Mobile eye-tracking in external environments remains challenging, despite recent advances in eye-tracking software and hardware engineering. Many current methods fail to deal with the vast range of outdoor lighting conditions and the speed at which these can change. This confines experiments to artificial environments where conditions must be tightly controlled. Additionally, the emergence of low-cost eye tracking devices calls for the development of analysis tools that enable non-technical researchers to process the output of their images. We have developed a fast and accurate method (known as “SET”) that is suitable even for natural environments with uncontrolled, dynamic and even extreme lighting conditions. We compared the performance of SET with that of two open-source alternatives by processing two collections of eye images: images of natural outdoor scenes with extreme lighting variations (“Natural”); and images of less challenging indoor scenes (“CASIA-Iris-Thousand”). We show that SET excelled in outdoor conditions and was faster, without significant loss of accuracy, indoors. SET offers a low cost eye-tracking solution, delivering high performance even in challenging outdoor environments. It is offered through an open-source MATLAB toolkit as well as a dynamic-link library (“DLL”), which can be imported into many programming languages including C# and Visual Basic in Windows OS (www.eyegoeyetracker.co.uk).

Background: Attention deficit and hyperactivity disorder (ADHD) has a profound impact on lives of thousands of children and their families. Objectives: Aim of this study was to determine effectiveness of training for mothers, on these children. Materials and Methods: In this quasi-experimental research, 30 mothers were randomly divided into control and experimental groups and the experimental group received Barkley management skills training in 9 sessions. Results: Findings showed that anxiety in children of trained mothers was decreased and self-esteem was increased. Conclusions:The training program for mothers can be an effective method for treatment of psychological disorders in children with ADHD.

Introduction Radiation therapy is one of the standard methods in the treatment of breast cancer. Radiotherapy-induced dermatitis (RID) is a common complication of radiotherapy (RT) resulting in less tolerance in RT and even discontinuation of treatment. Timolol is a β-adrenergic receptor antagonist that presents the best wound healing effects on both chronic and incurable wound healing. Topical forms of timolol could be effective in the prevention of RID due to the role of β-adrenergic receptors in skin cells and keratinocyte migration, as well as the anti-inflammatory effect of timolol. However, no placebo-controlled randomized trial is available to confirm its role. The current trial aimed to evaluate the efficacy of topical timolol 0.5% (w/w) on the RID severity and patients' quality of life (QOL). Method Patients aged older than 18 years with positive histology confirmed the diagnosis of invasive and localized breast cancer were included. Patients were randomized based on the random number table to receive each of the interventions of timolol 0.5% (w/w) or placebo topical gels from the first day of initiation of RT and for 6 weeks, a thin layer of gel twice daily. Patients were asked to use a thin layer of gel for at least two hours before and after radiation therapy. Primary outcomes were acute radiation dermatitis (ARD) grade using Radiation Therapy Oncology Group and the European Organization for Research and Treatment of Cancer (RTOG/EORTC) scale and severity of desquamation based on Common Terminology Criteria for Adverse Events (CTCAE), version 5.0. Secondary outcomes were QOL based on Skindex16 (SD-16), maximum grade of ARD, and time of initial RD occurrence. Results A total of 64 female patients with an age range of 33 to 79 years were included. The means (SD) of age were 53.88 (11.02) and 54.88 (12.48) in the control and timolol groups, respectively. Considering the RTOG/EORTC and CTCAE scores the difference between groups was insignificant (P-Value = 0.182 and P-Value = 0.182, respectively). In addition, the mean (SD) of time of initial RID occurrence in placebo and timolol groups were 4.09 (0.588) and 4.53 (0.983) weeks, respectively (P-Value = 0.035). The maximum grade of RID over time was significantly lower in the timolol group. During the study period, 75.0% of patients in placebo groups had grade 2 of ARD while in the timolol group it was 31.3% (P-Value = 0.002). QoL was not significantly different between groups (P-Value = 0.148). Conclusion Although the topical formulation of timolol, 0.5% (w/w), was found to reduce the average maximum grade of ARD and increase the mean (SD) time of initial RID occurrence, it showed no effect on ARD, severity, and QOL. However, future clinical trials should be performed to assess timolol gel formulation in larger study populations. Trial registration https://irct.ir/ IRCT20190810044500N11 (17/03/2021).

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Due to increasing number of network attacks, it is highly crucial to equip networks with an intrusion detection system (IDS). These systems must be able to deal with today's high speed and large scale networks. In this paper we propose a distributed IDS that performs both data capturing and data analyzing in a distributed fashion. This distributed mechanism enables our system to effectively operate within large scale and high traffic rate networks. We developed a grouping mechanism which divides computers in the network into subsets of computers with a leader and a few members. Subsequently, using a data sharing mechanism we were able to detect distributed attacks. Our data sharing mechanism added an overhead on the network traffic which is negligible compared to the overall network traffic. We simulated our method in NS2 simulation environment. Then we compared our proposed system with a centralized IDS in terms of detection rate, memory usage and packet loss rate. Results showed that our system's performance was better despite of some extra load imposed by distribution of data processing.

In order to attack to a network, an attacker first must find vulnerability points of the target network. This task is done through scanning. There are many methods of scan detection. Most of these methods are based on thresholding. Setting a proper threshold value is crucial and depends on many parameters such as network structure and time window. In this study we proposed a new scan detection method based on genetic algorithm (GA). This method has two phases. In the first phase we separate normal traffic from suspicious traffic and send only suspicious traffic to the second phase. This way the overhead of the process in the second phase is decreased considerably. In the second phase we aim to detect attacks with respect to two optimum parameters of threshold and memory. We compared our method with snort. Results showed that our method achieves better performance in both hit rate and false alarm rate.