K-Banhatti Sombor Invariants of Certain Computer Networks

Any number that can be uniquely determined by a graph is called a graph invariant. During the last twenty years’ countless mathematical graph invariants have been characterized and utilized for correlation analysis. However, no reliable examination has been embraced to decide, how much these invariants are related with a network graph or molecular graph. In this paper, it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science, mathematics, chemistry, pharmacy, informatics and biology in context with physical and chemical structures and networks, because k-banhatti sombor invariants are freshly presented and have numerous prediction qualities for different variants of bridge graphs or networks. The study solved the topology of a bridge graph/networks of three different types with two invariants K-Banhatti Sombor Indices and its reduced form. These deduced results can be used for the modeling of computer networks like Local area network (LAN), Metropolitan area network (MAN), and Wide area network (WAN), backbone of internet and other networks/structures of computers, power generation, bio-informatics and chemical compounds synthesis.     

Perovskite Solar Cells with ZnO Electron‐Transporting Materials

Perovskite solar cells (PSCs) have developed rapidly over the past few years, and the power conversion efficiency of PSCs has exceeded 20%. Such high performance can be attributed to the unique properties of perovskite materials, such as high absorption over the visible range and long diffusion length. Due to the different diffusion lengths of holes and electrons, electron transporting materials (ETMs) used in PSCs play a critical role in PSCs performance. As an alternative to TiO₂ ETM, ZnO materials have similar physical properties to TiO₂ but with much higher electron mobility. In addition, there are many simple and facile methods to fabricate ZnO nanomaterials with low cost and energy consumption. This review focuses on recent developments in the use of ZnO ETM for PSCs. The fabrication methods of ZnO materials are briefly introduced. The influence of different ZnO ETMs on performance of PSCs is then reviewed. The limitations of ZnO ETM‐based PSCs and some solutions to these challenges are also discussed. The review provides a systematic and comprehensive understanding of the influence of different ZnO ETMs on PSCs performance and potentially motivates further development of PSCs by extending the knowledge of ZnO‐based PSCs to TiO₂‐based PSCs.     

Dynamic Stability Improvement of Decentralized Wind Farms by Effective Distribution Static Compensator

Dynamic instability of decentralized wind energy farms is a major issue to deliver continuous green energy to electricity consumers. This instability is caused by variations of voltage and frequency parameters due to intermittencies in wind power. Previously, droop control and inverter-based schemes have been proposed to regulate the voltage by balancing reactive power, while inertial control, digital mapping technique of proportional-integral-differential (PID) controller and efficiency control strategy have been developed to regulate the frequency. In this paper, voltage stability is improved by a new joint strategy of distribution static compensator (DSTATCOM) six-pulse controller based reactive power management among decentralized wind turbines and controlled charging of capacitor bank. The frequency stability is ensured by a joint coordinated utilization of capacitor bank and distributed wind power turbines dispatching through a new DSTATCOM six-pulse controller scheme. In both strategies, power grid is contributed as a backup source with less priority. These new joint strategies for voltage and frequency stabilities will enhance the stable active power delivery to end users. A system test case is developed to verify the proposed joint strategies. The test results of the proposed new schemes are proved to be effective in terms of stability improvement of voltage, frequency and active power generation.     

DS spread spectrum signal acquisition using adaptive threshold techniques

Initial synchronization (i.e. acquisition) of the spreading wave-form is a significant problem in spread spectrum system design. In this paper, adaptive threshold techniques are employed in a serial search acquisition scheme for direct sequence (DS) spread spectrum signals to improve the mean acquisition time of the system. Two approaches for adpative threshold modelling are presented, analysed and compared, namely the sample test approach and the probability-of-error approach. The results show that, using an adaptive threshold, a significant improvement may be achieved in the mean acquisition time for a certain range of interference-to-signal ratios (ISRS). The type of interference assumed is narrowband interference, from which DS spread spectrum systems suffer most, in addition to additive white Gaussian noise (AWGN). © 1998 John Wiley & Sons, Ltd.     

PI3K-AKT Pathway Modulation by Thymoquinone Limits Tumor Growth and Glycolytic Metabolism in Colorectal Cancer

Colorectal cancer (CRC) is the third leading cause of death in men and the fourth in women worldwide and is characterized by deranged cellular energetics. Thymoquinone, an active component from Nigella sativa, has been extensively studied against cancer, however, its role in affecting deregulated cancer metabolism is largely unknown. Further, the phosphoinositide 3-kinase (PI3K) pathway is one of the most activated pathways in cancer and its activation is central to most deregulated metabolic pathways for supporting the anabolic needs of growing cancer cells. Herein, we provide evidence that thymoquinone inhibits glycolytic metabolism (Warburg effect) in colorectal cancer cell lines. Further, we show that such an abrogation of deranged cell metabolism was due, at least in part, to the inhibition of the rate-limiting glycolytic enzyme, Hexokinase 2 (HK2), via modulating the PI3/AKT axis. While overexpression of HK2 showed that it is essential for fueling glycolytic metabolism as well as sustaining tumorigenicity, its pharmacologic and/or genetic inhibition led to a reduction in the observed effects. The results decipher HK2 mediated inhibitory effects of thymoquinone in modulating its glycolytic metabolism and antitumor effects. In conclusion, we provide evidence of metabolic perturbation by thymoquinone in CRC cells, highlighting its potential to be used/repurposed as an antimetabolite drug, though the latter needs further validation utilizing other suitable cell and/or preclinical animal models.     

