Amid growing concerns about antibiotic resistance, innovative strategies are imperative in addressing bacterial infections in aquaculture. Quorum quenching (QQ), the enzymatic inhibition of quorum sensing (QS), has emerged as a promising solution. This study delves into the QQ capabilities of the probiotic strain Bacillus velezensis D-18 and its products, particularly in Vibrio anguillarum 507 communication and biofilm formation. Chromobacterium violaceum MK was used as a biomarker in this study, and the results confirmed that B. velezensis D-18 effectively inhibits QS. Further exploration into the QQ mechanism revealed the presence of lactonase activity by B. velezensis D-18 that degraded both long- and short-chain acyl homoserine lactones (AHLs). PCR analysis demonstrated the presence of a homologous lactonase-producing gene, ytnP, in the genome of B. velezensis D-18. The study evaluated the impact of B. velezensis D-18 on V. anguillarum 507 growth and biofilm formation. The probiotic not only controls the biofilm formation of V. anguillarum but also significantly restrains pathogen growth. Therefore, B. velezensis D-18 demonstrates substantial potential for preventing V. anguillarum diseases in aquaculture through its QQ capacity. The ability to disrupt bacterial communication and control biofilm formation positions B. velezensis D-18 as a promising eco-friendly alternative to conventional antibiotics in managing bacterial diseases in aquaculture. Full article

Background: Understanding the dynamics of conduction velocity (CV) and voltage amplitude (VA) is crucial in cardiac electrophysiology, particularly for substrate-based catheter ablations targeting slow conduction zones and low voltage areas. This study utilizes ultra-high-density mapping to investigate the impact of heart rate and pacing location on changes in the wavefront direction, CV, and VA of healthy pig hearts. Methods: We conducted in vivo electrophysiological studies on four healthy juvenile pigs, involving various pacing locations and heart rates. High-resolution electroanatomic mapping was performed during intrinsic normal sinus rhythm (NSR) and electrical pacing. The study encompassed detailed analyses at three levels: entire heart cavities, subregions, and localized 5-mm-diameter circular areas. Linear mixed-effects models were used to analyze the influence of heart rate and pacing location on CV and VA in different regions. Results: An increase in heart rate correlated with an increase in conduction velocity and a decrease in voltage amplitude. Pacing influenced conduction velocity and voltage amplitude. Pacing also influenced conduction velocity and voltage amplitude, with varying effects observed based on the pacing location within different heart cavities. Pacing from the right atrium (RA) decreased CV in all heart cavities. The overall CV and VA changes in the whole heart cavities were not uniformly reflected in all subregions and subregional CV and VA changes were not always reflected in the overall analysis. Overall, there was a notable variability in absolute CV and VA changes attributed to pacing. Conclusions: Heart rate and pacing location influence CV and VA within healthy juvenile pig hearts. Subregion analysis suggests that specific regions of the heart cavities are more susceptible to pacing. High-resolution mapping aids in detecting regional changes, emphasizing the substantial physiological variations in CV and VA. Full article

Introduction: Docetaxel, a taxane used in the treatment of solid tumours, exerts pharmacological activity when in its unbound form. We report a sensitive assay to quantify unbound docetaxel after oral administration of docetaxel plus encequidar (oDox+E). Unbound drug quantification is important due to its direct correlation with drug-related toxicity and therapeutic efficacy. We improve on the sensitivity of current assay methods and demonstrate the utility of the assay on a novel formulation of oral docetaxel. Methods: Ultrafiltration followed by high-performance liquid chromatography and tandem mass spectrometry (HPLC-MS/MS) was utilized. Long-term stability, precision, accuracy, and recovery experiments were conducted to validate the assay. Additionally, patient samples from a Phase I dose-escalation pharmacokinetic study were analyzed using the developed assay. Results: The assay method exhibited long-term stability with an observed change between 0.8 and 6.9% after 131 days of storage at −60 °C. Precision and accuracy quality controls met the FDA acceptance criteria. An average recovery of 88% was obtained. Patient sample analysis demonstrated successful implementation of the assay. Conclusion: A validated sensitive assay was developed with an LLOQ of 0.084 ng/mL using 485 µL of human plasma. The sensitivity of the assay allowed quantification of unbound docetaxel concentrations in an early-phase oDox+E clinical study to compare it against IV docetaxel using pharmacokinetic modelling. Successful development of oDox+E represents an opportunity to replace the current IV docetaxel regimen with an oral regimen with lower cost, decreased side effects, and improve patient quality of life and experience. Full article

