On Holistic Multi-Step Cyberattack Detection via a Graph-based Correlation Approach

While digitization of distribution grids through information and communications technology brings numerous benefits, it also increases the grid's vulnerability to serious cyber attacks. Unlike conventional systems, attacks on many industrial control systems such as power grids often occur in multiple stages, with the attacker taking several steps at once to achieve its goal. Detection mechanisms with situational awareness are needed to detect orchestrated attack steps as part of a coherent attack campaign. To provide a foundation for detection and prevention of such attacks, this paper addresses the detection of multi-stage cyber attacks with the aid of a graph-based cyber intelligence database and alert correlation approach. Specifically, we propose an approach to detect multi-stage attacks by leveraging heterogeneous data to form a knowledge base and employ a model-based correlation approach on the generated alerts to identify multi-stage cyber attack sequences taking place in the network. We investigate the detection quality of the proposed approach by using a case study of a multi-stage cyber attack campaign in a future-orientated power grid pilot.Comment: IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) 202

Validation of tracheal intubation of wire-reinforced endotracheal tube with ultrasonography

Objective. Te use of ultrasonography (US) is a new method for verifying the location of the endotracheal tube. Design. Our study was designed as a paired-data and investigator-blind clinical study for evaluating the efectiveness of US for verifcation of wire-reinforced endotracheal tube (WR-ETT) placement compared with capnography. Setting. Tis study was conducted on 56 patients scheduled for elective surgery under general anesthesia. Patients. Fify patients completed the study as 6 were excluded for various reasons. Intervention. Two diferent investigators performed the ultrasonography and intubation independently from one another. While investigator 1 attempted to verify the location of the WR-ETT with a portable ultrasonography with sagittal trans-tracheal view, investigator 2 intubated the patient and verifed the location of the ETT using capnography. Measurements. Time for verifying the location of the ETT using both US and capnography was recorded. Main Results. When the ultrasonography method was compared with capnography for verifcation of the WR-ETT placement, the results showed 95.75% sensitivity and 100% specifcity. Te average verifcation times for endotracheal intubation were 12.78 ± 7.46 s. and 24.44 ± 1.45 s. with US and capnography, respectively (p=0.003). Conclusion. Our results suggest that ultrasound identifcation of a WR-ETT within the trachea is a rapid and accurate method for confrmation of tracheal placement. Larger studies are needed before widespread use of this technique

Investigating the Cybersecurity of Smart Grids Based on Cyber-Physical Twin Approach

While the increasing penetration of information and communication technology into distribution grid brings numerous benefits, it also opens up a new threat landscape, particularly through cyberattacks. To provide a basis for countermeasures against such threats, this paper addresses the investigation of the impact and manifestations of cyberattacks on smart grids by replicating the power grid in a secure, isolated, and controlled laboratory environment as a cyber-physical twin. Currently, detecting intrusions by unauthorized third parties into the central monitoring and control system of grid operators, especially attacks within the grid perimeter, is a major challenge. The development and validation of methods to detect and prevent coordinated and timed attacks on electric power systems depends not only on the availability and quality of data from such attack scenarios, but also on suitable realistic investigation environments. However, to create a comprehensive investigation environment, a realistic representation of the study object is required to thoroughly investigate critical cyberattacks on grid operations and evaluate their impact on the power grid using real data. In this paper, we demonstrate our cyber-physical twin approach using a microgrid in the context of a cyberattack case study.Comment: IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) 202

On specification-based cyber-attack detection in smart grids

The transformation of power grids into intelligent cyber-physical systems brings numerous benefits, but also significantly increases the surface for cyber-attacks, demanding appropriate countermeasures. However, the development, validation, and testing of data-driven countermeasures against cyber-attacks, such as machine learning-based detection approaches, lack important data from real-world cyber incidents. Unlike attack data from real-world cyber incidents, infrastructure knowledge and standards are accessible through expert and domain knowledge. Our proposed approach uses domain knowledge to define the behavior of a smart grid under non-attack conditions and detect attack patterns and anomalies. Using a graph-based specification formalism, we combine cross-domain knowledge that enables the generation of whitelisting rules not only for statically defined protocol fields but also for communication flows and technical operation boundaries. Finally, we evaluate our specification-based intrusion detection system against various attack scenarios and assess detection quality and performance. In particular, we investigate a data manipulation attack in a future-orientated use case of an IEC 60870-based SCADA system that controls distributed energy resources in the distribution grid. Our approach can detect severe data manipulation attacks with high accuracy in a timely and reliable manner

