The Effectiveness of a Training Program using Neuro - Linguistic Programming (NLP) to Reduce Test Anxiety in Consideration of Biological Feedback

This research aims to study the influence of NLP training program in reducing test anxiety by analyzing biological feedback. This empirical study assessed pre- and post-tests of a study sample consisting of 30 students aged 19.6 years that were diagnosed with high test anxiety. The students were divided into an experimental group and a control group; each with 15 students. The experimental group was trained on 24 units of NLP strategies for 3 months, i.e. 2 units per week with each unit lasting for 40-60 minutes. The anxiety test scale was applied on par with observations of vital biological changes (heart rate and blood pressure). The results showed statistically significant differences in the average scores of test anxiety before and after applying the aforementioned program mean ± SD 198 ± 11.9 (P< 0.05) for the post-test results were better than the pre-test ones. Moreover, there were statistically significant differences between the experimental and control groups indicating better results achieved by the experimental group when they took the post-test. In sum, the NLP program had a highly positive influence in reducing test anxiety and undesirable biological changes when applied to the experimental grou

Dyeing of cotton fabrics using reactive dyes by microwave irradiation technique

Dyeing of cotton fabrics with reactive dyes using exhaustion method has been done using microwave irradiation technique. Different parameters such as dye concentration, alkali concentration, salt concentration, power of microwave used and liquor ratio have been studied and the results are compared with conventional technique. It is observed that the microwave technique saves 90 min in the dyeing time 75% in the salt used and 20% in alkali used, indicating the saving in time, energy and money. The overall fastness properties to rubbing, washing, light and perspiration for the dyed samples are ranging from very good to excellent

A large scale analysis of mHealth app user reviews

The global mHealth app market is rapidly expanding, especially since the COVID-19 pandemic. However, many of these mHealth apps have serious issues, as reported in their user reviews. Better understanding their key user concerns would help app developers improve their apps’ quality and uptake. While app reviews have been used to study user feedback in many prior studies, many are limited in scope, size and/or analysis. In this paper, we introduce a very large-scale study and analysis of mHealth app reviews. We extracted and translated over 5 million user reviews for 278 mHealth apps. These reviews were then classified into 14 different aspects/categories of issues reported. Several mHealth app subcategories were examined to reveal differences in significant areas of user concerns, and to investigate the impact of different aspects of mhealth apps on their ratings. Based on our findings, women’s health apps had the highest satisfaction ratings. Fitness activity tracking apps received the lowest and most unfavourable ratings from users. Over half of users who reported troubles leading them to uninstall mHealth apps gave a 1-star rating. Half of users gave the account and logging aspect only one star due to faults and issues encountered while registering or logging in. Over a third of users who expressed privacy concerns gave the app a 1-star rating. However, only 6% of users gave apps a one-star rating due to UI/UX concerns. 20% of users reported issues with handling of user requests and internationalisation concerns. We validated our findings by manually analysing a sample of 1,000 user reviews from each investigated aspect/category. We developed a list of recommendations for mHealth apps developers based on our user review analysis.Omar Haggag, John Grundy, Mohamed Abdelrazek, Sherif Hagga

HYBRID DEEP LEARNING APPROACH FOR VEHICLE’S RELATIVE ATTITUDE ESTIMATION USING MONOCULAR CAMERA

Relative pose estimation using a monocular camera is one of the most common approaches for aiding vehicle&rsquo;s navigation. It involves determining the position and orientation of a vehicle relative to its surroundings using only a single camera. This can be achieved through four main steps: feature detection and matching, motion estimation, filtering and optimization, and scale estimation. Feature tracking involves detecting and tracking distinctive visual features in the environment, such as corners or edges, and using their relative motion to estimate the camera's movement. This approach can be prone to errors due to feature detection and tracking difficulties, as well as issues with moving objects, occlusions, and changes in lighting conditions. These typical computer vision approaches are computationally intensive and may require significant processing power as well, which limits their real time application. This paper proposes a hybrid deep neural network approach for estimating the relative attitude of a vehicle using a monocular camera to aid in vehicle navigation. The proposed neural network adopts a relatively shallow architecture to minimize the computational cost and to meet the real-time requirements of low-cost processing systems. The network is trained using the KITTI dataset and can estimate the relative attitude of the vehicle with a RMSE of relative orientation of 0.017 degrees per frame. The processing time of the proposed approach is around 28 ms per frame including both the tracking and network prediction steps, which is significantly faster than the typical estimation pipelines. The results show that the proposed approach is a viable alternative to conventional computer vision methods and can significantly reduce computational costs, deal with the confusing scenarios of the moving objects while maintaining a good accuracy in estimating ego-motion

pH-Sensitive nanoparticles containing 5-fluorouracil and leucovorin as an improved anti-cancer option for colon cancer

