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Abstract The synchronisation in wireless cooperative relay networks is impossible to achieve in real environment utilising orthogonal space time block coding. There have been several approaches proposed to mitigate the effect of synchronisation among the relay nodes at the receiver. All have managed to reduce the inter‐symbol interference at the expense of low data rate with high detection complexity. Others achieved full data rate and high cooperative diversity using high decoding complexity that requires a feedback link. In this paper, a new approach is presented that reduces inter‐symbol interference, achieves full data rate and full cooperative diversity with low complexity. This uses a new efficient distributed orthogonal space time block coding design with a sub‐optimum detection scheme utilising dual relay nodes. This reduces the number of timing misalignments among the relay nodes and minimises the detection complexity. Furthermore, the new proposed method uses linear decoding process to achieve full data rate and full cooperative diversity without the need for any a feedback link. The analytical analysis and simulation results confirmed that sub‐optimum approach with the new efficient design are very effective at reducing the lack of synchronisation among the relay nodes at the destination node with low encoding and decoding complexities.

Multi-Agent Reinforcement Learning (MARL) has proven to be successful in cooperative assignments. MARL is used to investigate how autonomous agents with the same interests can connect and act in one team. MARL cooperation scenarios are explored in recreational cooperative augmented reality environments, as well as realworld scenarios in robotics. In this paper, we explore the realm of MARL and its potential applications in cooperative assignments. Our focus is on developing a multi-agent system that can collaborate to attack or defend against enemies and achieve victory withminimal damage. To accomplish this, we utilize the StarCraftMulti-Agent Challenge (SMAC) environment and train four MARL algorithms: Q-learning with Mixtures of Experts (QMIX), Value-DecompositionNetwork (VDN), Multi-agent Proximal PolicyOptimizer (MAPPO), andMulti-Agent Actor Attention Critic (MAA2C). These algorithms allow multiple agents to cooperate in a specific scenario to achieve the targeted mission. Our results show that the QMIX algorithm outperforms the other three algorithms in the attacking scenario, while the VDN algorithm achieves the best results in the defending scenario. Specifically, the VDNalgorithmreaches the highest value of battlewonmean and the lowest value of dead alliesmean. Our research demonstrates the potential forMARL algorithms to be used in real-world applications, such as controllingmultiple robots to provide helpful services or coordinating teams of agents to accomplish tasks that would be impossible for a human to do. The SMACenvironment provides a unique opportunity to test and evaluateMARL algorithms in a challenging and dynamic environment, and our results show that these algorithms can be used to achieve victory with minimal damage. [ABSTRACT FROM AUTHOR]

Solar and renewable energies applications got a great interest and attention in the last few decades. Problems related to CO2 emissions, air pollution, Ozone layer depletion, global warming and environment issues raise the necessity for getting a clean and safe energy. For this purpose, the Center for Solar Energy Studies (CSERS) in Libya conducted a huge research work in different applications for solar and renewable energies. One of these important activities is the Solar Gradient Solar Pond technology. It is an effective solar energy collection and storage system which presents a relatively simple and economic method of providing low grade energy with the advantage of annual storage cycle. This paper presents a general review on researches and studies on solar ponds that were conducted by CSERS research team. Tajoura’s Experimental Solar Pond (TESP) is designed as an experimental facility enabling the investigation of various aspects of pond performance. It is constructed by the Center for Solar Energy Studies, in joint cooperation with a Swiss company, with a surface area of about 830 m2, and a depth of 2.5 m, coupled with an evaporative pond of 105 m2 area and 1.5 m deep, equipped with all necessary equipments and measuring control system. The paper also shows the experience of operating MSF desalination unit coupled with TESP solar pond. Finally, other factors affecting the solar pond’s thermal stability were also discussed.

