Simmondsin as natural alternative fungicide in squash root rot disease

Jojoba (Simmondsia chinensis) meal was extracted with acetone, isopropanol, boiling distilled water and methanol to obtain simmondsin. Simmondsin was tested against Squash root rot disease at four concentrations (10, 20, 30 and 40 mg/ml) using the radial mycelia growth under greenhouse and field conditions. Rhizoctonia solani (Kuhn) and Fusarium solani (Mart.) were isolated from naturally infected squash roots collected from different localities in Qalubia Governorate. Evaluation simmondsin extracts revealed that acetone was the most effective as it prevented the myceial growth of F. solani and R. solani at 40 mg/ml, followed by isopropanol, boiling water and methanol in vitro. All extracts even at concentration 10 mg/ml had little effect and failed to produce a considerable reduction in growth of the tested fungi. Squash Eskandrany seeds were treated with simmondsin extracts before sowing in artificially infested soil with F. solani and R. solani (pot experiments) or soil naturally infected (epidemic soil) by the tested pathogenic fungi (field experiments) resulted in significant reduction in both damping- off and dead plant (resulted from infection by root-rot disease) compared with untreated seeds. Also, both acetone and isopropanol extract were more efficient in reducing infection by damping-off and root-rot than boiling distilled water and methanol. While, squash seeds treated with tested simmondsin extract significantly increased fruit yield/plot compared with untreated seeds. Also, all tested simmondsin extracts significant increased plant survival.Squash eskandrany seeds were treated with simmondsin extracts before sowing in artificially infested soil with F. solani and R. solani (pot experiments) or soil naturally infected (epidemic soil) by tested pathogenic fungi (field experience) resulted insignificant reduction in both damping- off and dead plant (resulted from infection by root-rot disease) compared with untreated seeds. Also, both Acetone and Isopropanol were more efficient reducing infection by damping-off and root-rot the high concentration 40 mg/ml than Boiling water and Methanol. On the other hand, squash seeds treated with tested simmondsin extract significantly increased fruit yield/plot compared with untreated seeds. Also, all tested simmondsin extracts significant increased plant survival

Curriculum innovations through advancement of MEMS/NEMS and wearable devices technologies

State of the art technologies using both micro- and nano-electromechanical systems (MEMS and NEMS) and wearable and Internet of Things (IoT) devices have impacted our daily lives in applications including wearable devices and sensor technology as applied to renewable energies and health sciences, among others. Several examples are device implants, optical devices, micro and nanomachining, embedded systems and integrated nano sensor systems. The recent Electrical and Computer Engineering (ECE) and Mechanical Engineering (ME) curricula lacked inclusion of these elements within their programs. Close scrutiny to the need of local industry from engineering graduates has emphasized the motivation to develop these materials into the engineering curricula. Within the ECE curriculum, a new senior course was developed to cover MEMS/NEMS devices as well as wearable and IoT devices with Bluetooth and wireless features. The MEMS/NEMS module of the new course integrates software CAD tools and hardware implementations. It is a project-based course where students learn software for the device process, then fabricate the device in the school laboratories. The wearable and IoT devices module introduces the students to Wearable and Internet of Things systems. It covers sensors and sensor fusion, embedded processors, tools for wearable and IoT applications, and design using Bluetooth and wireless IoT systems. The new course development objectives are hands-on practice, and preparation of senior students for industrial and research careers. In addition, an introductory MEMS topic section is added in the sophomore level electrical engineering course offered to mechanical engineering students. It introduces MEMS devices employed as energy conversion devices. Based on our recent feedback, the students have favorably accepted this MEMS addition to the course. This paper details the software and hardware development elements of the new course. It also presents the assessment data for students' satisfaction for both the electrical and computer engineering (ECE), and mechanical engineering (ME) students. © American Society for Engineering Education, 2017

Influence of a Hybrid MPPT Technique, SA-P&O, on PV System Performance under Partial Shading Conditions

