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Plant diseases worsen the threat of food shortage with the growing global population, and disease recognition is the basis for the effective prevention and control of plant diseases. Deep learning has made significant breakthroughs in the field of plant disease recognition. Compared with traditional deep learning, meta-learning can still maintain more than 90% accuracy in disease recognition with small samples. However, there is no comprehensive review on the application of meta-learning in plant disease recognition. Here, we mainly summarize the functions, advantages, and limitations of meta-learning research methods and their applications for plant disease recognition with a few data scenarios. Finally, we outline several research avenues for utilizing current and future meta-learning in plant science. This review may help plant science researchers obtain faster, more accurate, and more credible solutions through deep learning with fewer labeled samples.
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Doenças das Plantas , Aprendizado ProfundoRESUMO
Future phosphorus (P) shortages could seriously affect terrestrial productivity and food security. We investigated the changes in topsoil available P (AP) and total P (TP) in China's forests, grasslands, paddy fields, and upland croplands during the 1980s-2010s based on substantial repeated soil P measurements (63,220 samples in the 1980s, 2000s, and 2010s) and machine learning techniques. Between the 1980s and 2010s, total soil AP stock increased with a small but significant rate of 0.13 kg P ha-1 year-1 , but total soil TP stock declined substantially (4.5 kg P ha-1 year-1 ) in the four ecosystems. We quantified the P budgets of soil-plant systems by harmonizing P fluxes from various sources for this period. Matching trends of soil contents over the decades with P budgets and fluxes, we found that the P-surplus in cultivated soils (especially in upland croplands) might be overestimated due to the great soil TP pool compared to fertilization and the substantial soil P losses through plant uptake and water erosion that offset the P additions. Our findings of P-deficit in China raise the alarm on the sustainability of future biomass production (especially in forests), highlight the urgency of P recycling in croplands, and emphasize the critical role of country-level basic data in guiding sound policies to tackle the global P crises.
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Ecossistema , Solo , Fósforo/análise , Florestas , Plantas , ChinaRESUMO
We explored novel immunosuppressive agents with immune tolerance using a phenotypic drug discovery strategy, focusing on costimulatory molecules in T cells, and obtained triazolothienodiazepine derivatives. Their mechanism of action is to inhibit the bromodomain and extra-terminal domain (BET) family, as we have previously reported. Selective inhibition of the first bromodomain (BD1) of the BET family is expected to exert antitumor and immunosuppressive effects, similar to BET inhibitors. This study identified furopyridine derivatives 7 and 8 with high BD1 inhibitory activity and high selectivity over BD2. Compound 7 was found to be orally bioavailable and exhibited anti-inflammatory activity in a lipopolysaccharide-induced model.
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Piridinas , Piridinas/química , Piridinas/farmacologia , Piridinas/síntese química , Animais , Humanos , Administração Oral , Relação Estrutura-Atividade , Camundongos , Descoberta de Drogas , Lipopolissacarídeos/farmacologia , Lipopolissacarídeos/antagonistas & inibidores , Estrutura Molecular , Ratos , Domínios ProteicosRESUMO
Free available chlorine has been and is being applied in global water treatment and readily reacts with dissolved organic matter (DOM) in aquatic environments, leading to the formation of chlorinated products. Chlorination enhances the photoreactivity of DOM, but the influence of chlorinated compounds on the photogeneration of hydroxyl radicals (â¢OH) has remained unexplored. In this study, a range of chlorinated carboxylate-substituted phenolic model compounds were employed to assess their â¢OH photogeneration capabilities. These compounds demonstrated a substantial capacity for â¢OH production, exhibiting quantum yields of 0.1-5.9 × 10-3 through direct photolysis under 305 nm and 0.2-9.5 × 10-3 through a triplet sensitizer (4-benzoylbenzoic acid)-inducing reaction under 365 nm LED irradiation. Moreover, the chlorinated compounds exhibited higher light absorption and â¢OH quantum yields compared to those of their unchlorinated counterparts. The â¢OH photogeneration capacity of these compounds exhibited a positive correlation with their triplet state one-electron oxidation potentials. Molecular-level compositional analysis revealed that aromatic structures rich in hydroxyl and carboxyl groups (e.g., O/C > 0.5 with H/C < 1.5) within DOM serve as crucial sources of â¢OH, and chlorination of these compounds significantly enhances their capacity to generate â¢OH upon irradiation. This study provides novel insights into the enhanced photogeneration of â¢OH from chlorinated DOM, which is helpful for understanding the fate of trace pollutants in chlorinated waters.
