DFNS/PEI/Cu Nanocatalyst for Reduction of Nitro-aromatic Compounds

Catalysis Letters - Nitro-aromatic pollution in industrial waste streams threat wellbeing of water resources. This study investigates the performance of a copper-based nano catalyst to reduce...     

Mathematical formulation and heuristic algorithms for optimisation of auto-part milk-run logistics network considering forward and reverse flow of pallets

The operational planning of distribution network for automotive industry is complex with many conditions to consider, including heterogeneous fleet, enforcing the feasibility of 3D-packing of pallets into vehicles to address the vehicle's capacity in terms of weight and volume, compatibility of orders in a vehicle, returning empty pallets from assembly-plants backwards to suppliers, and delivery time windows. A mathematical model (MILP) is proposed that takes account of these conditions to minimise total transportation costs. The network structure can be a combination of direct shipment and milk-run for both forward and reverse flow of pallets. The model is solved optimally for small-size problems. For solving larger problems, a heuristic algorithm (in two versions) is proposed that uses a similarity measure to generate a reasonable list of orders. Best/first-fit strategies are employed to generate a feasible solution with the aid of a relaxed version of the proposed MILP. Improvement heuristics are also designed. Unlike most of existing constructive heuristics, our aim for developing the heuristic approach is to force routing decision, with all of its considerations, being made optimal. We also use the proposed best-fit strategy in the body of grouping evolution strategy (GES) algorithm to attain an effective meta-heuristic approach. The effectiveness of heuristics is tested on generated instances which demonstrates they are optimal for small-size problems. They are also tested on the data of daily auto-parts shipments gathered from the largest Iranian automobile company. Results demonstrate there exists a significant potential for cost saving through milk-run strategy compared with the direct shipping strategy.     

Calibration of low-pressure MEMS gas sensor for detection of hydrogen gas

Detection of hydrogen by sensors are significant for improvement and safe usage of hydrogen gas as an energy source. In this paper, the application of the MEMS gas sensor for detection of hydrogen gas is numerically studied to develop the application of this device in different industrial applications. The flow feature and force generation mechanism inside a rectangular enclosure with heat and cold arms as the non-isothermal walls are inclusively discussed. In this study, the pressure of hydrogen is varied from 62 to 1500 pa correspond to Knudsen number from 0.1 to 4.5 to investigate all characteristics of the thermal-driven force inside the MEMS sensor. In order to simulate a rarefied gas inside the micro gas detector, Boltzmann equations are applied to obtain high precision results. To solve these equations, Direct Simulation Monte Carlo (DSMC) approach is used as a robust method for the non-equilibrium flow field. The effects of length, thickness and temperature of arms are comprehensively investigated in different ambient pressures. In addition, the effect of various hydrogen concentrations on the Knudsen force is studied. Our findings show that maximum Knudsen force occurs at P = 387 pressure and intensifies when the length of the arms is increased from 50 μm to 150 μm. In addition, the obtained results demonstrate that the generated force is highly sensitive to hydrogen gas species and this enables device for detection of hydrogen gas.     

Energy‐efficient void avoidance geographic routing protocol for underwater sensor networks

Underwater wireless sensor networks (UWSNs) consist of a group of sensors that send the information to the sonobuoys at the surface level. Void area, however, is one of the challenges faced by UWSNs. When a sensor falls in a void area of communication, it causes problems such as high latency, power consumption, or packet loss. In this paper, an energy‐efficient void avoidance geographic routing protocol (EVAGR) has been proposed to handle the void area with low amount of energy consumption. In this protocol, a suitable set of forwarding nodes is selected using a weight function, and the data packets are forwarded to the nodes inside the set. The weight function includes the consumed energy and the depth of the candidate neighboring nodes, and candidate neighboring node selection is based on the packet advancement of the neighboring nodes toward the sonobuoys. Extensive simulation experiments were performed to evaluate the efficiency of the proposed protocol. Simulation results revealed that the proposed protocol can effectively achieve better performance in terms of energy consumption, packet drop, and routing overhead compared with the similar routing protocol.     

Assessing a Multivariate Approach Based on Scalogram Analysis for Agricultural Drought Monitoring

Due to the complexity of agricultural drought, univariate indices may not be suitable for assessing its impacts comprehensively. The main objective of this study was to develop a new multivariate drought index using the Scalogram concepts, in which the input data weights and their cluster separation were performed based on the entropy theory and fuzzy k-means algorithm, respectively. The newly developed index, named as SCI index, integrates the four weighted individual quantitative indicators such as the difference between precipitation and potential evapotranspiration (D_i), the moisture departure (d_i), the Soil Moisture index (SMI), and the Vegetation Condition Index (VCI) to quantify agricultural drought in monthly and annual timescales in the various climate conditions of Golestan province, Iran. Next, the Composite Drought Index (CDI) was calculated for the selected stations by the same variables in the SCI index as an input. According to the results a good agreement and a high behavioral similarity for the identifying moisture conditions was found between SCI index and CDI index and even other well-known drought indices such as SPEI and SPDI. But the intensity with extremes of wet and dry conditions in the CDI significantly were more than the SCI index and other ones. Comparing results obtained by the Standardized Yield Index (SYI) for rainfed wheat with the SCI index showed that at most stations when a severe drought as happened in 2000–2001 and 2007–2008, severe crops losses also occurred. The flexible structure of SCI index provides a comprehensive approach to quantify agricultural drought and can be adapted to characterize other types of drought on a practical basis.     

