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Rudge, Cibele, Iracema Calderon, Ana Almeida, Fernanda Piculo, Marilza Rudge et Angélica Barbosa. « Score Establishment and Brazilian Portuguese version of the Pregnancy Sexual Response Inventory (PSRI) ». Revista Brasileira de Ginecologia e Obstetrícia / RBGO Gynecology and Obstetrics 40, no 06 (juin 2018) : 322–31. http://dx.doi.org/10.1055/s-0038-1656536.
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Objective To establish the Pregnancy Sexual Response Inventory (PSRI) scores for each domain before and during pregnancy, and to publish the Brazilian Portuguese version of the PSRI. Methods Pregnant women were recruited during antenatal care; the PSRI was administered to 244 women prenatally at Faculdade de Medicina de Botucatu, at Universidade do Estado de São Paulo (UNESP, in the Portuguese acronym). The PSRI scores were estimated based on the Kings Health Questionnaire (KHQ) and the Medical Outcomes Study 36-item short form survey (SF-36). The raw scale type was used to standardize the minimal value and amplitude of each domain. For each domain, the score varied from 0 to 100, and the composite score was obtained as the domain average. The composite score before and during pregnancy was determined by the sum of the scores of all specific domains for each divided by the full domain number. The categorization of the scale into quartiles was established when all PSRI-specific and composite scores were combined. Results The composite and specific scores for each domain were categorized into quartiles: 0 < 25 as “very bad;” 25 < 50 as “bad;” 50 < 75 as “good” and 75 to 100 as “excellent.” The mean scores were lower during pregnancy than before pregnancy in 8 of the 10 domains. The Brazilian Portuguese PSRI version is presented. Conclusion This study allowed the establishment of the PSRI composite and specific scores for each domain, and the categorization of scores into quartiles: very bad, bad, good and excellent. In addition, the Brazilian Portuguese version of the PSRI is presented in full for application in the Brazilian population.
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Chinosi, C. « PSRI elements for the Reissner–Mindlin free plate ». Computers & ; Structures 83, no 31-32 (décembre 2005) : 2559–72. http://dx.doi.org/10.1016/j.compstruc.2005.07.005.
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Spirkovska, L., et M. B. Reid. « Coarse-coded higher-order neural networks for PSRI object recognition ». IEEE Transactions on Neural Networks 4, no 2 (mars 1993) : 276–83. http://dx.doi.org/10.1109/72.207615.
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Murakawa, Y., T. Yamashita, K. Ajiki, K. Sezaki, Y. Kanese et M. Omata. « Electrophysiological background of individual variability in electrical defibrillation efficacy ». American Journal of Physiology-Heart and Circulatory Physiology 271, no 3 (1 septembre 1996) : H1094—H1098. http://dx.doi.org/10.1152/ajpheart.1996.271.3.h1094.
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This study was performed to test whether heart-to-heart variability of defibrillation efficacy is attributable to differences in postshock refractory state of nondepolarized myocardium. In 30 anesthetized dogs, a localized potential gradient was created using 1-16 V of stimulus across a pair of platinum plate electrodes on the right ventricle (5-mm interelectrode distance). The postshock recovery interval (PSRI) of the relatively refractory myocardium directly adjacent to the excited area was estimated by measuring the recovery interval after an appropriately timed field stimulus. The transcardiac defibrillation threshold (DFT) was also determined. The results showed that DFT normalized by the weight of the heart was inversely correlated with the PSRI measured with a field stimulus of 6 V (local shock intensity approximately 5 V/cm) or more (6 V: r = -0.502, P < 0.005; 16 V: r = -0.635, P < 0.0005). This observation suggests that variability of defibrillation efficacy in intact hearts is largely due to differences in the postshock refractory state of the nondepolarized myocardium.
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Schönert, M., E. Zillmann, H. Weichelt, J. U. H. Eitel, T. S. Magney, H. Lilienthal, B. Siegmann et T. Jarmer. « The Tasseled Cap Transformation for RapidEye data and the estimation of vital and senescent crop parameters ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (28 avril 2015) : 101–8. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-101-2015.
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The retrieval of crop biophysical parameters using spectral indices obtained from high temporal and spatial resolution satellite data, is a valuable tool to monitor crop growth and status. Tasseled Cap Features (TCFs) for RapidEye data were derived from spectral variances typically present in agricultural scenes. The TCF Greenness (GRE) was aligned to the spectral variance of vital vegetation, and therefore, it represents the typical reflectance characteristics of green vegetation, with relatively higher reflectance at the nearinfrared (NIR) range. The TCF Yellowness (YEL) was aligned to correspond to the reflectance characteristics of senescent crops, with relatively higher reflectance in the visible portion of the spectrum due to chlorophyll breakdown, and lower reflectance in the NIR range due to cell structure decomposition compared to vital green vegetation. The goal of this work was to assess the potential of RapidEye’s TCFs for the prediction of green leaf area index (LAI), plant chlorophyll (Chl), and nitrogen (N) concentration, as well as the identification of senescence patterns. The linear relationships between the biophysical parameters and the TCFs were compared to the performance of the widely used indices NDVI and PSRI. Preliminary results indicate that GRE is strongly related to LAI in vital crops and suggests a higher predictive power than NDVI. YEL demonstrated a strong linear relation and a higher potential to estimate Chl and N concentration in senescent soft white winter wheat (<i>Triticum aestivum</i> L.) in comparison to PSRI. PSRI showed a stronger correlation to Chl in senescent soft white spring wheat (<i>Triticum aestivum</i> L.), compared to YEL. Results indicate that YEL may be used to characterize the variability in senescence status within fields. This information, in conjunction with soil fertility and yield maps, can potentially be used to designate precision management zones.
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Li, Tingwen, Jean-François Dietiker et Mehrdad Shahnam. « MFIX simulation of NETL/PSRI challenge problem of circulating fluidized bed ». Chemical Engineering Science 84 (décembre 2012) : 746–60. http://dx.doi.org/10.1016/j.ces.2012.09.024.
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Sobura, Szymon, Beata Hejmanowska, Małgorzata Widłak et Joanna Muszyńska. « The Application of Remote Sensing Techniques and Spectral Analyzes to Assess the Content of Heavy Metals in Soil – A Case Study of Barania Góra Reserve, Poland ». Geomatics and Environmental Engineering 16, no 4 (18 octobre 2022) : 187–213. http://dx.doi.org/10.7494/geom.2022.16.4.187.
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The understanding of the spatial and temporal dynamics of farmland processes is essential to ensure the proper crop monitoring and early decision making needed to support efficient resource management in agriculture. By creating appropriate crop management strategies, one can increase harvest efficiency while reducing costs, waste, chemical spraying, and inhibiting the impact of biotic and abiotic factors on crop stress. Only reliable spatial information makes it possible to comprehend the influence of various factors on the environment. The main objective of the research presented in the paper was to assess the possibility of using maps of vegetation and soil indices, such as NDVI, SAVI, IRECI, CIred-edge, PSRI and HMSSI, calculated on the basis of images from the Sentinel-2 satellite, to qualitatively determine the increased amount of heavy metals in the soil in the areas of small agricultural plots around the Barania Góra nature reserve in Poland.The conducted pilot project shows that the spectral indices: NDVI, SAVI, IRECI, CIred-edge, PSRI, and HMSSI, calculated on the basis of images from Sentinel-2, have the potential to assess the content of nickel zinc, chromium and cobalt in the soil on agricultural plots. However, the confirmation of the obtained results requires continuation of the research.
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Chalermsinsuwan, Benjapon, Pornpote Piumsomboon et Dimitri Gidaspow. « Kinetic theory based computation of PSRI riser : Part I—Estimate of mass transfer coefficient ». Chemical Engineering Science 64, no 6 (mars 2009) : 1195–211. http://dx.doi.org/10.1016/j.ces.2008.11.010.
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Yudarwati, Rani, Chiharu Hongo, Gunardi Sigit, Baba Barus et Budi Utoyo. « Bacterial Leaf Blight Detection in Rice Crops Using Ground-Based Spectroradiometer Data and Multi-temporal Satellites Images ». Journal of Agricultural Science 12, no 2 (15 janvier 2020) : 38. http://dx.doi.org/10.5539/jas.v12n2p38.
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This study presents a method for detecting rice crop damage due to bacterial leaf blight (BLB) infestation. Rice crop samples are first analyzed using a handheld spectroradiometer. Then, multi-temporal satellite image analysis is used to determine the most suitable vegetation indices for detecting BLB. The results showed that healthy plants have the highest first derivative value of spectral reflectance of the different categories of diseased plants. Significant difference can be found at approximately 690-770 nm (red edge region) which peak or maximum of the first derivative occurs in healthy crop whereas the highest percentage of BLB showed the lowest in that region. Moreover, visible bands such as blue, green, red, and red edge 1 band show variation of correlation in the early (vegetative) to generative stage then getting high especially in early of harvesting stage than the other bands; the NIR band exhibits a low correlation from the early stage of the growing season whereas the red and red edge bands reveal the highest correlations in the later stage of harvesting. Similarly, the satellite image analysis also reveals that disease incidence gradually increases with increasing age of the plant. The vegetation indices whose formulas consist of blue, green, red, and red edge bands (NGRDI, NPCI, and PSRI) exhibit the highest correlation with BLB infestation. NPCI and PSRI indices indicate that crop stress due to BLB is detected from ripening stage of NPCI then the senescence condition is then detected 12 days later. The coefficients of determination between these indices and BLB are 0.44, 0.63, and 0.67, respectively
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Guendler, Julianna Azevedo, Leila Katz, Maria Eduarda Duarte Mello Flamini, Andrea Lemos et Melania Maria Amorim. « Prevalence of Sexual Dysfunctions and their Associated Factors in Pregnant Women in an Outpatient Prenatal Care Clinic ». Revista Brasileira de Ginecologia e Obstetrícia / RBGO Gynecology and Obstetrics 41, no 09 (septembre 2019) : 555–63. http://dx.doi.org/10.1055/s-0039-1695021.