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Radical Hidroxila , Poluentes Químicos da Água , Radical Hidroxila/análise , Radical Hidroxila/química , Matéria Orgânica Dissolvida , Fotólise , Oxirredução , Ácidos Carboxílicos , Poluentes Químicos da Água/análiseRESUMO
A novel binding layer (BL) as part of the diffusive gradients in thin films (DGT) technique was developed for the two-dimensional visualization and quantification of labile phosphorus (P) in soils. This BL was designed for P detection by synchrotron-based X-ray fluorescence microscopy (XFM). It differs from the conventional DGT BL as the hydrogel is eliminated to overcome the issue that the fluorescent X-rays of P are detected mainly from shallow sample depths. Instead, the novel design is based on a polyimide film (Kapton) onto which finely powdered titanium dioxide-based P binding agent (Metsorb) was applied, resulting in superficial P binding only. The BL was successfully used for quantitative visualization of P diffusion from three conventional P fertilizers applied to two soils. On a selection of samples, XFM analysis was confirmed by quantitative laser-ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The XFM method detected significant differences in labile P concentrations and P diffusion zone radii with the P fertilizer incubation, which were explained by soil and fertilizer properties. This development paves the way for fast XFM analysis of P on large DGT BLs to investigate in situ diffusion of labile P from fertilizers and to visualize large-scale P cycling processes at high spatial resolution.
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Fertilizantes , Fósforo , Fósforo/análise , Fósforo/química , Fertilizantes/análise , Raios X , Solo/química , Difusão , Microscopia de FluorescênciaRESUMO
OBJECTIVE: This study was performed to estimate the effectiveness of novel oral hygiene instruction (OHI) focusing on areas with deep periodontal pockets for reduction of periodontal inflammation. BACKGROUND DATA DISCUSSING THE PRESENT STATUS OF THE FIELD: Because stained areas on the plaque chart do not always correspond to the areas with deep periodontal pockets, conventional OHI based on O'Leary's plaque control record (PCR) often provides guidance inconsistent with the target area. METHODS: This randomized clinical trial involved two groups: (1) OHI based on the PCR limited in deep pocket sites (novel OHI group) and (2) OHI based on O'Leary's PCR (conventional OHI group). The unique PCR (aggressive target for PCR [agPCR]; only counting the plaque-stained areas with PD at ≥4 mm sites) for the novel OHI was calculate by dedicated expression program. The probing depth (PD), bleeding on probing (BOP), and periodontal inflamed surface area (PISA) were obtained at the baseline and 5 to 6 months later. RESULTS: The approximation curve with PISA before and after instruction indicated that the PISA converged to a lower value after instruction in the novel OHI group. The approximation curve with the improvement rate of the PISA and agPCR showed a positive correlation in the novel OHI group but no correlation in the conventional OHI group. CONCLUSION: Control of inflammation was more effective in the novel OHI group. These results suggest that this novel OHI technique using our developed application could be used as a strategy to improve the effectiveness of brushing instruction.
