean vineyard. Muscat of Alexandria grapevines were monitored during 2019-2020. Two canopy shoot positioning treatments were applied: Vertical shoot positioning (VSP); and Modulated shoot positioning (MSP), the west side upper foliage released to promote partial shoot leaning, shading the clusters. Clusters were sampled at pea size (PS), veraison (VER) and full maturation (FM). Measurements included rachis anatomy and hydraulic conductance, and aquaporins (AQP) and stress-related genes expression in cluster tissues. Results show significant seasonal and interannual differences in Kh and vascular anatomy. At VER, Krachis , Krachis+pedicels, and xylem diameter decreased but were unaffected by treatments. The Phloem/Xylem ratio was either increased (2019) or reduced (2020) in MSP, compared to VSP. Most AQP were down-regulated at FM in pedicels, and up-regulated at VER in pulp. A potential maturation shift in MSP was observed, confirmed by the up-regulation of several stress-related genes in all tissues. The study pinpoints the role of canopy architecture in berry water relations and stress response during ripening.

The generation of forensic DNA profiles consisting of single nucleotide polymorphisms (SNPs) is now being facilitated by wider adoption of next-generation sequencing (NGS) methods in casework laboratories. At the same time, and in part because of this advance, there is an intense focus on the generation of SNP profiles from evidentiary specimens for so-called forensic or investigative genetic genealogy (FGG or IGG) applications. However, FGG methods are constrained by the algorithms for genealogical database searches, which were designed for use with single-source profiles, and the fact that many forensic samples are mixtures. To enable the use of two-person mixtures for FGG, we developed a workflow, MixDeR, for the deconvolution of mixed SNP profiles. MixDeR, a flexible and easy to use R package and Shiny app, processes ForenSeq Kintelligence® (QIAGEN, Inc.) SNP genotyping results and directs deconvolution of the profiles in EuroForMix (EFM). MixDeR then filters the EFM outputs to produce inferred single-source genotypes in reports formatted for use with GEDmatch® PRO. An optional MixDeR output includes metrics that assist with testing and validation of the workflow. As the Shiny app provides a graphical user interface and the software is designed to be run offline, MixDeR should be suitable for use by any laboratory developing FGG capabilities, no matter their bioinformatic resources or expertise.

In this study, we investigate the growth of EV ownership among Swedish households. Through detailed socio-economic data and the Swedish vehicle register, we are able compare characteristics of households that bought an EV in 2016 with those that became EV owners in 2020. We are thus able to describe and analyse the transition from the early EV owners to the early majority. Unlike many prior studies in the field, which are based on surveys or interviews, this study relies on registry data, thereby encompassing all car owners in Sweden. In this study, we have also scrutinized the significance of ownership mode by distinguishing between households that have chosen to purchase a car and those that have chosen to lease one. The results show that the demand for EVs has reached new consumer groups, e.g. both younger and older car buyers, and that the option to lease a car privately has broadened the market for new cars in general, and for EV’s in particular.

Regulation of the diet in terms of the content of soluble and insoluble fibre is of great importance from the point of view of dietetics, microbiology of the gastrointestinal tract and immunology of the organism. Dietary fibre plays an important role in maintaining the balance between the con-tinuity of gut mucus production (intestinal mucosa), the stability of the intestinal microbiome composition, the regeneration of the intestinal epithelium and the immune status within the gut-associated lymphoid tissue (GALT) are played by pectin and their metabolic products in the form of pectin oligosaccharides. The main purpose of this review was to focus on pectin, their functions, their impact on the human's health and on some of the most promising prebiotics due to their solubility in the gastrointestinal tract in the form of pectin oligosaccharides. They have the properties of pectin, but have also additional features and postbiotics obtained in fermentation process can affect the intestinal microbiome and GALT-related immunity. They can be obtained from plant agro-wastes.

The temperature variations caused by the climate changes taking place in the Basilicata region, southern Italy - Ionian Seaside of the Gulf of Taranto - on the territory of the DOP Matera vineyard, were studied by means of an analysis of temperature trends considering both the period of the vegetative-productive season of the vineyards and the whole year. Two datasets were analyzed for this study: data from ERA5-Land of the C3S Climate Data Store -relative to the 1981-2022 window- and data from 5 weather stations belonging to the agrometeorological network of the Lucanian Agency for Development and Innovation in Agriculture (SAL-ALSIA), relative to the 2000-2023 window. From the results of this study, it can be deduced that, for the historical period analyzed, the Matera DOP area showed a clear and worrying trend of increasing temperatures and, in par-ticular, minimum temperatures. This increase, moreover, is more evident at higher elevations than at lower elevations close to the sea. At lower altitudes, in fact, temperatures are strongly “buffered” by the thermoregulatory activity of the bordering Ionian Sea. It follows that the DOP Matera viticultural areas, and in particular the areas furthest from the coastal strip, will already have to adapt to severe climatic conditions that will undoubtedly affect the quality and typicality of the wines.

The paper presents the problem of damage detection in steel girders. Static displacements at the selected point of the structure play the role of measured variables. Structural response signal decomposition is performed according to the Mallat pyramid algorithm, which is used to perform the discrete wavelet transform (DWT). This procedure allows us to quite well determine the location of structural damage. The geometry and the placement of any defective part of the structure may have a random character. It can be assumed that the random processes occurring in the broadly understood structure mechanics are Gaussian in nature. The first four probabilistic moments are estimated using three approaches independent: semi-analytical (SAM), perturbative (SPT), and Monte-Carlo simulations (MCS). The semi-analytical random approach seems to be the most optimal due to the necessary computation time. The incorporation of the mathematical stochastic apparatus into the classical (deterministic) analysis of the statics of the structure makes it possible to estimate the reliability measures of the analyzed girder.

Previous high throughput screening studies indicated trans-eQTLs tend to be tissue specific. In this study, I probed if this feature can be used to identify tissue-specific gene regulatory networks. eQTL data (P<5e-8) for 16,259 genes were identified and their summary association statistics were obtained from the eQTLGen database. Next, eQTLs that display both cis and trans regulatory effects were selected and the association between their corresponding genes were examined by Mendelian randomization. 253 genes that exerted trans-regulatory impacts on 1,439 genes were identified. Majority of the identified gene-pairs aggregated into a gene regulatory network significantly enriched in hemo-immune processes. The robustness of finding was confirmed through simulation. Genes with higher gene expression heritabilities displayed broader regulatory impact in the network. The network displayed the scale-free topology, this provided the reason to examine the association of the network’s hub genes with the phenome. The outcome of analyses revealed GSDMB and ORMDL3 impact several disorders of immune origin and higher expression of HHEX is associated with lower triglycerides and risk of type 2 diabetes. This study reports trans-eQTLs can be used to identify tissue-specific gene regulatory networks and describes a workflow to achieve this purpose. The identified network displayed scale-free topology indicating the hub genes of a tissue-specific network could be targeted to prevent disease outcomes.

The effectiveness of a hybrid technique for identifying seismic damage in planar, multistory, steel X or V-braced frames is demonstrated here through an example of a six-story frame. This proposed technique, referred to as “M and P”, combines the instrumental Monitoring (M) with Pushover analysis (P). According to the methodology, the diagram of stepping eigenfrequencies of the frame in the inelastic region is initially plotted against seismic roof displacement. The fundamental natural frequency detected via the monitoring process is then utilized in this key diagram to reveal the inelastic roof displacement that corresponds to the damage state of the steel braced frame. This displacement is subsequently used as the target in the pushover analysis, facilitating the identification of seismic damage in the existing steel braced frame. Finally, the damage image is correlated with the damage stiffness matrix of the frame at the same inelastic roof displacement. The investigation results indicate that combining instrumental monitoring with pushover analysis enables accurate identification of seismic damage potential in existing steel braced frames.

Ferroptosis is a recently identified iron-dependent programmed cell death with lipid peroxides accumulation and condensation and compaction of the mitochondria. Recent study indicated that ferroptosis played a pivotal role in ischemic cardiac injury with the mechanisms remained largely unknown. This study demonstrated that iron overload occurred in the ischemia/reperfusion (I/R) cardiac tissues, which initiated myocardial ferroptosis. The expression levels of mitochondrial inner membrane protein MPV17 were reduced when ferroptosis occurred in cardiomyocytes treated with high levels of iron or in the ischemic cardiac tissues. Overexpression of MPV17 delivered via adenovirus significantly reduced ferroptosis in both cardiomyocytes subject to high levels of iron and cardiac I/R tissues. Mitochondrial glutathione (mtGSH), crucial for reactive oxygen species (ROS) scavenging and mitochondrial homeostasis maintenance, was depleted during myocardial ferroptosis caused by iron overload. The mechanistic study showed that MPV17 could increase mtGSH levels through maintaining the protein homeostasis of SLC25A10, which was a mitochondrial inner-membrane glutathione transporter. The absence of MPV17 during iron overload resulted in the ubiquitination-dependent degradation of SLC25A10, leading to impaired mitochondrial glutathione import. Moreover, we found that MPV17 was the targeted gene of Nrf2, which played a pivotal role in preventing lipid peroxides accumulation and ferroptosis. The decreased expression levels of Nrf2 led to the inactivation of MPV17 during iron overload-induced myocardial ferroptosis. In summary, this study demonstrated the critical role of MPV17 in protecting cardiomyocytes from ferroptosis and elucidated the Nrf2-MPV17-SLC25A10/mtGSH signaling pathway in the regulation of myocardial ferroptosis.

A new model for international bed numbers is applied to local area populations for English Clinical Commissioning Groups (CCGs) where the Age Standardized Mortality Rate (ASMR) is used as a measure of population health and hence for total occupied hospital bed demand (elective plus emergency admission types, including acute, rehabilitation, mental health, and maternity), rather than simple bed availability. A 100-unit increase in ASMR (European Standard population) leads to a 15.3 – 30.7 (feasible range) unit increase in occupied beds per 1,000 deaths. ASMR shows why the Australian states of the Northern Territory and Tasmania have an intrinsic higher bed demand than the other states – although in both cases the bed planning methodologies failed to indicate this need and both states show a large bed deficit. Due to the high volatility in bed demand the average bed demand for 2019 was determined by a linear trend using data for 2014/15 to 2019/20 — as the pre-COVID-19 baseline. The slope of the relationship between occupied beds per 1,000 deaths and deaths per 1,000 population shows a power law function. As is to be expected there is scatter around the trend line which will partly arise from uncertainty in the expected occupied beds in 2019, fluctuations in both ASMR and deaths per 1,000 population from one year to another, changes in the number of persons on the elective, outpatient and diagnostic waiting lists, and local area variation in births and consequently upon maternity, neonatal and pediatric bed demand. Additional variation in bed demand will arise from differences in the level of funding for social care, especially elderly care, and to a lesser extent upon patients using private health care, and charitable hospices for palliative care. However, after including the change in bed demand arising from ASMR the model is sufficiently accurate to identify gross differences in bed demand as a prelude to further investigation. The model requires further extension to cover specialty-level demand, and perhaps segregation between elective and emergency types of inpatient demand. A method for benchmarking the whole hospital’s average bed occupancy is given which enables them to run at optimum efficiency and safety. Using this method English hospitals can be shown to operate at highly disruptive and unsafe levels of bed occupancy leading to deleterious ‘turn-away’. Turn-away implies bed unavailability for the next arriving patient. The problems associated with crafting effective bed planning are illustrated using the English NHS as an example.

This study explores fault-tolerant consensus in leader-following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler-Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.

The accurate detection of clouds is an important first-step in the processing of remotely sensed satellite data analyses and subsequent cloud model predictions. While initial cloud retrieval technology began with the exploitation of one or two bands of satellite imagery, it has accelerated rapidly in recent years as sensor and retrieval technology have exploded, creating a new era in space exploration. Additionally, initial emphasis in satellite retrieval technology focused on cloud detection for cloud forecast models, more recently cloud screening in satellite acquired data is playing an increasingly critical role in the investigation of cloud free data for the retrieval of soil moisture, vegetation cover, ocean colour concentration and sea surface temperatures, as well as environmental monitoring of a host of products, e.g. atmospheric aerosol data, to study the Earth’s atmospheric and climatic systems. With about 60% of the Earth covered by clouds, on average, it is necessary to both accurately detect clouds in remote sensing data to screen cloud contaminate data in remote sensing analyses. In this paper, the evolution of cloud detection technology is highlighted with advancement in sensor hardware technology and possible AI algorithmic advances. Additionally, a discussion is presented on methods to obtain the cloud truth data needed to determine the accuracy of these cloud detection approaches.

