Many-Sources Large Deviations for Max-Weight Scheduling

In this paper, a many-sources large deviations principle (LDP) for the transient workload of a multi-queue single-server system is established where the service rates are chosen from a compact, convex and coordinate-convex rate region and where the service discipline is the max-weight policy. Under the assumption that the arrival processes satisfy a many-sources LDP, this is accomplished by employing Garcia's extended contraction principle that is applicable to quasi-continuous mappings. For the simplex rate-region, an LDP for the stationary workload is also established under the additional requirements that the scheduling policy be work-conserving and that the arrival processes satisfy certain mixing conditions. The LDP results can be used to calculate asymptotic buffer overflow probabilities accounting for the multiplexing gain, when the arrival process is an average of \emph{i.i.d.} processes. The rate function for the stationary workload is expressed in term of the rate functions of the finite-horizon workloads when the arrival processes have \emph{i.i.d.} increments.Comment: 44 page

Ransomware Detection Using Federated Learning with Imbalanced Datasets

Ransomware is a type of malware which encrypts user data and extorts payments in return for the decryption keys. This cyberthreat is one of the most serious challenges facing organizations today and has already caused immense financial damage. As a result, many researchers have been developing techniques to counter ransomware. Recently, the federated learning (FL) approach has also been applied for ransomware analysis, allowing corporations to achieve scalable, effective detection and attribution without having to share their private data. However, in reality there is much variation in the quantity and composition of ransomware data collected across multiple FL client sites/regions. This imbalance will inevitably degrade the effectiveness of any defense mechanisms. To address this concern, a modified FL scheme is proposed using a weighted cross-entropy loss function approach to mitigate dataset imbalance. A detailed performance evaluation study is then presented for the case of static analysis using the latest Windows-based ransomware families. The findings confirm improved ML classifier performance for a highly imbalanced dataset.Comment: 6 pages, 4 figures, 3 table

First-line therapy for post-traumatic stress disorder : a systematic review of cognitive behavioural therapy and psychodynamic approaches

Background: Despite evidence supporting cognitive behavioural therapy (CBT) based interventions as the most effective approach for treating posttraumatic stress disorder (PTSD) in randomised control trials, alternative treatment interventions are often used in clinical practice. Psychodynamic (PDT) based interventions are one example of such preferred approaches, this is despite comparatively limited available evidence supporting their effectiveness for treating PTSD. Aims: Existing research exploring effective therapeutic interventions for PTSD includes trauma-focused CBT involving exposure techniques. The present review sought to establish the treatment efficacy of CBT and PDT approaches, and considers the potential impact of selecting PDT-based techniques over CBT-based techniques for the treatment of PTSD.Results: The evidence reviewed provided examples supporting PDT-based therapy as an effective treatment for PTSD, but confirmed CBT as more effective in the treatment of this particular disorder. Comparable dropout rates were reported for both treatment approaches, suggesting that relative dropout rate should not be a pivotal factor in the selection of a PDT approach over CBT for treatment of PTSD.Conclusion/Implications: The need to routinely observe evidence-based recommendations for effective treatment of PTSD is highlighted and factors undermining practitioner engagement with CBT-based interventions for the treatment of PTSD are identified

Roadmap on digital holography [Invited]

This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography

Bayesian signaling game based efficient security model for MANETs

Game Theory acts as a suitable tool offering promising solutions to security-related concerns in Mobile Ad Hoc Networks (i.e., MANETs). In MANETs, security forms a prominent concern as it includes nodes which are usually portable and require significant coordination between them. Further, the absence of physical organisation makes such networks susceptible to security breaches, hindering secure routing and execution among nodes. Game Theory approach has been manipulated in the current study to achieve an analytical view while addressing the security concerns in MANETs. This paper offers a Bayesian-Signaling game model capable of analysing the behaviour associated with regular as well as malicious nodes. In the proposed model, the utility of normal nodes has been increased while reducing the utility linked to malicious nodes. Moreover, the system employs a reputation system capable of stimulating best cooperation between the nodes. The regular nodes record incessantly to examine their corresponding nodes’ behaviours by using the belief system of Bayes-rules. On its comparison with existing schemes, it was revealed that the presented algorithm provides better identification of malicious nodes and attacks while delivering improved throughput and reduced false positive rate

Fatigue life of machined components

A correlation between machining process and fatigue strength of machined components clearly exists. However, a complete picture of the knowledge on this is not readily available for practical applications. This study addresses this issue by investigating the effects of machining methods on fatigue life of commonly used materials, such as titanium alloys, steel, aluminium alloys and nickel alloys from previous literature. Effects of turning, milling, grinding and different non-conventional machining processes on fatigue strength of above-mentioned materials have been investigated in detail with correlated information. It is found that the effect of materials is not significant except steel in which phase change causes volume expansion, resulting in compressive/tensile residual stresses based on the amounts of white layers. It is very complex to identify the influence of surface roughness on the fatigue strength of machined components in the presence of residual stresses. The polishing process improves the surface roughness, but removes the surface layers that contain compressive residual stresses to decrease the fatigue strength of polished specimens. The compressive and tensile residual stresses improve and reduce fatigue strength, respectively. Grinding process induces tensile residual stresses on the machined surfaces due to high temperature generation. On the other hand, milling and turning processes induce compressive residual stresses. High temperature non-conventional machining generates a network of micro-cracks on the surfaces in addition to tensile residual stresses to subsequently reduce fatigue strength of machined components. Embedded grits of abrasive water jet machining degrade the fatigue performance of components machined by this method

What is the value of orthodontic treatment?

Orthodontic treatment is as popular as ever. Orthodontists frequently have long lists of people wanting treatment and the cost to the NHS in England was £258m in 2010-2011 (approximately 10% of the NHS annual spend on dentistry). It is important that clinicians and healthcare commissioners constantly question the contribution of interventions towards improving the health of the population. In this article, the authors outline some of the evidence for and against the claims that people with a malocclusion are at a disadvantage compared with those without a malocclusion and that orthodontic treatment has significant health benefits. The authors would like to point out that this is not a comprehensive and systematic review of the entire scientific literature. Rather the evidence is presented in order to stimulate discussion and debate

PI3K/AKT/mTOR signaling transduction pathway and targeted therapies in cancer

Abstract The PI3K/AKT/mTOR (PAM) signaling pathway is a highly conserved signal transduction network in eukaryotic cells that promotes cell survival, cell growth, and cell cycle progression. Growth factor signalling to transcription factors in the PAM axis is highly regulated by multiple cross-interactions with several other signaling pathways, and dysregulation of signal transduction can predispose to cancer development. The PAM axis is the most frequently activated signaling pathway in human cancer and is often implicated in resistance to anticancer therapies. Dysfunction of components of this pathway such as hyperactivity of PI3K, loss of function of PTEN, and gain-of-function of AKT, are notorious drivers of treatment resistance and disease progression in cancer. In this review we highlight the major dysregulations in the PAM signaling pathway in cancer, and discuss the results of PI3K, AKT and mTOR inhibitors as monotherapy and in co-administation with other antineoplastic agents in clinical trials as a strategy for overcoming treatment resistance. Finally, the major mechanisms of resistance to PAM signaling targeted therapies, including PAM signaling in immunology and immunotherapies are also discussed.