An experimental study of gas void fraction in dilute alcohol solutions in annular gap bubble columns using a four-point conductivity probe

The influence of alcohol concentration on the gas void fraction in open tube and annular gap bubble columns has been investigated using a vertical column with an internal diameter of 0.102 m, containing a range of concentric inner tubes, which formed an annular gap; the inner tubes had diameter ratios from 0.25 to 0.69. Gas (air) superficial velocities in the range 0.014–0.200 m/s were investigated. Tap water and aqueous solutions of ethanol and isopropanol, with concentrations in the range 8–300 ppm by mass, were used as the working liquids. Radial profiles of the local void fraction were obtained using a four-point conductivity probe and were cross-sectionally averaged to give mean values that were within 12% of the volume-averaged gas void fractions obtained from changes in the aerated level. The presence of alcohol inhibited the coalescence between the bubbles and consequently increased the mean gas void fraction at a given gas superficial velocity in both the open tube and the annular gap bubble columns. This effect also extended the range of homogeneous bubbly flow and delayed the transition to heterogeneous flow. Moreover, isopropanol results gave slightly higher mean void fractions compared to those for ethanol at the same mass fraction, due to their increased carbon chain length. It was shown that the void fraction profiles in the annular gap bubble column were far from uniform, leading to lower mean void fractions than were obtained in an open tube for the same gas superficial velocity and liquid composition.     

A wirelessly powered low-power digital temperature sensor

A wirelessly powered temperature sensor is presented in complementary metal-oxide-semiconductor (CMOS) 180-nm process. The wireless power transfer (WPT) is performed using resonant magnetic coupling, and a diode-less AC to DC conversion is achieved through a quadrature-oscillator with native-MOS. The quadrature-signals are subsequently used to control the diode-less rectifier switches. The on-chip temperature sensor exploits the subthreshold region temperature, and the sensed temperature is converted to frequency using a ring-oscillator, which is implemented using differential cross coupled oscillator-based delay cells. The temperature sensor architecture also employs a temperature-insensitive replica circuit to minimize process dependence and enhance power-supply rejection ratio (PSRR) of the sensing process. The application-specific integrated circuit has been designed and fabricated in 180-nm CMOS process and has dimensions of 2 mm × 2 mm. The measurement results demonstrate that the WPT circuit generates a DC voltage of 1V with a power transfer efficiency of 85% for distances 2 to 8 mm with settling time of microseconds to milliseconds. The temperature sensor demonstrates a resolution of < ±0.6C with a sensitivity of 0.52 mV/C and 126.9 Hz/C along with PSRR of −63dB and Integral Non-Linraity (INL) of 5% measured across six different dies. The back-scattering communication demonstrates a −53-dB signal at a distance of 4 mm without affecting the WPT efficiency. The total power consumption of the temperature sensor along with the integrated biases is 120 nW.     

Application of a novel hydrophilic infrared-transparent membrane to the differentiation between microcolonies of Enterobacter sakazakii and Klebsiella pneumoniae

A proof-of-concept study is reported for the differentiation between microcolonies of Enterobacter sakazakii and Klebsiella pneumoniae by means of a novel sample preparation for infrared (IR) analysis. A disposable, IR-transparent, microporous (0.2-microm pores), hydrophobic, polyethylene (PE) membrane (51 microm thick) was plasma treated under an oxygen atmosphere and used to (i) filter (or print microarrays of) dilute aqueous foodborne bacterial suspensions and (ii) subsequently grow bacterial microcolonies when the treated, hydrophilic PE membrane was placed over brain heart infusion agar medium and incubated. Because this unique membrane is transparent to IR light, isolated microcolonies (200 microm) of bacterial cells grown on this PE substrate for the first time could be directly fingerprinted by IR microspectroscopy in the transmission mode. Hence, time-consuming bacterial cell transfer from culture plates to an IR sample holder for subsequent measurement by IR spectroscopy was eliminated. Multivariate analysis of the observed IR spectra for microcolonies allowed the rapid differentiation between E. sakazakii and K. pneumoniae.     

