Preparation and electrochemical characterization of carbon dots/polyaniline composite materials

Polymer Bulletin - Conductive polymers have emerged as a kind of promising electrode material for supercapacitor due to their unique structure, large theoretical specific capacitance, good...     

Efficient estimators for the land mobile satellite channel

A novel class of adpative Kalman channel estimators (AKCEs) for low-data-rate signalling via the land mobile satellite (LMS) channel is presented in this paper. The proposed technique is based on a scheme known as the ‘parallel processing algorithm’ and assumes a discrete Gauss–Markov extension of the LMS channel model. Three different approaches compared against the non-adaptive filter show an improved estimation error variance under various environmental conditions. Trading off computational complexity and performance, the derived maximum a posteriori (MAP) approach has been found to be best applicable. © 1998 John Wiley & Sons, Ltd.     

Mango Leaf Disease Identification Using Fully Resolution Convolutional Network

Due to the high demand for mango and being the king of all fruits, it is the need of the hour to curb its diseases to fetch high returns. Automatic leaf disease segmentation and identification are still a challenge due to variations in symptoms. Accurate segmentation of the disease is the key prerequisite for any computer-aided system to recognize the diseases, i.e., Anthracnose, apical-necrosis, etc., of a mango plant leaf. To solve this issue, we proposed a CNN based Fully-convolutional-network (FrCNnet) model for the segmentation of the diseased part of the mango leaf. The proposed FrCNnet directly learns the features of each pixel of the input data after applying some preprocessing techniques. We evaluated the proposed FrCNnet on the real-time dataset provided by the mango research institute, Multan, Pakistan. To evaluate the proposed model results, we compared the segmentation performance with the available state-of-the-art models, i.e., Vgg16, Vgg-19, and Unet. Furthermore, the proposed model's segmentation accuracy is 99.2% with a false negative rate (FNR) of 0.8%, which is much higher than the other models. We have concluded that by using a FrCNnet, the input image could learn better features that are more prominent and much specific, resulting in an improved and better segmentation performance and diseases’ identification. Accordingly, an automated approach helps pathologists and mango growers detect and identify those diseases.     

Re-refining of used lubricant oil by solvent extraction using central composite design method

The primary aim of this study was to recover base oil from used oil using solvent extraction followed by the adsorption method. Many effective variables were examined within the solvent extraction method, including using different solvents, solvent/used oil, temperature and speed of blending. Central composite design (CCD) was applied as the statistical method. Response surface methodology was then used to find the optimum conditions in the process of extraction: ratio of solvent/used oil 2.4 and 3.12 vol/vol, temperature=54 and 18 °C, and speed of mixing=569 and 739 rpm for 1-butanol and methyl ethyl ketone (MEK), respectively. Various flocculation agents were used with the solvent, such as Sodium hydroxide (NaOH), Potassium hydroxide (KOH) and Monoethylamine (MEA); they provided an increase in the separation efficiency. The best result was obtained when using 2 grams of MEA/kg solvent; this amount of MEA increases sludge removal from 12.6% to 14.7%. In the process of clay adsorption, the variables that were tested included the ratio of clay/extract oil, temperature and time of contact. The best conditions in the process of adsorption by activated bentonite were a ratio of clay/extract oil=15 wt/vol%, temperature=120 °C, and time of contact=150 minutes. The recovered base oil was analyzed by Fourier transform infrared spectroscopy (FTIR) and compared to Iraqi specifications of base oils. The recovered base oil specifications were analyzed, including, viscosity @100 °C 8.32, 9.22 cSt, pour point ?17.35, ?22.23 °C, flash point 210.12, 223.04 °C, total acid number (TAN) 0.25, nill, total base number (TBN) nill, nill, ash 0.031, 0.0019 wt% and color 3.0, 2.5 for two types of base oil recovered using MEK, 1-butanol with activated bentonite, respectively.     

The impact of identifier style on effort and comprehension

A family of studies investigating the impact of program identifier style on human comprehension is presented. Two popular identifier styles are examined, namely camel case and underscore. The underlying hypothesis is that identifier style affects the speed and accuracy of comprehending source code. To investigate this hypothesis, five studies were designed and conducted. The first study, which investigates how well humans read identifiers in the two different styles, focuses on low-level readability issues. The remaining four studies build on the first to focus on the semantic implications of identifier style. The studies involve 150 participants with varied demographics from two different universities. A range of experimental methods is used in the studies including timed testing, read aloud, and eye tracking. These methods produce a broad set of measurements and appropriate statistical methods, such as regression models and Generalized Linear Mixed Models (GLMMs), are applied to analyze the results. While unexpected, the results demonstrate that the tasks of reading and comprehending source code is fundamentally different from those of reading and comprehending natural language. Furthermore, as the task becomes similar to reading prose, the results become similar to work on reading natural language text. For more “source focused” tasks, experienced software developers appear to be less affected by identifier style; however, beginners benefit from the use of camel casing with respect to accuracy and effort.     