As a booming branch of online retailing, live-streaming e-commerce can present abundant information dimensions and diverse forms of expression. Live-streaming e-commerce has enabled online retailers to interact with customers face-to-face, resulting in widespread instances of emotional and impulse buying behavior. Prior research in live-streaming e-commerce has suggested that live streamers’ characteristics, especially the live streamer’s face, can affect customers’ purchase intentions. The present research used questionnaire surveys and an eye tracking experiment to investigate the impact of live streamer’s facial attractiveness on consumer purchase intention for search-based and experience-based products. The questionnaire survey analyzed 309 valid questionnaires and revealed that attractive faces are the key influencing factor driving consumers’ impulse purchase intentions. Moreover, consumers’ emotional experience plays a partial mediating role in the process of live streamers’ faces influencing purchase intention. The eye tracking experiment further explored the mechanism of a live streamer’s facial attractiveness on consumers’ purchase intentions of search-based products and experience-based products from the perspective of visual attention by analyzing 64 valid sets of data. The results showed that attractive faces attract more consumers’ attention and, therefore, increase their purchase intention. Furthermore, there is a significant interaction between product type, the live streamer’s facial attractiveness, and consumers’ purchase intentions. In the case of unattractive live streamers, consumers are more likely to buy search-based products than experience-based products, while the purchase intention does not vary between search-based products and experience-based products in the case of attractive live streamers. The present study provides evidence for ‘beauty premium’ in live-streaming e-commerce and sheds light on the design of the match between live streamers and different types of products. Full article

The escalation of jellyfish stings has drawn attention to severe skin reactions, underscoring the necessity for novel treatments. This investigation assesses the potential of hydroxybenzoic acid derivatives, specifically protocatechuic acid (PCA) and gentisic acid (DHB), for alleviating Nemopilema nomurai Nematocyst Venom (NnNV)-induced injuries. By employing an in vivo mouse model, the study delves into the therapeutic efficacy of these compounds. Through a combination of ELISA and Western blot analyses, histological examinations, and molecular assays, the study scrutinizes the inflammatory response, assesses skin damage and repair mechanisms, and investigates the compounds’ ability to counteract venom effects. Our findings indicate that PCA and DHB significantly mitigate inflammation by modulating critical cytokines and pathways, altering collagen ratios through topical application, and enhancing VEGF and bFGF levels. Furthermore, both compounds demonstrate potential in neutralizing NnNV toxicity by inhibiting metalloproteinases and phospholipase-A₂, showcasing the viability of small-molecule compounds in managing toxin-induced injuries. Full article

While crises, like pandemics, have a negative impact on mental health, hope may affect it positively. However, hope during COVID-19 has hardly been explored. In this study, we explored the hope of interviewees in a podcast on hope in Amsterdam during the COVID-19 pandemic, which sought variations in the gender, spiritual backgrounds, and places of work of the interviewees. Underpinned by hermeneutic phenomenology, we thematically analyzed the six transcribed episodes. We found that the present was sketched as closed down, while hope related to (the potential of) spaces and the future opening up. Sources of hope were the vaccine, good weather, faith and trust, and the history of Amsterdam, which was characterized by resilience. Several participants appreciated their everyday life in a new way: COVID-19 made them slow down and aware of what really mattered, which was a source of hope. Frequently mentioned sources of hope were connections with others, and especially solidarity. Also, showing solidarity was identified as a way of offering hope to others. We conclude that both in our study and in several religions, the link between hope and solidarity is common, and that hope is a spiritual topic that is worth addressing in mental health care. Full article

