Modeling runoff from an agricultural watershed of western catchment of Chilika lake through ArcSWAT

Chilika lake is the biggest lagoon in the Indian Eastern coast and is a source of livelihood for peoples of the coastal region surrounding it mainly through fisheries. However, the deposition of sediments in the lake carried through runoff water from its drainage basins may alter this wetland ecosystem in future. Implementation of appropriate soil water conservation measures may reduce the sediment load in runoff water and thus may protect this lagoon ecosystem. Keeping in view these concerns, runoff water from a selected watershed of western catchment of Chilika lagoon was modeled through ArcSWAT with a purpose to estimate future runoff potential from western catchment. Effective hydraulic conductivity of main channel, base flow alpha factor, curve number corresponding to antecedent moisture content II, and roughness coefficient of main channel were found most sensitive parameters in decreasing order. Nash–Sutcliffe coefficient of predicted monthly runoff was 0.72 and 0.88 during calibration and validation period, respectively whereas root mean squared error of predicted monthly runoff was 54.5 and 66.1 mm, respectively. Modeling results indicated that about 60% of rainfall is partitioned to runoff water, which carry significant amount of sediment load and contributes to Chilika lake.     

$$\hbox {CuBO}_{2}$$ nanonetwork: a novel and significant candidate for photocatalytic dye degradation

\(\hbox {CuBO}_{2}\) is a novel material in the research field of transparent conducting oxide. In this study, \(\hbox {CuBO}_{2}\) nanostructures have been synthesized via sol–gel method. The phase formation is confirmed using an X-ray diffractometer. Detailed morphological analysis is performed by field emission scanning electron microscopy and transmission electron microscopy. A novel uniform nanonetwork-like structure is obtained and its band gap is found to be 4.24 eV. In ultraviolet light irradiation, this as-synthesized sample shows efficient photocatalytic activity for degradation of organic dye Rhodamine B. The degradation efficiency and the rate constant were calculated as \(\sim \)70% and \(1.32\times 10^{-3}\,\hbox {min}^{-1}\), respectively. This nanonetwork-like structure can be a potential candidate as the base material to attach various metals and metal oxide nanostructures to get highly efficient future photocatalysts. As a result, this study opens up a new gateway to fabricate novel environment-friendly nanocatalysts with high performance.     

Traffic Prediction Using Multifaceted Techniques: A Survey

Road transportation is the largest and complex nonlinear entity of the traffic management system. Accurate prediction of traffic-related information is necessary for an effective functioning of Intelligent Transportation System (ITS). It is still a challenge for the departments of transportation to choose an appropriate prediction technique for the ITS applications. That is, a user must be able to utilize the disseminated information effectively by the forecasting models. This paper provides a detailed survey of the latest forecasting technologies and contributes to understand the key concept behind the prediction approaches. To provide guidelines to the decision-maker, this paper reviews multifaceted techniques developed by various authors for traffic prediction. We start classifying each technique into four categories namely, Machine Learning (ML), Computational Intelligence (CI), Deep Learning (DL), and hybrid algorithms. Many have conducted survey using model-driven or data-driven methods. We are the first to explore the area of traffic prediction based on the advances in multifaceted techniques proposing algorithmic approaches for key traffic characteristics in the forecasting process. The role of dependent factors in the prediction are analyzed thoroughly. We have analyzed each algorithm chronologically based on various traffic traits. The approaches are summarized based on the rational usage and performance of each technique. The analysis led to several research queries, and the appropriate  responses are provided based on our detail survey. Finally, it is confirmed that currently, CI-MLs and DL hybrid techniques outperforms the rest in the field of traffic prediction. Ultimately suggested open challenges and future direction to explore the capability of DL and hybrid techniques further in the field of traffic prediction. 