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Placa Dentária , Higiene Bucal , Bolsa Periodontal , Humanos , Higiene Bucal/educação , Masculino , Placa Dentária/prevenção & controle , Feminino , Bolsa Periodontal/prevenção & controle , Pessoa de Meia-Idade , Índice Periodontal , Educação de Pacientes como Assunto/métodos , Adulto , Idoso , Índice de Placa DentáriaRESUMO
BACKGROUND: Health disparities, starkly exposed and exacerbated by coronavirus disease 2019, pose a significant challenge to healthcare system access and health outcomes. Integrating health inequalities into health technology assessment calls for robust analytical methodologies utilizing disaggregated data to investigate and quantify the scope of these disparities. However, a comprehensive summary of population datasets that can be used for this purpose is lacking. The objective of this review was to identify publicly accessible health inequalities data repositories that are potential resources for healthcare decision-making and future health technology assessment submissions. METHODS: An environmental scan was conducted in June of 2023 of six international organizations (World Health Organization, Organisation for Economic Co-operation and Development, Eurostat, United Nations Inter-agency Group for Child Mortality Estimation, the United Nations Sustainable Development Goals, and World Bank) and 38 Organisation for Economic Co-operation and Development countries. The official websites of 42 jurisdictions, excluding non-English websites and those lacking English translations, were reviewed. Screening and data extraction were performed by two reviewers for each data repository, including health indicators, determinants of health, and health inequality metrics. The results were narratively synthesized. RESULTS: The search identified only a limited number of country-level health inequalities data repositories. The World Health Organization Health Inequality Data Repository emerged as the most comprehensive source of health inequality data. Some country-level data repositories, such as Canada's Health Inequality Data Tool and England's Health Inequality Dashboard, offered rich local insights into determinants of health and numerous health status indicators, including mortality. Data repositories predominantly focused on determinants of health such as age, sex, social deprivation, and geography. CONCLUSION: Interactive interfaces featuring data exploration and visualization options across diverse patient populations can serve as valuable tools to address health disparities. The data they provide may help inform complex analytical methodologies that integrate health inequality considerations into healthcare decision-making. This may include assessing the feasibility of transporting health inequality data across borders.
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COVID-19 , Disparidades em Assistência à Saúde , Humanos , COVID-19/epidemiologia , Disparidades em Assistência à Saúde/estatística & dados numéricos , Acessibilidade aos Serviços de Saúde , SARS-CoV-2 , Tomada de Decisões , Saúde Global , Disparidades nos Níveis de SaúdeRESUMO
AIMS: This study explores the phosphate (Pi)-solubilizing characteristics and mechanisms of a novel phosphate-solubilizing bacterium, Agrobacterium deltaense C1 (C1 hereafter). METHODS AND RESULTS: The growth-promoting effects of C1 were investigated by gnotobiotic experiments, and the Pi-solubilizing mechanism was revealed by extracellular metabolomics, liquid chromatography analysis, and reverse transcription quantitative polymerase chain reaction. Results showed that C1 significantly increased Arabidopsis biomass and total phosphorus (P) content under P deficiency. Under Ca3(PO4)2 condition, the presence of C1 resulted in a significant and negative correlation between available P content and medium pH changes, implying that Pi dissolution occurs through acid release. Metabolomics revealed C1's ability to release 99 organic acids, with gluconic acid (GA), citric acid, and α-ketoglutaric acid contributing 64.86%, 9.58%, and 0.94%, respectively, to Pi solubilization. These acids were significantly induced by P deficiency. Moreover, C1's Pi solubilization may remain significant even in the presence of available P, as evidenced by substantial pH reduction and high gcd gene expression. Additionally, C1 produced over 10 plant growth-promoting substances. CONCLUSIONS: C1 dissolves Pi primarily by releasing GA, which enhances plant growth under P deficiency. Notably, its Pi solubilization effect is not significantly limited by available Pi.