Background and Objectives: In lumbar spine radiography, the oblique view is frequently utilized to assess the presence of spondylolysis and the morphology of facet joints. It is crucial to instantly determine whether the oblique angle is appropriate for the evaluation and the necessity of retakes after imaging. This study investigates the feasibility of using a convolutional neural network (CNN) to estimate the angle of lumbar oblique images. Since there are no existing lumbar oblique images with known angles, we aimed to generate synthetic lumbar X-ray images at arbitrary angles from computed tomography (CT) images and to estimate the angles of these images using a trained CNN. Methods: Synthetic lumbar spine X-ray images were created from CT images of 174 individuals by rotating the lumbar spine from 0° to 60° in 5° increments. A line connecting the center of the spinal canal and the spinous process was used as the baseline to define the shooting angle of the synthetic X-ray images based on how much they were tilted from the baseline. These images were divided into five subsets and trained using ResNet50, a CNN for image classification, implementing 5-fold cross-validation. The models were trained for angle estimation regression and image classification into 13 classes at 5° increments from 0° to 60°. For model evaluation, mean squared error (MSE), root mean squared error (RMSE), and the correlation coefficient (r) were calculated for regression analysis, and the area under the curve (AUC) was calculated for classification. Results: In the regression analysis for angles from 0° to 60°, the MSE was 14.833 degree², the RMSE was 3.820 degrees, and r was 0.981. The average AUC for the 13-class classification was 0.953. Conclusion: The CNN developed in this study was able to estimate the angle of an lumbar oblique image with high accuracy, suggesting its usefulness. Full article

Drusen are one of the most characteristic pathologies of precursor lesion of age-related macular degeneration (AMD). Drusen comprise a yellowish white substance that accumulates typically under the retinal pigment epithelium (RPE), and their constituents are lipids, complement, amyloid, crystallin, and others. In the past, many researchers have focused on drusen and tried to elucidate the pathophysiology of AMD because they believed that disease progression from early AMD to advanced AMD might be based on drusen or drusen might cause AMD. In fact, it is well established that drusen are the hallmark of precursor lesion of AMD and a major risk factor for AMD progression mainly based on their size and number. However, the existence of advanced AMD without drusen has long been recognized. For example, polypoidal choroidal vasculopathy (PCV), which comprises the majority of AMD cases in Asians, often lacks drusen. Thus, there is the possibility that drusen might be no more than a biomarker of AMD and not a cause of AMD. Now is the time to reconsider the relationship between AMD and drusen. In this review, we focus on early AMD pathogenesis based on basic research from the perspective of cholesterol metabolism and hypoxic response in the retina, and we discuss the role of drusen. Full article

The problem of finding the best path trajectory in a graph is highly complex due to its combinatorial nature, making it difficult to solve. Standard search algorithms focus on selecting the best path trajectory by introducing constraints to estimate a suitable solution, but this approach may overlook potentially better alternatives. Despite the number of restrictions and variables in path planning, no solution minimizes the computational resources used to reach the goal. To address this issue, a framework is proposed to compute the best trajectory in a graph by introducing the mathematical morphology concept. The framework builds a lattice over the graph space using mathematical morphology operators. The searching algorithm creates a metric space by applying the morphological covering operator to the graph and weighing the cost of traveling across the lattice. Ultimately, the cumulative traveling criterion creates the optimal path trajectory by selecting the minima/maxima cost. A test is introduced to validate the framework’s functionality, and a sample application is presented to validate its usefulness. The application uses the structure of the avenues as a graph. It proposes a computable approach to find the most suitable paths from a given start and destination reference. The results confirm that this is a generalized graph search framework based on morphological operators that can be compared to the Dijkstra approach. Full article

This study focuses on the development of a body for an electric racecar, utilizing CAD software for the design. A simplified full-vehicle geometric model was constructed. Based on fundamental theories of computational fluid dynamics and using CAE software platforms, the shear stress transport (SST) k-ω physical model was chosen to establish a three-dimensional computational model of the racecar’s external flow field. Simulations were conducted to analyze the pressure, airflow streamlines, and velocity distribution around the body and its surrounding flow field, elucidating the impact of body shape structure on aerodynamic characteristics. Finally, a manufacturing process for the body was designed, and a prototype was produced and integrated into the complete vehicle for road testing. The results indicate that the designed electric racecar body maintained consistent airflow over its surface, meeting the basic requirements of aerodynamics. Full article

