Modelling the moisture effect on the rate of spread of fire in a leaf-like fuel element

In this study, the effect of fuel moisture content (FMC) on the pyrolysis, ignition, and rate of drying processes of a leaf-like fuel element is numerically investigated. To start the ignition, an upward hot airflow is placed under the leaf-like fuel source. The dry fuel was considered as cellulose. The current study is validated against published experimental data, using the time history of fuel mass loss measurement. The effect of FMC on the mass fraction of oxygen is also investigated. The transient solver of FireFOAM, which uses the Large Eddy Simulation (LES), is used to perform the numerical simulations. The results confirm that an increase in the amount of fuel moisture content leads to a decrease in the rate of spread of the fire and an increase in the drying process time. It is also found that during both drying and pyrolysis process, different parts of a selected fuel element have different temperatures. This is mainly due to the decrease of moisture concentration near the ignition point. Results showed that at t= 6.5 s the volumetric average temperature of the solid fuel for the case with FMC 26%, is 642 K while for FMC of 34%, this temperature is 605 K

A Descriptive Analysis of Job Satisfaction among Faculty Members: Case of Private Vocational and Technical Education Institutions, Baabda, Mount Lebanon, Lebanon

The study aimed to assess Job Satisfaction (JS) among teaching staff in private vocational and technical education institutions in Mount Lebanon, Lebanon. The study is descriptive and analytic, using a sample of 200 teachers from 13 schools and institutes chosen according to the coordinated random method. A questionnaire created and validated by Warr, Cook, and Wall is adopted to measure job satisfaction. This questionnaire includes personal information like job status, educational level, number of years of work, monthly income, age, gender, and social status. Using a seven-level Likert scale, it also contains 15 items to measure various dimensions of job satisfaction (internal and external factors). Results show a low overall mean of 4.69 out of 7 with a standard deviation of 1.15 for job satisfaction, based on data analysis using the SPSS program. Also, the majority of respondents are not satisfied with the wage received (the overall mean of job satisfaction=3.83, with a standard deviation of 2.00); there is a low level of JS among teachers concerning the degree of job security (mean=4.13 with a standard deviation of 1.91); there are no statistically significant differences in JS among teachers due to demographics. Capitalizing on the results, recommendations are made

Supplemental irrigation management of rainfed grapevines under drought conditions using the CropSyst model

Aim of study: To determine how much water should be used and when it should be applied in rain-fed grapevine using a cropping system simulation model (CropSyst), and also the economic analysis of supplemental irrigation for rainfed grapevine.Area of study: This study was conducted at the School of Agriculture, Shiraz University, Shiraz, Iran, in 2012, 2013 and 2014.Material and methods: The CropSyst model was calibrated to predict the rainfed yields of ‘Askari’ and ‘Yaghooti’ grapevines in different climates using four amounts of SI: 250 L (I1), 500 L (I2), 1000 L (I3) and 0 (I4), five SI times: single in March (T1), single in April (T2), single in March + single in April (T3), single in May (T4) and single in June (T5).Main results: Treatment T3 increased the average simulated yield of ‘Askari’ by 15% to 40% at regions with P/ETo>0.6, 17% to 61% at 0.2<P/ETO<0.6, and 26% to 61% at P/ETO<0.2, while in ‘Yaghooti’ it increased about 2% to 41% at regions with P/ETo>0.6, 4% to 36% at 0.2<P/ETO<0.6 and 2% to 26% at P/ETO<0.2. By increasing the water price by 30% and 50%, net benefits for the ‘Askari’ decreased by about 31% and 54%, while 6% and 18%, for ‘Yaghooti’ respectively.Research highlights: The CropSyst model can successfully predict soil water content and grapevine yields. Application of SI in May increased significantly the grapevine yield as compared to other SI times

Design and Construction of Zana Robot for Modeling Human Player in Rock-paper-scissors Game using Multilayer Perceptron, Radial basis Functions and Markov Algorithms

