Integration of molecular biology tools for identifying promoters and genes abundantly expressed in flowers of Oncidium Gower Ramsey

<p>Abstract</p> <p>Background</p> <p>Orchids comprise one of the largest families of flowering plants and generate commercially important flowers. However, model plants, such as <it>Arabidopsis thaliana </it>do not contain all plant genes, and agronomic and horticulturally important genera and species must be individually studied.</p> <p>Results</p> <p>Several molecular biology tools were used to isolate flower-specific gene promoters from <it>Oncidium </it>'Gower Ramsey' (<it>Onc</it>. GR). A cDNA library of reproductive tissues was used to construct a microarray in order to compare gene expression in flowers and leaves. Five genes were highly expressed in flower tissues, and the subcellular locations of the corresponding proteins were identified using lip transient transformation with fluorescent protein-fusion constructs. BAC clones of the 5 genes, together with 7 previously published flower- and reproductive growth-specific genes in <it>Onc</it>. GR, were identified for cloning of their promoter regions. Interestingly, 3 of the 5 novel flower-abundant genes were putative trypsin inhibitor (<it>TI</it>) genes (<it>OnTI1</it>, <it>OnTI2 </it>and <it>OnTI3</it>), which were tandemly duplicated in the same BAC clone. Their promoters were identified using transient GUS reporter gene transformation and stable <it>A. thaliana </it>transformation analyses.</p> <p>Conclusions</p> <p>By combining cDNA microarray, BAC library, and bombardment assay techniques, we successfully identified flower-directed orchid genes and promoters.</p

Mg-modified Zn-Co-Fe-La nano ferrites: a study of structural, morphological, vibrational, electro-optical, dielectric and magnetic evolution

The series of Zn0.4Co0.6−xMgxFe1.9La0.1O4 (x = 0.0, 0.15, 0.30, 0.45, 0.6) nanoferrites prepared via co-precipitation technique. Scherrer and Williamson-Hall (W-H) methods were used to find the crystallite size (29.6–39.2 nm and 31.6–36.3 nm, respectively) and lattice constant was calculated (8.406–8.395 Å). Moreover, Fourier transform infrared (FTIR) spectroscopy revealed the existence of absorption bands along with functional groups. The vibrations of O2- ions at the tetrahedral and octahedral sites were shown by the Raman five active modes. DC resistivity reduced in the range of 5.2961 × 108 Ω cm to 9.6453 × 107 Ω cm for x = 0.0 to x = 0.6, respectively. The maximum DC resistivity and activation energy (0.1035 eV) were obtained at the parent sample (Zn0.4Co0.6Fe1.9La0.1O4). The optical bandgaps reduced from 2.61 to 1.47 eV, as the Mg2+ contents increased. With increasing frequency the dielectric loss and the dielectric constant decrease. The magnetic parameters such as saturation magnetization (Ms = 60.82–25.94 emu/g), remnant magnetization (Mr = 47.82–18.64 emu/g), and coercivity (Hc = 1334–511 Oe) demonstrated reducing trends with the increase of Mg2+ doping. The best magnetic behavior of the as-prepared samples suitable in microwave devices was observed for Zn0.4Co0.6Fe1.9La0.1O4 sample

Gas thermodynamic conditions of cold air entrainment by natural smoke exhaust system in case of compartment fire

Conditions of occurrence of abnormal operation of natural smoke exhaust system are analyzed when cold air is entrained into smoke exhaust windows preventing extraction of smoked heated gas layer beneath a ceiling (also known as plugholing). Analytical equation is derived for prediction of critical average volumetric temperature of gas layer beneath a ceiling when plugholing starts with consideration for the height of smoke exhaust window. This equation was compared with published experimental data and with numerical experiments using 3D field model of fire gas thermodynamics. It was found that the height of smoke exhaust window exerts significant influence on occurrence of plugholing and on maximum bulk flow rate of combustion products extracted from compartment via the window. © 2020, Institute of Advanced Scientific Research, Inc.. All rights reserved

