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One considers a group S of subjects and one uses the measured values of EEG waves and the levels of anxiety given by the psychologists for the members of S in order to construct a monotone measure µ. This measure µ is such that the levels of anxiety of the members of S are Choquet integrals with respect to µ. One infers that this is true for any other subject. This inference is validated by comparing the values obtained via the above mentioned method with the results given by the psychologists for another group of subjects S’. We think that this procedure is completely new for the computation of the anxiety degree.

As artificial intelligence (AI) is becoming increasingly integrated into critical infrastructures, it brings about both transformative benefits and unprecedented risks. AI has the potential to revolutionize the efficiency, reliability, and responsiveness of essential services, but it can also offer these benefits along with the vulnerability to a growing array of sophisticated adversarial attacks. This paper explores the evolving landscape of adversarial threats to AI systems, highlighting the potential of nation-state actors to exploit these vulnerabilities for geopolitical gains. A range of adversarial techniques is examined, including dataset poisoning, model stealing, and privacy inference attacks, and their potential impact on sectors such as energy, transportation, healthcare, and water management is assessed. The consequences of successful attacks are substantial, encompassing economic disruption, public safety risks, national security implications, and the erosion of public trust. Given the escalating sophistication of these threats, this paper proposes a comprehensive security framework that includes robust incident response protocols, specialized training, the development of a collaborative ecosystem, and the continuous evaluation of AI systems. The findings of this study 11 underscore the critical need for a proactive approach to AI security in order to safeguard the future of critical infrastructures in an increasingly AI-driven world.

Abstract Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerometer data. Validation involved two diverse cohorts, including over 1000 participants without gait labels, as well as 83 participants with labeled data: older adults with Parkinson's disease, proximal femoral fracture, chronic obstructive pulmonary disease, congestive heart failure, and healthy adults. ElderNet presented high accuracy (96.43 ± 2.27), specificity (98.87 ± 2.15), recall (82.32 ± 11.37), precision (86.69 ± 17.61), and F1 score (82.92 ± 13.39). The suggested method yielded superior performance compared to two state-of-the-art gait detection algorithms, with improved accuracy and F1 score (p

The perceived disadvantage faced by high school students from rural areas in pursuing higher education is often associated with the fact that these areas are by default affected by socio-economic disadvantages. The analysis of the results from the high school baccalaureate examination for Romania, which is mandatory for admission to higher education, and which plays a major role in ranking the applicants, shows the potential outcomes of the university admission policy targeting high school baccalaureate holders from rural areas. Under different scenarios, this can lead to either targeted admission places being allocated to students that would have been otherwise successfully admitted by competing on general admission places or could have helped students from other disadvantaged backgrounds. These results may help as a basis for guiding policy designs that can better target admission places for students from disadvantaged backgrounds.

Abstract Influenza viruses are responsible for a high number of infections and hospitalizations every year. In this study, we aimed to identify clinical and host-specific factors that influence the duration of hospitalization and the progression to acute respiratory failure (ARF) in influenza. We performed an analysis of data from a prospective active influenza surveillance study that was conducted over five seasons (2018/19 to 2022/23). A total of 1402 patients with influenza were included in the analysis, the majority of which (64.5%) were children (under 18 years), and 9.1% were elderly. At least one chronic condition was present in 29.2% of patients, and 9.9% of patients developed ARF. The median hospital stay was 4 days (IQR: 3, 6 days). The most important predictors of prolonged hospital stay and development of ARF were extremes of age (infants and elderly), presence of chronic diseases, particularly the cumulus of at least 3 chronic diseases, and late presentation to hospital. Among the chronic diseases, chronic obstructive pulmonary disease, cardiovascular disease, cancer, diabetes, obesity, and chronic kidney disease were strongly associated with a longer duration of hospitalization and occurrence of ARF. In this context, interventions aimed at chronic disease management, promoting influenza vaccination, and improving awareness and access to health services may contribute to reducing the impact of influenza not only in Romania but globally. In addition, continued monitoring of the circulation of influenza viruses is essential to limit their spread among vulnerable populations.

E-government plays a vital part in the progress of countries in the European Union, especially in Eastern European Member States. It facilitates citizens, irrespective of their geographic location or socioeconomic status, in accessing government services and information, as well as participating in digital interactions with public authorities. The current paper analyses the evolution of e-government in Eastern European Member States in terms of the general populations’ ability to utilize the internet for downloading and submitting government official forms. Also, the current research paper aims to provide a predictive model of the evolution of digital interactions with public authorities in Romania by using time series data, specific statistical tests, and Holt's additive double exponential smoothing model for forecasting. The results suggest that Romania has potential for growth in digital interactions with public authorities and acknowledge the need for investments in digital literacy programs, simplification of administrative procedures, and improvement of regional digital infrastructure.