A solar powered desalination unit which is working on a humidification –dehumidification technique (HDH) is one of the most important techniques used in seawater desalination in remote and rural areas. It is easy to design, operate and maintain. In this paper, a theoretical study based on a design methodology for a solar assisted desalination unit working on a HDH principle under the prevailing conditions of Tajoura-Libya is carried out. The main target is to study the effect of different design and operating parameters that influence the performance of the unit and its productivity under different design scenarios; (spring, summer, autumn and winter). Results show that the productivity of the unit is increased with a corresponding increase in the inlet air mass flow rate to the solar air heater, inlet water mass flow rate to the humidifier and cooling water mass flow rate to the dehumidifier. A significant increase in the productivity of the unit is achieved when the initial water temperature and the initial mass of water inside the storage tank were increased. Moreover, Gained Output Ratio, GOR, values vary between (0.27 and 0.79) for winter and spring designs and (1.94 and 2.75) for autumn and summer designs respectively. In general, the productivity of the unit is estimated to be within a range from a minimum of (2 ~ 4) kg/m2.day, in winter to a maximum of (10 ~ 12) kg/m2.day, in summer, which makes it very convenient for using in rural and remote areas.

Objectives. To explore the magnitude and determinants of burnout among emergency physicians and nurses working at emergency departments of hospitals in Abha and Khamis Mushait cities. Subjects and Methods. A cross-sectional hospital-based study was conducted in emergency departments of hospitals in Abha and Khamis Mushait cities belonging to Ministry of Health. All physicians (n=95) and nurses (n=187) currently working at these sites were invited to participate in the study by filling a validated self-administered questionnaire including two main sections: personal and professional characteristics of physicians and nurses as well as Maslach burnout inventory (MBI) to assess the three components of the burnout syndrome: emotional exhaustion, depersonalization, and reduced personal accomplishment. Results. The study included 282 physicians and nurses. The age of more than half of them (54.3%) ranged between 31 and 35 years. Most of them (70.9%) were females. About two-thirds of the respondents (66.3%) were nurses while the remaining 33.7% were physicians. Majority of the emergency healthcare professionals (88.7%) had high emotional exhaustion. The prevalence of high depersonalization (cynicism) was 20.6% whereas that of low personal accomplishment was 41.1% among emergency healthcare professionals. The overall prevalence of burnout among healthcare professionals was 16.3%. Multivariate logistic regression analysis revealed that male healthcare professionals were at almost higher three-folded risk for developing burnout compared to females (aOR=2.76; 95% confidence interval (CI): 1.21-6.28, p=0.017)). Smokers were at higher significant risk for burnout compared to nonsmokers (aOR=15.37; 95% CI: 7.06-33.45, p

The Center for Solar Energy Research and Studies (CSERS) has a good experience in operating and evaluating the thermal performance of small scale 5 m3/day Multi-Stage Flushing (MSF) desalination plant connected to solar pond according to the local weather conditions of Tajoura area. However, a new project has been suggested to run the desalination plant with vacuum tubes solar thermal collectors utilizing available technology and experience. In this study an attempt was made to make the best use of readily available components to operate the MSF desalination unit with field of solar thermal collectors. Several configurations of collectors and tank arrangements were designed and examined through the use of simulation software, TRNSYS. The study has shown that the layout-3 (two 500 litre storage tanks each of them connected to 9x5 vacuum tube collectors) gives the best performance with an annual solar fraction over 77% at load temperature of 70 °C with flow rate of 2500 lit/hr, and over 68% at load temperature of 80 °C for working condition of 8 hours daily. The study has also shown that running the desalination plant for 24 hours a day reduces the solar fraction of the solar collector field to 25%

OBJECTIVE: Natural wound dressings composed of gelatin (GEL) and chitosan (CH) impregnated with bioactive compounds (Nigella sativa oil) were prepared and characterized to evaluate their potential application. MATERIALS AND METHODS: The formulated composite was subjected to γ-irradiation. In vitro, the ferric-reducing antioxidant power (FRAP) assay and antibiofilm activities were evaluated. In vivo, the tissue wound-healing process was studied by applying GEL-CH-Nigella in dorsal skin rabbit tissue. On days 7 and 14, the biochemical biomarker and histological analysis were determined. RESULTS: At 10 kGy, FRAP assays exhibited the highest antioxidant activity (380 mmol/ kg). A significant inhibition of anti-biofilm activity was observed against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) (p<0.01). Fourteen days post-surgery, a significant reduction in thiobarbituric acid-reactive compounds (TBARs) was observed compared to the GELCH group. Concerning oxidative stress status, GEL-CH-Nigella significantly improved superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities. A histological analysis revealed that GEL-CH-Nigella accelerated wound closure and improved collagenisation and enhanced epidermal tissue thickness. CONCLUSIONS: These results indicate that GEL-CH-Nigella wound dressing is a promising biomaterial for engineered tissue. [ABSTRACT FROM AUTHOR]