Color Regeneration from Reflective Color Sensor Using an Artificial Intelligent Technique

A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages

Traces of trauma – a multivariate pattern analysis of childhood trauma, brain structure and clinical phenotypes

Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Self-regulated Learning Skills: Adaptation of Scale

The aim of this study is to adapt and examine the psychometric properties of Achievement Goal Scale (AGS) originally constructed by Elliot and McGregor (2001) and the Motivated Strategies for Learning Scale (MSLQ) originally constructed by Pintrich, Smith, Garcia and McKeachie (1991) in order to measure the self-regulated learning skills of high school students' in a chemistry course. The study group was comprised of 862 high school students attending a chemistry course in different public schools. The construct validity of the sub-scales included in the scales were tested by confirmatory factor analysis. For the reliability studies, the internal consistency coefficient Cronbach's alpha (α) values as well as McDonald's ω (omega) coefficients were calculated. In addition, item-total correlations were calculated for the reliability of each item in the scales. When the confirmatory factor analysis results were examined, it was accepted that the fit indices met the goodness of fit criteria for both the Achievement Goal Scale and Motivated Strategies for Learning Scale. Factor loadings of the items in both scales were statistically significant. These results showed that the Turkish forms of both scales have enough psychometric properties in terms of validity and reliability for a chemistry course

Climate change impacts in the Euphrates-Tigris Basin based on different model and scenario simulations

Hydro-climatic effects of future climate change in the Euphrates-Tigris Basin are investigated using dynamically downscaled outputs of different GCM (ECHAM5, CCSM3 and HadCM3) - emissions scenario (A1FI, A2 and B1) simulations. The suite of simulations (total five) enables an analysis taking into account the A2 emission scenario simulations of three different GCMs and another analysis based on the three different emissions scenario (A1FI, A2 and B1) simulations of one GCM (CCSM3). All scenario simulations indicate winter surface temperature increases in the entire basin, however, the increase is larger in the highlands. The greatest increase in the annual temperature by the end of century belongs to the CCSM3 A1FI simulation with an increment of 6.1 degrees C in the highlands. There is a broad agreement amongst the simulations in terms of the winter precipitation decrease in the highlands and northern parts and increase in the southern parts of the basin. A remarkable impact of warming could be seen on the snow water equivalent in the highlands where each simulation points out statistically significant decreases ranging from 55% (lower emissions) to 87% (higher emissions). Statistically significant declines (25-55%) are found for the annual surface runoff of the main headwaters area. Moreover, significant temporal shifts to earlier days (between 18 and 39 days depending on the scenario) are projected to occur in the surface runoff timing in the headwaters region. Projected annual surface runoff changes in all simulations suggest that the territories of Turkey and Syria within the basin are most vulnerable to climate change as they will experience significant decreases in the annual surface runoff. Eventually, however, the downstream countries, especially Iraq, may suffer more as they rely primarily on the water released by the upstream countries. The substantial changes in the hydro-climate of the basin, therefore, are likely to increase the challenges associated with the management of several dam reservoirs and hydropower plants in the basin in addition to causing further impacts on physical and biological components of the ecosystems along these rivers

Evaluation of mobile bearing unicompartmental knee arthroplasty, opening wedge, and dome-type high tibial osteotomies for knee arthritis

Objective: Three methods of surgery used in the treatment of knee osteoarthritis (OA) are mobile bearing unicompartmental knee arthroplasty (Oxford UKA), opening wedge high tibial osteotomy (HTO), and dome-type HTO. This article aimed to retrospectively compare these three methods in terms of outcomes for health status, patient satisfaction, and function