Synergistic effect of ozonated and electrolyzed water on the inactivation kinetics of Escherichia coli on goat meat

Ozonated and electrolyzed water have been reported to have bactericidal activities against most pathogenic and spoilage microorganisms associated with fresh meat and contact surfaces in meat processing facilities at room temperature. However, antimicrobial effects of these two treatments combined are not known. Therefore, the objective of this study was to evaluate the effectiveness of ozonated and electrolyzed water in combination for inactivating Escherichia coli K12 on goat meat. The combination of ozonated water and alkaline electrolyzed water resulted in higher log reductions (1.03 CFU/ml) compared to ozonated water alone (0.53 CFU/ml). Regression analysis performed using the GInaFiT tool showed that nonlinear Weibull models were more effective than log-linear models for describing the inactivation kinetics of E. coli K12 on goat meat.     

The enhancement of laminar jet cooling effectiveness at very high surface temperature by using Al2O3 nanofluid as a coolant

In the current study, as per the requirement of various metal quenching industries, high heat removal rate, low consumption rate of the coolant, and the minimum operating cost of the process have been tried to be achieved in the Leidenfrost region by using a nanofluid low mass flux laminar jet. In this regard, an indigenously designed and fabricated experimental setup was used and before experimentation, the coolant (Al₂O₃+Water) thermophysical properties variation was monitored for the mapping of the transfer characteristics during the cooling process. The thermal analysis discloses that the critical heat flux (CHF) depicts a trend with the rising nanoparticle concentration in the mixture; however, at the medium concentration (0.10% Al₂O₃) except the CHF region, in the remaining region, better heat removal rate is observed. The comparison of the current cooling methodology with that reported in literature clearly approves that the proposed process methodology mitigates the requirements described above.     

An Approach for the Microstructure-Sensitive Simulation of Shear-Induced Deformation and Recrystallization in Al–Si Alloys

Metallurgical and Materials Transactions A - Al alloys are known to experience extensive grain refinement during shear-assisted processing techniques, an effect driven by dynamic dislocation...     

LiDAR based hydro-conditioned hydrological modeling for enhancing precise conservation practice placement in agricultural watersheds

High resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Models (DEMs) improve hydrologic modeling and aid in identifying the targeted locations of best conservation practices (CPs) in agricultural watersheds. However, the inability of LiDAR data to represent the conveyance of water under or through the surfaces (i.e., bridges or culverts) impedes the simulated flow, resulting in false upstream pooling. Improper flow simulation affects the accuracy of pollutant load estimations and targeted locations delineated by watershed models or models built upon hydro-conditioned DEMs (hDEM). We propose a novel approach of Hydro-conditioning to modify LiDAR imagery through breach lines, which is essential to accurately replicate the landscape hydrologic connectivity. We compared variations in outcomes of Agricultural Conservation Planning Framework (ACPF), based on manual and automated hDEMs for Plum Creek watershed, Minnesota. The derived flow network, catchment boundaries, drainage areas, locations/number of practices depend on the chosen hDEM. Locations, size and shape of bioreactors, drainage management, farm ponds, nutrient removal wetlands, riparian buffers are severely affected by hydro-conditioning. Shuttle Radar Topography Mission (SRTM) validation of hDEMs showed that Mean Average Percentage Deviation (MAPE) for automated and manual hDEMs is 1.34 and 0.998 respectively. Also, proximity analysis with a buffer of 200 m showed that CPs’ locations delineated by manual hDEM match better with the existing ones as compared to automated hDEM. Results indicate that coupled approach of using automated and manual ‘hDEM’ is best suited for guiding stakeholders towards the field-scale planning in a cost-saving manner.