Review of: Carmen Borbély, Erika Mihálycsa, Petronia Petrar (eds.), Temporalities of Modernism, Milano, Ledizioni, 2022

The rising prevalence of eye disorders has raised concerns, emphasizing the need to accelerate the detection of retinal diseases. Early and accurate classification of these conditions is crucial for timely diagnosis and effective treatment in order to address critical situations. The recent advancements in retinal imaging have enhanced the diagnosis and management of Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME) or Drusen and the deep learning-based applications on Optical Coherence Tomography (OCT) images have further revolutionized the field by enabling automated, precise, and efficient disease classification, paving the way for earlier interventions and improved patient outcomes. This study investigates the use of Vision Transformers (ViTs) and Convolutional Neural Networks (CNNs) for automated retinal disease classification. Three models were implemented: ViT, DeepViT, and a hybrid model combining ResNet50 with ViT, trained and evaluated on a publicly available OCT dataset. The hybrid model achieved the highest accuracy of 99.97%, thanks to its ability to capture both local and global features. This study underscores the potential of ViTs in medical image analysis and their integration with CNNs to develop accurate, robust, and scalable diagnostic tools, showing great promise for clinical applications.

Abstract The objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub height set at 80 m. Wind power potential was assessed using the Weibull analysis. The values of the scale coefficient c were determined, and a large monthly variation was observed, with values ranging from 1.92 to 8.36 m/s and an annual value of 4.95 m/s. Monthly values for the shape coefficient k varied between 0.86 and 1.53, with an annual value of 1.07. Additionally, the capacity factor of the turbines was determined, ranging from 17.75 to 22.22%. The Vestas turbine, with a nominal power of 2 MW and a capacity factor of 22.22%, proved to be the most efficient wind turbine for the specific conditions of the location. The quantity of greenhouse gas emissions that will be reduced if this type of turbine is implemented was also calculated, considering the average CO2 emission intensity factor (kg CO2/kWh) of the national electricity system.

The digitisation of public administration offers many benefits for both employees and citizens, improving resource management and fostering the development of innovative public services. Effective digitisation prioritises the needs of citizens, with an emphasis on simplicity, speed and transparency in public services. This comprehensive digital transformation presents opportunities for increased transparency, accountability, efficiency and improved tax collection, which have become even more crucial during the COVID-19 pandemic as online solutions have soared. Our research provides an in-depth analysis of strategic management in public administrations, focusing in particular on the impact of digitisation on local tax revenue collection in Romania over the period 2015-2021. Authority for the Digitalization of Romania plays a key role in advancing the digitisation of public administration. This thesis examines the Authority’s contributions to the transformation of public services through digital means, with a focus on improving efficiency, transparency and citizen engagement. Analysing key initiatives and strategic frameworks implemented by the Authority, the research highlights significant progress in streamlining administrative processes and improving public service delivery. The study also explores the challenges faced in the digital transformation journey and provides recommendations for overcoming these obstacles. Using data from the national e-payment platform ghiseul.ro, we used panel data analysis, complemented by reliability and robustness testing, to explore this impact. Through comprehensive analysis and case studies, the paper highlights the critical impact of Romania’s efforts on the digital evolution of its public sector, promoting a more responsive and efficient governance model.

Abstract Background Multiple sclerosis is a progressive neurological disease that affects the central nervous system, resulting in various symptoms. Among these, impaired mobility and fatigue stand out as the most prevalent. The progressive worsening of symptoms adversely alters quality of life, social interactions and participation in activities of daily living. The main objective of this study is to bring new insights into the impact of a multidisciplinary inpatient rehabilitation on supervised walking tests, physical activity (PA) behavior and everyday gait patterns. Methods A total of 52 patients, diagnosed with multiple sclerosis, were evaluated before and after 3 weeks of inpatient rehabilitation. Each measurement period consisted of clinical assessments and 7 days home monitoring using foot-mounted sensors. In addition, we considered two subgroups based on the Expanded Disability Status Scale (EDSS) scores: ‘mild’ (EDSS

Explosion protection is of particular importance for safety as explosions also endanger the health of workers due to the uncontrolled effects of flames and pressure, the presence of harmful reaction products and the consumption of oxygen in the ambient air breathed by workers. CuAlBe alloy is proposed as a solution for mechanical actuators such as gears that work in environments with possible explosive atmosphere. Made of CuBe master alloy and pure aluminum in a induction furnace the material present large grains in melted state. After the hot rolling (heated 600s at 900°C) of the ingots small variation of chemical composition was observed based on the oxidation of the material, appearance of small cracks on the edges and a preferential orientation of the grains along the lamination direction. Scanning electron microscopy (SEM) was used to characterize the microstructural states of CuAlBe as laminated and heat treated states.