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Objective To determine the prevalence of sexual dysfunction and its associated factors in pregnant women. Methods A descriptive, cross-sectional study including 262 pregnant women aged 18 years or older with gestational age between 10 and 35 weeks. Women with urinary tract infections and conditions of gestational risk were excluded. The Pregnancy Sexual Response Inventory (PSRI) questionnaire was used. We performed a univariate descriptive analysis, and comparisons between the mean values of the sexual function domains were made using the Student t-test. The chi-squared test was used to determine the association between the independent and dependent variables. The prevalence ratios, with their respective 95% confidence intervals, were also estimated, and a multivariate analysis was performed. Results A total of 64.9% of women reported a decrease in the frequency of sexual activity during pregnancy. Slightly more than half of the women (50.8%) were satisfied, and arousal was reported as excellent/good by 30.5% of them. The frequency of sexual difficulties/dysfunctions increased with pregnancy, rising from 5.7% to 58.8%, and pain during sexual intercourse was reported by 45.8% of them. Having higher education degree decreased the chance of being sexually dissatisfied by 50%. The total PSRI score showed a significant decrease from the prepregnancy period (mean score = 89.8, “excellent”) to the pregnancy period (mean score = 59.2, “good”). Conclusion The mean sexual function score during pregnancy was classified as good, although most pregnant women reported at least one type of alteration in the sexual function domains, and the report of dissatisfaction was more frequent in women with lower schooling.
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Subramanian, G. Ganesan, T. Suresh Padmanabhan, I. A. Chidambaram et B. Paramasivam. « Pseudo-Derivative Feedback Controller for Automatic Generation Control in a Deregulated Power System with Hydrogen Energy Storage ». Journal of New Materials for Electrochemical Systems 24, no 2 (30 juin 2021) : 84–94. http://dx.doi.org/10.14447/jnmes.v24i2.a05.
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This paper is focused on design and application of Pseudo-Derivative Feedback (PDF) controller for Automatic Generation Control (AGC) of a two-area thermal reheat interconnected power system treated in deregulated condition. The proposed controller gains are tuned simultaneously using Flower Pollination Algorithm (FPA) in order to achieve the optimal transient response of the test system. The control performance of the PDF controller is compared with Proportional Integral (PI) and Proportional Integral Derivative (PID) controllers. Further to improve the AGC performance, Hydrogen Energy Storage (HES) are included in its control area. The execution of HES unit captures the underlying fall in frequency as well as the tie line control power deviations after a sudden load unsettling influence. The simulation results demonstrate that the proposed PDF controller enhance the dynamic response of the deregulated power system as compared with PI and PID contrtoller. The frequency oscillation and tie-line power deviations in the control zones are reduced and the settling time is additionally enhanced when HES unit takes an interest in the frequency regulation along with the traditional generators. Additionally, the Power System Restoration Indices (PSRI) is figured in view of system dynamic performances and the remedial measures to be taken can be decreed. These PSRI shows that the ancillary service requirement to enhances the effectiveness of physical task of the power system with the expanded transmission limit in the system. The presence of an Hydrogen Energy Storage (HES) water electrolyser coupled to a fuel cell improves significantly the control and operation of an energy system and provides good margin of stability of the grid system compared to that a system without HES unit.
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Irie, Kenji, Hiroyuki Araki et Yasuji Oshima. « Mutations in a Saccharomyces cerevisme host showing increased holding stability of the heterologous plasmid pSRI ». Molecular and General Genetics MGG 225, no 2 (février 1991) : 257–65. http://dx.doi.org/10.1007/bf00269857.
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Żelazny, Wiktor R., et Jan Lukáš. « Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability ». Remote Sensing 12, no 20 (21 octobre 2020) : 3462. http://dx.doi.org/10.3390/rs12203462.
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Hyperspectral imaging (HSI) has been gaining recognition as a promising proximal and remote sensing technique for crop drought stress detection. A modelling approach accounting for the treatment effects on the stress indicators’ standard deviations was applied to proximal images of oilseed rape—a crop subjected to various HSI studies, with the exception of drought. The aim of the present study was to determine the spectral responses of two cultivars, ‘Cadeli’ and ‘Viking’, representing distinctive water management strategies, to three types of watering regimes. Hyperspectral data cubes were acquired at the leaf level using a 2D frame camera. The influence of the experimental factors on the extent of leaf discolorations, vegetation index values, and principal component scores was investigated using Bayesian linear models. Clear treatment effects were obtained primarily for the vegetation indexes with respect to the watering regimes. The mean values of RGI, MTCI, RNDVI, and GI responded to the difference between the well-watered and water-deprived plants. The RGI index excelled among them in terms of effect strengths, which amounted to −0.96[−2.21,0.21] and −0.71[−1.97,0.49] units for each cultivar. A consistent increase in the multiple index standard deviations, especially RGI, PSRI, TCARI, and TCARI/OSAVI, was associated with worsening of the hydric regime. These increases were captured not only for the dry treatment but also for the plants subjected to regeneration after a drought episode, particularly by PSRI (a multiplicative effect of 0.33[0.16,0.68] for ‘Cadeli’). This result suggests a higher sensitivity of the vegetation index variability measures relative to the means in the context of the oilseed rape drought stress diagnosis and justifies the application of HSI to capture these effects. RGI is an index deserving additional scrutiny in future studies, as both its mean and standard deviation were affected by the watering regimes.
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Chalermsinsuwan, Benjapon, Pornpote Piumsomboon et Dimitri Gidaspow. « Kinetic theory based computation of PSRI riser : Part II—Computation of mass transfer coefficient with chemical reaction ». Chemical Engineering Science 64, no 6 (mars 2009) : 1212–22. http://dx.doi.org/10.1016/j.ces.2008.11.006.
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Subramanian, G. Ganesan, Albert Alexander Stonier, Geno Peter et Vivekananda Ganji. « Application of Flower Pollination Algorithm for Solving Complex Large-Scale Power System Restoration Problem Using PDFF Controllers ». Complexity 2022 (31 août 2022) : 1–12. http://dx.doi.org/10.1155/2022/7157524.
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Automatic Generation Control (AGC) in modern power systems is getting complex, due to intermittency in the output power of multiple sources along with considerable digressions in the loads and system parameters. To address this problem, this paper proposes an approach to calculate Power System Restoration Indices (PSRI) of a 2-area thermal-hydro restructured power system. This study also highlights the necessary ancillary service requirements for the system under a deregulated environment to cater to large-scale power failures and entire system outages. An abrupt change in consumer load demands and disturbances in any control region (area) of a multiarea (interrelated) system causes severe fluctuations in frequency and interarea power exchanges. However, simple Proportional and Integral (PI) controllers are most prevalent in the literature to effectively resolve AGC issues, while its integral gain is smaller due to the larger overshoot in transient performance. Therefore, an attempt has been made with a novel control strategy, known as the pseudoderivative feedforward with feedback (PDFF) controller, is developed to keep the interarea power exchanges and the frequency to the specified limits after load changes. A PDFF controller is designed and implemented using the flower pollination algorithm (FPA) to obtain optimal dynamic performance for different types of potential power flows in a restructured power system under investigation. The proposed PDFF controller localizes the zero at an optimal place that reduces the rise time of the step-response to reduce the excessive overshoot and gives much better dynamic performances as compared to the PI control structure. The Integral Square Error (ISE) is considered as a performance criterion to derive the optimized gain of the PDFF control structure using FPA. Different PSRI are computed based on the transient response of the 2-area deregulated multisource system and different restoration measures to be taken are also discussed. The simulation results clearly show that the proposed approach is very powerful in decreasing the frequency and tie-power digressions under different load perturbations.
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Araki, Hiroyuki, et Yasuji Oshima. « An autonomously replicating sequence of pSRI plasmid is effective in two yeast species, Zygosaccharomyces rouxii and Saccharomyces cerevisiae ». Journal of Molecular Biology 207, no 4 (juin 1989) : 757–69. http://dx.doi.org/10.1016/0022-2836(89)90242-8.
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Burns, Justin L., et Thomas J. DiChristina. « Anaerobic Respiration of Elemental Sulfur and Thiosulfate by Shewanella oneidensis MR-1 Requires psrA, a Homolog of the phsA Gene of Salmonella enterica Serovar Typhimurium LT2 ». Applied and Environmental Microbiology 75, no 16 (19 juin 2009) : 5209–17. http://dx.doi.org/10.1128/aem.00888-09.
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ABSTRACT Shewanella oneidensis MR-1, a facultatively anaerobic gammaproteobacterium, respires a variety of anaerobic terminal electron acceptors, including the inorganic sulfur compounds sulfite (SO3 2−), thiosulfate (S2O3 2−), tetrathionate (S4O6 2−), and elemental sulfur (S0). The molecular mechanism of anaerobic respiration of inorganic sulfur compounds by S. oneidensis, however, is poorly understood. In the present study, we identified a three-gene cluster in the S. oneidensis genome whose translated products displayed 59 to 73% amino acid similarity to the products of phsABC, a gene cluster required for S0 and S2O3 2− respiration by Salmonella enterica serovar Typhimurium LT2. Homologs of phsA (annotated as psrA) were identified in the genomes of Shewanella strains that reduce S0 and S2O3 2− yet were missing from the genomes of Shewanella strains unable to reduce these electron acceptors. A new suicide vector was constructed and used to generate a markerless, in-frame deletion of psrA, the gene encoding the putative thiosulfate reductase. The psrA deletion mutant (PSRA1) retained expression of downstream genes psrB and psrC but was unable to respire S0 or S2O3 2− as the terminal electron acceptor. Based on these results, we postulate that PsrA functions as the main subunit of the S. oneidensis S2O3 2− terminal reductase whose end products (sulfide [HS−] or SO3 2−) participate in an intraspecies sulfur cycle that drives S0 respiration.
