A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

A Puzzle of Quantum Phase Transition on Gd-IMC by Tuning of Conduction Electron Concentration

Based on the critical unstable of both crystal and magnetic structure of Gd-intermetallic compound near the competition of two strongly independent subsystem （＂local 4f7＂ and ＂conduction electron concentration＂）, a new QPT （quantum point transition） is predicted by calculation of： （1） The band structure and density of state by density functional theory where a strong narrowing fluidity of fermions around EF with shifted to negative value ＂-0.8 eV ＂is observable in the Gd-intermetalliccompound system while in the Y-case, it is not dominated. An antiferromagnetic state on the fluidity of conduction band can be investigated; （2） The internal magnetic field due to short range exchange interaction Jij between the nearest neighbor of local magnetic moment of stable s-state of Gd （L = 0） through the mean field approximation and of Eigenvalue-Eigenfunction ~.（k） are calculated. While a strong negative value of Jy is predicted, the eigenvalue L（k） of the system shows a strong antiferromagnetic phase in the reciprocal lattice direction 〈010〉, 〈001〉 in the correlation length 3.38 ~A. Although the antiferromagnetic state at Rc 〈_ 3.38 °A is a puzzle but it is completely dominated at Rc = 9 °A after passing through the competition between ）.λmin（O） and λmin（π） in the ranger of 3.2 °A 〈 Rc 〈 9 °A. Since both of the antiferromagnetic subsystems are sensitive to the predicted KF, the effect of decreasing of conduction electron is proposed to investigate, the change of the antiferromagnetic ordering state to the competition of ferromagnetic state （in direction 〈010〉） and antiferromagnetic state （in direction 〈001 〉 and 〈 100〉） resulted to paramagnetic state in the long range Rc = 9 °A.     

Solving a bi-objective cell formation problem with stochastic production quantities by a two-phase fuzzy linear programming approach

We propose a bi-objective cell formation problem with demand of products expressed in a number of probabilistic scenarios. To deal with the uncertain demand of products, a framework of two-stage stochastic programming model is presented. The proposed model considers minimizing the sum of the miscellaneous costs (machine constant cost, expected machine variable cost, cell fixed-charge cost, and expected intercell movement cost) and expected total cell loading variation. Because of conflicting objectives, we develop a two-phase fuzzy linear programming approach for solving bi-objective cell formation problem. To show the effectiveness of the proposed approach, numerical examples are solved and the results are compared with the two existing approaches in the literature. The computational results show that the proposed fuzzy method achieves lower objective functions as well as higher satisfaction degrees.     

Dithiocarbamate as an efficient intermediate for the synthesis of 2-(alkylthio)thiazol-4(5H)-ones

An effective approach for the synthesis of 2-(alkylthio)thiazol-4(5H)-ones from alkyl dithiocarbamates and chloroacetyl chloride in the presence of NaHCO₃ has been developed. Good to excellent yields of products, simple reaction conditions and general applicability are the most important advantages of this protocol.     

Integrating a broader notion of food security and gender empowerment into the African Green Revolution

A Green Revolution for Africa is emerging after decades of neglect of Africa’s agricultural systems. To counter these years of neglect, the then United Nations Secretary-General Kofi Annan called for “a uniquely African Green Revolution”. Since then, a number of initiatives have emerged or are emerging to realize this important vision. As more money and attention galvanizes much-needed action on the African Green Revolution, a vigorous debate is required to ensure that the mission of improving food security on the world’s poorest continent is achieved in the most effective, comprehensive and inclusive manner possible. The African Green Revolution cannot be limited to increasing yields of staple crops but must be designed as a driver of sustainable development, which includes gender empowerment and nutrition elements. This paper first reviews the Asian Green Revolution’s successes and shortcomings from a nutrition and gender perspective and then outlines what the global community can do to ensure that some of the limitations of the Asian Green Revolution, specifically with regard to nutrition and gender, are not repeated.     

High yield gold nanoparticle‐based DNA isolation method for human papillomaviruses genotypes from cervical cancer tissue samples

