Mouth tracking for hands-free robot control systems

In this paper, we propose a mouth tracking method for remote robot control systems. The main idea behind the work is to help disabled people, who cannot operate any keyboard or joystick, to control a robot without use of their hands. The mouth tracking method is mainly based on the AdaBoost feature detection approach. By adding new Haar-like features for detecting the corner of the mouth, the speed and accuracy of detection are improved. The AdaBoost feature detection combined with the Kalman filter accomplished continuous and accurate mouth tracking. Meanwhile, the gripping commands for the robot manipulator were obtained through recognition of mouth shape, such as for a pouting mouth or a grinning mouth. To assess the validity of the method, mouth detection experiments and robot cargo transport experiments were conducted. The results indicate that the proposed method can realize mouth tracking and robot operations that are quick and accurate in retrieving items successfully.     

Tunable Reverse‐Biased Graphene/Silicon Heterojunction Schottky Diode Sensor

A new chemical sensor based on reverse‐biased graphene/Si heterojunction diode has been developed that exhibits extremely high bias‐dependent molecular detection sensitivity and low operating power. The device takes advantage of graphene's atomically thin nature, which enables molecular adsorption on its surface to directly alter graphene/Si interface barrier height, thus affecting the junction current exponentially when operated in reverse bias and resulting in ultrahigh sensitivity. By operating the device in reverse bias, the work function of graphene, and hence the barrier height at the graphene/Si heterointerface, can be controlled by the bias magnitude, leading to a wide tunability of the molecular detection sensitivity. Such sensitivity control is also possible by carefully selecting the graphene/Si heterojunction Schottky barrier height. Compared to a conventional graphene amperometric sensor fabricated on the same chip, the proposed sensor demonstrated 13 times higher sensitivity for NO₂ and 3 times higher for NH₃ in ambient conditions, while consuming ～500 times less power for same magnitude of applied voltage bias. The sensing mechanism based on heterojunction Schottky barrier height change has been confirmed using capacitance‐voltage measurements.     

Moving from Resource Development to Resource Management: Problems,Prospects and Policy Recommendations for Sustainable Groundwater Management in Bangladesh

Water Resources Management - Increased groundwater accessibility resulting from the expansion of deep and shallow tube wells helped Bangladesh attain near self-sufficiency in rice, with national...     

Double gene targeting PCR assay for the detection of Crocodylus porosus in commercial products

The demand for crocodile meat is quickly growing because of its exotic and organoleptic appeal and also the low content of cholesterol and lipids. Moreover, crocodile oil and blood have been used in alternative medicines for treating asthma and several other ailments since ancient times. Furthermore, crocodile hides have great demand in leather industries. All of these have collectively contributed to the extensive hunting, illegal trading and consequent decline of crocodiles in most parts of the world. To keep space with the growing demands, some crocodile species such as Crocodylus porosus have been raised in farms and its commercial trades have been legalised. However, demand for wild crocodiles in foods and medicines has continued in high gear. Recently, several DNA-based methods have been proposed for crocodile detection, but those assays are based on single gene and longer-sized amplicon targets that break down during extensive processing. To address this gap, here we developed and validated a highly stable double gene targeted multiplex PCR assay for the identification of C. porosus materials in commercial products. The assay involved two short sites from C. porosus atp6 (77 bp) and cytb (127 bp) genes and a universal internal control (99 bp) for eukaryotes. The PCR primers were cross-tested against 18 species and validated under pure and mixed matrices under extensive boiling, autoclaving and microwave cooking conditions. Finally, it was used to identify five crocodile-based commercial products. The lower limits of detection for atp6 and cytb genes were 0.001 ng and 0.01 ng DNA, respectively, in pure meat and 1% under mixed matrices. Some inherent features, such as 77–127 bp amplicon sizes, exceptional stability and superior sensitivity, suggested the assay could be used for the identification of C. porosus in any forensic specimen.     

Characterization of β-lactamase- and efflux pump-mediated multiple antibiotic resistance in Salmonella Typhimurium

Food Science and Biotechnology - This study aimed to assess the β-lactamase- and efflux pump-mediated antibiotic resistance in Salmonella Typhimurium (WT-ST), ciprofloxacin-induced...     

Phthalates in indoor dust in Kuwait: implications for non‐dietary human exposure

Phthalates are semivolatile organic compounds with a ubiquitous environmental distribution. Their presence in indoor environments is linked to their use in a variety of consumer products such as children's toys, cosmetics, food packaging, flexible PVC flooring among others. The goal of this study was to investigate the occurrence and concentration of phthalates in dust from homes in Kuwait and to assess non‐dietary human exposure to these phthalates. Dust samples were randomly collected from 21 homes and analyzed for eight phthalates. The concentrations of total phthalates were log normally distributed and ranged from 470 to 7800 μg/g. Five phthalates [Di(2‐ethylhexyl) phthalate (DEHP), Di‐n‐octyl phthalate (DnOP), Di‐n‐butyl phthalate (DBP), Benzyl butyl phthalate (BzBP), and Dicyclohexyl phthalate (DcHP)] were routinely detected. The major phthalate compound was DEHP at a geometric mean concentration of 1704 μg/g (median, 2256 μg/g) accounting for 92% of the total phthalates measured. Using the measured concentrations and estimates of dust ingestion rates for children and adults, estimated human non‐dietary exposure based on median phthalate concentrations ranged from 938 ng/kg‐bd/day for adults to 13362 ng/kg‐bd/day for toddlers. The difference in exposure estimates between children and adults in this study supports previous reports that children are at greater risk from pollutants that accumulate indoors.     

