A CNN-LSTM network with multi-level feature extraction-based approach for automated detection of coronavirus from CT scan and X-ray images.

Auto-detection of diseases has become a prime issue in medical sciences as population density is fast growing. An intelligent framework for disease detection helps physicians identify illnesses, give reliable and consistent results, and reduce death rates. Coronavirus (Covid-19) has recently been one of the most severe and acute diseases in the world. An automatic detection framework should therefore be introduced as the fastest diagnostic alternative to avoid Covid-19 spread. In this paper, an automatic Covid-19 identification in the CT scan and chest X-ray is obtained with the help of a combined deep learning and multi-level feature extraction methodology. In this method, the multi-level feature extraction approach comprises GIST, Scale Invariant Feature Transform (SIFT), and Convolutional Neural Network (CNN) extract features from CT scans and chest X-rays. The objective of multi-level feature extraction is to reduce the training complexity of CNN network, which significantly assists in accurate and robust Covid-19 identification. Finally, Long Short-Term Memory (LSTM) along the CNN network is used to detect the extracted Covid-19 features. The Kaggle SARS-CoV-2 CT scan dataset and the Italian SIRM Covid-19 CT scan and chest X-ray dataset were employed for testing purposes. Experimental outcomes show that proposed approach obtained 98.94% accuracy with the SARS-CoV-2 CT scan dataset and 83.03% accuracy with the SIRM Covid-19 CT scan and chest X-ray dataset. The proposed approach helps radiologists and practitioners to detect and treat Covid-19 cases effectively over the pandemic.

Trace metals in different socioeconomic indoor residential settings, implications for human health via dust exposure.

In this study a number of heavy metals namely chromium (Cr), cadmium (Cd), zinc (Zn), barium (Ba), copper (Cu), manganese (Mn), cobalt (Co), rubidium (Rb), selenium (Se) are studied in the floor and air condition (AC) filter dust collected from urban and rural households of Saudi Arabia. To the best of our knowledge, many of these heavy metals are reported for the very first time in the indoor dust of Saudi Arabia. Studied metals were higher in urban dust than rural except Mn and Rb which were significantly higher (P < 0.05) in rural dust. All metals, except Cd, Zn, and Ba in urban settings, were detected at higher (P < 0.05) levels in AC filter dust than household floor dust from both rural and urban residential settings. Levels of the two dominant metals i.e., Zn and Mn were up to 1600 and 700 µg/g, respectively in studied dust samples. Also associations between heavy metals and a number of different socio-economic parameters were studied which was significant for some trace metals. In literature exposure to many of trace metals are associated with various health problems, therefore health risk assessment for the Saudi population was calculated by incremental lifetime cancer risk (ILCR) and hazardous index (HI) via dust ingestion, inhalation, and dermal contact. The ILCR for all metals was within the tolerable range of reference values of USEPA (1 × 10- 11 to 1 × 10- 4). However, calculated HI for Mn, Cu, Ni, and Zn was more than 1 via dust exposure, which signifies the non-carcinogenic risk. The study highlights the occurrence of toxic metals in the indoor environments of Saudi Arabia and provides baseline data for future studies on these toxic metals in the region.

Preoperative Three-Dimensional Strain Imaging Identifies Reduction in Left Ventricular Function and Predicts Outcomes After Cardiac Surgery.