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Frank, Thiago, Anne Smith, Bill Houston, Emily Lindsay et Xulin Guo. « Differentiation of Six Grassland/Forage Types in Three Canadian Ecoregions Based on Spectral Characteristics ». Remote Sensing 14, no 9 (28 avril 2022) : 2121. http://dx.doi.org/10.3390/rs14092121.
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Differentiation of grassland/forage types and accurate estimates of their location and extent are important for understanding their ecological processes and for applying appropriate management practices. We are aiming to reveal the different spectral characteristics of six grassland/forage land covers in three ecoregions located in the Canadian Prairies, based on field data and satellite images. Three spectral indices representing productivity (Normalized Difference Vegetation Index (NDVI)), moisture content (Normalized Difference Moisture Index (NDMI)), and plant photosynthetic activity (Plant Senescence Reflectance Index (PSRI)) were used for comparison of means, comparison of coefficient of variation (CV), and analysis of variance (ANOVA). The results indicated that different grassland types show distinguishable spectral characteristics in the Moist-Mixed and Mixed Ecoregions, while it was not possible to differentiate the classes in the Fescue Ecoregion. To further investigate the within-sites and between-sites heterogeneity, we calculated the CV in a 3 × 3 window and placed them in comparative triangles to demonstrate their potential separability. Results indicated that the triangles based on the CV offered greater class separability in the Fescue Ecoregion and in the Mixed Ecoregion.
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Balasundram, Siva K., et Yen Mee Chong. « Use of Selected Spectral Ratios to Assess the Response of Pineapple to Potassium Nutrition ». Journal of Smart Science and Technology 1, no 1 (26 septembre 2021) : 16–22. http://dx.doi.org/10.24191/jsst.v1i1.11.
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Potassium (K) nutrition in pineapple grown on tropical peat can be problematic due to high precipitation which encourages leaching losses. Non-destructive tools that can assess K deficiency and the accompanying changes in biophysical and biochemical properties within pineapple is a good strategy to employ. In this study, we assessed the biophysical changes in pineapple (var. MD2) in response to different K rates by using a hyperspectral approach. K deficiency was detected at 171 days after planting. Shortage of K also exhibited a shift in red edge towards shorter wavelengths between 500-700 nm. In addition, spectral ranges of 430-680 nm, as well as 680-752 nm were found to be most effective in differentiating spectral response to varying K rates. Three vegetation indices, i.e. Normalized Pigment Chlorophyll Index (NPCI), Plant Senescence Index (PSRI) and Red-edge Vegetation Index (RVSI) were found to best describe K treatment effects on pineapple canopy reflectance. This study could be extended further to include pineapple varieties other than MD2, and also key nutrients, such as N and P, for better fertilizer management in peat-grown pineapple.
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Marzano, Gilberto, Velta Lubkina et Svetlana Usca. « DEVELOPING PRACTICES FOR ADULT EDUCATORS ’ EVALUATION ». SOCIETY, INTEGRATION, EDUCATION. Proceedings of the International Scientific Conference 2 (24 juillet 2015) : 162. http://dx.doi.org/10.17770/sie2014vol2.672.
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In recent years, there have been significant changes in the field of adult education. These changes have brought new opportunities for adult educators, expanding the types of programs offered to adult learners. The increasing role and spreading of adult education has given rise to the issue of adult educators' evaluation, because of overarching goal of evaluation is to improve the quality of the work of an institution. This paper focuses on EduEval (Evaluation for the Professional Development of Adult Education Staff), an EU funded project which is grounded in an action-research based on the active involvement of practitioners engaged in adult educators’ evaluation. The project aims at investigating the issue of adult educators' evaluation in some European countries (which are: Latvia, Italy, Poland, Spain and Greece). Thus paper illustrates the project objectives, and reports from the scientific approach which is used by Personality Socialization Research Institute (PSRI) of Rezeknes Augstskola (Latvia) to conduct an explorative survey on evaluation practices in the specific scope of adult social educators.
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Yang, Ji, Thomas W. Russell, Dianna M. Hocking, Jennifer K. Bender, Yogitha N. Srikhanta, Marija Tauschek et Roy M. Robins-Browne. « Control of Acid Resistance Pathways of Enterohemorrhagic Escherichia coli Strain EDL933 by PsrB, a Prophage-Encoded AraC-Like Regulator ». Infection and Immunity 83, no 1 (3 novembre 2014) : 346–53. http://dx.doi.org/10.1128/iai.02758-14.
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EnterohemorrhagicEscherichia coli(EHEC) O157:H7 causes bloody diarrhea and hemolytic-uremic syndrome (HUS) and is the most prevalentE. coliserotype associated with food-borne illness worldwide. This pathogen is transmitted via the fecal-oral route and has a low infectious dose that has been estimated to be between 10 and 100 cells. We and others have previously identified three prophage-encoded AraC-like transcriptional regulators, PatE, PsrA, and PsrB in the EHEC O157:H7 EDL933 strain. Our analysis showed that PatE plays an important role in facilitating survival of EHEC under a number of acidic conditions, but the contribution of PsrA and PsrB to acid resistance (AR) was unknown. Here, we investigated the involvement of PsrA and PsrB in the survival ofE. coliO157:H7 in acid. Our results showed that PsrB, but not PsrA, enhanced the survival of strain EDL933 under various acidic conditions. Transcriptional analysis using promoter-lacZreporters and electrophoretic mobility shift assays demonstrated that PsrB activates transcription of thehdeAoperon, which encodes a major acid stress chaperone, by interacting with its promoter region. Furthermore, using a mouse model, we showed that expression of PsrB significantly enhanced the ability of strain EDL933 to overcome the acidic barrier of the mouse stomach. Taken together, our results indicate that EDL933 acquired enhanced acid tolerance via horizontally acquired regulatory genes encoding transcriptional regulators that activate its AR machinery.
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Fabre, Sophie, Rollin Gimenez, Arnaud Elger et Thomas Rivière. « Unsupervised Monitoring Vegetation after the Closure of an Ore Processing Site with Multi-Temporal Optical Remote Sensing ». Sensors 20, no 17 (25 août 2020) : 4800. http://dx.doi.org/10.3390/s20174800.
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Ore processing is a source of soil heavy metal pollution. Vegetation traits (structural characteristics such as spatial cover and repartition; biochemical parameters—pigment and water contents, growth rate, phenological cycle…) and plant species identity are indirect and powerful indicators of residual contamination detection in soil. Multi-temporal multispectral satellite imagery, such as the Sentinel-2 time series, is an operational environment monitoring system widely used to access vegetation traits and ensure vegetation surveillance across large areas. For this purpose, methodology based on a multi-temporal fusion method at the feature level is applied to vegetation monitoring for several years from the closure and revegetation of an ore processing site. Features are defined by 26 spectral indices from the literature and seasonal and annual change detection maps are inferred. Three indices—CIred-edge (CIREDEDGE), IRECI (Inverted Red-Edge Chlorophyll Index) and PSRI (Plant Senescence Reflectance Index)—are particularly suitable for detecting changes spatially and temporally across the study area. The analysis is conducted separately for phyto-stabilized vegetation zones and natural vegetation zones. Global and specific changes are emphasized and explained by information provided by the site operator or meteorological conditions.
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Mallmann, C. L., A. F. Zaninni et W. Pereira Filho. « VEGETATION INDEX BASED IN UNMANNED AERIAL VEHICLE (UAV) TO IMPROVE THE MANAGEMENT OF INVASIVE PLANTS IN PROTECTED AREAS, SOUTHERN BRAZIL ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (6 novembre 2020) : 521–24. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-521-2020.
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Abstract. The biological invasion is considered the second largest global threat to the maintenance and conservation of natural ecosystems biodiversity. Strategies and actions that guide the control and monitoring of invasive species in protected areas are still a challenge on the management of these areas. Remote sensing is potential tool to detect and monitoring these species, gaining a timeline scale and allowing the adoption of more effective control methods. In this study, search to evaluate the vegetation index potential by using multispectral images acquired by UAV as a support on detection and monitoring of invasive plants in Quarta Colônia State Park located on the Brazil’s southern region. A sampling area with a density of invasive plants above 80% was evaluated, with predominance of Psidium guajava and Ligustrum lucidum, generating a large data set from the extracted indexes. Among the evaluated index, the ones that showed the most potential in this study were Green Normalized Difference Vegetation Index (GNDVI), Plant Senescence Reflectance Index (PSRI) and Red Green Ratio Index (RGRI). Believe us that the use of UAVs platforms will be an important tool for the management of invasive species in protected areas.
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Ha, Thuan, Yanben Shen, Hema Duddu, Eric Johnson et Steven J. Shirtliffe. « Quantifying Hail Damage in Crops Using Sentinel-2 Imagery ». Remote Sensing 14, no 4 (16 février 2022) : 951. http://dx.doi.org/10.3390/rs14040951.