In today’s rapidly evolving digital landscape, the significance of password guessing techniques in both offensive and defensive strategies is paramount. Passwords serve as a crucial line of defense for both individuals and corporations, safeguarding their sensitive systems and data. Therefore, assessing the effectiveness of these access credentials is a critical task. However, existing research in this field often encounters limitations, such as a lack of sufficient training data and extended model training times. Current methods often struggle with limited training data and lengthy training times. This paper introduces BBPE-AE, a novel Auto Encoder Network (AE) designed for password guessing. BBPE-AE utilizes Byte-level Byte Pair Encoding (BBPE) to extract frequent tokens from password datasets without length restrictions, employing a dynamic window technique to capture complex patterns. Experimental results on Hotmail and Myspace datasets demonstrate exceptional performance, achieving high similarity rates (BLEU-Unigram: 0.90, BLEU-Bigram: 0.82 for Hotmail; BLEU-Unigram: 0.90, BLEU-Bigram: 0.81 for Myspace). BBPE-AE generates realistic passwords that meet HIBP (Have I Been Pwned) standards, minimizing duplication. These findings highlight the effectiveness of BBPE-AE in enhancing security by generating realistic passwords, ultimately safeguarding sensitive systems and data.

The paper delves into the critical issue of damage detection within the guy cable of a truss steel mast, a pivotal component in structural integrity. It introduces a model wherein damage manifests as a localized cross-section reduction in a single element of the cable. Employing Discrete Wavelet Transform (DWT), a pioneering methodology, the study scrutinizes the behavior of the affected elements through static structural analyses. Signal decomposition via the Mallat pyramid algorithm facilitates comprehensive examination. Static displacements at the connection point between the cable and the truss mast serve as the measured variables. Through systematic investigation, the paper evaluates the impact of damage size and location, external loading force, and cable tension force on the efficacy of the proposed approach. Utilizing data derived from Finite Element Method (FEM) computations for wavelet analysis the authors substantiate the findings with numerical examples, thus offering valuable insights into damage detection strategies for structural health monitoring and engineering applications.

Objective. To test the hypothesis that a session of unilateral tSMS over the dominant primary motor cortex (M1) in healthy subjects produces a transient decrease in manual dexterity. Methods. A triple-blinded randomized control trial was conducted in 40 healthy participants who were allocated to real- or sham-tSMS group. Each participant underwent one session of tSMS and were assessed before, immediately after, 15 minutes, and 40 minutes after stimulation. Outcome measures were Finger Tapping Test (FTT), 5-seconds FTT, nine Hole Peg Test, and the hand grip assessment. Results: Significant differences were found between groups 15 minutes after stimulation in favor of the tSMS group in the FTT (2.2 ± 0.99; CI= .18-4.22; d= .84p=.034), and 5-second FTT (4.2 ± 1.98; CI= .199-8.2, d= .68; p=.04). In the intragroup analysis, a significantly lower number of taps 15 minutes after stimulation was observed in sham group (3.3 ± 1.01; CI= .47-6.13; d= .42; p=.015), but not in the real stimulation group. Conclusion: A unilateral session of tSMS in the M1 of the dominant hemisphere of healthy individuals does not reduce manual dexterity or grip strength. This technique could have benefits on the motor performance of the arm contralateral to the stimulated motor cortex

Soil water balance (SWB) in woody crops is sometimes difficult to estimate with one-dimensional models because these crops do not completely cover the soil and usually have a deep root system, particularly when cropped under rainfed conditions in a Mediterranean climate. In this study, the actual crop evapotranspiration (ETc act) is estimated with the soil water balance model SIMDualKc which uses the dual-Kc approach (relating the fraction of soil cover with the crop coefficients) to improve the estimation of the water requirements of a rainfed vineyard, using data from a deep soil profile. The actual basal crop coefficient (Kcb act) obtained using the SIMDualKc model was compared with the Kcb act estimated using the A&amp;P approach, which is a simplified approach based on measurements of the fraction of ground cover and crop height. Spectral vegetation indices derived from Landsat-5 satellite data were used to determine the fraction of ground cover (fc VI) and thus, the density coefficient (Kd). The SIMDualKc model was calibrated using soil water content (SWC) measurements down to a depth of 1.85 meters, which significantly improved the conditions for using a SWB estimation model. The test of the model was performed using a different SWC dataset. A good agreement between simulated and field measured SWC was observed for both data sets along the crop season, with RMSE&lt;12.0 mm, NRMSE &lt;13%. The calibrated Kcb values were 0.15, 0.60 and 0.52 for the initial, mid-season, and end season, respectively. The ratio between actual (ETc act) and crop evapotranspiration (ETc) was quite low between veraison and maturity (mid-season), corresponding to 36%, indicating that the rainfall was not sufficient to satisfy the vineyards water requirements. Spectral vegetation indices used to compute fc VI were unable to fully track the plants’ conditions when water stress. However, ingestion of data from remote sensing showed promising results that could be used to support decisions making in irrigation scheduling. Further studies on the use of the A&amp;P approach using remote sensing data are required.

The Solvency II regulatory framework specifies procedures and parameters for determining solvency capital requirements (SCRs) for insurance companies. The proposed standard SCR calculations involve two steps. The Value–at–Risk (VaR) of each risk driver is measured and, in a second step, all components are aggregated to the company’s overall SCR, using the Standard Formula. This formula has two inputs: the VaRs of the individual risk drivers and their correlations. The appropriate calibration of these input parameters has been the purpose of various Quantitative Impact Studies that have been conducted during recent years. This paper demonstrates that the parameter calibration for the equity–risk module—overall, with about 25%, the most significant risk component—is seriously flawed, giving rise to spurious and highly erratic parameter values. As a consequence, an implementation of the Standard Formula with the currently proposed calibration settings for equity–risk is likely to produce inaccurate, biased and, over time, highly erratic capital requirements.

Mulberry leaves, when infected by pathogens, can suffer significant yield loss or even death if early disease detection and timely spraying are not performed. To enhance the detection performance of mulberry leaf diseases in natural environments and to precisely locate early small lesions, we propose a high-precision, high-efficiency disease detection algorithm named YOLOv8-RFMD. Based on improvements to You Only Look Once version 8 (YOLOv8), we first proposed the Multi Dimension Feature Attention (MDFA) module, which integrates important features at the pixel-level, spatial and channel dimensions. Building on this, we designed the RFMD Module, which consists of the Conv-BatchNomalization-SiLU (CBS) module, Receptive-Field Coordinated Attention (RFCA) Conv, and MDFA, replacing the Bottleneck in the model’s Residual block. We then employed Adown down sampling structure to reduce the model size and computational complexity. Finally, to improve the detection precision of small lesion features, we replaced the complete intersection over union (CIOU) loss function with the Normalized Wasserstein Distance (NWD) loss function. Results show that the YOLOv8-RFMD model achieves an mAP50 of 94.3% and an mAP50:95 of 67.8% on experimental data, representing increases of 2.9% and 4.3% respectively compared to the original model. The model size is reduced by 0.53 MB to just 5.45 MB, and the number of floating-point operations is reduced by 0.3 G to only 7.8 G. The improved model meets the deployment requirements of mobile embedded devices and can provide a theoretical reference for the automated spraying operations of mulberry leaves.

Background/Objectives: The Perilla frutescens plant has historically been used to protect against inflammation and redox stress. This has been attributed in part to the high content of various polyphenols. Despite this, the complement of polyphenolic components in Perilla extract is not yet fully defined. The aim of this study was to characterise the polyphenolic composition in Perilla extract, and its effect on the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2), which during inflammation and oxidative stress binds to the antioxidant response element (ARE) found on the promoter of phase II antioxidant enzymes. Methods: Following extraction using four solvents of different properties, the total phenolic, flavonoid and ortho-diphenolic content of Perilla extract were determined. Individual phenolic compounds were identified and quantified by RP-HPLC. Dual Luciferase assay using a reporter plasmid containing a human NQO1 ARE-luciferase fusion was employed to determine the potential protective effect of the Perilla fractions against redox stress. Results: HPLC analysis revealed that the highest phenolic content was present in the polar extracts. A total of 35 distinct polyphenolic compounds were identified, with rosmarinic acid being the major constituent. On cells in vitro, the methanol Perilla fraction showed protection against redox stress, with the luciferase assay displaying up to 1.5 fold increase in the induction of the human NQO1 ARE-luciferase reporter. Conclusions: While Perilla extract seems to be mainly protecting against inflammation and redox stress through the action of rosmarinic acid, further work is required on the synergystic effects between different polyphenols.

To decrease oral pathogens and increase the number of beneficial bacteria, probiotics and bioactive compounds made via microbial bioconversion are recently used. In addition, the interest regarding probiotics-mediated bioconversion with popular medicinal plants is increasing. These compounds produced during the process exhibit synergistic effect and enhance a variety of biological activities including pathogen inhibition in host. Therefore, we developed bioconverted milk with high inhibitory activity against oral pathogens and α-glucosidase. Lactiplantibacillus plantarum SMFM2016-RK was chosen as the probiotic due to its beneficial characteristics such as high acid and bile tolerance, antioxidant activity, and α-glucosidase inhibition. Based on the minimal bactericidal concentration against three oral pathogens, the following appropriate concentrations of Artemisia herba-alba extract were added to milk: 5 mg/mL of A. herba-alba ethanol extract and 25 mg/mL of A. herba-alba hot-water extract. Four bioconverted milks (BM), BM1, BM2, BM3, and BM4, were produced by combining L. plantarum SMFM2016-RK alone, L. plantarum SMFM2016-RK and ethanol extract, L. plantarum SMFM2016-RK and hot-water extract, and L. plantarum SMFM2016-RK with both extracts. As a result of antimicrobial activity, BM3 inhibited the growth of Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis the most, and BM4 suppressed the growth of Fusobacterium nucleatum the most. In addition, bioconverted milk containing A. herba-alba (BM2, BM3, and BM4) inhibited α-glucosidase more effectively than BM1. In conclusion, A. herba-alba-added milk bioconverted by L. plantarum SMFM2016-RK displayed the growth inhibitory effect on oral pathogens and the α-glucosidase inhibitory activity, thus it necessitates to evaluate the effects on the alleviation of oral diseases and glycemic control through future animal experiments.

Alpha emitters like plutonium pose severe health risks when ingested, damaging DNA and potentially causing cancer. Traditional detection methods require proximity within millimeters of the contamination source, presenting safety risks and operational inefficiencies. Long-range detection through alpha radioluminescence (RL) offers a promising alternative. However, most of the previous experiments have been carried out under controlled conditions that preclude the overwhelming effect of ambient light. This study demonstrates successful detection of a 3 MBq alpha emitter in an open environment using a newly developed, lightweight compact alpha camera. This camera incorporates a deep-cooled CCD and a specially designed lens system with a low f-number to maximum the signal intensity. The lens was also designed to minimize blue shift effects of filters. Nighttime imaging was achieved with a dual-filter system using a sandwich filters assembly centered at 337 nm and 343 nm for capturing alpha RL and subtracting background light, respectively. At night, the alpha source was detected from 1 meter away within one minute. The system was also evaluated under simulated urban lighting conditions. For daytime imaging, a stack of tilted 276 nm short pass filters minimized sunlight interference, enabling clear detection of the alpha source at 70 cm within 10 minutes under indirect sunlight. This research not only underscores the viability of long-range optical detection of alpha emitters for environmental monitoring and scientific research but also highlights its ability to enhance nuclear safety and public health in real-world settings.

Rice has become the second major food among rural people. It is one of the most nutrient and low-cost food available in Asia. Rice is composed of two major subspecies as Japonica and Indica and it belongs to the Poaceae family. The World Bank predicts that rice demand will grow 51% faster than population growth in 2025. It is high time to develop a model which predicts the type of infected paddy leaf and avoids the loss of grains. In this paper, the proposed hybrid CNN model, three CNN networks with different layer properties are trained parallel. The extracted feature from these CNN networks is combined to provide the classification of the type of infected leaf. Fieldwork was carried and about 340 samples are collected from five different types of classes. The proposed hybrid model was tested with both the fieldwork dataset and also with an available dataset on the internet. The experimental results show that the proposed model outperforms the other CNN network and yields an accuracy value of 98%, a precision value of 95%, and a misclassification rate of 4% respectively.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

Cigar stacking fermentation is a key step in tobacco aroma enhancement and miscellaneous gas reduction, which both have a great influence on increasing cigar flavor and improving industrial availability. To analyze the effect of cigar tobacco leaf (CTLs) microbial community structure on volatiles during cigar stacking fermentation, this study used multi-omics technology to reveal the changes in microbial community structure and volatiles of different cigar varieties during stacking fermentation, in addition to exploring the interaction mechanism of microbiome and volatiles. The results showed that the dominant microbial compositions of different CTL varieties during stacking fermentation were similar, which included Staphylococcus, Corynebacterium 1, Aerococcus, and Aspergillus. These dominant microbes mainly affected the microbial community structure and characteristic microorganisms of CTLs through microbial interactions, thereby influencing the transformation of volatiles. Characteristic microorganisms of different CTLs varieties such as Trichothecium, Trichosporon, Thioalkalicoccus and Jeotgalicoccus, were found to posively correlate with characteristic volatiles like megastigmatrienone 4, pyrazine, tetramethyl-, geranyl acetone, and 2-undecanone, 6,10-dimethyl-, respectively. This in turn affected the aroma and sensory quality of the CTLs. This study provides theoretical support for the analysis of the mechanism of microorganisms on volatiles and aroma, and development of microbial agents during cigar stacking fermentation.