BACKGROUND: Echocardiography-based speckle-tracking strain imaging is an emerging modality to assess left ventricular function. The aim of this study was to investigate the change in left ventricular systolic function after cardiac surgery with 3-dimensional (3D) speckle-tracking strain imaging and to determine whether preoperative 3D strain is an independent predictor of acute and long-term clinical outcomes after aortic valve, mitral valve, and coronary artery bypass grafting operations. METHODS: In total, 163 adult patients undergoing aortic valve, mitral valve, and coronary artery bypass surgeries were enrolled prospectively and had complete data sets. Demographic, operative, and outcome data were collected. 3D transthoracic echocardiograms were preformed preoperatively and on second to fourth postoperative day. Blinded off-line analysis was performed for left ventricular 2-dimensional (2D) ejection fraction (EF2D) and 3D ejection fraction (EF3D) and global peak systolic area, longitudinal, circumferential, and radial strain. RESULTS: 3D global strain correlated well with EF3D. Ventricular function as measured by strain imaging decreased significantly after all types of cardiac surgery. When preoperative EF3D was used, receiver operating characteristic curves identified reference values for 3D global strain corresponding to normal, mildly reduced, and severely reduced ventricular function. Normal ventricular function (EF3D ≥ 50%) corresponded to 3D global area strain -25%, with area under curve = 0.86 (0.81-0.89). Patients with reduced preoperative 3D global area strain had worse postoperative outcomes, including length of intensive care unit stay (4 vs 3 days, P = .001), major adverse events (27% vs 11%, P = .03), and decreased 1-year event-free survival (69% vs 88%, P = .005). After we controlled for baseline preoperative risk models including European System for Cardiac Operative Risk Evaluation score and surgery type, preoperative strain was an independent predictor of both short- and long-term outcomes, including length of intensive care unit stay, postoperative inotrope score, and 1-year event-free survival. CONCLUSIONS: This study shows that cardiac surgery was associated with an acute reduction in postoperative left ventricular function, when evaluated with 3D strain imaging. In addition, preoperative 3D strain was demonstrated to be an independent predictor of acute and long-term clinical outcomes after cardiac surgery. The use of noninvasive 3D transthoracic echocardiogram strain imaging before cardiac surgery may provide added information to aid in perioperative risk stratification and management for these high-risk patients.

Tailored pancreatic reconstruction after pancreaticoduodenectomy: a single-center experience of 892 cases.

BACKGROUND: Pancreatic reconstruction following pancreaticoduodenectomy (PD) is still debatable even for pancreatic surgeons. Ideally, pancreatic reconstruction after PD should reduce the risk of postoperative pancreatic fistula (POPF) and its severity if developed with preservation of both exocrine and endocrine pancreatic functions. It must be tailored to control the morbidity linked to the type of reconstruction. This study was to show the best type of pancreatic reconstruction according to the characters of pancreatic stump. METHODS: We studied all patients who underwent PD in our center from January 1993 to December 2015. Patients were categorized into three groups depending on the presence of risk factors of postoperative complications: low-risk group (absent risk factor), moderate-risk group (presence of one risk factor) and high-risk group (presence of two or more risk factors). RESULTS: A total of 892 patients underwent PD for resection of periampullary tumor. BMI >25 kg/m2, cirrhotic liver, soft pancreas, pancreatic duct diameter <3 mm, and pancreatic duct location from posterior edge <3 mm are risk variables for development of postoperative complications. POPF developed in 128 (14.3%) patients. Delayed gastric emptying occurred in 164 (18.4%) patients, biliary leakage developed in 65 (7.3%) and pancreatitis presented in 20 (2.2%). POPF in low-, moderate- and high-risk groups were 26 (8.3%), 65 (15.7%) and 37 (22.7%) patients, respectively. Postoperative morbidity and mortality were significantly lower with pancreaticogastrostomy (PG) in high-risk group, while pancreaticojejunostomy (PJ) decreases incidence of postoperative steatorrhea in all groups. CONCLUSIONS: Selection of proper pancreatic reconstruction according to the risk factors of patients may reduce POPF and postoperative complications and mortality. PG is superior to PJ as regards short-term outcomes in high-risk group but PJ provides better pancreatic function in all groups and therefore, PJ is superior in low- and moderate-risk groups.

Outcomes of pancreaticoduodenectomy in elderly patients.

BACKGROUND: Although the mortality and morbidity of pancreaticoduodenectomy (PD) have improved significantly over the past years, the concerns for elderly patients undergoing PD are still present. Furthermore, the frequency of PD is increasing because of the increasing proportion of elderly patients and the increasing incidence of periampullary tumors. This study aimed to analyze the outcomes of PD in elderly patients. METHODS: We studied all patients who had undergone PD in our center between January 1995 and February 2015. The patients were divided into three groups based on age: group I (patients aged <60 years), group II (those aged 60 to 69 years) and group III (those aged ≥70 years). The primary outcome was the rate of total postoperative complications. Secondary endpoint included total operative time, hospital mortality, length of postoperative hospital stay, delayed gastric emptying, re-exploration, and survival rate. RESULTS: A total of 828 patients who had undergone PD for resection of periampullary tumor were included in this study. There were 579 (69.9%) patients in group I, 201 (24.3%) in group II, and 48 (5.8%) in group III. The overall incidence of complications was higher in elderly patients (25.9% in group I, 36.8% in group II, and 37.5% in group III; P=0.006). There were more patients complicated with delayed gastric emptying in group II compared with the other two groups. There was no significant difference in the incidence of postoperative pancreatic fistula, biliary leakage, pancreatitis, pulmonary complications and hospital mortality. CONCLUSIONS: PD can be performed safely in selected elderly patients. Advanced age alone should not be a contraindication for PD. The outcome of elderly patients who have undergone PD is similar to that of younger patients, and the increased rate of complications is due to the presence of associated comorbidities.