Redhwan A Al-Naggar,1 Mahfoudh Abdulghani,2,14 Muhamed T Osman,3 Waqar Al-Kubaisy,1 Aqil Mohammad Daher,15 Khairun Nain Bin Nor Aripin,4 Ali Assabri,5 Dawood A Al-Hidabi,6 Mohamed Izham B Mohamed Ibrahim,7 Ahmed Al-Rofaai,8 Hisham S Ibrahim,9 Hassanain Al-Talib,10 Alyaa Al-Khateeb,11 Gamil Qasem Othman,6 Qaid Ali Abdulaziz,6 Karuthan Chinna,12 Yuri V Bobryshev131Population Health and Preventive Medicine Department, Faculty of Medicine, Universiti Teknologi MARA, 2Pharmacology Department, International Medical School, Management and Science University, 3Department of Pathology, Faculty of Medicine & Defence Health, National Defence University of Malaysia, Kuala Lumpur, Malaysia, 4Faculty of Medicine and Health Sciences, Islamic Science University of Malaysia, Kuala Lumpur, Malaysia; 5Community Medicine Department, Faculty of Medicine and Health Science, Sana'a University, 6University of Science and Technology, Sana'a, Yemen; 7College of Pharmacy, Qatar University, Doha, Qatar; 8School of Biological Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia, 9Physiology Discipline-Faculty Of Medicine and Health Sciences-Universiti Sultan Zainal Abidin, Terengganu, Malaysia, 10Laboratory Medical Science Cluster, Drug Discovery & Health Community of Research, Faculty of Medicine, Universiti Teknologi MARA, 11Biochemistry and Molecular Medicine Discipline, Drug Discovery & Health Community of Research, Faculty of Medicine, Universiti Teknologi MARA, 12Social and Preventive Medicine, University Malaya, Kuala Lumpur, Malaysia; 13Faculty of Medicine, School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia; 14Pharmacology Department, Unaizah College of Pharmacy (UCP), Qassim University, Al Qassim, Saudi Arabia; 15Department of Community medicine, Faculty of Medicine & Defence Health, National Defence University of Malaysia, Kuala Lumpur, MalaysiaBackground: Students’ perceptions of their learning environment, by defining its strengths and weaknesses, are important for continuous improvement of the educational environments and curriculum. Therefore, the aim of this study was to explore students' perceptions of their learning environment, among medical students in Malaysia. Various aspects of the education environment were compared between year levels and sex.Methods: This cross-sectional study was conducted at the Management and Science University, Shah Alam, Malaysia in 2012. A total number of 438 medical students participated in this study, and the response rate was 87.6%. Data were analyzed using SPSS. Comparisons of the mean scores of Dundee Ready Education Environment Measure (DREEM) subscales were calculated. The t-test was used to determine statistically significant differences.Results: The majority of the study participants were female, Malay, and from year 3 (68.7%, 65.3%, and 55.7%; respectively). Analysis of each of the 50 items of the DREEM inventory showed that 47 items scored ranged between 2.00 and 3.00, and three items scored below 2.00. These were identified as problem areas in this medical school that are required to be critically addressed. The overall score showed that the medical students’ perceptions were positive. The students' perception toward educational environment was positive for all five DREEM subscales.Conclusion: The study found that, in general, the perceptions of the participants about the learning environment were positive. Nevertheless, the study also found there is a need for curriculum improvement in this school and identified priority areas for such improvement.Keywords: students’ perceptions, DREEM, Malaysia, learning environment, medical education

One of the main problems that negatively affect the operation of salt gradient solar ponds and influence its thermal stability is the maintenance of salt gradient profile. Evaporation pond (EP) is designed to generate the salt which is lost by upward salt diffusion from the lower convective zone (LCZ) of the solar pond. Another attractive method is the Evaporation Surface facility (ES). Regions with moderate to high precipitation favor Evaporation Surfaces over Evaporation Ponds. Dry climates will generally favor Evaporation Ponds for the brine re-concentration. This paper investigates the differences between (EP) and (ES) both as a source for salt brine generation by evaporation. The effect of (EP) depth on the area ratio and daily variations of salt concentrations for three years of operation is shown. Results show that evaporation can be a reasonable method for salt brine generation. Reducing the depth of (EP) improves the capability of (EP) for brine re-concentration. It also increases the (EP) surface area for the same quantity of saline water used. Therefore, ESs are more powerful than Eps in salt re-concentration.