In the event of an abrupt sunlight reduction scenario there is a time window that occurs between when food stores would likely run out for many countries (~6 months or less) and ~1 year when resilient foods are scaled up. A promising temporary resilient food is leaf protein concentrate (LPC). Although it is possible to extract LPC from tree biomass (e.g. leaves and needles), neither the yields nor the toxicity of the protein concentrates for humans from the most common tree species has been widely investigated. To help fill this knowledge gap, this study uses high-resolution mass spectrometry and an open source toolchain for non-targeted screening of toxins on five common North American coniferous species: Western Cedar, Douglas Fir, Ponderosa Pine, Western Hemlock, and Lodgepole Pine. The yields for LPC extraction from the conifers ranged from 1% to 7.5%. The toxicity screenings confirm that these trees may contain toxins that can be consumed in small amounts and additional studies including measuring the quantity of each toxin are needed. The results indicate that LPC is a promising candidate to be used as resilient food, but future work is needed before LPCs from conifers can be used as a wide-scale human food.

Two types of trenches cross-section in conventional vertical and brand new reverse-V-shape have fabricated on SCD substrate by micro-jet water-assist laser, the epitaxial lateral overgrowth technique has applied by microwave plasma chemical vapor deposition system in forming multiple micrometer-size channels. Raman and SEM techniques have applied in analyze both types growth layer characterization. Optical microscope has used to test microchannels hollowness. As a result, with the brand new reverse-V-shape trench, epitaxial lateral overgrowth layer reaches higher SCD surface morphology and crystal quality.

This paper reveals some properties of the cumulative entropy of consecutive k-out-of-n:F system's lifetime. First, we introduce a method for calculating the cumulative entropy of their lifetime and explore its preservation properties using established stochastic orders. Ad- ditionally, we obtain useful bounds that can used in situations where the distribution function of the system's component lifetimes are complicated or systems have large components. To support practical applications, we present two nonparametric estimators for the cumulative entropy of these systems. The efficiency and performance of these estimators are illustrated with simulated datasets and further validated with real data sets.

Densely urbanized areas, with a low percentage of green vegetation, are highly exposed to Heat Waves (HW) which nowadays are increasing in terms of frequency and intensity also in the middle-latitude regions, due to ongoing Climate Change (CC). Their negative effects may combine with those of the UHI (Urban Heat Island), a local phenomenon where air temperatures in the compact built up cores of towns increase more than those in the surrounding rural areas, with significant impact on the quality of urban environment, on citizens health and energy consumption and transport, as it has occurred in the summer of 2003 on France and Italian central-northern areas. In this context this work aims at designing and developing a methodology based on aero-spatial remote sensing (EO) at medium-high resolution and most recent GIS techniques, for the extensive characterization of the urban fabric response to these climatic impacts related to the temperature within the general framework of supporting local and national strategies and policies of adaptation to CC. Due to its extension and variety of built-up typologies, the municipality of Rome was selected as test area for the methodology development and validation. First of all, we started by operating through photointerpretation of cartography at detailed scale (CTR 1: 5000) on a reference area consisting of a transect of about 5x20 km, extending from the downtown to the suburbs and including all the built-up classes of interest. The reference built-up vulnerability classes found inside the transect were then exploited as training areas to classify the entire territory of Rome municipality. To this end, the satellite EO HR (High Resolution) multispectral data, provided by the Landsat sensors were used within a on purpose developed "supervised" classification procedure, based on data mining and “object-classification” techniques. The classification results were then exploited for implementing a calibration method, based on a typical UHI temperature distribution, derived from MODIS satellite sensor LST (Land Surface Temperature) data of the summer 2003, to obtain an analytical expression of the vulnerability model, previously introduced on a semi-empirical basis.

K-band radar waves have high penetration and low attenuation coefficients. However, the wavelength of this radar wave is relatively short; thus, designing and preparing both broadband and wide-angle radar wave absorbers in this band presents considerable challenges. In this study, a resin-based K-band radar wave absorber with a biomimetic lotus leaf structure was designed and formed by UV curing. Here, microscale lotus leaf papillae and antireflection structures were prepared using a DLP 3D printer, and the contact angle between the material and water droplets was increased from 56° to 130°. In addition, the influence of the geometric parameters of the lotus leaf antireflection structure on the electromagnetic absorption performance and mechanical strength was investigated. After simulation optimization, the maximum electromagnetic loss of the lotus leaf structure 3D printed sample was −32.3 dB, and the electromagnetic loss was below −10 dB in the 20.8–26.5 GHz frequency range. When the radar incidence angle was 60°, the maximum electromagnetic loss was still less than −10 dB. The designed lotus leaf structure has a higher mechanical energy absorption per unit volume (337.22 KJ/m3) and per unit mass (0.55 KJ/Kg) than commonly used honeycomb lightweight structures during the elastic deformation stage, and we expect that the designed structure can be used as an effective lightweight material for K-band radar stealth.

Studies were initiated to find new effective fungicides to use under field conditions to identify novel options for improved disease management in sugar beet. Cercospora-leaf spot (CLS) of sugar beet, caused by Cercospora beticola Sacc., is a major foliar disease of sugar beet in all sugar beet growing areas, worldwide. The disease is now dominant in almost all sugar beet growing areas of Europe, including Hungary. The epidemic spread of this disease can cause up to 50% yield loss. The use of fungicides has been being an integral part of the control of CLS of sugar beet, due to lack of efficacy from non-chemical alternatives. In recent decades, the emergence of resistant strains in C. beticola Sacc. populations have reduced the efficacy of some fungicides (Quinoine inside Inhibitors (QoI) – FRAC Group 11; and DeMethylation-Inhibitors (DMI) – FRAC Group 3) because of repeated use over many uears. Resistance of CLS to fungicides belonging to different groups of active substances has been described in many countries of the world, including Hungary. The picolinamides are a new distinct group of fungal respiration inhibitors (Inhibition of Complex III) belonging to Quinoine inside Inhibitors (QiI). Two novel fungicides from the group of picolinamides (Qil – FRAC Group 21) – fenpicoxamid and florylpicoxamid– were tested and evaluated over two seasons, in vegetation period of 2020 and 2021 for controlling CLS of sugar beet in Hungary. Both fungicides were applied as straight formulated products at a range of dose rates, and they showed very effective control of CLS compared to the untreated control check plots and the reference fungicide product difenoconazole. The results consistently showed all tested dose rates of fenpicoxamid and florylpicoxamid provided effective control against CLS of sugar beet in addition to a clear dose response curve. Disease severity, in terms of area under the disease progress curve values (AUDPC), was significantly correlated with yield decrease, while no significant context existed between disease severity and sugar content of the roots. Additionally, the results showed in two investigated years, the efficacy of both picolinamide fungicides applied at 75 g ai/ha provided significantly better % control on CLS of sugar beet than the DMI fungicide difenoconazole applied at 100 g ai/ha dose rate. Fenpicoxamid is already registered in Europe in cereals and label extension is planned in sugar beet and other crops. Florylpicoxamid is not yet registered in Europe but is beginning to be approved in countries across the globe in a range of crops and is continuously under evaluation for potential markets.

: This study focuses on optimizing chlorophyll extraction techniques and strategically placing leaf disks to enhance chlorophyll concentration in sesame (Sesamum indicum L.) leaves. Thirty sesame genotypes, categorized into light green (LG), middle green (MG), and deep green (DG) pigment groups based on leaf coloration, were selected from a larger pool of field-grown accessions. The investigation involved determining optimal SPAD value index measurements, quantifying pigment concentrations, exploring extraction solvents, and selecting suitable leaf disk positions. Significant variations in chlorophyll content were observed across genotypes, greenness categories, and leaf disk positions. The categorization of genotypes into DG, MG, and LG groups revealed a correlation between leaf appearance and chlorophyll content. The study highlighted a consistent relationship between carotenoids and chlorophyll, indicating their role in adaptation to warm environments. Examination of leaf disk positions revealed a significant chlorophyll gradient along the leaf blade, emphasizing the need for standardized protocols. Chlorophyll extraction experiments identified DMSO and 96% ethanol, particularly the later incubated for 10 minutes at 85°C, as effective choices. This recommendation considers factors like cost-effectiveness, time efficiency, safety, and environmental regulations, ensuring consistent and simplified extraction processes. For higher chlorophyll extraction, focusing on leaf tips and the 75% position along the sesame leaf blade is suggested, consistently yielding higher chlorophyll content. Our findings therefore, underscores insightful knowledge on chlorophyll gradients and encouraging for standardized protocols, that enabling researchers to refine experimental designs for precise and comparable chlorophyll measurements. Recommended solvent choices ensure reliable outcomes in plant physiology, ecology, and environmental studies.

The pollution of the bays in Abidjan is a major concern for the Ivorian policy makers. In fact, the pollution of the bays induce high costs to the society while impacting population health dramatically. As a result, pollution reduction management of production activities has been undertaken in the Cocody Bay area. To our knowledge, no study has yet proposed a model to evaluate the cost-effectiveness of these pollution management strategies. A cost-effectiveness model, based on Monte Carlo simulation, was developed to assess the economic and environmental impacts of various scenarios characterized by a set of production practices, both in the short term and in the long term. The authors discuss the steps and input parameters of the model presented. The proposed model may serve as the basis for identifying an optimal production scenario defined as the scenario with the best incremental cost-effectiveness ratio considering a willingness to pay (WTP) threshold. The WTP, to be estimated based on the gross domestic product of Côte d’Ivoire, represents the opportunity costs associated with selecting the optimal scenario. The current framework can also be applied to other settings facing similar challenge.

Mineral nutrition is essential for plant growth and interaction of plants with biotic and abiotic stresses. Mango twig-tip dieback (MTTD) is a new type of mango decline, but its impact on the trees’ mineral nutrition is unknown. This study was conducted to determine the effect of MTTD infection on the nutrient status, balance, and resorption efficiency (RE) of mango. Leaf nutrient concentrations and deviation from the optimum percentage (DOP) indices of ‘Kensington Pride’ (KP) mango trees with low (LD) and high (HD) levels of MTTD infections were analyzed to compare the foliar nutrition status and nutrient balance between the LD and HD trees. Moreover, the nutrient resorption efficiency of MTTD-infected dried leaves (RE_D) was compared with the resorption efficiency of healthy (RE_S) leaves of KP mangoes. The concentrations of the total Ca, Mg, Cu, Fe, Mn, and Zn were lower in the HD trees than in the LD trees. But the total K content was higher in the HD trees, and its DOP index was sufficient, while the total K concentration was low and deficient level in LD trees. Moreover, DOP indices for total Ca, Mn, and Zn were less deficient in LD trees than in HD trees, and overall nutrient imbalances were exacerbated in HD trees. RE_D was significantly lower than RE_S for the total N, P, S, Cu, Fe, and Zn but significantly higher than RE_S for K. The study underscores the significant influence of MTTD on the mineral nutrition of KP mangoes, revealing distinct nutrient variations between trees with low and high MTTD infection levels. These findings have important implications for mango crop management, emphasizing the need for targeted nutrient interventions to address imbalances induced by MTTD and enhance the overall health and resistance of mango trees against MTTD infection.

Boron (B) toxicity is an important stress that negatively affects maize yield and quality production. The excessive B content in agricultural lands is a growing problem due to the increase in arid and semi-arid areas because of climate change. Recently, two Peruvian maize landraces, Sama and Pachía, were physiologically characterized based on their tolerance to B toxicity, the former being more tolerant to B excess than Pachía. However, many aspects regarding the molecular mechanisms of these two maize landraces against B toxicity are still unknown. In this study, a leaf proteomic analysis of Sama and Pachía was performed. Out of a total of 2793 proteins identified only 303 proteins were differentially accumulated. Functional analysis indicated that many of these proteins are involved in transcription and translation processes, amino acids metabolism, photosynthesis, carbohydrate metabolism, protein degradation, and protein stabilization and folding. Compared to Sama, Pachía had a higher number of differentially expressed proteins related to protein degradation, and transcription and translation processes under B toxicity conditions, which might reflect the greater protein damage caused by B toxicity in Pachía. Our results suggest that higher tolerance to B toxicity of Sama can be attributed to more stable photosynthesis that would avoid damage caused by stromal over-reduction under this stress condition.

Rigid-body visual tracking is an active research field with many practical applications including visual surveillance and intelligent transport system. In this paper, we define a new problem domain, called visual growth tracking, to track different parts of an object that grow non-uniformly over space and time for application in image-based plant phenotyping. The paper introduces a novel method to detect and track each leaf of a plant for automated leaf stage monitoring. The method has four phases: optimal view selection, plant architecture determination, leaf tracking and generation of a leaf status report. The proposed method uses a graph theoretic approach to reliably detect and track individual leaves by overcoming the challenge of leaf-losses based on temporal image sequence analysis for automatically generating the leaf status report containing the following phenotypes, i.e., the emergence timing of each leaf, total number of leaves present at any time, the day on which a particular leaf stopped growing, and the length and relative growth rate of individual leaves. The proposed method demonstrates high accuracy in detecting leaves and tracking them through the early vegetative stages of maize plants based on experimental evaluation on a publicly available benchmark dataset.

