The Bivariate Transmuted Family of Distributions: Theory and Applications

The bivariate distributions are useful in simultaneous modeling of two random variables. These distributions provide a way to model models. The bivariate families of distributions are not much widely explored and in this article a new family of bivariate distributions is proposed. The new family will extend the univariate transmuted family of distributions and will be helpful in modeling complex joint phenomenon. Statistical properties of the new family of distributions are explored which include marginal and conditional distributions, conditional moments, product and ratio moments, bivariate reliability and bivariate hazard rate functions. The maximum likelihood estimation (MLE) for parameters of the family is also carried out. The proposed bivariate family of distributions is studied for the Weibull baseline distributions giving rise to bivariate transmuted Weibull (BTW) distribution. The new bivariate transmuted Weibull distribution is explored in detail. Statistical properties of the new BTW distribution are studied which include the marginal and conditional distributions, product, ratio and conditional momenst. The hazard rate function of the BTW distribution is obtained. Parameter estimation of the BTW distribution is also done. Finally, real data application of the BTW distribution is given. It is observed that the proposed BTW distribution is a suitable fit for the data used.     

High-efficiency remediation of cadmium (Cd2+) from aqueous solution using poultry manure– and farmyard manure–derived biochars

Farmyard manure (FYM-BC) and poultry manure (PM-BC) derived biochars were applied as adsorbents to remove Cd²⁺ from water. Results indicated that PM-BC was a more efficient adsorbent than FYM-BC at all experimental conditions. Maximum Cd²⁺ adsorption was observed at pH 4, temperature 318 K and contact time 1 h, regardless of biochar type. The Langmuir model predicted maximum adsorption capacity of 90.09 mg g^?1 for PM-BC. The data fitting to pseudo-second-order model proposed chemisorption of Cd²⁺ onto biochars. Thermodynamics indicated that adsorption was spontaneous and endothermic. Post-adsorption analysis provided evidences of strong chemical interactions between biochars’ functional groups and Cd²⁺ ions.     

Preparation and characterization of PPRC/EPDM thermoplastic vulcanizates: A comparative study

Thermoplastic vulcanizates (TPVs) of polypropylene random copolymer (PPRC) with ethylene–propylene diene monomer rubber (EPDM) were prepared through in situ and ex situ compatibilization techniques. Silanized silica as nanofiller was incorporated in the ex situ compatibilized TPVs. Mechanical properties were measured for different formulated TPVs with increasing loading of EPDM from 10 to 30 phr. A comparative data is generated to discuss the effect of two compatibilization techniques and addition of silica filler in the TPVs. The degradation studies were also carried out to check the stability of the blends under harsh ultraviolet environment. The in situ compatibilized TPVs provided better overall mechanical properties. Moreover, it is worth mentioning that the properties of ex situ compatiblized TPVs were enhanced by incorporation of silanized silica filler. Silanized silica filler helped in reducing the die swell significantly. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46726.     

Separation of heavy metal and protein from wastewater by sulfonated polyphenylsulfone ultrafiltration membrane process prepared by glycine betaine enriched coagulation bath

This work deals with a simple and eco-friendly approach for the development of ultrafiltration membranes for the separation of environmentally hazardous substances from the water source. Polysulfone and sulfonated polyphenylsulfone blend ultrafiltration membranes were fabricated by the non-solvent induced phase inversion technique. Prepared membranes were characterized for their morphology, hydrophilicity, porosity, filtration and antifouling properties. The blend membranes with 15 wt% of sPPSU demonstrated the best performance with water flux of 190.33 Lm^?2h^?1 and flux recovery ratio of 86.56%. The effect of aq. glycine betaine (GB) coagulation bath on the membrane property and performance was studied and compared with commonly used additives such as NaCl and NMP. The GB in coagulation bath exhibited better flux and performance with protein rejection of 66.3%, 74.0% and 91.2% for trypsin, pepsin, and bovine serum albumin, respectively, and heavy metal rejection of 75.2% and 87.6% for polymer enhanced ultrafiltration of Cd²⁺ and Pb²⁺ ions, respectively.     