Computational intelligence techniques for HVAC systems: A review

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO2 emissions. The drive to reduce energy use and associated greenhouse gas emissions from buildings has acted as a catalyst in the development of advanced computational methods for energy efficient design, management and control of buildings and systems. Heating, ventilation and air-conditioning (HVAC) systems are the major source of energy consumption in buildings and ideal candidates for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of computational intelligence (CI) techniques for HVAC design, control, management, optimization, and fault detection and diagnosis. This article presents a comprehensive and critical review on the theory and applications of CI techniques for prediction, optimization, control and diagnosis of HVAC systems. The analysis of trends reveals that the minimisation of energy consumption was the key optimization objective in the reviewed research, closely followed by the optimization of thermal comfort, indoor air quality and occupant preferences. Hardcoded Matlab program was the most widely used simulation tool, followed by TRNSYS, EnergyPlus, DOE-2, HVACSim+ and ESP-r. Metaheuristic algorithms were the preferred CI method for solving HVAC related problems and in particular genetic algorithms were applied in most of the studies. Despite the low number of studies focussing on multi-agent systems (MAS), as compared to the other CI techniques, interest in the technique is increasing due to their ability of dividing and conquering an HVAC optimization problem with enhanced overall performance. The paper also identifies prospective future advancements and research directions.     

Micronization of ketoprofen by the rapid expansion of supercritical solution process

The particle size of the pharmaceutical substances is important for their bioavailability (the percentage of the drug absorbed compared to its initial dosage). The absorption rate can be increased by reducing particle size of the drug particles. This study was conducted to investigate the effects of the extraction pressure (140–220 bar), extraction temperature (308–338 K), nozzle length (2–15 mm), effective nozzle diameter (450–1700 μm), and collection distance (1–10 cm) on the size and morphology of the precipitated ketoprofen particles. The characterization (size and morphology) of the particles was investigated using scanning electron microscopy (SEM). The average particle size of the original material was 115.42 μm, while the average particle size of the micronized particles is between 0.35 and 7.03 μm near to quisi-spherical, needle and irregular shape depending upon the experimental conditions.     

Morphological and Rheological Characteristics of PVP–CeO2 Blends

This work focuses on the flow behavior of the blend comprising polyvinyl pyrrolidone and cerium (IV) oxide (CeO₂) particles in submicron size, under low shear rates. The polyvinyl pyrrolidone–CeO₂ blends have been prepared and characterized by scanning electron microscopy, X-ray diffraction, and viscometry. The generation of core–shell morphology was verified from the scanning electron micrographs. Scanning electron microscopy shows that the blend formed is of porous nature. The particle size of CeO₂ increases with the concentration of both CeO₂ and polymer due to aggregation. The blend containing as high as 35?wt% of CeO₂ was found to exhibit pseudo-plastic response under low shear rate. The reasons for the observed morphology and other properties along with mechanism were explained. The main factor, which governs the properties of the end product, was van der Waals attractive forces that exist among the constituents of the system prepared.     

Multi Sensor-Based Implicit User Identification

Smartphones have ubiquitously integrated into our home and work environments, however, users normally rely on explicit but inefficient identification processes in a controlled environment. Therefore, when a device is stolen, a thief can have access to the owner’s personal information and services against the stored passwords. As a result of this potential scenario, this work proposes an automatic legitimate user identification system based on gait biometrics extracted from user walking patterns captured by smartphone sensors. A set of preprocessing schemes are applied to calibrate noisy and invalid samples and augment the gait-induced time and frequency domain features, then further optimized using a non-linear unsupervised feature selection method. The selected features create an underlying gait biometric representation able to discriminate among individuals and identify them uniquely. Different classifiers are adopted to achieve accurate legitimate user identification. Extensive experiments on a group of 16 individuals in an indoor environment show the effectiveness of the proposed solution: with 5 to 70 samples per window, KNN and bagging classifiers achieve 87–99% accuracy, 82–98% for ELM, and 81–94% for SVM. The proposed pipeline achieves a 100% true positive and 0% false-negative rate for almost all classifiers.     

Quantifying Rainfall and Flooding Impacts on Groundwater Levels in Irrigation Areas: GIS Approach

Landscapes continuously irrigated without proper drainage for a long period of time frequently experience a rise in water-table levels. Waterlogging and salinization of irrigated areas are immediate impacts of this situation in arid areas, especially when groundwater salinity is high. Flooding and heavy rainfall further recharge groundwater and accelerate these impacts. An understanding of regional groundwater dynamics is required to implement land and water management strategies. The purpose of this study is to quantify the impact of flood and rain events on spatial scales using a geographic information system (GIS). This paper presents a case study of shallow water-table levels and salinity problems in the Wakool irrigation district located in the Murray irrigation area with groundwater average electrical conductivity greater than 25,000?μS/cm. This area has experienced several large flood events during the past several decades. Piezometric data are interpolated to generate a water-table surface for each event by applying the Kriging method of spatial interpolation using the linear variogram model. Spatial and temporal analysis of major flood events over the last four decades is conducted using calculated water-table surfaces to quantify the change in groundwater storage and shallow water-table levels. The drainage impact of a subsurface drainage scheme partially covering the area has also been quantified in this paper. The results show that flooding and local rainfall have a significant impact on shallow groundwater. The study also found that postflood climatic conditions (evaporation and rainfall) play a significant role in the groundwater dynamics of the area. The spatial net average groundwater recharge during the flooding events ranges from 0.19 to 0.52?ML/ha. The GIS-based techniques described in this paper can be used for net recharge estimation in semiarid regions where it is important to quantify net recharge impacts of regional flooding and local rainfall. The spatial visualization of the net recharge in a GIS environment can help prioritize management actions by local communities.