Leaf springs are suspension components constituted of several structural and assembly components. Once the leaves are assembled, a stress state due to the assembly process is developed. Thus, the quantification of the assembly stress level should be known in order to be accounted for in the structural design. The aim of this article is precisely to quantify the assembly stress level in parabolic leaf springs for railway freight wagons. An experimental method with the aid of extensometry is considered to evaluate elastic assembly stresses. Next, a numerical model of the leaf spring assembly process with the required boundary conditions is developed to support the experimental results and allow obtaining a distribution of surface stresses along the master leaf length. The development of this work resulted in a surface stress profile along the length of the master leaf generated by the assembly process, where the deviations of the numerical outcomes regarding the analysed spots with strain gauges are mostly of little relevance.

Leaf variegation pale yellowing is observed in the Calcineurin B-Like-Interacting Protein Kinase14 (CIPK14) overexpression line (oeCIPK14) and double knockout WHIRLY1/WHIRLY3 (why1/3) lines of Arabidopsis, the distribution of WHIRLY1 (WHY1) protein between plastids and the nucleus are affected by the phosphorylation of WHY1 by CIPK14. To elucidate the coregulation of CIPK14 and WHIRLY1/WHIRLY3 mediated leaf pale yellowing, a differential proteomic analysis is conducted between the oeCIPK14 variegated (oeCIPK14-var) line, why1/3 variegated (why1/3-var) line and wild type (WT). More than 800 protein spots are distinguished on each gel, 67 differential abundance proteins (DAPs) are identified by matrix-assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF-MS), of which, 34 DAPs are in the oeCIPK14-var, 33 DAPs are in the why1/3-var compared to WT. Five overlapping proteins differentially change both in the oeCIPK14-var and in the why1/3-var. They are ATP-dependent Clp protease proteolytic subunit-related protein 3 (ClpR3), Ribulose bisphosphate carboxylase large chain (RBL), Beta-amylase 3 (BAM3), Ribosome-recycling factor (RRF), Ribulose bisphosphate carboxylase small chain (RBS). Bioinformatics analysis show that most of DAPs are involved in photosynthesis, defense and antioxidation pathway, protein metabolism, amino acid metabolism, energy metabolism, malate biosynthesis, lipid metabolism and transcription. Thus, the photosystem parameters are measured that the content of chlorophyll, the photochemical efficiency of PSⅡ (Fv/Fm), and electron transport rates (ETR) decrease in the why1/3-var and oeCIPK14-var, but the non-photochemical quenching (NPQ) increases. Both mutants show high sensitivity to strong light. Based on the annotation of DAPs from both why1/3-var and oeCIPK14-var lines, we conclude that CIPK14 phosphorylation mediated WHY1 deficiency in plastids is related to impairment of protein metabolism leading to chloroplast dysfunction.

This study introduces a novel, robust, and efficient method for the simultaneous quantitative determination of three sunscreen filters namely 4-methylbenzylidene camphor, octyl methoxycinnamate, and avobenzone, in a moisturizing sunscreen cream specifically designed for acne-prone skin. The method employs high performance liquid chromatography with photodiode-array detection, providing reliable separation of the analytes. Chromatographic separation was achieved using a Fortis Phenyl analytical column (150.0 x 2.1 mm, 5 μm), with isocratic elution at a flow rate of 0.4 mL/min. The mobile phase was composed of a 57/43 (v/v) mixture of acetonitrile/45 mM aqueous ammonium formate solution, ensuring sufficient resolution and peak symmetry for the target compounds. The method was validated comprehensively for critical performance parameters, including linearity, precision, accuracy, and robustness. Linearity was established across a suitable range for all three analytes, with high correlation coefficients. Precision was confirmed with intra-run and total precision coefficients of variation of ≤ 4.6 %, while accuracy assessments yielded a percent recovery between 98.6 and 100.4, for all quality control levels. Additionally, the method was able to effectively separate the sunscreen filters from other cosmetic ingredients, such as [β-(1.3), (1.6)-D-glucan], Low Molecular Weight (LMW) hyaluronic acid and plant extracts ensuring specificity in complex formulations. This straightforward and time efficient sample preparation process, involving methanol extraction followed by serial dilution, makes the method suitable for routine quality control in cosmetic laboratories. The method was successfully applied to the analysis of two different lots of a commercial sunscreen cream, achieving excellent recovery for all filters, ranging between 94.6% and 99.8%, thus demonstrating its reliability and applicability for the quality control of cosmetics.

In this paper we suggest a first ever construction of fractional integral and differential operators based on signed measures including a vector-valued case. The study focuses on constructing the fractional power of the Riemann-Stieltjes integral with a signed measure, using semigroup theory. The main result is a theorem that provides the exact form of a semigroup for the Riemann-Stieltjes integral with a measure having a countable number of extrema. The article provides examples of semigroups based on integral operators with signed measures and discusses the fractional powers of differential operators with partial derivatives.

In this paper, the transmutation operator method is used to construct an exact solution to the initial boundary value problem for the equation of multidimensional free transverse vibration of a thin elastic plate with a singular Bessel operator acting on geometric variables. We emphasize that multidimensional Erdélyi–Kober operators of fractional order have the property of a transmutation operator, allowing one to transform more complex multidimensional partial differential equations with singular coefficients acting over all variables into simpler ones. If formulas for solutions are known for a simple equation, then we also obtain representations for solutions to the first complex partial differential equation with singular coefficients. In particular, it is successfully applied to the singular differential equations, especially with Bessel-type operators. Using this operator, the considered problem is reduced to a similar problem without the Bessel operator. Based on the solution to the auxiliary problem, an exact solution to the original problem is constructed and analyzed.

Plant leaf area index (LAI) is a key characteristic affecting field canopy microclimate. In addition to traditional professional measuring instruments, smartphone camera sensors have been used to measure plant LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5° angle. To validate further the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that both methods can be used to reveal the conifer leaf-growing trajectory. However, the method with the phone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regard to four aspects that can affect LAI: gap fraction, leaf projection ratio, sensor field of view (FOV), and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5° method to overestimate the gap fraction and hence underestimate conifer LAI, especially when tree height is greater than 2.0 m. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

Chronic wounds remain a significant clinical challenge, necessitating the exploration of novel therapeutic agents. Sedum telephium L. (syn. Hylotelephium telephium (L.) H. Ohba) leaf juice, known for its traditional medicinal uses, was evaluated for its wound healing properties. This study aimed to chemically characterize the leaf juice and assess its efficacy in promoting wound healing in vitro. Fresh leaves were collected and processed to obtain the juice, which was analyzed for polyphenols, flavonoids, polysaccharides, and proteins. Key bioactive compounds, including flavonols such as kaempferol glycosides and quercetin glycosides, were identified. The juice and its polysaccharidic fraction were tested on human keratinocytes (HaCaT) and fibroblasts (HFF-1) to assess cell viability, wound closure, and the production of growth factors and pro-collagen I. Our results indicated that the whole juice significantly enhanced wound closure in both cell types, with a marked increase in fibroblast growth factor (FGF) and LAP(TGF-β1) production in keratinocytes, highlighting its potential mechanisms of action. The polysaccharidic fraction alone showed limited efficacy, emphasizing the importance of the complete phytocomplex. These findings suggest that Sedum telephium L. represents a promising candidate in the setting of skin regeneration and repair.

Chili peppers (Capsicum annuum L.) are economically important crop worldwide. Pepper yellow leaf cure Thailand virus (PepYLCTHV), a Begomovirus causing yellow leaf mosaic disease of chili pepper has been reported to damage 95% economic loss under favorable epidemic conditions. Thirty-one chili genotypes were screened for resistance to PepYLCTHV disease through challenge inoculation using 10-15 viruliferous whiteflies per plant. We purified two resistant lines (PEP6 and PEP12) through four generations of selfing and selection through challenged inoculations. At the 28 days after inoculations two chili genotypes showed symptoms less based on disease severity and percentage of disease incidence of 30 plants PEP6 showed a disease severity 3.64 with 69.33 % DI and PEP12 showed a disease severity 3.83 with 77.67 % DI. PEP6 and PEP12 were selected for pure-line development for four cycles.Both varieties showed an increase in percentage of the resistant plant 12.78 % and 16.77 %, respectively. These lines have potential for release as resistant lines for improvement chili pepper resistance to PepYLCTHV and for developing maker associated with the resistant trait.

3D measurement is a high-throughput method that can record a large amount of information. In this study, we have developed new methods that could be used for morphological analysis of plants from the information contained in 3D data. Specifically, we investigated characteristics that can be measured by scale (dimension) and/or visual assessment by humans. The characteristics that can be measured on a scale-related dimension were tested based on the bounding box, convex hull, column solid, and voxel. Furthermore, for characteristics that can be evaluated by visual assessment, we propose a new method using normal vectors and local curvature (LC) data. For these examinations, we used our highly accurate all-around 3D plant modelling system. The correlation coefficients between manual measurements and the scale-related methods were all above 0.9. In particular, the differences in LC calculated from the normal vector data allowed us to visualize and quantify the concavity and convexity of leaves. Furthermore, we also found a difference in the time point at which leaf blistering began to develop among the cultivars. The precise 3D model made it possible to perform quantitative measurements of lettuce size and morphological characteristics. In addition, the newly proposed LC-based analysis method made it possible to quantify the characteristics that rely on visual assessment.

Effectively mapping and monitoring rubber plantation is still changing. Previous studies have explored the potential of phenology features for rubber plantation mapping through a pixel-based approach (pixel-based phenology approach). However, in fragmented mountainous Xishuangbanna, it could lead to noises and low accuracy of resultant maps. In this study, we investigated the capability of an integrated approach by combining phenology information with an object-based approach (object-based phenology approach) to map rubber plantations in Xishuangbanna. Moderate Resolution Imaging Spectroradiometer (MODIS) data were firstly used to acquire the temporal profile and phenological features of rubber plantations and natural forests, which delineates the time windows of defoliation and foliation phases. Landsat images were then used to extract a phenology algorithm comparing three different approaches: pixel-based phenology, object-based phenology, and extended object-based phenology to separate rubber plantations and natural forests. The results showed that the two object-based approaches achieved higher accuracy than the pixel-based approach, having overall accuracies of 96.4%, 97.4%, and 95.5%, respectively. This study proved the reliability of a phenology-based rubber mapping in fragmented landscapes with a distinct dry/cool season using Landsat images. This study indicated that the object-based phenology approaches can effectively improve the accuracy of the resultant maps in fragmented landscapes.

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

Alzheimer's disease (AD) is a stealthy and progressive neurological disorder that is a leading cause of dementia in the global elderly population, imposing a significant burden on both the elderly and society. Currently, the condition is treated with medications that alleviate symptoms. Nonetheless, these drugs may not consistently produce the desired results and can cause serious side effects. Hence, there is a vigorous pursuit of alternative options to enhance the quality of life for patients. Ginkgo biloba (GB), an herb with historical use in traditional medicine, contains bioactive compounds such as terpenoids (Ginkgolides A, B, and C), polyphenols, organic acids, and flavonoids (quercetin, kaempferol, and isorhamnetin). These compounds are associated with anti-inflammatory, antioxidant, and neuroprotective properties, making them valuable for cognitive health. A systematic search across three databases using specific keywords GB in AD and dementia yielded 1702 documents, leading to the selection of 15 clinical trials for synthesis. In eleven studies, GB extract/EGb 761® was shown to improve cognitive function, neuropsychiatric symptoms, and functional abilities in both dementia types. In four studies, however, there were no significant differences between the GB-treated and placebo groups. Significant improvements were observed in scores obtained from the Mini-Mental State Examination (MMSE), Short Cognitive Performance Test (SKT), and Neuropsychiatric Inventory (NPI). While the majority of synthesized clinical trials show Ginkgo biloba has promising potential in these conditions, more research is needed to determine optimal dosages, effective delivery methods, and appropriate pharmaceutical formulations. Furthermore, a thorough assessment of adverse effects, exploration of long-term use implications, and investigation into potential drug interactions are critical aspects that must be carefully evaluated in future studies.

Let BT4l denotes a subclass of bounded turning functions connected with a four-leaf-type domain. The goal of the study is to probe into coefficients of |b6|, |b7|, |b8|, the bounds of the logarithmic coefficients and the third-order determinants of H3,1, H3,2, H3,3 for functions in this class.