In the exploration of sustainable construction materials, the application of ferronickel slag (FNS) in creating pervious concrete has been investigated, considering its potential to meet the dual requirements of mechanical strength and fluid permeability. To elucidate the statistical properties and models for predicting the performance of FNS-composited pervious concrete with different sizes of aggregates and mixtures, a series of experiments, including 54 kinds of mixtures and three kinds of aggregate, were conducted. The focus was on measuring the compressive strength and the permeability coefficient. The results indicate that the compressive strength of pervious concrete decreases with the increase in aggregate size, while the permeability coefficient increases with the increase in aggregate size. Through normalization, the variability of these properties was quantitatively analyzed, revealing coefficients of variation for the concrete’s overall compressive strength and the permeability coefficient at 0.166, 0.132, and 0.150, respectively. Predictive models were developed using machine learning techniques, such as Linear Regression, Support Vector Machines, Regression Trees, and Gaussian Process Regression. These models demonstrated proficiency in forecasting the concrete’s compressive strength and permeability coefficient. Full article

The steel industry is one the three biggest producers of carbon dioxide and it is experiencing technical challenges due to the gradual decrease in the quality of iron ore. Steel is extensively used in the construction industry for structural applications like steel components, while steel fibres are intensively used as additives to concrete in order to improve its performance. It is thus important to consider the use of recycled steel as a replacement for virgin steel in order to address the aforementioned environmental consequences. This paper applies the eco-efficiency framework to determine the economic and environmental implications of the use of recycled fibre in concrete as a replacement for virgin steel. A number of concrete mixes were considered that used virgin, recycled, and treated recycled rebar in concrete. The eco-efficiency framework, which uses a life-cycle assessment approach to calculate the environmental and economic values of concrete mixes in order to determine the portfolio positions of these concrete mixes, was used for comparison purposes and to establish the eco-efficient option(s). Whilst the recovery and recycling process is energy-intensive, the use of recycled steel fibre in reinforced concrete has been found to be eco-efficient and deliver the same level of mechanical performance compared to that obtained using virgin steel fibre. Treating steel fibre could improve its technical performance, but it was found to increase both costs and environmental impacts and was therefore identified as not being eco-efficient. Full article

Sorting unreelable inferior cocoons during the reeling process is essential for obtaining high-quality silk products. At present, silk reeling enterprises mainly rely on manual sorting, which is inefficient and labor-intensive. Automated sorting based on machine vision and sorting robots is a promising alternative. However, the accuracy and computational complexity of object detection are challenges for the practical application of automatic sorting, especially for small stains of inferior cocoons in images of densely distributed cocoons. To deal with this problem, an efficient fine-grained object detection network based on attention mechanism and multi-scale feature fusion, called AMMF-Net, is proposed for inferior silkworm cocoon recognition. In this model, fine-grained object features are key considerations to improve the detection accuracy. To efficiently extract fine-grained features of silkworm cocoon images, we designed an efficient hybrid feature extraction network (HFE-Net) that combines depth-wise separable convolution and Transformer as the backbone. It captures local and global information to extract fine-grained features of inferior silkworm cocoon images, improving the representation ability of the network. An efficient multi-scale feature fusion module (EMFF) is proposed as the neck of the object detection structure. It improves the typical down-sampling method of multi-scale feature fusion to avoid the loss of key information and achieve better performance. Our method is trained and evaluated on a dataset collected from multiple inferior cocoons. Extensive experiments validated the effectiveness and generalization performance of the HFE-Net network and the EMFF module, and the proposed AMMF-Net achieved the best detection results compared to other popular deep neural networks. Full article

