Optimising the production of energy from coblended food waste and biosolids using batch reactor studies

Energy production from a coblended mixture of biosolids and food waste was optimised for hydrogen and methane production. Four different blends were prepared by varying the carbohydrate : protein (carb : pro) ratios. The biosolids contained a low carbohydrate fraction and so was not suitable for hydrogen production when used alone. However coblending this waste with a carbohydrate‐enriched food waste produced a greater hydrogen yield, making this option viable. Batch studies showed that the optimised mix had a biosolids concentration of 25.7% (w/w). The largest hydrogen yield of 198.5 mL/gVS_removed was observed when the carb : pro was 2.78, and this was threefold higher than the other carb : pro ratios evaluated in this study. The digestate recovered after hydrogen recovery had a C : N of 17.5, which is in the ideal range for methane production. The biochemical methane potential test showed a methane yield of 239 mL/gVS_removed, and the total volatile solids destruction following two‐phase hydrogen and methane production was 93%.     

Genetic programming based formulation of rotation capacity of wide flange beams

This study is a pioneer work that proposes genetic programming (GP) as a new approach for the explicit formulation of available rotation capacity of wide-flange beams which is an important phenomenon that determines the plastic behaviour of steel structures. The database for the GP formulation is based on extensive experimental results from literature. The results of the GP-based formulation are compared with numerical results obtained by a specialized computer program and existing analytical equations. The results indicate that the proposed GP formulation performs quite well compared to numerical results and existing analytical equations and is quite practical for use.     

Kallikrein gene expression in human pituitary tissues

Somatostatin has been suggested to influence the somatotrophic axis outside the central nervous system, in reducing GH-induced IGF-I mRNA and IGF-I generation. This study aimed to determine whether such effects were mediated via the GH receptor (GHR). GH-deficient dwarf rats aged 45-47 days (n = 8 per group) received twice daily subcutaneous injections of octreotide (1 mg/kg) (group O), saline (group S), octreotide (1 mg/kg) plus bovine GH (0.25 mg/kg) (group OG), or bovine GH (0.25 mg/kg) plus saline (group G) for 10 days. Octreotide-treated animals had less weight gain compared with saline-treated animals, but not when GH cotreated (group OG vs G). Octreotide had an overall effect on decreasing length gain (P < 0.01). Serum IGF-I (ng/ml) was reduced by octreotide (group O 171 +/- 11, group S 239 +/- 20, P < 0.01; group OG 283 +/- 30, group G 362 +/- 10, P < 0.001), as was serum insulin (P < 0.001). A significant decrease in hepatic and muscle IGF-I mRNA expression was found as expected, yet this was not associated with decreased hepatic GHR expression. Rather, an increase in hepatic 125I-bovine GH specific binding was observed (P < 0.001) and, in GH-cotreated animals (OG), hepatic GHR and GH binding protein (GHBP) mRNA expression were also increased by octreotide by approximately 40%. In muscle, octreotide was associated with an approximately 30% decrease in GHBP mRNA and no effect on GHR mRNA. This study suggests that the suppressive effects of octreotide on IGF-I metabolism, at least in liver, are not mediated via down-regulation of GHR expression, but more likely by direct effects on IGF-I expression.     

Comparison of Bougainvillea spectabilis and Bougainvillea glabra species inhibited in Pakistan based on microscopic studies: Light microscope and scanning electron microscope

The anatomical variations of two plants from the Nyctaginaceae family, Bougainvillea spectabilis and Bougainvillea glabra, were studied using light and scanning electron microscopy methods in this work. Bougainvillea is a dicotyledonous with defensive traits that can withstand extreme (hot and dry) settings; according to the findings, crystal inclusions in cells, woody spines, and an abnormal development pattern are all features that help them survive against predators and are unique to this species. The Bougainvillea plant's leaves are arranged in simple pattern, alternate to each other along stem having an undulate leaves edge and an oval form. The xylem and phloem, palisade, parenchyma midrib, spongy mesophyll, raphide crystal bundles, and trichomes were all visible when bracts and leaves were transversally sectioned and dyed with toluidine blue O (TBO). The presence of crystals was confirmed by a detailed examination of the transverse leaves by using bright-field and cross-polarizing microscopy. Dissecting microscopic examination showed that all the leaves revealed leaves venation pattern that had midvein, lateral veins areoles, and trichomes. Although trichomes have been identified on both sides, a closer look at a cleaned leaf dyed with TBO showed multicellular abundant trichomes on adaxial surface. Stomata complexes were typically found on the abaxial surface of the leaf according to epidermal peels. Present studies also showed that on adaxial side, stomata were lesser in number or were absent and also showed that the morphologies of the pavement cells on the adaxial and abaxial sides of the leaf differed.     

