Influence of Ni (II) oxime complex coupled with the combination of diverse sized ZnO nanoparticles on Photovoltaic Performance

The one side selective synthesis of quinoline carboxylic acid oxime complex was carried out successfully. The as-prepared quinoline carboxylic acid oxime complex was complexed with nickel (II) salts to form nickel (II) oxime complex. These complexes were further adsorbed onto ZnO films containing ZnO nanoparticles of various sizes. ZnO films containing a diverse proportion of ZnO nanoparticles were investigated to enhance the photovoltaic efficiency of the dye-sensitized solar cell. The as-synthesized complex was characterized by scanning electron microscopy (SEM), Ultra violet visible spectroscopy (UV-vis), Fourier Transform Infrared Spectroscopy (FT-IR) spectroscopy, 1Hydrogen Nuclear magnetic resonance spectroscopy (1HNMR), Liquid chromatography coupled with mass spectrometry (LC-MR), Brunauer–Emmett–Teller (BET), and Attenuated total reflection Infra-red spectroscopy (ATR-IR). The combination of large and small ZnO nanoparticles has significantly improves the photovoltaic efficiency. The optimum mixing ratio for the best performance (0.127%) of a dye-sensitized solar cell is achieved by mixing the small: large ZnO particles in a ratio 60:40. The increased efficiency is due to the harvesting of light caused by scattering effect from larger sized ZnO particles. The ZnO layer consisting of smaller particles which are very next to the ZnO bigger particles makes a good electronic contact between film electrode and the Indium-doped tin oxide glass substrate resulting in the increases in the dye molecules adsorption. The over-layered, large-sized ZnO particles enhance the light-harvesting by light scattering effect. Compared to the other mixtures of ZnO films, there is a decrease in the photovoltaic performance of the solar cell when ZnO particles (small and large in a ratio 1:1) were adsorbed onto the Ni (II) oxime complex, which are caused due to the decrease in the surface area and dye aggregation.

Design and Experimental Verification of a Single-Phase Asymmetric Hybrid Multi-level Inverter

In recent years, multi-level inverters have emerged as a feasible power conversion solution for medium and high power applications due to better harmonic performance and ability to operate at high voltage/power when compared to traditional two-level inverters. Since the output level of the multi-level inverters depends on the number of the switching elements, as more levels are required, more switching elements are used. This situation makes the circuit and the control design complex and the losses to upsurge. To overcome these limitations and produce low harmonic content at the output, reduced switch count topologies are popular. In this study, a single-phase asymmetric hybrid multi-level inverter is proposed by combining diode clamped and cascaded H-bridge topologies. The inputs of the proposed inverter are selected as two unequal DC voltage sources. In this regard, fewer switching elements are used to obtain the same number of voltage levels at the output when compared to traditional multi-level inverters. The efficiency and the harmonic performance of the proposed topology is both verified by simulation and experimental studies. The gating signals of the semiconductor switches are produced by phase disposition pulse width modulation with carriers’ frequency of 4 kHz. It is shown by the experiments that a maximum efficiency of 94 % and a total harmonic distortion of 29 % are attained in the case studies.

Influence of Administration Route and Dose on Biodistribution Profile and Effects of PEG-PLA Nanoparticles in Mice

Polyethylene glycol-polylactic acid nanoparticles (PEG-PLA NPs) represent a new generation of parenteral therapeutics systems. Following administration, these NPs possess the potential to interact with biological machinery. Therefore, it is essential to get a systematic understanding of the biological fate of these NPs to evaluate their safety. In the present study, two doses (20 and 40 mg/kg) of technetium-99m labeled PEG-PLA NPs were administered intravenous (i.v.) and oral into mice and the distribution was assessed at 1, 2, 4 and 24 h post administration. Biodistribution and blood kinetic profiles revealed the extended systemic circulation of the NPs. Dose-dependent presence of NPs (p<0.05) was detected in the blood, liver, lung, spleen, and kidney of i.v. injected mice, and also in the blood, lung, spleen, stomach, and intestine of oral administered mice. The consequences of NP interaction with the biological components were studied by measurement of hematology, oxidative stress, genotoxic and histological parameters. Significantly increased levels of oxidative stress markers such as glutathione were observed in the liver, and spleen of i.v. injected mice and liver, stomach, and intestine of orally treated mice. Decreased lipid peroxidation levels (p<0.05) were observed in the liver of orally treated mice versus untreated mice. Even though PEG-PLA NPs have been shown to induce oxidative DNA damage, interestingly no histological lesions were observed in selected organs except lung of i.v. treated mice, which showed moderate vascular congestion. Such insights on in vivo distribution and understanding of nano-bio interactions at molecular and genetic levels are considered fundamental for the designing of safer nanoparticles for biomedical applications.

