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Legal protection for consumers must be considered because the existence of consumers is prone to fraud. Personal consumer data protect one form of legal protection for consumers in conducting transactions with business actors, both domestic and foreign transactions. With the times at this time, consumer data that exists on business actors, both in the form of state-owned enterprises or business actors in the private form, is a lot of consumer data that these business actors trade and this consumer data is widely known. The problem studied is how the consumer’s legal protection of personal data on digital platforms. Research methods are using normative research methods, namely by explaining the issues and views of consumer legal protection of personal data on existing legal regulatory, digital platforms. The results illustrate that for now, consumer legal protection of personal data on digital platforms still refers to several laws and regulations in Indonesia. The government is also preparing a Draft Law on Personal Data Protection, which will become lex specialis. For the protection of personal consumer data in Indonesia related to personal data on digital platforms.

The double-pipe heat exchanger is one of the most popular heat exchanger devices. In this study, the concentric tube heat exchanger as the double pipe heat exchanger device was simulated with ANSYS code FLUENT. The simulation was done by based on the Reynolds number variation from 400010.000 using the method of co-current and counter flow. The hydrodynamic and thermal simulation results agree with the empirical correlation of the Pethukov and Dittus-Bolter equations, respectively. The friction factors of the water base fluid and nanofluid f TiO2/water f (0.1 vol.%) do not result in a significant difference in the turbulent flow regime for both co-current and counter flow. The thermal performance of TiO2/water (0.1% vol) nanofluid as indicated by the value of the heat transfer coefficient results in an increase of 6.9% for counter low flow and 6.0% for co-current flow. Meanwhile, the direction of fluid flow in the heat exchanger does not have a significant effect on its thermal performance.

Introduction Lung cancer (LC) is the most common cause of cancer-related deaths worldwide. Its early detection can be achieved with a CT scan. Two large randomised trials proved the efficacy of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk populations. The decrease in specific mortality is 20%–25%.Nonetheless, implementing LCS on a large scale faces obstacles due to the low number of thoracic radiologists and CT scans available for the eligible population and the high frequency of false-positive screening results and the long period of indeterminacy of nodules that can reach up to 24 months, which is a source of prolonged anxiety and multiple costly examinations with possible side effects.Deep learning, an artificial intelligence solution has shown promising results in retrospective trials detecting lung nodules and characterising them. However, until now no prospective studies have demonstrated their importance in a real-life setting.Methods and analysis This open-label randomised controlled study focuses on LCS for patients aged 50–80 years, who smoked more than 20 pack-years, whether active or quit smoking less than 15 years ago. Its objective is to determine whether assisting a multidisciplinary team (MDT) with a 3D convolutional network-based analysis of screening chest CT scans accelerates the definitive classification of nodules into malignant or benign. 2722 patients will be included with the aim to demonstrate a 3-month reduction in the delay between lung nodule detection and its definitive classification into benign or malignant.Ethics and dissemination The sponsor of this study is the University Hospital of Nice. The study was approved for France by the ethical committee CPP (Comités de Protection des Personnes) Sud-Ouest et outre-mer III (No. 2022-A01543-40) and the Agence Nationale du Medicament et des produits de Santé (Ministry of Health) in December 2023. The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations.Trial registration number NCT05704920.

This research focused on evaluating the technical viability of using biodiesel with a blending ratio of 40% v/v, which is expected to be implemented soon in Indonesia. Two kinds of biodiesel blends were prepared, a blend of 60% diesel fuel and 40% biodiesel (B40) and a blend of 60% diesel fuel, 30% biodiesel, and 10% hydrogenated vegetable oil (HVO) (B30D10). The fuels were tested on EuroII vehicles without any engine modifications through a 50,000 km endurance road test. Laboratory tests were also performed at certain traveled distances to evaluate various engine parameters, including power, fuel economy, exhaust emissions, and used engine oil properties. Engine components were inspected upon the completion of the road test. Cold-start ability was also examined to confirm the suitability of the investigated biofuels at low-temperature operating conditions in Indonesia. The road test results showed that vehicles fuelled with B40 and B30D10 could reach a distance of 50,000 km without encountering any technical issues. The laboratory evaluation during the road test indicated that B30D10 had a higher power and fuel economy than B40, with a maximum difference of 2%. Furthermore, B30D10 emitted lower CO, HC, and PM emissions than B40 throughout the distance traveled, with maximum differences of 11.4%, 14.7%, and 22.6%, respectively, but led to 15% higher NOx. Engine component inspection and used engine oil analysis confirmed the fulfillment of the manufacturer's recommendations for both B40 and B30D10. Finally, B40 and B30D10 were suitable for operating at low ambient temperatures in Indonesia, confirming them as practical options to be implemented in the nationwide 40% biodiesel blend fuel.

