Retail investors' financial risk tolerance and their risk-taking behaviour: The role of demographics as differentiating and classifying factors

AbstractThis paper empirically examines whether demographic factors namely gender, age, marital status, income, occupation, and education could be used individually or in combination to differentiate among retail investors in terms of financial risk tolerance (FRT) and risk taking behaviour (FRB), and classify retail investors into FRT and FRB categories. A single cross sectional survey was conducted among 778 retail investors with various levels of investment experience, through a structured questionnaire covering a variety of demographic factors. Four of the six demographic factors were found to be useful in differentiating between levels of investors' FRT and FRB as well as classifying individuals into different FRT and FRB categories

Novel drug delivery system

This investigation aims to evaluate the Anti tumour potential of the petroleum ether extract of Abrus precatorius Linn (PEEAP) on Ehrlich Ascitis Carcinoma (EAC) tumour model. Tumour was induced in mice by intraperitoneal injection of EAC cells (1 ×10 6 cells/mouse). PEEAP was administered to the experimental animals at the dose levels of 250,500 and 1000 mg/kg per day after 24 hrs of tumour inoculation. The anti tumour effect of PEEAP was evaluated by assessing and body weight, survival time, haematological parameters. Oral administration of PEEAP increased the survival time of the EAC bearing mice. The PEEAP brought back the alter levels of the haematological parameters in a dose dependent manner in EAC bearing mice. The results were comparable to that of the result obtained from the animals treated with the standard drug 5-flurouracil (20mg/kg.b.w). Thus present study revealed that PEEAP possessed significant anti tumour activity. This article can be downloaded from www.ijpbs.ne

Testing capital structure theories using error correction models: Evidence from China, India, and South Africa

The objective of this study is to empirically examine the capital structure theories that can explain the capital structure choice made by the firms that are operating in China, India, and South Africa. The study tests the capital structure theories as a stand-alone basis as well as an integrated framework of nested models using advanced dynamic panel data methods with a data-set of 1,183 firms with 12,187 firm-year observations spanning the period 1999–2016. Findings suggest that the firms adjust toward target leverage very quickly and trade-off theory explains the firms’ capital structure choice better than pecking order theory in the stand-alone model as well as the model nesting these two theories. This study contributes to the empirical literature of capital structure in the following way. First, this study uses error correction framework as a general specification of the widely used partial adjustment model. Second, the study uses advanced panel data estimators to estimate partial adjustment model and error correction model. Finally, the different specifications are tested using a large data-set of firms in China, India, and South Africa that has not been done so far

Predictive Model Techniques with Energy Efficiency for IoT-Based Data Transmission in Wireless Sensor Networks

Wireless sensor networks are limited by the vast majority of goods with limited resources. Power consumption, network longevity, throughput, routing, and network security are only a few of the research issues that have not yet been addressed in sensor networks based on the Internet of Things. Prior to becoming widely deployed, sensor networks built on the Internet of Things must overcome a variety of technological obstacles as well as general and specific hazards. In order to address the aforementioned problems, this research sought to improve rogue node detection, reduce packet latency/packet loss, increase throughput, and lengthen network lifetime. Wireless energy harvesting is suggested in the proposed three-layer cluster-based wireless sensor network routing protocol to extend the energy lifespan of the network. For the purpose of recognising and blacklisting risky sensor node behaviour, a three-tier clustering architecture with an integrated security mechanism is suggested. This clustering approach is cost-based, and the sink node selects the cluster and grid heads based on the cost function’s value. With its seemingly endless potential across a wide range of industries, including intelligent transportation, the Internet of Things (IoT) has gained prominence recently. To analyse the nodes and clustering strategies in IoT, the suggested method PSO is applied. A plethora of new services, programmes, electrical devices with integrated sensors, and protocols have been produced as a result of the Internet of Things’ explosive growth in popularity

Detection and Feature Extraction of Mri and Ct Images Using Medical Images

An efficient procedure for specifically defining the tumor boundary present in an input MRI picture is proposed in this article. Various mammogram photographs were taken and examined for the comparative analysis. CA segmentation and other existing algorithms such as Otsu's thresholding and canny edge detection were used to model brain MRI images. CA segmentation is the best choice out of any of these segmentation processes. Its simplicity over a single slice and lower susceptibility to initialization, reliability in terms of computation time, robustness against diverse and heterogeneous tumor forms, computational efficiency, and ease of use are all factors. In oncologic imaging, segmentation of brain tumors on diagnostic photographs is important for cancer management and surveillance. With the advent of image driven surgical methods, it is becoming more common. Outlining the brain tumor contour, which is normally performed manually on contrast enhanced T1-weighted MRI in current clinical practice, is a critical phase in preparing spatially localized radiotherapy. Cellular Automaton-based seeded tumor segmentation is used to segment solid brain tumors in this article. It aids physicians and researchers in the preparation of radio surgery and the evaluation of treatment reaction. The findings show that the collected pictures may be used to make an accurate diagnosis.   &nbsp

Polarization Stable Triband Thin Square-Shaped Metamaterial Absorber

An efficient triband metamaterial absorber is presented for X- and K-band applications. The unit cell is of simple shape. The absorber is fabricated on a thin polyamide, which makes it flexible. The parameters of the designed absorber are optimized. The simulated results show that it has good absorption rate and polarization stability. The stability is exhibited over a wide range in both TE and TE modes of the incident waves. The measured results are on par with the simulated results. The measurement is carried out with the waveguide measurement method