Liver cystic echinococcosis in humans — a study of 30 cases

The aim of this study is to demonstrate the clinical manifestations and diagnostic approach to liver hydatid disease and suggest its treatment. The prospective study was carried out on 30 patients with liver hydatidosis. Hepatologic examinations were based on: medical history, physical examination, biochemical and serological tests, ultrasonography and computed tomography scanning. Twenty-five (83.3 %) patients underwent radical cyst resection, while in 5 (16.7 %) cases liver resection with left lobectomy was also performed. Hydatid cyst was histopathologically verified in all the patients. Our results showed that the patients with multiple cysts had impaired functional liver tests significantly more often than patients with unilocular cyst. In addition, ultrasonography and computed tomography scans are the valid imaging procedures in diagnosis. Radical, surgical resection of hepatic hydatid cysts is the goal of treatment

Applying advanced data analytics and machine learning to enhance the safety control of dams

The protection of critical engineering infrastructures is vital to today’s so- ciety, not only to ensure the maintenance of their services (e.g., water supply, energy production, transport), but also to avoid large-scale disasters. Therefore, technical and financial efforts are being continuously made to improve the safety control of large civil engineering structures like dams, bridges and nuclear facilities. This con- trol is based on the measurement of physical quantities that characterize the struc- tural behavior, such as displacements, strains and stresses. The analysis of monitor- ing data and its evaluation against physical and mathematical models is the strongest tool to assess the safety of the structural behavior. Commonly, dam specialists use multiple linear regression models to analyze the dam response, which is a well- known approach among dam engineers since the 1950s decade. Nowadays, the data acquisition paradigm is changing from a manual process, where measurements were taken with low frequency (e.g., on a weekly basis), to a fully automated process that allows much higher frequencies. This new paradigm escalates the potential of data analytics on top of monitoring data, but, on the other hand, increases data quality issues related to anomalies in the acquisition process. This chapter presents the full data lifecycle in the safety control of large-scale civil engineering infrastructures (focused on dams), from the data acquisition process, data processing and storage, data quality and outlier detection, and data analysis. A strong focus is made on the use of machine learning techniques for data analysis, where the common multiple linear regression analysis is compared with deep learning strategies, namely recur- rent neural networks. Demonstration scenarios are presented based on data obtained from monitoring systems of concrete dams under operation in Portugal.info:eu-repo/semantics/acceptedVersio

Study of electron transmission through a metallic capillary

In this work we study the transmission of charged particles through a single cylindrically shaped metallic capillary of microscopic dimensions with a large aspect ratio. We used electrons as projectiles. Our results suggest the existence of guiding of the electron beam by a metallic capillary.29th International Conference on Photonic, Electronic, and Atomic Collisions (ICPEAC), Jul 22-28, 2015, Toledo, Spai

Antioxidant, antimicrobial and anticancer activity of the lichens Cladonia furcata, Lecanora atra and Lecanora muralis

<p>Abstract</p> <p>Background</p> <p>The aim of this study is to investigate in vitro antioxidant, antimicrobial and anticancer activity of the acetone extracts of the lichens <it>Cladonia furcata, Lecanora atra </it>and <it>Lecanora muralis</it>.</p> <p>Methods</p> <p>Antioxidant activity was evaluated by five separate methods: free radical scavenging, superoxide anion radical scavenging, reducing power, determination of total phenolic compounds and determination of total flavonoid content. The antimicrobial activity was estimated by determination of the minimal inhibitory concentration by the broth microdilution method against six species of bacteria and ten species of fungi. Anticancer activity was tested against FemX (human melanoma) and LS174 (human colon carcinoma) cell lines using MTT method.</p> <p>Results</p> <p>Of the lichens tested, <it>Lecanora atra </it>had largest free radical scavenging activity (94.7% inhibition), which was greater than the standard antioxidants. Moreover, the tested extracts had effective reducing power and superoxide anion radical scavenging. The strong relationships between total phenolic and flavonoid contents and the antioxidant effect of tested extracts were observed. Extract of <it>Cladonia furcata </it>was the most active antimicrobial agent with minimum inhibitory concentration values ranging from 0.78 to 25 mg/mL. All extracts were found to be strong anticancer activity toward both cell lines with IC₅₀values ranging from 8.51 to 40.22 μg/mL.</p> <p>Conclusions</p> <p>The present study shows that tested lichen extracts demonstrated a strong antioxidant, antimicrobial and anticancer effects. That suggest that lichens may be used as as possible natural antioxidant, antimicrobial and anticancer agents to control various human, animal and plant diseases.</p

Quasi-autonomous quantum thermal machines and quantum to classical energy flow

There are both practical and foundational motivations to consider the thermodynamics of quantum systems at small scales. Here we address the issue of autonomous quantum thermal machines that are tailored to achieve some specific thermodynamic primitive, such as work extraction in the presence of a thermal environment, while having minimal or no control from the macroscopic regime. Beyond experimental implementations, this provides an arena in which to address certain foundational aspects such as the role of coherence in thermodynamics, the use of clock degrees of freedom and the simulation of local time-dependent Hamiltonians in a particular quantum subsystem. For small-scale systems additional issues arise. Firstly, it is not clear to what degree genuine ordered thermodynamic work has been extracted, and secondly non-trivial back-actions on the thermal machine must be accounted for. We find that both these aspects can be resolved through a judicious choice of quantum measurements that magnify thermodynamic properties up the ladder of length-scales, while simultaneously stabilising the quantum thermal machine. Within this framework we show that thermodynamic reversibility is obtained in a particular Zeno limit, and finally illustrate these concepts with a concrete example involving spin systems

Automated Essay Scoring in Foreign Language Students Based on Deep Contextualised Word Representations

We introduce a method for automated grading of handwritten essays written by foreign language learners of French. The handwriting recognition system allows digitising the essays for further processing and functions at a low character error rate. The transcriptions are then vectorised using embeddings from state-of-the-art pre-trained natural language processing models. On top of the extracted word-level features, a deep recurrent network was trained for grade predictions for essays, using the nine different grading criteria as target variables. Scores on these criteria were previously obtained from human expert raters for more than 6’000 student essays. We present preliminary findings on prediction accuracy and discuss possible future developments and applications of the system