The object detection technique depends on various methods for duplicating the dataset without adding more images. Data augmentation is a popular method that assists deep neural networks in achieving better generalization performance and can be seen as a type of implicit regularization. This method is recommended in the case where the amount of high-quality data is limited, and gaining new examples is costly and time-consuming. In this paper, we trained YOLOv7 with a dataset that is part of the Open Images dataset that has 8,600 images with four classes (Car, Bus, Motorcycle, and Person). We used five different data augmentations techniques for duplicates and improvement of our dataset. The performance of the object detection algorithm was compared when using the proposed augmented dataset with a combination of two and three types of data augmentation with the result of the original data. The evaluation result for the augmented data gives a promising result for every object, and every kind of data augmentation gives a different improvement. The mAP@.5 of all classes was 76%, and F1-score was 74%. The proposed method increased the mAP@.5 value by +13% and F1-score by +10% for all objects. [ABSTRACT FROM AUTHOR]

Autonomous agents can explore the environment around them when equipped with advanced hardware and software systems that help intelligent agents minimize collisions. These systems are developed under the term Artificial Intelligence (AI) safety. AI safety is essential to provide reliable service to consumers in various fields such as military, education, healthcare, and automotive. This paper presents the design of an AI safety algorithm for safe autonomous navigation using Reinforcement Learning (RL). Machine Learning Agents Toolkit (ML-Agents) was used to train the agent with a proximal policy optimizer algorithm with an intrinsic curiosity module (PPO+ ICM). This training aims to improve AI safety and minimize or prevent any mistakes that can cause dangerous collisions by the intelligent agent. Four experiments have been executed to validate the results of our research. The designed algorithm was tested in a virtual environment with four different models. A comparison was presented in four cases to identify the best-performing model for improving AI safety. The designed algorithm enabled the intelligent agent to perform the required task safely using RL. A goal collision ratio of 64% was achieved, and the collision incidents were minimized from 134 to 52 in the virtual environment within 30 min. [ABSTRACT FROM AUTHOR]

Background Cholinergic urticaria is uncommon and accounts for 10% of all young adults. To date, there is no effective therapy for cholinergic urticaria.Objective To determine the therapeutic efficacy of different drug combinations in the treatment of cholinergic urticaria.Patients and Methods The participants included in the study are in the age range of 16 to 29 years, with cholinergic urticaria of any duration as diagnosed by physicians. Patients were recruited from Asthma and Allergy Centers in Baghdad and Tikrit. The selected patients were divided randomly into 3 groups according to the treatment protocol. All patients completed screening before treatment.Results The study indicated that cholinergic urticaria was completely controlled in 30.4% of patients (group A) receiving 4 mg of chlorpheniramine maleate, half hour before the exercise, plus chlordiazopoxide (5 mg) and clindium bromide (2.5 mg) tablets, 3 times daily. However, cure rate was higher (83.1%) in patients (group B) receiving 4 mg of chlorpheniramine maleate (histadine), 3 times daily, plus 25 mg of maprotiline HCl (ludiomil), once daily at night. Furthermore, the complete cure rate was 85.4% in patients (group C) receiving 4 mg of chlorpheniramine maleate (histadine)3 times daily, plus 200 mg of cimetidine (tagadine), 3 times daily. The frequency of relapse was higher in group A (89%) as compared with group B (68.4%) and group C (23.5%) (P