     

Tuning the BODIPY core for its potential use in DSSC: a quantum chemical approach

Boron dipyrromethene (BODIPY) is a highly promising candidate for use in dye-sensitized solar cell (DSSC), because of its attractive absorption characteristics such as strong extinction coefficients in the visible and near-IR ranges (70000–80000 \(\hbox {M}^{-1}\) \(\hbox {cm}^{-1})\), large quantum yields, longer excited-state lifetime and also high solubility in many organic solvents. Moreover, the absorption peaks can be shifted towards longer wavelengths when functionalized at suitable positions of the BODIPY core. Herein, on the basis of density functional theory (DFT) and time-dependent DFT, we provide the opto-electronic properties of BODIPY core-functionalized dyes to see their applicability in organic DSSC. Our systematic analyses reveal that the 2,6 substituted dyes show better photovoltaic properties compared to the 3,5 substituted ones. On the basis of empirical relationship, we have also calculated the photo-induced electron injection times of some dye-\(\hbox {TiO}_{2}\) composites, which seem to be in the ultrafast time scale, thus rendering them a promising candidate for DSSC applications. Our theoretical studies provide that judiciously designed BODIPY core-derived dyes show certain unique spectroscopic and electronic features that make them highly advantageous in DSSC applications as compared to other organic dyes.     

Electronic structures and reactivities of monometallic and bimetallic clusters of Au and Cu

The variation of the Au 4f binding energy of Au clusters with the cluster size has been established by measuring the binding energies of clusters whose size distributions were independently determined by HREM and STM. The binding energy increases significantly when the cluster size is less than 2 nm. Au-Cu bimetallic clusters of the composition Cu₃Au have been deposited for the first time on carbon substrates. The shifts in the core level binding energies of the bimetallic clusters show the effect of alloying in the case of large clusters, but show effects of both alloying and cluster size in the case of the small clusters. The interaction of CO with Cu₃Au clusters is stronger than with a bulk Cu metal. The interaction of CO with small Cu clusters also seems to be stronger than with bulk Cu or with large Cu clusters.     

Usability is more valuable predictor than product personality for product choice in human-product physical interaction

Product personality and product usability are two important factors which can influence consumers' product choice. Published literature are available regarding independent impact of product personality and product usability on product choice but no research has been reported so far for understanding their collective influence on product choice. In addition, which factor between usability and product personality contributing more in product choice is still not clear. Current research thus aimed to bridge these research gaps by establishing inter-relationships among product personality, usability and product choice. To achieve this goal, two separate experiments were conducted. Results of first experiment revealed that products having high product usability also possessed strong product personality. Following second experiment, it was observed that solitary influence of product usability on product choice was more than the standalone influence of product personality in human-product physical interaction. Moreover, it unfolded the fact that product usability mediates the influence of product personality towards product choice. Established interrelationships among product personality, usability and product choice, would help designer and ergonomists to decide how product attributes could be manipulated to enhance product personality and/or product usability to ensure product choice.     

Performance improvement of DC-DC converter using L-D-based modified GaN-FET driver

Bootstrap capacitor in FET gate driver plays an important role in the transient performance of the half bridge configured synchronous buck DC-DC converter especially in the top switch. In this paper, a new bootstrap capacitor based GaN-FET driver is proposed. This new GaN-FET driver is tested in a synchronous buck converter for performance verification like immunity, transient response, and voltage ringing. A comparison study with the existing LM5113 (Texas Instrument)–based driver for GaN-FET and IR2110-based Si-MOSFET driver on a DC-DC converter is carried out to show the performance improvement using the proposed GaN-FET driver. The simulation study is performed on spice-based NI-Multisim 14.1. Finally, the designed GaN-FET driver is tested on a 60-W synchronous buck DC-DC converter in open-loop and closed-loop configuration.     

A highly linear CMOS transconductance amplifier in 180?nm process technology

The present article describes the design and analysis of an operational transconductance amplifier (voltage to current converter) with wide linear input range. The proposed configuration combines the techniques of signal attenuation and source degeneration in order to reduce the odd order harmonic distortion significantly. The proposed circuit is compared with several circuit topologies based on MOS differential pairs with respect to their achievable linearity, input referred noise and power consumption. The linear transconductor is designed and simulated in 180?nm CMOS process technology with 1.8?V power supply. Simulation results show third order harmonic distortion (HD ₃) of ?70?dB for 600?mV_pp input signal. For 1% transconductance variation the linear range is about 1.2?V_pp. The input referred noise of the transconductor is $70\,\hbox{nV}/\sqrt{\text {Hz}}$ at 10?MHz. The quiescent power consumption is only 450???W.