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In this study, oxidative desulfurization (ODS) of modeled and real oil samples was investigated using manganese-dioxide-supported, magnetic-reduced graphene oxide nanocomposite (MnO2/MrGO) as a catalyst in the presence of an H2O2/HCOOH oxidation system. MnO2/MrGO composite was synthesized and characterized by scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) analyses. The optimal conditions for maximum removal of dibenzothiophene (DBT) from modeled oil samples were found to be efficient at 40 °C temperature, 60 min reaction time, 0.08 g catalyst dose/10 mL, and 2 mL of H2O2/formic acid, under which MnO2/MrGO exhibited intense desulfurization activity of up to 80%. Under the same set of conditions, the removal of only 41% DBT was observed in the presence of graphene oxide (GO) as the catalyst, which clearly indicated the advantage of MrGO in the composite catalyst. Under optimized conditions, sulfur removal in real oil samples, including diesel oil, gasoline, and kerosene, was found to be 67.8%, 59.5%, and 51.9%, respectively. The present approach is credited to cost-effectiveness, environmental benignity, and ease of preparation, envisioning great prospects for desulfurization of fuel oils on a commercial level.

Multivariate data sets are common in various application areas, such as wireless sensor networks (WSNs) and DNA analysis. A robust mechanism is required to compute their similarity indexes regardless of the environment and problem domain. This study describes the usefulness of a non-metric-based approach (i.e., longest common subsequence) in computing similarity indexes. Several non-metric-based algorithms are available in the literature, the most robust and reliable one is the dynamic programming-based technique. However, dynamic programming-based techniques are considered inefficient, particularly in the context of multivariate data sets. Furthermore, the classical approaches are not powerful enough in scenarios with multivariate data sets, sensor data or when the similarity indexes are extremely high or low. To address this issue, we propose an efficient algorithm to measure the similarity indexes of multivariate data sets using a non-metric-based methodology. The proposed algorithm performs exceptionally well on numerous multivariate data sets compared with the classical dynamic programming-based algorithms. The performance of the algorithms is evaluated on the basis of several benchmark data sets and a dynamic multivariate data set, which is obtained from a WSN deployed in the Ghulam Ishaq Khan (GIK) Institute of Engineering Sciences and Technology. Our evaluation suggests that the proposed algorithm can be approximately 39.9% more efficient than its counterparts for various data sets in terms of computational time.

The protocols in underwater acoustic wireless sensor networks (UAWSNs) that address reliability in packets forwarding usually consider the connectivity of the routing paths up to one- or two-hops. Since senor nodes are connected with one another using other nodes in their neighborhood, such protocols have compromised reliability. It is because these protocols do not guarantee the presence of neighbors beyond the selected one- or two-hops for connectivity and path establishment. This is further worsened by the harshness and unpredictability of the underwater scenario. In addition, establishment of the routing paths usually requires the nodes’ undersea geographical locations, which is infeasible because currents in water cause the nodes to move from one position to another. To overcome these challenges, this paper presents two routing schemes for UAWSNs: reliability-aware routing (RAR) and reliability-aware cooperative routing with adaptive amplification (RACAA). RAR considers complete path connectivity to advance packets to sea surface. This overcomes packets loss when connectivity is not established and forwarder nodes are not available for data routing. For all the established paths, the probability of successfully transmitting data packets is calculated. This avoids the adverse channel effects. However, sea channel is unpredictable and fluctuating and its properties may change after its computation and prior to information transmission. Therefore, cooperative routing is introduced to RAR with adaptive power control of relays, which makes the RACAA protocol. In RACAA, a relay node increases its transmit power than normal when the error in the data; it receives from the sender, is more than 50 % before transferring it further to destination. This further increases the reliability when such packets are forwarded. Unlike the conventional approach, the proposed protocols are independent of knowing the geographical locations of nodes in establishing the routes, which is computationally challenging due to nodes’ movements with ocean currents and tides. Simulation results exhibit that RAR and RACAA outperform the counterpart scheme in delivering packets to the water surface.