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Hailstorms are a frequent natural weather disaster in the Canadian Prairies that can cause catastrophic damage to field crops. Assessment of damage for insurance claims requires insurance inspectors to visit individual fields and estimate damage on individual plants. This study computes temporal profiles and estimates the severity of hail damage to crops in 54 fields through the temporal analysis of vegetation indices calculated from Sentinel-2 images. The damage estimation accuracy of eight vegetative indices in different temporal analyses of delta index (pre-and post-hail differences) or area under curve (AUC) index (time profiles of index affected by hail) was compared. Hail damage was accurately quantified by using the AUC of 32 days of Normalized Difference Vegetation Indices (NDVI), Normalized Difference Water Index (NDWI), and Plant Senescence Radiation Index (PSRI). These metrics were well correlated with ground estimates of hail damage in canola (r = −0.90, RMSE = 8.24), wheat (r = −0.86, RMSE = 12.27), and lentil (r = 0.80, RMSE = 17.41). Thus, the time-series changes in vegetation indices had a good correlation with ground estimates of hail damage which may allow for more accurate assessment of the extent and severity of hail damage to crop land.
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Jardim, Carlos Cesar Silva, Alessandra Conceição de Oliveira, Anamari Viegas de Araújo Motomiya, Rosilene Oliveira dos Santos et Valéria Lima da Silva. « AVALIAÇÃO DA VARIAÇÃO ESPECTRAL DO CERRADO POR SENSOR REMOTO PASSIVO ». REVISTA ENGENHARIA NA AGRICULTURA - REVENG 27, no 6 (21 octobre 2019) : 542–55. http://dx.doi.org/10.13083/reveng.v27i6.947.
Texte intégralRésumé :
O Cerrado é a segunda maior cobertura vegetal natural do Brasil, perfazendo cerca de 23% da área total, localizado na maioria de sua extensão no Planalto Central Brasileiro. Para a análise do Cerrado é utilizado o sensoriamento remoto, que está amplamente aplicado para o monitoramento de coberturas vegetais, e principalmente avaliando o desempenho espacial e/ou fisiológico. Os índices de vegetação são técnicas para monitoramento das plantas, sendo os índices utilizados green NDVI, red NDVI, NPCI, PSRI, SAVI, SR analisados com auxílio das imagens do satélite Landsat 8, e o software Arcmap®. O objetivo do trabalho foi analisar imagens do satélite Landsat 8 para a caracterização sazonal da vegetação do Cerrado correlacionando com os elementos climáticos de mesmo período, com intuito de verificar a resposta ambiental aos fatores abióticos. A correlação linear de Pearson demonstrou uma forte correlação entre os índices, e a correlação dos índices de vegetação com os dados climáticos demonstraram uma forte correlação com a umidade relativa do ar e uma fraca influência para o balanço hídrico. Conclui-se que as imagens obtidas gratuitamente são eficientes para caracterização do acúmulo de biomassa em vegetações naturais.
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Fernández-Manso, Alfonso, et Carmen Quintano. « A Synergetic Approach to Burned Area Mapping Using Maximum Entropy Modeling Trained with Hyperspectral Data and VIIRS Hotspots ». Remote Sensing 12, no 5 (6 mars 2020) : 858. http://dx.doi.org/10.3390/rs12050858.
Texte intégralRésumé :
Southern European countries, particularly Spain, are greatly affected by forest fires each year. Quantification of burned area is essential to assess wildfire consequences (both ecological and socioeconomic) and to support decision making in land management. Our study proposed a new synergetic approach based on hotspots and reflectance data to map burned areas from remote sensing data in Mediterranean countries. It was based on a widely used species distribution modeling algorithm, in particular the Maximum Entropy (MaxEnt) one-class classifier. Additionally, MaxEnt identifies variables with the highest contribution to the final model. MaxEnt was trained with hyperspectral indexes (from Earth-Observing One (EO-1) Hyperion data) and hotspot information (from Visible Infrared Imaging Radiometer Suite Near Real-Time 375 m active fire product). Official fire perimeter measurements by Global Positioning System acted as a ground reference. A highly accurate burned area estimation (overall accuracy = 0.99%) was obtained, and the indexes which most contributed to identifying burned areas included Simple Ratio (SR), Red Edge Normalized Difference Vegetation Index (NDVI750), Normalized Difference Water Index (NDWI), Plant Senescence Reflectance Index (PSRI), and Normalized Burn Ratio (NBR). We concluded that the presented methodology enables accurate burned area mapping in Mediterranean ecosystems and may easily be automated and generalized to other ecosystems and satellite sensors.
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McDonald, Mary Ruth, Cyril Selasi Tayviah et Bruce D. Gossen. « Human vs. Machine, the Eyes Have It. Assessment of Stemphylium Leaf Blight on Onion Using Aerial Photographs from an NIR Camera ». Remote Sensing 14, no 2 (9 janvier 2022) : 293. http://dx.doi.org/10.3390/rs14020293.
Texte intégralRésumé :
Aerial surveillance could be a useful tool for early detection and quantification of plant diseases, however, there are often confounding effects of other types of plant stress. Stemphylium leaf blight (SLB), caused by the fungus Stemphylium vesicarium, is a damaging foliar disease of onion. Studies were conducted to determine if near-infrared photographic images could be used to accurately assess SLB severity in onion research trials in the Holland Marsh in Ontario, Canada. The site was selected for its uniform soil and level topography. Aerial photographs were taken in 2015 and 2016 using an Xnite-Canon SX230NDVI with a near-infrared filter, mounted on a modified Cine Star—8 MK Heavy Lift RTF octocopter UAV. Images were taken at 15–20 m above the ground, providing an average of 0.5 cm/pixel and a field of view of 15 × 20 m. Photography and ground assessments of disease were carried out on the same day. NDVI (normalized difference vegetation index), green NDVI, chlorophyll index and plant senescence reflective index (PSRI) were calculated from the images. There were differences in SLB incidence and severity in the field plots and differences in the vegetative indices among the treatments, but there were no correlations between disease assessments and any of the indices.
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Diah, Rodhiah Diah. « FAKTOR INTERNAL YANG MENENTUKAN KINERJA USAHA RITEL PRODUK FASHION di TANGERANG ». Jurnal Muara Ilmu Ekonomi dan Bisnis 2, no 1 (11 septembre 2018) : 113. http://dx.doi.org/10.24912/jmieb.v2i1.1617.
Texte intégralRésumé :
Penelitian ini bertujuan untuk menjelaskan faktor-faktor yang menentukan kinerja suatu usaha kecil ritel fashion , menentukan diantara faktor tersebut mana yang paling dominan dapat dilakukan untuk mengukur kinerja usaha ritel. Diteliti 200 pedagang ritel produk fashion yang terdapat di 10 lokasi usaha ritel pasar tradisional di Tangerang, dipilih secara purposive sampling pada beberapa pasar tradisional di Tangerang. Sebuah evaluasi dilakukan dengan sejumlah pendekatan faktor-faktor kinerja yang ditemukan dalam beberapa literature. Meliputi faktor internal yang dipersepsikan dari pemilik ritel berdasarkan penilaian subyektif. Pengumpulan data diperoleh melalui kuesioner dengan menggunakan skala likert. Analisis dilakukan dengan menggunakan analisis faktor melalui program SPSS Versi 20. Hasil dari penelitian menunjukan bahwa dari 27 item faktor internal direduksi menjadi 6 buah faktor yang dominan yaitu SDM2 (Sumber daya manusia pada item jiwa kepemimpinan, TO3 (Operasional pada ketersediaan mesin/peralatan), PSR2 (Pasar dan Pemasaran pada daya beli masyarakat), PSR9 ( pasar dan pemasaran pada kegiatan promosi), KEU2 (keuangan modal pinjaman),PSR4 (pasar dan pemasaran pada produk pengganti) merupakan faktor yang terbentuk sebagai penentu kinerja usaha ritel. Dan yang paling dominan mempengaruhi kinerja usaha ritel terdapat pada faktor PSR2 (pasar dan pemasaran dalam daya beli masyarakat). Dengan demikian hasil penelitian diharapkan dapat memberikan kontribusi bagi pedagang ritel dan input berbagai faktor internal kinerja pada usaha kecil ritel yang harus diperbaiki. Sehingga kelayakan strategis bagi usaha ritel dapat terus ditingkatkan. Kata Kunci: usaha ritel, kinerja, faktor internal, factor analysis
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Mamelin, Yu V., G. F. Kopytov et V. Yu Buzko. « Studying Optical Characteristics of Diffused Light Reflecting from Naturally Senescing Leaves of Deciduous Trees ». Herald of the Bauman Moscow State Technical University. Series Natural Sciences, no 5 (92) (octobre 2020) : 72–82. http://dx.doi.org/10.18698/1812-3368-2020-5-72-82.
Texte intégralRésumé :
Study object included leaves of deciduous trees in the Krasnodar Territory at different stages of senescing visually manifested in their color alteration. Study subject was the optical characteristics of light diffused reflection from green, yellow-green and yellow leaves of deciduous trees in the Krasnodar Territory during the autumn season. Work objective lies in identifying the possibility to establish differences between green leaves of deciduous trees, and yellow-green and yellow leaves of deciduous trees using the terrain multispectral and hyperspectral sounding methods, as well as collecting information on spectral characteristics of the diffused light being reflected from various biological objects. Results of quantitative and qualitative analysis of data obtained through the diffused light reflectance spectroscopy from leaves of deciduous trees are presented. Narrow-band vegetation indices mNDVI705, mSR705, CRI1, SIPI and PSRI were used in quantitative analysis of data on the diffused light reflection spectra obtained from green, yellow-green and yellow leaves of deciduous trees. It was revealed that the use of narrow-band vegetation indices in the remote sensing algorithms using multi- and hyperspectral cameras makes it possible to rather accurately distinguish leaves at different stages of senescing. Optical characteristics of diffused light reflection from green, yellow-green and yellow leaves of deciduous trees, which are typical species of trees in urban and rural plantings in the Krasnodar Territory, are described for the first time
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Jiang, Yu, Huijuan Wei, Shengxi Hou, Xuebo Yin, Shanshan Wei et Dong Jiang. « Estimation of Maize Yield and Protein Content under Different Density and N Rate Conditions Based on UAV Multi-Spectral Images ». Agronomy 13, no 2 (31 janvier 2023) : 421. http://dx.doi.org/10.3390/agronomy13020421.
