Metatarsophalangeal joint pain in psoriatic arthritis: a cross-sectional study

Methods. Thirty-four consecutive patients with PsA (mean age 45.3 years, 65% female, mean disease duration 9.9 years) and 22 control participants (mean age 37.9 years, 64% female) underwent clinical and US examination to determine the presence of pain, swelling, synovitis, erosions, effusions and submetatarsal bursae at the MTP joints. Mean barefoot peak plantar pressures were determined at each MTP joint. Levels of pain, US-determined pathology and peak pressures were compared between groups. Binary logistic regression was used to identify demographic, clinical examination-derived, US-derived and plantar pressure predictors of pain at the MTP joints in the PsA group. Results. The presence of pain, deformity, synovitis, erosions (P < 0.001) and submetatarsal bursae and peak plantar pressure at MTP 3 (P < 0.05) were significantly higher in the PsA group. MTP joint pain in PsA was independently predicted by high BMI, female gender and the presence of joint subluxation, synovitis and erosion. Conclusion. These results suggest local inflammatory and structural factors, together with systemic factors (gender, BMI), are predominantly responsible for painful MTP joints in PsA, with no clear role for plantar pressure characteristics

ESASCF: Expertise Extraction, Generalization and Reply Framework for an Optimized Automation of Network Security Compliance

The Cyber threats exposure has created worldwide pressure on organizations to comply with cyber security standards and policies for protecting their digital assets. Vulnerability assessment (VA) and Penetration Testing (PT) are widely adopted Security Compliance (SC) methods to identify security gaps and anticipate security breaches. In the computer networks context and despite the use of autonomous tools and systems, security compliance remains highly repetitive and resources consuming. In this paper, we proposed a novel method to tackle the ever-growing problem of efficiency and effectiveness in network infrastructures security auditing by formally introducing, designing, and developing an Expert-System Automated Security Compliance Framework (ESASCF) that enables industrial and open-source VA and PT tools and systems to extract, process, store and re-use the expertise in a human-expert way to allow direct application in similar scenarios or during the periodic re-testing. The implemented model was then integrated within the ESASCF and tested on different size networks and proved efficient in terms of time-efficiency and testing effectiveness allowing ESASCF to take over autonomously the SC in Re-testing and offloading Expert by automating repeated segments SC and thus enabling Experts to prioritize important tasks in Ad-Hoc compliance tests. The obtained results validate the performance enhancement notably by cutting the time required for an expert to 50% in the context of typical corporate networks first SC and 20% in re-testing, representing a significant cost-cutting. In addition, the framework allows a long-term impact illustrated in the knowledge extraction, generalization, and re-utilization, which enables better SC confidence independent of the human expert skills, coverage, and wrong decisions resulting in impactful false negatives

Tracking the invasion of Hemiramphus far and Saurida undosquamis along the southern Mediterranean coasts: A Local Ecological Knowledge study

Local Ecological Knowledge of 92 professional fishers from Tunisia and Libya was used to investigate on the occurrence and establishment of the exotic Hemiramphus far and Saurida undosquamis along the southern Mediterranean coasts. According to fisherman’s knowledge, H. far and S. undosquamis appeared in Libya, in 1980 and 1989 respectively. In Tunisia these species were observed afterwards, in 2004 and 2007. Currently both H. far and S. undosquamis result to be well distributed and established, along the entire surveyed area, from Tubrouk (eastern Libya) to Tabarka (western Tunisia). A statistical analysis of the qualitative trends in abundance perceived by the respondents show that both species have significantly increased in abundance in Tunisia. In Libya an increase of the abundance of H. far was also apparent during the first decade of the 21st century but the current abundance of S. undosquamis resulted to be stable at the level of occasional captures. Given the lack of regular environmental monitoring programmes in the area, these findings provide information that could not have been obtained otherwise. Besides improving our understanding on the status and chronology of these invasions, this approach highlights the value of fisherman’s knowledge to reconstruct ecological process in the course of rapid historical modifications

Hierarchical reinforcement learning for efficient and effective automated penetration testing of large networks

Penetration testing (PT) is a method for assessing and evaluating the security of digital assets by planning, generating, and executing possible attacks that aim to discover and exploit vulnerabilities. In large networks, penetration testing becomes repetitive, complex and resource consuming despite the use of automated tools. This paper investigates reinforcement learning (RL) to make penetration testing more intelligent, targeted, and efficient. The proposed approach called Intelligent Automated Penetration Testing Framework (IAPTF) utilizes model-based RL to automate sequential decision making. Penetration testing tasks are treated as a partially observed Markov decision process (POMDP) which is solved with an external POMDP-solver using different algorithms to identify the most efficient options. A major difficulty encountered was solving large POMDPs resulting from large networks. This was overcome by representing networks hierarchically as a group of clusters and treating each cluster separately. This approach is tested through simulations of networks of various sizes. The results show that IAPTF with hierarchical network modeling outperforms previous approaches as well as human performance in terms of time, number of tested vectors and accuracy, and the advantage increases with the network size. Another advantage of IAPTF is the ease of repetition for retesting similar networks, which is often encountered in real PT. The results suggest that IAPTF is a promising approach to offload work from and ultimately replace human pen testing

