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Predicting the actual Formability associated with Cross Organic-Inorganic Perovskites with an Interpretable Machine Studying Technique.
As an essential nutrient required for plant growth and development, sulfur (S) deficiency in productive systems limits yield and quality. This special issue hosts a collection of original research articles, mainly based on contributions from the 11th International Plant Sulfur Workshop held on 16-20 September 2018 in Conegliano, Italy, focusing on the following topics (1) The germinative and post-germinative behaviour of Brassica napus seeds when severe S limitation is applied to the parent plants; (2) the independence of S deficiency from the mRNA degradation initiation enzyme PARN in Arabidopsis; (3) the glucosinolate distribution in the aerial parts of sel1-10, a disruption mutant of the sulfate transporter SULTR1;2, in mature Arabidopsis thaliana plants; (4) the accumulation of S-methylcysteine as its γ-glutamyl dipeptide in Phaseolus vulgaris; and (5) the role of ferric iron chelation-strategy components in the leaves and roots of maize, have provided new insights into the effect of S availability on plant functionality. Moreover, the role of S deficiency in root system functionality has been highlighted, focusing on (6) the contribution of root hair development to sulfate uptake in Arabidopsis, and (7) the modulation of lateral root development by the CLE-CLAVATA1 signaling pathway under S deficiency. The role of S in plants grown under drought conditions has been investigated in more detail focusing (8) on the relationship between S-induced stomata closure and the canonical ABA signal transduction machinery. Furthermore, (9) the assessment of S deficiency under field conditions by single measurements of sulfur, chloride, and phosphorus in mature leaves, (10) the effect of fertilizers enriched with elemental S on durum wheat yield, and (11,12) the impact of elemental S on the rhizospheric bacteria of durum wheat contributed to enhance the scientific knowledge on S nutrition under field conditions.The life cycles of retroviruses rely on the limited proteolysis catalyzed by the viral protease. Numerous eukaryotic organisms also express endogenously such proteases, which originate from retrotransposons or retroviruses, including DNA damage-inducible 1 and 2 (Ddi1 and Ddi2, respectively) proteins. In this study, we performed a comparative analysis based on the structural data currently available in Protein Data Bank (PDB) and Structural summaries of PDB entries (PDBsum) databases, with a special emphasis on the regions involved in dimerization of retroviral and retroviral-like Ddi proteases. In addition to Ddi1 and Ddi2, at least one member of all seven genera of the Retroviridae family was included in this comparison. We found that the studied retroviral and non-viral proteases show differences in the mode of dimerization and density of intermonomeric contacts, and distribution of the structural characteristics is in agreement with their evolutionary relationships. Multiple sequence and structure alignments revealed that the interactions between the subunits depend mainly on the overall organization of the dimer interface. We think that better understanding of the general and specific features of proteases may support the characterization of retroviral-like proteases.Wireless Body Area Network (WBAN) is a highly promising technology enabling health providers to remotely monitor vital parameters of patients via tiny wearable and implantable sensors. In a WBAN, medical data is collected by several tiny sensors and usually transmitted to a server-side (e.g., a cloud service provider) for long-term storage and online/offline processing. However, as the health data includes several sensitive information, providing confidentiality and fine-grained access control is necessary to preserve the privacy of patients. In this paper, we design an attribute-based encryption (ABE) scheme with lightweight encryption and decryption mechanisms. Our scheme enables tiny sensors to encrypt the collected data under an access control policy by performing very few computational operations. Also, the computational overhead on the users in the decryption phase is lightweight, and most of the operations are performed by the cloud server. In comparison with some excellent ABE schemes, our encryption mechanism is more than 100 times faster, and the communication overhead in our scheme decreases significantly. We provide the security definition for the new primitive and prove its security in the standard model and under the hardness assumption of the decisional bilinear Diffie-Hellman (DBDH) problem.Protein arginine deimination leading to the non-coded amino acid citrulline remains a key question in the field of post-translational modifications ever since its discovery by Rogers and Simmonds in 1958. Citrullination is catalyzed by a family of enzymes called peptidyl arginine deiminases (PADIs). Initially, increased citrullination was associated with autoimmune diseases, including rheumatoid arthritis and multiple sclerosis, as well as other neurological disorders and multiple types of cancer. selleck screening library During the last decade, research efforts have focused on how citrullination contributes to disease pathogenesis by modulating epigenetic events, pluripotency, immunity and transcriptional regulation. However, our knowledge regarding the functional implications of citrullination remains quite limited, so we still do not completely understand its role in physiological and pathological conditions. Here, we review the recently discovered functions of PADI2-mediated citrullination of the C-terminal domain of RNA polymerase II in transcriptional regulation in breast cancer cells and the proposed mechanisms to reshape the transcription regulatory network that promotes cancer progression.The detection of pig behavior helps detect abnormal conditions such as diseases and dangerous movements in a timely and effective manner, which plays an important role in ensuring the health and well-being of pigs. Monitoring pig behavior by staff is time consuming, subjective, and impractical. Therefore, there is an urgent need to implement methods for identifying pig behavior automatically. In recent years, deep learning has been gradually applied to the study of pig behavior recognition. Existing studies judge the behavior of the pig only based on the posture of the pig in a still image frame, without considering the motion information of the behavior. However, optical flow can well reflect the motion information. Thus, this study took image frames and optical flow from videos as two-stream input objects to fully extract the temporal and spatial behavioral characteristics. Two-stream convolutional network models based on deep learning were proposed, including inflated 3D convnet (I3D) and temporal segment networks (TSN) whose feature extraction network is Residual Network (ResNet) or the Inception architecture (e.
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