In wireless underwater sensor networks (WUSNs), network protocols for information routing are usually designed when a significant number of nodes are present in the network. Therefore, for sparse conditions, when a noticeable reduction in the number of nodes occurs, the performance of such protocols exhibits a degraded behavior pattern. To cope with routing issues when sparse conditions prevail, two routing algorithms for WUSNs are proposed in this paper. They are energy-aware scalable reliable and void-hole mitigation routing (ESRVR) and cooperative energy-aware scalable reliable and void-hole mitigation routing (Co-ESRVR). The ESRVR uses a number of strategies. Firstly, it uses two hop neighbors’ information to develop routing trajectories for information advancement, as one hop information cannot avoid a void-hole, a condition when a node is not able to find neighbors towards the sea surface, and more than two hop information is difficult to obtain when sparse conditions prevail. Secondly, when a void-hole still exists, the protocol uses a backward transmission mechanism to find other routing paths to deliver packets to the end target. Thirdly, the time by which a packet is held by a node prior to transmission is short for the nodes with low energy, depth and high count of neighbors. This reduces packets loss and avoids congestion of the channel. It also helps the nodes with no or few neighbors to hold the packet for a significant chunk of time until they find suitable neighbors, due to sea tides and currents, for further packets’ advancement. The Co-ESRVR further adds reliability to information advancement by adding routing in a cooperative fashion to ESRVR, which involves packets advancement to destination along two paths: directly from source and via a relayed path. This provides multiple paths for data advancement to the sea surface, so that if one path is badly affected by the harsh sea characteristics, others may not be. Unlike the counterpart protocol, the proposed algorithms are not dependent on a node’s geographical location or the distance from the sea surface, which increases their scalability and reduces the computational complexity. Performance analysis displays superior behavior patterns of the proposed algorithms over the counterpart in terms of the compared characteristics.

Groundwater supplies approximately half of the total global domestic water demand. It also complements the seasonal and annual variabilities of surface water. Monitoring of groundwater fluctuations is mandatory to envisage the composition of terrestrial water storage. This research provides an overview of traditional techniques and detailed discussion on the modern tools and methods to monitor groundwater fluctuations along with advanced applications. The groundwater monitoring can broadly be classified into three groups. The first one is characterized by the point measurement to measure the groundwater levels using classical instruments and electronic and physical investigation techniques. The second category involves the extensive use of satellite data to ensure robust and cost-effective real-time monitoring to assess the groundwater storage variations. Many satellite data are in use to find groundwater indirectly. However, GRACE satellite data supported with other satellite products, computational tools, GIS techniques, and hydro-climate models have proven the most effective for groundwater resources management. The third category is groundwater numerical modeling, which is a very useful tool to evaluate and project groundwater resources in future. Groundwater numerical modeling also depends upon the point-based groundwater monitoring, so more research to improve point-based detection methods using latest technologies is required, as these still play the baseline role. GRACE and numerical groundwater modeling are suggested to be used conjunctively to assess the groundwater resources more efficiently.

Background and Objective: Present research work was designed and conducted to verify the safe use of kajal, a popular eye cosmetic, which is widely used to beautify eyes throughout the world especially in South Asia and Middle East region. Material and Method: The toxicological studies were conducted in experimental animals for a period of 90 days to clarify misleading thoughts associated with its long term use including lead toxicity. The study was carried out in Albino rats of Wister strain and New Zealand White rabbits. Hashmi kajal dibya (net weight 4.25g), an eye cosmetic manufactured by M/s A.Q. and company international Pakistan was used as source for study. The ingredients claimed by the manufacturer are zinc oxide, wax, cinnamonum camphora, processed carbon black and clarified butter. Result: The elemental analysis resulted in presence of zinc 9.56%, lead 0.09% and total ash 41.01%, while sulfur, antimony, mercury and arsenic were not detected in the sample. The sub-chronic toxicological studies revealed that no toxicological effects were found in experimental animals. All the animals of test and control groups exhibited normal physiological activities and an increase in body weights. Lead and Zinc levels remained constant throughout the experimental period and no mortality was recorded. Furthermore, liver and kidney function tests were normal, indicating non-toxic effect of the kajal on vital organs. Conclusion: So it can be assumed that this eye cosmetic is non-toxic and can be used safely in humans. Bangladesh Journal of Medical Science Vol.18(1) 2019 p.118-123

The Internet of Things has gained substantial attention over the last few years, because of connecting daily things in a wide range of application and domains. A large number of sensors require bandwidth and network resources to give-and-take queries among a heterogeneous IoT network. Network flooding is a key questioning strategy for successful exchange of queries. However, the risk of the original flooding is prone to unwanted and redundant network queries which may lead to heavy network traffic. Redundant, unwanted, and flooded queries are major causes of inefficient utilization of resources. IoT devices consume more energy and high computational time. More queries leads to consumption of more bandwidth, cost, and miserable QoS. Current existing approaches focused primarily on how to speed up the basic routing for IoT devices. However, solutions for flooding are not being addressed. In this paper, we propose a cluster-based flooding (CBF) as an interoperable solution for network and sensor layer devices which is also capable minimizing the energy consumption, cost, network flooding, identifying, and eliminating of redundant flooding queries using query control mechanisms. The proposed CBF divides the network into different clusters, local queries for information are proactively maintained by the intralayer cluster (IALC), while the interlayer cluster (IELC) is responsible for reactively obtain the routing queries to the destinations outside the cluster. CBF is a hybrid approach, having the potential to be more efficient against traditional schemes in term of query traffic generation. However, in the absence of appropriate redundant query detection and termination techniques, the CBF may generate more control traffic compared to the standard flooding techniques. In this research work, we used Cooja simulator to evaluate the performance of the proposed CBF. According to the simulation results the proposed technique has superiority in term of traffic delay, QoS/throughput, and energy consumption, under various performance metrics compared with traditional flooding and state of the art.