The electricity sector has been undergoing profound transformations. In particular, the Portuguese self-consumer regime has allowed customers of the medium and low voltage electricity grid to be producers/consumers of electricity, actively contributing to greater energy efficiency. In this context, the energy that comes from the sun is not used to its maximum. In addition, photovoltaic cells have a characteristic operating curve (voltage vs. current), in which any operating point is reflected. Within this curve, there is a particular point known as the maximum power point (MPP) at which the cell supplies the maximum power output to a load. If the cell does not operate at this point, it has lower efficiency values. To harness maximum power under standard and dynamic shading conditions, there are various techniques of low complexity for capturing maximum power. We present a maximum power point tracking (MPPT) algorithm capable of dealing with the problem of partial shading. This algorithm involves modifying one of the most used algorithms within photovoltaic systems, known as P&O, using a simulated annealing (SA) algorithm. P&O is often used due to its straightforward implementation, but it is susceptible to partial shade conditions. Sampling was added to this algorithm to a better approach to the point of maximum power using the SA, and then to attain a more precise convergence with P&O. Implementing a maximum power point tracking method under partial shading was the major goal of this study

A reproducible protocol for regeneration and transformation in canola (Brassica napus L.)

The objective of the present study is to develop an efficient protocol for shoot and plant regeneration using five commercial canola cultivars grown under the Egyptian agricultural conditions. The regeneration efficiency from hypocotyl explants was examined. The data indicated that embryonic calli were formed within two weeks in the presence of 1 mgl-1 2,4-D. Adventitious shoots emerged from the embryonic callus in the presence of 4.5 mgl-1 BA. The cultivars showed a varied response to shoot regeneration. Regeneration frequency was high in the cultivar Sarow-4 (68%) followed by Masrri L-16 (64%) compared with the other cultivars tested. Hypocotyl explants from the cultivars Sarow-4 and Semu-249 were inoculated and co-cultivated with Agrobacterium tumefaciens strain LBA4404 harboring a binary vector pBI-121 containing the neomycin phosphotransferase-II gene (NPT-II). The resulted putative transgenic plantlets were able to grow under knanamycin containing medium. The stable integration of the NPT-II gene into the plant genomes was tested by PCR using NPT-II -specific primers. The GUS gene expression can be detected only in the transgenic plants. The reported protocol in the present study is repeatable and can be used to regenerate transgenic canola plants expressing the genes present in A. tumifaciens binary vectors.Keywords: Agrobacterium, canola, GUS assay, regeneration, fransformation, NPT II gen

Deployment of Compressed MobileNet V3 on iMX RT 1060

Deep Neural Networks (DNN) are prominent in most applications today. From self-driving cars, sentiment analysis, surveillance systems, and robotics, they have been used extensively. Among DNNs, Convolutional Neural Networks (CNN) have achieved massive success in computer vision applications as the human visual system inspires their architecture. However, striving to achieve higher accuracies, CNN complexity, parameters, and layers were increased, which led to a drastic surge in their size, making their deployment challenging. Over the years, many researchers have proposed various techniques to alleviate this issue-one of them being Design Space Exploration (DSE) to minimize size and computation with little compromise to accuracy. MobileNet V3 is one such architecture designed to achieve good accuracy while being mindful of resources. It produces an accuracy of 88.93% on CIFAR-10 with a size of 15.3MB. This paper further reduces its size to 2.3MB while boosting its accuracy to 89.13% using DSE techniques. It is then deployed into NXP's i.MX RT1060 Advanced Driver Assistance System (ADAS) platform

Synthesis and antitumor activity of some novel thiophene, pyrimidine, coumarin, pyrazole and pyridine derivatives

