Experimental investigation of impact of diesel particulate filter on smoke and NO<Subscript>x</Subscript> emissions of a Euro-I compression ignition engine with active and off-board regeneration

Old engines (Euro III or earlier) produce more emissions, and it will be difficult to entirely stop their usage especially in developing and under-developed nations; hence, it is desired that appropriate emission reduction technologies are tested on such engines to analyze their feasibility and economical acceptability. While most such studies have been conducted on constant speed stationary engines and modern engines, this study tried to analyze the effectiveness of an uncoated wall-flow type ceramic diesel particulate filter on a Euro-I, water-cooled, direct injection, variable speed, compression ignition engine in a laboratory set-up in India. Also, this study focused on diesel particulate filter regeneration by two methods: active regeneration by diesel injection in the particulate filter using an electronic control unit and off-board regeneration by taking out and heating the diesel particulate filter in an electrical resistance furnace at 650 °C for 10 h. The results, in the form of smoke emission, NO_x emission and engine performance, obtained using both the regeneration methods were analyzed, and conclusions were drawn. It was found that using diesel particulate filter, particulate matter emissions (smoke) were almost entirely eliminated. It was also found that off-board regeneration had numerous advantages compared to active regeneration. Since a furnace would be needed for off-board regeneration, an exchange process for diesel particulate filter is suggested.     

Development and gamma-scintigraphy study of Hibiscus rosasinensis polysaccharide-based microspheres for nasal drug delivery

Objective: This work describes the application of natural plant polysaccharide as pharmaceutical mucoadhesive excipients in delivery systems to reduce the clearance rate through nasal cavity.

Methods: Novel natural polysaccharide (Hibiscus rosasinensis)-based mucoadhesive microspheres were prepared by using emulsion crosslinking method for the delivery of rizatriptan benzoate (RB) through nasal route. Mucoadhesive microspheres were characterized for different parameters and nasal clearance of technetium-99m (^99mTc)-radiolabeled microspheres was determined by using gamma-scintigraphy.

Results: Their Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) studies showed that the drug was stable during preparation of microspheres. Aerodynamic diameter of microspheres was in the range 13.23?±?1.83–33.57?±?3.69?µm. Change in drug and polysaccharide ratio influenced the mucoadhesion, encapsulation efficiency and in-vitro release property. Scintigraphs taken at regular interval indicate that control solution was cleared rapidly from nasal cavity, whereas microspheres showed slower clearance (p?Conclusion: Natural polysaccharide-based microspheres achieved extended residence by minimizing effect of mucociliary clearance with opportunity of sustained delivery for longer duration.     

Fine-Grained Multivariate Time Series Anomaly Detection in IoT

Sensors produce a large amount of multivariate time series data to record the states of Internet of Things (IoT) systems. Multivariate time series timestamp anomaly detection (TSAD) can identify timestamps of attacks and malfunctions. However, it is necessary to determine which sensor or indicator is abnormal to facilitate a more detailed diagnosis, a process referred to as fine-grained anomaly detection (FGAD). Although further FGAD can be extended based on TSAD methods, existing works do not provide a quantitative evaluation, and the performance is unknown. Therefore, to tackle the FGAD problem, this paper first verifies that the TSAD methods achieve low performance when applied to the FGAD task directly because of the excessive fusion of features and the ignoring of the relationship’s dynamic changes between indicators. Accordingly, this paper proposes a multivariate time series fine-grained anomaly detection (MFGAD) framework. To avoid excessive fusion of features, MFGAD constructs two sub-models to independently identify the abnormal timestamp and abnormal indicator instead of a single model and then combines the two kinds of abnormal results to detect the fine-grained anomaly. Based on this framework, an algorithm based on Graph Attention Neural Network (GAT) and Attention Convolutional Long-Short Term Memory (A-ConvLSTM) is proposed, in which GAT learns temporal features of multiple indicators to detect abnormal timestamps and A-ConvLSTM captures the dynamic relationship between indicators to identify abnormal indicators. Extensive simulations on a real-world dataset demonstrate that the proposed algorithm can achieve a higher F1 score and hit rate than the extension of existing TSAD methods with the benefit of two independent sub-models for timestamp and indicator detection.     

