Eco-structured biosorptive removal of basic fuchsin using pistachio nutshells: A definitive screening design-based approach

Biosorptive removal of basic fuchsin (BF) from wastewater samples was achieved using the recycled agro-wastes of pistachio nut shells (PNS). Seven adsorbents were developed; raw shells (RPNS) and the thermally activated biomasses at six different temperatures (250–500 °C). Two measures were implemented to assess the performance of utilized adsorbents; %removal (%R) and adsorption capacity (qe). RPNS proved to be the best among the tested adsorbents. A smart approach, definitive-screening design (DSD) was operated to test the impact of independent variables on the adsorption capacity of RPNS. pH, adsorbent dose (AD), dye concentration (DC), and stirring time (ST), were the tested variables. Analysis of variance (ANOVA), control, and quality charts helped establishing regression model. Characterization was performed using Fourier- transform infrared (FT-IR)/Raman spectroscopies together with thermogravimetric analysis (TGA) and scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDX) analyses. The surface area and other textural properties were determined using the Brunauer Emmett-Teller (BET) analysis. Removal of 99.71% of BF with an adsorption capacity of 118.2 mg/g could be achieved using a factorial blend of pH 12, 100 mg/50 mL of RPNS, and 250 ppm BF for 20 min. Equilibrium studies reveal that the adsorption is physisorption with adsorption energy of 7.45 kJ/mol as indicated by Dubinin-Radushkevich (DR) and Langmuir isotherms. Moreover, adsorption follows pseudo-second-order kinetics with respect to BF and is controlled by the adsorption rate.This work was made possible by Qatar University Internal Student Grant [QUST-2-CAS-2019-18] from Qatar University. The statements made herein are solely the responsibility of the authors. The publication of this article was funded by the Qatar National Library.Scopu

Study The Applications of Water Deficiency Levels and Ascorbic Acid Foliar on Growth Parameters and Yield of Summer Squash Plant (Cucurbita pepo L.)

Two field experiments study during 2015 and 2016 summer seasons on sandy loam soil under drip irrigation system by Nile river water, at the Agricultural Research and Production Station National Research Centre, El- Nubaria region, EL- Beheira Governorate,  Egypt. This study focused on the applications of different water deficiency levels (100, 80 and 60% of F.C. i.e. field capacity) and ascorbic acid (AsA) spraying foliar application with different concentrations (0, 50 and 100 ppm) as antioxidant on growth parameters and yield as well as photosynthetic pigments content of summer squash plants (Cucurbitapepo L.cv. Eskandrani). Results indicated that, decreasing water levels caused a significant reduction in the all tested growth and yield parameters, i.e., canopy weight, root weight, number of leaves, leaves fresh weight and leaf area as well as photosynthetic pigments content (total chl., and carotenoids), total yield, fruit weight and length. While increasing ascorbic acid spraying foliar application levels as antioxidant significantly increased the aforementioned parameters in the two seasons as compared with control. On the other hand, decreasing water levels caused a significant increasing in leaf proline content, leaf cell sap osmotic pressure, dry matter % and fruit TSS in the two growing seasons as compared with control.Keywords: water stress, water deficiency, ascorbic acid, antioxidant, growth, yield, summer squash plant and Cucurbita pepo.

Protective effects of some fruit juices with low-fat diet on rat testis damaged by carbon tetrachloride: A genetic and histological study

Oxidative stress, free radical, lipid peroxidation and antioxidant have become a common expression with most disease and methods for protection. Carbon tetrachloride (CCl4) is an industrial solvent which has destructive effects on a cell while most fruit juices have antioxidant effects. The aim of this study was to investigate the protective role of fruit juice on testis after toxic effect with CCl4 through oxidative stress with basal diet and low-fat diet. Seventy-five male albino rats were used for this study in which the juices of three fresh fruit, yellow apples (Malus domestica, L.), red grapes containing seeds (Vitis vinifera, L.) and pomegranates (Punica granatum, L.) were used as therapeutic agents. Histological sections of testis indicated that low-fat diet has obvious effects than basal diet in both the low-fat diet with CCl4 "LdC""con++", LdC with grape juice 2 ml "grpL2", LdC with pomegranate juice 2 ml "pomL2" and hyper effect in LdC with pomegranate juice 4 ml "pomL4" while it was equal in effect with basal diet in the other treatments. Low-fat diet gave significant effects (about 75% recovery in con++, LdC with Apple juice 2 ml and 4 ml "appL2, appL4" , LdC with grape juice 4 ml "grpL4" and pomL2) while 25% began to recover as shown in basal diet with pomegranate juice 4 ml "pomB4" and grpL2. Treatment of rats with pomegranate juice ameliorated the toxic effects of CCl4 with low-fat diet on Semi-random RAPD-DNA profile. Low-fat diet with fruit juice had positive effect against toxicity induced by CCl4 in testes of rats on the level of histological and DNA-RAPD studies.Key words: CCl4, rat testis, yellow apples, red grapes, pomegranates, low-fat diet, oxidative stress