Fe3O4 inverse spinal super paramagnetic nanoparticles

The present article reports an energy efficient method for the synthesis of superparamagnetic ferrite (Fe₃O₄) nanoparticles (10-40 nm) and their annealing effect on the morphology, size, curie temperature and magnetic behavior at 50, 300, 400 and 500 °C. The synthesized nanoparticles were characterized by various spectroscopic techniques like FT-IR and UV-visible. The crystalline structure and particle size were estimated through solid phase as well as the liquid phase using XRD, TEM and DLS techniques. Superparamagnetic behavior of nanoparticles was confirmed by VSM. The EPR study reveals that the main feature of X-Band solid state EPR spectrum has strong transition at g_eff ∼ 3.23 (2100G) and a relatively weak transition at g_eff ∼ 2.05 (3300G). The later transition further confirms the super paramagnetic nature of these nano ferrites. The activation energy and order of weight losses of nano ferrites were found to be: 39.6 KJ mol⁻¹ and 0.21 orders (600-800 °C), respectively, analyze with the help of TGA while the specific surface area (23.1 m² g⁻¹) and pore size (9 Å) were determined by Quanta chrome BET instrument.     

Structural and ferroelectric properties of hafnium substituted BiFeO3 multiferroics synthesized via auto combustion technique

A series of BiFe_1-xHf_(3/4)xO₃ ( 0%, 5%, 10%, 15% and 20%) nanoparticles were synthesized by simple auto combustion technique using citric acid as a fuel. Thermogravimetric (TGA), differential thermogravimetric (DTA), structural, magnetic, dielectric and ferroelectric analyses were investigated. Thermogravimetric analysis provides information of temperature at which phase develops (600?°C). DTA predicts ferroelectric to paraelectric transformation temperature which is found to be 822?°C. X-ray diffraction (XRD) results confirm formation of distorted rhombohedral structure for all compositions along with few traces of Bi₂₅FeO₄₀. The tolerance factor is increased from 0.845 to 0.853 due to larger ionic radius of Hf⁴⁺ substitution on Fe site. Crystallite size (D) is found in the range of 24.2–30.48?nm. Saturation magnetization (Ms) is increased to 16 times and remanent magnetization (Mr) is increased to 8 times than that of pure BiFeO₃. This increment in magnetic parameters is due to reduction of oxygen vacancies, small crystalline size (less than 62?nm), structural distortion and unbalancing condition for antiferromagnetic magnetic moments of Fe³⁺ ions. Dielectric parameters depict decrement behavior with increasing of applied field up to 3?GHz. For Fe_1-xHf_(3/4)xO₃, lower value of dielectric permittivity for all compositions is due to reduction of polarization and less growth of grains but more growth of grain boundaries because of mismatching of Hf and Fe³⁺ ions. P-E hysteresis loop changes from round shape to elliptical shape and it confirms less lossy nature of ferroelectric loops. Higher values of Ms as well as Mr but lower values of dielectric constant as well as remanent polarization for these nanoparticles make them useful for MeRAM (magnetoelectric random access memory) and high resonant applications.     

On the Surface Metrology of Bimetallic Components

A bimetallic component may perform better than its monometallic counterpart in terms of sustainability (i.e., cost, weight, and environmental impacts of primary material production). Thus, the usages of such components are likely to increase in the years to come. Three distinct segments (segments of the constituent materials and joint area) underlie a bimetallic component, necessitating a rather unique surface characterization methodology. The objective of this study is to shed some lights on the surface characterization of a bimetallic component using both conventional and non-conventional approaches. In order to get insights into the surface finish of a bimetallic component, specimens are prepared by joining bars made of commercially pure Titanium (Ti) and Aluminum (Al). The specimens are then turned under some predefined cutting conditions, and the surface profile heights across the joint area are measured by using noncontact surface metrology equipment. The surface profiles are characterized by using the conventional parameters. In addition, the complexity of the surfaces is quantified by using the information content based parameter. Moreover, to quantify the degree of uncertainty, probability/possibility distributions are induced from the profile heights. Both conventional and proposed parameters are equally important for quantifying the surface roughness of a bimetallic component.     

Evolutionary game of end-of-life vehicle recycling groups under government regulation

Clean Technologies and Environmental Policy - This paper studies the competition between the illegal recycling group and the legitimate recycling group in the recycling market of end-of-life...     

Enhanced photoelectrochemical water splitting using zinc selenide/graphitic carbon nitride type-II heterojunction interface

The objective of this research is to construct a type-II heterojunction interface for effective photoelectrochemical (PEC) water splitting for hydrogen generation. A series of ZnSe/g-C₃N₄ heterojunctions is prepared by ultrasonication procedure and tested for PEC water splitting for the first time. The successful formation of ZnSe/g-C₃N₄ is confirmed by phase, morphological and optical analysis. Linear sweep voltammetry of 0.05 ZG (0.05% ZnSe/g-C₃N₄) showed a six-fold higher photocurrent density of 500 μA than g-C₃N₄. These results are supported by the Tafel slopes and PL (photoluminescence spectroscopy) studies by showing the smallest slope and lesser electron-hole recombination for 0.05 ZG. Increased lifetime of 107 ms and a higher donor density of 3.6 × 10¹⁹ cm^?3 for 0.05 ZG is observed. The smallest semicircle for 0.05 ZG in EIS implies the least charge transfer resistance among the prepared heterojunctions. All the results comply with each other showing the successful formation of type-II heterojunction for enhanced PEC water splitting.