Multi-Agent Deep Reinforcement Learning-Driven Mitigation of Adverse Effects of Cyber-Attacks on Electric Vehicle Charging Station

An electric vehicle charging station (EVCS) infrastructure is the backbone of transportation electrification. However, the EVCS has myriads of exploitable vulnerabilities in software, hardware, supply chain, and incumbent legacy technologies such as network, communication, and control. These standalone or networked EVCS open up large attack surfaces for the local or state-funded adversaries. The state-of-the-art approaches are not agile and intelligent enough to defend against and mitigate advanced persistent threats (APT). We propose the data-driven model-free distributed intelligence based on multiagent Deep Reinforcement Learning (MADRL)-- Twin Delayed Deep Deterministic Policy Gradient (TD3) -- that efficiently learns the control policy to mitigate the cyberattacks on the controllers of EVCS. Also, we have proposed two additional mitigation methods: the manual/Bruteforce mitigation and the controller clone-based mitigation. The attack model considers the APT designed to malfunction the duty cycles of the EVCS controllers with Type-I low-frequency attack and Type-II constant attack. The proposed model restores the EVCS operation under threat incidence in any/all controllers by correcting the control signals generated by the legacy controllers. Also, the TD3 algorithm provides higher granularity by learning nonlinear control policies as compared to the other two mitigation methods. Index Terms: Cyberattack, Deep Reinforcement Learning(DRL), Electric Vehicle Charging Station, Mitigation.Comment: Submitted to IEEE Transactions on Smart Grid

Line tension and structure of smectic liquid crystal multilayers at the air-water interface

At the air/water interface, 4,-8-alkyl[1,1,-biphenyl]-4-carbonitrile (8CB) domains with different thicknesses coexist in the same Langmuir film, as multiple bilayers on a monolayer. The edge dislocation at the domain boundary leads to line tension, which determines the domain shape and dynamics. By observing the domain relaxation process starting from small distortions, we find that the line tension is linearly dependent on the thickness difference between the coexisting phases in the film. Comparisons with theoretical treatments in the literature suggest that the edge dislocation at the boundary locates near the center of the film, which means that the 8CB multilayers are almost symmetric with respect to the air/water interface.Comment: 21 pages, 6 figure

The vaginal-PVPA: A vaginal mucosa-mimicking in vitro permeation tool for evaluation of mucoadhesive formulations

Drug administration to the vaginal site has gained increasing attention in past decades, highlighting the need for reliable in vitro methods to assess the performance of novel formulations. To optimize formulations destined for the vaginal site, it is important to evaluate the drug retention within the vagina as well as its permeation across the mucosa, particularly in the presence of vaginal fluids. Herewith, the vaginal-PVPA (Phospholipid Vesicle-based Permeation Assay) in vitro permeability model was validated as a tool to evaluate the permeation of the anti-inflammatory drug ibuprofen from liposomal formulations (i.e., plain and chitosan-coated liposomes). Drug permeation was assessed in the presence and absence of mucus and simulated vaginal fluid (SVF) at pH conditions mimicking both the healthy vaginal premenopausal conditions and vaginal infection/pre-puberty/post-menopause state. The permeation of ibuprofen proved to depend on the type of formulation (i.e., chitosan-coated liposomes exhibited lower drug permeation), the mucoadhesive formulation properties and pH condition. This study highlights both the importance of mucus and SVF in the vaginal model to better understand and predict the in vivo performance of formulations destined for vaginal administration, and the suitability of the vaginal-PVPA model for such investigations

Developing a scalable training model in global mental health: pilot study of a video-assisted training Program for Generalist Clinicians in Rural Nepal.

BackgroundIn low- and middle-income countries, mental health training often includes sending few generalist clinicians to specialist-led programs for several weeks. Our objective is to develop and test a video-assisted training model addressing the shortcomings of traditional programs that affect scalability: failing to train all clinicians, disrupting clinical services, and depending on specialists.MethodsWe implemented the program -video lectures and on-site skills training- for all clinicians at a rural Nepali hospital. We used Wilcoxon signed-rank tests to evaluate pre- and post-test change in knowledge (diagnostic criteria, differential diagnosis, and appropriate treatment). We used a series of 'Yes' or 'No' questions to assess attitudes about mental illness, and utilized exact McNemar's test to analyze the proportions of participants who held a specific belief before and after the training. We assessed acceptability and feasibility through key informant interviews and structured feedback.ResultsFor each topic except depression, there was a statistically significant increase (Δ) in median scores on knowledge questionnaires: Acute Stress Reaction (Δ = 20, p = 0.03), Depression (Δ = 11, p = 0.12), Grief (Δ = 40, p < 0.01), Psychosis (Δ = 22, p = 0.01), and post-traumatic stress disorder (Δ = 20, p = 0.01). The training received high ratings; key informants shared examples and views about the training's positive impact and complementary nature of the program's components.ConclusionVideo lectures and on-site skills training can address the limitations of a conventional training model while being acceptable, feasible, and impactful toward improving knowledge and attitudes of the participants

Controlling magnetic exchange and anisotropy by non-magnetic ligand substitution in layered MPX3 (M = Ni, Mn; X = S, Se)