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Fosfatos , Microbiologia do Solo , Fosfatos/metabolismo , Fósforo/metabolismo , Agrobacterium/genética , Agrobacterium/metabolismo , Bactérias/genéticaRESUMO
To investigate the effects of modified carbon-based materials on soil environmental remediation and crop physiological regulation, this research relied on rice pots with lead (Pb) and cadmium (Cd) composite contamination. Dolomite, montmorillonite, attapulgite and sepiolite modified biochar with different doses have been developed to explore the mechanisms on heavy metal passivation, nutrient improvement, microbial activation, and crop growth. The results indicated that the modified materials effectively reduced heavy metal bioavailability and accumulation in plant tissues through adsorption complexation. Specifically, under montmorillonite and sepiolite modified treatments, the Grains-Pb content significantly decreased by 29.23-30.31% and 27.49-30.58%, compared to the control group (CK). Meantime, carbon-based materials increased available nutrient levels, providing a biological substrate for soil microorganisms metabolism. The content of ammonium nitrogen (NH4+-N) and available phosphorus (AP) in different proportions of montmorillonite modified biochar increased by 10.99-13.98% and 55.76-77.86%, respectively, compared to CK. Furthermore, sepiolite modified biochar enhanced bacterial community diversity, significantly improving the tolerance and resistance of bacterial communities such as Proteobacteria and Acidobacteria to heavy metals. Meanwhile, carbon-based materials enhanced community stability and network complexity, improving microbial stress resistance to adverse environments. In summary, montmorillonite and sepiolite modified biochar regulated microbial community interaction mechanisms by mitigating the physiological toxicity of heavy metals. This process enhanced soil available nutrients and ecological function stability, which had significant implications for improving crop growth and quality.
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Referring to the natural succession to restore polluted land is one of the most vital assignments to solving the environmental problems. However, there is little understanding of the natural restoration of nutrient biogeochemical cycles in abandoned land with severe metal pollution. To clarify the nutrient cycling process and the influence of organisms on it, we investigated the magnitude of rhizosphere effects on soil nitrogen (N), phosphorus (P) and sulphur (S) cycles in natural restoration of an abandoned metal mine, as well as the roles of plants and microorganisms in the nutrient cycles. Our data revealed that the rhizosphere had higher levels of ammoniation than non-rhizosphere soil at both stages of restoration. In the early stage, the rhizosphere had greater levels of inorganic phosphorus and organophosphorus solubilisation, as well as sulphite oxidation, compared to non-rhizosphere soil. The bacterial composition influenced the N and S cycles, while the fungal composition had the greatest effect on the P cycles. Furthermore, rhizosphere nutrition cycles and microbial communities altered according plant strategy. Overall, the plants that colonize the early stages of natural recovery demonstrate enhanced restoration of nutrient efficiency. These results contribute to further knowledge of nutrient recovery in mining areas, as well as suggestions for selecting remedial microorganisms and plants in metal-polluted environments.
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BACKGROUND: Embryo quality is usually regarded as a key predictor of successful implantation and clinical pregnancy potential. The identification of embryos that have the capacity to implant and result in a healthy pregnancy is a crucial part of in vitro fertilization (IVF). Usually, morphologically high-quality embryos are chosen for embryo transfer in IVF treatment. The aim of this study was to assess the association between the available blastocyst formation rate and the clinical pregnancy outcome following the first fresh embryo transfer cycle and provide systematic individual treatment to adjust endometrial receptivity for the next transfer cycle. METHODS: This retrospective, single-center study included 512 fresh embryo transfers conducted between 11/2019 and 08/2021, which consisted of 385 cleavage-stage (Day 3) and 127 blastocyst-stage (Day 5) embryo transfers. The two groups were divided into a clinical pregnancy group and a nonclinical pregnancy group for comparison. The association between the available blastocyst formation rate and the clinical pregnancy rate in the Day 3 and Day 5 transfer groups were considered. RESULTS: In the Day 3 group, there were 275 clinical pregnancies, and the clinical pregnancy rate was 71.43%. Although the two pronuclei (2PN) oocyte rate and available embryo rate at Day 3 were significantly higher in the clinical pregnancy group than the nonclinical pregnancy group (P < 0.05), the blastocyst formation rate and the available blastocyst formation rate were not significantly different between the clinical pregnancy group and the nonclinical pregnancy group (P > 0.05). In the Day 5 group, there were 81 clinical pregnancies, and the clinical pregnancy rate was 63.78%. No baseline characteristics showed any obvious differences between the clinical pregnancy group and nonclinical pregnancy group (P > 0.05). The blastocyst formation rate in the nonclinical pregnancy group was higher than that in the clinical pregnancy group, but the difference was not statistically significant (81.06% vs. 77.03%, P = 0.083). Interestingly, the available blastocyst formation rate and the Day 5 available blastocyst formation rate were significantly higher in the nonclinical pregnancy group than the clinical pregnancy group (66.19% vs. 60.79%, P = 0.014; 54.58% vs. 46.98%, P = 0.007). CONCLUSIONS: In fresh cycles, the available blastocyst formation rate was not associated with the clinical pregnancy outcome for Day 3 embryo transfers, and the available blastocyst formation rate was not positively correlated with the clinical pregnancy outcome for Day 5 embryo transfers.
