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Can be delayed treatment together with acetaminophen safe and effective to avoid surgical ligation amid incredibly preterm neonates using chronic evident ductus arteriosus?
The identification of plant disease is an imperative part of crop monitoring systems. Computer vision and deep learning (DL) techniques have been proven to be state-of-the-art to address various agricultural problems. This research performed the complex tasks of localization and classification of the disease in plant leaves. In this regard, three DL meta-architectures including the Single Shot MultiBox Detector (SSD), Faster Region-based Convolutional Neural Network (RCNN), and Region-based Fully Convolutional Networks (RFCN) were applied by using the TensorFlow object detection framework. All the DL models were trained/tested on a controlled environment dataset to recognize the disease in plant species. Moreover, an improvement in the mean average precision of the best-obtained deep learning architecture was attempted through different state-of-the-art deep learning optimizers. The SSD model trained with an Adam optimizer exhibited the highest mean average precision (mAP) of 73.07%. The successful identification of 26 different types of defected and 12 types of healthy leaves in a single framework proved the novelty of the work. In the future, the proposed detection methodology can also be adopted for other agricultural applications. Moreover, the generated weights can be reused for future real-time detection of plant disease in a controlled/uncontrolled environment.The film formation step of latexes constitutes one of the challenges of these environmentally friendly waterborne polymers, as the high glass transition (TG) polymers needed to produce hard films to be used as coatings will not produce coherent films at low temperature. This issue has been dealt by the use of temporary plasticizers added with the objective to reduce the TG of the polymers during film formation, while being released to the atmosphere afterwards. The main problem of these temporary plasticizers is their volatile organic nature, which is not recommended for the environment. Therefore, different strategies have been proposed to overcome their massive use. One of them is the use of hydroplasticization, as water, abundant in latexes, can effectively act as plasticizer for certain types of polymers. In this work, the effect of three different grafted hydroplasticizers has been checked in a (meth)acrylate copolymer, concluding that itaconic acid showed the best performance as seen by its low minimum film-formation temperature, just slightly modified water resistance and better mechanical properties of the films containing itaconic acid. Furthermore, film formation monitoring has been carried out by Differential Scanning Calorimety (DSC), showing that itaconic acid is able to retain more strongly the water molecules during the water losing process, improving its hydroplasticization capacity.Temperature response of double network (DN) hydrogels composed of thermoresponsive poly(N,N'-diethylacrylamide) (PDEAAm) and hydrophilic polyacrylamide (PAAm) or poly(N,N`-dimethylacrylamide) (PDMAAm) was studied by a combination of swelling measurements, differential scanning calorimetry (DSC) and 1H NMR and UV-Vis spectroscopies. Presence of the second hydrophilic network in DN hydrogels influenced their thermal sensitivity significantly. DN hydrogels show less intensive changes in deswelling, smaller enthalpy, and entropy changes connected with phase transition and broader temperature interval of the transition than the single network (SN) hydrogels. Above the transition, the DN hydrogels contain significantly more permanently bound water in comparison with SN hydrogels due to interaction of water with the hydrophilic component. Unlike swelling and DSC experiments, a rather abrupt transition was revealed from temperature-dependent NMR spectra. BMS935177 Release study showed that model methylene blue molecules are released from SN and DN hydrogels within different time scale. New thermodynamical model of deswelling behaviour based on the approach of the van't Hoff analysis was developed. The model allows to determine thermodynamic parameters connected with temperature-induced volume transition, such as the standard change of enthalpy and entropy and critical temperatures and characterize the structurally different states of water.The excited state Raman spectra of 4-dicyanomethylene-2-methyl-6-(p-dimethylaminostyryl)-4H-pyran (DCM) in the locally-excited (LE) and the intramolecular charge transfer (ICT) states have been separately measured by time-resolved stimulated Raman spectroscopy. In a polar dimethylsulfoxide solution, the ultrafast ICT of DCM with a time constant of 1.0 ps was observed in addition to the vibrational relaxation in the ICT state of 4-7 ps. On the other hand, the energy of the ICT state of DCM becomes higher than that of the LE state in a less polar chloroform solution, where the initially-photoexcited ICT state with the LE state shows the ultrafast internal conversion to the LE state with a time constant of 300 fs. The excited-state Raman spectra of the LE and ICT state of DCM showed several major vibrational modes of DCM in the LE and ICT conformer states coexisting in the excited state. Comparing to the time-dependent density functional theory simulations and the experimental results of similar push-pull type molecules, a twisted geometry of the dimethylamino group is suggested for the structure of DCM in the S1/ICT state.We thank Costa-Santos C [...].The Kelch-like ECH-associated protein 1 (KEAP1)-nuclear factor E2-related factor 2 (NRF2) module is a key component in the detoxification and antioxidant system in animals, which plays crucial roles in cell homeostasis and cytoprotection, and consequently in carcinogenesis and disease development. However, this system seems to have diverged throughout evolution across different organisms, and the question of whether a similar system exists in plants has thus far remained unresolved. In this study, a KEAP1 ortholog was identified in rice (Oryza sativa L., OsKEAP1) and its properties were characterized via in silico and laboratory studies. To reveal OsKEAP1's function, two knockdown mutants, oskeap1-1 and oskeap1-2, were generated by targeted mutagenesis in the 5' untranslated region (UTR) using the CRISPR-Cas9 system. In silico analysis showed that OsKEAP1 has a Kelch-repeat domain which is identical to those of animals and a plant-specific development and cell death (DCD) domain in place of the broad-complex, tramtrack, bric-a-brac (BTB) domain found in animals.
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