What do faculties specializing in brain and neural sciences think about, and how do they approach, brain-friendly teaching-learning in Iran?

Objective: to investigate the perspectives and experiences of the faculties specializing in brain and neural sciences regarding brain-friendly teaching-learning in Iran. Methods: 17 faculties from 5 universities were selected by purposive sampling (2018). In-depth semi-structured interviews with directed content analysis were used. Results: 31 sub-subcategories, 10 subcategories, and 4 categories were formed according to the “General teaching model”. “Mentorship” was a newly added category. Conclusions: A neuro-educational approach that consider the roles of the learner’s brain uniqueness, executive function facilitation, and the valence system are important to learning. Such learning can be facilitated through cognitive load considerations, repetition, deep questioning, visualization, feedback, and reflection. The contextualized, problem-oriented, social, multi-sensory, experiential, spaced learning, and brain-friendly evaluation must be considered. Mentorship is important for coaching and emotional facilitation

Do optimization methods in deep learning applications matter?

With advances in deep learning, exponential data growth and increasing model complexity, developing efficient optimization methods are attracting much research attention. Several implementations favor the use of Conjugate Gradient (CG) and Stochastic Gradient Descent (SGD) as being practical and elegant solutions to achieve quick convergence, however, these optimization processes also present many limitations in learning across deep learning applications. Recent research is exploring higher-order optimization functions as better approaches, but these present very complex computational challenges for practical use. Comparing first and higher-order optimization functions, in this paper, our experiments reveal that Levemberg-Marquardt (LM) significantly supersedes optimal convergence but suffers from very large processing time increasing the training complexity of both, classification and reinforcement learning problems. Our experiments compare off-the-shelf optimization functions(CG, SGD, LM and L-BFGS) in standard CIFAR, MNIST, CartPole and FlappyBird experiments.The paper presents arguments on which optimization functions to use and further, which functions would benefit from parallelization efforts to improve pretraining time and learning rate convergence

Medication management in mental health: nurses’ perceptions of their work with service users and carers

Aim: This study aimed to ascertain registered mental health nurses’ perceptions of their role involving medication management interventions with clients and their carers. Medicine-related interventions include administration, assessment of therapeutic effect potential side-effects education, liaison with service users and influence in prescribing decisions. Design and methods: The study used a qualitative design. Ten registered nurses were interviewed. Findings: Three themes were identified all related to the nurse context of work, role and client and carer need: improved dialogue, information and education, and adherence issues. Practice implications: Nurses use their clinical expertise in medication management to help achieve optimum therapeutic outcomes

Gamified cognitive control training for remitted depressed individuals : user requirements analysis

Background: The high incidence and relapse rates of major depressive disorder demand novel treatment options. Standard treatments (psychotherapy, medication) usually do not target cognitive control impairments, although these seem to play a crucial role in achieving stable remission. The urgent need for treatment combined with poor availability of adequate psychological interventions has instigated a shift toward internet interventions. Numerous computerized programs have been developed that can be presented online and offline. However, their uptake and adherence are oftentimes low. Objective: The aim of this study was to perform a user requirements analysis for an internet-based training targeting cognitive control. This training focuses on ameliorating cognitive control impairments, as these are still present during remission and can be a risk factor for relapse. To facilitate uptake of and adherence to this intervention, a qualitative user requirements analysis was conducted to map mandatory and desirable requirements. Methods: We conducted a user requirements analysis through a focus group with 5 remitted depressed individuals and individual interviews with 6 mental health care professionals. All qualitative data were transcribed and examined using a thematic analytic approach. Results: Results showed mandatory requirements for the remitted sample in terms of training configuration, technological and personal factors, and desirable requirements regarding knowledge and enjoyment. Furthermore, knowledge and therapeutic benefits were key requirements for therapists. Conclusions: The identified requirements provide useful information to be integrated in interventions targeting cognitive control in depression

Methods of the survey of consumer finances

Consumer surveys

KASR: A Reliable and Practical Approach to Attack Surface Reduction of Commodity OS Kernels

Commodity OS kernels have broad attack surfaces due to the large code base and the numerous features such as device drivers. For a real-world use case (e.g., an Apache Server), many kernel services are unused and only a small amount of kernel code is used. Within the used code, a certain part is invoked only at runtime while the rest are executed at startup and/or shutdown phases in the kernel's lifetime run. In this paper, we propose a reliable and practical system, named KASR, which transparently reduces attack surfaces of commodity OS kernels at runtime without requiring their source code. The KASR system, residing in a trusted hypervisor, achieves the attack surface reduction through a two-step approach: (1) reliably depriving unused code of executable permissions, and (2) transparently segmenting used code and selectively activating them. We implement a prototype of KASR on Xen-4.8.2 hypervisor and evaluate its security effectiveness on Linux kernel-4.4.0-87-generic. Our evaluation shows that KASR reduces the kernel attack surface by 64% and trims off 40% of CVE vulnerabilities. Besides, KASR successfully detects and blocks all 6 real-world kernel rootkits. We measure its performance overhead with three benchmark tools (i.e., SPECINT, httperf and bonnie++). The experimental results indicate that KASR imposes less than 1% performance overhead (compared to an unmodified Xen hypervisor) on all the benchmarks.Comment: The work has been accepted at the 21st International Symposium on Research in Attacks, Intrusions, and Defenses 201

Binding an event to its source at encoding improves children\u27s source monitoring

Children learn information from a variety of sources and often remember the content but forget the source. While the majority of research has focused on retrieval mechanisms for such difficulties, the present investigation examines whether the way in which sources are encoded influences future source monitoring. In Study 1, 86 children aged 3 to 8 years participated in two photography sessions on different days. Children were randomly assigned to either the Difference condition (they were asked to pay attention to differences between the two events), the Memory control condition (asked to pay attention with no reference to differences), or the No-Instruction control (no special instructions were given). One week later, during a structured interview about the photography session, the 3-4 year-olds in the No-Instruction condition were less accurate and responded more often with \u27don\u27t know\u27 than the 7-8 year-olds. However, the older children in the Difference condition made more source confusions than the younger children suggesting improved memory for content but not source. In Study 2, the Difference condition was replaced by a Difference-Tag condition where details were pointed out along with their source (i.e., tagging source to content). Ninety-four children aged 3 to 8 years participated. Children in the Difference-Tag condition made fewer source-monitoring errors than children in the Control condition. The results of these two studies together suggest that binding processes at encoding can lead to better source discrimination of experienced events at retrieval and may underlie the rapid development of source monitoring in this age range