Texte intégralRésumé :
In the field of precision agriculture research, it is very important to monitor crop growth in time so as to effectively conduct field diagnosis and management and accurately predict yield and quality. In this experiment, the relationship between the vegetation index of Zhengdan 958 and Suyu 41 and their yield and quality when reducing N application (25 and 50% N reduction compared to local conventional N application rate) under low, medium and high planting densities (60,000, 75,000 and 90,000 plants·ha−1) during 2018–2020 was investigated using multispectral images obtained from UAV monitoring. The results showed that under different density treatments, the normalized vegetation index (NDVI) and ratio vegetation index (RVI) decreased with the decrease in nitrogen application, while the plant senescence reflectance index (PSRI) increased. Through principal component analysis (PCA) and subordinate function analysis, the comprehensive score of each treatment can reflect the maize yield and total protein content under each treatment. Based on the vegetation index, predictive models of maize yield and protein content were established. The best prediction period for grain yield and protein content were physiological maturity and 35 days after silking (R4), respectively. The R2 of the predictive models are greater than 0.734 and 0.769, respectively. Multi-period and multi-vegetation indexes can better monitor crop growth and help agricultural field management.
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Liu, Xuefang, Wentao Liu, Haitao Wei et Quanwen Zhu. « Monitoring Wheat Leaf Nitrogen Content Using HJ-CCD Images and Ridge Regression ». Journal of Biobased Materials and Bioenergy 16, no 5 (1 octobre 2022) : 707–14. http://dx.doi.org/10.1166/jbmb.2022.2232.
Texte intégralRésumé :
Remote sensing has long been used in agricultural applications, especially crop growth monitoring. Leaf nitrogen content (LNC) of field crop It is an important indicator of crop quality final grain yield. Many studies have used remote sensing technology to estimate the LNC of various crops. However, the performances of these estimations vary. To further improve the estimation accuracy, this research investigated the quantifiable relationships between satellite remote sensing variable images acquired from the Chinese four-band HJ-CCD sensor and wheat LNC. The ridge regression algorithms were used to build and verify multivariate remote sensing modelling of wheat LNC estimation. Results revealed that collinearities existed between wheat LNC and most of the chosen remote sensing variables. The ridge regression model for monitoring of wheat LNC adopted NDVI, GNDVI, NRI, SIPI, PSRI, DVI, RVI and EVI as independent variables and obtained optimal regularization coefficient (lambda, λ) 0.024 and RMSE 0.128 using cross validation method. Through validation from data sets of different years and regions, the coefficients of determination (R2) of wheat LNC monitoring model were 0.701 and 0.641, respectively, while its RMSE were 0.114 and 0.121, respectively. The results demonstrated that this model could be used for monitoring wheat LNC with high accuracy and confirmed that model was not limited by years and regions of wheat planting.
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Tilly, N., F. Reddig, U. Lussem et G. Bareth. « FIRST INVESTIGATION OF MEDITERRANEAN OAK TREE VITALITY WITH HIGH-RESOLUTION WORLDVIEW-3 SATELLITE DATA : COMPARING TEN VEGETATION INDICES AND THREE MACHINE LEARNING CLASSIFIERS ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (21 août 2020) : 1069–76. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1069-2020.
Texte intégralRésumé :
Abstract. Oak trees are the primary component in Mediterranean agro-silvopastoral systems. Since the second half of the 20th century, however, a severe oak decline has been observed. Climate change reinforces this problem, which is consistent with worldwide observable tree dieback. As the trees have significant ecological and socio-economic functions, their observation and assessment of vitality are increasingly researched. Satellite remote sensing is very well suitable for large-scale surveys of the extensive and sometimes hardly accessible areas. This study investigates the usability of high-resolution WorldView-3 data for the classification of tree vitality. The ground truth was collected on an Andalusian dehesa at the end of September 2019, timely corresponding with the satellite data acquisition. After customary post-processing of the WorldView-3 data, 10 vegetation indices (ARVI, CIgreen, CSI, DPI, EVI, GNDVI, NDVI, PSRI, RENDVI, and RGI) were calculated from the multispectral image. Three machine learning classifiers (Maximum Likelihood, Random Forest, and Support Vector Machine) were then used for a supervised image classification with three vitality classes (healthy, sick, and dead). Independent ground truth data were used for the validation. The best results were achieved with the red edge normalized difference vegetation index (RENDVI) and the Support Vector Machine classifier (F1 scores between 0.27 and 0.72). A maximal overall accuracy of around 0.6 is, however, improvable. Further studies should focus on other classification methods, more reliable ground truth, and combined analyses of spectral and structural data.
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Nur Aini, Bariroh Isriya, Dwi Puspitasari et Yan Watequlis Syaifudin. « IDENTIFIKASI KEMIRIPAN JUDUL TUGAS AKHIR PSTI DAN PSMI DI POLITEKNIK NEGERI MALANG ». Jurnal Informatika Polinema 1, no 4 (22 mars 2017) : 62. http://dx.doi.org/10.33795/jip.v1i4.125.
Texte intégralRésumé :
Membuat tugas akhir atau skripsi merupakan syarat yang harus dipenuhi oleh mahasiswa untuk kelulusan. Tak jarang karya yang dihasilkan memiliki kemiripan baik dari judul ataupun isi. Hal ini menjadi permasalahan tersendiri karena sebaiknya tugas akhir atau skripsi memiliki judul yang berbeda supaya karya yang dihasilkan semakin beragam. Untuk mengatasi permasalahan diatas perlunya dilakukan seleksi saat akan mengajukan tugas akhir atau skripsi. Seleksi awal dapat dilakukan melalui judul yang akan diajukan. Seleksi dilakukan dengan cara melihat serta membandingkan antara judul yang diusulkan dengan judul yang sudah pernah diajukan sebelumnya. Dalam penelitian ini teknik yang digunakan untuk menyelesaikan masalah adalah dengan menggunakan teknik text mining. Teknik text mining merupakan penerapan konsep dan teknik data mining untuk mencari pola dalam teks. Proses penganalisisan teks guna mendapat informasi yang bermanfaat untuk tujuan tertentu. Proses data mining untuk data dokumen atau teks memerlukan lebih banyak tahapan, mengingat data teks memiliki karakteristik yang lebih kompleks daripada data biasa.
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Weisz, Daniel A., Virginia M. Johnson, Dariusz M. Niedzwiedzki, Min Kyung Shinn, Haijun Liu, Clécio F. Klitzke, Michael L. Gross, Robert E. Blankenship, Timothy M. Lohman et Himadri B. Pakrasi. « A novel chlorophyll protein complex in the repair cycle of photosystem II ». Proceedings of the National Academy of Sciences 116, no 43 (8 octobre 2019) : 21907–13. http://dx.doi.org/10.1073/pnas.1909644116.
Texte intégralRésumé :
In oxygenic photosynthetic organisms, photosystem II (PSII) is a unique membrane protein complex that catalyzes light-driven oxidation of water. PSII undergoes frequent damage due to its demanding photochemistry. It must undergo a repair and reassembly process following photodamage, many facets of which remain unknown. We have discovered a PSII subcomplex that lacks 5 key PSII core reaction center polypeptides: D1, D2, PsbE, PsbF, and PsbI. This pigment–protein complex does contain the PSII core antenna proteins CP47 and CP43, as well as most of their associated low molecular mass subunits, and the assembly factor Psb27. Immunoblotting, mass spectrometry, and ultrafast spectroscopic results support the absence of a functional reaction center in this complex, which we call the “no reaction center” complex (NRC). Analytical ultracentrifugation and clear native PAGE analysis show that NRC is a stable pigment–protein complex and not a mixture of free CP47 and CP43 proteins. NRC appears in higher abundance in cells exposed to high light and impaired protein synthesis, and genetic deletion of PsbO on the PSII luminal side results in an increased NRC population, indicative that NRC forms in response to photodamage as part of the PSII repair process. Our finding challenges the current model of the PSII repair cycle and implies an alternative PSII repair strategy. Formation of this complex may maximize PSII repair economy by preserving intact PSII core antennas in a single complex available for PSII reassembly, minimizing the risk of randomly diluting multiple recycling components in the thylakoid membrane following a photodamage event.
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DMİTRİEV, Pavel, Boris KOZLOVSKY, Anastasiya DMİTRİEVA, Vladimir LYSENKO, Vasily CHOKHELİ, Tatiana MİNKİNA, Saglara MANDZHİEVA, Svetlana SUSHKOVA et Tatyana VARDUNİ. « Identification of species of the genus Quercus L. with different responses to soil and climatic conditions according to hyperspectral survey data ». EURASIAN JOURNAL OF SOIL SCIENCE (EJSS) 12, no 1 (1 janvier 2023) : 37–62. http://dx.doi.org/10.18393/ejss.1183524.