The study of phytotherapy in dentistry is relevant due to the low occurrence of research in the treatment of oral pathologies, such as caries and periodontal disease. Thus, the aim of this research was to characterize the chemical composition of extracts from the leaves of Couroupita guianensis Aubl, including toxicological evaluation and the antioxidant and antimicrobial potential against Staphylococcus aureus, Streptococcus mutans and Candida albicans. Three extracts were prepared using assisted ultrasound, originating the Crude Ultrasound Extract (CUE) and Soxhlet apparatus, originating the Crude Soxhlet Extract (CSE) and the Ethanol Soxhlet Extract (ESE). In the analysis of the chemical composition, the presence of flavonoids, tannins and saponins were detected. LC-DAD analysis revealed the presence of caffeic acid, sinapic acid, rutin, quercetin, luteolin, kaempferol and apigenin in all extracts. In the GC-MS analysis, stigmasterol and β-sitosterol were identified in CUE and CSE. The antioxidant potentials, determined by the DPPH• and ABTS•+ methods, the ESE showed higher antioxidant activity (2.98 ± 0.96 and 4.93 ± 0.90, respectively). In the evaluation of toxicity, the CUE 50µg/mL and the ESE 50 µg/mL presented growth stimulation of Allium cepa roots. At a concentration of 750µg/mL, all extracts inhibited root growth. None of the extracts showed toxicity against Artemia salina. Antibacterial action was detected in all extracts, mainly against the microorganisms S. aureus and S. mutans; however, the antifungal action against C. albicans was not detected. From the results, the extracts of C. guianensis have therapeutic potential for use in the control of microorganisms in the oral microbiota.

The horse chestnut leaf miner Cameraria ohridella (Lepidoptera: Gracillariidae) is an invasive pest of horse chestnut and has spread through Europe since 1985. The horse chestnut leaf blotch Guignardia aesculi (Botryosphaeriales: Botryosphaeriaceae) is a fungal disease that also seriously damages horse chestnut trees in Europe. The interaction between the leaf miner and the fungus has not yet been sufficiently described. Therefore, the aim of the present study was to assess leaf damage inflicted to horse chestnut by both C. ohridella and G. aesculi during the vegetation season and to model their interaction. The damage to leaf area was measured monthly from May to September 2013 in České Budějovice, the Czech Republic. A simple phenomenological model describing the expected dynamics of the two species was developed. The study revealed a significant effect of sampling site and sampling period on the damage caused by both the pest and the fungus. The mathematical model indicates that infestation by C. ohridella is more affected by G. aesculi than vice versa. The possible mechanisms affecting the relationship between G. aesculi and C. ohridella are discussed.

Litsea martabanica root's antioxidant and AChE activity showed promise as a pesticide detoxification agent in our previous study. In addition to roots, its leaves can help mitigate pesticide exposure, although there is limited scientific evidence supporting their efficacy. However, the use of roots in many countries, such as Thailand, could contribute to environmental degradation, as highland communities traditionally cut down whole trees to obtain them. This study aims to evaluate the antioxidant activity and anti-pesticide potential of water extracts from L. martabanica leaves instead of its roots through in vitro and in vivo investigations. The findings showed that L. martabanica water extracts and fractions demonstrated varied antioxidant activity. The water extract, obtained using traditional extraction methods, was chosen for in vivo experiments. Rats received the extract followed by chlorpyrifos exposure for 16 days. Results indicated reduced acetylcholinesterase activity in chlorpyrifos-exposed rats, while treatment with leaf extract led to increased activity, suggesting its potential as a detoxifying agent. Histopathological examination revealed no liver cell necrosis and showed liver cell regeneration, indicating potential protection against free radical-induced liver damage without affecting rat liver weight or biochemical profiles. Utilizing L. martabanica leaves for healthcare purposes holds promise without negative environmental impact.

Cortex Periplocae, as a traditional Chinese herbal medicine, has been widely used for autoimmune diseases, especially rheumatoid arthritis. Due to its potential pharmaceutical values, more studies about the biological activities of Cortex Periplocae have been conducted recently. Meanwhile, the adverse reaction of Cortex Periplocae is not a negligible problem in clinic. In this article, we reviewed a series of articles and summarized the recent studies of Cortex Periplocae in the areas of phytochemistry and pharmacology. More than 100 constituents have been isolated and identified from Cortex Periplocae, including steroids, cardiac glycosides, terpenoids, and fatty acid compounds. The crude extracts of Cortex Periplocae and its active compounds exhibit various biological activities, such as cardiotonic effect, anticancer action, and anti-inflammatory effect. This paper aims to provide an overall review on the bioactive ingredients, pharmacological effect, and toxicity of this plant. Furthermore, this review suggests investigating and developing new clinical usages according to the above pharmacological effects.

The monitoring of coastal waters using satellite data, from sensors including Sentinel-3 OLCI, has become a vital tool in the management of these water environments; especially when it comes to improving our understanding of the effects of climate change on these regions. In this study, Level-2 water products derived from different OLCI Sentinel-3 processors were validated against a comprehensive in situ dataset from the NW Baltic Sea proper region. The products validated were those of the regionally adapted Case-2 Regional Coast Colour (C2RCC) OLCI processor (v1.0 and v2.1), as well as the latest standard Level-2 OLCI case 2 (Neural Network) products from Sentinel-3’s processing baseline: Baseline Collection 003 (BC003), including “CHL_NN”, “TSM_NN”, and “ADG443_NN”. Furthermore, the effect of the current EUMETSAT system vicarious calibration (SVC) on the Level-2 water products was also validated. Results showed that the system vicarious calibration (SVC) reduces the reliability of the Level-2 OLCI products. For example, the application of these SVC gains to the OLCI data for the regionally adapted v2.1 C2RCC products resulted in RMSD increases of 36% for “conc_tsm”; 118% for “conc_chl”; 33% for “iop_agelb”; 50% for “iop_adg”; and 10% for “kd_z90max” using a ±3h validation window. The findings indicate that the current EUMETSAT SVC gains should be applied and interpreted with caution in the region of study at present. A key outcome of the paper recommends the development of a regionally specific SVC against AERONET-OC data for the region.

Supplementation with 200% of the recommended daily dietary quantity of copper modified vascular contraction and relaxation through increased reactive oxygen species (ROS) and prostaglandin formation, which modified the antioxidant status of middle–aged rats. In this study, young (1 month old) male Wistar rats (n/group = 10) received a diet supplemented with 6.45 mg copper/kg (100%—Group A) for 8 weeks. The experimental group received 12.9 mg copper/kg of diet (200%—Group B). Experimental supplementation with 200% copper increased the copper concentration in the blood, liver, and kidneys; increased the ROS concentration in the aortic rings; and enhanced the sensitivity of the aortic rings to acetylcholine. We observed increased participation of nitric oxide (NO) derived from inducible NO synthase (iNOS) in vascular contraction and a decreased net effect of vasodilator prostanoids derived from cyclooxygenase–2 (COX–2) in vascular relaxation. Supplementation with 200% copper was less significant than expected after previous studies conducted with middle–aged rats.

This study employed High-Performance Liquid Chromatography coupled with Diode Array De-tector and Mass Spectrometry (HPLC-DAD-MS) to characterize bioactive compounds in olive leaf extracts. The analysis revealed a diverse metabolic profile, predominantly composed of tyrosol, flavonoids, and hydroxycinnamic acid. The antioxidant activity of the extracts demonstrated their efficacy, with variations observed between neutral and acidic pH conditions. Encapsulation was explored as a preservation method, successfully maintaining the integrity of phenolic compounds in both liquid and powdered forms. All four extracts have an undeniable antimicrobial effect. Moreover, the antibacterial activity tested on E. coli ATCC 25922 and S. aureus ATCC 25923 strains significantly improved post-encapsulation, particularly for the acidic pH extract. The findings suggest that encapsulation can potentially conserve and/or enhance the antimicrobial activity of olive leaf extract, paving the way for developing functional products with improved shelf life and nutritional properties. Further investigations are recommended to elucidate underlying mecha-nisms and optimize encapsulation processes to maximize the benefits of olive leaf extract in di-verse applications.

The most relevant fungal disease of the olive tree in Portugal is anthracnose, which has negative effects on fruit destruction and consequently on the yield and quality of the olive oil. Moreover, the loss of quality caused by olive fruit fly is associated with the presence of fungi in the galleries made by the larvae. The present study focuses on the effect of olive anthracnose and olive fly on the content of bioactive compounds, namely on hydroxytyrosol (HYT) and its derivatives (health claim) in olive oils extracted from 'Galega Vulgar' and 'Cobrançosa' cultivars. The olives, with different damage levels (olive fly and anthracnose disease), were harvested in Castelo Branco (Center of Portugal) in organic rainfed orchards, at four harvest times during 2019, 2020 and 2021 harvest years. The fruits were immediately submitted to olive oil extraction. The results of the quality criteria show that Galega olive oils extracted from olives with a higher anthracnose incidence show no conformity for the Extra Virgin Olive Oil (EVOO) and Virgin Olive Oil (VOO) categories, with high acidity values and negative sensory notes accompanied by the disappearance of oleacein (the main phenolic compound of both monovarietal olive oils). Conversely, no sensory defects were observed in Cobrançosa olive oils extracted from fruit with high anthracnose and olive fly incidence. Moreover, despite a decrease in all the positive attributes associated with the cultivar, namely in oleacein and oleocanthal contents, quality criteria were still in accordance with the EVOO category. The total HYT and tyrosol (TYR) content (&gt; 5 mg/20g) allows the use of the health claim on the label of all the analysed Cobrançosa olive oils.

The progress in markerless technologies is bringing clinicians tools to rapidly evaluate tests such as Timed Up and Go (TUG) without compromising the time of the assessment, yet it raises questions about the potential trade-off in accuracy compared to traditional marker-based systems, suggesting that the precision of these evaluations is not yet conclusively established. The OpenCap system is an easy tool to process 3D kinematics with two iPhone cameras placed in front of the subject. Previous research has primarily focused on walking and movement towards the cameras with the subject facing the cameras (WF) and thus has been unable to disentangle the differences in the movement directions. We have compared the OpenCap system with a standard marker-based system for both walking directions. In OpenCap, we found significantly worse results capturing walking facing away from the cameras (RW). Compared to the marker-based system, our findings indicate troubles measuring kinematic parameters but provide good accuracy in measuring spatial-temporal parameters. These insights pave the way for refining markerless assessment technologies, potentially enhancing their utility in clinical settings.

In strawberry cultivation, precise disease management is crucial for maximizing yields and reducing unnecessary fungicide use. Traditional methods for measuring Leaf Wetness Duration (LWD), a critical factor in assessing the risk of fungal diseases such as botrytis fruit rot and anthracnose, have been reliant on sensors with known limitations in accuracy and reliability and difficulties with calibrating. To overcome these limitations, this study introduced an innovative algorithm for leaf wetness detection systems employing high-resolution imaging and deep learning technologies, including convolutional neural networks (CNNs). Implemented at the University of Florida's Plant Science Research and Education Unit (PSREU) in Citra, Florida, USA and expanded to three additional locations across Florida, USA, the system captured and analyzed images of a reference plate to accurately determine the wetness and, consequently, the LWD. The comparison of system outputs with manual observations across diverse environmental conditions demonstrated the enhanced accuracy and reliability of the artificial intelligence-driven approach. By integrating this system into the Strawberry Advisory System (SAS), this study provided an efficient solution to improve disease risk assessment and fungicide application strategies, promising significant economic benefits and sustainability advances in strawberry production.

Six solvent fractions isolated from flower bud and leaf ethanolic extracts of Cleistocalyx operculatus were analyzed for their phytochemical contents including phenolics, flavonoids, saponins, tannins, and alkaloids. Antioxidant activities were measured using the ABTS, DPPH, and FRAP assays. The results showed that flower bud aqueous fraction (BAF) and leaf aqueous fraction (LAF) rich in phenolic content (768.18 and 490.74 mg GAE/g dry extract, respectively) exhibited significantly higher antioxidant activities than other fractions. Flower bud hexane fraction (BHF) had remarkably high flavonoid and saponin contents (134.77 mg QE/g and 153.33 mg OA/g dry extract, respectively), followed by that of leaf hexane fraction (LHF) (76.54 mg QE/g and 88.25 mg OA/g dry extract, respectively). BHF and LHF were found to have extremely high antibacterial activity against two H. pylori strains ATCC 51932 and 43504 (MICs of 125 µg/ml). Interestingly, DMC (2’,4’-Dihydroxy-6’-methoxy-3’,5’-dimethylchalcone) isolated from BHF displayed greater antibacterial activity against the bacterial strains (MICs of 25–50 µg/ml) than those of the fractions. In addition, DMC presented potent inhibitory effects on H. pylori-urease (IC50 of 3.2 µg/ml) and α-amylase (IC50 of 83.80 µg/ml), but no inhibition against α-glucosidase. It was also demonstrated that DMC showed its pronounced inhibitory effects on urease activity and biofilm formation of H. pylori, and could increase the membrane permeability of the bacterial cells. Scanning electron micrographs depict that BHF and DMC had strong effects on the cell shape and significantly induced distortion and damage of the cell membrane. The fractions and DMC showed no significant toxicity to four tested human cell lines. Efforts to reduce antibiotic use indicate the need for further researches of the flower buds and DMC as potential products to prevent or treat gastric H. pylori infections.