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Transferência Embrionária , Fertilização in vitro , Feminino , Gravidez , Humanos , Estudos Retrospectivos , Taxa de Gravidez , Resultado da Gravidez , Blastocisto , EndométrioRESUMO
As a high production volume chemical with recognized sensory irritation and widespread exposure, the human health risk potential of formaldehyde has been reviewed by many international regulatory agencies and scientific advisory bodies. A scientific panel, the Human Studies Review Board, under the auspices of the EPA's Toxic Substances Control Act (TSCA) program recently reviewed the sensory irritation studies included in the 2022 Draft Integrated Risk Information System (IRIS) Formaldehyde Hazard Assessment in the context of their use in a weight of evidence evaluation of acute inhalation health effects. This panel issued a series of recommendations on the use of these studies for the purposes of calculating exposure limits (e.g., study design preferences; uncertainty adjustment). Considering that these recommendations might reflect topic areas with varying degrees of scientific consensus, this commentary reflects on commonalities and distinctions amongst international formaldehyde exposure limits based on sensory irritation. Notably, each review panel charged with an assessment of the science recommended that no adjustment was needed to account for either exposure duration or human variability. These areas of scientific consensus should be considered as the best available science for the purposes of setting exposure limits in the anticipated TSCA Risk Evaluation on formaldehyde.
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Formaldeído , Humanos , Medição de Risco , Administração por Inalação , Formaldeído/toxicidadeRESUMO
Atlantic salmon aquaculture companies in British Columbia (BC) must report fish health events to Fisheries and Oceans Canada (DFO) as part of their licensing conditions. Our study aimed to summarize these fish health events reported by Atlantic salmon sites in BC to identify spatial and spatio-temporal clusters. We conducted descriptive, retrospective global, and local cluster analyses using Moran's I and scan statistics. Between 2016 and 2022, 265 fish health events were reported. The annual incidence ranged from 5.60 (95% CI: 3.90-7.80) to 6.86 (95% CI: 4.70-9.60) health events per 100 active site-months. The most common events were yellow mouth (60.75%; 161/265) and salmonid rickettsial septicaemia (SRS) (15.47%; 41/265). The Moran's I index was positive and significant for yellow mouth, SRS, and overall fish health events at different distance bands. Most of the spatial and spatio-temporal clusters were identified in the west-central and southwestern parts of Vancouver Island. Our study hypothesizes that management practices, environmental conditions, and water quality parameters may have influenced the increased reporting of fish health events in these regions. Overall, the study highlights the potential of publicly available data for practical risk mapping in understanding the patterns of farmed Atlantic salmon diseases in BC.