In this paper, the implementation of artificial neural networks (multilayer perceptron [MLP] and radial base functions [RBF]) and the upgraded Markov chain model have been studied and performed to identify the human behavior patterns during rock, paper, and scissors game. The main motivation of this research is the design and construction of an intelligent robot with the ability to defeat a human opponent. MATLAB software has been used to implement intelligent algorithms. After implementing the algorithms, their effectiveness in detecting human behavior pattern has been investigated. To ensure the ideal performance of the implemented model, each player played with the desired algorithms in three different stages. The results showed that the percentage of winning computer with MLP and RBF neural networks and upgraded Markov model, on average in men and women is 59%, 76.66%, and 75%, respectively. Obtained results clearly indicate a very good performance of the RBF neural network and the upgraded Markov model in the mental modeling of the human opponent in the game of rock, paper, and scissors. In the end, the designed game has been employed in both hardware and software which include the Zana intelligent robot and a digital version with a graphical user interface design on the stand. To the best knowledge of the authors, the precision of novel presented method for determining human behavior patterns was the highest precision among all of the previous studies

A Review article of Streptococcus pyogenes infection: Rick factors, prevention and management strategies

Background:-Streptococcus pyogenes is an exclusively human pathogen. This bacterial species is responsible for a large variety of infections. Objective: This review identified published articles on the risk factors, prevention and control strategies for streptococcus diseases. Material and methods: A systematic search was carried out to identify papers published on the Web of Science, PubMed, Scopus, and Google Scholar electronic databases in an attempt to provide basic information about Streptococcus infections, potential risks for their spread, and treatment and prevention strategies. Results: The more common methods for Streptococcus pyogenes transmission are through respiratory droplets, skin lesions brought on by Streptococcus pyogenes contact with infected objects or devices. Another potential mode is foodborne transmission but more research is needed to determine this infection route. Native communities, and those of low socio-economic status worldwide were found particularly susceptible to Streptococcus diseases, as well as children, older adults and those with impaired immune system. Those groups are susceptible to Streptococcus pyogenes infections and their complications with higher infectious rates in educational institutions, hospitals, over-crowding and the continuous increase in social contact. The importance of improving living conditions and personal and hand hygiene is one of the techniques in the management and prevention of Streptococcus pyogenes infections. Infection control methods must be highlighted with greater precision. Conclusion: Prevention and control measures should target the improvement of living conditions, and personal and hand hygiene. Adherence to infection prevention and control practices should be emphasized in high-risk settings

Comorbidities among infertile women at NKST hospital Mkar-Gboko, North-Central Nigeria

Background:  Infertility, a common, non-fatal ailment, is sometimes associated with substantial comorbidity that can add adverse outcomes during treatment or pregnancy and increase costs of care. This study aims to assess the magnitude and pattern of comorbidities in infertile Nigerian women.Method: This descriptive retrospective study was undertaken at NKST Hospital Mkar-Gboko, Nigeria, from 1st January 2005 to 31st July 2013. Clinic records of patients who attended the gynaecological outreach clinic were retrieved and analyzed using descriptive statistics and test of associations with Microsoft Excel 2013.  Jos University Teaching Hospital gave ethical clearance.Results: 1,926 women seen during the study period, 1030 (53.5%) presented for infertility care. 941 (91.4%) women had complete records, among them, 476 (50.5%) met the inclusion criteria, and their records were analyzed. The mean age of the women was 32.6±6.0 years with a range of 20 to 53 years, see Table1. There were 52 comorbid conditions among the 476 women. The comorbidities included uterine myoma, previous appendectomy/pelvic surgeries, genital tract infections/retroviral disease, hypertension, obesity and diabetes, among others, see Table 4. Table 2 and 3 shows there is a significant statistical association between comorbidity type, age, parity, duration of infertility and symptoms complex between infertile women and comorbidities (p<0.05).Conclusion: Comorbidities that can influence treatment and pregnancy outcomes are common among infertile women in central Nigeria. This finding strongly supports the routine assessment of women for comorbidities during infertility care for appropriate multidisciplinary management and counselling

Digital Mapping of Surface and Subsurface Soil Organic Carbon and Soil Salinity Variation in a Part of Qazvin Plain (Case Study: Abyek and Nazarabad Regions)

IntroductionKnowledge of the spatial distribution of soil salinity and soil organic carbon (SOC) leads to obtaining valuable information that is effective in decision-making for agricultural activities. More than a third of the world's land is affected by salt, which threatens the growth and production of crops, and prevents the development of sustainable agriculture. The high electrical conductivity (EC) content in soils poses significant challenges in arid and semi-arid regions, greatly impacting agricultural production. Saline and sodic soils often exhibit high levels of sodium which is a key characteristic. The presence of sodium ions leads to the destabilization of soil aggregates and the dispersion of soil particles resulting in the closure of soil pores. Consequently, unfavorable changes occur in the soil physical, chemical, and biological properties increasing its susceptibility to water and wind erosion. Additionally, high sodium levels can lead to the decomposition of soil organic carbon (SOC). SOC is crucial for water retention, cation exchange, and nutrient availability, making its reduction in agricultural soils a significant threat to sustainable soil management. Therefore, the investigation of soils in terms of EC and SOC contents and their spatial distribution is of great importance to support decision-makers in agricultural development planning to reduce challenges related to food security in arid and semi-arid regions.Materials and MethodsThis study was conducted with the aim of investigating the EC and SOC in topsoil (0-30 cm) and subsoil (30-60 cm) layers using four machine learning (ML) algorithms namely, random forest (RF), decision tree (DTr), support vector regression (SVR) and artificial neural network (ANN) performed in Qazvin Plain. The study area includes a part of agricultural lands and natural areas of Alborz and Qazvin provinces, between the Nazarabad and Abyek cities in Iran. This region with an area of 60,000 hectares is located at latitude 35° 54´ to 36° 54´ to the north and 50° 15´ to 50° 39´ to the east. This research was carried out in four stages including (i) soil sampling and measuring the physical and chemical properties of the soil and preparation of environmental covariates from a digital elevation model (DEM) with spatial resolution 12.5 m and Landsat 8 satellite imagery with spatial resolution 30 m by SAGA GIS and ENVI software, (ii) spatial modeling of soil EC and SOC in the topsoil and subsoil layers by the RF, SVR, ANN, and DTr ML algorithms, (iii) evaluating the efficiency of the ML algorithms and determining the relative importance of environmental covariates, and (iv) preparation of spatial prediction maps of EC and SOC in the topsoil (0-30 cm) and subsoil (30-60 cm) layers in the study area.Results and Discussion         The result of the spatial prediction maps of EC showed that the studied area has non-saline to very saline soils up to a depth of 60 cm. It is also possible that the EC equivalent shows a decreasing trend in soil salinity with a depth from 6.05 to 5.55 ds/m from the topsoil to the subsoil layer. The highest amount of SOC was observed in the surface layer equal to 3.3%. Globally SOC content decreased from the surface (average of 0.84%) to depth (average of 0.4%). The high spatial variability of SOC showed that the soils of the study area are affected by management activity. Environmental covariates were extracted as a proxy of topography and remote sensing indices including elevation, diffuse Insolation (Diffuse), Multi-Resolution Index of Valley Bottom Flatness (MrVBF), Normalized Differences Vegetation Index (NDVI), SAGA wetness index (SWI) and wind Effect (WE) were used as representatives of soil formation factors. The topography parameters, including the elevation, diffuse insolation, and Multi-Resolution Index of Valley Bottom Flatness, were most closely related to EC and SOC variations in each topsoil and subsoil layer. Elevation can be justified around 50% and 35% of EC and 28.56% and 29.47% of SOC variations in the topsoil and subsoil layers, respectively, followed by the diffuse variable can succeed to justified 19.7% and 25.1% of EC and 27.28% and 27.67% of SOC spatial variations in the topsoil and subsoil layers, respectively.The results confirmed that the RF was recognized as outperforming the ML model for predicting EC in the topsoil (R2 =0.74, RMSE =0.36, and nRMSE= 0.07), as well as predicting SOC in topsoil and subsoil layers (R2= 90 and R2=0.80), followed by the DTr for predicting EC (R2 0.77, RMSE/0.9, and nRMSE 0.17) in the subsoil layer in comparison other models. Conclusion       The RF (Random Forest) and DTr (Decision Tree) models incorporating topographic parameters demonstrated satisfactory accuracy in predicting the variation of topsoil and subsoil electrical conductivity (EC) and soil organic carbon (SOC) in the study area. Topography plays a crucial role in soil formation, and elevation-based topographic attributes are commonly used as key predictors in digital soil mapping projects. The variability in topography influences water flow and sedimentation processes which, in turn, affects soil development and the spatial distribution of soil properties. The resulting soil maps can be valuable tools for decision-making programs related to soil management in the region

Clinical Prediction of Blood Parameters Associated with Breast, Colon, Thyroid, Ovarian, and Prostate Cancer

Cancer is a cellular change caused by uncontrolled cell growth and division. This disease develops from the growth of abnormal cells that have the potential to invade or spread to other parts of the body. The aim of this study was to investigate the relationship between blood parameters (e.g., Mean corpuscular volume (MCV), Mean corpuscular hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC), Haemoglobin&nbsp;(HGB), White&nbsp;Blood&nbsp;Cell&nbsp;(WBC), and Red&nbsp;Blood&nbsp;Cell (RBC)) and different types of cancer. Breast cancer, thyroid gland cancer, ovarian cancer, testicular cancer, brain tumors as well as other types of cancer are based on the cell of the tissue found on or in the body. Any of these types of cancer are associated with a variety of health issues that put the patient's life in danger. Performing the complete blood count (CBC) test prior to or after a cancer diagnosis is necessary as abnormalities in the body can cause blood component rates to either increase or decrease, depending on the type of cancer, the patient's physiological mechanism, and the structural component. Since the CBC test belongs to hematology, drawing a blood sample and putting it into the anticoagulant tube for testing were preferred. In this study, the blood components of almost all patients were normal except for a few of them which may be due to other medical and biological factors. There is a significant relationship between blood parameters and cancer types.&nbsp

Burgeoning Polymer Nano Blends for Improved Controlled Drug Release: A Review

With continual rapid developments in the biomedical field and understanding of the important mechanisms and pharmacokinetics of biological molecules, controlled drug delivery systems (CDDSs) have been at the forefront over conventional drug delivery systems. Over the past several years, scientists have placed boundless energy and time into exploiting a wide variety of excipients, particularly diverse polymers, both natural and synthetic. More recently, the development of nano polymer blends has achieved noteworthy attention due to their amazing properties, such as biocompatibility, biodegradability and more importantly, their pivotal role in controlled and sustained drug release in vitro and in vivo. These compounds come with a number of effective benefits for improving problems of targeted or controlled drug and gene delivery systems; thus, they have been extensively used in medical and pharmaceutical applications. Additionally, they are quite attractive for wound dressings, textiles, tissue engineering, and biomedical prostheses. In this sense, some important and workable natural polymers (namely, chitosan (CS), starch and cellulose) and some applicable synthetic ones (such as poly-lactic-co-glycolic acid (PLGA), poly(lactic acid) (PLA) and poly-glycolic acid (PGA)) have played an indispensable role over the last two decades for their therapeutic effects owing to their appealing and renewable biological properties. According to our data, this is the first review article highlighting CDDSs composed of diverse natural and synthetic nano biopolymers, blended for biological purposes, mostly over the past five years; other reviews have just briefly mentioned the use of such blended polymers. We, additionally, try to make comparisons between various nano blending systems in terms of improved sustained and controlled drug release behavior