Cloud computing is intensifying the necessity for searchable encryption (SE) for data protection in cloud storage. SE encrypts data to preserve its confidentiality while offering a secure search facility on the encrypted data. Typical index-based SEs in data sharing scenarios can effectively search secure keyword indexes. However, due to the smaller size of the keyword space, SEs using a public key are susceptible to a Keyword Guessing Attack (KGA) and other statistical information leakage. In this paper, for secure search in a data sharing scenario, we propose Random Searchable enCryption (RanSCrypt) that adds randomness to a transformed keyword to increase its space and aspires to make it irreversible. At the core of the mechanism, two keywords are garbled with randomness, still enabling another party to determine if the two garbled keywords (RanSCrypt’s terms REST and Trapdoor) are the same or not without knowing the actual keywords. As SE in a public key setting suffers from vulnerability to KGA, RanSCrypt transfers into a symmetric key setting with minimum overhead and without losing the features of a data sharing scenario. RanSCrypt also adulterates the search result to add perplexity and provides full control of access only to the data receiver. The receiver can cull out the erroneous results from the search result locally. Finally, we introduce a new type of attack on SE, namely, the Keyword Luring Attack (KLA), and show that RanSCrypt is safe from KLA attack due to adulteration of the result. Our security analysis proves RanSCrypt is invulnerable against KGA and leaks no information.

Smart grid (SG) vision has come to incorporate various communication technologies, which facilitate residential users to adopt different scheduling schemes in order to manage energy usage with reduced carbon emission. In this work, we have proposed a residential load management mechanism with the incorporation of energy resources (RESs) i.e., solar energy. For this purpose, a real-time electricity price (RTP), energy demand, user preferences and renewable energy parameters are taken as an inputs and genetic algorithm (GA) has been used to manage and schedule residential load with the objective of cost, user discomfort, and peak-to-average ratio (PAR) reduction. Initially, RTP is used to reduce the energy consumption cost. However, to minimize the cost along with reducing the peaks, a combined pricing model, i.e., RTP with inclining block rate (IBR) has been used which incorporates user preferences and RES to optimally schedule load demand. User comfort and cost reduction are contradictory objectives, and difficult to maximize, simultaneously. Considering this trade-off, a combined pricing scheme is modelled in such a way that users are given priority to achieve their objective as per their requirements. To validate and analyze the performance of the proposed algorithm, we first propose mathematical models of all utilized loads, and then multi-objective optimization problem has been formulated. Furthermore, analytical results regarding the objective function and the associated constraints have also been provided to validate simulation results. Simulation results demonstrate a significant reduction in the energy cost along with the achievement of both grid stability in terms of reduced peak and high comfort.

We reported the comparative studies of the optimization of solution-processable tungsten trioxide (WO3) as a hole transporting layer (HTL) in inverted organic photovoltaics (OPVs) using spin coating, slot-die coating, and spray coating technologies for scaling-up applications. To facilitate the technology’s transition into commercial manufacturing, it is necessary to explore the role of scalable technologies for low-cost and efficient device fabrication. We investigated the role of diluting WO3 with isopropanol as an HTL in inverted OPVs to solve the issue of poor wettability of the hydrophobic surface of the PBDB-T: ITIC bulk heterojunction layer. The optimal dilution ratios of WO3 with isopropanol were 1:4, 1:4 and 1:8 with spin coating, slot-die coating and spray coating techniques, respectively. We evaluated the device performance by conducting a current density–voltage (J-V) analysis, incident photon-to-current conversion efficiency (IPCE) measurements, and ultraviolet–visible (UV-Vis) absorbance spectra for various WO3 concentrations. The J-V characteristics revealed that slot-die coating resulted in the highest performance, followed by the spray coating technology. We further investigated the impact of the annealing temperature on device performance for both slot-die- and spray-coated diluted WO3. The highest device performance was achieved at an annealing temperature of 120 °C for both coating technologies. This research offers valuable insights into the scalable fabrication of inverted OPV devices, paving the way for cost-effective and efficient large-scale production.