Shoulder Pain among Rehabilitated Spinal Cord Injured Persons Using Manually Propelled Wheelchairs in the Gaza Strip: A Survey

Shoulder pain among paraplegic persons has negative effects on their lives. The prevalence of shoulder pain among persons with spinal cord injury (SCI) varies from 30% to 70% in different studies and may be related to repetitive use of the shoulder during self-care and wheelchair-related activities. Purpose: This study focused on the prevalence of shoulder pain and examined its effects on activities of daily living and social participation, and on functional, work and recreational or athletic activities. It also aimed to detect the degree of satisfaction with shoulder functioning wheelchair users who were paraplegic due to spinal cord injury, in the Gaza strip. Methods: Cross sectional study design was used to collect data from 80 persons with paraplegia, post rehabilitation, who were still using manual wheelchairs (MWC) for ambulation. After giving informed consent, the selected persons were interviewed directly in their homes, and filled questionnaires which included the demographic data, Wheelchair User’s Shoulder Pain Index (WUSPI) and Shoulder Rating Questionnaire (SRQ). Results: The prevalence rate of shoulder pain among paraplegics who use manual wheelchairs was 62%. Pushing a wheelchair for 10 minutes or more, and propulsion up ramps or inclines outdoors were the most common activities that caused and exacerbated shoulder pain. Sixty four percent from among the study sample mentioned that they had no limitation in shoulder-using ability during daily personal and household activities, while the rest experienced different degrees of limitation. Seventy-four percent reported no limitation during recreational or athletic activities

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Human hand posture detection and recognition is a challenging problem in computer vision. We introduce an algorithm that is capable to recognize hand posture in a sophisticated background. The system combines two algorithms to achieve better detection rate for hand. Recently Viola et al. in have introduced a rapid object detection scheme; we use this approach to detect the hand posture in the first set of consecutive frames. The chromatic color distribution of skin can be found within this cluster. As the shape of hand posture keep changing in the subsequent frames, the skin regions updated dynamically. The classification of hand posture makes use of static feature for locating and counting hand fingers. Kalman Filter is used to track the face and hand blobs based on their position. In the experiments, we have tested our system in various environments, and results showed effectiveness of the approach

The development of automated spatial and temporal measurement system for lab-scale local scour

The spatial and temporal measurements of local scour around bridge piers provide the quantification of local scouring process. Most studies on a laboratory scale faced difficulties in obtaining a holistic local spatial variability around bridge pier, especially for continuous small time interval. Long experimental period, which could take up to few days, does not permit a consistent time interval spatial scour measurement due in particular to the physical constraints that exist under laboratory conditions. This study proposed an automated, cost-effective system which is capable of detecting changes in both spatial and temporal local scour. The system allows measurement to be made by using data recorder at an adjustable distance (± 0.1 mm) and angle (± 0.1˚) from the original position, which is programmed and controlled with an Arduino, which is an open source microcontroller with multiple capability of controlling electrical components such as motors and sensors. When the data recorder is in position, data is automatically captured and sequentially saved at a particular spatial interval. In this study, a web camera was used as a data recorder to capture images in the azimuthal plane for a one-hour interval. Images were captured for 30 seconds per measurement per position. The system was set up to monitor and measure the temporal and spatial local scour continuously in an 80-hour experiment. Results show that the location of maximum scour depth varied for different time intervals, and migrated from downstream to upstream of the pier. The rate of scour decreased as duration of experiment was increased. The system was able to provide a holistic view of both spatial and temporal variability in the development of local scour on a laboratory scale

Recycling of Date Pits Into a Green Adsorbent for Removal of Heavy Metals: A Fractional Factorial Design-Based Approach