Cytotoxicity of Newly Synthesized Quinazoline–Sulfonamide Derivatives in Human Leukemia Cell Lines and Their Effect on Hematopoiesis in Zebrafish Embryos

Many quinazoline derivatives with pharmacological properties, such as anticancer activity, have been synthesized. Fourteen quinazoline derivatives bearing a substituted sulfonamide moiety (4a–n) were previously synthesized and fully characterized. These compounds exerted antiproliferative activity against cell lines derived from solid tumors. Herein, the antileukemic activities of these compounds (4a–n) against two different leukemia cell lines (Jurkat acute T cell and THP-1 acute monocytic) were investigated. Our investigation included examining their activity in vivo in a zebrafish embryo model. Remarkably, compounds 4a and 4d were the most potent in suppressing cell proliferation, with an IC₅₀ value range of 4–6.5 µM. Flow cytometry analysis indicated that both compounds halted cell progression at the G2/M phase and induced apoptosis in a dose-dependent manner. RT-PCR and Western blot analyses also showed that both compounds effectively induced apoptosis by upregulating the expression of proapoptotic factors while downregulating that of antiapoptotic factors. In vivo animal toxicity assays performed in zebrafish embryos indicated that compound 4d was more toxic than compound 4a, with compound 4d inducing multiple levels of teratogenic phenotypes in zebrafish embryos at a sublethal concentration. Moreover, both compounds perturbed the hematopoiesis process in developing zebrafish embryos. Collectively, our data suggest that compounds 4a and 4d have the potential to be used as antileukemic agents.     

Particle Swarm Optimization for Solving Sine-Gordan Equation

The term ‘optimization’ refers to the process of maximizing the beneficial attributes of a mathematical function or system while minimizing the unfavorable ones. The majority of real-world situations can be modelled as an optimization problem. The complex nature of models restricts traditional optimization techniques to obtain a global optimal solution and paves the path for global optimization methods. Particle Swarm Optimization is a potential global optimization technique that has been widely used to address problems in a variety of fields. The idea of this research is to use exponential basis functions and the particle swarm optimization technique to find a numerical solution for the Sine-Gordan equation, whose numerical solutions show the soliton form and has diverse applications. The implemented optimization technique is employed to determine the involved parameter in the basis functions, which was previously approximated as a random number in the work reported till now in the literature. The obtained results are comparable with the results obtained in the literature. The work is presented in the form of figures and tables and is found encouraging.     

IoT-Driven Optimal Lightweight RetinaNet-Based Object Detection for Visually Impaired People

Visual impairment is one of the major problems among people of all age groups across the globe. Visually Impaired Persons (VIPs) require help from others to carry out their day-to-day tasks. Since they experience several problems in their daily lives, technical intervention can help them resolve the challenges. In this background, an automatic object detection tool is the need of the hour to empower VIPs with safe navigation. The recent advances in the Internet of Things (IoT) and Deep Learning (DL) techniques make it possible. The current study proposes IoT-assisted Transient Search Optimization with a Lightweight RetinaNet-based object detection (TSOLWR-ODVIP) model to help VIPs. The primary aim of the presented TSOLWR-ODVIP technique is to identify different objects surrounding VIPs and to convey the information via audio message to them. For data acquisition, IoT devices are used in this study. Then, the Lightweight RetinaNet (LWR) model is applied to detect objects accurately. Next, the TSO algorithm is employed for fine-tuning the hyperparameters involved in the LWR model. Finally, the Long Short-Term Memory (LSTM) model is exploited for classifying objects. The performance of the proposed TSOLWR-ODVIP technique was evaluated using a set of objects, and the results were examined under distinct aspects. The comparison study outcomes confirmed that the TSOLWR-ODVIP model could effectually detect and classify the objects, enhancing the quality of life of VIPs.     

Intelligent Deep Convolutional Neural Network Based Object Detection Model for Visually Challenged People

Artificial Intelligence (AI) and Computer Vision (CV) advancements have led to many useful methodologies in recent years, particularly to help visually-challenged people. Object detection includes a variety of challenges, for example, handling multiple class images, images that get augmented when captured by a camera and so on. The test images include all these variants as well. These detection models alert them about their surroundings when they want to walk independently. This study compares four CNN-based pre-trained models: Residual Network (ResNet-50), Inception v3, Dense Convolutional Network (DenseNet-121), and SqueezeNet, predominantly used in image recognition applications. Based on the analysis performed on these test images, the study infers that Inception V3 outperformed other pre-trained models in terms of accuracy and speed. To further improve the performance of the Inception v3 model, the thermal exchange optimization (TEO) algorithm is applied to tune the hyperparameters (number of epochs, batch size, and learning rate) showing the novelty of the work. Better accuracy was achieved owing to the inclusion of an auxiliary classifier as a regularizer, hyperparameter optimizer, and factorization approach. Additionally, Inception V3 can handle images of different sizes. This makes Inception V3 the optimum model for assisting visually challenged people in real-world communication when integrated with Internet of Things (IoT)-based devices.