Improving SIEM for critical SCADA water infrastructures using machine learning

Network Control Systems (NAC) have been used in many industrial processes. They aim to reduce the human factor burden and efficiently handle the complex process and communication of those systems. Supervisory control and data acquisition (SCADA) systems are used in industrial, infrastructure and facility processes (e.g. manufacturing, fabrication, oil and water pipelines, building ventilation, etc.) Like other Internet of Things (IoT) implementations, SCADA systems are vulnerable to cyber-attacks, therefore, a robust anomaly detection is a major requirement. However, having an accurate anomaly detection system is not an easy task, due to the difficulty to differentiate between cyber-attacks and system internal failures (e.g. hardware failures). In this paper, we present a model that detects anomaly events in a water system controlled by SCADA. Six Machine Learning techniques have been used in building and evaluating the model. The model classifies different anomaly events including hardware failures (e.g. sensor failures), sabotage and cyber-attacks (e.g. DoS and Spoofing). Unlike other detection systems, our proposed work helps in accelerating the mitigation process by notifying the operator with additional information when an anomaly occurs. This additional information includes the probability and confidence level of event(s) occurring. The model is trained and tested using a real-world dataset

High prevalence of Trichomonas gallinae in wild columbids across western and southern Europe

Avian trichomonosis is known as a widespread disease in columbids and passerines, and recent findings have highlighted the pathogenic character of some lineages found in wild birds. Trichomonosis can affect wild bird populations including endangered species, as has been shown for Mauritian pink pigeons Nesoenas mayeri in Mauritius and suggested for European turtle doves Streptopelia turtur in the UK. However, the disease trichomonosis is caused only by pathogenic lineages of the parasite Trichomonas gallinae. Therefore, understanding the prevalence and distribution of both potentially pathogenic and non-pathogenic T. gallinae lineages in turtle doves and other columbids across Europe is relevant to estimate the potential impact of the disease on a continental scale

Serum markers in interstitial pneumonia with and without Pneumocystis jirovecii colonization: a prospective study

<p>Abstract</p> <p>Background</p> <p>In patients with chronic respiratory disease, <it>Pneumocystis jirovecii (P. jirovecii) </it>colonization is observed, and may influence disease progression and systemic inflammation. <it>Pneumocystis </it>pneumonia causes interstitial changes, so making a diagnosis of PCP in patients who have interstitial pneumonia (IP) with <it>P. jirovecii </it>colonization is sometimes difficult based on radiography.</p> <p>Methods</p> <p>This study investigated the prevalence of <it>P. jirovecii </it>colonization in IP patients and assessed pulmonary injury due to <it>P. jirovecii </it>colonization by measurement of serum markers (KL-6, SP-A, SP-D, and (1→3) β-D-glucan (β-D-glucan)) and the peripheral lymphocyte counts, prospectively. A total of 75 patients with idiopathic pulmonary fibrosis (n = 29), collagen vascular-related interstitial pneumonia (n = 19), chronic bronchitis or pneumonia (n = 20), and <it>Pneumocystis </it>pneumonia (n = 7) were enrolled in this prospective study. <it>P. jirovecii </it>DNA was detected in sputum samples, while serum markers and the lymphocyte count were measured in the peripheral blood.</p> <p>Results</p> <p>IP patients (idiopathic pulmonary fibrosis and collagen vascular-related IP) who received oral corticosteroids had a high prevalence of <it>P. jirovecii </it>colonization (23.3%). In IP patients, oral corticosteroid therapy was a significant risk factor for <it>P. jirovecii </it>colonization (<it>P </it>< 0.05). Serum markers did not show differences between IP patients with and without <it>P. jirovecii </it>colonization. The β-D-glucan level and lymphocyte count differed between patients with <it>Pneumocystis </it>pneumonia or <it>P. jirovecii </it>colonization.</p> <p>Conclusion</p> <p>Serum levels of KL-6, SP-A, SP-D, and β-D-glucan were not useful for detecting <it>P. jirovecii </it>colonization in IP patients. However, the serum β-D-glucan level and lymphocyte count were useful for distinguishing <it>P. jirovecii </it>colonization from <it>pneumocystis </it>pneumonia in IP patients.</p

External validation of a COPD prediction model using population-based primary care data: a nested case-control study