Intrinsic motivation helps autonomous exploring agents traverse a larger portion of their environments. However, simulations of different learning environments in previous research show that after millions of timesteps of successful training, an intrinsically motivated agent may learn to act in ways unintended by the designer. This potential for unintended actions of autonomous exploring agents poses threats to the environment and humans if operated in the real world. We investigated this topic by using Unity's MachineLearningAgent Toolkit (ML-Agents) implementation of the Proximal Policy Optimization (PPO) algorithm with the Intrinsic Curiosity Module (ICM) to train autonomous exploring agents in three learning environments. We demonstrate that ICM, although designed to assist agent navigation in environments with sparse reward generation, increasing gradually as a tool for purposely training misbehaving agent in significantly less than 1 million timesteps.We present the following achievements: 1) experiments designed to cause agents to act undesirably, 2) a metric for gauging how well an agent achieves its goal without collisions, and 3) validation of PPO best practices. Then, we used optimized methods to improve the agent's performance and reduce collisions within the same environments. These achievements help further our understanding of the significance of monitoring training statistics during reinforcement learning for determining how humans can intervene to improve agent safety and performance. [ABSTRACT FROM AUTHOR]

Neutron transport codes are essential tools in nuclear reactor and shielding design. Transport codes implement an iterative technique that suffers from slow convergence while solving highly scattering problems. This necessitated the development of acceleration methods, among which, the diffusion synthetic acceleration (DSA) is the fastest and the only stable method.In this paper we present the development of “TDMGDSA”, a two dimensional multi-group diffusion synthetic accelerated neutron transport computer code. TDMGDSA implements DSA to solve the discrete ordinate equations in X–Y geometry for three spatial differencing schemes; the diamond, weighted diamond, and linear discontinuous differencing. TDMGDSA is the first to implement a linear form of DSA for the diamond differencing, and is one of the first to implement DSA for the weighted diamond and linear discontinuous differencing schemes. TDMGDSA has been tested and is shown to be working reliably.

The synchronisation in wireless cooperative relay networks is impossible to achieve in real environment utilising orthogonal space time block coding. There have been several approaches proposed to mitigate the effect of synchronisation among the relay nodes at the receiver. All have managed to reduce the inter‐symbol interference at the expense of low data rate with high detection complexity. Others achieved full data rate and high cooperative diversity using high decoding complexity that requires a feedback link. In this paper, a new approach is presented that reduces inter‐symbol interference, achieves full data rate and full cooperative diversity with low complexity. This uses a new efficient distributed orthogonal space time block coding design with a sub‐optimum detection scheme utilising dual relay nodes. This reduces the number of timing misalignments among the relay nodes and minimises the detection complexity. Furthermore, the new proposed method uses linear decoding process to achieve full data rate and full cooperative diversity without the need for any a feedback link. The analytical analysis and simulation results confirmed that sub‐optimum approach with the new efficient design are very effective at reducing the lack of synchronisation among the relay nodes at the destination node with low encoding and decoding complexities. [ABSTRACT FROM AUTHOR]

Endogenous pectin methylesterase (PME) is the enzyme responsible for phase separation and cloud loss in orange juice (OJ) manufacturing. The effect of kiwi's PME inhibitor (PMEI), nanomilling, and pasteurization on OJ quality was evaluated. The microbial quality, PME activity, OJ separation, pH, ascorbic acid content and the sensory characteristics of the juice were followed during 5 weeks storage (4°C). PMEI as freeze‐dried kiwi powder (0.3%, w/w) succeeded in inhibiting 89.3% of the OJ PME without affecting the microbial and the sensory quality. Nanomilling of OJ pulp, to prepare nano‐particles OJ (NPOJ), reduced the initial microbial load by 1.65 and 1.83 log for psychrotrophs and yeasts and molds, respectively; significantly (p <.05) inactivated 40.9% of the residual PME activity and the juice separation was significantly reduced by 48.3% (after 14 days of storage). Nanomilling exhibited no effect on OJ pH, but slight (p <.05) decrease in ascorbic acid content was noted. The combination of PMEI with NPOJ resulted in improved OJ stability with reduced separation to 36.4% of that of control. Such combination also allowed to use a lower pasteurization temperature at lower exposure time (60°C/5 min) needed to obtain new NPOJ with comparable high quality as fresh OJ and which has a shelf life of 3 weeks (4°C). [ABSTRACT FROM AUTHOR]