This service aims to increase the knowledge of the elderly in Kenongrejo Village regarding balanced nutrition and degenerative diseases. The method of implementing this service was socialization and mentoring. The evaluation instrument for this activity was the help of an evaluation rubric which was then analyzed descriptively. The results of this service showed that the knowledge of the elderly regarding food menu arrangements for the elderly increased by 45%; participants' understanding of various degenerative diseases that occurred in the elderly increased by 30%; awareness of the importance of routine health control for the elderly increased by 42%; participants' motivation in participating in outreach/counseling increased 30%; and implementation of socialization/counseling programs increased 100%. Based on the service activities that had been carried out, socialization and mentoring activities were going well and could provide changes in behavior patterns for the elderly in Kenongrejo Village.

Abstract Formal methods are proven techniques that provide a rigorous mathematical basis to software development. In particular, they allow the quality of development to be effectively improved by making accurate and explicit modelling, so that anomalies like ambiguities and incompleteness are identified in the early phases of the software development process. Semi‐formal UML models and formal Timed Automata models are used to design a telerehabilitation system through a practical approach based on abstraction and refinement. The formal verification of expected properties of the system is performed by the Uppaal tool. The motivation of this work is threefold: (i) showing the usefulness of formal methods to satisfy the validation needs of a medical telerehabilitation system; (ii) demonstrating our approach of system analysis through refinements to guide the development of a complex system; and (iii) highlighting, from a real‐life experience, the usefulness of models to involve the stakeholders all along the design of a system, from requirements to detailed specifications.

Corrosion is a chemical reaction between metal and chemical substances in free air influenced by typographical conditions, climate, and humidity levels around the metal object. If left unchecked, it can cause damage to the metal infrastructure, material losses, and harm in terms of safety and security. Therefore, a way to inhibit corrosion is needed by creating an environmentally friendly inhibitor from natural materials. One of them is by utilizing Sambiloti leaf as a natural inhibitor. Sambiloto leaves contain tannins which can inhibit corrosion well. This study aimed to determine the efficiency of Sambiloto leaves ethanol extract in inhibiting the corrosion rate of metals in the corrosive medium of well water. HCl was soaked for seven days to determine the correlation between the corrosion rate and extract concentration in different corrosive media. Sambiloto leaves were extracted using the soxhletation method using 96% ethanol solution, then distilled to obtain a pure extract. Sambiloto leaf extract was then varied in concentration, namely 1%, 5%, 10%, and 15%. The corrosive medium is well water and HCl, and the metal material used is nails. The results showed that adding Sambiloto extract with a concentration of 15% in both corrosive mediums had the highest inhibitor efficiency values, namely 97.32% in the corrosive HCl medium and 69.3% in the corrosive well water medium. The results of the regression analysis showed that the addition of Sambiloto extract had a significant effect on the corrosion rate in well water media. In contrast, in the HCl medium, the addition of Sambiloto extract did not significantly affect the corrosion rate.

Background: Innovative research training programmes funded by the European Union are essential for the forging of highly skilled researchers to tackle, via breakthrough ideas and solutions, the challenges of our society. Being able to track, measure and analyse innovative aspects of the Marie Sklodowska-Curie Actions, Innovative Training Networks under the Horizon2020 funding scheme enables the impact assessment of such programmes, while filtering best practices and the generated knowledge that could ultimately breed and create further innovation. In parallel, it helps the identification of areas for improvement, the understanding of new needs to be accommodated and the co-design and implementation of EU funding policy activities to further promote innovation and excellence for researchers across Europe and beyond. Methods: In this study, a novel methodological approach is proposed for tracking and analysing innovation, using a representative sample of projects. Basic innovation indicators are examined and considered from the existing literature and from the applicable Multi-Annual Framework Programme Horizon2020. Additional ones are defined, complemented by questionnaires/surveys findings, to capture innovative aspects for which the standard indicators do not apply. Data mining and data visualization tools are used for the collection and processing of data. Innovation Radar2 (IR) reports and HorizonResultsBooster3 services are also engaged for the cross-validation of the identified innovative aspects. Results/Conclusions: The study provides first-level input for policy-feedback activities, by identifying scientific domains and EU countries that may potentially require more attention for innovation generation. It highlights domains that are front-runners and can be used as examples or best practices for under-represented domains in terms of innovative outputs. Collaboration with organisations, defined as medium/high innovators, can increase innovation generation and success in future projects. Best practices are collected to serve as references for designing impactful future training programmes. The excellence of the H2020-MSCA-ITN actions is confirmed via the generated innovations.

Teaching Point: Recognizing the distinct imaging features of parosteal lipoma.

