Amended hybrid multi-verse optimizer with genetic algorithm for solving task scheduling problem in cloud computing

The Journal of Supercomputing - The central cloud facilities based on virtual machines offer many benefits to reduce the scheduling costs and improve service availability and accessibility. The...     

Theoretical Investigation of Cubic BaVO<Subscript>3</Subscript> and LaVO<Subscript>3</Subscript> Perovskites via Tran–Blaha-Modified Becke–Johnson Exchange Potential Approach

The full potential linearized augmented plane wave method of density functional theory has been used to investigate the structural, electronic, magnetic and thermoelectric properties of cubic perovskites BaVO₃ and LaVO₃. The ferromagnetic ground state has been found to be stable by comparing the total energies of non-spin-polarized and spin-polarized calculations performed for optimized unit cells. For both compounds, the bond length and tolerance factor are also measured. From the band structures and density of states plots, it is found that both compounds are half-metallic. We found that the presence of V at the octahedral site of these perovskites develops exchange splitting through p-d hybridization, which results in a stable ferromagnetic state. The observed exchange splitting is further clarified from the magnetic moment, charge and spin of the anion and cations. Finally, we also presented the calculated thermoelectric properties of these materials, which show that half-metallic BaVO₃ and LaVO₃ materials are potential contenders for thermoelectric applications.     

Eco‐friendly synthesis of silver nanoparticles and its larvicidal property against fourth instar larvae of Aedes aegypti

In this study, larvicidal activity of silver nanoparticles (AgNPs) synthesised using apple extract against fourth instar larvae of Aedes aegypti was determined. As a result, the AgNPs showed moderate larvicidal effects against Ae. aegypti larvae (LC₅₀  = 15.76 ppm and LC₉₀  = 27.7 ppm). In addition, comparison of larvicidal activity performance of AgNPs at high concentration prepared using two different methods showed that Ae. aegypti larvae was fully eliminated within the duration of 2.5 h. From X‐ray diffraction, the AgNP crystallites were found to exhibit face centred cubic structure. The average size of these AgNPs as estimated by particle size distribution was in the range of 50–120 nm. The absorption maxima of the synthesised Ag showed characteristic Ag surface plasmon resonance peak. This green synthesis provides an economic, eco‐friendly and clean synthesis route to Ag.Inspec keywords: silver, nanofabrication, X‐ray diffraction, zoology, particle size, nanoparticles, biomedical materials, nanomedicineOther keywords: time 2.5 h, size 50 nm to 120 nm, silver nanoparticle, larvicidal property, instar larvae, Aedes aegypti, larvicidal effect, larvicidal activity performance, X‐ray diffraction, nanoparticle particle size distribution, absorption maxima, silver surface plasmon resonance peak     

Efficient and 1,8-diiodooctane-free ternary organic solar cells fabricated via nanoscale morphology tuning using small-molecule dye additive

The ternary strategy for incorporating multiple photon-sensitive components into a single junction has emerged as an effective method for optimizing the nanoscale morphology and improving the device performance of organic solar cells (OSCs).In this study,efficient and stable ternary OSCs were achieved by introducing the small-molecule dye (5E,5'E)-5,5'-(4',4″-(1,2-diphenylethene-1,2-diyl)bis(biphenyl-4',4-diyl))bis(methan-1-yl-1-ylidene)bis(3-ethyl-2-thioxothia zolidin-4-one) (BTPERn) into poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiopheneco-3-fluorothieno[3,4-b]thiophene-2-carboxylate] (PTB7-Th):[6,6]-phenyl C71 butyric acid methyl ester (PC71BM) blend films processed using a 1,8-diiodooctane (DIO)-free solvent.The incorporation of BTPE-Rn enhanced the short-circuit current density and fill factor of the ternary OSCs compared with those of binary OSCs.An investigation of the optical,electronic,and morphological properties of the ternary blends indicated that the third component of BTPE-Rn not only promoted the photon utilization of blends through the energy-transfer process but also improved the electron mobility of the blends owing to the fullerene-rich nanophase optimization.More importantly,this ternary strategy of utilizing a small-molecule dye to replace the photounstable DIO additive enhanced the operational stability of the OSCs.     