Securing China's rice harvest: unveiling dominant factors in production using multi-source data and hybrid machine learning models.

Ensuring the security of China's rice harvest is imperative for sustainable food production. The existing study addresses a critical need by employing a comprehensive approach that integrates multi-source data, including climate, remote sensing, soil properties and agricultural statistics from 2000 to 2017. The research evaluates six artificial intelligence (AI) models including machine learning (ML), deep learning (DL) models and their hybridization to predict rice production across China, particularly focusing on the main rice cultivation areas. These models were random forest (RF), extreme gradient boosting (XGB), conventional neural network (CNN) and long short-term memory (LSTM), and the hybridization of RF with XGB and CNN with LSTM based on eleven combinations (scenarios) of input variables. The main results identify that hybrid models have performed better than single models. As well, the best scenario was recorded in scenarios 8 (soil variables and sown area) and 11 (all variables) based on the RF-XGB by decreasing the root mean square error (RMSE) by 38% and 31% respectively. Further, in both scenarios, RF-XGB generated a high correlation coefficient (R2) of 0.97 in comparison with other developed models. Moreover, the soil properties contribute as the predominant factors influencing rice production, exerting an 87% and 53% impact in east and southeast China, respectively. Additionally, it observes a yearly increase of 0.16 °C and 0.19 °C in maximum and minimum temperatures (Tmax and Tmin), coupled with a 20 mm/year decrease in precipitation decline a 2.23% reduction in rice production as average during the study period in southeast China region. This research provides valuable insights into the dynamic interplay of environmental factors affecting China's rice production, informing strategic measures to enhance food security in the face of evolving climatic conditions.

Food applications of bioactive biomaterials based on gelatin and chitosan.

Food packaging must guarantee the products' quality during the different operations including packing and maintenance throughout transportation and storage until to consumption. Thus, it should satisfy, both, food freshness and quality preservation and consumers health safety. Natural bio-sourced polymers have been explored as safe edible materials for several packaging applications, being interestingly carrier of bioactive substances, once added to improve films' properties. Gelatin and chitosan are among the most studied biomaterials for the preparation of edible packaging films due to their excellent characteristics including biodegradability, compatibility and film-forming property. These polymers could be used alone or in combination with other polymers to produce composite films with the desired physicochemical and mechanical properties. When incorporated with bioactive substances (natural extracts, polyphenolic compounds, essential oils), chitosan/gelatin-based films acquired various biological properties, including antioxidant and antimicrobial activities. The emerging bioactive composite films with excellent physical attributes represent excellent packaging alternative to preserve different types of foodstuffs (fruits, meat, fish, dairy products, …) and have shown great achievements. This chapter provides the main techniques used to prepare gelatin- and chitosan- based films, showing some examples of bioactive compounds incorporated into the films' matrix. Also, it illustrates the outstanding advantages given by these biomaterials for food preservation, when used as coating and wrapping agents.

Non-chemical weed management: Harnessing flame weeding for effective weed control.

The goal of the current study was to create and assess the effectiveness of a hand-pulled ergonomically designed flame weeder. The developed weeder was tested in the field at three operating pressures (20, 30 and 40 Psi) and forward speeds (1.00, 1.25 and 1.50 km/h) to study their effects on plant damage, survival rates, weight preservation rates, weed management effectiveness, soil temperatures, and gas and energy consumption. Thereafter, at optimized values of forward speed and operating pressure, a comparative assessment of flame weeding with traditional methods (mechanical and manual weeding) was done in terms of weed control effectiveness, operational time, energy consumption, and cost of operation. Results showed that the optimal performance of the designed flame weeder was achieved when operated at a speed of 1 km/h and an operating pressure of 40 psi. The survival rate, weight preservation rate, weed control efficiency, change in soil temperature, recovery rate, plant damage, gas consumption, and energy consumption were observed to be 27.3 %, 32.5 %, 91.1 %, 40.74 °C, 8.5 %, 2.2 %, 4.05 kg/h, and 2500.24 MJ/ha, respectively, at optimized values of forward speed (1.00 km/h) and operating pressure (40 Psi). The actual field capacity, field efficiency and operating cost of the flame weeder were 0.0755 ha/h, 94.94 %, and 3620.81 ₹/ha, respectively. Hand weeding had the best level of weed control effectiveness, but it was a laborious, time-consuming process. When compared to manual weeding, flame weeding was 50.42 % cheaper and 94.82 % faster.

