Characterization of vanadyl phthalocyanine based surface-type capacitive humidity sensors

This study presents the fabrication and characterization of novel surface-type capacitive humidity sensors using vanadyl phthalocyanine (VOPc) as the active material. The devices, which comprise three different thicknesses,have been fabricated using the thermal evaporation technique. A thin film of VOPc is deposited on thoroughly cleaned glass substrates with pre-pattemed Ag electrodes. The capacitive effect of the samples under humidity has been in-vestigated. Comparison of the samples with different thicknesses shows that the thinnest device seems more sensitive towards humidity. The humidity dependent capacitance properties of the sensor make it beneficial for use in commercial hygrometers.     

Dye-tolerant marine Acinetobacter baumannii-mediated biodegradation of reactive red

The objective of this study was to isolate a potent dye-degrading microbe that can be used to reduce the pollution caused by industrial dyes.Reactive red 198 is an extensively used textile dye and is a major environmental pollutant in water bodies. In this study, a bacterial strain was isolated from sea sediments and identified as Acinetobacter baumannii with 16S rRNA sequencing. The isolated bacteria were immobilized in calcium alginate and decolorization studies were carried out to determine the optimum pH, temperature, dye concentration, inoculum volume,and static/agitated condition using the one factor at a time(OFAT) approach. The Box-Behnken design, a type of response surface methodology,was adopted to improve the degradation efficiency. At 37℃ using an inoculum volume of six beads, 96.20% decolorization was observed in 500 mg/L of reactive red 198 after 72 h. Dye degradation was confirmed with UV-visible spectroscopy and Fourier-transform infrared(FTIR)spectroscopy studies of the dye and degraded metabolites. Microbial toxicity studies using Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa and phytotoxicity studies using Vigna radiata proved that the toxicity of the dye was significantly reduced after degradation. We can conclude that the isolated A. baumannii strain is an efficient dye-degrading microbe that can be used to reduce the pollution caused by industrial dyes.     

BAS-ADAM: An ADAM Based Approach to Improve the Performance of Beetle Antennae Search Optimizer

In this paper, we propose enhancements to Beetle Antennae search (BAS) algorithm, called BAS-ADAM, to smoothen the convergence behavior and avoid trapping in local-minima for a highly non-convex objective function. We achieve this by adaptively adjusting the step-size in each iteration using the adaptive moment estimation (ADAM) update rule. The proposed algorithm also increases the convergence rate in a narrow valley. A key feature of the ADAM update rule is the ability to adjust the step-size for each dimension separately instead of using the same step-size. Since ADAM is traditionally used with gradient-based optimization algorithms, therefore we first propose a gradient estimation model without the need to differentiate the objective function. Resultantly, it demonstrates excellent performance and fast convergence rate in searching for the optimum of non-convex functions. The efficiency of the proposed algorithm was tested on three different benchmark problems, including the training of a high-dimensional neural network. The performance is compared with particle swarm optimizer (PSO) and the original BAS algorithm.      

Mixture equations of state: Composition dependence

This paper discusses theoretical models for the composition dependence of equations of state and compares the quality of predictions against experimental thermodynamic property data. The mean density approximation (MDA) and the van der Waals one-fluid (VDW1) model are compared with hybrid mixing rules (HMR), in which rigorous composition dependence is used for the second and third virial coefficients and the conformai solution model is used for equation-of-state density terms beyond the third virial term. It is found that when values of unity are used for all binary and three-body unlike interaction parameters, calculated densities for methane-normal heptane mixtures have average absolute deviations of 3.54% for MDA, 4.04% for VDW1, and 2.59% for HMR. When vapor-liquid equilibrium calculations were performed for the methane-normal heptane system, average absolute deviations of calculatedK values from experimental values were 16.7% for methane and 36.4% for normal heptane using HMR, whereas when conformal solution model (CSM) mixing rules were used, the results were 34.8% for methane and 66.7% for normal heptane. When the binary interaction parameter for the characterization of interaction energies is determined, it is found to be less sensitive to state conditions in the case of HMR than either MDA or VDW1. These preliminary results suggest the potential of mixture equation-of-state methods which utilize rigorous composition dependence for the lower-order virial coefficients.Paper presented at the Second U.S.-Japan Joint Seminar on Thermophysical Properties, June 23, 1988, Gaithersburg, Maryland, U.S.A.     

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.     

Preparation and thermophysical properties of nano-sized Ln2Zr2O7 (Ln?=?La, Nd, Sm, and Gd) ceramics with pyrochlore structure

Rare earth zirconates (Ln₂Zr₂O₇, Ln = La, Nd, Sm, and Gd) with pyrochlore structure were prepared by hydrothermal method with polyethylene glycol as surfactant. X-ray diffraction, thermogravimetric analysis/differential scanning calorimetry, Fourier transform infrared spectroscopy, Raman spectroscopy, and field emission scanning electron microscopy were utilized to characterize the phase structure, thermal decomposition, and morphology of the products. Qualitative analysis indicates that the as-prepared zirconates are pyrochlore-type structures. The specific surface area, lattice parameter, and average crystallite size of the as-prepared products are closely related to the ionic radius. The activation energy of crystal growth shows an increasing trend with the decrease in ionic radii. The sintering behavior of compacted body was also investigated, revealing that the sintering-resistance properties of Ln₂Zr₂O₇ are descending as the order of La₂Zr₂O₇, Nd₂Zr₂O₇, Sm₂Zr₂O₇, and Gd₂Zr₂O₇.     