Emerging models for predicting risk of chronic obstructive pulmonary disease (COPD) require external validation in order to assess their clinical value. We validated a previous model for predicting new onset COPD in a different database. We randomly drew 38,597 case-control pairs (total N = 77,194) of individuals aged ≥35 years and matched for sex, age, and general practice from the United Kingdom Clinical Practice Research Datalink database. We assessed accuracy of the model to discriminate between COPD cases and non-cases by calculating area under the receiver operator characteristic (ROC(AUC)) for the prediction scores. Analogous to the development model, ever smoking (OR 6.70; 95%CI 6.41–6.99), prior asthma (OR 6.43; 95%CI 5.85–7.07), and higher socioeconomic deprivation (OR 2.90; 95%CI 2.72–3.09 for highest vs. lowest quintile) increased the risk of COPD. The validated prediction scores ranged from 0–5.71 (ROC(AUC) 0.66; 95%CI 0.65–0.66) for males and 0–5.95 (ROC(AUC) 0.71; 95%CI 0.70–0.71) for females. We have confirmed that smoking, prior asthma, and socioeconomic deprivation are key risk factors for new onset COPD. Our model seems externally valid at identifying patients at risk of developing COPD. An impact assessment now needs to be undertaken to assess whether this prediction model can be applied in clinical care settings

Relationship between efficiency and clinical effectiveness indicators in an adjusted model of resource consumption : a cross-sectional study

Background: Adjusted clinical groups (ACG®) have been widely used to adjust resource distribution; however, the relationship with effectiveness has been questioned. The purpose of the study was to measure the relationship between efficiency assessed by ACG® and a clinical effectiveness indicator in adults attended in Primary Health Care Centres (PHCs). Methods: Research design: cross-sectional study. Subjects: 196, 593 patients aged >14 years in 13 PHCs in Catalonia (Spain). Measures: Age, sex, PHC, basic care team (BCT), visits, episodes (diagnoses), and total direct costs of PHC care and co-morbidity as measured by ACG® indicators: Efficiency indices for costs, visits, and episodes (costs EI, visits EI, episodes EI); a complexity or risk index (RI); and effectiveness measured by a general synthetic index (SI). The relationship between EI, RI, and SI in each PHC and BCT was measured by multiple correlation coefficients (r). Results: In total, 56 of the 106 defined ACG® were present in the study population, with five corresponding to 44.5% of the patients, 11 to 68.0% of patients, and 30 present in less than 0.5% of the sample. The RI in each PHC ranged from 0.9 to 1.1. Costs, visits, and episodes had similar trends for efficiency in six PHCs. There was moderate correlation between costs EI and visits EI (r = 0.59). SI correlation with episodes EI and costs EI was moderate (r = 0.48 and r = −0.34, respectively) and was r = −0.14 for visits EI. Correlation between RI and SI was r = 0.29. Conclusions: The Efficiency and Effectiveness ACG® indicators permit a comparison of primary care processes between PHCs. Acceptable correlation exists between effectiveness and indicators of efficiency in episodes and costs

Selected Schizosaccharomyces pombe Strains Have Characteristics That Are Beneficial for Winemaking

At present, wine is generally produced using Saccharomyces yeast followed by Oenococus bacteria to complete malolactic fermentation. This method has some unsolved problems, such as the management of highly acidic musts and the production of potentially toxic products including biogenic amines and ethyl carbamate. Here we explore the potential of the fission yeast Schizosaccharomyces pombe to solve these problems. We characterise an extensive worldwide collection of S. pombe strains according to classic biochemical parameters of oenological interest. We identify three genetically different S. pombe strains that appear suitable for winemaking. These strains compare favourably to standard Saccharomyces cerevisiae winemaking strains, in that they perform effective malic acid deacidification and significantly reduce levels of biogenic amines and ethyl carbamate precursors without the need for any secondary bacterial malolactic fermentation. These findings indicate that the use of certain S. pombe strains could be advantageous for winemaking in regions where malic acid is problematic, and these strains also show superior performance with respect to food safety