     

An improved long short-term memory networks with Takagi-Sugeno fuzzy for traffic speed prediction considering abnormal traffic situation

Traffic speed prediction is an emerging paradigm for achieving a better transportation system in smart cities and improving the heavy traffic management in the intelligent transportation system (ITS). The accurate traffic speed prediction is affected by many contextual factors such as abnormal traffic conditions, traffic incidents, lane closures due to construction or events, and traffic congestion. To overcome these problems, we propose a new method named fuzzy optimized long short-term memory (FOLSTM) neural network for long-term traffic speed prediction. FOLSTM technique is a hybrid method composed of computational intelligence (CI), machine learning (ML), and metaheuristic techniques, capable of predicting the speed for macroscopic traffic key parameters. First, the proposed hybrid unsupervised learning method, agglomerated hierarchical K-means (AHK) clustering, divides the input samples into a group of clusters. Second, based on parameters the Gaussian bell-shaped fuzzy membership function calculates the degree of membership (high, low, and medium) for each cluster using Takagi-Sugeno fuzzy rules. Finally, the whale optimization algorithm (WOA) is used in LSTM to optimize the parameters obtained by fuzzy rules and calculate the optimal weight value. FOLSTM evaluates the accurate traffic speed from the abnormal traffic data to overcome the nonlinear characteristics. Experimental results demonstrated that our proposed method outperforms the state-of-the-art approaches in terms of metrics such as mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE).     

Synthesis of iron nano-catalyst using Acalypha indica leaf extracts for biogas production from mixed liquor volatile suspended solids

A simple, rapid and eco-friendly procedure was adopted to synthesize iron nano-catalyst (FeNCs) using the leaf extracts of Acalypha indica. The effectiveness of synthesized FeNCs was evaluated for the biogas production from mixed liquor volatile suspended solids (MLVSS). The FeNCs were characterized using UV-Visible spectroscopy, Fourier Transform Infrared spectroscopy, Scanning Electron Microscope and X-Ray Diffraction. The catalytic activity of the synthesized additives of FeNCs during the anaerobic process showed a drastic reduction in the hydraulic retention time of 6days for biogas production 85–90%. This study also showed a significant increase in the total biogas production when MLVSS supplemented with 0.3 g/L FeNCs. The aforementioned additive yielded 0.345 (L/g volatile solids reduced) biogas which is relatively lesser (63%) when compared with the control 0.25 (L/g VS reduced) and their bulk salts 0.055 (L/g VS reduced).     

OFDM-Based TVWS-IEEE Standards: A Survey of PHY and Cognitive Radio Features

Cognitive radio (CR) has been recognized as future prospect for efficient and dynamic allocation of bandwidth among users of which dynamic spectrum access is an important aspect focusing on identification and opportunistic utilization of vacant spectrum in television broadcasting licensed bands, known as television white spaces (TVWS). TVWS has been selected by numerous IEEE standards spanning diverse operating zones for implementing CR technology. Specifically, we focus our attention to IEEE 802.22, IEEE 802.11af and IEEE 802.15.4m standards operating in TVWS pertaining to regional, local and personal area networks respectively. The PHY layer in each of these standards is depending on orthogonal frequency division multiplexing (OFDM) for spectrum-wise efficient communication as well as dynamic frequency allocation. Pertinent OFDM design challenges corresponding to IEEE standards in TVWS are revealed. PHY layer structure and cognitive techniques employed in cognition-aware IEEE standards in TVWS are reviewed in detail. Lastly, open research issues and implementation challenges for TVWS IEEE standards are highlighted.

     

Human Age and Gender Prediction Based on Neural Networks and Three Sigma Control Limits

A person’s face provides a lot of information such as age, gender, and identity. Faces play an important role in the estimation/prediction of the age and gender of persons, just by looking at their face. Perceiving human faces and modeling the distinctive features of human faces that contribute most toward face recognition are some of the challenges faced by computer vision and psychophysics researchers. There are many methods have been proposed in the literature for the facial features for age and gender classification. In this research, an attempt is made to classify human age and gender using feed forward propagation neural networks in coarser level. Further final classification is done using 3-sigma control limits in finer level. Proposed approach efficiently classifies three age groups including children, middle-aged adults, and old-aged adults. Similarly two gender groups classified into male and female by the proposed method.The performance of the system is further improved by employing multiple hierarchical decision using three sigma control limits applied on the output of the neural network classifier. The mean and standard deviation has been considered on the output generated from the neural network classifier, and three sigma control limits has been applied to define the range of values for the specific category of age and gender. The efficiency of the system is demonstrated through the experimental results using benchmark database images.     