Date pits (DPs) have been recycled into a low-cost adsorbent for removing of selected heavy metals (HMs) from artificially contaminated aqueous solutions. Adsorption of targeted HMs, both by raw date pits (RDP) and burnt date pits (BDP) was tested. Results showed that BDP is more efficient as an adsorbent and mostly adsorbing Cu(II). A novel approach; fractional factorial design (2k−p – FrFD) was used to build the experimental pattern of this study. The effects of four factors on the maximum percentage (%) of removal (Y) were considered; pH, adsorbent dose (AD), heavy metal concentration (HMC), and contact time (CT). Statistically significant variables were detected using Pareto chart of standardized effects, normal and half-normal plots together with analysis of variance (ANOVA) at 95.0 confidence intervals (CI). Optimizing (maximizing) the percentage (%) removal of Cu(II) by BDP, was performed using optimization plots. Results showed that the factors: pH and adsorbent dose (AD) affect the response positively. Scanning electron microscopy (SEM) was used to study the surface morphology of both adsorbents while fourier-transform infrared spectroscopy (FTIR) was employed to get an idea on the functional groups on the surface and hence the adsorption mechanism. Raman spectroscopy was used to characterize the prepared adsorbents before and after adsorption of Cu(II). Equilibrium studies show that the adsorption behavior differs according to the equilibrium concentration. In general, it follows Langmuir isotherm up to 155 ppm, then Freundlich isotherm. Free energy of adsorption (ΔGad) is −28.07 kJ/mole, when equilibrium concentration is below 155 ppm, so the adsorption process is spontaneous, while (ΔGad) equals +17.89 kJ/mole above 155 ppm, implying that the process is non-spontaneous. Furthermore, the adsorption process is a mixture of physisorption and chemisorption processes, which could be endothermic or exothermic reactions. The adsorption kinetics were described using a second order model.Funding. This work was made possible by UREP award [UREP 20-116-1-020] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors

Breast Milk Macronutrients in Relation to Infants’ Anthropometric Measures

BACKGROUND: Breast milk (BM) is the main nutritional source for newborns before they are capable to eat and consume other foods. BM has carbohydrates, lipids, complex proteins, and other biologically active components which have a direct effect on infant growth. AIM: The aim of the study was to correlate anthropometric data of the infant to macronutrients in BM (fat, protein, and carbohydrates) and to find some modifiable issues affecting macronutrient contents of BM for the benefits of upcoming infants. METHODS: One hundred breastfeeding mothers participated in the study, they were recruited from the outpatient clinic, El Demerdash Hospital, Ain Shams University, from September 2019, to December 2019. BM was expressed by an electric pump, macronutrient content was assessed. Anthropometric data of the babies and mothers were obtained, gestational age, parity, age of the women, and the route of birth were recorded. RESULTS: For the macronutrients content of milk, a positive significant correlation was observed between BM fat, protein, and lactose. Infants’ body mass index (BMI) was negatively related to the fat content of BM, while no relation was found between BMI and protein or lactose content of the milk. BM fat content was negatively correlated with gestational age and maternal age. Positive correlations were found between BMI and protein, lactose and infant age. Protein content was negatively correlated with parity. No impact of infant’s sex on BM composition and as regards maternal diet, high protein consumption leading to increase BM protein content. CONCLUSIONS: The current study confirms that BM macronutrient composition has a wide variability; this variability is associated with each macronutrient, respectively. To improve BM composition, one could aim for improving the nutritional balance in lactating women, especially for protein intake. More well-designed longitudinal studies about factors that influence human milk compositions are warranted

Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia

Rainfall is considered as one of the major components of the hydrological process; it takes significant part in evaluating drought and flooding events. Therefore, it is important to have an accurate model for rainfall forecasting. Recently, several data-driven modeling approaches have been investigated to perform such forecasting tasks as multi-layer perceptron neural networks (MLP-NN). In fact, the rainfall time series modeling involves an important temporal dimension. On the other hand, the classical MLP-NN is a static and has a memoryless network architecture that is effective for complex nonlinear static mapping. This research focuses on investigating the potential of introducing a neural network that could address the temporal relationships of the rainfall series. <br><br> Two different static neural networks and one dynamic neural network, namely the multi-layer perceptron neural network (MLP-NN), radial basis function neural network (RBFNN) and input delay neural network (IDNN), respectively, have been examined in this study. Those models had been developed for the two time horizons for monthly and weekly rainfall forecasting at Klang River, Malaysia. Data collected over 12 yr (1997–2008) on a weekly basis and 22 yr (1987–2008) on a monthly basis were used to develop and examine the performance of the proposed models. Comprehensive comparison analyses were carried out to evaluate the performance of the proposed static and dynamic neural networks. Results showed that the MLP-NN neural network model is able to follow trends of the actual rainfall, however, not very accurately. RBFNN model achieved better accuracy than the MLP-NN model. Moreover, the forecasting accuracy of the IDNN model was better than that of static network during both training and testing stages, which proves a consistent level of accuracy with seen and unseen data