Search Results (17)

In this study, the effect of inlet-turbulence intensity on the friction coefficient for the transitional boundary layer has been investigated computationally. For this purpose, two equation turbulence models of Std. k-ε, RNG k-ε, Std. k-ω, and SST k-ω have been compared with the Gamma–Theta (GT) transitional model, and it has been found that the Gamma–Theta model is the most consistent model with the experimental values of the ERCOFTAC T3A test case. Then, the effect of inlet-turbulence intensity on the friction coefficient has been computed by using this Gamma–Theta model. The transition from laminar to turbulence is shortened with increasing turbulence intensity by changing it from 1% to 10%. The most suitable inlet-turbulence intensity value with the experimental results of the ERCOFTAC T3A test case is found as Tu = 3.3%. Full article

Background: In Western countries, 10–20% of adults have gallstones, of which about 1–3% of patients are symptomatic for biliary colic. The treatment with ursodeoxycholic acid is debated. Silymarin is emerging nowadays as a natural substance with choleretic and beneficial properties, useful in the case of gallbladder sludge. Aim: The aim of our study was to evaluate the efficacy of supplementation with a mix of natural compounds (milk thistle 150 mg, artichoke 150 mg, and green tea 150 mg) in patients affected by biliary sludge in reducing biliary colic and biliary sludge and improving lipid profiles after 3 months of treatment compared to a control group. Patients and Methods: This was an interventional open study on 65 consecutive adult patients (23 M/42 F; mean age 61.0 ± 18.7 years) affected by biliary sludge without indication for surgery, admitted to the Internal Medicine Department of San Carlo di Nancy Hospital Rome. Forty patients were treated with milk thistle 150 mg, artichoke 150 mg, and green tea 150 mg, 2 capsules/day for three months, and followed up for abdominal ultrasound, the frequency of occurrence of biliary colic, and blood tests. Twenty-five control group patients were followed up for abdominal ultrasound, the frequency of occurrence of biliary colic, and blood tests after 3 months. Results: In Group A, we observed a disappearance of biliary sludge in 32.4% (12/37) of patients compared to 8.7% in the control group (p < 0.05). In 32.4% of treated patients, we report a reduction in biliary sludge. There were no side effects during treatment. In both groups, we registered a significant reduction in transaminases and gamma-glutamyl transferase (γ-GT) (p < 0.05). No significant modification of the lipid profile was observed. Conclusions: The treatment with a mix of natural compounds (milk thistle, artichoke, and green tea) in patients affected by symptomatic biliary colic resulted in efficacy and safety in reducing biliary sludge, biliary colic, and transaminases levels after three months of treatment. The limitations of this study include a small number of patients and the absence of long-term follow up after the end of treatment. Full article

Landslides pose significant risks to human lives and infrastructure. The Medea region in Algeria is particularly susceptible to these destructive events, which result in substantial economic losses. Despite this vulnerability, a comprehensive landslide map for this region is lacking. This study aims to develop a novel hybrid metaheuristic model for the spatial prediction of landslide susceptibility in Medea, combining the Adaptive Neuro-Fuzzy Inference System (ANFIS) with four novel optimization algorithms (Genetic Algorithm—GA, Particle Swarm Optimization—PSO, Harris Hawks Optimization—HHO, and Salp Swarm Algorithm—SSA). The modeling phase was initiated by using a database comprising 160 landslide occurrences derived from Google Earth imagery; field surveys; and eight conditioning factors (lithology, slope, elevation, distance to stream, land cover, precipitation, slope aspect, and distance to road). Afterward, the Gamma Test (GT) method was used to optimize the selection of input variables. Subsequently, the optimal inputs were modeled using hybrid metaheuristic ANFIS techniques and their performance evaluated using four relevant statistical indicators. The comparative assessment demonstrated the superior predictive capabilities of the ANFIS-HHO model compared to the other models. These results facilitated the creation of an accurate susceptibility map, aiding land use managers and decision-makers in effectively mitigating landslide hazards in the study region and other similar ones across the world. Full article