Recent discoveries in two-dimensional (2D) magnetism have intensified the investigation of van der Waals (vdW) magnetic materials and further improved our ability to tune their magnetic properties. Tunable magnetism has been widely studied in antiferromagnetic metal thiophosphates MPX3. Substitution of metal ions M has been adopted as an important technique to engineer the magnetism in MPX3. In this work, we have studied the previously unexplored chalcogen X substitutions in MPX3 (M = Mn/Ni; X = S/Se). We synthesized the single crystals of MnPS3-xSex (0 < x < 3) and NiPS3-xSex (0 < x < 1.3) and investigated the systematic evolution of the magnetism with varying x. Our study reveals the effective tuning of magnetic interactions and anisotropies in both MnPS3 and NiPS3 upon Se substitution. Such efficient engineering of the magnetism provides a suitable platform to understand the low-dimensional magnetism and develop future magnetic devices

Metformin and Myocardial Injury in Patients With Diabetes and ST-Segment Elevation Myocardial Infarction: A Propensity Score Matched Analysis

BACKGROUND: Although animal studies have documented metformin's cardioprotective effects, the impact in humans remains elusive. The study objective was to explore the association between metformin and myocardial infarct size in patients with diabetes presenting with ST‐segment elevation myocardial infarction. METHODS AND RESULTS: Data extraction used the National Cardiovascular Data CathPCI Registry in all patients with diabetes aged >18 years presenting with ST‐segment elevation myocardial infarction at 2 academic medical centers from January 2010 to December 2013. The exposure of interest was ongoing metformin use before the event. Propensity score matching was used for the metformin and nonmetformin groups on key prognostic variables. All matched pairs had acceptable D scores of <10%, confirming an efficient matching procedure. The primary outcome was myocardial infarct size, reflected by peak serum creatine kinase–myocardial band, troponin T, and hospital discharge left ventricular ejection fraction. Of all 1726 ST‐segment elevation myocardial infarction cases reviewed, 493 patients had diabetes (28.5%), with 208 metformin users (42.1%) and 285 nonusers. Matched pairs analysis yielded 137 cases per group. The difference between metformin and nonmetformin groups was −18.1 ng/mL (95% CI −55.0 to 18.8; P=0.56) for total peak serum creatine kinase–myocardial band and −1.1 ng/mL (95% CI −2.8 to 0.5; P=0.41) for troponin T. Median discharge left ventricular ejection fraction in both groups was 45, and the difference between metformin and nonmetformin users was 0.7% (95% CI −2.2 to 3.6; P=0.99). CONCLUSIONS: No statistically significant association of cardioprotection was found between metformin and myocardial infarct size in patients with diabetes and acute ST‐segment elevation myocardial infarction

Relating Satellite Imagery with Grain Protein Content

Satellite images, captured during the growing seasons of barley, sorghum and wheat were analysed to establish a relationship between the spectral response and the harvested grain protein content. This study was conducted near Jimbour (approx. 151 degrees 10'E and 27 degrees 05'S) in southern Queensland. Grain protein contents of the geo-referenced samples, collected manually during the harvest, were determined using a laboratory-based near-infrared spectrophotometer. Grain protein contents in grain varied between 7.4 - 15.2% in barley, 6.2 - 10.6% in sorghum and 13.1 - 15.6% in wheat. The Landsat images of 18 September 1999 (a week after barley flowering), 5 March 2000 (three weeks before sorghum harvest), and 15 August 2001 (two weeks before wheat flowering) were analysed. Additionally, an ASTER image of 24 September 2001 (three weeks after wheat flowering) was also examined. Digital numbers, extracted from raw image bands and derived indices, were correlated with grain protein contents. The grain protein content in barley was correlated strongly (r>0.80) with bands 2, 4 and 5 of the Landsat scene, first principal component, and the tasselled cap brightness and greenness indices. Similarly, wheat protein content was well correlated (r>0.75) with the near infrared band (band 4) of the Landsat scene, first principal component, and the tasselled cap brightness, greenness and wetness indices. The band 3 (near infrared band) of the ASTER image, captured well after flowering, was moderately correlated (

DeltaPhish: Detecting Phishing Webpages in Compromised Websites

The large-scale deployment of modern phishing attacks relies on the automatic exploitation of vulnerable websites in the wild, to maximize profit while hindering attack traceability, detection and blacklisting. To the best of our knowledge, this is the first work that specifically leverages this adversarial behavior for detection purposes. We show that phishing webpages can be accurately detected by highlighting HTML code and visual differences with respect to other (legitimate) pages hosted within a compromised website. Our system, named DeltaPhish, can be installed as part of a web application firewall, to detect the presence of anomalous content on a website after compromise, and eventually prevent access to it. DeltaPhish is also robust against adversarial attempts in which the HTML code of the phishing page is carefully manipulated to evade detection. We empirically evaluate it on more than 5,500 webpages collected in the wild from compromised websites, showing that it is capable of detecting more than 99% of phishing webpages, while only misclassifying less than 1% of legitimate pages. We further show that the detection rate remains higher than 70% even under very sophisticated attacks carefully designed to evade our system.Comment: Preprint version of the work accepted at ESORICS 201