Molecular detection of Grapevine fleck virus-like viruses

Molecular reagents have been developed for virus-specific and simultaneous (virus-non-specific) detection of Grapevine fleck virus (GFkV) and allied viruses, ie. Grapevine asteroid mosaic-associated virus (GAMaV) and Grapevine red globe virus (GRGV). Degenerate primers designed on nucleotide sequences of the RNA-dependent RNA polymerase (RD) and methyltransferase (MTR) domains of the GFkV genome, were able to give amplification products of the expected size from total nucleic acid extracts of:vines infected with GFkV, GAMaV, and GRGV;a Californian grapevine accession infected by a marafi-like virus;Greek grapevine accessions infected by an unidentified agent that induced symptoms reminiscent of those elicited by GAMaV in Vitis rupestris.Degenerate primers designed on the nucleotide sequence of the helicase (HEL) domain of the GFLV genome recognized all the above viruses except for GAMaV and the unidentified Greek viral agent. RD primer set worked well also with crude grapevine cortical scrapings, thus constituting a useful universal reagent for the non-specific molecular identification of GFkV-like viruses in Vitis . The marafi-like virus from California was amplified by all sets of primers, but was recognized only by the GRGV-specific probe, suggesting that it is a likely isolate of GRGV: Likewise, the unidentified virus from Greek vines shared sequence homology with GFkV and allied viruses (GAMaV and GRGV) but exhibited differences relevant enough that call for further investigations to establish its taxonomic position. While GRGV was identified, though with a very low incidence, in some 11 southern Italian grapevine cultivars, no evidence was obtained for infection by GAMaV in any of 50 cultivars analyzed.

Intracellular \u3cem\u3eListeria monocytogenes\u3c/em\u3e Comprises a Minimal but Vital Fraction of the Intestinal Burden Following Foodborne Infection

Listeria monocytogenes is a highly adaptive bacterium that replicates as a free-living saprophyte in the environment as well as a facultative intracellular pathogen that causes invasive foodborne infections. The intracellular life cycle of L. monocytogenes is considered to be its primary virulence determinant during mammalian infection; however, the proportion of L. monocytogenes that is intracellular in vivo has not been studied extensively. In this report, we demonstrate that the majority of wild-type (strain EGDe) and mouse-adapted (InlAm-expressing) L. monocytogenes recovered from the mesenteric lymph nodes (MLN) was extracellular within the first few days after foodborne infection. In addition, significantly lower burdens of L. monocytogenes were recovered from the colon, spleen, and liver of gentamicin-treated mice than of control mice. This led us to investigate whether intracellular replication of L. monocytogenes was essential during the intestinal phase of infection. We found that lipoate protein ligase-deficient L. monocytogenes (ΔlplA1) mutants, which display impaired intracellular growth, were able to colonize the colon but did not persist efficiently and had a significant defect in spreading to the MLN, spleen, and liver. Together, these data indicate that the majority of the L. monocytogenes burden in the gastrointestinal tract is extracellular, but the small proportion of intracellular L. monocytogenes is essential for dissemination to the MLN and systemic organs

Inverse Problems in a Bayesian Setting

In a Bayesian setting, inverse problems and uncertainty quantification (UQ) --- the propagation of uncertainty through a computational (forward) model --- are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.Comment: arXiv admin note: substantial text overlap with arXiv:1312.504

Measuring Impact of Air and Agricultural Soil Pollution on Social Development in Saudi Arabia

This research aimed to measure the impact of air and agricultural soil pollution on social development in Saudi Arabia from the period 1995–2019 by using social development indicators, concentrating on the percentages of expenditure on education and health, and the Human Development Index. In addition, this study uses multiple regressions in estimating the model to study the impact of air pollution and agricultural soil on social development. Results of the study showed that a 10% change in the number of chemical fertilizers and pesticides used in Saudi agriculture leads to a change in the total number of inpatients by 0.7% and 0.5%, respectively. It was also found that an increased percentage of health expenditure to total government spending by 10% leads to a decrease in the total number of patients in the hospital by 1.8%. An increase in air pollution, expressed as a 10% increase in CO2 emissions, increases the total number of hospitalized patients by 11.1%.  The increasing total number of patients by 10% leads to a decrease in the total productivity of the worker, as an indicator of 1.8%. Furthermore, a change of 10% in the ratio of education expenditure to total government expenditure leads to a change in the same direction of the Human Development Index by 9.6%. In light of these results, it can be recommended that the country need to reduce air pollution by expanding the use of natural gas in the industrial and transportation sectors, in addition to reducing the use of nitrogenous fertilizers and pesticides in Saudi agriculture through the expansion of clean farming and good agricultural practices