The current computational fluid dynamics (CFD) speculate reveals piston bowl geometry’s impact on an immediate base engine execution and discharge. Different bowl shapes, that is, shallow combustion ...chamber, hemispheric combustion chamber, and toroidal combustion chamber (TCC), were made with a reference compression ratio of 17.5:1. ANSYS V18.1 was used for numerical investigation, in tandem with the wise burning model. It was clearly identified that TCC cylinder bowl geometry delivered the proper air–fuel mixing blend inside the cylinder chamber, which prompts a homogeneous charge. Further, analytical experiments were completed to break down the TCC cylinder bowl geometry by shifting the profundity of the bowls. The case with 1.26 mm decline top to bottom of the bowl from the benchmark TCC and covered with zirconium coating gives better results. TCC produced a very powerful squish over a short period of time. TCC’s fraction of mass in
carbon monoxide
emissions is down to 0.03 at 25o crank angle after TDC while both hemispherical combustion chamber and shallow depth combustion chamber are measured at nearly 0.1. It was found that TCC gave a better performance compared with the other two designs at full load conditions while operating from medium to high engine speed. Overall, the low-speed application of the engine was suitable for SCC design, and TCC design was suitable for higher-speed application.
The efficient operation of the present day power system is an important issue to satisfy the customer needs. To improve the performance of the existing power system, the flexible alternating current ...transmission system (FACTS) devices have been attracted by an engineering community with the expertise in power system. This article proposes the self-adaptive firefly algorithm (SAFA) for placement of FACTS devices, which identifies the appropriate type, best possible locations and optimal parameters of FACTS devices. Static var compensator, thyristor controlled series compensator and unified power flow controller are considers as FACTS devices for their placement. The objectives are to improve the power system performance by placement of FACTS devices through minimising real power loss, improving voltage profile and enhancing the voltage stability. Effectiveness of the proposed SAFA is tested on standard IEEE 30 and IEEE 57 bus systems with different objectives. The results are compared with other approaches, which clearly indicate the effectiveness and usefulness of the proposed method.
Bacterial blight (BB) and fungal blast diseases are the major biotic constraints that limit rice productivity. To sustain yield improvement in rice, it is necessary to developed yield potential of ...the rice varieties by incorporation of biotic stress resistance genes. Tellahamsa is a well-adapted popular high yielding rice variety in Telangana state, India. However, the variety is highly susceptible to BB and blast. In this study, simultaneous stepwise transfer of genes through marker-assisted backcross breeding (MABB) strategy was used to introgress two major BB (Xa21 and xa13) and two major blast resistance genes (Pi54 and Pi1) into Tellahamsa. In each generation (from F.sub.1 to ICF.sub.3) foreground selection was done using gene-specific markers viz., pTA248 (Xa21), xa13prom (xa13), Pi54MAS (Pi54) and RM224 (Pi1). Two independent BC.sub.2 F.sub.1 lines of Tellahamsa/ISM (Cross-I) and Tellahamsa/NLR145 (Cross-II) possessing 92% and 94% recurrent parent genome (RPG) respectively were intercrossed to develop ICF1-ICF.sub.3 generations. These gene pyramided lines were evaluated for key agro-morphological traits, quality, and resistance against blast at three different hotspot locations as well as BB at two locations. Two ICF.sub.3 gene pyramided lines viz., TH-625-159 and TH-625-491 possessing four genes exhibited a high level of resistance to BB and blast. In the future, these improved Tellahamsa lines could be developed as mega varieties for different agro-climatic zones and also as potential donors for different pre-breeding rice research.
Zinc Finger MIZ-Type Containing 1 (Zmiz1), also known as ZIMP10 or RAI17, is a transcription cofactor and member of the Protein Inhibitor of Activated STAT (PIAS) family of proteins. Zmiz1 is ...critical for a variety of biological processes including vascular development. However, its role in the lymphatic vasculature is unknown. In this study, we utilized human dermal lymphatic endothelial cells (HDLECs) and an inducible, lymphatic endothelial cell (LEC)-specific Zmiz1 knockout mouse model to investigate the role of Zmiz1 in LECs. Transcriptional profiling of ZMIZ1-deficient HDLECs revealed downregulation of genes crucial for lymphatic vessel development. Additionally, our findings demonstrated that loss of Zmiz1 results in reduced expression of proliferation and migration genes in HDLECs and reduced proliferation and migration in vitro. We also presented evidence that Zmiz1 regulates Prox1 expression in vitro and in vivo by modulating chromatin accessibility at Prox1 regulatory regions. Furthermore, we observed that loss of Zmiz1 in mesenteric lymphatic vessels significantly reduced valve density. Collectively, our results highlight a novel role of Zmiz1 in LECs and as a transcriptional regulator of Prox1, shedding light on a previously unknown regulatory factor in lymphatic vascular biology.
Abstract
This work provides a high-level overview of the performance parameters of a nanoparticle-fuelled engine emulsion. The nanoparticle of cobalt chromite was created by a straightforward ...laboratory procedure. The nanoparticles were introduced at concentrations of 20 ppm, 40 ppm, 60 ppm, and 80 ppm, with the optimal concentration being found to be a Kapok methylester-20 (KME20) blend. Varying the timings and operated the engine at a constant speed 1800 rpm. Injections can be given at 19, 23, or 27 degrees before the before top dead centre, which are referred to as retardation, standard, and advanced, respectively. The Brake thermal efficiency is increased by 7.2% when the blend of KME20 with 80 ppm advanced is compared to the triggered ignition delay. Unburnt hydrocarbon and carbon monoxide levels in the 80 ppm-Advanced KME20 mix are reduced by 37.86% and 41.66%, respectively, when compared to the standard injection period. Oxides of nitrogen and carbon monoxide in the blend KME20 with 20 ppm - retardation rose by 16.45 and 9.5 percent, respectively, compared to the duration of normal injections. Increased the brake thermal efficiency for KME20 with nanoparticles at concentration of 80 ppm is 7.5% as related to same blend without doping of nanoparticles. Using kapok methyl ester with nanoparticles doped in the standard engine can improve efficiency and performance.