Study on dislocation density,microstructure, and mechanical properties of P92 steel for different heat treatment conditions

The impact of various heat treatment procedures on microstructure, dislocation density, hardness, tensile characteristics, and impact toughness of P92 steel was examined in the current experiment. The martensitic microstructure and average microhardness of 463 HV 0.2±8 HV 0.2 of the normalized steel were prevalent. A tempering procedure was carried out at 760 °C for a range of 2 hours to 6 hours. Additionally, an X-ray diffraction examination was carried out, and the results were used to determine the dislocation density. The normalized sample was characterized by a high dislocation density. The dislocation density was decreased by tempering of normalized samples. With an increase in tempering time, the effect of the treatment coarsened the grains, precipitates, and decreased the area fraction of precipitates. After tempering, MX, M₂₃C₆, and M₇C₃ types precipitates were found to have precipitated, according to energy dispersive spectroscopy and x-ray diffraction research. The ideal tempering period was determined to be 4 hours at a tempering temperature of 760 °C based on the microstructure and mechanical characteristics. Steel that was tempered at 760 °C for 4 hours had a yield strength of 472 MPa, an ultimate tensile strength of 668.02 MPa, and an elongation of 26.05 %, respectively.     

Sol-gel processed barium titanate ceramics and thin films

Ferroelectric barium titanate (BaTiO3) ceramics and thin films have been prepared from barium acetate (Ba(CH3COO)2) and titanium (IV) isopropoxied (Ti((CH3)2CHO)4) precursors by a sol–gel technique. The as-grown powder and thin films were found to be amorphous, which crystallized to the tetragonal phase after annealing at 700°C in air for 1 h. Both the ceramics and thin films showed well-saturated polarization–field (P–E) hysteresis loops at room temperature. The value of the spontaneous polarization, PS, remnant polarization, Pr, and coercive field, Ec, of the ceramics and thin films determined from the P–E hysteresis loop were found to be 19.0 and 12.6; 14.0 and 3.2 G cm–2, and 30 and 53 kV cm–1, respectively. The coercive field of the film determined from the capacitance–voltage, C–V, characteristics is slightly lower than that determined from the P–E hysteresis loop (43 kV cm–1). The room-temperature dielectric constant, , of the ceramics and films was found to be 1135 and 370, respectively. Both the films and ceramics showed dielectric anomaly peaks at 125 °C, showing ferroelectric to paraelectric phase transition. © 1998 Kluwer Academic Publishers     

Chromatic aberrations of radial gradient-index lenses. I. Theory

Chromatic effects of radial gradient-index materials have been analyzed, and several important conclusions have been derived in terms of material dispersion data. The use of Buchdahl dispersion data, both for base glass materials and ion-exchange pairs, provides some simple relationships for chromatic aberration and helps in selecting suitable materials for producing achromatic radial gradient-index lenses.     

Domain-specific initial population strategy for compliant mechanisms using customized genetic algorithm

Genetic algorithms (GAs) can precisely handle the discrete structural topology optimization of single-piece elastic structures called compliant mechanisms. The initial population of these elastic structures is mostly generated by assigning the material at random. This causes disconnected or unfeasible designs and further rule-based repairing can result in representation degeneracy. However, the problem-specific initial population can affect the performance of GAs like other operators. In this paper, a domain-specific initial population strategy is developed that generates geometrically feasible structures for path generating compliant mechanisms (PGCMs). It is coupled with the elitist non-dominated sorting genetic algorithm (NSGA-II) which has been customized for structural topology optimization. The performance of initial population strategy over random initialization using customized NSGA-II is checked on single and bi-objective optimization problems. Based on the results, it is observed that the custom initialization outperforms the random initialization by dominating all the solutions and exploring larger area of posed objectives. The elastic structures obtained by solving two examples of PGCMs using domain specific initial population strategy are also presented.