A modular analysis of the Auxin signalling network

Auxin is essential for plant development from embryogenesis onwards. Auxin acts in large part through regulation of transcription. The proteins acting in the signalling pathway regulating transcription downstream of auxin have been identified as well as the interactions between these proteins, thus identifying the topology of this network implicating 54 Auxin Response Factor (ARF) and Aux/IAA (IAA) transcriptional regulators. Here, we study the auxin signalling pathway by means of mathematical modeling at the single cell level. We proceed analytically, by considering the role played by five functional modules into which the auxin pathway can be decomposed: the sequestration of ARF by IAA, the transcriptional repression by IAA, the dimer formation amongst ARFs and IAAs, the feedback loop on IAA and the auxin induced degradation of IAA proteins. Focusing on these modules allows assessing their function within the dynamics of auxin signalling. One key outcome of this analysis is that there are both specific and overlapping functions between all the major modules of the signaling pathway. This suggests a combinatorial function of the modules in optimizing the speed and amplitude of auxin-induced transcription. Our work allows identifying potential functions for homo- and hetero-dimerization of transcriptional regulators, with ARF:IAA, IAA:IAA and ARF:ARF dimerization respectively controlling the amplitude, speed and sensitivity of the response and a synergistic effect of the interaction of IAA with transcriptional repressors on these characteristics of the signaling pathway. Finally, we also suggest experiments which might allow disentangling the structure of the auxin signaling pathway and analysing further its function in plants

Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: The impact of a local calibration

<p>Abstract</p> <p>Background</p> <p>In the financing of a national health system, where pharmaceutical spending is one of the main cost containment targets, predicting pharmacy costs for individuals and populations is essential for budget planning and care management. Although most efforts have focused on risk adjustment applying diagnostic data, the reliability of this information source has been questioned in the primary care setting. We sought to assess the usefulness of incorporating pharmacy data into claims-based predictive models (PMs). Developed primarily for the U.S. health care setting, a secondary objective was to evaluate the benefit of a local calibration in order to adapt the PMs to the Spanish health care system.</p> <p>Methods</p> <p>The population was drawn from patients within the primary care setting of Aragon, Spain (n = 84,152). Diagnostic, medication and prior cost data were used to develop PMs based on the Johns Hopkins ACG methodology. Model performance was assessed through r-squared statistics and predictive ratios. The capacity to identify future high-cost patients was examined through c-statistic, sensitivity and specificity parameters.</p> <p>Results</p> <p>The PMs based on pharmacy data had a higher capacity to predict future pharmacy expenses and to identify potential high-cost patients than the models based on diagnostic data alone and a capacity almost as high as that of the combined diagnosis-pharmacy-based PM. PMs provided considerably better predictions when calibrated to Spanish data.</p> <p>Conclusion</p> <p>Understandably, pharmacy spending is more predictable using pharmacy-based risk markers compared with diagnosis-based risk markers. Pharmacy-based PMs can assist plan administrators and medical directors in planning the health budget and identifying high-cost-risk patients amenable to care management programs.</p

Two Distinct Triatoma dimidiata (Latreille, 1811) Taxa Are Found in Sympatry in Guatemala and Mexico

Approximately 10 million people are infected with Trypanosoma cruzi, the causative agent of Chagas disease, which remains the most serious parasitic disease in the Americas. Most people are infected via triatomine vectors. Transmission has been largely halted in South America in areas with predominantly domestic vectors. However, one of the main Chagas vectors in Mesoamerica, Triatoma dimidiata, poses special challenges to control due to its diversity across its large geographic range (from Mexico into northern South America), and peridomestic and sylvatic populations that repopulate houses following pesticide treatment. Recent evidence suggests T. dimidiata may be a complex of species, perhaps including cryptic species; taxonomic ambiguity which confounds control. The nuclear sequence of the internal transcribed spacer 2 (ITS2) of the ribosomal DNA and the mitochondrial cytochrome b (mt cyt b) gene were used to analyze the taxonomy of T. dimidiata from southern Mexico throughout Central America. ITS2 sequence divides T. dimidiata into four taxa. The first three are found mostly localized to specific geographic regions with some overlap: (1) southern Mexico and Guatemala (Group 2); (2) Guatemala, Honduras, El Salvador, Nicaragua, and Costa Rica (Group 1A); (3) and Panama (Group 1B). We extend ITS2 Group 1A south into Costa Rica, Group 2 into southern Guatemala and show the first information on isolates in Belize, identifying Groups 2 and 3 in that country. The fourth group (Group 3), a potential cryptic species, is dispersed across parts of Mexico, Guatemala, and Belize. We show it exists in sympatry with other groups in Peten, Guatemala, and Yucatan, Mexico. Mitochondrial cyt b data supports this putative cryptic species in sympatry with others. However, unlike the clear distinction of the remaining groups by ITS2, the remaining groups are not separated by mt cyt b. This work contributes to an understanding of the taxonomy and population subdivision of T. dimidiata, essential for designing effective control strategies