The aim of this study was to assess whether dietary supplementation with a nutraceutical blend comprising extracts of bergamot and artichoke—both standardized in their characteristic polyphenolic fractions—could positively affect serum lipid concentration and insulin sensitivity, high-sensitivity C-reactive protein (hs-CRP), and indexes of non-alcoholic fatty liver disease (NAFLD) in 90 healthy individuals with suboptimal cholesterol levels. Participants were randomly allocated to treatment with a pill of either active treatment or placebo. After 6 weeks, the active-treated group experienced significant improvements in levels of triglycerides (TG), apolipoprotein B-100 (Apo B-100), and apolipoprotein AI (Apo AI) versus baseline. Total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), non-high density lipoprotein cholesterol (Non-HDL-C), and hs-CRP also significantly decreased in the active-treated group compared to both baseline and placebo. At the 12-week follow-up, individuals allocated to the combined nutraceutical experienced a significant improvement in TC, LDL-C, Non-HDL-C, TG, Apo B-100, Apo AI, glucose, alanine transaminase (ALT), gamma-glutamyl transferase (gGT), hs-CRP, several indexes of NAFLD, and brachial pulse volume (PV) in comparison with baseline. Improvements in TC, LDL-C, Non-HDL-C, TG, fatty liver index (FLI), hs-CRP, and endothelial reactivity were also detected compared to placebo (p < 0.05 for all). Overall, these findings support the use of the tested dietary supplement containing dry extracts of bergamot and artichoke as a safe and effective approach for the prevention and management of a broad spectrum of cardiometabolic disorders. Full article

Along with concerns regarding societal aging, the dietary requirements of older adults have become a priority. Older adults in Korea experience difficulties consuming animal protein sources as they age. Therefore, this study aimed to develop a senior-friendly food product using mackerel. Accordingly, carbohydrates and proteins were added to the brine solution before saturated vapor treatment. Calcium lactate and poly-gamma-glutamic acid were added to the sauce, and when compared to four commercial products (GT_R, GT_K, PC_K, and AC_G) in an acceptance test, the product was found to exhibit the highest overall liking score (p < 0.001). Higher flavor-liking and familiarity ratings were found to increase purchase intention, while higher flavor-liking, overall-liking, and familiarity ratings increased recommendation intention. Those in mid-to-late adulthood preferred the GT_R and PC_K samples, whereas the AC_G sample was preferred by those in very late adulthood. AC_G sample analysis suggested that those in the very late adulthood group had a relatively higher acceptance of spiciness. In this study, a calcium-added mackerel stew product was manufactured, meeting the standards for senior-friendly food in Korea. It will serve as a baseline for further research on fish- and mackerel-based foods for older adults, which is in its early stages. Full article

Allium hookeri (AH) has been used as a nutritional and medicinal food in Asia for many years. Our previous studies have described its anti-diabetic, anti-obesity, and anti-inflammatory activities in animal models and prediabetes. This study investigated whether AH could improve glycemia by modulating insulin secretion in prediabetic subjects through an in-depth study. Eighty prediabetic subjects (100 ≤ fasting plasma glucose < 140 mg/dL) were randomly assigned to a placebo (n = 40) group or an ethanol AH extract (500 mg/day, n = 40) group for 12 weeks. Dietary intake and physical activity, blood glucose (an oral glucose tolerance test for 120 min), insulin (insulin response to oral glucose for 120 min), area under the curve (AUC) of glucose or insulin after oral glucose intake, insulin sensitivity markers, C-peptide, adiponectin, glycated hemoglobin A1c (HbA1c) levels, hematological tests (WBC, RBC, hemoglobin, hematocrit, and platelet count), blood biochemical parameters (ALP, AST, total bilirubin, total protein, albumin, gamma-GT, BUN, creatinine, LD, CK, and hs-CRP), and urine parameters (specific gravity and pH) were examined at both baseline and 12 weeks after supplementation with placebo or AH capsules. Fifty-eight participants (placebo group: 20 men and 10 women; AH group: 13 men and 15 women) completed the study. AH supplementation moderately reduced postprandial blood glucose at 60 min (−6.14 mg/dL, p = 0.061), postprandial insulin levels at 90 min (−16.69 µU/mL, p = 0.017), the glucose AUC at 90 min (−412.52 mg*min/dL, p = 0.021), as well as the insulin AUC at 90 min (−978.77 µU*min/mL, p = 0.021) and 120 min (−1426.41 µU*min/mL, p = 0.015) when compared with the placebo group. However, there were no effects of AH on dietary intake and physical activity; HOMA index; HbAlc; C-peptide; or adiponectin, hematological-, blood biochemical-, and urinary markers. To confirm the effects of AH extract on blood glucose insulin sensitivity, C57BL/6J or C57BL/KsJ-db/db mice were used (n = 8/group). Body weight, fasting plasma glucose level, lipid profiles, liver and renal function, pancreatic histology, and insulin immunoreactivity were assessed. In the diabetic db/db mice, hyperglycemia, which was accompanied by an increase in insulin secretion in diabetic mice, was significantly reduced by AH treatment, resulting in the alleviation of β-cell overcompensation and insulin resistance. We confirmed that AH supplementation can effectively control blood glucose and insulin levels by improving insulin sensitivity and may be a potential agent for glycemic control in subjects with prediabetes and type 2 diabetes mellitus. Full article