Texte intégralRésumé :
Soil standing may be studied indirectly using remote sensing through an assessment of state of the plants growing on it. The ability to evaluate the physiological state of plants using the hyperspectral survey data also provides a tool to characterize vegetation cover and individual samples of woody plants. In the present work the hyperspectral imaging was applied to identify the species of the woody plants evaluating the differences in their physiological state. Samples of Quercus macrocarpa Michx., Q. robur L. and Q. rubra L. were studied using Cubert UHD-185 hyperspectral camera over five periods with an interval of 7-10 days. In total, 80 vegetation indices (VIs) were calculated. Sample sets of values of VIs were analyzed using analysis of variance (ANOVA), principal component analysis (PCA), decision tree (DT), random forest (RF) methods. It was shown using the ANOVA, that the following VIs are the most dependent on the species affiliation of the samples: Carter2, Carter3, Carter4, CI, CI2, CRI4, Datt, Datt2, GMI2, Maccioni, mSR2, MTCI, NDVI2, OSAVI2, PRI, REP_Li, SR1, SR2, SR6, Vogelmann, Vogelmann2, Vogelmann4. VIs that are effective for the separation of oak species, were also revealed using the DT method – these are Boochs, Boochs2, CARI, CRI1, CRI3, D1, D2, Datt, Datt3; Datt4, Datt5, DD, DDn, EGFN, Gitelson, MCARI2, MTCI, MTVI, NDVI3, PRI, PSND, PSRI, RDVI, REP_Li, SPVI, SR4, Vogelmann, Vogelmann2, Vogelmann3. PCA and RF methods reliably differentiated Q. rubra from Q. robur and Q. macrocarpa. Q. rubra, unlike other species, was under stress from the impact of soil pH against the background of drought. This was manifested in leaf chlorosis. Influence of the environmental stress factors on the reliability and efficiency of species identification was demonstrated. Q. robur and Q. macrocarpawere were poorly separated by PCA and RF methods all over the five periods of the experiment.
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Schaffer, Frederick M., Ravinder Agarwal, Jutta Helm, Robert L. Gingell, J. Michael A. Roland et Kathleen M. O'Neil. « Poststreptococcal Reactive Arthritis and Silent Carditis : A Case Report and Review of the Literature ». Pediatrics 93, no 5 (1 mai 1994) : 837–39. http://dx.doi.org/10.1542/peds.93.5.837.
Texte intégralRésumé :
Between 1984 and 1988, a resurgence of acute rheumatic fever (ARF) was reported in several pediatric centers.1-3 During the same time, pediatric cases,4-6 and, recently, adult cases6 of poststreptococcal reactive arthritis (PSRA) have been reported. Although several of these patients had or developed multisystemic manifestations,4,5 none of these cases fully adhered to the guidelines of the revised Jones criteria.7 Thus, these individuals were given the diagnosis of PSRA or poststreptococcal rheumatic syndrome (PSRS) rather than ARF.4-6,8-10 One of the leading causes of acquired pediatric heart disease in North America is carditis of ARF,3 and severe cases can result in congestive heart failure, the need for valve replacement, or death.11
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Bergdahl, Roland, Christin Grundström, Patrik Storm, Wolfgang Schröder et Uwe Sauer. « Photosystem II assembly factor HCF136 from A. thaliana at 1.67 Å resolution ». Acta Crystallographica Section A Foundations and Advances 70, a1 (5 août 2014) : C1170. http://dx.doi.org/10.1107/s2053273314088299.
Texte intégralRésumé :
The High Chlorophyll Fluorescence 136 protein (HCF136) is essential for the assembly and repair of Photosystem II (PSII) and its central reaction centre (RC)[1]. HCF136 is an abundant protein in the thylakoid lumen and has been suggested to directly interact with subunits of the RC. The multi-subunit pigment-protein PSII complex is imbedded in the thylakoid membrane of the oxygenic photosynthetic organisms, and responsible for water splitting during oxygenic photosynthesis. PSII harbours more than 20 different integral and peripheral membrane proteins and its assembly requires a high level of coordination[2]. Two proteins D1 (psbA) and D2 (psbD) form the core of the complex and bind most of the redox-active co-factors. The PSII RC contains, in addition to D1 and D2, the intrinsic PsbI subunit and cytochrome b559. Light is a harmful substrate and subunits are damaged during the water-splitting reaction. The largest irreversible damage is experienced by the central D1 protein that has the highest turnover rate of all thylakoid proteins. Analysis of mutated A. thaliana has identified HCF136 as an essential factor for PSII RC assembly and RC turnover and repair[3]. In order to gain functional and structural insight in the way the HCF136 protein is involved in the PSII repair cycle, we have cloned, expressed, purified and crystallized the HCF136 protein from A. thaliana. Here we present the structure of this doughnut shaped WD40 domain family protein determined at 1.67 Å resolution. Biochemical and biophysical analysis of HCF136 and components of the PSII RC are under way.
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Zhang, Hao, Haitao Ge, Ye Zhang, Yingchun Wang et Pengpeng Zhang. « Slr0320 Is Crucial for Optimal Function of Photosystem II during High Light Acclimation in Synechocystis sp. PCC 6803 ». Life 11, no 4 (26 mars 2021) : 279. http://dx.doi.org/10.3390/life11040279.
Texte intégralRésumé :
Upon exposure of photosynthetic organisms to high light (HL), several HL acclimation responses are triggered. Herein, we identified a novel gene, slr0320, critical for HL acclimation in Synechocystis sp. PCC 6803. The growth rate of the Δslr0320 mutant was similar to wild type (WT) under normal light (NL) but severely declined under HL. Net photosynthesis of the mutant was lower under HL, but maximum photosystem II (PSII) activity was higher under NL and HL. Immunodetection revealed the accumulation and assembly of PSII were similar between WT and the mutant. Chlorophyll fluorescence traces showed the stable fluorescence of the mutant under light was much higher. Kinetics of single flash-induced chlorophyll fluorescence increase and decay revealed the slower electron transfer from QA to QB in the mutant. These data indicate that, in the Δslr0320 mutant, the number of functional PSIIs was comparable to WT even under HL but the electron transfer between QA and QB was inefficient. Quantitative proteomics and real-time PCR revealed that expression profiles of psbL, psbH and psbI were significantly altered in the Δslr0320 mutant. Thus, Slr0320 protein plays critical roles in optimizing PSII activity during HL acclimation and is essential for PSII electron transfer from QA to QB.
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Nguyen, Canh, Vasit Sagan, Matthew Maimaitiyiming, Maitiniyazi Maimaitijiang, Sourav Bhadra et Misha T. Kwasniewski. « Early Detection of Plant Viral Disease Using Hyperspectral Imaging and Deep Learning ». Sensors 21, no 3 (22 janvier 2021) : 742. http://dx.doi.org/10.3390/s21030742.
Texte intégralRésumé :
Early detection of grapevine viral diseases is critical for early interventions in order to prevent the disease from spreading to the entire vineyard. Hyperspectral remote sensing can potentially detect and quantify viral diseases in a nondestructive manner. This study utilized hyperspectral imagery at the plant level to identify and classify grapevines inoculated with the newly discovered DNA virus grapevine vein-clearing virus (GVCV) at the early asymptomatic stages. An experiment was set up at a test site at South Farm Research Center, Columbia, MO, USA (38.92 N, −92.28 W), with two grapevine groups, namely healthy and GVCV-infected, while other conditions were controlled. Images of each vine were captured by a SPECIM IQ 400–1000 nm hyperspectral sensor (Oulu, Finland). Hyperspectral images were calibrated and preprocessed to retain only grapevine pixels. A statistical approach was employed to discriminate two reflectance spectra patterns between healthy and GVCV vines. Disease-centric vegetation indices (VIs) were established and explored in terms of their importance to the classification power. Pixel-wise (spectral features) classification was performed in parallel with image-wise (joint spatial–spectral features) classification within a framework involving deep learning architectures and traditional machine learning. The results showed that: (1) the discriminative wavelength regions included the 900–940 nm range in the near-infrared (NIR) region in vines 30 days after sowing (DAS) and the entire visual (VIS) region of 400–700 nm in vines 90 DAS; (2) the normalized pheophytization index (NPQI), fluorescence ratio index 1 (FRI1), plant senescence reflectance index (PSRI), anthocyanin index (AntGitelson), and water stress and canopy temperature (WSCT) measures were the most discriminative indices; (3) the support vector machine (SVM) was effective in VI-wise classification with smaller feature spaces, while the RF classifier performed better in pixel-wise and image-wise classification with larger feature spaces; and (4) the automated 3D convolutional neural network (3D-CNN) feature extractor provided promising results over the 2D convolutional neural network (2D-CNN) in learning features from hyperspectral data cubes with a limited number of samples.
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Olmo, Valentina, Enrico Tordoni, Francesco Petruzzellis, Giovanni Bacaro et Alfredo Altobelli. « Use of Sentinel-2 Satellite Data for Windthrows Monitoring and Delimiting : The Case of “Vaia” Storm in Friuli Venezia Giulia Region (North-Eastern Italy) ». Remote Sensing 13, no 8 (15 avril 2021) : 1530. http://dx.doi.org/10.3390/rs13081530.
Texte intégralRésumé :
On the 29th of October 2018, a storm named “Vaia” hit North-Eastern Italy, causing the loss of 8 million m3 of standing trees and creating serious damage to the forested areas, with many economic and ecological implications. This event brought up the necessity of a standard procedure for windthrow detection and monitoring based on satellite data as an alternative to foresters’ fieldwork. The proposed methodology was applied in Carnic Alps (Friuli Venezia Giulia, NE Italy) in natural stands dominated by Picea abies and Abies alba. We used images from the Sentinel-2 mission: 1) to test vegetation indices performance in monitoring the vegetation dynamics in the short period after the storm, and 2) to create a windthrow map for the whole Friuli Venezia Giulia region. Results showed that windthrows in forests have a significant influence on visible and short-wave infrared (SWIR) spectral bands of Sentinel-2, both in the short and the long-term timeframes. NDWI8A and NDWI were the best indices for windthrow detection (R2 = 0.80 and 0.77, respectively) and NDVI, PSRI, SAVI and GNDVI had an overall good performance in spotting wind-damaged areas (R2 = 0.60–0.76). Moreover, these indices allowed to monitor post-Vaia forest die-off and showed a dynamic recovery process in cleaned sites. The NDWI8A index, employed in the vegetation index differencing (VID) change detection technique, delimited damaged areas comparable to the estimations provided by Regional Forest System (2545 ha and 3183 ha, respectively). Damaged forests detected by NDWI8A VID ranged from 500 m to 1500 m a.s.l., mainly covering steep slopes in the south and east aspects (42% and 25%, respectively). Our results suggested that the NDWI8A VID method may be a cost-effective and accurate way to produce windthrow maps, which could limit the risks associated with fieldwork and may provide a valuable tool to plan tree removal interventions in a more efficient way.