Senna rugosa is a species found in the Cerrado and used in folk medicine as a vermifuge and in the treatment of poisonous snakebites accidents. In this work, we identified the main secondary metabolites present in ethanolic extracts of the leaves (ELSR) and roots (ERSR) of S. rugosa and evaluated the potential cytoprotective effect against cellular macromolecular damage, as well as the cytotoxic properties of the extracts on the K562 and Jurkat leukemic cell lines. The identification of metabolites was done by liquid chromatography coupled with mass spectrometry. The antioxidant activities were investigated by direct ABTS•+ and DPPH• radical scavenging methods, protection against oxidative damage in proteins and DNA. The cytotoxic properties were investigated against healthy cells, isolated from human peripheral blood (PBMC) and leukemic cell lines. The leaf extract contains catechin, rutin, epigallocatechin derivatives, kaempferol glycosides, luteolin, and dimeric and trimeric procyanidins, while the root extract profile shows obtusichromoneside derivatives, 2-methoxystypandrone, stilbene derivatives, naphthopyranones, and flavanone derivatives. The extracts showed antioxidant activity, with IC50 of 4.86 ± 0.51 µg/mL and 8.33 ± 0.90 µg/mL in the ABTS assay for ELSR and ERSR, respectively. And in the DPPH• assay, the IC50 was 19.98 ± 1.96 µg/mL for ELSR and 13.37 ± 1.05 µg/mL for ERSR. The extracts protected macromolecules against oxidative damage at concentrations of 5 µg/mL. The cytotoxicity test against leukemic strains was observed after 24 and 48 hours of treatment. After 48 h, results against the K562 cell line demonstrate IC50 of 242.54 ± 2.38 µg/mL and 223.00 ± 2.34 µg/mL for ELSR and ERSR , respectively. While against the Jurkat cell line, these extracts showed IC50 of 171.45 ± 2.25 µg/mL and 189.30 ± 2.27 µg/mL, respectively Results on PBMC viability, demonstrate that the extracts showed selectivity for the leukemic cell lines. Together, our results reveal that the leaves and roots of S. rugosa have completely distinct and complex chemical compositions. This study expands the repertoire of identified chemical compounds and underscores their significant pharmacological potential in conditions related to oxidative stress and leukemia.

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible to occur and hence lead to economic and human catastrophes. The aim of this document is precisely to characterise the mechanical crack growth behaviour of the 51CrV4 spring steel representative of leaf springs under cyclic conditions, that is, crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio are also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

Tomato leaf curl disease (TLCD) is the most common viral disease in the tomato plant. It is caused by begomoviruses, which are viruses that cause plant development to be slowed. Many of the traditional disease management methods are still in use. They are, however, ineffective and out of date. Modern biotechnology is being used to detect illness in tomato plants as early as possible, thus reducing damage to the plants. Through genetic engineering, the spread of viruses may be controlled or prevented entirely. Here reviewed many methods for decreasing or eliminating the viral influence on crop growth through biotechnology and genomics. We also investigated the possibility of genetic engineering to reduce or remove the virus TLCD impact on tomato crop development.

Microencapsulation using polymer materials is a potent process to protect and prolong the survival of probiotics. Cissampelos pareira leaf contains natural gelling agents that possess solidifying properties. This study aimed to investigate the development of microencapsulation containing Lacticaseibacillus paracasei using C. pareira extract as a natural encapsulating material. The absorption bands near 1603 cm−1 and 1725 cm−1 detected by Infrared spectroscopy (FTIR) were identified as pectin in C. pareira structure. The L. paracasei-C. pareira microcapsules (LP-CP) showed high encapsulation efficiency by 90.5% which was confirmed by the evaluation of their survival rate. Under thermal conditions (85oC), bacterial viability detected in the microcapsules was 69% as opposed to non-encapsulated bacteria where viability was as low as 5%. Furthermore, the microcapsule presented 75% bacterial viability whereas the free cells showed 30% under acidic conditions (pH 2). During storage conditions, LP-CP viability remained at 50% when the storage time was extended to 90 days whereas, the survival rate of free cells significantly decreased by 100% after 90 days. This information suggests that C. pareira is a potent polymer which can be used as an eco-friendly material for the microencapsulation of probiotics relevant as dietary supplementation for humans or animals.

Lettuce (Lactuca sativa) is a leafy vegetable that provides a valuable source of phytonutrients for a healthy human diet. Assessment of plant growth and composition is vital for determining crop yield and overall quality, however, classical laboratory analyses are slow and costly. Therefore, new, less expensive, more rapid, and non-destructive approaches are being developed, including those based on (hyper)spectral reflectance. Additionally, it is also important to determine how plant phenotypes respond to fertilizer treatments and whether these differences in response can be detected from analyses of hyperspectral image data. In the current study, we demonstrate the suitability of hyperspectral imaging in combination with machine learning models to estimate the content of chlorophyll (SPAD), anthocyanins (ACI), glucose, fructose, sucrose, vitamin C, β-carotene, N, P, K, dry matter content, and plant fresh weight. The implemented five classification and regression machine learning models showed high accuracy in classifying the lettuces by the applied fertilizers treatments and estimating nutrient concentrations. To reduce the input (predictor data, i.e., hyperspectral data) dimension, 13 principal components were found and applied in models. The implemented artificial neural network models of the machine learning algorithm demonstrated high accuracy (r = 0.85 ... 0.99) in estimating fresh leaf weight, and contents of chlorophyll, anthocyanins, N, P, K, and β-carotene. The four applied classification models of machine learning demonstrated 100% accuracy in classifying the studied baby leaf lettuces by phenotype when certain fertilizer treatments were applied.

The origin of a product, consumer familiarity, and purchasing identity are factors that affect perception of cheese consumption. The present study aims at identifying consumers’ conceptualizations and attitudes towards local Greek cheeses of the North-Aegean Sea islands, such as Ladotyri, Graviera, Kasseri, Kaskavali, Melichloro, and Kalathaki, some of which have a Protected Designation of Origin (PDO) status, as opposed to cheeses of non-Greek origin, such as Cheddar, Regatto, and Gouda. Sensory and emotional attributes of local, local PDO, and imported cheeses, and drivers associated with consumers’ choice and acceptance above and beyond their sensory attributes were studied, using three methods: a) Flash Profile to gain insight into the sensory positioning of products and description of samples, b) qualitative analysis of focus groups to pinpoint consumer knowledge, preference, and consumption criteria, and c) a new methodology for natural language processing and sentiment analysis of social media posts to determine consumer conceptualizations. Social media posts have proven to be a valuable source of linguistic and cultural data for cheeses. Local cheeses, including PDO products, were found to be linked to village life and family gatherings, home, tradition, and childhood memories, with saltiness and hardness being their main sensory attributes. Imported cheeses were linked to fast food, pizza, and snacking, with elasticity and gumminess as prominent sensory qualities. The main criterion of purchase was intended usage and versatility, taste and texture, price, and familiarity. The findings provide key sensory attributes, information about consumer purchasing criteria, and relevant vocabulary for the promotion of cheeses as agri-food and gastronomic identity key products.

Pepper leaf segmentation plays a crucial role in monitoring pepper leaf diseases in various backgrounds and ensuring the healthy growth of peppers. However, existing transformer-based segmentation methods suffer from computational inefficiency, excessive parameterization, and limited utilization of edge information. To tackle these challenges, we propose an adaptive multi-scale MLP framework, named AMS-MLP, which combines the multi-path aggregation module (MPAM) and the multi-scale context relation mask module (MCRD) to refine the object boundaries in pepper leaf segmentation. AMS-MLP consists of an encoder-based network, an adaptive multi-scale MLP (AM-MLP) module, and a decoder network. In the encoder network, the MPAM module effectively fuses five-scale features to generate a single-channel mask, improving the accuracy of pepper leaf boundary extraction. The AM-MLP module divides the input features into two branches: the global multi-scale MLP branch captures long-range dependencies between image information, while the local multi-scale MLP branch focuses on extracting local feature maps. Adaptive attention mechanism is designed to dynamically adjust the weights of global and local features. The decoder network incorporates the MCRD module into the convolutional layer, enhancing the extraction of boundary features. To verify the performance of the proposed method, we conducted extensive experiments on three pepper leaf datasets with different backgrounds. The results demonstrate mIoU scores of 97.39%, 96.91%, and 97.91%, as well as F1 scores of 98.29%, 97.86%, and 98.51%, respectively. Comparative analysis with U-Net and state-of-the-art models reveals that the proposed method dramatically improves the accuracy and efficiency of pepper leaf image segmentation.

Soil-borne Trichoderma spp. have been extensively studied for their biocontrol activities against pathogens and growth promotion ability with plants. However, the beneficial effect of Trichoderma on inducing resistance against insect herbivores has been considered only recently. Among diverse Trichoderma species, consistent with previous reports, we showed that root colonization by T. virens triggered induced systemic resistance (ISR) to leaf-infecting fungal pathogens. Whether T. virens induces ISR to insect pests has not been tested before. In this study, we investigated whether T. virens affects jasmonic acid (JA) biosynthesis and defense against fall armyworm (FAW) and western corn rootworm (WCR). Unexpectedly, the results showed that T. virens colonization of maize seedlings grown in autoclaved soil suppressed wound-induced production of JA, resulting in reduced resistance to FAW. Similarly, the bacterial endophyte Pseudomonas chlororaphis 30-84 suppressed systemic resistance to FAW due to reduced JA. Further comparative analyses of the systemic effects of these endophytes when applied into sterile or non-sterile field soil showed that both T. virens and P. chlororaphis 30-84 triggered ISR against hemibiotrophic fungal pathogen Colletotrichum graminicola in both soil conditions, but only suppressed resistance to FAW in sterile soil. In contrast to the effect on FAW defense, T. virens colonization of maize roots suppressed WCR larvae survival and weight gain. This is the first report suggesting the potential role of T. virens as a biocontrol agent against WCR.

Leaf color mutants (LCMs) are important resources for studying diverse metabolic processes such as chloroplast biogenesis and differentiation, pigments’ biosynthesis and accumulation, and photosynthesis. However, in Dendrobium officinale, LCMs are yet to be fully studied and exploited due to the unavailability of reliable RGs (reference genes) for qRT-PCR (quantitative real-time reverse transcription PCR) normalization. Hence, this study took advantage of previously released transcriptome data to select and evaluate the suitability of ten candidate RGs, including Actin (Actin), polyubiquitin (UBQ), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), elongation factor 1-α (EF1α), β-tubulin (β-TUB), α-tubulin (α-TUB), 60S ribosomal protein L13-1 (RPL13AD), aquaporin PIP1-2 (PIP1-2), Intima protein (ALB3) and Cyclin (CYCB1-2) for normalizing leaf color-related genes’ expression levels via qRT-PCR. Stability rankings analysis via common software Best-Keeper, GeNorm, and NormFinder disclosed that both ten genes met the requirements of RGs. Of them, EF1α exhibited the highest stability and was selected as the most reliable. The reliability and accuracy of EF1α were confirmed through qRT-PCR analysis of fifteen chlorophyll pathway-related genes. The expression patterns of these genes via EF1α normalization were consistent with the results by RNA-Seq. Our results will pave the way for molecular dissection of leaf color mutations in D. officinale.

Accordingly, a lot of dry direct seeding rice would be dense planted, that the initial seedling quantity could approach or even exceed the targeted effective panicle number. While limit information is available to evaluate the effects of involved novel nitrogen application methods, that total nitrogen once applied at a determined leaf age stage, on the yield formation traits of such dense planted dry direct seeding rice. The two-year experiments with total 180 kg ha-1 nitrogen once applied time treatments at sixth (L6), seventh (L7), eighth (L8), ninth (L9) and tenth (L10) leaf age stages were carried out. Results showed that the above-ground dry matter weight at maturity and grain yield of L8 was 2.1% ~ 11.8% and 4.0% ~ 9.9% higher than those of other treatments. Compared to other treatments, the higher above-ground dry matter weight after heading stage, bigger mean leaf area index with higher leaf area index at heading stage, increased leaf area duration, crop growth rate and net assimilation rate from jointing to heading period were important traits of higher grain yield formation of L8. In addition, the L8 had relative higher grain-leaf ratio traits than other treatments. Overall, a total 180 kg ha-1 nitrogen with mixed urea and compound fertilizer once applied at eighth leaf age stage would be suggest a useful high yield cultivation method for dense planted dry direct seeding rice in rice-wheat rotation system.

(1) Background: Since microplastics in the aquatic environment are difficult to prevent and can cause adverse physiological and biochemical reactions to various organisms, we aimed to analyze the effectiveness of an eco-friendly removal method using aquatic plants with high ornamental value and excellent water purification ability. (2) Methods: Iris pseudacorus and Lythrum anceps were planted in tap water contaminated with microplastics to analyze the removal rate and root adsorption of microplastics. (3) Results: The amount of microplastics in the planting boxes of Iris pseudacorus and Lythrum anceps was significantly reduced, and the adsorption of microplastics on the roots was confirmed. (4) Conclusions: It was found that the removal of microplastics in water by aquatic plants is effective and that microplastic pollution does not significantly affect plant growth. However, the removal of microplastics by adsorption on plant roots may be affected by various environmental factors, so it is necessary to consider various limitations.