Many studies have shown the high efficacy of histamine H₃ receptor ligands in preventing weight gain. In addition to evaluating the efficacy of future drug candidates, it is very important to assess their safety profile, which is established through numerous tests and preclinical studies. The purpose of the present study was to evaluate the safety of histamine H₃/sigma-2 receptor ligands by assessing their effects on locomotor activity and motor coordination, as well as on the cardiac function, blood pressure, and plasma activity of certain cellular enzymes. The ligands tested at a dose of 10 mg/kg b.w. did not cause changes in locomotor activity (except for KSK-74) and did not affect motor coordination. Significant reductions in blood pressure were observed after the administration of compounds KSK-63, KSK-73, and KSK-74, which seems logically related to the increased effect of histamine. Although the results of in vitro studies suggest that the tested ligands can block the human ether-a-go-go-related gene (hERG) potassium channels, they did not affect cardiac parameters in vivo. It should be noted that repeated administration of the tested compounds prevented an increase in the activity of alanine aminotransferase (AlaT) and gamma-glutamyl transpeptidases (gGT) observed in the control animals fed a palatable diet. The obtained results show that the ligands selected for this research are not only effective in preventing weight gain but also demonstrate safety in relation to the evaluated parameters, allowing the compounds to proceed to the next stages of research. Full article

Thymelaea microphylla Coss. et Dur (T. microphylla), a medicinal herb that grows in arid and desert pastures, has been traditionally utilized by Moroccans to treat many diseases, including kidney failure. This study aims to evaluate the nephroprotective effect against gentamicin-induced nephrotoxicity (GM), and thus the antioxidant activity of an aqueous extract rich in flavonoids from the aerial part of T. microphylla (APTM). The antioxidant activity of APTM was assessed using the 2-2-diphenyl-1-picrylhydrazyl (DPPH) scavenging test and the β-carotene bleaching assay. The nephroprotective effect of this extract was evaluated in two doses of 200 and 400 mg/kg in GM-exposed male rats. Acute toxicity of the APTM was tested out on Swiss albino mice using 2000 mg/kg as the dose limit. The findings showed that the aqueous extract of APTM is abundant in total polyphenols and flavonoids and has significant antioxidant properties against DPPH radicals and β-carotene oxidation. According to the acute toxicity research findings, the administered doses of the APTM extract do not cause toxicity and death. A significant increase in the serum concentrations of creatinine, urea, uric acid, sodium, chloride, calcium, gamma-glutamyl transpeptidase (gamma-GT), and alkaline phosphatase, as well as an increase in urinary volume, water consumption, and relative kidney weight, were all caused by the administration of GM to rats. In addition, a significant reduction in urinary concentrations of creatinine, uric acid, urea, and albumin, and thus the clearance of creatinine and weight gain were observed in rats injected with GM. Also, the administration of GM dramatically raised the malondialdehyde level in the kidneys. Likewise, rats that had been poisoned with GM had histological kidney abnormalities. However, the daily treatment of APTM aqueous extract to rats given GM injections dramatically improved the biochemical and histological parameters affected by GM administration in rats. Finally, APTM extract enhanced GM’s biochemical and histological indicators of nephrotoxicity, supporting its use as an ethnomedicinal. Full article