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Guo, Jiawei, Yu Jin, Huichun Ye, Wenjiang Huang, Jinling Zhao, Bei Cui, Fucheng Liu et Jiajian Deng. « Recognition of Areca Leaf Yellow Disease Based on PlanetScope Satellite Imagery ». Agronomy 12, no 1 (23 décembre 2021) : 14. http://dx.doi.org/10.3390/agronomy12010014.
Texte intégralRésumé :
Areca yellow leaf disease is a major attacker of the planting and production of arecanut. The continuous expansion of arecanut (Areca catechu L.) planting areas in Hainan has placed a great need to strengthen the monitoring of this disease. At present, there is little research on the monitoring of areca yellow leaf disease. PlanetScope imagery can achieve daily global coverage at a high spatial resolution (3 m) and is thus suitable for the high-precision monitoring of plant pest and disease. In this paper, PlanetScope images were employed to extract spectral features commonly used in disease, pest and vegetation growth monitoring for primary models. In this paper, 13 spectral features commonly used in vegetation growth and pest monitoring were selected to form the initial feature space, followed by the implementation of the Correlation Analysis (CA) and independent t-testing to optimize the feature space. Then, the Random Forest (RF), Backward Propagation Neural Network (BPNN) and AdaBoost algorithms based on feature space optimization to construct double-classification (healthy, diseased) monitoring models for the areca yellow leaf disease. The results indicated that the green, blue and red bands, and plant senescence reflectance index (PSRI) and enhanced vegetation index (EVI) exhibited highly significant differences and strong correlations with healthy and diseased samples. The RF model exhibits the highest overall recognition accuracy for areca yellow leaf disease (88.24%), 2.95% and 20.59% higher than the BPNN and AdaBoost models, respectively. The commission and omission errors were lowest with the RF model for both healthy and diseased samples. This model also exhibited the highest Kappa coefficient at 0.765. Our results exhibit the feasible application of PlanetScope imagery for the regional large-scale monitoring of areca yellow leaf disease, with the RF method identified as the most suitable for this task. Our study provides a reference for the monitoring, a rapid assessment of the area affected and the management planning of the disease in the agricultural and forestry industries.
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Xiong, Qin, Wenwu Ye, Duseok Choi, James Wong, Yongli Qiao, Kai Tao, Yuanchao Wang et Wenbo Ma. « Phytophthora Suppressor of RNA Silencing 2 Is a Conserved RxLR Effector that Promotes Infection in Soybean and Arabidopsis thaliana ». Molecular Plant-Microbe Interactions® 27, no 12 (décembre 2014) : 1379–89. http://dx.doi.org/10.1094/mpmi-06-14-0190-r.
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The genus Phytophthora consists of notorious and emerging pathogens of economically important crops. Each Phytophthora genome encodes several hundreds of cytoplasmic effectors, which are believed to manipulate plant immune response inside the host cells. However, the majority of Phytophthora effectors remain functionally uncharacterized. We recently discovered two effectors from the soybean stem and root rot pathogen Phytophthora sojae with the activity to suppress RNA silencing in plants. These effectors are designated Phytophthora suppressor of RNA silencing (PSRs). Here, we report that the P. sojae PSR2 (PsPSR2) belongs to a conserved and widespread effector family in Phytophthora. A PsPSR2-like effector produced by P. infestans (PiPSR2) can also suppress RNA silencing in plants and promote Phytophthora infection, suggesting that the PSR2 family effectors have conserved functions in plant hosts. Using Agrobacterium rhizogenes-mediated hairy roots induction, we demonstrated that the expression of PsPSR2 rendered hypersusceptibility of soybean to P. sojae. Enhanced susceptibility was also observed in PsPSR2-expressing Arabidopsis thaliana plants during Phytophthora but not bacterial infection. These experiments provide strong evidence that PSR2 is a conserved Phytophthora effector family that performs important virulence functions specifically during Phytophthora infection of various plant hosts.
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Wang, Zheng, Fei Zhang, Xianlong Zhang, Ngai Weng Chan, Hsiang-te Kung, Xiaohong Zhou et Yishan Wang. « Quantitative Evaluation of Spatial and Temporal Variation of Soil Salinization Risk Using GIS-Based Geostatistical Method ». Remote Sensing 12, no 15 (27 juillet 2020) : 2405. http://dx.doi.org/10.3390/rs12152405.
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Soil salinization is one of the environmental threats affecting the sustainable development of arid oases in the northwest of China. Thus, it is necessary to assess the risk of soil salinity and analyze spatial and temporal changes. The objective of this paper is to develop a temporal and spatial soil salinity risk assessment method based on an integrated scoring method by combining the advantages of remote sensing and GIS technology. Based on correlation coefficient analysis to determine the weights of risk evaluation factors, a comprehensive scoring system for the risk of salinity in the dry and wet seasons was constructed for the Ebinur Lake Wetland National Nature Reserve (ELWNNR), and the risk of spatial variation of soil salinity in the study area was analyzed in the dry and wet seasons. The results show the following: (1) The risk of soil salinity during the wet season is mainly influenced by the plant senescence reflectance index (PSRI), deep soil water content (D_wat), and the effect of shallow soil salinity (SH_sal). The risk of soil salinity during the dry season is mainly influenced by shallow soil salinity (SH_sal), land use and land cover change (LUCC), and deep soil moisture content (D_wat). (2) The wet season was found to have a high risk of salinization, which is mainly characterized by moderate, high, and very high risks. However, in the dry season, the risk of salinity is mainly characterized by low and moderate risk of salinity. (3) In the ELWNNR, as the wet season changes to dry season (from May to August), moderate-risk area in the wet season easily shifts to low risk and risk-free, and the area of high risk in the wet season easily shifts to moderate risk. In general, the overall change in salinity risk of the ELWNNR showed a significant relationship with changes in lake water volume, indicating that changes in water volume play an important role in the risk of soil salinity occurrence. Ideally, the quantitative analysis of salinity risk proposed in this study, which takes into account temporal and spatial variations, can help decision makers to propose more targeted soil management options.
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Li, Xingrong, Chenghai Yang, Wenjiang Huang, Jia Tang, Yanqin Tian et Qing Zhang. « Identification of Cotton Root Rot by Multifeature Selection from Sentinel-2 Images Using Random Forest ». Remote Sensing 12, no 21 (25 octobre 2020) : 3504. http://dx.doi.org/10.3390/rs12213504.
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Cotton root rot is a destructive cotton disease and significantly affects cotton quality and yield, and accurate identification of its distribution within fields is critical for cotton growers to control the disease effectively. In this study, Sentinel-2 images were used to explore the feasibility of creating classification maps and prescription maps for site-specific fungicide application. Eight cotton fields with different levels of root rot were selected and random forest (RF) was used to identify the optimal spectral indices and texture features of the Sentinel-2 images. Five optimal spectral indices (plant senescence reflectance index (PSRI), normalized difference vegetation index (NDVI), normalized difference water index (NDWI1), moisture stressed index (MSI), and renormalized difference vegetation index (RDVI)) and seven optimal texture features (Contrast 1, Dissimilarity 1, Entory 2, Mean 1, Variance 1, Homogeneity 1, and Second moment 2) were identified. Three binary logistic regression (BLR) models, including a spectral model, a texture model, and a spectral-texture model, were constructed for cotton root rot classification and prescription map creation. The results were compared with classification maps and prescription maps based on airborne imagery. Accuracy assessment showed that the accuracies of the classification maps for the spectral, texture, and spectral-texture models were 92.95%, 84.81%, and 91.87%, respectively, and the accuracies of the prescription maps for the three respective models were 90.83%, 87.14%, and 91.40%. These results confirmed that it was feasible to identify cotton root rot and create prescription maps using different features of Sentinel-2 imagery. The addition of texture features had little effect on the overall accuracy, but it could improve the ability to identify root rot areas. The producer’s accuracy (PA) for infested cotton in the classification maps for the texture model and the spectral-texture model was 2.82% and 1.07% higher, respectively, than that of the spectral model, and the PA for treatment zones in the prescription maps for the two respective models was 8.6% and 8.22% higher than that of the spectral model. Results based on the eight cotton fields showed that the spectral model was appropriate for the cotton fields with relatively severe infestation and the spectral-texture model was more appropriate for the cotton fields with low or moderate infestation.
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Cerasoli, Sofia, Manuel Campagnolo, Joana Faria, Carla Nogueira et Maria da Conceição Caldeira. « On estimating the gross primary productivity of Mediterranean grasslands under different fertilization regimes using vegetation indices and hyperspectral reflectance ». Biogeosciences 15, no 17 (14 septembre 2018) : 5455–71. http://dx.doi.org/10.5194/bg-15-5455-2018.