2-Cyano-N-(thiazol-2-yl) acetamide (2a) and 2-cyano-N-(oxazol-2-yl) acetamide (2b) were obtained via the reaction of ethylcyanoacetate with either 2-aminothiazole (1a) or 2-aminooxazole (1b). The the formed products were directed toward the reaction with cyclopentanone and elemental sulphur in the presence of triethylamine to give cyclopenta[b]thiophene derivatives (3a,b). The latter products when reacted with either ethylcyanoacetate or malononitrile to form compounds 4a,b and 5a,b, respectively. Compounds 4a,b were aimed to synthesize some heterocyclic compounds; thus internal cyclization reactions were introduced to form compounds 6a,b. Also, compounds 4a,b reacted with salicylaldehyde, hydrazine derivatives and either urea or thiourea to produce coumarin derivatives (7a,b), pyrazole derivatives (8a-d) and pyrimidine derivatives (9a-d), respectively. Reaction of either benzaldehyde or benzene diazonium chloride (11) with compounds 4a,b afforded compounds 10a,b and 12a,b, respectively. On the other hand, compounds 5a,b underwent internal cyclization to form pyrimidine derivatives 13a,b. Also when compounds 5a,b reacted with either ethylcyanoacetate or malononitrile they gave pyridine derivatives (15a-d) through the formation of intermediates (14a-d). Finally, formation of fused pyrimidine derivatives (17a,b) was afforded through the reaction of compounds 5a,b and salicylaldehyde, applying two different pathways. First pathway used catalytic amount of piperidine to form compounds 16a,b; the latter products underwent cyclization to give compounds 17a,b. The second pathway using catalytic amount of sodium ethoxide solution directly in one step afforded compounds 17a,b. The structures of the newly synthesized compounds were established using IR, 1H NMR, 13C NMR and mass spectrometry and their antitumor activity was investigated. Some of these compounds showed promising inhibitory effects on the three different cell lines. However, fused pyrimidine acetonitrile derivatives 6a and 6b exerted the highest inhibitory effect comparable to that of doxorubicin

A pilot study in humans of microneedle sensor arrays for continuous glucose monitoring

Although subcutaneously implanted continuous glucose monitoring (CGM) devices have been shown to support diabetes self-management, their uptake remains low due to a combination of high manufacturing cost and limited accuracy and precision arising from their invasiveness. To address these points, minimally invasive, a solid microneedle array-based sensor for continuous glucose monitoring is reported here. These intradermal solid microneedle CGM sensors are designed for low cost manufacturing. The tolerability and performance of these devices is demonstrated through clinical studies, both in healthy volunteers and participants with type 1 diabetes (T1D). The geometry of these solid microneedles allows them to penetrate dermal tissue without the need for an applicator. The outer surface of these solid microneedles are modified as glucose biosensors. The microneedles sit in the interstitial fluid of the skin compartment and monitor real-time changes in glucose concentration. Optical coherence tomography measurements revealed no major axial movement of the microneedles in the tissue. No significant adverse events were observed and low pain scores were reported when compared to catheter insertion, deeming it safe for clinical studies in T1D. These amperometric sensors also yielded currents that tracked venous blood glucose concentrations, showing a clinically acceptable correlation. Studies in people with T1D gave a mean absolute relative difference (MARD) of 9% (with respect to venous blood glucose) with over 94% of the data points in the A and B zones of the Clarke error grid. These findings provide baseline data for further device development and a larger clinical efficacy and acceptability study of this microneedle intradermal glucose sensor in T1D

Squeeze-and-Excitation SqueezeNext: An Efficient DNN for Hardware Deployment

Convolution neural network is being used in field of autonomous driving vehicles or driver assistance systems (ADAS), and has achieved great success. Before the convolution neural network, traditional machine learning algorithms helped the driver assistance systems. Currently, there is a great exploration being done in architectures like MobileNet, SqueezeNext & SqueezeNet. It improved the CNN architectures and made it more suitable to implement on real-time embedded systems. This paper proposes an efficient and a compact CNN to ameliorate the performance of existing CNN architectures. The intuition behind this proposed architecture is to supplant convolution layers with a more sophisticated block module and to develop a compact architecture with a competitive accuracy. Further, explores the bottleneck module and squeezenext basic block structure. The state-of-the-art squeezenext baseline architecture is used as a foundation to recreate and propose a high performance squeezenext architecture. The proposed architecture is further trained on the CIFAR-10 dataset from scratch. All the training and testing results are visualized with live loss and accuracy graphs. Focus of this paper is to make an adaptable and a flexible model for efficient CNN performance which can perform better with the minimum tradeoff between model accuracy, size, and speed. Having a model size of 0.595MB along with accuracy of 92.60% and with a satisfactory training and validating speed of 9 seconds, this model can be deployed on real-time autonomous system platform such as Bluebox 2.0 by NXP