An Optimal Harvesting Strategy of a Three Species Syn-ecosystem with Commensalism and Stochasticity

In this paper we have studied the stability of three typical species syn-ecosystem. The system comprises of one commensal S1 and two hosts S2 and S3 . Both S2 and S2 benefit S1 without getting themselves affected either positively or adversely. Further S2 is a commensal of S3 and S3 is a host of both S1 and S2. Limited resources have been considered for all the three species in this case. The model equations of the system constitute a set of three first order non-linear ordinary differential equations. The possible equilibrium points of the model are identified. We have also studied the local and global stabilities. We have analyzed the bionomic equilibrium and optimal harvesting strategy using Pontryagin’s maximum principle. We have investigated the inhabitant intensities of the fluctuations (variances) around the positive equilibrium due to noise and have investigated the stability. We have also checked the MATLAB numerical simulations for stability of the system

Prodromal herpes zoster mimicking odontalgia – A diagnostic challenge

Herpes zoster (shingles) is caused by reactivation of the latent varicella zoster virus which is present due to an earlier varicella infection (chicken-pox). Herpes Zoster is a less common and endemic disease than varicella, although factors causing reactivation are still not well known, but it occurs in older and/or immunocompromised individuals. Involvement of C3, T5, L1, L2 and first division of trigeminal nerve are the most frequently encountered whereas the involvement of second and third division of trigeminal nerve is rarely seen. During the prodromal stage, the only presenting symptom may be odontalgia, which may prove to be a diagnostic challenge for the dentist, since many diseases can cause orofacial pain, and the diagnosis must be properly established before final treatment. Here we present a case of herpes zoster involving the second division of trigeminal nerve masquerading as odontalgia. The difficulties in diagnosis and management are discussed.KEYWORDS: herpes zoster, odontalgia, prodromal, trigeminal

On the interesting course of dichloroketene addition to 1,5-dimethyl-1,5-cyclooctadiene

Reaction of dichloroketene with 1,5-dimethyl-1,5 COD 6 charters an eventful course to furnish novel tricyclic ketone 10, through the intermediacy of tricyclic hydroxy olefin 9, in which the two carbon atoms of dichloroketene form a bridge across the eight mem-bered ring

Localization of multi-class on-road and aerial targets using mmwave FMCW radar

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Efficient Hardware Architectures for Accelerating Deep Neural Networks: Survey

In the modern-day era of technology, a paradigm shift has been witnessed in the areas involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). Specifically, Deep Neural Networks (DNNs) have emerged as a popular field of interest in most AI applications such as computer vision, image and video processing, robotics, etc. In the context of developed digital technologies and the availability of authentic data and data handling infrastructure, DNNs have been a credible choice for solving more complex real-life problems. The performance and accuracy of a DNN is a way better than human intelligence in certain situations. However, it is noteworthy that the DNN is computationally too cumbersome in terms of the resources and time to handle these computations. Furthermore, general-purpose architectures like CPUs have issues in handling such computationally intensive algorithms. Therefore, a lot of interest and efforts have been invested by the research fraternity in specialized hardware architectures such as Graphics Processing Unit (GPU), Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), and Coarse Grained Reconfigurable Array (CGRA) in the context of effective implementation of computationally intensive algorithms. This paper brings forward the various research works carried out on the development and deployment of DNNs using the aforementioned specialized hardware architectures and embedded AI accelerators. The review discusses the detailed description of the specialized hardware-based accelerators used in the training and/or inference of DNN. A comparative study based on factors like power, area, and throughput, is also made on the various accelerators discussed. Finally, future research and development directions are discussed, such as future trends in DNN implementation on specialized hardware accelerators. This review article is intended to serve as a guide for hardware architectures for accelerating and improving the effectiveness of deep learning research.publishedVersio

A study on Seed germination of Cassia alata Linn an antiallergenic plant

Cassia alata known as candle bush or Ringworm tree belongs to Cesalpinaceae family, which was found in diverse habitats in the tropics. C. alata leaves containing some chemical substances like chrysophanic acid, is a common ingredient in soaps, shampoos and lotions. The effectiveness of this plant against skin diseases is confirmed by modern scientific studies. The seed germination was gradually decreased by increasing the age of the seeds. Seed propagation is still used as a specialized tool for breeding purposes and for the propagation of pathogen-free plant material

Micropropagation of Crotalaria laburnifolia L. – An ethnomedicinally important herbal species

A protocol for in vitro shoot multiplication in Crotalaria labumifolia L. through nodal explants was established. Excision and culture of the nodal segments from in vitro developed shoots on fresh MS medium with concentration of BA (1mg/1) facilitated development of multiple shoots. Subsequent cultures enhanced the rate of shoot proliferation. Shoots cultured on ½ MS medium containing NAA (0.5 mg/1) initiated roots well compared with IBA and this is the most suitable protocol studied in C. labumifolia. The present study is the first report on in vitro regeneration in this species&nbsp

Determination of Phase Composition of Cobalt Nanoparticles Using 59Co Internal Field Nuclear Magnetic Resonance

It is well known that cobalt exhibits polymorphism, i.e., the co-existence of both the hcp and fcc phases. In particular, the method of synthesis and other thermodynamic conditions is known to play a crucial role in determining the particular phase of cobalt. In this work, we have compared the phase composition of the cobalt nanoparticles synthesized using two different solvents (water) and ethanol (Co@C). XRD measurements confirm the existence of fcc phase in commercial cobalt nanoparticles (Co@A), co-existence of fcc and hcp phases in Co@B, while the existence of the hcp phase in Co@C. We have studied these cobalt nanoparticles using 59Co internal field nuclear magnetic resonance (IFNMR) for verification of phase composition. Our studies reveal that the Co@A has fcc as a major phase with minor quantity hcp phase. Co@B exhibits approximately equal amount of fcc and hcp phase while Co@C exhibits hcp as a major phase with minor fcc phase. Our SEM micrograph studies confirm that the cobalt particles have spherical shape in the fcc phase. The cobalt particles exhibit both spherical and dendrite morphology confirming the co-existence of fcc and hcp phases, while the sample with pure hcp phase exhibits the dendrite morphology. Our studies also throw light on understanding the effect of solvent in the phase formation of the cobalt nanoparticles