Investigation into the Effects of Crystalline Admixtures and Coatings on the Properties of Self-Healing Concrete.

One fascinating concept for enhancing the durability and lifespan of concrete buildings involves the use of self-healing concrete. This study focuses on the effect of crystalline admixtures and coatings on various properties of self-healing concrete and provides a comparison with traditional concrete. Four different concrete mixtures were prepared to assess their effectiveness in bridging crack openings, their flexural and compressive strengths, and water absorption. Various testing methods, including destructive, semi-destructive, and non-destructive tests, were used in this research. The capacity of the mixes to repair themselves was assessed on the destroyed and semi-destroyed test specimens using crack-healing and microstructure testing. Additionally, all mixtures were also subjected to the slump cone test and air content test in order to investigate the characteristics of the concrete in its fresh state. The findings demonstrate that crystalline coating and admixture combinations have significant potential for healing concrete. The compressive and bending strengths of self-healing concrete mixtures were shown to be slightly higher compared to traditional concrete when the additive dose was increased. Self-healing concrete mixtures also exhibited much lower water absorption, a tightly packed and improved microstructure, and signs of healed gaps, all of which indicate greater durability.

Novel garden cress-fish gelatin based ointment: Improvement of skin wound healing in rats through modulation of anti-inflammatory and antioxidant states.

This study aimed to investigate the ability of aqueous extract of Lepidium sativum seeds (LSE) to improve the wound healing process in rat models. The gelatin, extracted from the skin of smooth-hound shark using citric acid, was used as a support material for ointment. Animals were divided into four groups of six rats each: an untreated control group, a control group treated with Moist Exposed Burn Ointment (MEBO), a treated group with gelatin gel, and a treated group with gelatin gel fortified with 20 mg/mL LSE. Phenolics profile analysis showed that the major compounds in LSE were catechin (125 µg/g) and quinic acid (105 µg/g). In vitro antioxidant tests showed that LSE has interesting activities to scavenge ABTS•+ radicals (IC50 = 0.22 mg/mL) and inhibit the oxidation of linoleic acid. A significant decline in the antioxidant enzymes activities and an increase in the level of thiobarbituric acid reactive substances (TBARS) and inflammatory markers was observed within the injured tissues of the untreated rats compared to rats treated with MEBO. Interestingly, when the wounded tissue was treated with gelatin gel a remarkable reversal of this trend occurred. Further, by enrichment of gelatin gel with LSE, the levels of CAT, GPx and SOD activities significantly increased by 35, 126, and 212 %, respectively, whereas the TBARS level was reduced by 31 %. These results were consistent with the wound contraction percentage and histological analysis, which suggest the potential effect of LSE-enriched gelatin gels to regenerate damaged tissues.

Enhancing groundwater vulnerability assessment for improved environmental management: addressing a critical environmental concern.

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer's highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.

Investigating a hybrid extreme learning machine coupled with Dingo Optimization Algorithm for modeling liquefaction triggering in sand-silt mixtures.

Liquefaction is a devastating consequence of earthquakes that occurs in loose, saturated soil deposits, resulting in catastrophic ground failure. Accurate prediction of such geotechnical parameter is crucial for mitigating hazards, assessing risks, and advancing geotechnical engineering. This study introduces a novel predictive model that combines Extreme Learning Machine (ELM) with Dingo Optimization Algorithm (DOA) to estimate strain energy-based liquefaction resistance. The hybrid model (ELM-DOA) is compared with the classical ELM, Adaptive Neuro-Fuzzy Inference System with Fuzzy C-Means (ANFIS-FCM model), and Sub-clustering (ANFIS-Sub model). Also, two data pre-processing scenarios are employed, namely traditional linear and non-linear normalization. The results demonstrate that non-linear normalization significantly enhances the prediction performance of all models by approximately 25% compared to linear normalization. Furthermore, the ELM-DOA model achieves the most accurate predictions, exhibiting the lowest root mean square error (484.286 J/m3), mean absolute percentage error (24.900%), mean absolute error (404.416 J/m3), and the highest correlation of determination (0.935). Additionally, a Graphical User Interface (GUI) has been developed, specifically tailored for the ELM-DOA model, to assist engineers and researchers in maximizing the utilization of this predictive model. The GUI provides a user-friendly platform for easy input of data and accessing the model's predictions, enhancing its practical applicability. Overall, the results strongly support the proposed hybrid model with GUI serving as an effective tool for assessing soil liquefaction resistance in geotechnical engineering, aiding in predicting and mitigating liquefaction hazards.