Enhanced Piezoelectric,Ferroelectric, and Electrostrictive Properties of Lead-Free (1-x)BCZT-(x)BCST Electroceramics with Energy Harvesting Capability

Next-generation electronics and energy technologies can now be developed as a result of the design, discovery, and development of novel, environmental friendly lead (Pb)-free ferroelectric materials with improved characteristics and performance. However, there have only been a few reports of such complex materials’ design with multi-phase interfacial chemistry, which can facilitate enhanced properties and performance. In this context, herein, novel lead-free piezoelectric materials (1-x)Ba_0.95Ca_0.05Ti_0.95Zr_0.05O₃-(x)Ba_0.95Ca_0.05Ti_0.95Sn_0.05O₃, are reported, which are represented as (1-x)BCZT-(x)BCST, with demonstrated excellent properties and energy harvesting performance. The (1-x)BCZT-(x)BCST materials are synthesized by high-temperature solid-state ceramic reaction method by varying x in the full range (x = 0.00–1.00). In-depth exploration research is performed on the structural, dielectric, ferroelectric, and electro-mechanical properties of (1-x)BCZT-(x)BCST ceramics. The formation of perovskite structure for all ceramics without the presence of any impurity phases is confirmed by X-ray diffraction (XRD) analyses, which also reveals that the Ca²⁺, Zr⁴⁺, and Sn⁴⁺ are well dispersed within the BaTiO₃ lattice. For all (1-x)BCZT-(x)BCST ceramics, thorough investigation of phase formation and phase-stability using XRD, Rietveld refinement, Raman spectroscopy, high-resolution transmission electron microscopy (HRTEM), and temperature-dependent dielectric measurements provide conclusive evidence for the coexistence of orthorhombic + tetragonal (Amm2 + P4mm) phases at room temperature. The steady transition of Amm2 crystal symmetry to P4mm crystal symmetry with increasing x content is also demonstrated by Rietveld refinement data and related analyses. The phase transition temperatures, rhombohedral-orthorhombic (T_R-O), orthorhombic- tetragonal (T_O-T), and tetragonal-cubic (T_C), gradually shift toward lower temperature with increasing x content. For (1-x)BCZT-(x)BCST ceramics, significantly improved dielectric and ferroelectric properties are observed, including relatively high dielectric constant ε_r ≈ 1900–3300 (near room temperature), ε_r ≈ 8800–12 900 (near Curie temperature), dielectric loss, tan δ ≈ 0.01–0.02, remanent polarization P_r ≈ 9.4–14 µC cm⁻², coercive electric field E_c ≈ 2.5–3.6 kV cm⁻¹. Further, high electric field-induced strain S ≈ 0.12–0.175%, piezoelectric charge coefficient d₃₃ ≈ 296–360 pC N⁻¹, converse piezoelectric coefficient ${(d_{33}^{\ast })}_{\mathrm{ave}}$≈ 240–340 pm V⁻¹, planar electromechanical coupling coefficient k_p ≈ 0.34–0.45, and electrostrictive coefficient (Q₃₃)_avg ≈ 0.026–0.038 m⁴ C⁻² are attained. Output performance with respect to mechanical energy demonstrates that the (0.6)BCZT-(0.4)BCST composition (x = 0.4) displays better efficiency for generating electrical energy and, thus, the synthesized lead-free piezoelectric (1-x)BCZT-(x)BCST samples are suitable for energy harvesting applications. The results and analyses point to the outcome that the (1-x)BCZT-(x)BCST ceramics as a potentially strong contender within the family of Pb-free piezoelectric materials for future electronics and energy harvesting device technologies.     

Radiation-curable prepreg composites

Advanced composites, specifically carbon-fiber-reinforced epoxies, are used extensively for a variety of demanding structural applications, primarily because of their high strength-to-weight and stiffness-to-weight ratios, corrosion resistance, and damage tolerance characteristics. Electron beam (EB) treatment can be used to produce useful physical and/or chemical changes in plastics and composites by initiating various polymerization and crosslinking reactions. The advantages of using EB rather than thermal curing for carbon-fiber-reinforced epoxy composites include curing at ambient temperature, reduced curing times, and fewer volatiles. An EB-curable carbon fiber-acrylated epoxy composite is being developed for various applications. The tensile properties of the 14-ply EB-cured epoxy laminate were comparable with the properties of the thermally cured laminates used in the aircraft industry. Research is continuing to develop resin formulations and select coupling agents to improve the compression properties of EB-cured laminates.