Interface evolution in the platelet-like SiC@C and SiC@SiO<Subscript>2</Subscript> monocrystal nanocapsules

Carbon-coated SiC@C nanocapsules (NCs) with a hexagonal platelet-like morphology were fabricated by a simple direct current (DC) arc-discharge plasma method.The SiC@C NCs were monocrystalline,120-150 nm in size,and approximately 50 nm thick.The formation of the as-prepared SiC@C NCs included nucleation of truncated octahedral SiC seeds and subsequent anisotropic growth of the seeds into hexagonal nanoplatelets in a carbon-rich atmosphere.The disordered carbon layers on the SiC@C NCs were converted into SiO2 shells of SiC@SiO2 NCs by heat treatment at 650 ℃ in air,during which the shape and inherent characteristics of the crystalline SiC core were obtained.The interface evolution from carbon to SiO2 shells endowed the SiC@SiO2 NCs with enhanced photocatalytic activity due to the hydrophilic and transparent nature of the SiO2 shell,as well as to the photosensitive SiC nanocrystals.The band gap of the nanostructured SiC core was determined to be 2.70 eV.The SiC@SiO2 NCs degraded approximately 95％ of methylene blue in 160 min under visible light irradiation.     

Low-Dimensional Halide Perovskites and Their Advanced Optoelectronic Applications

Nano-Micro Letters - A NiFe2O4/expanded graphite (NiFe2O4/EG) nanocomposite was prepared via a simple and inexpensive synthesis method. Its lithium storage properties were studied with the goal of...     

On the performance of different capability indices under normal and non-normal distributions

In this article, we have examined the performance of some useful capability indices using normal and non-normal distributions. The confidence intervals are calculated and mean coverage rates are observed for different capability indices. The effects of symmetry and kurtosis of parent distributions are examined on the mean coverage rates of different capability indices. Moreover, we have investigated the robustness (of confidence interval) using the median and percentile-based indices. We have considered the well-known distributions including normal, gamma, t, Weibull, and chi-squared. For these process scenarios, we have observed that some indices resist disturbance only in symmetry of the parent distribution, some resist the disturbance in symmetry and kurtosis of the distribution, and some indices don’t resist against either type of disturbance.     

On the Efficiency of Runs Rules Schemes for Process Monitoring

There are two main types of variations, namely, common and special causes leading to in‐control and out‐of‐control states, respectively. Control charts are popular tools used to differentiate between these two states of a process. Implementation of runs rules schemes with control charts is an attractive approach for process monitoring. This study is designed to describe the methodology of runs rules schemes and discuss their implementation for different types of control charts. We have considered memory‐less charts, namely, , S, and R charts for our study purposes. It is examined that the efficiency gain depends on the number of decision points utilized to implement a given rule. Moreover, superiority of runs rules schemes may vary for different types of location and dispersion charts. An application example using a dataset is also included in the study for practical considerations. Copyright © 2015 John Wiley & Sons, Ltd.     

Three-dimensional macroscale assembly of Pd nanoclusters

Construction of macro-materials with highly oriented microstructures and well-connected interfaces between building blocks is significant for a variety of applications. However, it is still challenging to confine the desired structures. Thus, well-defined building blocks would be crucial to address this issue. Herein, we present a facile process based on 1.8 nm Pd nanoclusters (NCs) to achieve centimeter-size assemblages with aligned honeycomb structures, where the diameter of a single tubular moiety is ～4 μm. Layered and disordered porous assemblages were also obtained by modulating the temperature in this system. The reconciled interactions between the NCs were crucial to the assemblages. As a comparison, 14 nm Pd nanoparticles formed only aggregates. This work highlights the approach of confining the size of the building blocks in order to better control the assembly process and improve the stability of the structures.

Open image in new window

     

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.