Impact of Helicobacter pylori Status on Postoperative Morbidities After Laparoscopic Sleeve Gastrectomy in an Endemic Region (a Retrospective Multicentric Study).

PURPOSE: Studies are still ongoing to determine whether Helicobacter pylori (HP) may affect the results of laparoscopic sleeve gastrectomy (LSG). The main research objectives were HP prevalence in patients with severe obesity and the effects of HP status on outcomes. PATIENTS AND METHODS: This multicenter retrospective study included patients with severe obesity who had LSG. The patients were grouped into three groups based on the HP status of preoperative endoscopic biopsies and postoperative specimen results: group I (negative HP), group II (eradicated HP), and group III (positive HP). The primary outcome was the overall postoperative morbidities. RESULTS: One thousand six hundred fifteen patients who underwent LSG for severe obesity were included in this study. Seven hundred fifty (46.4%) patients had negative HP, and 637 (39.4%) patients had eradicated HP, whereas 228 (14.1%) patients had positive HP. The antral and gastric body wall thickness was significantly noticed with positive HP. The groups had no significant differences regarding postoperative complication frequency, severity, and hospital mortality. The rates of gastric leakage in the three groups do not differ significantly. BMI > 50, gastropexy, gastric thickness, and antral resection were found to be independent risk factors for the occurrence of postoperative complications after LSG. There was no statistical significance as regards postoperative %TWL and %EWL among the three groups. CONCLUSION: The early results of LSG do not appear to be impacted by HP's status. The early postoperative course is unaffected by HP eradication anymore. Therefore, routine preoperative HP testing may not be as necessary, and management can be finished after LSG.

Study on the effect of geometrical and operational parameters on performance dynamics of modified rotary blades using DEM.

The geometric features and operational parameters of rotary blades on rotary tillers significantly impact their performance characteristics. The sweepback angle is a geometric feature of the 'L'-shaped rotary blade that has remained unexplored in previous studies. This study aimed to analyze the effect of geometrical and operational parameters on the performance dynamics of the 'L'-shaped rotary blade. The investigation was conducted using the discrete element method (DEM) and further validated through experiments conducted in a soil bin. The simulation experiment was conducted by dividing the particle bed into horizontal particle zones. The effect of the geometrical (sweepback angle) and operational parameters (forward speed, rotational speed, and depth) on the power requirement, disturbance intensity, and mixing index was studied. The novel method was adopted to determine the mixing capability of rotary blades in terms of sub-domain mixing index (SMI) and overall mixing index (OMI). The results revealed that the power requirements for a sweepback angle of 18° were 26.39% and 16.50% lower than those for sweepback angles of 6° and 12°, respectively. The sweepback angle tends to have the least effect on the overall mixing index compared to operational parameters. The average particle velocity decreased by 22.19% and 29.60% with sweepback angles of 12° and 18°, respectively, compared to the sweepback angle of 6°. The relative error during the experiment varied between 1.29% and 13.51%. It was concluded that the sweepback angle was found to be a feasible option for reducing the power requirement with good mixing indices.

Utilizing adaptive deformable convolution and position embedding for colon polyp segmentation with a visual transformer.