Exploring the impact of individual capabilities on ecosystem services and farmers’ well-being is conducive to discovering the complex relationship between ESs and human well-being, and has clear practical value for the sustainable management and improvement of farmers’ well-being in ecologically fragile areas in China. An importance–accessibility index of ESs was constructed and the objective well-being and subjective well-being of farmers were assessed. Subsequently, the relationship among capabilities, ESs, and well-being was elucidated based on a structural equation model. The results showed that fruits, pest control, fuelwood, water conservation, and wild food were the ES types that contributed most to farmers’ well-being. There were some similarities and differences between the dimensions of objective and subjective well-being. For example, farmers with adequate leisure time reported higher leisure satisfaction and farmers with relatively adequate income levels reported the lowest income satisfaction. The direct effect of capabilities on ESs and objective well-being was significant, and the direct effect of capabilities on their subjective well-being was not significant. Their capabilities had a significant indirect impact on their objective well-being by influencing ESs and did not have a significant indirect impact on their subjective well-being by influencing ESs; their capabilities had a significant indirect impact on their subjective well-being by influencing the ESs and objective well-being. Physical health, mental health, and agricultural skills were the key types of capabilities that influenced the farmers’ access to ESs and well-being. Improving these capabilities can enable local farmers to more fully access ESs and improve their well-being. Full article

In light of the European Union’s zero-emissions policy and the growing demand for energy associated with technological advances, it is necessary to consider adopting technologies and innovative solutions that simultaneously reduce greenhouse gas emissions while increasing potential extraction from existing hydrocarbon deposits, for example. This can result in increased production from deposits with low reservoir energy values or those in which the energy value does not allow the resource to be exploited on its own. By using a hydraulic drilling nozzle that harnesses the hydraulic energy of the fluid stream for workover, the possibility of increasing the contact between the reservoir layer and the producing well increases in direct proportion to the number of small-diameter radial wells drilled with a hydraulic rotary head from a horizontal well toward the reservoir layer. The main aspect of this paper is to outline an algorithm for the design of rotary drilling heads to maximize the use of the hydraulic energy from fluid streams flowing from the face of innovative drilling tools. The presented design algorithm allows changing the mutual position between the holes in the face section and the angle of the holes with respect to the longitudinal axis of the designed hydraulic rotary nozzle, simplifying the design work. The use of the rotary head developed using this algorithm enables seamless drilling in rocks with compressive strength R_c = 50 MPa, considering the drilling progress at ROP = 4 mm/s. Full article

The ability to inhibit conflicting information is pivotal in the dynamic and high-speed context of fast-ball sports. However, the behavioral and electrophysiological characteristics underlying the cognitive inhibition processes associated with table tennis expertise remain unexplored. This study aims to bridge these research gaps by utilizing the color-word Stroop task and the spatial Stroop task alongside event-related potential (ERP) measurements to investigate domain-general and domain-specific cognitive inhibition among table tennis athletes. The study involved a total of 40 participants, including 20 table tennis athletes (11 males and 9 females; mean age 20.75 years) and 20 nonathletes (9 males and 11 females; mean age 19.80 years). The group differences in the Stroop effect on behavioral outcomes and ERP amplitudes were compared within each task, respectively. In the color-word Stroop tasks, athletes exhibited smaller incongruent-related negative potential amplitudes (N_inc; 300–400 ms; p = 0.036) and a diminished Stroop effect on late sustained potential amplitudes (LSP; 500–650 ms; p = 0.028) than nonathletes, although no significant differences were observed in behavioral outcomes (p > 0.05). Conversely, in the spatial Stroop tasks, athletes not only responded more swiftly but also exhibited reduced Stroop effects on both LSP amplitudes (350–500 ms; p = 0.004) and reaction times (p = 0.002) relative to nonathletes. These findings suggest that table tennis athletes excel in cognitive inhibition in the context of both domain-general and domain-specific tasks, particularly exhibiting enhanced performance in tasks that are closely aligned with the demands of their sport. Our results support the neural efficiency hypothesis and improve our understanding of the interactions between cognitive functions and table tennis expertise. Full article

