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A mathematical model is created to analyze the impact of Thompson and Troian slip boundaries over a contracting/expanding surface sustaining nanofluid-containing carbon nanotubes along a stagnation point flow. Both multi-wall (MWCNTs) and single-wall (SWCNTs) carbon nanotubes are taken into consideration, with water serving as the base liquid. The flow is obtained due to the stretching or contracting of the surface. The thermal radiation, activation energy, buoyancy impacts, and chemical processes called quartic autocatalysis are additionally added to the original mathematical model. The MATLAB-constructed bvp4c function involving the three-stage Lobatto IIIa formula for the numerical results of dimensionless velocity, concentration, and temperature profiles are used. By contrasting it against a published paper in this limited instance, it is determined whether the suggested mathematical model is legitimate. In this sense, a remarkable consensus is achieved. Graphical representations are used to depict the behavior of many non-dimensional flow variables, such as the slip velocity parameter, the inertia coefficient, the porosity parameter, and the solid volume fraction. Surface drag force computations are reported to examine the effects at the permeable stretching surface. It has been shown that increasing the slip velocity factor increases the fluid streaming velocity while decreasing the surface drag force. If the endothermic/exothermic coefficient increases, the local thermal transfer efficiency falls. For nanofluids, the changing viscosity factor increases axial velocity while decreasing temperature distribution. Additionally, the solid volumetric fraction improves the temperature distributions by lowering the concentration profile and speed. [ABSTRACT FROM AUTHOR]

Recently, formation flying of multiple unmanned aerial vehicles (UAVs) found numerous applications in various areas such as surveillance, industrial automation and disaster management. The accuracy and reliability for performing group tasks by multiple UAVs is highly dependent on the applied control strategy. The formation and trajectories of multiple UAVs are governed by two separate controllers, namely formation and trajectory tracking controllers respectively. In presence of environmental effects, disturbances due to wind and parametric uncertainties, the controller design process is a challenging task. This article proposes a robust adaptive formation and trajectory tacking control of multiple quad-rotor UAVs using super twisting sliding mode control method. In the proposed design, Lyapunov function-based adaptive disturbance estimators are used to compensate for the effects of external disturbances and parametric uncertainties. The stability of the proposed controllers is guaranteed using Lyapunov theorems. Two variants of the control schemes, namely fixed gain super twisting SMC (STSMC) and adaptive super twisting SMC (ASTSMC) are tested using numerical simulations performed in MATLAB/Simulink. From the results presented, it is verified that in presence of disturbances, the proposed ASTSMC controller exhibits enhanced robustness as compared to the fixed gain STSMC. [ABSTRACT FROM AUTHOR]

The discounted {0-1} knapsack problem (D{0-1}KP) is a multi-constrained optimization and an extended form of the 0-1 knapsack problem. The DKP is composed of a set of item batches where each batch has three items and the objective is to maximize profit by selecting at most one item from each batch. Therefore, the D{0-1}KP is complex and has found many applications in real economic problems and other areas where the concept of promotional discounts exists. As DKP belongs to a binary class problem, so the novel binary particle swarm optimization variant with modifications is proposed in this paper. The acceleration coefficients are important parameters of the particle swarm optimization algorithm that keep the balance between exploration and exploitation. In conventional binary particle swarm optimization (BPSO), the acceleration coefficients of each particle remain the same in iteration, whereas in the proposed variant, fitness-based acceleration coefficient binary particle swarm optimization (FACBPSO), values of acceleration coefficients are based on the fitness of each particle. This modification enforces the least fit particles to move fast and best fit accordingly, which accelerates the convergence speed and reduces the computing time. Experiments were conducted on four instances of DKP having 10 datasets of each instance and the results of FACBPSO were compared with conventional BPSO and the new exact algorithm using a greedy repair strategy. The results demonstrate that the proposed algorithm outperforms PSO-GRDKP and the new exact algorithm in solving four instances of D{0-1}KP, with improved convergence speed and feasible solution time. [ABSTRACT FROM AUTHOR]

The limited aqueous solubility of many active pharmaceutical ingredients (APIs) is responsible for their poor performance and low drug levels in blood and at target sites. Various approaches have been adopted to tackle this issue. Most recently, mesoporous silica nanoparticles (MSN) have gained attention of pharmaceutical scientists for bio-imaging, bio-sensing, gene delivery, drug solubility enhancement, and controlled and targeted drug release. Here, we have successfully incorporated the poorly water soluble antiviral drug velpatasvir (VLP) in MSN. These spherical particles were 186 nm in diameter with polydispersity index of 0.244. Blank MSN have specific surface area and pore diameter of 602.5 ± 0.7 m2/g and 5.9 nm, respectively, which reduced after successful incorporation of drug. Drug was in amorphous form in synthesized VLP-loaded silica particles (VLP-MSN) with no significant interaction with carrier. Pure VLP showed poor dissolution with progressive increment in pH of dissolution media which could limit its availability in systemic circulation after oral administration. After VLP loading in silica carriers, drug released rapidly over a wide range of pH values, i.e., 1.2 to 6.8, thus indicating an improvement in the solubility profile of VLP. These particles were biocompatible, with an LD50 of 448 µg/mL, and in-vivo pharmacokinetic results demonstrated that VLP-MSN significantly enhanced the bioavailability as compared to pure drug. The above results clearly demonstrate satisfactory in-vitro performance, biocompatibility, non-toxicity and in-vivo bioavailability enhancement with VLP-MSN. [ABSTRACT FROM AUTHOR]