Neurotrophins are considered as an attractive target for the development of antidepressants with a novel mechanism of action. Previously, the dimeric dipeptide mimetics of individual loops of nerve growth factor, NGF (GK-6, loop 1; GK-2, loop 4) and brain-derived neurotrophic factor, BDNF (GSB-214, loop 1; GTS-201, loop 2; GSB-106, loop 4) were designed and synthesized. All the mimetics of NGF and BDNF in vitro after a 5–180 min incubation in a HT-22 cell culture were able to phosphorylate the tropomyosin-related kinase A (TrkA) or B (TrkB) receptors, respectively, but had different post-receptor signaling patterns. In the present study, we conduct comparative research of the antidepressant-like activity of these mimetics at acute and subchronic administration in the forced swim test in mice. Only the dipeptide GSB-106 that in vitro activates mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK), phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) and phospholipase C-gamma (PLC_γ) post-receptor pathways exhibited antidepressant-like activity (0.1 and 1.0 mg/kg, ip) at acute administration. At the same time, the inhibition of any one of these signaling pathways completely prevented the antidepressant-like effects of GSB-106 in the forced swim test. All the NGF mimetics were inactive after a single injection regardless of post-receptor in vitro signaling patterns. All the investigated dipeptides, except GTS-201, not activating PI3K/AKT in vitro unlike the other compounds, were active at subchronic administration. The data obtained demonstrate that the low-molecular weight BDNF mimetic GSB-106 that activates all three main post-receptor TrkB signaling pathways is the most promising for the development as an antidepressant. Full article

Electric vehicles have been issued to achieve sustainable mobility. Main factors to sustainable electric vehicle (EV) are that lithium-ion battery (LIB) has to maintain lower cost, lighter weight, SOC (state of charge), thermal stability, and driving ranges. In this study, nickel-cobalt-manganese (NCM), lithium iron phosphate (LFP), and lithium manganese oxide (LMO), which are used as representative positive electrode materials, were applied to battery cells. Then, the battery characteristics at the system level, according to the application of different positive electrode materials, were compared and analyzed. To this end, each of the 18650 cylindrical battery cells was modeled by applying different positive electrode active materials. The battery modeling was based on a database provided by GT(Gamma Technologies)-AutoLion. To analyze the thermal stability and capacity loss according to the temperature of the battery cell by applying different C-rate discharge and temperature conditions for each positive electrode active material, an electrochemical-based zero-dimensional (0D) analysis was performed. A test was also performed to determine the model feasibility by using a MACCOR 4300 battery charger/discharger. Moreover, a lumped battery pack modeling was performed to extend the modeled battery cell to an EV battery pack. By combining the pack and one-dimensional (1D) EV models, various driving cycles were described to investigate the battery performance at the vehicle level. It was found that the 0D electrochemistry-coupled 1D vehicle model could well predict the feasible tendencies considering various positive electrode materials of the LIB battery cell. Full article

Appropriate input selection for the estimation matrix is essential when modeling non-linear progression. In this study, the feasibility of the Gamma test (GT) was investigated to extract the optimal input combination as the primary modeling step for estimating monthly pan evaporation (EP_m). A new artificial intelligent (AI) model called the co-active neuro-fuzzy inference system (CANFIS) was developed for monthly EP_m estimation at Pantnagar station (located in Uttarakhand State) and Nagina station (located in Uttar Pradesh State), India. The proposed AI model was trained and tested using different percentages of data points in scenarios one to four. The estimates yielded by the CANFIS model were validated against several well-established predictive AI (multilayer perceptron neural network (MLPNN) and multiple linear regression (MLR)) and empirical (Penman model (PM)) models. Multiple statistical metrics (normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (NSE), Pearson correlation coefficient (PCC), Willmott index (WI), and relative error (RE)) and graphical interpretation (time variation plot, scatter plot, relative error plot, and Taylor diagram) were performed for the modeling evaluation. The results of appraisal showed that the CANFIS-1 model with six input variables provided better NRMSE (0.1364, 0.0904, 0.0947, and 0.0898), NSE (0.9439, 0.9736, 0.9703, and 0.9799), PCC (0.9790, 0.9872, 0.9877, and 0.9922), and WI (0.9860, 0.9934, 0.9927, and 0.9949) values for Pantnagar station, and NRMSE (0.1543, 0.1719, 0.2067, and 0.1356), NSE (0.9150, 0.8962, 0.8382, and 0.9453), PCC (0.9643, 0.9649, 0.9473, and 0.9762), and WI (0.9794, 0.9761, 0.9632, and 0.9853) values for Nagina stations in all applied modeling scenarios for estimating the monthly EP_m. This study also confirmed the supremacy of the proposed integrated GT-CANFIS model under four different scenarios in estimating monthly EP_m. The results of the current application demonstrated a reliable modeling methodology for water resource management and sustainability. Full article

