Adsorptive removal of crystal violet from aqueous solution by ultrasonic-assisted synthesized zirconium-2,6-naphthalenedicarboxylate metal-organic framework.

Zirconium-2,6-naphthalenedicarboxylate metal-organic framework (Zr-NDC MOF) was prepared using ultrasound-assisted synthesis and tested for the adsorptive removal of crystal violet (CV) dye from aqueous solution. The pristine Zr-NDC was characterized using powder X-ray diffraction, scanning electron microscopy, thermogravimetric analysis, and energy-dispersive X-ray spectroscopy, Fourier-transform infrared, elemental analysis, and dynamic light scattering techniques. The maximum percentage removal of CV dye was found to be 99.

Airborne Hyperspectral Imagery for Band Selection Using Moth-Flame Metaheuristic Optimization.

In this research, we study a new metaheuristic algorithm called Moth-Flame Optimization (MFO) for hyperspectral band selection. With the hundreds of highly correlated narrow spectral bands, the number of training samples required to train a statistical classifier is high. Thus, the problem is to select a subset of bands without compromising the classification accuracy.

Elder emotion classification through multimodal fusion of intermediate layers and cross-modal transfer learning.

The objective of the work is to develop an automated emotion recognition system specifically targeted to elderly people. A multi-modal system is developed which has integrated information from audio and video modalities. The database selected for experiments is ElderReact, which contains 1323 video clips of 3 to 8 s duration of people above the age of 50.

Histogram of States Based Assistive System for Speech Impairment Due to Neurological Disorders.

Assistive speech technology is a challenging task because of the impaired nature of dysarthric speech, such as breathy voice, strained speech, distorted vowels, and consonants. Learning compact and discriminative embeddings for dysarthric speech utterances is essential for impaired speech recognition. We propose a Histogram of States (HoS)-based approach that uses Deep Neural Network-Hidden Markov Model (DNN-HMM) to learn word lattice-based compact and discriminative embeddings.

Age-related changes in serum levels of insulin-like growth factor-II and its binding proteins correlate with calcaneal bone mineral density among post-menopausal South-Indian women.

Background: Insulin-like growth factor (IGF) system components are important regulators of bone metabolism, which have a predominant role in determining bone mineral density (BMD). While the serum levels of IGF-I are regulated by various systemic hormones and growth factors, IGF-II levels reflect the skeletal production relative to physical activity, mechanical loading, aging, race etc. Though various studies have been carried out among women of different ethnic groups to understand the relationship between serum levels of IGF-II and BMD, the results seem to be quite inconclusive.