Applying Artificial Intelligence Techniques to Improve Clinical Diagnosis of Alzheimer’s Disease

Alzheimer's disease (AD) is a significant regular type of dementia that causes damage in brain cells. Early detection of AD acting as an essential role in global health care due to misdiagnosis and sharing many clinical sets with other types of dementia, and costly monitoring the progression of the disease over time by magnetic reasoning imaging (MRI) with consideration of human error in manual reading. Our proposed model in the first stage, apply the medical dataset to a composite hybrid feature selection (CHFS) to extract new features for select the best features to improve the performance of the classification process due to eliminating obscures. In the second stage, we applied a dataset to a stacked hybrid classification system to combine Jrip and random forest classifiers with six model evaluations as meta-classifier individually to improve the prediction of clinical diagnosis. All experiments conducted on a laptop with an Intel Core i7- 8750H CPU at 2.2 GHz and 16 G of ram running on windows 10 (64 bits). The dataset evaluated using an explorer set of WEKA data mining software for the analysis purpose. The experimental show that the proposed model of (CHFS) feature extraction performs better than proncipal component analysis (PCA), and lead to effectively reduced the false-negative rate with a relatively high overall accuracy with support vector machine (SVM) as meta-classifier of 96.50% compared to 68.83% which is considerably better than the previous state-of-the-art result. The receiver operating characteristic (ROC) curve was equal to 95.5%. Also, the experiment on MRI images Kaggle dataset of CNN classification process with 80.21% accuracy result. The results of the proposed model show an accurate classify Alzheimer's clinical samples against MRI neuroimaging for diagnoses AD at a low cost.

Discovering Customer Paths from Location Data with Process Mining

customer paths can be used for several purposes, such as understanding customer needs, defining bottlenecks, improving system performance. Two of the principal difficulties depend on discovering customer paths due to dynamic human behaviors and collecting reliable tracking data. Although machine learning methods have contributed to individual tracking, they have complex iterations and problems to produce understandable visual results. Process mining is a methodology that can rapidly create process flows and graphical representations. In this study, customer flows are created with process mining in a supermarket. The differences between the paths of customers purchased and non-purchased are discussed. The results show that both groups have almost similar visit duration, which is 87.5 minutes for purchased customers and 86.6 minutes for non-purchased customers. However, the duration of aisles is relatively small in non-purchased customer flows because customers aim to return or change the item instead of buying.

Nonlinear Analysis of Tie Confined Columns

Columns, being a very important component of the building structure, are required to be strong enough and also sufficiently deformable to withstand all possible static and dynamic loads to maintain the integrity of the structure throughout their entire life. The strength and the deformability of the columns can be increased by confining the concrete with lateral reinforcements provided in the form of the spirals, hoops or ties. Several experimental and analytical studies have been carried out by various researchers over the years to determine the extent of improvement that can be made to the strength and ductility of the columns, subjected to concentric loading, by confining them using lateral reinforcements. In the present study three-dimensional finite element models of confined concrete columns have been made using ANSYS and analyzed under the application of static concentric loading to find out the effects of lateral confinement. Suitable material models for both concrete and steel have been chosen and nonlinear finite element analysis (FEA) of laterally confined three-dimensional concrete column models have been carried out. The numerical methodology, at first, has been verified against previous experimental results. Then different types of lateral confinements have been modeled and the stress-strain responses and the complex stress distribution patterns have been studied and compared to find out the better type of confinement.

A Design Insight for Substitution of Metal Shims with Reverse Engineered Element in Tool Post for Alignment of Tool-Work Center

This research work propounds and analyses the comparison of solution to the issue of height adjustment of tool in four way tool post. The customary way of tool lifting in tool post to centre of work i.e. by adding/removing metal packing, is altered by introducing a design alternative for tool lifting, an upgradation in the former proposed design named solid double cone threaded pin (SDCTP). It is explicitly studied to investigate its limitation and scope for further design amendments. In the premise, a revised design is proposed including modifications named as solid cone threaded pin (SCTP) and is fabricated along with its assembly. Mathematical calculations of least count and screw thread analysis are performed on both the pins. Finite element analysis on CREO is executed to calculate stresses induced for diverse loads to analyze pin failure conditions. The results of new modified design is compared with the erstwhile concluding that SCTP design is preferable over SDCTP design entailing precise tool adjustment, saving time and higher efficiency in machining operations. The paper subsequently explores conventional tool lifting method and its shortfall, shortcomings of former design, revised design and its comparison, fabrication of revised design, conclusions and future ambit.