A new formulation for web crippling strength of cold-formed steel sheeting using genetic programming

This study presents Genetic programming (GP) as a new tool for the formulation of web crippling strength of cold-formed steel decks for various loading cases. There is no well established analytical solution of the problem due to complex plastic behaviour. The objective of this study is to provide an alternative robust formulation to related design codes and to verify the robustness of GP for the formulation of such structural engineering problems. The training and testing patterns of the proposed GP formulation are based on well established experimental results from the literature. The GP based formulation results are compared with experimental results and current design codes and found to be more accurate.     

A Novel Approach for Bolted T-Stub Connections

This paper reports an investigation into new connection types and their behaviors determined using full-scale experiments. T-shaped connections were created using the IPE standard profile. The aim of this study was to analyze the influence of T connections based on the IPE standard profile, height of beam to height of T-stub joint (H) of T-stub joints, and lengths (X) of T-stub joints on the behavior of steel connections, in order to provide the necessary data for improving Eurocode 3 and enable efficient use of residue IPE standard profiles and back to the consumption cycle. While the moment resistance values increased with an increase in H from H_min to H_max in model groups with X of 126 mm, and the energy dissipation increased with an increase in H from H_min to H_max and also with an increase in the lengths (X) of T-stub joints from 54 to 126 mm.     

Consideration of the residual stress distributions in fatigue crack growth calculations for assessing welded steel joints

To better understand the crack closure and propagation, an analytical model is established. The residual stress effect on fatigue crack growth equations has been considered using the residual stress intensity factor (SIF) (K_res). The joint geometries, residual stress distributions (σ_res) and residual stress ratio (R_res) were considered also. K_res are calculated using the analytical weight function (WF) method and different residual stress distributions. It is to be emphasized that the current approach is little investigated. This is because the WF has already been developed to calculate SIF for an existing crack. The current approach calculates K_res for the crack that initiates and propagates until failure. Different stress distributions have been used, and R_res is defined. The validity of using the WF has been shown. SIF due to applied load (K_app) and applied stress ratio (R_app) have been considered. Fatigue crack growth rate was investigated in accordance with the current approach. The results have been verified and benchmarked.     

Type 2 Diabetes Risk Prediction Using Deep Convolutional Neural Network Based-Bayesian Optimization

Diabetes mellitus is a long-term condition characterized by hyperglycemia. It could lead to plenty of difficulties. According to rising morbidity in recent years, the world’s diabetic patients will exceed 642 million by 2040, implying that one out of every ten persons will be diabetic. There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’ lives. Due to its rapid development, deep learning (DL) was used to predict numerous diseases. However, DL methods still suffer from their limited prediction performance due to the hyperparameters selection and parameters optimization. Therefore, the selection of hyper-parameters is critical in improving classification performance. This study presents Convolutional Neural Network (CNN) that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm (BOA) has been employed for hyperparameters selection and parameters optimization. Two issues have been investigated and solved during the experiment to enhance the results. The first is the dataset class imbalance, which is solved using Synthetic Minority Oversampling Technique (SMOTE) technique. The second issue is the model's poor performance, which has been solved using the Bayesian optimization algorithm. The findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%, F1-score of 0.88.6, and Matthews Correlation Coefficient (MCC) of 0.88.6.     

Investigation of charge transport mechanism in semiconducting La<Subscript>0.5</Subscript>Ca<Subscript>0.5</Subscript>Mn<Subscript>0.5</Subscript>Fe<Subscript>0.5</Subscript>O<Subscript>3</Subscript> manganite prepared by sol–gel method

Here in, we report the charge transport mechanism in semiconducting La_0.5Ca_0.5Mn_0.5Fe_0.5O₃ (LCMFO) polycrystalline material synthesized via sol–gel auto combustion route. X-ray diffraction (XRD) analysis confirmed the orthorhombic phase of the prepared material. Temperature dependent resistivity and impedance spectroscopy measurements have been carried out to probe the dielectric and electrical conduction mechanism which revealed a change of Mott variable range to the small polaronic hopping conduction mechanism around 303 K. The complex impedance and modulus spectra undoubtedly showed the contribution of both grain and grain boundary effect on the conduction properties of LCMFO. An equivalent circuit [(R_gbQ_gb) (R_gQ_g)] model has been used to address the electrical parameters associated with the different phases (grains and grain boundaries) having different relaxation times. The values of resistances of two phases obtained after fitting the equivalent circuit in the nyquist plot have been analyzed which confirmed the change of conduction mechanism around 303 K. The resultant change in conduction mechanism is also supported by the conductivity plots.