Sorghum cobalt analysis on not determined wave length with atomic absorption spectrophotometer on background correction mode

This study was to know the better wave length on measuring cobalt content in forage sorghum hybrid (Sorghum bicolor) with an atomic absorption spectrophotometer. The analysis was on background correction mode with three wave lengths; 240.8, 240.7 (determined wave length or recommended wave length) and 240.6 nm, respectively. The larger absorbance value on the 240.7 nm, apparently, it might be considered as a good wave length but the smaller background value was a more important factor for the analysis as was shown on 240.6 nm. Correlation coefficients between the values on 240.7 nm: 240.6 nm and between them (240.8 nm: 240.6 nm) were higher and this common 240.6 nm was considered the better wave length.Key words: Atomic absorption spectrophotometer; background correction mode, cobalt analysis, forage sorghum, not determined wave lengths

Iron content in forage sorghum (Sorghum bicolor (L.) Moench) measured on different slit widths with atomic absorption spectrometry

Our objective was to know the right slit width for iron (Fe) concentration of forage sorghum, sorghum hybrid (Sorghum bicolor (L.) Moench), and also to discern which water treatment sludge (WTS) were good for ruminant's health with the feeding sorghum on the present study. The present experiment was carried out on a randomized block design with four treatments; Control, alum sludge compost, alum sludge + NPK (nitrogen, phosphorus, potassium fertilizers), alum sludge compost + NPK (nitrogen, phosphorus, potassium fertilizers). Sorghum hybrid was harvested, and iron content of it was analyzed with an atomic absorption spectrophotometer on background correction (BGC) mode. In order to analyze the iron (Fe) content of the sorghum with the spectrophotometer, three different slit widths conditions were used; 0.15, 0.20 and 0.25 nm. Absorbance and background values were obtained during the Fe analyses with the apparatus. When the background value is small, it is preferred for some trace metals’ analyses. Both (AM/BS) ratio (mean of the absorbance values<AM> to the standard deviation of back ground values<BS>) and (AS<standard deviation of the absorbance values>/BS) ratio, were larger on 0.25 nm slit than those on 0.15 and 0.20 nm slit, and, from our experiment, the condition seemed better on the 0.25 nm slit for the iron analysis with the spectrophotometer. Therefore, the sorghum hybrid grown on (Alum+NPK) and on (Compost only) might be dangerous for ruminants because of their higher values than 200 mg Fe/kg DM (dry matter).Key words: Absorbance, alum sludge, atomic absorption spectrophotometer, background, forage sorghum hybrid, iron, slit

Imaging of Repaired Rotator Cuff

info:eu-repo/semantics/publishedVersio

Development and Validation of 3-Year Atrial Fibrillation Prediction Models Using Electronic Health Record With or Without Standardized Electrocardiogram Diagnosis and a Performance Comparison Among Models.

Background Improved prediction of atrial fibrillation (AF) may allow for earlier interventions for stroke prevention, as well as mortality and morbidity from other AF-related complications. We developed a clinically feasible and accurate AF prediction model using electronic health records and computerized ECG interpretation. Methods and Results A total of 671 318 patients were screened from 3 tertiary hospitals. After careful exclusion of cases with missing values and a prior AF diagnosis, AF prediction models were developed from the derivation cohort of 25 584 patients without AF at baseline. In the internal/external validation cohort of 117 523 patients, the model using 6 clinical features and 5 ECG diagnoses showed the highest performance for 3-year new-onset AF prediction (C-statistic, 0.796 [95% CI, 0.785-0.806]). A more simplified model using age, sex, and 5 ECG diagnoses (atrioventricular block, fusion beats, marked sinus arrhythmia, supraventricular premature complex, and wide QRS complex) had comparable predictive power (C-statistic, 0.777 [95% CI, 0.766-0.788]). The simplified model showed a similar or better predictive performance than the previous models. In the subgroup analysis, the models performed relatively better in patients without risk factors. Specifically, the predictive power was lower in patients with heart failure or decreased renal function. Conclusions Although the 3-year AF prediction model using both clinical and ECG variables showed the highest performance, the simplified model using age, sex, and 5 ECG diagnoses also had a comparable prediction power with broad applicability for incident AF