Gold nanoparticles (AuNPs) are commonly used in biosensors of various kinds. However, its application to extract DNA from cancer tissues has not been extensively studied. The purification of DNA from cancer tissues is an important step in diagnostic and therapeutic development. Almost, all cervical cancer cases are associated with high‐risk human papillomavirus (HR‐HPV) infection. Accurate viral diagnosis has so far relied on the extraction of adequate amounts of DNA from formalin‐fixed, paraffin‐embedded (FFPE) tissue samples. Till now, no specific and sensitive DNA purification method has been introduced for the extraction of HR‐HPV from FFPE tissue. Since the commercially available purification kits are not sensitive and specific enough for HR‐HPV DNA targets, in this study, a DNA purification method was designed based on AuNPs to purify sufficient amounts of HR‐HPV DNA from cervical cancer tissue samples. AuNPs were coated with a series of oligonucleotide probes to hybridize to specific DNA sequences of HR‐HPV genotypes. Results showed that 733 out of 800 copies of type‐specific HPV DNA were recovered with complete specificity, compared to 36 copies with a standard commercial kit (Qiagen FFPE). The high yield of DNA (91.6%) is the main advantage of the AuNPs‐probe purification method.Inspec keywords: cancer, biological tissues, microorganisms, gold, DNA, lab‐on‐a‐chip, gynaecology, purification, biochemistry, molecular biophysics, nanoparticles, nanomedicine, cellular biophysicsOther keywords: specific extraction method, cervical cancer tissue samples, high‐risk human papillomavirus infection, paraffin‐embedded tissue samples, specific DNA purification method, sensitive DNA purification method, FFPE tissue, HR‐HPV DNA targets, specific DNA sequences, HR‐HPV genotypes, type‐specific HPV DNA, AuNP‐probe purification method, gold nanoparticle‐based DNA isolation method, oligonucleotide, human papillomaviruse genotypes, clinical samples, Au     

The Effect of Measurement Errors on Correlation Estimates in Spike-Interval Sequences

The serial correlogram (SCG) is used to determine the amount of dependence in spike-interval sequences. This communication demonstrates the effects of measurement errors [i.e., false alarms (FA's) and false dismissals (FD's) in spike-detection algorithms] on correlation coefficients when the sequence has a practical sample size.     

Effect of ultrasound- and pulsed electric field-assisted enzymatic treatment on the recovery and quality of sunflower oil

The aim of this study was to evaluate the effect of cavitation and electroporation on enzymolysis extraction of sunflower oil. The optimum extraction conditions during 2 h under enzyme-assisted extraction (EAE) with a maximum oil yield of ≈23.70 ± 0.11% were as follows: cellulase/pectinase ratio 2:1, enzyme concentration 2%, pH 4.5, liquid/solid ratio 6:1 ml/g, and extraction temperature 40°C. Under the optimized enzymatic conditions, the application of ultrasound- (250 W) and pulsed electric field- (1.2 kV/cm; 52.4 kJ/kg) assisted enzymatic extraction for 30 min significantly increased the oil extraction yield by 91.1% and 18.6%, respectively, as compared with EAE.     

Heterogenous Server Placement for Delay Sensitive Applications in Green Mobile Edge Computing

Wireless Personal Communications - The importance of environmental pollution has motivated the researchers to investigate the electrical power consumption of any emerging technology. Edge Computing...     

Effects of active chitosan-flaxseed mucilage-based films on the preservation of minced trout fillets: A comparison among aerobic,vacuum, and modified atmosphere packaging

The objectives of the current study were to examine physical–mechanical, structural, and morphological characteristics of chitosan-flaxseed mucilage films enriched with Ziziphora clinopodioides essential oil (ZEO; 0%, 0.25%, and 0.5%) and sesame oil (SO; 0% and 0.75%) and to provide useful information for the preservation of minced trout fillet's using antimicrobial films under aerobic, vacuum, and modified atmosphere conditions for 16 days. The films showed thickness, tensile strength, puncture force, puncture deformation, water vapor transmission rate, water vapor permeability, swelling index, and oxygen permeability values ranging 0.082–0.86 mm, 33.34–46.83 MPa, 25.69–53.08 N, 11.45–28.45 mm, 17.48–26.73 g/m² h, 8.57–12.49 × 10⁻⁴ g mm/m² h Pa, 12.45–38.43%, and 3.02–13.32 × 10⁻¹² cm³/m² s Pa, respectively. The following order of effect on the microbial spoilage population of treated samples was found in the applied packaging methods: modified atmosphere packaging > vacuum packaging > aerobic packaging. The final microbial population of treated samples was 0.35–4.91 log CFU/g lower than the controls after 16 days of refrigerated storage. At the end of the storage, the total volatile base nitrogen, peroxide value, and thiobarbituric acid reactive substances of untreated samples were 34.02–48.6 mg of N/100 g, 1.43–2.32 meq of peroxide/1000 g, and 3.33–4.24 mg of malondialdehyde/kg, respectively. The lowest corresponding values were recorded for the treated samples with ZEO 0.5% + SO 0.75% films by 14.26–17.73 mg of N/100 g, 0.48–0.86 meq of peroxide/1000 g, and 1.08–1.48 mg of malondialdehyde/kg, respectively.