A hybrid individual-based mathematical model to study bladder infections

RB was supported by a fellowship funded by the Medical Research Council, MR/P014704/1, and also acknowledges funding from the Academy of Medical Sciences (London), the Wellcome Trust (London), the UK Government Department of Business, Energy and Industrial Strategy (London), the British Heart Foundation (London), and the Global Challenges Research Fund (Swindon, UK; grant number SBF003\1052). TL gratefully acknowledges support from the Italian Ministry of University and Research (MUR) through the grant Dipartimenti di Eccellenza 2018-2022 (Project no. E11G18000350001) and the PRIN 2020 project (No. 2020JLWP23) Integrated Mathematical Approaches to Socio-Epidemiological Dynamics (CUP: E15F21005420006).Introduction: Bladder infections are common, affecting millions each year, and are often recurrent problems. Methods: We have developed a spatial mathematical framework consisting of a hybrid individual-based model to simulate these infections in order to understand more about the bacterial mechanisms and immune dynamics. We integrate a varying bacterial replication rate and model bacterial shedding as an immune mechanism. Results: We investigate the effect that varying the initial bacterial load has on infection outcome, where we find that higher bacterial burden leads to poorer outcomes, but also find that only a single bacterium is needed to establish infection in some cases. We also simulate an immunocompromised environment, confirming the intuitive result that bacterial spread typically progresses at a higher rate. Conclusions: With future model developments, this framework is capable of providing new clinical insight into bladder infections.Publisher PDFPeer reviewe

Bridge Monitoring Using Vehicle-Induced Vibration

Due to growing traffic demand, aging civil infrastructure raises the need for reliable tools to monitor structural health conditions, usable to plan informed maintenance and emergency management. Several structures with historical and monumental importance are instrumented with structural health monitoring (SHM) systems nowadays. However, even the failure of "minor" viaducts could endanger the safety of travelers and goods. Lately, dense wireless sensor networks (WSNs) based on MEMS devices are used to cut costs and simplify the deployment of SHM systems while collecting as much information as possible. However, dense WNSs are affected by data management, synchronization, and battery replacement issues, which make them unappealing for widespread use. This study presents an original damage identification algorithm based on sparse sensor networks. Traveling vehicles are exploited to obtain spatial information and accurately identify the location of structural anomalies. The curvature influence line of the monitored bridge can be calculated by processing the acceleration response measured at a given instrumented location through a low-pass filter. In this procedure, sensors operate individually, not needing energy-consuming synchronization. The proposed identification algorithm is verified on real data collected on a steel truss bridge subject to artificially induced damage

Domination of Discrete Distributed Systems

The domination is an original way for systems classification, based on input and output operators. In this paper, we consider first a class of controlled discrete distributed parameter systems (DPS). We extend the domination concept to these systems. By duality, we consider a classification for discrete observed systems, based on output operators. We give various characterizations and the main properties in the general case, and then by means of the choice of actuators and sensors

Petrology and geodynamic significance of the post-collisional Pan-African magmatism in the Eastern Saghro area (Anti-Atlas, Morocco)

The Saghro Group consists of a thick volcanic-sedimentary sequence with intercalated basaltic lavas, the first magmatic event in eastern Saghro area. Nd isotopes of basaltic pillow lavas show T-DM model ages ranging from 640 to 580 Ma, which represent a maximum age for basalt eruption. Granitoids within the Saghro Group consist of a charnockitic suite, tonalites, granodiorites and monzogranites. They are high-K calc-alkaline (HKCA) with a post-collisional character, and were emplaced at high-levels in the crust. Their ages of emplacement are within the 580-560 Ma bracket, implying that the entire Saghro Group is slightly older than or partly coeval to granitoid emplacement and implying a common geodynamical setting. Sr-Nd isotopic compositions and Nd T-DM model ages point to a mixed origin, combining a juvenile mantle source and an Eburnean crustal component, which could be the West African Craton (WAC). The juvenile component in the Saghro granitoids could be the depleted upper mantle that has sourced the earlier basalts. Field observations, geochemical and geochronological data together support that, during the Pan-African orogeny, the Anti-Atlas was subjected to a regional transpressional to transtensional event. This event would have been responsible for the dissection of the northern margin of the WAC into several blocks, the development of deep sedimentary basins and the emplacement of HKCA magmas. (C) 2009 Elsevier Ltd. All rights reserved

Preliminary modeling of the oil trapping between teeth for spur gears

This study focuses on the phenomenon of oil trapping in the tooth spaces of spur gears. It presents the first obtained results in order to provide an estimation of the power losses due to the compression of the oil trapped between the inter teeth meshing spaces in a high-speed transmission for internal and external spur gears. It first allows, to model the inter teeth spaces at any time and offers limits for the trapped fluid volume and axial and radial discharge surfaces. The discretization impact result is discussed.Then, the influence of certain design and operating parameters such as module, pressure angle, addendum modification coefficient and rotational speed on these discharge surfaces and trapped volume is presented

Domination of Discrete Distributed Systems

The domination is an original way for systems classification, based on input and output operators. In this paper, we consider first a class of controlled discrete distributed parameter systems (DPS). We extend the domination concept to these systems. By duality, we consider a classification for discrete observed systems, based on output operators. We give various characterizations and the main properties in the general case, and then by means of the choice of actuators and sensors

Analisa Sentimen Publik Mengenai Perekonomian Indonesia pada Masa Pandemi Covid-19 di Twitter Menggunakan Metode Klasifikasi K-NN dan Svm

Pandemi global virus Covid-19 yang sedang mewabah dunia kini telah memberi berbagai pengaruh pada sektor seperti pendidikan, kesehatan, pariwisata, transportasi termasuk perekonomian di Indonesia. Fenomena ini menuai berbagai tanggapan dari masyarakat yang kerap menjadikan media sosial, salah satunya Twitter sebagai alat untuk melakukan proses pertukaran informasi. Pendapat yang terkandung dapat dilakukan analisis menggunakan teknik text mining yaitu proses analisis sentimen yang merupakan cara untuk mengetahui pandangan ataupun opini seseorang terhadap suatu fenomena, baik itu berupa pandangan positif, negatif maupun netral. Data yang diambil merupakan data hasil crawling menggunakan API Twitter dan sebagai data pendukung digunakan pengambilan data melalui kuesioner kepada pengguna Twitter di Indonesia. Dataset yang digunakan pada penelitian ini berjumlah 422 data yang terdiri dari 211 data berlabel positif dan 211 data berlabel negatif. Metode yang dipakai dalam penelitian ini adalah metode K-Nearest Neighbors (K-NN) dan Support Vector Machine (SVM). Berdasarkan hasil pengujian menggunakan confusion matrix didapatkan akurasi dari analisis sentimen menggunakan metode K-NN sebanyak 76%. Sedangkan akurasi dari analisis sentimen menggunakan metode SVM sebanyak 78%