Being a vital component of electrical power systems, transformers significantly influence the system stability and reliability of power supplies. Damage to transformers may lead to significant economic losses. The efficient identification of transformer faults holds paramount importance for the stability and security of power grids. The existing methods for identifying transformer faults include oil chromatography analysis, temperature assessment, frequency response analysis, vibration characteristic examination, and leakage magnetic field analysis. These methods suffer from limitations such as limited sensitivity, complexity in operation, and a high demand for specialized skills. In this paper, we propose a method to identify external short-circuit faults of power transformers based on fault recording data on short-circuit currents. It involves analyzing the current signals of various windings during faults, extracting appropriate features, and utilizing a classification algorithm based on a support vector machine (SVM) to determine fault types and locations. The influence of different kernel functions on the classification accuracy of SVM is discussed. The results indicate that this method can proficiently identify the type and location of external short-circuit faults in transformers, achieving an accuracy rate of 98.3%. Full article

In order to drive electric vehicle adoption and bolster grid stability, the incorporation of battery swapping stations (BSSs) into the power grid is imperative. Conversely, network reconfiguration plays a crucial role in optimizing energy exchange within the power network, ensuring its economical and safe operation. Therefore, this study proposes an optimal planning method for battery swapping stations that integrates dynamic power distribution network reconfiguration while addressing technical aspects of the grid. The proposed method aims to concurrently optimize the placement and capacity of battery swapping stations, along with power distribution network reconfiguration, to enhance grid reliability and efficiency. The optimization model accounts for various factors including power quality, technical considerations, grid limitations, and operational expenses. A multi-objective optimization framework is devised to simultaneously reduce system losses, improve voltage stability, and mitigate environmental impacts of the power distribution network incorporating DG units. Case studies are conducted to illustrate the efficacy of the proposed approach in enhancing overall grid performance while accommodating the integration of battery swapping stations. The findings underscore the significance of considering technical factors and grid reconfiguration in battery swapping station planning to achieve optimal system operation and maximize benefits for electric vehicle users and grid operators alike. Full article

Since 2016, the Ministry of Ecology and Environment and the Beijing Municipal Government have adjusted the minimum concentration limit for ambient air dustfall several times, indicating that they attach great importance to dustfall. To grasp the pollution characteristics and sources of dustfall, in this work, the filtration method was used to determine the insoluble dustfall and water-soluble dustfall in the urban area of Beijing. From our analysis, the influence of the meteorological parameters on dustfall was found, and the chemical components of dustfall were determined. The positive matrix factorization (PMF) model was also utilized to analyze the sources of dustfall. The results indicated that the average amount of dustfall in 2021–2022 was 4.4 t·(km²·30 d)⁻¹, and the proportion of insoluble dustfall deposition was 82.4%. Dustfall was positively correlated with the average wind speed and temperature and negatively correlated with the relative humidity and rain precipitation. The impact of the meteorological parameters on insoluble dustfall and water-soluble dustfall was the opposite. The average proportions of crustal material, ions, organic matter, element carbon, trace elements, and unknown components were 48%, 16%, 14%, 1.4%, 0.20%, and 20%, respectively. The proportions of the crustal material and ions were the highest in spring (57%) and summer (37%). The contribution rates of fugitive dust source, secondary inorganic source, mobile source, coal combustion source, snow melting agent source, and other sources were 42.4%, 19.3%, 8.3%, 3.0%, 2.7%, and 24.3%, respectively. This study supported dustfall pollution control by analysing the pollutant characteristics and sources of dustfall from the standpoint of total chemical components. In order to better control dustfall pollution, control measures and evaluation standards for fugitive dust pollution should be formulated. Full article