Parenteral administration of chemotherapeutic drugs, 5-fluorouracil (5-FU) and leucovorin (LV), is commonly used to treat large bowel carcinomas such as colon cancer (CC) and colorectal carcinoma (CRC). Our study aims to design a novel nanoparticulate drug-delivery vehicle for oral use capable of colon-specific release. A modified double-emulsion solvent evaporation method was used in the preparation of pH-responsive Eudargit S100 polymeric nanoparticles, loaded with 5-FU/LV combination (5-FU/LV-loaded Eudargit S100 NPs). Our optimized drug-loaded NP showed a pH-responsive drug release and exhibited significantly more cytotoxic actions in cancer-cell lines than free drugs. These findings open the way for conducting clinical trials for colon malignancies treated with nanoparticles

Spectrophotometric determination of the sulfhydryl containing drug mesna

AbstractFour simple and sensitive spectrophotometric methods were developed for the determination of the sulfhydryl containing drug mesna (MSN). Methods I and II rely on nucleophilic aromatic substitution reactions using two UV tagging reagents namely: 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole (NBD-Cl) for method I and 2,4-dinitrofluorobenzene (DNFB) for method II. Both reactions took place in alkaline buffered medium and the obtained yellowish products were measured at 414 and 332nm for methods I and II, respectively. Methods III and IV are indirect spectrophotometric methods based on the suppressive effect of MSN on the absorption of two ternary complex systems which are composed of 1,10-phenanthroline, silver and eosin for method III and 1,10-phenanthroline, silver and bromopyrogallol red for method IV. The decrease in absorbance of the ternary complexes was measured at 547 and 635nm for methods III and IV, respectively. All the experimental parameters affecting these reactions were carefully studied and optimized. The methods were validated as per the ICH guidelines. The methods were applicable in the linearity ranges 4–18μg/mL for method I, 4–16μg/mL for method II, 0.25–2.25μg/mL for method III and 0.25–1.75μg/mL for method IV. The proposed methods were successfully applied for the analysis of MSN in its commercial ampoules and no interference was encountered from the present excipients as indicated by the satisfactory percentage recoveries. The results obtained were in a good agreement with those obtained from a previously published method of the investigated drug

Use of some plant essential oils as post-harvest botanical fungicides in the management of anthracnose disease of mango fruits (Mangifera indica L.) caused by Colletotrichum gloeosporioides

Abstract Mango suffers fro m several diseases at all stages of its life. Anthracnose, caused by the fungus Colletotrichum gleosporioides is the most important post harvest disease of mango. The aim of this study was to test the possibility of the use of some plant essential oils i.e. Basel oil (Ocimum basilicum), Orange oil (Citrus sinensis), Lemon oil (Citrus Medica) and Mustard oil (Brassica juncea L.) to reduce postharvest losses induced by Colletotrichum gloeosporioides (Penz.) in mango fruits. In this study, the antifungal activity of essential oils under in vitro condition were assayed by tested various concentrations (0, 50,100 and 150µg/ ml)) and under in vivo condition by used different essential oil concentrations (0, 250,500 and 1000pp m) on inoculated mango fruits. Results of the present study showed that orange oil at all tested concentrations were a significant reducing the fungal linear growth if co mpared with other tested essential oils. At low concentration 50 (µg/ ml) orange oil caused 10.0% reduction in fungal growth, while at 100 (µg/ ml) caused 72.2% and at high tested concentration 150 (µg/ ml) caused a comp lete reduction in myceliu m linear growth of pathogenic fungus. Meanwhile, at low tested concentration 50 (µg/ ml), mustard oil caused a highly significantly reduction of the percentage of fungal spore germination by 70.8 % followed by basil oil by 64.7%. Results of in vivo studies showed that, at low concentration 250 ppm, mustard oil caused a highly reduction of anthracnose incidence of mango fru its by 79.9% fo llo wed by basil o il with 66.7% .On the other hand, orange and lemon oil at low concentration (250ppm) were showed a highly effect to reducing the percentage of rotting fruit tissue by 84.5 and 75.0%, respectively if co mpared with other treat ments and un-treated fruits

A Novel Approach in Pigment Printing Using Nano-keratin Based Binder

This study is devoted to preparation and characterization of nano-keratin based binder (NKBB) from cheap renewable natural resources, namely coarse Egyptian wool or feather. The prepared NKBB is utilized as a biodegradable, environment-friendly and relatively cheap binder in textile pigment printing of polyester, pure polyacrylic, viscose, polyester/viscose, and polyester/acrylic fabrics. Different concentrations of the prepared NKBB as well as its mixture with commercially produced one are used in the pigment printing paste. The colour strength of the printed fabrics as well as their fastness properties to light, washing, and perspiration are evaluated. The effect of the used binder on the bending stiffness of the printed fabrics is also assessed. Results show that the NKBB gives almost the same colour strength and fastness properties as the commercial binder with improved stiffness of the printed samples in relation to that printed with commercial one

Relativistic Compact Objects in Isotropic Coordinates

We present a matrix method for obtaining new classes of exact solutions for Einstein's equations representing static perfect fluid spheres. By means of a matrix transformation, we reduce Einstein's equations to two independent Riccati type differential equations for which three classes of solutions are obtained. One class of the solutions corresponding to the linear barotropic type fluid with an equation of state $p=\gamma \rho$ is discussed in detail.Comment: 9 pages, no figures, accepted for publication in Pramana-Journal of Physic