Polyp detection is a challenging task in the diagnosis of Colorectal Cancer (CRC), and it demands clinical expertise due to the diverse nature of polyps. The recent years have witnessed the development of automated polyp detection systems to assist the experts in early diagnosis, considerably reducing the time consumption and diagnostic errors. In automated CRC diagnosis, polyp segmentation is an important step which is carried out with deep learning segmentation models. Recently, Vision Transformers (ViT) are slowly replacing these models due to their ability to capture long range dependencies among image patches. However, the existing ViTs for polyp do not harness the inherent self-attention abilities and incorporate complex attention mechanisms. This paper presents Polyp-Vision Transformer (Polyp-ViT), a novel Transformer model based on the conventional Transformer architecture, which is enhanced with adaptive mechanisms for feature extraction and positional embedding. Polyp-ViT is tested on the Kvasir-seg and CVC-Clinic DB Datasets achieving segmentation accuracies of 0.9891 ± 0.01 and 0.9875 ± 0.71 respectively, outperforming state-of-the-art models. Polyp-ViT is a prospective tool for polyp segmentation which can be adapted to other medical image segmentation tasks as well due to its ability to generalize well.

Integrated assessment of the impact of land use changes on groundwater recharge and groundwater level in the Drava floodplain, Hungary.

Land-use/land-cover (LULC) change is considered a key human factor influencing groundwater recharge in floodplains. Without accurate estimations, the impact of LULC change on water balance components may be either significantly understated or exaggerated. This paper assesses the impacts of LULC changes from 1990 to 2018 on water balance components and groundwater levels of the Drava floodplain, Hungary, where human interference has led to a critical environmental situation. In this study, a spatially-distributed water balance model (WetSpass-M), and a groundwater flow model (MODFLOW-NWT) were integrated to assess the impacts of LULC changes. The moderate expansion of built-up areas increased surface runoff, while the afforestation of arable land and meadows and the overgrowth of bare mudflats with willow shrubs increased evapotranspiration. As a consequence, total annual groundwater recharge decreased by 5.3 × 107 m3 in the floodplain with an average of 335 mm year-1 and 317 mm year-1 in 2012 and 2018, respectively. Moreover, an average groundwater level decline by 0.1 m is observed in the same period. Declined groundwater recharge, increased runoff, and evapotranspiration exerted a negative effect on water resources in the Drava basin. The approach tested in this paper allows temporal and spatial estimation of hydrological components under the changes of LULC, providing quantitative information for decision-makers and stakeholders to implement efficient and sustainable management of water resources in the Drava floodplain. The provided integrated model is also applicable to regionally.

Improving detention ponds for effective stormwater management and water quality enhancement under future climate change: a simulation study using the PCSWMM model.

Urban surfaces are often covered by impermeable materials such as concrete and asphalt which intensify urban runoff and pollutant concentration during storm events, and lead to the deterioration of the quality of surrounding water bodies. Detention ponds are used in urban stormwater management, providing two-fold benefits: flood risk reduction and pollution load minimization. This paper investigates the performance of nine proposed detention ponds (across the city of Renton, Washington, USA) under different climate change scenarios. First, a statistical model was developed to estimate the pollutant load for the current and future periods and to understand the effects of increased rainfall on stormwater runoff and pollutant loads. The Personal Computer Storm Water Management Model (PCSWMM) platform is employed to calibrate an urban drainage model for quantifying stormwater runoff and corresponding pollutant loads. The calibrated model was used to investigate the performance of the proposed nine (9) detention ponds under future climate scenarios of 100-year design storms, leading to identifying if they are likely to reduce stormwater discharge and pollutant loads. Results indicated significant increases in stormwater pollutants due to increases in rainfall from 2023 to 2050 compared to the historical period 2000-2014. We found that the performance of the proposed detention ponds in reducing stormwater pollutants varied depending on the size and location of the detention ponds. Simulations for the future indicated that the selected detention ponds are likely to reduce the concentrations (loads) of different water quality constituents such as ammonia (NH3), nitrogen dioxide (NO2), nitrate (NO3), total phosphate (TP), and suspended solids (SS) ranging from 18 to 86%, 35-70%, 36-65%, 26-91%, and 34-81%, respectively. The study concluded that detention ponds can be used as a reliable solution for reducing stormwater flows and pollutant loads under a warmer future climate and an effective adaptation option to combat climate change related challenges in urban stormwater management.

High-efficiency electromagnetic energy harvesting using double-elliptical metasurface resonators.