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Supplemental dietary rumen available fats show promise as enteric methane (eCH4) mitigators for lactating dairy cows. However, concerns include variability in eCH4 response and possible negative effects on dairy cow performance. Successful implementation of this mitigation option requires better prediction of responses specifically to rumen available fatty acids (FA) as well as understanding the modulating effects of other dietary and animal characteristics. Using meta-analytic and meta-regression techniques, 35 published studies with diet definition were used to assess changes in eCH4 emissions and lactation performance associated with supplemental fat, specific supplemental rumen available FA types, and other dietary characteristics. Enteric CH4 (g/d) was reduced by 3.77% per percentage unit of supplemental rumen available ether extract (EE). Supplemental rumen available PUFA (C18:2 and C18:3) and UFA (C18:1, C18:2, C18:3) mitigated eCH4 (g/d) emissions in dairy cows by 6.88 and 4.65% per percentage unit increase, respectively. The anti-methanogenic effects of PUFA, MUFA and MCFA increased with correspondingly greater basal dietary levels of each FA type. Higher rumen-degradable starch (RDS; >18% DM) in the basal diet promoted greater reductions in eCH4 yield (eCH4/DMI, g/kg) with supplemental rumen available PUFA and UFA. Both milk fat percentage and yield (kg/d) were reduced with rumen available fat supplementation with a reduction of 7.8% and 6.0%, respectively, relative to control diets. Our results highlight the importance of determining basal levels of the rumen available FA before providing supplemental rumen available FA as an option for enteric eCH4 mitigation. Dairy nutritionists can use estimates generated from this analysis to predict changes in eCH4 emissions and dairy cow performance associated with dietary supplementation of rumen available EE and specific rumen available FA types for the purpose of eCH4 mitigation.
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Ração Animal , Dieta , Suplementos Nutricionais , Lactação , Metano , Leite , Rúmen , Animais , Bovinos , Rúmen/metabolismo , Metano/biossíntese , Metano/metabolismo , Feminino , Dieta/veterinária , Leite/química , Leite/metabolismo , Ácidos GraxosRESUMO
BACKGROUND: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition software have been used to ease this burden, they have limitations in terms of accuracy and addressing provider-specific metrics. The integration of ambient artificial intelligence (AI)-powered solutions offers a promising way to improve documentation while fitting seamlessly into existing workflows. OBJECTIVE: This study aims to assess the accuracy and quality of Subjective, Objective, Assessment, and Plan (SOAP) notes generated by ChatGPT-4, an AI model, using established transcripts of History and Physical Examination as the gold standard. We seek to identify potential errors and evaluate the model's performance across different categories. METHODS: We conducted simulated patient-provider encounters representing various ambulatory specialties and transcribed the audio files. Key reportable elements were identified, and ChatGPT-4 was used to generate SOAP notes based on these transcripts. Three versions of each note were created and compared to the gold standard via chart review; errors generated from the comparison were categorized as omissions, incorrect information, or additions. We compared the accuracy of data elements across versions, transcript length, and data categories. Additionally, we assessed note quality using the Physician Documentation Quality Instrument (PDQI) scoring system. RESULTS: Although ChatGPT-4 consistently generated SOAP-style notes, there were, on average, 23.6 errors per clinical case, with errors of omission (86%) being the most common, followed by addition errors (10.5%) and inclusion of incorrect facts (3.2%). There was significant variance between replicates of the same case, with only 52.9% of data elements reported correctly across all 3 replicates. The accuracy of data elements varied across cases, with the highest accuracy observed in the "Objective" section. Consequently, the measure of note quality, assessed by PDQI, demonstrated intra- and intercase variance. Finally, the accuracy of ChatGPT-4 was inversely correlated to both the transcript length (P=.05) and the number of scorable data elements (P=.05). CONCLUSIONS: Our study reveals substantial variability in errors, accuracy, and note quality generated by ChatGPT-4. Errors were not limited to specific sections, and the inconsistency in error types across replicates complicated predictability. Transcript length and data complexity were inversely correlated with note accuracy, raising concerns about the model's effectiveness in handling complex medical cases. The quality and reliability of clinical notes produced by ChatGPT-4 do not meet the standards required for clinical use. Although AI holds promise in health care, caution should be exercised before widespread adoption. Further research is needed to address accuracy, variability, and potential errors. ChatGPT-4, while valuable in various applications, should not be considered a safe alternative to human-generated clinical documentation at this time.