Machine-type communication (MTC) is an emerging communication trend where intelligent machines are capable of communicating with each other without human intervention. Mobile cellular networks, with their wide range, high data rates, and continuously decreasing costs, offer a good infrastructure for implementing them. However, power consumption is a great issue, which has recently been addressed by 3GPP (3rd Generation Partnership Project) by defining power-saving mechanisms. In this paper, we address the problem of modeling these power-saving mechanisms. Currently existing modeling schemes do not consider the full range of states in the discontinuous reception (DRX) mechanism in LTE-A networks. We propose a semi-Markov based analytical model, which closes this gap and shows very good results in terms of predicting performance evaluation metrics, such as the power-saving factor and wake-up latency of MTC devices compared to simulation experiments. Furthermore, we offer an evaluation of the DRX parameters and their impact on power consumption of MTC devices. [ABSTRACT FROM AUTHOR]

The ever-growing Internet of Things (IoT) data traffic is one of the primary research focuses of future mobile networks. 3rd Generation Partnership Project (3GPP) standards like Long Term Evolution-Advanced (LTE-A) have been designed for broadband services. However, IoT devices are mainly based on narrowband applications. Standards like LTE-A might not provide efficient spectrum utilization when serving IoT applications. The aggregation of IoT data at an intermediate node before transmission can answer the issues of spectral efficiency. The objective of this work is to utilize the low cost 3GPP fixed, inband, layer-3 Relay Node (RN) for integrating IoT traffic into 5G network by multiplexing data packets at the RN before transmission to the Base Station (BS) in the form of large multiplexed packets. Frequency resource blocks can be shared among several devices with this method. An analytical model for this scheme, developed as an r-stage Coxian process, determines the radio resource utilization and system gain achieved. The model is validated by comparing the obtained results with simulation results. [ABSTRACT FROM AUTHOR]

Wound healing faces significant challenges in clinical settings. It often contains a series of dynamic and complex physiological healing processes. Instead of creams, ointments and solutions, alternative treatment approaches are needed. The main objective of the study was to formulate bacitracin zinc-loaded topical patches as a new therapeutic agent for potential wound healing. A free radical polymerization technique was optimized for synthesis. Polyethylene glycol-8000 (PEG-8000) was chemically cross-linked with acrylic acid in aqueous medium, using Carbopol 934 as a permeation enhancer and tween 80 as surfactant. Ammonium persulfate and N,N'-Methylenebisacrylamide (MBA) were utilized as initiator and cross-linker. FTIR, DSC, TGA, and SEM were performed, and patches were evaluated for swelling dynamics, sol-gel analysis, in vitro drug release in various media. A Franz diffusion cell was used for the permeation study. Irritation and wound healing with the drug-loaded patches were also studied. The characterization studies confirmed the formation of a cross-linked hydrogel network. The highest swelling and drug release were observed in formulations containing highest Polyethylene glycol-8000 and lowest N,N'-Methylenebisacrylamide concentrations. The pH-sensitive behavior of patches was also confirmed as more swelling, drug release and drug permeation across skin were observed at pH 7.4. Fabricated patches showed no sign of irritation or erythema as evaluated by the Draize scale. Faster wound healing was also observed with fabricated patches compared to marketed formulations. Therefore, such a polymeric network can be a promising technology for speeding up wound healing and minor skin injuries through enhanced drug deposition. [ABSTRACT FROM AUTHOR]

Rhizoctonia solani is a species complex composed of many genetically diverse anastomosis groups (AG) and their subgroups. It causes economically important diseases of soybean worldwide. However, the global genetic diversity and distribution of R. solani AG associated with soybean are unknown to date. In this study, the global genetic diversity and distribution of AG associated with soybean were investigated based on rDNA-ITS sequences deposited in GenBank and published literature. The most prevalent AG, was AG-1 (40%), followed by AG-2 (19.13%), AG-4 (11.30%), AG-7 (10.43%), AG-11 (8.70%), AG-3 (5.22%) and AG-5 (3.48%). Most of the AG were reported from the USA and Brazil. Sequence analysis of internal transcribed spacers of ribosomal DNA separated AG associated with soybean into two distinct clades. Clade I corresponded to distinct subclades containing AG-2, AG-3, AG-5, AG-7 and AG-11. Clade II corresponded to subclades of AG-1 subgroups. Furthermore, AG and/or AG subgroups were in close proximity without corresponding to their geographical origin. Moreover, AG or AG subgroups within clade or subclades shared higher percentages of sequence similarities. The principal coordinate analysis also supported the phylogenetic and genetic diversity analyses. In conclusion, AG-1, AG-2, and AG-4 were the most prevalent AG in soybean. The clade or subclades corresponded to AG or AG subgroups and did not correspond to the AG's geographical origin. The information on global genetic diversity and distribution will be helpful if novel management measures are to be developed against soybean diseases caused by R. solani. [ABSTRACT FROM AUTHOR]