Nanomembrane‐Based,Thermal‐Transport Biosensor for Living Cells

Knowledge of materials' thermal‐transport properties, conductivity and diffusivity, is crucial for several applications within areas of biology, material science and engineering. Specifically, a microsized, flexible, biologically integrated thermal transport sensor is beneficial to a plethora of applications, ranging across plants physiological ecology and thermal imaging and treatment of cancerous cells, to thermal dissipation in flexible semiconductors and thermoelectrics. Living cells pose extra challenges, due to their small volumes and irregular curvilinear shapes. Here a novel approach of simultaneously measuring thermal conductivity and diffusivity of different materials and its applicability to single cells is demonstrated. This technique is based on increasing phonon‐boundary‐scattering rate in nanomembranes, having extremely low flexural rigidities, to induce a considerable spectral dependence of the bandgap‐emission over excitation‐laser intensity. It is demonstrated that once in contact with organic or inorganic materials, the nanomembranes' emission spectrally shift based on the material's thermal diffusivity and conductivity. This NM‐based technique is further applied to differentiate between different types and subtypes of cancer cells, based on their thermal‐transport properties. It is anticipated that this novel technique to enable an efficient single‐cell thermal targeting, allow better modeling of cellular thermal distribution and enable novel diagnostic techniques based on variations of single‐cell thermal‐transport properties.     

Evaluation of an ultrasonic acid digestion procedure for total heavy metals determination in environmental and biological samples

In this study, a sample preparation method based on ultrasonic assisted acid digestion (UAD) has been evaluated for total heavy metals (Cd, Cr, Ni and Pb) determination in different environmental (soil, sediment and sewage sludge), and biological (fish muscles, vegetables and grains) samples, using electrothermal atomic absorption spectrometry (ETAAS). The investigated parameters influencing UAD such as presonication time, sonication time, temperature of ultrasonic bath, and different acid mixtures were fully optimized, whereas power was maintained constant at 100% of nominal power of ultrasonic bath. Six different sets of above parameters were applied on six certified reference materials (CRMs) having different matrices. The accuracy of the method was also tested by comparing the results with those obtained from conventional hot plate assisted acid digestion method on same CRMs. Analytical results for HMs by both methods showed no significant difference at 95% confidence limit (p<0.05). Recoveries of HMs ranging from 96.2% to 102% and 96.3% to 98.6% were obtained from biological and environmental samples, respectively. The average relative standard deviation of UAD method varied between 3.5% and 8.2%, depending on the analyte.     

Effect of V doping concentration on the electronic structure,optical and photocatalytic properties of nano-sized V-doped anatase TiO2

V-doped TiO₂ with V/Ti ratio of 1–5% has been synthesized by hydrothermal method and then characterized by XRD, TEM, BET specific surface area, XPS and UV–vis. absorption spectra. The photocatalytic activity of the as-synthesized samples was investigated by the degradation of methylene blue in aqueous solution under visible light irradiation. Density functional theory (DFT) based calculations were performed to investigate the mechanism of band gap narrowing, the shift of light absorption edge, the location of V in the TiO₂ lattice and the variation in electronic and optical properties of TiO₂ with the increase of V doping concentration. Irrespective of the V doping concentration, TEM images indicate that all the doped samples were composed of equiaxed spherical anatase TiO₂ particles with good crystallinity and uniform particle size distribution. Both the experimental results from XPS survey and the theoretical calculation argue that the doped V replaces the lattice Ti and form substitutional impurity. The visible light absorption can be optimized by adjusting the V doping concentration. Among the doped samples with different V doping concentrations, the sample with V/Ti ratio of 2% depicts better visible light photocatalytic activity due to the enhanced visible light absorption and improved separation of electron–hole pairs.     

An overview of smart packaging technologies for monitoring safety and quality of meat and meat products

The food packaging sector has experienced much development since its inception. In the past few decades, innovations in packaging sector have led to the development of smart packaging (SP) systems that carve a niche in a highly competitive food industry. SP systems have great potential for improving the shelf‐life, and safety of food products apart from their basic roles of protecting the products against unwanted biological, chemical, and physical damage and keeping them clean. Indicators and sensors, SP components, are used for real‐time monitoring of meat quality and subsequently inform the retailers and consumers about the freshness, microbiological, temperature, and shelf life status of the products. Barcodes and radio‐frequency identification tags are employed in meat packaging for real‐time information about the authenticity, and traceability of the products in the supply chain. Recently, innovations in SP technologies resulted in fast, sensitive, and effective detection, sensing, and record keeping of freshness, microbiological, and shelf life status of meat and meat products. The SP system shows promise for extensive utilization in the meat industry in response to the consumer appreciation for safe, and quality meat products, as well as their waste reduction notions. This paper gives an updated overview of ongoing scientific research, and recent technological advances that offer the perspectives of developing smart meat packaging systems that are capable of monitoring the physical, microbial, and chemical changes of the package contents from producer to the point of sale and even beyond, and remediating potential adverse reactions.