Assessment of Fire Risk in the Readymade Garment Industry in Dhaka,Bangladesh

Readymade garments are the most important export item from Bangladesh, yet the working conditions and fire safety records in the factories are often not up to the standard. Despite a number of initiatives to curb fire accidents in the garment industry, there are still a significant number of fire occurrences in this industry. Unfortunately, there is no comprehensive statistics on the current status of fire provisions and management practices in the readymade garment factories in Bangladesh. Given the management practices (soft issues) are often as important as structural fire safety measures, yet difficult to regulate, this paper develops a fire risk index (FRI), the first of its kind in Bangladesh, for soft parameters in the garment industry. FRI for 60 random garment factories are developed through surprise inspections to understand the current status of fire risk due to inadequacies in the soft parameters. Results show that the mean FRI is 2.8 on a scale of 5.0, which indicates an alarming condition. Locked exit doors, lack of emergency announcement system and lack of fire drills are the three worst performers among the 24 investigated parameters and require immediate attention from the regulators and stakeholders. We also observed a U-shaped relationship between FRI and factory size. Factories that are members of the industry’s trade lobby generally have better fire safety practices than the non-members. Given the importance of the readymade garment sector in many developing countries, poor fire safety record and lack of information on fire safety, our approach of developing an FRI for the industry can be very useful to understand the immediate concerns and thus to curb fatalities and injuries from fire accidents in this sector.     

Nanofiltration Membrane Process for the Removal of Arsenic from Drinking Water

The removal of arsenic from drinking water by nanofiltration membranes was investigated. Experiments were conducted with tap water to which arsenate and arsenite were added. Two types of nanofiltration membranes, i.e., NF‐90 and NF‐200, have been tested. The effect of various operating conditions, e.g., applied pressure, feed concentration, pH and temperature, were also investigated. The pH and arsenic concentration in the feed and the operating temperature are found to be decisive factors in determining the arsenic concentration remaining in the permeate. The level of removal of As(V) was higher than 98 % for both membranes, but that of As(III) was much lower. It can be concluded that by controlling the operating parameters, source water containing As(V) may be recovered as drinking water to EPA maximum contaminant level quality standards, but that water containing As(III) must undergo a pre‐oxidation treatment before passing through the nanofiltration membrane in order to maintain drinking water quality.     

Investigation of combined heat and mass transfer by Lie group analysis with variable diffusivity taking into account hydrodynamic slip and thermal convective boundary conditions

The present paper investigates heat and mass transfer over a moving porous plate with hydrodynamic slip and thermal convective boundary conditions and concentration dependent diffusivity. The similarity representation of the system of partial differential equations of the problem is obtained through Lie group analysis. The resulting equations are solved numerically by Maple with Runge–Kutta–Fehlberg fourth–fifth order method. A representative set of results for the physical problem is displayed to illustrate the influence of parameters (velocity slip parameter, convective heat transfer parameter, concentration diffusivity parameter, Prandtl number and Schmidt number) on the dimensionless axial velocity, temperature and concentration field as well as the wall shear stress, the rate of heat transfer and the rate of mass transfer. The analytical solutions for velocity and temperature are obtained. Very good agreements are found between the analytical and numerical results of the present paper with published results.     

Machine Learning-based USD/PKR Exchange Rate Forecasting Using Sentiment Analysis of Twitter Data

This study proposes an approach based on machine learning to forecast currency exchange rates by applying sentiment analysis to messages on Twitter (called tweets). A dataset of the exchange rates between the United States Dollar (USD) and the Pakistani Rupee (PKR) was formed by collecting information from a forex website as well as a collection of tweets from the business community in Pakistan containing finance-related words. The dataset was collected in raw form, and was subjected to natural language processing by way of data preprocessing. Response variable labeling was then applied to the standardized dataset, where the response variables were divided into two classes: “1” indicated an increase in the exchange rate and “ −1” indicated a decrease in it. To better represent the dataset, we used linear discriminant analysis and principal component analysis to visualize the data in three-dimensional vector space. Clusters that were obtained using a sampling approach were then used for data optimization. Five machine learning classifiers—the simple logistic classifier, the random forest, bagging, naïve Bayes, and the support vector machine—were applied to the optimized dataset. The results show that the simple logistic classifier yielded the highest accuracy of 82.14% for the USD and the PKR exchange rates forecasting.