Variability in traits forming the Leaf Economics Spectrum (LES) among and within crop species play a key role in governing agroecosystem processes. However, studies evaluating the extent, causes, and consequences of within-species variation in LES traits for some of the world’s most common crops remain limited. We quantified variation in nine leaf traits measured across 90 vines of five wine grape (Vitis vinifera) varieties at two ontogenetic stages. Grape traits covary along an intraspecific LES, in patterns similar to those documented in wild plants. Across varieties, high rates of photosynthesis (A), and leaf nitrogen (N) concentrations, are coupled with low leaf mass per area (LMA), while the opposite suite of traits defines the “resource conserving end” of this intraspecific LES in grape. Variety identity predicted of leaf physiological (A) and morphological traits (i.e., leaf area and leaf mass), while leaf chemical traits and LMA were best explained by ontogenetic stage. All varieties expressed greater resource conserving trait syndromes (i.e., higher LMA, lower N, lower Amass) later in the growing season. Traits related to leaf hydraulics, including instantaneous water-use efficiency (WUE), were unrelated to LES and other resource capture traits, and were better explained by spatial location. Our results highlight the relative contributions of genetic vs. phenotypic factors in structuring this variation and point to a key role of domestication in governing trait relationships in the world’s crops.

Abstract: Peptide pools composed of short amino acid sequences have proven to be versatile tools in various research areas and clinical applications. They are powerful tools for epitope mapping, immunotherapy, and vaccine development. Their importance lies in their ability to map complex protein structures, enabling a comprehensive understanding of immune responses and facilitating the identification of potential therapeutic agents. The application of peptide pools also extends to the field of personalized medicine, offering tailored solutions for diseases such as cancer and infectious diseases. Peptide pools are complex mixtures of immunostimulatory antigens primarily intended for T-cell stimulation. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products with limited stability. This makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. None of these are routinely available for these products. Synthesis and purification of all labeled peptides might be required. Usually, this approach would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, which would worsen the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector (at 214 nm) for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein-Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.

Green leaf volatiles (GLVs) are important in giving grape a fresh and green aroma. But the changes in GLVs during the phenological development of grapevines are not well known. This study analysed the GLVs and transcription levels of associated biosynthetic genes in six grape species from the Loess Plateau region at five stages of maturation. Thirteen GLVs were detected, showing unique patterns for each grape type at various growth phases. The primary components in six grapes were (E)-2-Hexenal, (E)-2-Hexen-1-ol, and Hexanal. With the exception of Cabernet Franc in 2019, the overall GLV contents of the six types generally increased during growth and development, peaking or stabilizing at harvest. And Sauvignon Blanc, Cabernet Gernischt, and Cabernet Sauvignon exhibited higher total contents among the varieties. Correlation analysis revealed a strong positive correlation between the levels of Hexanal, 1-Hexanol, (E)-2-Hexen-1-ol, (Z)-3-Hexenyl acetate, Nonanal, and (E, E)-2,6-Nonadienal and the expression of VvHPL and VvAAT genes in the LOX-HPL pathway. Specifically, VvHPL emerges as a potential candidate gene responsible for species-specific differences in GLV compounds. Comprehending the changing patterns in the biosynthesis and accumulation of GLVs offers viticulturists and enologists the opportunity to devise targeted strategies for improving the aromatic profile of grapes and wines.

The tea leaf paradox (TLP) describes unsteady fluid motions which help entrain and deposit suspended particles at the center of rotation. Various applications depend on the TLP for particle separations spanning across orders of magnitude in length scales and is an important problem in fluid mechanics. Despite papers describing the phenomena, the efficacy of particle separation using the TLP remains unclear as to the relative importance of for example hydrostatics, particle-fluid density ratio, wall friction, liquid bath aspect ratio and the rotation speed. The dynamics involved are notably complex and require a careful tuning of each variable. In this study, we have investigated the role of the limit of the aggregation dynamics in rotational flows within 3D-printed vessels of various sizes in tandem with particle imaging to probe the dissipation effects on the particle motions. We have found that the liquid bath aspect ratio limits how much aggregation may occur for a particle-fluid density ratio greater than unity (e.g., $\rho_p/\rho_f >1$, where $\rho_p$ is the density of the particle and $\rho_f$ is the ambient fluid density.

Sphingolipids are ubiquitous in eukaryotes and certain prokaryotes, where they serve as vital components of biological membranes and as bioactive molecules. Chloroplasts have complex membrane structures that play crucial roles in photosynthesis, but their specific sphingolipidome remains unreported. In this study, we used high-performance liquid chromatography-mass spectrometry (HPLC-MS/MS) to analyze the sphingolipidome of purified Arabidopsis thaliana chloroplasts. We detected 92 chloroplast sphingolipids. The chloroplast sphingolipidome differed from total leaf (TL) samples, having a higher content of free long-chain bases and hydroxyceramides, and a greater proportion of complex sphingolipids with 16C fatty acid (FA) forms. Notably, chloroplast glucosylceramides were predominantly the d18:1 h16:0 and t18:1 h16:0 forms, rather than the 24C FA form found in TL and other cellular structures. Comparing the sphingolipidomes of different cellular structures underscores the inhomogeneity of intracellular distribution of sphingolipids. This provides a robust reference for further elucidating the function of sphingolipids in plant cells.

In large-scale parallel computing and communication systems, an interconnect network structure is usually modeled as a graph, in which vertices and edges correspond to processors and communication links, respectively. In a graph, the vertices and edges are likely to fail, so we must think about the fault tolerance of a graph. Connectivity is an important parameter in the study of faulty tolerance for a graph. In this paper, we study a special class of connectivity: $m$-component connectivity, this is a natural generalization of the classical connectivity of graphs defined in terms of the minimum vertex-cut. Let $F$ is a vertex set of $G$ $(i.e, F\subseteq V(G))$, if the following conditions are satisfied, we say $F$ is a $m$-component cut: $(1)$ $G-F$ is disconnected; $(2)$ the number of components in $G-F$ is greater than or equal to $m$. In another word, the $m$-component connectivity $c\kappa_{m}(G)$ is defined as $min\{|F|~|~F\subseteq V(G)$ and $F$ is a $m$-component cut$\}$. Determining $m$-component connectivity is still unsolved in most interconnection networks even for small $m'$s. Leaf-sort graph is a special Cayley graph, it has many special properties that are different from other Cayley graphs. So we need to pay attention to some of it's special properties when we study it. In this paper, we can get the values: $c\kappa_{3}(CF_{n})=3n-6$ $(n$ is odd$)$ and $c\kappa_{3}(CF_{n})=3n-7$ $(n$ is even$)$ for $n\geq3$; $c\kappa_{4}(CF_{n})=\frac{9n-21}{2}$ $(n$ is odd$)$ and $c\kappa_{4}(CF_{n})=\frac{9n-24}{2}$ $(n$ is even$)$ for $n\geq4$; $c\kappa_{5}(CF_{n})=6n-16$ $(n$ is odd$)$ and $c\kappa_{5}(CF_{n})=6n-18$ $(n$ is even$)$ for $n\geq5$.

Natural rubber is an important national strategic and industrial raw material. Leaf anthracnose of rubber tree caused by the Colletotrichum species is one of the important factors restricting the yield of natural rubber. In this study, we isolated and identified strain Bacillus velezensis SF334 that exhibited significant antagonistic activity against both of C. australisinense and C. siamense, the dominant species of Colletotrichum causing leaf anthracnose of rubber trees in Hainan province of China, from a pool of 223 bacterial strains. The cell supernatants of SF334 had a significant prevention effect for leaf anthracnose of rubber tree with an efficacy of 79.67% against C. siamense and 71.8% against C. australisinense, respectively. We demonstrated that SF334 can lead to the lysis of C. australisinense and C. siamense mycelium by causing mycelial expansion, resulting in mycelial rupture and subsequent death. B. velezensis SF334 also harbors some traits of plant growth-promoting rhizobacterium such as secreting siderophore, protease, cellulose, pectinase and auxin of indole-3-acetic acid (IAA), as well as has broad-spectrum antifungal activity against some important plant pathogenic fungi. The genome combined with comparative genomic analyses indicated that SF334 possesses most genes of the central metabolic and secondary metabolites of B. velezensis strains. To our knowledge, this is the first time to report a Bacillus velezensis strain as a promising biocontrol agent against leaf anthracnose of rubber tree caused by C. siamense and C. australisinense. The results suggest that B. velezensis could be a potential candidate agent for leaf anthracnose of rubber tree.

The main purpose of our research is the evaluation of the efficacity of solvent polarity on phenolic composition, as well as the antibacterial, and antioxidant activities of extract of Moroccan Mentha aquatica L., leaves. To attempt these objectives, the HPLC-DAD was used to identify the biomolecules. The total amount of phenolic and flavonoid content was determined using the Folin-Ciocalteu and aluminum trichloride processes as well as the DPPH, RP, and TAC tests were used to evaluate the antioxidant capabilities. In addition, by employing both in vitro and in silico analysis through the microdilution method, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extracts were assessed against multidrug-resistant bacteria. Furthermore, the High-Performance Liquid Chromatography (HPLC) analysis indicated that all extracts of M. aquatica were abundant in noteworthy phytochemical compounds, especially gallic acid, vanillic acid, chlorobenzoic acid, quercetin, and kaempferol. Furthermore, the results indicated that the total phenolic content was higher in hydroethanolic extract (62.19 ± 1.19 mg GAE/g DW) in contrast to the acetonic and aqueous extracts (22.22 ± 0.64, and 22.44± 0.57 mg GAE/g DW) respectively. Similarly, the aqueous ethanol extract contained the greatest flavonoid concentration, with values of 29.15± 0.09 mg QE/g DW when compared with the other extracts. The seam extract poses excellent antioxidant power with an IC50 of 0.06 ± 0.00 mg/mL for the DPPH test, and lower RP with EC50 of 80± 0.00 µg/ml when compared with acetonic and aqueous extract (370± 0.00 and 460± 0.01 µg/mL) respectively. Moreover, the hydroethanolic extract has a high level of TAC 75.09± 2.00 mg EAA/g DW, followed by aqueous extract carrying a value of 28.53 ± 1.36 mg EAA/g DW. The antibacterial capacity is ranged between 0.78 ± 0.05 mg/mL and 12.60 ± 0.00 mg/L. The results of the in-silico study demonstrated that quercetin, vanillic acid, and naringenin components contribute to the antioxidant capability. While gallic acid, kaempferol, and quercetin components are attributed to the antibacterial capacity.

Experimental systems to simulate future elevated CO2 conditions in the field often have large, rapid fluctuations in CO2. To examine possible impacts of such fluctuations on photosynthesis, intact leaves of field grown plants of five species were exposed to two-minute cycles of CO2 between 400 and 800 mol mol-1 lasting a total of 10 minutes, with photosynthesis, stomatal conductance and PSII fluorescence measured at the end of each half-cycle, and also 10 minutes after the end of the cycling. Prior to the cyclic CO2 treatments, steady-state responses of leaf gas exchange and fluorescence to CO2 were determined. In four of the five species, in which stomatal conductance decreased with increasing CO2, the cyclic CO2 treatments reduced stomatal conductance. In those species, both photosynthesis and the photochemical efficiency of PSII were reduced at limiting internal CO2 levels, but not at saturating CO2. In the fifth species, there was no change in stomatal conductance with CO2, and no change in either photosynthesis or PSII efficiency at any CO2 level with CO2 cycling. It is concluded that in many, but not all, species fluctuations in CO2 may reduce photosynthesis at low CO2 partly by decreasing the photochemical efficiency of photosystem II, as well as by decreasing stomatal conductance.

Globally, the gastroenteritis or diarrhoea has become a more significant problem today due to infection caused by foodborne/ waterborne pathogen Vibrio cholera. In this concern, an investigation was carried out to evaluate the vibriocidal potential of the different solvent extracts of leaf and rhizome of Maranta arundinacea under in vitro condition. For this, aqueous, methanolic, ethanolic and hexane extracts of both leaf and rhizome of M. arundinacea were tested against the pre-isolated strains of Vibrio cholerae such as SPAB1, SPAB4 and SPAB5 by agar well diffusion and minimum inhibitory concentration (MIC) method. All the solvent extracts of both leaf and rhizome were found to be active against the tried strains of V. cholera however, ethanolic extract showed maximum inhibitory effect against SPAB1 strain with an inhibition zone of 26.23 ± 0.53 mm (MIC of 80.00 ± 10.06 µg/ ml) and 24.27 ± 0.12 mm (MIC of 100.00 ± 12.82 µg/ ml) in rhizome and leaf samples, respectively. Then, the effectiveness was followed in SPAB4 and SPAB5 however, it was not much more significant to that of SPAB1. Therefore, it was suggested that the rhizome and leaf extracts which proved to be potentially effective can be used as the natural alternative for the treatment of diarrhoea caused by Vibrio infection.

