Academic literature on the topic 'DCDM'

This paper propose a new multiplexing technique which use the bipolar RZ signal to realize duty cycle division multiplexing (DCDM) ,we call it Absolute Polar Duty Cycle Division Multiplexing (APDCDM).Multiplexing and demultiplexing principle of APDCDM are analyzed. Here we have designed a optical fiber transmission system based on APDCDM of three users by Joint simulation with Optisystem and Matlab. Simulation result shows the feasibility of this system. By the analysis of signal energy, explain APDCDM can carry more users than DCDM.

Two kinds of graphene coatings are obtained by the graphene drop-coating drying method (DCDM) and the coating graphene conductive adhesive (CGCA). The effects of these two kinds of graphene coatings on the friction, wear, and voltage signals of the electrical contact interface are explored. The test results show that the presence of the graphene coating can effectively reduce the friction coefficient and friction force, and the graphene coating prepared by the DCDM possesses the best ability in reducing the friction coefficient. Although the presence of the graphene coating will lead to the increase in interface contact voltage at the initial stage, the voltage signal gradually becomes stable with the progress of friction and wear, suggesting that the graphene coating will not affect the stability of sliding electrical contact. Wear analysis results show that the graphene coating prepared by the DCDM has a good anti-wear effect, and the graphene particles in the abrasion area play the role of solid lubrication. Finite element analysis results show that the graphene coating will generate thermal expansion when electric current is applied, accordingly avoid the direct contact between the metal substrate, and, thus, reduce the interface friction and alleviate the wear degree of interface. However, the normal force fluctuation of the interface may increase.

Abstract The stability of particles in the cosmic soup is an important property that can affect the cosmic evolution. In this work, we update the constraints on the decaying cold dark matter scenario, when the decay products are effectively massless. We assume, as a base case, that all of dark matter is unstable and it can decay on cosmological time scales. We then extend the analysis to include the scenario where only a fraction of dark matter is unstable, while the remaining part is composed of the standard, stable, dark matter. We consider observations of cosmological probes at linear scales, i.e., Planck 2018 cosmic microwave background temperature, polarization, and lensing measurements, along with geometrical information from baryon acoustic oscillation (BAO) measurements from SDSS DR7, BOSS DR12, eBOSS DR16 and 6dFGS, to derive conservative constraints on the dark matter decay rate. We consider these dataset separately, to asses the relative constraining power of each dataset, as well as together to asses the joint constraints. We find the most stringent upper limit on the decay rate of decaying cold dark matter particles to be ΓDCDM < 0.129 × 10-18 s-1 (or, equivalently, the dark matter lifetime τ DCDM > 246 Gyr) at 95% C.L. for the combination of Planck primary anisotropies, lensing and BAO. We further explore one-parameter extensions of our baseline DCDM model. Namely, we vary the sum of neutrino masses, the curvature density parameter, and the tensor-to-scalar ratio along with the DCDM parameters. When varying the tensor-to-scalar ratio we also add data from the BICEP/Keck experiment.

The control of plant leaf diseases is crucial as it affects the quality and production of plant species with an effect on the economy of any country. Automated identification and classification of plant leaf diseases is, therefore, essential for the reduction of economic losses and the conservation of specific species. Various Machine Learning (ML) models have previously been proposed to detect and identify plant leaf disease; however, they lack usability due to hardware sophistication, limited scalability and realistic use inefficiency. By implementing automatic detection and classification of leaf diseases in fruit trees (apple, grape, peach and strawberry) and vegetable plants (potato and tomato) through scalable transfer learning on Amazon Web Services (AWS) SageMaker and importing it into AWS DeepLens for real-time functional usability, our proposed DeepLens Classification and Detection Model (DCDM) addresses such limitations. Scalability and ubiquitous access to our approach is provided by cloud integration. Our experiments on an extensive image data set of healthy and unhealthy fruit trees and vegetable plant leaves showed 98.78% accuracy with a real-time diagnosis of diseases of plant leaves. To train DCDM deep learning model, we used forty thousand images and then evaluated it on ten thousand images. It takes an average of 0.349s to test an image for disease diagnosis and classification using AWS DeepLens, providing the consumer with disease information in less than a second.

This research aimed to evaluate the interactions and effects of 2 and 4% addition levels of poultry slaughterhouse fat (chicken tallow) and soybean oil in diets for broiler chickens. Two experiments were carried out using one-day-old male Cobb chicks in an entirely random design with a 2x2 factorial scheme. In the first experiment, 560 chicks were used to evaluate performance and carcass characteristics. In the second experiment, 100 chicks were used to determine the nutrient digestibility, dietary energy utilization and the lipase and amylase pancreatic activity. There was no interaction between the fat sources and the addition levels for any of the analyzed variables, except for the digestibility coefficient of dry matter (DCDM), which was higher in diets added with 2% soybean oil when compared to chicken tallow. The addition of 4% fat in the diet, regardless of fat source, improved the digestibility coefficient of ethereal extract (DCEE) and increased weight gain and feed intake. Moreover, in the initial phase, the addition of 4% fat to the diet increased lipase activity when compared to diets with 2% addition, and a positive correlation between DCEE and pancreatic lipase activity was observed. In conclusion, there is no interaction between fat sources and addition levels, except for DCDM. Carcass characteristics are not influenced by any of the studied factors. The addition of 4% fat increases pancreatic lipase activity and improves DCEE, resulting in greater weight gain, regardless of the tested fat source, making chicken tallow a great alternative to soybean oil.

The role of octopamine (OA) in the feeding system of the pond snail, Lymnaea stagnalis , was studied by applying behavioural tests on intact animals, and a combination of electrophysiological analysis and morphological labelling in the isolated central nervous system. OA antagonists phentolamine, demethylchlordimeform (DCDM) and 2–chloro–4–methyl–2–(phenylimino)–imidazolidine (NC–7) were injected into intact snails and the sucrose–induced feeding response of animals was monitored. Snails that received 25–50 mg kg -1 phentolamine did not start feeding in sucrose, and the same dose of NC–7 reduced the number of feeding animals by 80–90% 1–3 hours after injection. DCDM treatment reduced feeding by 20–60%. In addition, both phentolamine and NC–7 significantly decreased the feeding rate of those animals that still accepted food after 1–6 hours of injection. In the central nervous system a pair of buccal neurons was identified by electrophysiological and morphological criteria. After double labelling (intracellular staining with Lucifer yellow followed by OA–immunocytochemistry) these neurons were shown to be OA immunoreactive, and electrophysiological experiments confirmed that they are members of the buccal feeding system. Therefore the newly identified buccal neurons were called OC neurons (putative OA containing neurons or OAergic cells). Synchronous intracellular recordings demonstrated that the OC neurons share a common rhythm with feeding neurons either appearing spontaneously or evoked by intracellularly stimulated feeding interneurons. OC neurons also have synaptic connections with identified members of the feeding network: electrical coupling was demonstrated between OC neurons and members of the B4 cluster motoneurons, furthermore, chemically transmitted synaptic responses were recorded both on feeding motoneurons (B1, B2 cells) and the SO modulatory interneuron after the stimulation of OC neurons. However, elementary synaptic potentials could not be recorded on the follower cells of OC neurons. Prolonged (20 to 30 s) intracellular stimulation of OC cells activated the buccal feeding neurons leading to rhythmic activity pattern (fictive feeding) in a way similar to OA applied by perfusion onto isolated central nervous system (CNS) preparations. Our results suggest that OA acts as a modulatory substance in the feeding system of Lymnaea stagnalis and the newly identified pair of OC neurons belongs to the buccal feeding network.