Appraisal of Agriglass in Promoting Maize Production Under Abiotic Stress Conditions

An agriglass composition containing different oxides acts as a slow release for macro and micro nutrients and was chosen to improve maize yield under most important abiotic stresses which affecting agriculture development; salinity and drought. A field experiment was performed in salt affected soil (EC =?7.5 dSm^??1) by using different water deficit rates (I1 = 100, I2 = 85 and I3 = 70% of maize water requirements). Irrigation levels were located in main plots. Every main-plot divided into six sub-plots contained glassy fertilizer treatments [F1 = 55 kg fed^?1 with 1/2 mm diameter of agriglass (fed. =?4200 m²), F2 = 55 kg fed^?1 with 1 mm diameter, F3 = 80 kg fed^?1 with 1/2 mm diameter, F4 = 80 kg fed^?1 with 1 mm diameter, F5 = Recommendations of Ministry of Agriculture and F6 = control]. The experimental results demonstrated that, ears, straw, grains and biological yields increased with increasing both water and agriglass rates. Application of agriglass as a slow release fertilizer improved yield more than mineral fertilizer. Some growth parameters, water use efficiency (IWUE), macronutrients concentration and their relations were included. Other studies on residual effect of agriglass and the annual application rates to withstand salinity and drought stress by strategic crops are required.     

Radiolabeling,Preparation, and Bioevaluation of 99mTc-Azathioprine as a Potential Targeting Agent for Solid Tumor Imaging

Radiochemistry - Azathioprine, an antitumor agent, was labeled with 99mTc using stannous chloride dihydrate as a reducing agent. Factors such as the amounts of the reducing agent and substrate, pH,...     

Assessment of Dam Overtopping Reliability using SUFI Based Overtopping Threshold Curve

Estimation of earth-fill dam height and dimension of spillway are strongly depend on accurate evaluation of dam overtopping reliability. Ideally, whole random and effective variables on overtopping should be considered for dam overtopping reliability assessment. However, taking into account all affecting random variables as well as overtopping reliability assessment using algorithms such as Monte Carlo (MC) could be excessively time consuming and impossible in some cases. In this study, new approach has been introduced as conditional reliability method and it has been tried to reduce the simulations time significantly by using combination of rainfall threshold theory, SUFI (Sequential Uncertainty Fitting) and MC methods. According two defined indexes, the obtain results shown, the relative error of new approach in computation of Jamishan dam overtopping reliability is less than 0.23%. Also, time saving in new method against to regular MC method is more than 87%. So, the new introduced method has more efficiency with acceptable accuracy for assessment of dam overtopping reliability. In addition, among hydrological and hydraulic uncertainties, hydrological uncertainties have more effect on overtopping reliability.     

A smart process controller framework for Industry 4.0 settings

This paper presents a smart supervisory framework for a single process controller, designed for Industry 4.0 shop floors. This digitization of a full supervisory suite for a single process controller enables self-awareness, self-diagnosis, self-prognosis, and self-healing (by definition, these "self" elements are missing from other supervisory frameworks diagnosing numerous controllers in parallel). The proposed framework is aligned with the concept of a Cyber Physical System (CPS), since its implementation generates a rich cyber physical entity of the controlled process. This CPS entity can either be considered as the process digital twin, or can provide a solid basis for generating it. Finally, the framework includes the main characteristics of Industry 4.0, such as advanced use of Artificial Intelligence (AI) and big data analysis. The framework is based on four modules: (1) Control and Awareness module—performing both continuous process control and adjustments, as well as machine learning (ML) and statistical process control (SPC) for identifying abnormalities that require further diagnosis; (2) Process -diagnosis module—performing continual (recurrent) analysis of the process state and trends; (3) Prognosis and Healing module—performing prognosis and automated intervention via parameter changes, re-configurations, and automated maintenance; (4) External Interaction Platform—an interactive module for interfacing with experts, presenting them with the process analysis information and obtaining feedback from them as part of a learning process. Using an implementation showcase to illustrate the methodological framework’s applicability, we demonstrate its real-world potential. The proposed framework could serve as a guide for implementing smart process control and maintenance systems in Industry 4.0 shop floors. It could also provide a firm basis for comparison with future suggested frameworks. Future research directions could include pursuing improvements to the proposed process control framework and validating the framework by case studies of its implementation.

     

Proton-Detected Solid-State NMR of the Cell-Free Synthesized α-Helical Transmembrane Protein NS4B from Hepatitis C Virus

Proton-detected 100 kHz magic-angle-spinning (MAS) solid-state NMR is an emerging analysis method for proteins with only hundreds of microgram quantities, and thus allows structural investigation of eukaryotic membrane proteins. This is the case for the cell-free synthesized hepatitis C virus (HCV) nonstructural membrane protein 4B (NS4B). We demonstrate NS4B sample optimization using fast reconstitution schemes that enable lipid-environment screening directly by NMR. 2D spectra and relaxation properties guide the choice of the best sample preparation to record 2D ¹H-detected ¹H,¹⁵N and 3D ¹H,¹³C,¹⁵N correlation experiments with linewidths and sensitivity suitable to initiate sequential assignments. Amino-acid-selectively labeled NS4B can be readily obtained using cell-free synthesis, opening the door to combinatorial labeling approaches which should enable structural studies.     

A Constitutive Equation of Thermoelasticity for Solid Materials

A new constitutive equation of thermoelasticity for crystals is presented based on the interatomic potential and solid mechanics at finite temperature. Using the new constitutive equation, the calculations for crystal copper and graphene are carried out under different loading paths at different temperatures. The calculated results are in good agreement with those of the previous thermoelasticity constitutive equation based on quantum mechanics, which clearly indicates that our new constitutive equation of thermoelasticity is correct. A lot of comparisons also show that the present theory is more concise and efficient than the previous thermal stress theory in the practical application.