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Relações Médico-Paciente , Humanos , Documentação/métodos , Registros Eletrônicos de Saúde , Inteligência ArtificialRESUMO
Selenium (Se) is a trace element that is essential for human health. Daily dietary Se intake is governed by the food chain through soil-plant systems. However, the cadmium (Cd) content tends to be excessive in seleniferous soil, in which Se and Cd have complex interactions. Therefore, it is a great challenge to grow crops containing appreciable amounts of Se but low amounts of Cd. We compared the effects of five Se-transforming bacteria on Se and Cd uptake by Brassica rapa L. in a native seleniferous Cd-polluted soil. The results showed that three Se-oxidizing bacteria (LX-1, LX-100, and T3F4) increased the Se content of the aboveground part of the plant by 330.8%, 309.5%, and 724.3%, respectively, compared to the control (p < 0.05). The three bacteria also reduced the aboveground Cd content by 15.1%, 40.4%, and 16.4%, respectively (p < 0.05). In contrast, the Se(IV)-reducing bacterium ES2-45 and weakly Se-transforming bacterium LX-4 had no effect on plant Se uptake, although they did decrease the aboveground Cd content. In addition, the three Se-oxidizing bacteria increased the Se available in the soil by 38.4%, 20.4%, and 24.0%, respectively, compared to the control (p < 0.05). The study results confirm the feasibility of using Se-oxidizing bacteria to simultaneously enhance plant Se content and reduce plant Cd content in seleniferous Cd-polluted soil.
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Selênio , Poluentes do Solo , Humanos , Cádmio/análise , Areia , Biodegradação Ambiental , Biofortificação , Solo , Produtos Agrícolas , Oxirredução , Poluentes do Solo/análiseRESUMO
Understanding past and current trends is crucial in the fashion industry to forecast future market demands. This study quantifies and reports the characteristics of the trendy walking styles of fashion models during real-world runway performances using three cutting-edge technologies: (a) publicly available video resources, (b) human pose detection technology, and (c) multivariate human-movement analysis techniques. The skeletal coordinates of the whole body during one gait cycle, extracted from publicly available video resources of 69 fashion models, underwent principal component analysis to reduce the dimensionality of the data. Then, hierarchical cluster analysis was used to classify the data. The results revealed that (1) the gaits of the fashion models analyzed in this study could be classified into five clusters, (2) there were significant differences in the median years in which the shows were held between the clusters, and (3) reconstructed stick-figure animations representing the walking styles of each cluster indicate that an exaggerated leg-crossing gait has become less common over recent years. Accordingly, we concluded that the level of leg crossing while walking is one of the major changes in trendy walking styles, from the past to the present, directed by the world's leading brands.
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Marcha , Caminhada , Humanos , Caminhada/fisiologia , Análise Multivariada , Marcha/fisiologia , Análise por Conglomerados , Análise de Componente Principal , Fenômenos Biomecânicos/fisiologia , Gravação em Vídeo/métodos , Postura/fisiologiaRESUMO
Systematically and comprehensively enhancing road traffic safety using artificial intelligence (AI) is of paramount importance, and it is gradually becoming a crucial framework in smart cities. Within this context of heightened attention, we propose to utilize machine learning (ML) to optimize and ameliorate pedestrian crossing predictions in intelligent transportation systems, where the crossing process is vital to pedestrian crossing behavior. Compared with traditional analytical models, the application of OpenCV image recognition and machine learning methods can analyze the mechanisms of pedestrian crossing behaviors with greater accuracy, thereby more precisely judging and simulating pedestrian violations in crossing. Authentic pedestrian crossing behavior data were extracted from signalized intersection scenarios in Chinese cities, and several machine learning models, including decision trees, multilayer perceptrons, Bayesian algorithms, and support vector machines, were trained and tested. In comparing the various models, the results indicate that the support vector machine (SVM) model exhibited optimal accuracy in predicting pedestrian crossing probabilities and speeds, and it can be applied in pedestrian crossing prediction and traffic simulation systems in intelligent transportation.