A hybrid electric vehicle (HEV) is a product that can greatly alleviate problems related to the energy crisis and environmental pollution. However, replacing such a battery will increase the cost of usage before the end of the life of a HEV. Thus, research on the multi-objective energy management control problem, which aims to not only minimize the gasoline consumption and consumed electricity but also prolong battery life, is necessary and challenging for HEV. This paper presents an adaptive equivalent consumption minimization strategy based on a recurrent neural network (RNN-A-ECMS) to solve the multi-objective optimal control problem for a plug-in HEV (PHEV). The two objectives of energy consumption and battery loss are balanced in the cost function by a weighting factor that changes in real time with the operating mode and current state of the vehicle. The near-global optimality of the energy management control is guaranteed by the equivalent factor (EF) in the designed A-ECMS. As the determined EF is dependent on the optimal co-state of the Pontryagin’s minimum principle (PMP), which results in the online ECMS being regarded as a realization of PMP-based global optimization during the whole driving cycle. The time-varying weight factor and the co-state of the PMP are map tables on the state of charge (SOC) of the battery and power demand, which are established offline by the particle swarm optimization (PSO) algorithm and real historical traffic data. In addition to the mappings of the weight factor and the major component of the EF linked to the optimal co-state of the PMP, the real-time performance of the energy management control is also guaranteed by the tuning component of the EF of A-ECMS resulting from the Proportional plus Integral (PI) control on the deviation between the battery SOC and the optimal trajectory of the SOC obtained by the Recurrent Neural Network (RNN). The RNN is trained offline by the SOC trajectory optimized by dynamic programming (DP) utilizing the historical traffic data. Finally, the effectiveness and the adaptability of the proposed RNN-A-ECMS are demonstrated on the test platform of plug-in hybrid electric vehicles based on GT-SUITE (a professional integrated simulation platform for engine/vehicle systems developed by Gamma Technologies of US company) compared with the existing strategy. Full article

Due to nonuniform rainfall distribution in Taiwan, groundwater is an important water source in certain areas that lack water storage facilities during periods of drought. Therefore, groundwater recharge is an important issue for sustainable water resources management. The mountainous areas and the alluvial fan areas of the Jhuoshui River basin in Central Taiwan are considered abundant groundwater recharge regions. This study aims to investigate the interactive mechanisms between surface water and groundwater through statistical techniques and estimate groundwater level variations by a combination of artificial intelligence techniques and the Gamma test (GT). The Jhuoshui River basin in Central Taiwan is selected as the study area. The results demonstrate that: (1) More days of accumulated rainfall data are required to affect variable groundwater levels in low-permeability wells or deep wells; (2) effective rainfall thresholds can be properly identified by lower bound screening of accumulated rainfall; (3) daily groundwater level variation can be estimated effectively by artificial neural networks (ANNs); and (4) it is difficult to build efficient models for low-permeability wells, and the accuracy and stability of models is worse in the proximal-fan areas than in the mountainous areas. Full article

Prediction of the groundwater dynamics via models can help better manage the groundwater resources and guarantee their sustainable use. Three types of data-driven models are built for groundwater depth prediction in the plain of Shijiazhuang, the capital of Hebei Province in North China. The data-driven models include the Power Function Model (PFM), Back-Propagation Artificial Neural Network (BPANN) and Support Vector Machines (SVM) with two kernel functions of linear kernel function (LKF) and radial basis function (RBF). Five classes of factors (including 12 indices) are considered as potential model input variables. The Gamma Test (GT) is adopted in this study to help identify the relative importance of the input indices and tackle the tricky issue of the optimal input combinations for the data-driven models. The established models are evaluated in both fitting and testing procedures based on the root mean squared error (RMSE) and Nash-Sutcliffe efficiency (E) for different input combination schemes. The results show that SVM (RBF) performs the best. It is interesting to find that the natural factors (i.e., precipitation and evaporation) are less relevant to the groundwater depth variations. The methods used in this study have much significance for groundwater depth prediction in areas lacking hydrogeological data. Full article

This paper develops a class of density regression models based on proportional hazards family, namely, Gamma transformation proportional hazard (Gt-PH) model . Exact inference for the regression parameters and hazard ratio is derived. These estimators enjoy some good properties such as unbiased estimation, which may not be shared by other inference methods such as maximum likelihood estimate (MLE). Generalised confidence interval and hypothesis testing for regression parameters are also provided. The method itself is easy to implement in practice. The regression method is also extended to Lasso-based variable selection. Full article