Mechanical and thermal properties of hybrid carbon fibre–phenolic matrix composites containing graphene nanoplatelets and graphite powder

Carbon fibre–phenolic matrix (CF–P) composites containing graphene nanoplatelets (GNPs) were manufactured for improved mechanical and thermal properties. For comparison, micrometer-size pyrolytic graphite powder (GP) was also incorporated in CF–P composites. The loading of carbon fibres was kept constant at 60?wt-% while the quantity of GNPs was varied from 0.1?wt-% to 0.3?wt-% and GP from 1.0?wt-% to 3.0?wt-%. Only GNPs were functionalised by ultraviolet-ozone treatment to improve their dispersion in the matrix while all the composites were manufactured by hand layup method and characterised by scanning electron microscopy, impact, flexural, thermogravimetry and ablation tests. The composite containing 0.3?wt-% GNPs showed considerable improvement in ablation, flexural and impact testing as compared to CF-P composites containing GP. Finally, the ablation mechanisms of post-ablated composites were discussed in the light of available data in the literature.     

A Robust Wearable Point-of-Care CNT-Based Strain Sensor for Wirelessly Monitoring Throat-Related Illnesses

Point-of-care testing (POC) has the ability to detect chronic and infectious diseases early or at the time of occurrence and provide a state-of-the-art personalized healthcare system. Recently, wearable and flexible sensors have been employed to analyze sweat, glucose, blood, and human skin conditions. However, a flexible sensing system that allows for the real-time monitoring of throat-related illnesses, such as salivary parotid gland swelling caused by flu and mumps, is necessary. Here, for the first time, a wearable, highly flexible, and stretchable piezoresistive sensing patch based on carbon nanotubes (CNTs) is reported, which can record muscle expansion or relaxation in real-time, and thus act as a next-generation POC sensor. The patch offers an excellent gauge factor for in-plane stretching and spatial expansion with low hysteresis. The actual extent of muscle expansion is calculated and the gauge factor for applications entailing volumetric deformations is redefined. Additionally, a bluetooth-low-energy system that tracks muscle activity in real-time and transmits the output signals wirelessly to a smartphone app is utilized. Numerical calculations verify that the low stress and strain lead to excellent mechanical reliability and repeatability. Finally, a dummy muscle is inflated using a pneumatic-based actuator to demonstrate the application of the affixed wearable next-generation POC sensor.     

Design Criteria for Horseshoe and Spiral-Based Interconnects for Highly Stretchable Electronic Devices

Stretchable electronics can be used for numerous advanced applications such as soft and wearable actuators, sensors, bio-implantable devices, and surgical tools because of their ability to conform to curvilinear surfaces, including human skin. The efficacy of these devices depends on the development of stretchable geometries such as interconnection-based configurations and the associated mechanics that helps to achieve optimum configurations. This work presents the essential mechanics of silicon (Si) island-interconnection structures, which include horseshoe and spiral interconnections, without reducing the areal efficiency. In particular, this study demonstrates the range of the geometrical parameters where they have a high stretchability and cyclic life. The numerical results predict the areas that are prone to breaking followed by experimental validation. The figure-of-merit for these configurations is achieved by mapping the fracture-free zones for in-plane and out-of-plane stretching with essential implications in stretchable and wearable system design. Furthermore, this work demonstrates the mechanical response for a range of materials (i.e., copper, gold, aluminum, silver, and graphene) that experience the plastic deformations in contrast to conventionally used Si-based devices that represent the extended usage for advanced stretchable electronic devices. The detailed mechanics of these configurations provides comprehensive guidelines to manufacture wearable and stretchable electronic devices.     

Predicting the crease recovery performance and tear strength of cotton fabric treated with modified N‐methylol dihydroxyethylene urea and polyethylene softener

This study aimed at developing a model for predicting the crease recovery performance and tear strength of cotton fabric using modified N‐methylol dihydroxyethylene urea, polyethylene softener, catalyst, curing time and curing temperature as the predictor variables. A quarter factorial design was constructed and, based on the experimental results, regression models were built to predict crease recovery angle and tear strength of the treated fabric. All experimental design and statistical analysis steps were implemented, using Minitab statistical software.     

Automated Renal Cell Carcinoma Subtype Classification Using Morphological, Textural and Wavelets Based Features

We present a new image quantification and classification method for improved pathological diagnosis of human renal cell carcinoma. This method combines different feature extraction methodologies, and is designed to provide consistent clinical results even in the presence of tissue structural heterogeneities and data acquisition variations. The methodologies used for feature extraction include image morphological analysis, wavelet analysis and texture analysis, which are combined to develop a robust classification system based on a simple Bayesian classifier. We have achieved classification accuracies of about 90% with this heterogeneous dataset. The misclassified images are significantly different from the rest of images in their class and therefore cannot be attributed to weakness in the classification system.     

Correction to: Deposition of bismuth sulfide and aluminum doped bismuth sulfide thin films for photovoltaic applications

Journal of Materials Science: Materials in Electronics -