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Objective: To understand the performance of EndNote 20 and Zotero 6's full text retrieval features. Methods: Using the University of York's subscriptions, we tested and compared EndNote and Zotero's full text retrieval. 1,000 records from four evidence synthesis projects were tested for the number of: full texts retrieved; available full texts retrieved; unique full texts (found by one program only); and differences in versions of full texts for the same record. We also tested the time taken and accuracy of retrieved full texts. One dataset was tested multiple times to confirm if the number of full texts retrieved was consistent. We also investigated the available full texts missed by EndNote or Zotero by: reference type; whether full texts were available open access or via subscription; and the content provider. Results: EndNote retrieved 47% of available full texts versus 52% by Zotero. Zotero was faster by 2 minutes 15 seconds. Each program found unique full texts. There were differences in full text versions retrieved between programs. For both programs, 99% of the retrieved full texts were accurate. Zotero was less consistent in the number of full texts it retrieved. Conclusion: EndNote and Zotero do not find all available full texts. Users should not assume full texts are correct; are the version of record; or that records without full texts cannot be retrieved manually. Repeating the full text retrieval process multiple times could yield additional full texts. Users with access to EndNote and Zotero could use both for full text retrieval.
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Armazenamento e Recuperação da Informação , Armazenamento e Recuperação da Informação/métodos , Humanos , Software , New York , UniversidadesRESUMO
Understanding the spatial distribution of plant available soil nutrients and influencing soil properties and delineation soil nutrient management zones (MZs) are important for implementing precision nutrient management options (PNMO) in an area to achieve maintainable crop production. We assessed spatial distribution pattern of plant available sulphur (S) (PAS), boron (B) (PAB), zinc (PAZn), manganese (PAMn), iron (PAFe), and copper (PACu), and soil organic carbon (SOC), pH, and electrical conductivity (EC) to delineate soil nutrients MZs in northeastern region of India. A total of 17,471 representative surface (0-15 cm depth) soil samples were collected from the region, processed, and analysed for above-mentioned soil parameters. The values of PAS (0.22-99.2 mg kg-1), PAB (0.01-6.45 mg kg-1), PAZn (0.05-13.9 mg kg-1), PAMn (0.08-158 mg kg-1), PAFe (0.50-472 mg kg-1), PACu (0.01-19.2 mg kg-1), SOC (0.01-5.80%), pH (3.19-7.56) and EC (0.01-1.66 dS m-1) varied widely with coefficient of variation of 15.5-108%. The semivariogram analysis highlighted exponential, Gaussian and stable best fitted models for soil parameters with weak (PACu), moderate (PAB, PAZn, PAFe, SOC, pH, and EC) and strong (PAS, and PAMn) spatial dependence. The ordinary kriging interpolation revealed different distribution patterns of soil parameters. About 14.8, 27.5, and 3.40% area of the region had PAS of ≤15.0 mg kg-1, PAB of ≤0.50 mg kg-1, and PAZn of had ≤0.90 mg kg-1, respectively. About 67.5, and 32.5% area had SOC content >1.00 and < 1.00%, respectively. Soil pH was ≤5.50, and >5.50 to ≤6.50 in 41.7 and 40.3% area of the region, respectively. The techniques of principal component analysis and fuzzy c-mean algorithm clustering produced 6 MZs of the region with different areas and values of soil parameters. The MZs had different levels of deficiency pertaining to PAS, PAB, and PAZn. The produced MZ maps could be used for managing PAS, PAB, PAZn, SOC and soil pH in order to implement PNMO. The study highlighted the usefulness of MZ delineation technique for implementation of PNMO in different cultivated areas for sustainable crop production.