Digital forensic analysis of the private mode of browsers on Android

The smartphone has become an essential electronic device in our daily lives. We carry our most precious and important data on it, from family videos of the last few years to credit card information so that we can pay with our phones. In addition, in recent years, mobile devices have become the preferred device for surfing the web, already representing more than 50% of Internet traffic. As one of the devices we spend the most time with throughout the day, it is not surprising that we are increasingly demanding a higher level of privacy. One of the measures introduced to help us protect our data by isolating certain activities on the Internet is the private mode integrated in most modern browsers. Of course, this feature is not new, and has been available on desktop platforms for more than a decade. Reviewing the literature, one can find several studies that test the correct functioning of the private mode on the desktop. However, the number of studies conducted on mobile devices is incredibly small. And not only is it small, but also most of them perform the tests using various emulators or virtual machines running obsolete versions of Android. Therefore, in this paper we apply the methodology we presented in a previous work to Google Chrome, Brave, Mozilla Firefox, and Tor Browser running on a tablet with Android 13 and on two virtual devices created with Android Emulator. The results confirm that these browsers do not store information about the browsing performed in private mode in the file system. However, the analysis of the volatile memory made it possible to recover the username and password used to log in to a website or the keywords typed in a search engine, even after the devices had been rebootedThis work has received financial support from the Consellería de Cultura, Educación e Ordenación Universitaria of the Xunta de Galicia (accreditation 2019- 2022 ED431G-2019/04, reference competitive group 2022-2024, ED431C 2022/16) and the European Regional Development Fund (ERDF), which acknowledges the CiTIUS-Research Center in Intelligent Technologies of the University of Santiago de Compostela as a Research Center of the Galician University System. This work was also supported by the Ministry of Economy and Competitiveness, Government of Spain (Grant No. PID2019-104834 GB-I00). X. Fernández-Fuentes is supported by the Ministerio de Universidades, Spain under the FPU national plan (FPU18/04605)S

Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders.

Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development

Reliability-based structural assessment of historical masonry arch bridges: The case study of Cernadela bridge

Nowadays, several historical masonry arch bridges present a deficient state of conservation due to degradation processes induced by natural or human actions. Usually, these constructions have significant economic, cultural, and heritage value. Therefore, they shall be thoroughly assessed to verify their structural integrity and safety condition. For this purpose, reliability-based structural assessments are typically performed. However, the associated outcomes (i.e., reliability index and probability of failure) highly rely on the accuracy of the structural parameters uncertainty quantification. This work presents a study regarding the influence of the scattering of the arches’ thickness dimensions in the load-carrying capacity assessment of the Cernadela Bridge, a historical stone bridge located in Galicia, Spain. The study first involved a comprehensive experimental campaign to characterize the outer and inner bridge geometry through geomatic techniques, i.e., terrestrial laser scanning and ground penetrating radar. Subsequently, a limit analysis model was developed, considering only the arches’ outer (visible) data. From this initial structural assessment, a reliability index of 2.38 was obtained. The influence of the uncertain structural parameters, both geometric features and material properties, in the collapse load was investigated through a global variance-based sensitivity analysis (i.e., Sobol’ indices) complemented by a surrogate modeling strategy based on the Kriging approach. Finally, the measured inner geometry of the arches was introduced in the computational model through Bayesian inference procedures. Thus, two new structural assessments were performed: first, by considering the updated distributions of all arches thicknesses, and second, by considering only the updated distributions of the non-influential ones. Reliability indexes of 1.51 and 2.33 were derived, thus highlighting the importance of a proper uncertainty quantification process and the relevance of the sensitivity analysis outcomes to identify the critical parameters on the bridge mechanical response.This work has been partially supported by the Spanish Ministry of Science and Innovation through the project Ref. TED2021- 130497A-I00. This work has also received funding from the European Union's Horizon 2020 research and innovation program under Grant Agreement No 958171. This document reflects only the views of the author (s) . Neither the Innovation and Networks Executive Agency (INEA) nor the European Commission is in any way responsible for any use that may be made of the information it contains. M. Solla acknowledges the grant RYC2019-026604-I funded by MCIN/AEI/10.13039/501100011033 and by "ESF Investing in your future." O. Bouzas acknowledges the human resources grant: "Axudas para a contratacion de personal investigador predoutoral en formacion da Universidade De Vigo 2022" (PREUVIGO-22) funded by Universidade de Vigo

Software tools for performance modeling of parallel programs

This paper presents a framework based on a user driven methodology to obtain analytical models of MPI applications on parallel systems in a systematic and easy to use way. This methodology consists of two stages. In the first one, instrumentation of the source code is performed using CALL, which is a profiling tool for interacting with the code in an easy, simple and direct way. New features are added to CALL to obtain different performace metrics and store the performance information in XML files. Using this information, an analytical model of the performance behavior is obtained in the second stage by means of R, a language and environment for statistical analysis. The structure of the whole framework is detailed in this paper, and some selected examples are used to show its practical use.

Combined gelatin-chondroitin sulfate hydrogels with graphene nanoparticles

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Combined Gelatin-Chondroitin Sulfate Hydrogels with graphene nanoparticles

10 pages, 5 figures, 3 tablesCreating flexible, high-strength hydrogels from harmless, low-cost natural polymers is an area of intense research today due to their potential applications in the biomedical field, which demands materials with ambivalent physicochemical features. In particular, great efforts were devoted to the preparation of sustainable biohydrogels, composed of hydrophilic networks of renewable, biocompatible, biodegradable, and low-cost biopolymers. Bionanocomposites are a promising synthetic approach to combine specific multifunctional materials with targeted physicochemical properties. Novel bionanocomposite hydrogels were designed by combining both chondroitin sulfate (CS) as well as gelatin (GE) obtained from the waste generated by the fish industries to form double fibre networks with tailored properties. In addition, hybrid bionanocomposites were achieved by introducing graphene nanoparticles (xGnP) into the double fibrillar network (GE/CS) to enhance the physicochemical properties. The bionanocomposite nanostructures were characterized by Fourier transform infrared spectroscopy (FTIR), differential scanning calorimeter (DSC) while their rheological properties and thermal stability were determined by rheological and thermogravimetric analyses (TGA), respectively. The likely interactions between CS and gelatin in the GE/CS hydrogel network were proved by ATR-FTIR spectroscopy. The incorporation of xGnP improved the mechanical properties of the GE/CS fibrillary network by an order of magnitude in the shear storage modulus. Eventually, the generated bionanocomposites hydrogels and bionanocomposite hybrid hydrogels have promising potential for applications in many biomedical fields, including drug delivery and tissue engineering by mimicking tissue extracellular matrix components such as the gelatin for collagen and the CS in the cartilageThe authors acknowledge the financial support received from Project KET4F-Gas-SOE2/P1/P0823, which is co-financed by the European Regional Development Fund within the framework of Interreg Sudoe Programme and project PID2019-105827RB-I00–Agencia Estatal de Investigación, SpainPeer reviewe

Analytical Performance Models of Parallel Programs in Clusters

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