Search

A field experiment was carried out during the spring and fall seasons of 2021 at Al-Hamidiya Research Station of the College of Agriculture, With the aim of studying the effect of soaking seeds with Atonik growth regulator and seeding dates on growth characteristics and plant nutrients content for three varieties of sorghum. A randomized complete block design with split-split plot arrangement was used with three replications. The main plot included seeding dates for both spring and fall seasons, while the sub-plot included the concentrations of the growth regulator (Atonk) which are 0-, 2.5- and 5-ml L-1, while the three varieties (Inqath, Lelu and Giza 113) were allocated to the sub-sub plots. The results showed the superiority of the cultivar Inqath in most of the studied traits such as leaf area, plant content of chlorophyll and plant content of potassium, phosphorous and nitrogen (4406, 3888 cm2 and 58.36 59.17 spad) for both seasons, respectively. Whereas, Giza 113 cultivar outperformed in terms of plant height for both seasons. The plants which seeds soaked at a concentration of 5 ml L-1 also outperformed in all studied traits seeding date had a significant effects for both seasons. The interaction between the studied factors had a significant effect for most of the traits.

A field experiment was carried out during the spring and fall seasons of 2021 at Al-Hamidiya Research Station of the College of Agriculture, With the aim of studying the effect of soaking seeds with Atonik growth regulator and seeding dates on growth characteristics and plant nutrients content for three varieties of sorghum. A randomized complete block design with split-split plot arrangement was used with three replications. The main plot included seeding dates for both spring and fall seasons, while the sub-plot included the concentrations of the growth regulator (Atonk) which are 0-, 2.5- and 5-ml L -1, while the three varieties (Inqath, Lelu and Giza 113) were allocated to the sub-sub plots. The results showed the superiority of the cultivar Inqath in most of the studied traits such as leaf area, plant content of chlorophyll and plant content of potassium, phosphorous and nitrogen (4406, 3888 cm2 and 58.36 59.17 spad) for both seasons, respectively. Whereas, Giza 113 cultivar outperformed in terms of plant height for both seasons. The plants which seeds soaked at a concentration of 5 ml L-1 also outperformed in all studied traits seeding date had a significant effects for both seasons. The interaction between the studied factors had a significant effect for most of the traits. [ABSTRACT FROM AUTHOR]

Copyright of Revista Latinoamericana de Hipertension is the property of Revista Latinoamericana de Hipertension and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract One of the significant challenges of the Radio over fibre (RoF) Medium Access Control (MAC) protocol is the propagation delay. This delay can lead to serious issues, such as higher propagation delay resulting in collisions and unnecessary retransmissions. Quantum entanglement is an excellent candidate to overcome the propagation delay of the RoF MAC protocol. A new quantum MAC protocol is proposed, named the Quantum Entanglement‐based MAC protocol (QE‐MAC), in which Quantum Teleportation is utilised to address the propagation delay. Four entanglement states are employed to represent the control packets of the classical MAC protocol, and data is transmitted over the classical channel. Instead of using control packets such as acknowledgement, request to send, and Clear to send, state transitions are employed. This approach avoids the delay and collision issues associated with control packets, resulting in a significant improvement in network performance. The delay, duty cycle (DC), and power consumption of the proposed QE‐MAC protocol are formulated and derived. The protocol is evaluated in terms of delay, DC, and power consumption, demonstrating superior performance compared to the classical RoF MAC protocol. In comparison to published works, our proposed approach has successfully reduced both delay and power consumption by 35%.

In this paper, we study the modern mathematical theory of the optimal control problem associated with the fractional Roesser model and described by Caputo partial derivatives, where the functional is given by the Riemann-Liouville fractional integral. In the formulated problem, a new version of the increment method is applied, which uses the concept of an adjoint integral equation. Using the Banach fixed point principle, we prove the existence and uniqueness of a solution to the adjoint problem. Then the necessary and sufficient optimality condition is derived in the form of the Pontryagin’s maximum principle. Finally, the result obtained is illustrated by a concrete example.

Lagrangian modelling can be used to derive mathematical models for complex power electronic converters. This approach uses scalar quantities (kinetic and potential energy) to derive models, which is simpler than using (vector-based) force balance equations. It employs generalized coordinates, making it easier to deal with complex systems with constraints. This systematic approach results in equations that can be expressed in state-space form, which allows for the simplification of the simulation and design process and the use of many standard software packages for system analysis and simulation. In this work, contributions are made regarding the procedure to be followed for the Lagrangian modelling of power converters and the incorporation of constraints within the Lagrangian framework. Furthermore, for the first time, Lagrangian modelling is extended to non-ideal, high-fidelity descriptions of standard power electronic circuits.

Rhododendron arboreum: Sm., also known as Burans is traditionally used as an anti-inflammatory, anti-diabetic, hepatoprotective, adaptogenic, and anti-oxidative agent. It has been used since ancient times in Indian traditional medicine for various liver disorders. However, the exact mechanism behind its activity against NAFLD is not known. The aim of the present study is to investigate the molecular mechanism of Rhododendron arboreum flower (RAF) in the treatment of NAFLD using network pharmacology and molecular docking methods. Bioactives were also predicted for their drug-likeness score, probable side effects and ADMET profile. Protein-protein interaction (PPI) data was obtained using the STRING platform. For the visualisation of GO analysis, a bioinformatics server was employed. Through molecular docking, the binding affinity between potential targets and active compounds were assessed. A total of five active compounds of RAF and 30 target proteins were selected. The targets with higher degrees were identified through the PPI network. GO analysis indicated that the NAFLD treatment with RAF primarily entails a response to the fatty acid biosynthetic process, lipid metabolic process, regulation of cell death, regulation of stress response, and cellular response to a chemical stimulus. Molecular docking and molecular dynamic simulation exhibited that rutin has best binding affinity among active compounds and selected targets as indicated by the binding energy, RMSD, and RMSF data. The findings comprehensively elucidated toxicity data, potential targets of bioactives and molecular mechanisms of RAF against NAFLD, providing a promising novel strategy for future research on NAFLD treatment.

Rotational shafts are pivotal components in industrial settings and are responsible for transmitting torque and rotational motion. Despite their significance, these shafts are susceptible to faults, particularly cracks, which can adversely affect the system's performance and safety. Hence, efficient crack detection and diagnosis ensure safety, reliability, and costeffectiveness. This research aims to develop an Artificial Neural Network (ANN) model that can effectively identify cracks occurring at different depths and locations in rotating shafts, which operate at varying rotational speeds. Vibration signals were obtained and subjected to preprocessing using a bandpass filter to isolate the shaft signals from other components. Subsequently, time-domain statistical features were extracted from the filtered signals. An optimal feature selection methodology was employed to rank the extracted features, and the highest-ranking features were chosen for training the ANN model. The findings of this research indicate that the developed model achieved a classification accuracy of 94.4%.