•Estimation of candidate buses using Loss Sensitivity Factor, helps in reducing search space.•GSA to answer optimization problems with discontinuous solution space & objectives where global optimum ...is desired.•GSA is verified on reputed 33, 69, 85 & 141 Bus RDN.•Results attained make evident that GSA is superior to the techniques discussed in preceding literatures.
Power generated in generating station is transmitted through transmission lines and fed to the consumers through distribution substation. The power distributed into the network has losses, which is greater in distribution system compared to transmission system. This problem could be addressed by placing capacitor at strategic location due to which the kW loss can be minimized and the net savings can be maximized. This paper adopts two methods where the first method being the sensitivity analysis and the second method is the Gravitational Search Algorithm (GSA). Sensitivity analysis is a methodical technique, which is used to reduce the search space and to arrive at an accurate solution for recognizing the locality of capacitors. Capacitor values are allocated for the respective locations using GSA. The overall precision and dependability of the adopted approach were authenticated and verified on few radial distribution network with diverse topologies of varying sizes and complexities and also compared with an analytical Interior Point algorithm and one of the meta-heuristic optimization technique called Simulated Annealing. Computational outcomes obtained showed that the proposed method is capable of generating optimal solutions.
The main objective of Internet of Things (IoT) is connecting with different objects via Internet without human intervention. Wireless Sensor Networks (WSNs) which involves ubiquitous computing ...through which small sensors are connected to the Internet and are used for collecting data. Significant amount of information flowing in the internet is made up of sensory data. To resolve the storage issues of the huge data generated by IoT, the Hadoop Distributed File System are used that streams data to user applications as required. It is difficult to accomplish analysis of vast amount of data (big data) with existing data processing methods. To avoid redundant and irrelevant data, the data needs to be classified. This work presents the use of Support Vector Machine, and Adaboost classifiers, and modifying Adaboost classifier with Genetic Algorithm (GA), Stochastic Diffusion Search (SDS), and Particle Swarm Optimization (PSO). To avoid redundant classifiers, an ensemble algorithm is proposed in this work, PSO with Adaboost classifier and SDS-GA with Adaboost classifier, that can reinitialize attributes, thus avoiding reaching local optimum, and optimizing the coefficients of Adaboost weak classifiers. The proposed algorithms effectively classify the data gathered from WSN and IoT applications. The outcomes of the experiment showed that the proposed SDS-GA algorithm is efficient over other algorithms with respect to accuracy, precision, recall, f measure and false discovery rate.
Shape is an objective characteristic of an object. A boundary separates a physical object from its surroundings. It defines the shape and regulates energy flux into and from an object. Visual ...perception of a definite shape (geometry) of physical objects is an abstraction. While the perceived geometry at an object's sharp interface (macro) creates a Euclidian illusion of actual shape, the notion of diffuse interfaces (micro) allows an understanding of the realistic form of objects. Here, we formulate a dimensionless geometric entropy of plant leaves (SL) by a 2-D description of a phase-field function. We applied this method to 112 tropical plant leaf images. SL was estimated from the leaf perimeter (P) and leaf area (A). It correlates positively with a fractal dimensional measure of leaf complexity, viz., segmental fractal complexity. Leaves with a higher P: A ratio have higher SL and possess complex morphology. The univariate cluster analysis of SL reveals the taxonomic relationship among the leaf shapes at the genus level. An increase in SL of plant leaves could be an evolutionary strategy. The results of morphological complexity presented in this paper will trigger discussion on the causal links between leaf adaptive stability/efficiency and complexity. We present SL as a derived plant trait to describe plant leaf complexity and adaptive stability. Integrating SL into other leaf physiological measures will help to understand the dynamics of energy flow between plants and their environment.
Neurodevelopmental disorders (NDDs) are a class of pathologies arising from perturbations in brain circuit formation and maturation with complex etiological triggers often classified as environmental ...and genetic. Neuropsychiatric conditions such as autism spectrum disorders (ASD), intellectual disability (ID), and attention deficit hyperactivity disorders (ADHD) are common NDDs characterized by their hereditary underpinnings and inherent heterogeneity. Genetic risk factors for NDDs are increasingly being identified in non-coding regions and proteins bound to them, including transcriptional regulators and chromatin remodelers. Importantly,
mutations are emerging as important contributors to NDDs and neuropsychiatric disorders. Recently,
mutations in transcriptional co-factor Zmiz1 or its regulatory regions have been identified in unrelated patients with syndromic ID and ASD. However, the role of Zmiz1 in brain development is unknown. Here, using publicly available databases and a Zmiz1 mutant mouse model, we reveal that Zmiz1 is highly expressed during embryonic brain development in mice and humans, and though broadly expressed across the brain, Zmiz1 is enriched in areas prominently impacted in ID and ASD such as cortex, hippocampus, and cerebellum. We investigated the relationship between Zmiz1 structure and pathogenicity of protein variants, the epigenetic marks associated with Zmiz1 regulation, and protein interactions and signaling pathways regulated by Zmiz1. Our analysis reveals that Zmiz1 regulates multiple developmental processes, including neurogenesis, neuron connectivity, and synaptic signaling. This work paves the way for future studies on the functions of Zmiz1 and highlights the importance of combining analysis of mouse models and human data.
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