Effect of large graphene particle size on structure, optical property and photocatalytic activity of graphene-titanate nanotube composites

Available online 19 October 2021In this work we investigate the crystal transformation and optical properties of hydrothermal titania nanotube (TNT) when combining with large size of exfoliated graphene achieved by electrochemical process (EC-Gr). The TNT monoclinic structure has been changed to TiO2 anatase phase when TNT was grown in the presence of graphene dispersion. The effect of graphene on the evolution of TNT crystal could be understood by the interaction of carbon elements in graphene and Ti4+ ions in the titania structure. Due to the carrier separation which reduced recombination rate of excited photoelectrons and holes revealed by photoluminescence characterizations, the visible light photocatalytic activity in degradation of methylene blue in solution of the composite was enhanced. The photocatalytic enhancement was discussed and clarified based on UV–vis diffuse absorption spectra and time-resolved photoluminescence investigation.Vo Cao Minh, Phan Tan Dat, Pham Thi Thuy, Nguyen Xuan Sang, Nguyen Tri Tuan, Tran Thanh Tung, Dusan Losi

Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network

Robotics is one of the most emerging technologies today, and are used in a variety of applications, ranging from complex rocket technology to monitoring of crops in agriculture. Robots can be exceptionally useful in a smart hospital environment provided that they are equipped with improved vision capabilities for detection and avoidance of obstacles present in their path, thus allowing robots to perform their tasks without any disturbance. In the particular case of Autonomous Nursing Robots, major essential issues are effective robot path planning for the delivery of medicines to patients, measuring the patient body parameters through sensors, interacting with and informing the patient, by means of voice-based modules, about the doctors visiting schedule, his/her body parameter details, etc. This paper presents an approach of a complete Autonomous Nursing Robot which supports all the aforementioned tasks. In this paper, we present a new Autonomous Nursing Robot system capable of operating in a smart hospital environment area. The objective of the system is to identify the patient room, perform robot path planning for the delivery of medicines to a patient, and measure the patient body parameters, through a wireless BLE (Bluetooth Low Energy) beacon receiver and the BLE beacon transmitter at the respective patient rooms. Assuming that a wireless beacon is kept at the patient room, the robot follows the beacon’s signal, identifies the respective room and delivers the needed medicine to the patient. A new fuzzy controller system which consists of three ultrasonic sensors and one camera is developed to detect the optimal robot path and to avoid the robot collision with stable and moving obstacles. The fuzzy controller effectively detects obstacles in the robot’s vicinity and makes proper decisions for avoiding them. The navigation of the robot is implemented on a BLE tag module by using the AOA (Angle of Arrival) method. The robot uses sensors to measure the patient body parameters and updates these data to the hospital patient database system in a private cloud mode. It also makes uses of a Google assistant to interact with the patients. The robotic system was implemented on the Raspberry Pi using Matlab 2018b. The system performance was evaluated on a PC with an Intel Core i5 processor, while the solar power was used to power the system. Several sensors, namely HC-SR04 ultrasonic sensor, Logitech HD 720p image sensor, a temperature sensor and a heart rate sensor are used together with a camera to generate datasets for testing the proposed system. In particular, the system was tested on operations taking place in the context of a private hospital in Tirunelveli, Tamilnadu, India. A detailed comparison is performed, through some performance metrics, such as Correlation, Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), against the related works of Deepu et al., Huh and Seo, Chinmayi et al., Alli et al., Xu, Ran et al., and Lee et al. The experimental system validation showed that the fuzzy controller achieves very high accuracy in obstacle detection and avoidance, with a very low computational time for taking directional decisions. Moreover, the experimental results demonstrated that the robotic system achieves superior accuracy in detecting/avoiding obstacles compared to other systems of similar purposes presented in the related works. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature