CHEMICAL AND TECHNOLOGICAL EVALUATION OF SOME SWEET POTATO VARIETIES

This investigation was carried out to evaluate the chemical characteristics of new eight sweet potato varieties namely, CEMSA 74-228, SANTO AMARA, NC 1525 and KEMB 37 (creamy flesh) and JAPON TRESMESINO, LO 323, TAINUNG 64 and BEAUREGARD (yellow flesh ), and study their suitability for processing. The obtained re-sults reveal that SANTO AMARA and KEMB37 varieties were the best ones having the highest content of chemical constituents compared with those of the other studied creamy flesh sweet pota-to varieties. Moreover, 140 days from planting was the best harvesting time that achieved the highest chemical characteristics. All selected creamy sweet potato varieties had adequate miner-als contents especially, KEMB 37 followed by NC 1525 and CEMSA 74-228 then SANTO AMARA varieties that could be considered good sources of minerals for human nutrition. Yellow flesh sweet potatoes have been recognized as valuable sources of carbohydrates, protein, dietary fibers and could be considered as good sources of both vitamin C and total carotenoids. Moreover, TAINUNG 64 and LO 323 were found to be good sources of β-carotene (pro- vitamin A). The more suitable har-vesting time for yellow sweet potato varieties, which recorded the highest levels of essential ele-ments, was 140 days from planting. On the other hand, TAINUNG 64 variety could be considered the best one compared to the other examined vari-ties. The most suitable varieties that having good quality attributes for processing were SANTO AMARA and KEMB 37 as creamy flesh and TAINUNG 64 and BEAUREGARD as yellow flesh sweet potato varieties. Moreover, these va-rieties could be successfully used in the produc-tion of new and untraditional sweet potato prod-ucts

Effect of Protocol of Care on Clinical Outcomes of Patients with Chest Tube Post Cardiothoracic Surgery

Cardiothoracic surgery is a surgical specialty, which deals with the diagnosis and management of surgical conditions of the heart, lungs and esophagus (1) .Chest tube (CT) is an invasive procedure which inserted post cardiothoracic surgery to facilitate lung expansion and allowing  the drainage of fluids from the chest cavity. Aim: this study aimed to evaluate the effect of protocol of care on clinical outcomes of patients with chest tube post cardiothoracic surgery. Materials and method a quasi-experimental research design was conducted at Cardiothoracic Surgery Department at Tanta University hospital. A purposive sample of 80 adult patients with chest tube based on statistical power analysis were selected and divided into two equal group 40 patients in each group as follows: Group 1: (Study group): consist of 40 adult patients were received protocol of care implemented by the researcher. Group 2: (Control group): consists of 40 adult patients who were received routine nursing care by hospital nursing staff. Three Tools were used to collect the data .Tool (I) Biosocio-demographic characteristics. Tool (II) Chest tube assessment, Tool (III) Pain assessment. Results:- The mean duration of ICU stay in control group (6.77) was higher than in the study group (4.97) days, more than half (52.6%)of the patients in the control group at the 7th day of the study had elevated body temperature comparing to none  in the study group, nearly two third (62.5%) of patients has  a positive culture swab in the control group at the  7th day of the study group ,compared to about  third(35%) of patients in the study group. More than half of patients (52.5%) in the control group had a severe pain during removal of chest tube compared to small percentage (5.0%) in the study group. Conclusions and recommendations:-Protocol of nursing care which was composed of deep breathing and coughing   exercises, sterile technique during chest tube dressing, and cold application, are recommended for all cardiothoracic surgical patients with chest tube. Keywords: Protocol of Care, Clinical Outcomes, Cardiothorathic Surger

Predicting market performance using machine and deep learning techniques

Today, forecasting the stock market has been one of the most challenging issues for the “artificial intelligence” AI research community. Stock market investment methods are sophisticated and rely on analyzing massive volumes of data. In recent years, machine-learning techniques have come under increasing scrutiny to assess and improve market predictions over traditional approaches. The observation in time is due to their dependence. Their predictions are crucial tasks in data mining and have attracted great interest and considerable effort over the past decades. Tackling this challenge remains difficult due to the inherent characteristics of time series data, including its high dimensionality, large volume of data, and constant updates. Exploration of Machine Learning and Deep Learning methods undertaken to enhance the effectiveness of conventional approaches. In this document, we aim precisely to forecast the performance of the stock market at the close of the day by applying various machine-learning algorithms on the two data sets “CoinMarketCap, CryptoCurrency” and thus analyze the predictions of the architectures

Machine learning algorithms for forecasting and categorizing euro-to-dollar exchange rates

Forecasting changes in foreign exchange rates is a well-explored and widely recognized area within finance. Numerous research endeavors have delved into the utilization of methods in machine learning to analyze and predict movements in the foreign exchange market. This work employed several machine-learning techniques such as Adaboost, logistic regression, gradient boosting, random forest classifier, bagging, Gaussian naïve Bayes, extreme gradient boosting classifier, decision tree classifier, and our approach (we have combined three models: logistic regression, random forest classifier, and Gaussian naive Bayes). Our objective is to predict the most advantageous times for purchasing and selling the euro about the dollar. We integrated a range of technical indicators into the training dataset to enhance the precision of our techniques and strategy. The outcomes of our experiment demonstrate that our approach outperforms alternative methods, achieving superior prediction performance. Our methodology yielded an accuracy of 0.948. This study will empower investors to make informed decisions about their future EUR/USD transactions, helping them identify the most advantageous times to buy and sell within the market

Dietary clenbuterol modifies the expression of genes involved in the regulation of lipid metabolism and growth in the liver, skeletal muscle, and adipose tissue of Nile tilapia (Oreochromis niloticus)

The current study aimed to evaluate whether clenbuterol, a β2-adrenergic agonist, supplementation in Nile tilapia (Oreochromis niloticus) diets can influence growth and blood parameters. Besides, assessment of adipogenic genes as fatty acid synthase (FAS) and lipoprotein lipase (LPL) which is a key enzyme in the regulation of the flux of fatty acids in liver, muscle, and adipose tissue as well as muscle growth-regulating genes as myostatin (MYO) in muscle and insulin-like growth factor-1 (IGF-1) in liver. The fish were allocated into three equal groups; control group that fed basal diet only and the other two groups fed a basal diet containing clenbuterol at two doses 5 ppm and 10 ppm/kg diet for 30 consecutive days. Results revealed that clenbuterol supplementation significantly increased body weight, decreased liver, spleen and abdominal fat weights, and decreased total circulatory cholesterol and triacylglycerol levels. Moreover, clenbuterol inhibits lipogenesis by downregulation of FAS gene expression by dose and time-dependent manner in the liver while enhanced lipolysis in both the liver and in the adipose tissue. Moreover, lipolysis was reduced in muscle by dose 10 ppm on day 30. Furthermore, clenbuterol presented higher gene expression of MYO and IGF-1 in muscle and liver respectively by dose 5 ppm at day 15 on the other hand, these findings were reversed by day 30 compared with control. In conclusion, clenbuterol efficacy was apparent in a dose and time response pattern to boost growth and reduce fat deposition rates, indicating for the first time that clenbuterol has a profitable growth impact on Nile tilapia