A semilinear quadratic equation of the form $A_{ij}\left(x\right)u^{ij}=B_i(x,u)u^i+F(x,u)$ defines a metric $A_{ij}$; therefore, it is possible to relate the Lie point symmetries of the equation with the symmetries of this metric. The Lie symmetry conditions break into two sets: one set containing the Lie derivative of the metric wrt the Lie symmetry generator, and the other set containing the quantities $B_i(x,u),F(x,u).$ From the first set, it follows that the generators of Lie point symmetries are elements of the conformal algebra of the metric $A_{ij}$, while the second set serves as constraint equations, which select elements from the conformal algebra of $A_{ij}.$ Therefore, it is possible to determine the Lie point symmetries using a geometric approach based on the computation of the conformal Killing vectors of the metric $A_{ij}$. In the present article, the nonlinear Poisson equation ${\Delta }_{g}u-f\left(u\right)=0$ is studied. The metric defined by this equation is 1 + 2 decomposable along the gradient Killing vector ${\partial }_t$. It is a conformally flat metric, which admits 10 conformal Killing vectors. We determine the conformal Killing vectors of this metric using a general geometric method, which computes the conformal Killing vectors of a general $1+(n-1)$ decomposable metric in a systematic way. It is found that the nonlinear Poisson equation ${\Delta }_{g}u-f\left(u\right)=0$ admits Lie point symmetries only when $f\left(u\right)=ku$, and in this case, only the Killing vectors are admitted. It is shown that the Noether point symmetries coincide with the Lie point symmetries. This approach/method can be used to study the Lie point symmetries of more complex equations and with more degrees of freedom. Full article

Carbon uptake of vegetation is controlled by phenology and photosynthetic carbon uptake capacity. However, our knowledge of the seasonal responses of vegetation productivity to phenological and physiological changes in alpine ecosystems is still weak. In this study, we quantified the spatio-temporal variations of vegetation phenology and gross primary productivity (GPP) across the source region of the Yellow River (SRYR) by analyzing MODIS-derived vegetation phenology and GPP from 2001 to 2019, and explored how vegetation phenology and maximum carbon uptake capacity (GPP_max) affected seasonal GPP over the region. Our results showed that the SRYR experienced significantly advanced trends (p < 0.05) for both start (SOS) and peak (POS) of the growing season from 2001 to 2019. Spring GPP (GPP_spr) had a significantly increasing trend (p < 0.01), and the earlier SOS had obvious positive effects on GPP_spr. Summer GPP (GPP_sum) was significantly and negatively correlated to POS (p < 0.05). In addition, GPP_max had a significant and positive correlation with GPP_sum and GPP_ann (p < 0.01), respectively. It was found that an earlier spring-summer phenology and higher photosynthetic peak enhanced the photosynthetic efficiency of vegetation in spring and summer and altered the seasonal patterns of vegetation productivity in the SRYR under warming and wetting climates. This study indicated that not only spring and autumn phenology but also summer phenology and maximum carbon uptake capacity should be regarded as crucial indicators regulating the carbon uptake process in alpine ecosystems. This research provides important information about how changes in phenology affect vegetation productivity in alpine ecosystems under global climate warming. Full article

Bovine Dewclaw Dermatitis (BDCD) is a hoof disease characterized by inflammation of the second and fifth accessory digits and the skin in this region. This pathology is poorly described in the literature; however, it has recently been observed in beef cattle in the Amazon Biome, Brazil. The objective of this study was to perform a clinical diagnosis and identify the risk factors associated with BDCD onset in cattle in the studied biome. Samples were collected from eight farms with extensive breeding systems located in Xinguara, Rondon do Pará, Curionópolis, and Ipixuna do Pará in the state of Pará, Brazil. A total of 706 Nellore and Nellore crossbred with taurine bovine of both sexes were evaluated, with males aged between 2 and 4 years and a mean weight of 650 kg, and females aged between 2 and 11 years and a mean weight of 400 kg. Distal extremities were inspected during cattle management, and in cases of dewclaw lesions, a specific examination was carried out after proper restraint. Cattle were diagnosed with BDCD on all farms analyzed. Of the 706 cattle inspected, 49 (6.94%) showed BDCD, of which 19 (38.77%) were Nellore and 30 (61.22%) were crossbred. This was the first study to determine BDCD’s occurrence in extensive farming systems in the Amazon region, also showing that pastures with large amounts of stumps and stones, the physical structure of pens, and trauma and injury incidence during animal management are the most important predisposing factors for the onset of BDCD. Full article