Innovative research training programmes funded by the European Union are essential for the forging of highly skilled researchers to tackle, via breakthrough ideas and solutions, the challenges of our society. Being able to track, measure and analyse innovative aspects of the Marie Sklodowska-Curie Actions, Innovative Training Networks under the Horizon2020 funding scheme enables the impact assessment of such programmes, while filtering best practices and the generated knowledge that could ultimately breed and create further innovation. In parallel, it helps the identification of areas for improvement, the understanding of new needs to be accommodated and the co-design and implementation of EU funding policy activities to further promote innovation and excellence for researchers across Europe and beyond. In this study, a novel methodological approach is proposed for tracking and analysing innovation, using a representative sample of projects. Basic innovation indicators are examined and considered from the existing literature and from the applicable Multi-Annual Framework Programme Horizon2020. Additional ones are defined, complemented by questionnaires/surveys findings, to capture innovative aspects for which the standard indicators do not apply. Data mining and data visualization tools are used for the collection and processing of data. Innovation Radar 2 (IR) reports and HorizonResultsBooster 3 services are also engaged for the cross-validation of the identified innovative aspects. The study provides first-level input for policy-feedback activities, by identifying scientific domains and EU countries that may potentially require more attention for innovation generation. It highlights domains that are front-runners and can be used as examples or best practices for under-represented domains in terms of innovative outputs. Collaboration with organisations, defined as medium/high innovators, can increase innovation generation and success in future projects. Best practices are collected to serve as references for designing impactful future training programmes. The excellence of the H2020-MSCA-ITN actions is confirmed via the generated innovations.

ABSTRACT The pathogenicity of Mycoplasma hominis is poorly understood, mainly due to the absence of efficient genetic tools. A polyethylene glycol-mediated transformation protocol was recently developed for the M. hominis reference strain M132 using the pMT85-Tet plasmid. The transformation efficiency remained low, hampering generation of a large mutant library. In this study, we improved transformation efficiency by designing M. hominis-specific pMT85 derivatives. Using the Gibson Assembly, the Enterococcus-derived tet(M) gene of the pMT85-Tet plasmid was replaced by that of a M. hominis clinical isolate. Next, the Spiroplasma-derived spiralin gene promoter driving tet(M) expression was substituted by one of three putative regulatory regions (RRs): the M. hominis arginine deiminase RR, the M. hominis elongation factor Tu RR, or the 68 bp SynMyco synthetic RR. SynMyco-based construction led to a 100-fold increase in transformation efficiency in M. hominis M132. This construct was also transformed into the M. hominis PG21 reference strain and three other clinical isolates. The transposon insertion locus was determined for 128 M132-transformants. The majority of the impacted coding sequences encoded lipoproteins and proteins involved in DNA repair or in gene transfer. One transposon integration site was in the mycoplasma immunoglobulin protease gene. Phenotypic characterization of the mutant showed complete disruption of the human antibody cleavage ability of the transformant. These results demonstrate that our M. hominis-optimized plasmid can be used to generate large random transposon insertion libraries, enabling future studies of the pathogenicity of M. hominis. IMPORTANCE Mycoplasma hominis is an opportunistic human pathogen, whose physiopathology is poorly understood and for which genetic tools for transposition mutagenesis have been unavailable for years. A PEG-mediated transformation protocol was developed using the pMT85-Tet plasmid, but the transformation efficiency remained low. We designed a modified pMT85-Tet plasmid suitable for M. hominis. The use of a synthetic regulatory region upstream of the antibiotic resistance marker led to a 100-fold increase in the transformation efficiency. The generation and characterization of large transposon mutagenesis mutant libraries will provide insight into M. hominis pathogenesis. We selected a transformant in which the transposon was integrated in the locus encoding the immunoglobulin cleavage system MIB–MIP. Phenotypic characterization showed that the wild-type strain has a functional MIB–MIP system, whereas the mutant strain had lost the ability to cleave human immunoglobulins.

Background: Innovative research training programmes funded by the European Union are essential for the forging of highly skilled researchers to tackle, via breakthrough ideas and solutions, the challenges of our society. Being able to track, measure and analyse innovative aspects of the Marie Sklodowska-Curie Actions, Innovative Training Networks under the Horizon2020 funding scheme enables the impact assessment of such programmes, while filtering best practices and the generated knowledge that could ultimately breed and create further innovation. In parallel, it helps the identification of areas for improvement, the understanding of new needs to be accommodated and the co-design and implementation of EU funding policy activities to further promote innovation and excellence for researchers across Europe and beyond. Methods: In this study, a novel methodological approach is proposed for tracking and analysing innovation, using a representative sample of projects. Basic innovation indicators are examined and considered from the existing literature and from the applicable Multi-Annual Framework Programme Horizon2020. Additional ones are defined, complemented by questionnaires/surveys findings, to capture innovative aspects for which the standard indicators do not apply. Data mining and data visualization tools are used for the collection and processing of data. Innovation Radar2 (IR) reports and HorizonResultsBooster3 services are also engaged for the cross-validation of the identified innovative aspects. Results/Conclusions: The study provides first-level input for policy-feedback activities, by identifying scientific domains and EU countries that may potentially require more attention for innovation generation. It highlights domains that are front-runners and can be used as examples or best practices for under-represented domains in terms of innovative outputs. Collaboration with organisations, defined as medium/high innovators, can increase innovation generation and success in future projects. Best practices are collected to serve as references for designing impactful future training programmes. The excellence of the H2020-MSCA-ITN actions is confirmed via the generated innovations.