This study introduces a metasurface (MS) based electrically small resonator for ambient electromagnetic (EM) energy harvesting. It is an array of novel resonators comprising double-elliptical cylinders. The harvester's input impedance is designed to match free space, allowing incident EM power to be efficiently absorbed and then maximally channelled to a single load through optimally positioned vias. Unlike the previous research works where each array resonator was connected to a single load, in this work, the received power by all array resonators is channelled to a single load maximizing the power efficiency. The performance of the MS unit cell, when treated as an infinite structure, is examined concerning its absorption and harvesting efficiency. The numerical results demonstrate that the MS unit cell can absorb EM power, with near-perfect absorption of 90% in the frequency range of 5.14 GHz to 5.5 GHz under normal incidence and with a fractional bandwidth of 21%. The MS unit cell also achieves higher harvesting efficiency at various incident angles up to 60o. The design and analysis of an array of 4x4 double elliptical cylinder MS resonators integrated with a corporate feed network are also presented. The corporate feed network connects all the array elements to a single load, maximizing harvesting efficiency. The simulation and measurement results reveal an overall radiation to AC efficiency of about 90%, making it a prime candidate for energy harvesting applications.

Techno-functional characterization of gelatin extracted from the smooth-hound shark skins: Impact of pretreatments and drying methods.

Gelatin derived from marine by-products could be an interesting alternative to classic mammalian gelatin. The pretreatment and extraction conditions could influence the size of the resulting peptide chains and therefore their techno-functional properties. Thus, it is important to optimize the production process to get a gelatin for the appropriate applications. Skin pretreatment was done by microwaves or oven-drying and the extracted gelatin was dried by spray- or freeze-drying. Freeze-dried gelatin extracted from untreated skin (FGUS) had the highest gelatin yield (10.40%). Gelatin proximate composition showed that proteins were the major component (87.12-89.95%), while lipids showed the lowest contents (0.65-2.26%). Glycine showed the highest level (299-316/1000 residues) in the extracted gelatins. Proline and hydroxyproline residues of gelatins from untreated skin were significantly higher than those from pretreated skin-gelatin. FTIR spectra were characterized by peaks of the amide A (3430-3284 cm-1), B (3000-2931 cm-1), I (1636-1672 cm-1), II (1539-1586 cm-1) and III (1000-1107 cm-1). Spray-drying decreased the gelling properties of gelatins, since it reduced gelling and melting temperatures compared to freeze-drying. Skin pretreatment significantly reduced the gel strength of gelatin by about 50-100 g depending on the gelatin drying method. The FGUS showed better surface properties compared to other gelatins. The highest emulsion activity index (39.42 ± 1.02 m2/g) and foaming expansion (172.33 ± 2.35%) were measured at 3% FGUS. Therefore, the promising properties of freeze-dried gelatin derived from untreated skin, gave it the opportunity to be successfully used as a techno-functional ingredient in many formulations.

Amino acids and protein profiles of defatted camel and cow milk fractions: correlation with their in vitro antioxidant and antidiabetic activities.

Introduction: This work presents proteins, amino acids profiles and antioxidant and properties of camel and cow milk fractions produced using an integrated coagulation-centrifugation process. Methods: Antioxidant activity using DPPH radical scavenging assay; and antidiabetic activity antidiabetic activity using in vitro α-amylase inhibitory activity were assessed on defatted milk fractions and their extracts using water/ethanol or HCl/ethanol solvents. Protein profiles and amino acids composition were analyzed by high-performance liquid chromatography. Results and discussions: The predominant protein found in cow and camel milk was ß-casein in sodium caseinate, ß-lactoglobulin was found in the whey of cow milk, whereas α-lactalbumin was detected in the whey fractions of camel. The primary amino acids (comprising 1% to 5.2%) in skim milk and sweet whey milk were leucine, proline, and lysine. However, acid whey, casein fractions (sodium caseinate, and ß-casein) from both camel and cow milk exhibited elevated concentrations of histidine, leucine, lysine and proline (1.12 - 6.62%). Camel milk and its different protein fractions showed an interesting in vitro α-amylase inhibitory activity varying, according to different milk fractions and extraction methods, from 19.10 ± 1.40 to 97.40 ± 1.50%. Whatever the used method, the whey fractions from camel milk, both acid and sweet, displayed ed the highest antioxidant activity. Principal components analysis showed a positive correlation between the total phenols content, antioxidant (DPPH assay) and antidiabetic (α amylase inhibition test) activities within the milk fractions. Sweet and acid cow milk fractions seem to be the most promising for deeper exploration of in vivo biological activities and are promising milk derivatives for specific nutritional diet and/or functional food formulation.