Crowdsourcing geospatial data for Earth and human observations: a review

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and rigorously examines specific platforms and paradigms pertinent to data collection. Furthermore, it addresses salient challenges, encompassing data quality, inherent biases, and ethical dimensions. We contend that this thorough analysis will serve as an invaluable scholarly resource, encapsulating the current state-of-the-art in crowdsourced geospatial data, and offering strategic directions for future interdisciplinary research and applications across various sectors

Signaling Role of Fructose Mediated by FINS1/FBP in Arabidopsis thaliana

Sugars are evolutionarily conserved signaling molecules that regulate the growth and development of both unicellular and multicellular organisms. As sugar-producing photosynthetic organisms, plants utilize glucose as one of their major signaling molecules. However, the details of other sugar signaling molecules and their regulatory factors have remained elusive, due to the complexity of the metabolite and hormone interactions that control physiological and developmental programs in plants. We combined information from a gain-of-function cell-based screen and a loss-of-function reverse-genetic analysis to demonstrate that fructose acts as a signaling molecule in Arabidopsis thaliana. Fructose signaling induced seedling developmental arrest and interacted with plant stress hormone signaling in a manner similar to that of glucose. For fructose signaling responses, the plant glucose sensor HEXOKINASE1 (HXK1) was dispensable, while FRUCTOSE INSENSITIVE1 (FINS1), a putative FRUCTOSE-1,6-BISPHOSPHATASE, played a crucial role. Interestingly, FINS1 function in fructose signaling appeared to be independent of its catalytic activity in sugar metabolism. Genetic analysis further indicated that FINS1–dependent fructose signaling may act downstream of the abscisic acid pathway, in spite of the fact that HXK1–dependent glucose signaling works upstream of hormone synthesis. Our findings revealed that multiple layers of controls by fructose, glucose, and abscisic acid finely tune the plant autotrophic transition and modulate early seedling establishment after seed germination

Molecular markers for tolerance of European ash (Fraxinus excelsior) to dieback disease identified using Associative Transcriptomics

Tree disease epidemics are a global problem, impacting food security, biodiversity and national economies. The potential for conservation and breeding in trees is hampered by complex genomes and long lifecycles, with most species lacking genomic resources. The European Ash tree Fraxinus excelsior is being devastated by the fungal pathogen Hymenoscyphus fraxineus, which causes ash dieback disease. Taking this system as an example and utilizing Associative Transcriptomics for the first time in a plant pathology study, we discovered gene sequence and gene expression variants across a genetic diversity panel scored for disease symptoms and identified markers strongly associated with canopy damage in infected trees. Using these markers we predicted phenotypes in a test panel of unrelated trees, successfully identifying individuals with a low level of susceptibility to the disease. Co-expression analysis suggested that pre-priming of defence responses may underlie reduced susceptibility to ash dieback

Solvothermal Synthesis and Characterization of Chalcopyrite CuInSe2 Nanoparticles

The ternary I-III-VI2 semiconductor of CuInSe2 nanoparticles with controllable size was synthesized via a simple solvothermal method by the reaction of elemental selenium powder and CuCl as well as InCl3 directly in the presence of anhydrous ethylenediamine as solvent. X-ray diffraction patterns and scanning electron microscopy characterization confirmed that CuInSe2 nanoparticles with high purity were obtained at different temperatures by varying solvothermal time, and the optimal temperature for preparing CuInSe2 nanoparticles was found to be between 180 and 220 °C. Indium selenide was detected as the intermediate state at the initial stage during the formation of pure ternary compound, and the formation of copper-related binary phase was completely deterred in that the more stable complex [Cu(C2H8N2)2]+ was produced by the strong N-chelation of ethylenediamine with Cu+. These CuInSe2 nanoparticles possess a band gap of 1.05 eV calculated from UV–vis spectrum, and maybe can be applicable to the solar cell devices