Results showed that mulberry leaves could significantly reduce backfat thickness (P&lt;0.05) and increase intramuscular fat (IMF) content (P&lt;0.05). Lipidomics analysis showed that mulberry leaves improved lipid profile composition and increased the proportion of triglycerides (TG). Interestingly, IMF content was positively correlated with acyl C18:2 and negatively correlated with C18:1 of differential TGs. In addition, cecal microbiological analysis showed that mulberry leaves could increase the abundance of bacteria such as UCG−005, Muribaculaceae_norank, Prevotellaceae_NK3B31_group, Limosilactobacillus, and so on. At the same time improve the L-tyrosine-baton rouge ester, Oleic acid methyl ester, 21-deoxycortisol, N-acetyldihydrosphingosine, Mulberrin relative abundance. In this study, we found that mulberry leaves could extremely significantly increasing the mRNA relative expression of lipoprotein lipase (LPL), fatty acid-binding protein 4 (FABP4) and peroxisome proliferators-activated receptor γ (PPARγ) in muscle (P＜0.01), significantly increasing mRNA relative expression of diacylglycerol acyltransferase 1 (DGAT1) (P＜0.05) and significantly decreasing the mRNA relative expression of acetyl CoA carboxylase (ACC) (P＜0.05), and aignificantly upregulated hormone-sensitive triglyceride lipase (HSL), peroxisome proliferators-activated receptor α (PPARα) mRNA relative expression (P＜0.05) in backfat. In addition mulberry leaves could increased serum leptin and adiponectin (P＜0.01). Ultimately lead to up-regulation of IMF and down-regulation of backfat.

Questionnaires for self-report of food-elicited emotions are an established practice in consumer studies. However, most tools are originally developed in English and translated into other languages, which limits their use. The aim of this study was to develop the first Greek emotion lexicon and measurement tool for consumers, using standard methodology and extending it. The lexicon was compiled using linguistic sources and extended using the World Wide Web and a popular social media platform for the collection of authentic language and usage data. Terms were also collected from consumers using questionnaires and a variety of stimuli. Terms collected from consumers only comprise: healthy, distrustful, curious, childish, impressed, tolerant, impatient It was validated by application in various case studies, providing discrimination across and within food categories, and by comparison to the Greek translation of a standard tool in English, the EsSense Profile. The comparison was conducted by measuring emotions elicited by six food categories and demonstrated that it is preferable to use emotion measurement tools developed in the linguistic and cultural context of intended use, as they convey consumers’ emotions naturally and more accurately. This tool can be used as a Check- or Rate- All-That-Apply questionnaire to measure consumer responses to food categories and products. The methodology and validation presented can be applied for the compilation of emotion lexicons in languages less studied than English.

Staphylococcus aureus and coagulase-negative staphylococci account for about 80% of infections associated with medical devices and are associated with increased virulence due to their ability to form biofilm. In this study, we aimed to construct a comprehensive reference map followed by significant pathway analysis in the proteome of S. aureus biofilm grown for 3-days as compared with 24 h planktonic using a high-resolution TMT based MS. We identified proteins associated with secondary metabolites, ABC transporters, biosynthesis of amino acids, response to stress, and amino sugar and nucleotide sugar metabolism were significantly upregulated in the 3-day biofilm. In contrast, proteins associated with virulence factors, microbial metabolism in diverse environments, translation, and energy metabolism were significantly downregulated. GO functional annotation indicated that more proteins are involved in metabolic processes, catalytic activity, and binding in biofilm, respectively. Among the significantly dysregulated proteins, hyaluronidase (hysA) in conjunction with chitinase may play a significant role in the elimination and/or prevention of biofilm development. This study advances the current S. aureus subproteomes, identified potential pathways significant to biofilm biology and helped to understand their potential role in S. aureus which may shed light on developing new therapeutic regimes including antibiofilm agents in the treatment of biofilm-infections related with implantable medical devices.

This paper presents machine learning methods for approximate solutions of reaction-diffusion equations with multivalued interaction functions. This approach addresses the challenge of finding all possible solutions for such equations, which often lack uniqueness. The proposed method utilizes physics-informed neural networks (PINNs) to approximate generalized solutions.

The aim of this work was to classify the business incubators in Spain according to the four phases of the startup’s incubation process. Considering that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the business incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis has been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors. Finally, the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3, named activity monitoring and control, was related to phase 3 or basic incubation variables. Cluster analysis facilitates the grouping of business incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small sized business incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factors 1 and 2. Factor 3, although positive, it is susceptible to improvement. They are the largest group of business incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

Background: Vestibular Neuritis (VN) induces Acute Vestibular Syndrome (AVS). This study aimed to identify predictive factors of VN recovery by healing and/or compensation. Methods: In this longitudinal and prospective study, 40 patients were included. The first assessment (T0) included medical history taking (general and specific), for cardiovascular risk factors (CVRFs), a battery of diagnostic tests, bithermal caloric test (BCT), video Head Impulse Test (VHIT) and skull vibration induced nystagmus (SVIN). All patients also completed a Dizziness Handicap Inventory (DHI). All assessments were repeated 90±15 days (T3) later. Subjective criteria compensation were based on DHI total score and objective criteria compensation on the instrumental test results. Four groups of patients (A, B, C, D) were delineated by combining patients with normal vs abnormal vestibular tests and patients with normal vs abnormal DH. Results: CVRFs were associated with a poorer recovery of symptoms but not the age or BMI. Vestibular tests mainly BCT (canal paresis %), VHIT (lateral semicircular canal gain) and SVINT (nystagmus slow phase velocity) recovered within normal values in 20%, 20%, 26% of cases respectively at T3 for the 40-patient group. Conclusions: Vascular risk factors (hypercholesterolemia) are correlated with patients who do not recover their symptoms either by healing or compensation. The evolution did not show any significant difference between high or low frequency vestibular tests in patients recovering from their symptoms. However, some patients with objective recovery may continue to show persisting subjective symptoms.

The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

The work is devoted to assessing changes in the water regime of the Lan River in modern conditions and the near future with the aim of developing a strategy for the rational use of the water potential of small rivers in the Belarusian Polesie region. There was a tendency towards an increase in annual runoff at the Loktyshi and Mokrovo gauging stations during the study period from 1948 to 2015, which was caused by anthropogenic factors in the form of amelioration measures. Testing the hypothesis about the homogeneity of the runoff series under consideration for periods with different averaging intervals has showed heterogeneity for some types of runoff. This was caused by intensive economic activity, which significantly disrupts the natural hydrological regime. A runoff forecast was made for the Lan River at the Mokrovo gauging station for the period up to 2035 based on archive of meteorological data using a multi-model ensemble of four CMIP5 scenarios. A slight decrease in runoff was predicted, caused by additional evaporation from the water surface of the reservoir due to increased air temperature, as well as a slight shift in the peak of the spring flood to March. Results of calculating of permissible withdrawal of surface water from the Lan River for the needs of the Loktyshi fish farm have shown great influence of the fish farm on the river runoff volume that requires strict adherence to scientifically based regimes for managing the water regime of the Loktyshi Reservoir and the Loktyshi fish farm.

Sixty years ago in the lab adjacent to Fred Sanger (1958 Nobel Prize for protein chemistry), I discovered the cell surface hydroxyproline-rich glycoproteins. Nature keeps some of her secrets longer than others. It has taken many years to dissect the molecular function and biological role of extensins and arabinogalactan proteins (AGPs). Extensins template the formation of new cell walls. AGPs remained baffling and enigmatic until a Eureka moment when computer prediction of AGP calcium binding depicted paired glucuronic acid residues and thus the likely role of a cell surface AGP-Ca²⁺capacitor: In conjunction with the auxin-activated proton pump that releases bound Ca²⁺ it led us to formulate the Hechtian Growth Oscillator as A Global Paradigm with a pivotal role in Ca²⁺ homeostasis. The ramifications are profound. They cannot be shrugged off with sceptical disdain but demand critical reappraisal of current dogma. Phyllotaxis is an ancient problem; it involves an essential role for auxin and the auxin efflux “PIN” proteins together with mechanotransduction of stress-strain as phyllotactic determinants. However, a general explanation remains elusive despite much effort, particularly by mathematicians. Here we propose a novel biochemical algorithm: Hechtian oscillator transduction of cell wall stress generates phyllotactic patterns quite independent of a mathematical approach. Plants simply use different rules and follow a different route.

A method based on ultra performance liquid chromatography with diode array detector (UPLC-DAD) was developed for quantitative analysis of five active compounds and chemical fingerprint analysis of Rosa rugosa. Ten batches of Rosa rugosa collected from different plantations in the Xinjiang region of China were used to establish the fingerprint. The feasibility and advantages of the used UPLC fingerprint were verified for its similarity evaluation by systematically comparing chromatograms with professional analytical software recommended by State Food and Drug Administration (SFDA) of China. In quantitative analysis, the five compounds showed good regression (R²=0.999 5) within the test ranges and the recovery of the method was in the range of 94.2–103.8%. The similarities of the fingerprints of 10 batches of the samples were more than 0.981. The developed UPLC fingerprint method is simple, reliable and validated for the quality control and identification of Rosa rugosa. Additionally, simultaneous quantification of five major bioactive ingredients in the Rosa rugosa samples was conducted to interpret the consistency of the quality test. The results indicated that the UPLC fingerprint as a characteristic distinguishing method combining similarity evaluation and quantification analysis, can be successfully used to assess the quality and to identify the authenticity of Rosa rugosa.

Aiming at the problem of small size of some spots on apple leaves and the difficulty of accurate detection of spot targets brought by the complex background of the orchard, this paper takes the alternaria leaf spot, rust, brown spot, grey spot and frog eye leaf spot on apple leaves as the research object, and proposes a high-accuracy detection model YOLOv5-Res and lightweight detection model YOLOv5-Res4 are proposed. Firstly, a multiscale feature extraction module ResBlock is designed by combining the Inception multi-branch structure and ResNet residual idea. Secondly, a lightweight feature fusion module C4 is designed to reduce the number of model parameters while improving the detection ability of small targets. Finally, a parameter streamlining strategy based on optimized model architecture is proposed. The experimental results show that the performance of YOLOv5-Res model and YOLOv5-Res4 model is significantly improved, the [email protected] value is improved by 2.8% and 2.2% compared with YOLOv5s model and YOLOv5n model, respectively, and the size of YOLOv5-Res model and YOLOv5-Res4 model is only 10.8MB and 2.4MB, and the number of model parameters is reduced compared with YOLOv5s model and YOLOv5n model. counts are reduced by 22% and 38.3% compared to the YOLOv5s model and YOLOv5n model.

The few studies dealing with leaf phenological responses to elevated nutrients in forest trees have given ambiguous results, i.e., while some reported delayed leaf-out and autumn leaf senescence, others reported advanced leaf phenology caused by increased nutrition. This study aimed to determine the effects of experimentally increased phosphorus (+P) on the leaf phenologies of two juvenile provenances of common beech and sessile oak. Other objectives were to determine whether there are interspecies differences as well as intraspecies variations. Saplings were excavated in two mixed beech-oak stands and transplanted into four wooden boxes filled with a commercial soil substrate. Phosphorus fertilizer was added to two of the boxes, while the remaining boxes served as controls. Both species responded to +P treatment with advanced autumn leaf senescence in the first year of the experiment. Leaf senescence in common beech began significantly earlier, while in both species, the process was accelerated compared to that in the control. In the second year, the leaf senescence response to +P treatment was even more pronounced in both species. The +P effect on leafing phenology was absent in both common beech provenances and in an oak provenance. However, the other oak provenance showed advanced leafing, indicating the existence of intraspecies differences.

Leaf temperature (T_leaf) influences photosynthesis and respiration. Currently, there is a growing interest on including lianas in productivity models due to their increasing abundance, and their detrimental effects on net primary productivity in tropical environments. Therefore, understanding the differences of T_leaf between lianas and trees is important for future of forest on whole ecosystem productivity. Here we determined the displayed leaf temperature (T_d= T_leaf – ambient temperature) of several species of lianas and their host trees during ENSO and non-ENSO years to evaluate if the presence of lianas affects the T_d of their host trees, and if leaves of lianas and their host trees exhibit differences in T_d. Our results suggest that close to midday, the presence of lianas does not affect the T_d of their host trees; however, lianas tend to have higher values of T_d than their hosts across seasons, in both ENSO and non-ENSO years. Although lianas and trees tend to have similar physiological-temperature responses, differences in T_d could lead to significant differences in rates of photosynthesis and respiration based temperature response curves. Future models should thus consider differences in leaf temperature between these life forms to achieve robust predictions of productivity.

Rotorcrafts operate HUMS for fault diagnosis, but the capabilities of HUMS analysts are important due to the complex mechanical configuration of rotorcraft and the difficulty of analysis. Accordingly, an advanced algorithm is needed to identify faults, and flight data can be used to develop the algorithm. However, flight data contains abnormal or missing data due to problems such as sensor defects, which can be a major problem in algorithm development. Therefore, in this paper, we study a gap filling method using MLP to obtain normal data when there are problems such as abnormal or missing data in rotorcraft flight data. Existing methods typically fill the gap through interpolation or curve fitting using the before and after values of missing data. However, in this study, normal values were estimated using the values of other parameters at the moment of missing or abnormal data occurred. As a result of evaluating the performance of the trained MLP using normal data, it was confirmed that the output of the model well estimates the changing trend of the target. And when abnormal data was applied to the trained model, it was confirmed that point outliers were eliminated and appropriate values were found in the case of missing data.