A robust scheduling for the multi-mode project scheduling problem with a given deadline under uncertainty of activity duration

The problem of this paper deals with the multi-mode project scheduling problem under uncertainty of activity duration where only the renewable resources are taken into account and a given deadline has to be met at the cost of recruiting additional resources. A heuristic algorithm is employed to solve this problem, and to maintain the robustness of the baseline schedule, the concept of critical chain project management (CCPM) is applied in which a new definition to resource buffer is considered. A simulation methodology is used to determine the size and location of resource buffers in the schedules in which three different buffer sizes and three different uncertainty levels are considered. Results and analysis of the simulation outcomes illustrate that resource buffers are useful and should be simulated by the CCPM schedules, as they help to decrease the total duration of the project during implementation and meet the deadline of the project with more assurance.     

Optical and photocatalytic properties of the Fe-doped TiO2 nanoparticles loaded on the activated carbon

In this work, Fe-doped (1?wt%) TiO₂ loaded on the activated carbon nano-composite was prepared using a sol-gel method. A prepared nano-composite was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), BET surface area, Fourier transform infrared spectroscopy (FTIR), photoluminescence (PL) spectroscopy and UV–Vis diffuse reflectance spectroscopy (DRS). The photocatalytic activity of the nano-composite was evaluated through degradation of synthetic textile wastewater, reactive red 198, under visible light irradiations. The XRD result indicated that the TiO₂ nano-composite contained only anatase phase. The surface area of the TiO₂ increased from 48?m²/g to 100?m²/g through the fabrication of the nano-composite. The FE-SEM results indicate that the TiO₂ particles with an average particle size of 35–70?nm can be deposited homogeneously on the activated carbon surface. DRS showed that the Fe doping in the TiO₂ -activated carbon nano-composite induced a significant red shift of the absorption edge and then the band gap energy decreased from 3.3 to 2.9?eV. Photocatalytic results indicated that the photocatalytic activity of the Fe doped TiO₂ increased under visible light irradiation in the presence of the activated carbon.     

Green synthesis of ZnO and ZnO/CuO nanocomposites in <Emphasis Type="Italic">Mentha longifolia</Emphasis> leaf extract: characterization and their application as anti-bacterial agents

In this work, we fabricated ZnO and ZnO/CuO nanocomposites using Mentha longifolia leaf extract as a natural, non-toxic, and efficient stabilizer. Anti-bacterial activities of the prepared samples against two pathogenic bacteria, Escherichia coli (Gram-negative), and Staphylococcus aureus (Gram-positive) were investigated. The properties of the as-prepared samples were characterized by XRD, EDX, SEM, TEM, TGA, FT-IR, UV–Vis DRS, and BET instruments. The XRD analysis indicated that the size of crystallites was decreased for the ZnO powder prepared in the presence of the leaf extract. The SEM images showed that the samples consist of spherical shaped well-distributed particles. In addition, the presence of biomolecules from the leaf extract was revealed by EDX, TGA, FT-IR, and UV–Vis DRS analyses, which are important in biosynthesis process. The highest anti-bacterial activity belonged to the ZnO/CuO (10%) nanocomposite and the other compounds, including ZnO/CuO (5%), ZnO (ext), and ZnO (W) were in the next ranks, respectively. It was observed that the viability percentages against E. coli (10.16?±?2.2) is higher than that of S. aureus (17.1?±?0.87) in the presence of the ZnO/CuO (10%) nanocomposite. Ultimately, the mechanism for the action of the ZnO/CuO (10%) nanocomposite was explored through the SEM images, which involved the disruption of the bacterial membranes.     

Highly Conductive Ti3C2Tx MXene Hybrid Fibers for Flexible and Elastic Fiber‐Shaped Supercapacitors

Fiber‐shaped supercapacitors (FSCs) are promising energy storage solutions for powering miniaturized or wearable electronics. However, the scalable fabrication of fiber electrodes with high electrical conductivity and excellent energy storage performance for use in FSCs remains a challenge. Here, an easily scalable one‐step wet‐spinning approach is reported to fabricate highly conductive fibers using hybrid formulations of Ti₃C₂T_x MXene nanosheets and poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate. This approach produces fibers with a record conductivity of ≈1489 S cm^?1, which is about five times higher than other reported Ti₃C₂T_x MXene‐based fibers (up to ≈290 S cm^?1). The hybrid fiber at ≈70 wt% MXene shows a high volumetric capacitance (≈614.5 F cm^?3 at 5 mV s^?1) and an excellent rate performance (≈375.2 F cm^?3 at 1000 mV s^?1). When assembled into a free‐standing FSC, the energy and power densities of the device reach ≈7.13 Wh cm^?3 and ≈8249 mW cm^?3, respectively. The excellent strength and flexibility of the hybrid fibers allow them to be wrapped on a silicone elastomer fiber to achieve an elastic FSC with 96% capacitance retention when cyclically stretched to 100% strain. This work demonstrates the potential of MXene‐based fiber electrodes and their scalable production for fiber‐based energy storage applications.     

Incremental one-class classifier based on convex–concave hull

Pattern Analysis and Applications - One subject that has been considered less is a binary classification on data streams with concept drifting in which only information of one class (target class)...