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Abstract. We applied an empirical modelling approach for gross primary productivity (GPP) estimation from hyperspectral reflectance of Mediterranean grasslands undergoing different fertilization treatments. The objective of the study was to identify combinations of vegetation indices and bands that best represent GPP changes between the annual peak of growth and senescence dry out in Mediterranean grasslands. In situ hyperspectral reflectance of vegetation and CO2 gas exchange measurements were measured concurrently in unfertilized (C) and fertilized plots with added nitrogen (N), phosphorus (P) or the combination of N, P and potassium (NPK). Reflectance values were aggregated according to their similarity (r≥90 %) in 26 continuous wavelength intervals (Hyp). In addition, the same reflectance values were resampled by reproducing the spectral bands of both the Sentinel-2A Multispectral Instrument (S2) and Landsat 8 Operational Land Imager (L8) and simulating the signal that would be captured in ideal conditions by either Sentinel-2A or Landsat 8. An optimal procedure for selection of the best subset of predictor variables (LEAPS) was applied to identify the most effective set of vegetation indices or spectral bands for GPP estimation using Hyp, S2 or L8. LEAPS selected vegetation indices according to their explanatory power, showing their importance as indicators of the dynamic changes occurring in community vegetation properties such as canopy water content (NDWI) or chlorophyll and carotenoids ∕ chlorophyll ratio (MTCI, PSRI, GNDVI) and revealing their usefulness for grasslands GPP estimates. For Hyp and S2, bands performed as well as vegetation indices to estimate GPP. To identify spectral bands with a potential for improving GPP estimates based on vegetation indices, we applied a two-step procedure which clearly indicated the short-wave infrared region of the spectra as the most relevant for this purpose. A comparison between S2- and L8-based models showed similar explanatory powers for the two simulated satellite sensors when both vegetation indices and bands were included in the model. Altogether, our results describe the potential of sensors on board Sentinel-2 and Landsat 8 satellites for monitoring grassland phenology and improving GPP estimates in support of a sustainable agriculture management.
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Varo-Martínez, Mª Ángeles, et Rafael M. Navarro-Cerrillo. « Stand Delineation of Pinus sylvestris L. Plantations Suffering Decline Processes Based on Biophysical Tree Crown Variables : A Necessary Tool for Adaptive Silviculture ». Remote Sensing 13, no 3 (27 janvier 2021) : 436. http://dx.doi.org/10.3390/rs13030436.
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Many planted Pinus forests are severely affected by defoliation and mortality processes caused by pests and droughts. The mapping of forest tree crown variables (e.g., leaf area index and pigments) is particularly useful in stand delineation for the management of declining forests. This work explores the potential of integrating multispectral WorldView-2 (WV-2) and Airborne Laser Scanning (ALS) data for stand delineation based on selected tree crown variables in Pinus sylvestris plantations in southern Spain. Needle pigments (chlorophyll and carotenes) and leaf area index (LAI) were quantified. Eight vegetation indices and ALS-derived metrics were produced, and seven predictors were selected to estimate and map tree crown variables using a Random Forest method and Gini index. Chlorophylls a and b (Chla and Chlb) were significantly higher in the non-defoliated and moderately defoliated trees than in severely defoliated trees (F = 14.02, p < 0.001 for Chla; F = 13.09, p < 0.001 for Chlb). A similar response was observed for carotenoids (Car) (F = 14.13, p < 0.001). The LAI also showed significant differences among the defoliation levels (F = 26.5, p < 0.001). The model for the chlorophyll a pigment used two vegetation indices, Plant Senescence Reflectance Index (PSRI) and Carotenoid Reflectance Index (CRI); three WV-2 band metrics, and three ALS metrics. The model built to describe the tree Chlb content used similar variables. The defoliation classification model was established with a single vegetation index, Green Normalized Difference Vegetation Index (GNDVI); two metrics of the blue band, and two ALS metrics. The pigment contents models provided R2 values of 0.87 (Chla, RMSE = 12.98%), 0.74 (Chlb, RMSE = 10.39%), and 0.88 (Car, RMSE = 10.05%). The cross-validated confusion matrix achieved a high overall classification accuracy (84.05%) and Kappa index (0.76). Defoliation and Chla showed the validation values for segmentations and, therefore, in the generation of the stand delineation. A total of 104 stands were delineated, ranging from 6.96 to 54.62 ha (average stand area = 16.26 ha). The distribution map of the predicted severity values in the P. sylvestris plantations showed a mosaic of severity patterns at the stand and individual tree scales. Overall, the findings of this work underscore the potential of WV-2 and ALS data integration for the assessment of stand delineation based on tree health status. The derived cartography is a relevant tool for developing adaptive silvicultural practices to reduce Pinus sylvestris mortality in planted forests at risk due to climate change.
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Samutri, Erni. « Alteration of Mother’s Sexual Activity during Pregnancy ». Jurnal Ners dan Kebidanan Indonesia 8, no 1 (27 mai 2020) : 17. http://dx.doi.org/10.21927/jnki.2020.8(1).17-25.
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<p><strong>Background</strong>: Sexual activity during pregnancy is one of the significant issues for both pregnant women and health care provider, though rarely disclosed. Studies on this topic have been done broadly, though still no conclusion.</p><p><strong>Objective:</strong> To analize the change of mother’s sexual activity before and during pregnancy and to describe resources used by mother to find information related to sexual activity during pregnancy.</p><p><strong>Method:</strong> A descriptive cross sectional study conducted on pregnant mothers who undergo antenatal care at Tegalrejo public health center, Yogyakarta. Sample was determined using quota sampling which total sample was 78 partisipants (every trimester consist of 26 pregnant mothers) and not have significant health problem related to their pregnancy (e.g. high risk pregnancy condition, vaginal bleeding, etc.). Data was collected using Indonesian version of Pregnancy Sexuality and Respon Inventory (PSRI) questionnaire which reliable to used (Cronbach’s alpha: 0.714). Data were analyzed by paired t test. Significant change of sexual activity among trimesters was analyzed using post hoc.</p><p><strong>Results:</strong> There was significant changes in biological aspect of mothers’ sexual activity before and during pregnancy, especially second (<em>p</em> 0.002) and third trimester (<em>p</em> 0.000) and the changes led to the decline. There was significant decline in emotional aspect of sexual activities of mothers in all trimesters of pregnancy (<em>p</em><0.05). Meanwhile in physical aspect of sexual activities, there was significant decline in second (<em>p</em> 0.000) and third trimester (<em>p</em> 0.000). Respondents got information on sexual activities during pregnancy from numerous sources, but the most common was from health care provider (35.9%).</p><strong>Conclusion:</strong> Providing the right informatian and consultation related this topic will help mother to understand their physiological change related to sexual activity and help mother and spouse to choose the right decision in doing sexual activity during pregnancy.
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Bąk, Justyna, Weronika Sofińska-Chmiel, Maria Gajewska, Paulina Malinowska et Dorota Kołodyńska. « Determination of the Ni(II) Ions Sorption Mechanism on Dowex PSR2 and Dowex PSR3 Ion Exchangers Based on Spectroscopic Studies ». Materials 16, no 2 (9 janvier 2023) : 644. http://dx.doi.org/10.3390/ma16020644.
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This paper estimates the suitability of the strongly basic anion exchangers, Dowex PSR2 and Dowex PSR3, as sorbents of nickel ions in aqueous solutions. These actions are aimed at searching for new solutions due to the growing discharge of nickel into wastewaters, primarily due to its addition to steel. The nickel sorption experiments were conducted under static conditions and resulted in the optimization of pH, phase contact time, initial solution concentration, and temperature. The next step was to calculate the kinetic, isothermal, and thermodynamic parameters. Moreover, the ion exchangers were characterized by means of Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and CHN elemental analysis. It was found that the sorption process was most effective at pH 6 after 240 min and at the temperature of 293 K. The values of the thermodynamic parameters revealed that the adsorption was exothermic and spontaneous. The physicochemical analyses combined with the experimental research enabled determination of the sorption mechanism of Ni(II) ions.
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Jowkar, Zahra, Zahra Fattah, Zahra Khorshidi Asl et Seyed Ahmadreza Hamidi. « Stress, Sleep Quality, and Academic Performance among Dental Students in Shiraz, Iran ». International Journal of Dentistry 2022 (29 mai 2022) : 1–7. http://dx.doi.org/10.1155/2022/3781324.
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Background. Quality of sleep and stress level can affect the health, capacity of learning, and academic performance of the students. This study aimed to investigate the association between stress and sleep quality with academic performance among undergraduate clinical dental students in Shiraz, Iran. Methods. This cross-sectional study was conducted during the second semester of the academic year 2020–2021 among clinical dental students at Shiraz Dental School, Iran. A total of 138 students completed Pittsburgh Sleep Quality Index (PSQI) and dental environment stress (DES) questionnaire. The grade point averages (GPAs) of the previous terms of the participants were also collected. Data analysis was performed using Kolmogorov–Smirnov test, the one-way ANOVA, post hoc Duncan’s test, nonparametric Kruskal–Wallis H test, Wilcoxon–Mann–Whitney test, and the chi-squared test. The p values of less than 0.05 were considered statistically significant. Results. Clinical dental students participated in this study experienced moderate levels of stress and poor sleep quality. Mean total DES and PSGI scores did not differ by sex, year of study, marital status, and place of residence ( p values >0.05). Most of the students (52.9%) had moderate GPAs. A significant relationship was observed between sex and GPA as well as between place of residence and GPA ( p values <0.05). No significant differences were found between DES total score or PSQI score and GPA categories ( p values >0.05). A significant direct relationship between DES total score and PSQI score was observed ( p < 0.05 ). Conclusion. Dental undergraduates in Shiraz, Iran, experienced moderate levels of stress and poor sleep quality. The results showed no significant difference between sleep quality or DES and academic achievement. However, a significant direct correlation was observed between sleep quality and dental environment stress.
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Moser, Christopher C., Christopher C. Page et P. Leslie Dutton. « Tunneling in PSII ». Photochemical & ; Photobiological Sciences 4, no 12 (2005) : 933. http://dx.doi.org/10.1039/b507352a.
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