Gut microbiota has complex immune functions, related to different pathologies, including multiple sclerosis (MS).This study evaluated the influence of treatments on gut microbiota in people with MS (PwMS). The research comprised 60 participants, including 39 PwMS and 21 healthy controls (HC). Among the PwMS, 20 were prescribed a disease-modifying therapy (DMT), either interferon beta1a or teriflunomide, while 19 received a combination of classical DMT and an immunoglobulin Y (IgY) supplement. For each participant, two sets of gut samples were collected: one at the study's outset and another after two months. Alpha and beta diversity analyses revealed no significant differences between groups. In comparison to the HC, the MS group exhibited an increase in Prevotella stercorea and a decrease in Faecalibacterium prausnitzii. Following treatment, individuals with MS showed enrichment in Lachnospiraceae and Streptococcus. The second sample, compared to the first one, demonstrated an increase in Bifidobacterium angulatum and a decrease in Oscillospira for individuals with MS. Gut microbiota diversity in PwMS is not significantly different to HC. However, specific taxonomic changes indicate the presence of a dysbiosis state. The use of DMTs and immunoglobulin Y supplements may contribute to alterations in microbial composition, potentially leading to the restoration of a healthier microbiome.

Nullities represent procedural sanctions that intervene if the fundamental principles of the criminal process are not respected. What is imperative to mention is the fact that these procedural sanctions operate only judicially, which means that they must be ascertained by the judicial body. Unlike the old regulation, the new criminal procedure code regulates new cases of relative nullity and essentially changes the procedure for the application of nullities, the new legislator wanting to impose a new technique for approaching the drafting of the rules. Thus, we find the rules that regulate the conduct of the criminal process in the code of criminal procedure, Constitution, special laws, CEDO s.a. With regard to the procedural phase in which these rules may be violated, the cited provisions are applicable from the start of the criminal prosecution in rem, throughout the criminal prosecution, the preliminary chamber, in court, appeal, extraordinary appeals, including in the execution of court decisions.

This investigation examines the influence of Laval nozzle geometry on thrust production using the method of characteristics. It explores various divergent section configurations, analyzing their impact on nozzle design and performance. Comparative analysis of software tools, study of supersonic flow phenomena, and application of the method of characteristics form the core of this research. Findings showcase strong agreement between computational tools, emphasizing the Mach number's role in divergent section shape variations and thrust force. Additionally, the study scrutinizes over-expansion and under-expansion phenomena, validated through computational simulations. Future research should be aimed at enhancing computational methodologies and investigating additional parameters affecting nozzle performance, promising advancements in rocket propulsion technology.

Acinetobacter baumannii, a notorious opportunistic pathogen, presents a formidable challenge in both clinical and environmental fields due to its resilience and ability to acquire resistance. This study undertook a comprehensive analysis of 183 A. baumannii isolates collected between 2019 and 2022 from intra-hospital infections (IHI), hospital sewages (Hs), wastewater treatment plants (WWTP), and adjacent river waters from two Southern cities, focusing on their resistome, virulome, and mobilome through isolation on chromogenic media, identification by MALDI-TOF-MS and antibiotic susceptibility testing by disk diffusion) followed by genotypic characterization [Whole Genome Sequencing (WGS), 3rd generation sequencing through the MinION (ONT) platform, pangenome description, and respectively horizontal gene transfer through conjugation assays]. Our findings reveal significant genomic plasticity and the prevalence of high-risk international clones, underlining the potential of these isolates to act as reservoirs for antibiotic resistance genes (ARGs) that could be dynamically exchanged between clinical and environmental settings through mobile genetic elements (MGEs) such as the pMAL1 plasmids and the critical role of WWTPs in the persistence and spread of A. baumannii. Moreover, our study presents the first report of the co-occurrence of blaOXA-23 and blaOXA-72 in A. baumannii ST2 clone. Thus, our research underscores the necessity for integrated surveillance and targeted interventions across healthcare and environmental sectors to mitigate the risk posed by this adaptable pathogen.

In this study, we leverage sentiment analysis to investigate public perception towards environmental issues as conveyed through global news articles and its potential implications on the transition to a low-carbon economy. Utilizing an extensive corpus of news articles sourced globally, we deploy Natural Language Processing (NLP) techniques to quantify sentiment in these articles, capturing public sentiment’s dynamism and complexity towards various environmental issues. Our methodology involves sentiment scoring of key aspects like “climate change”, “climate policy”, “renewable energy”, “solar energy”, “wind energy”, and “environmental impact” which facilitated a detailed sentiment trend analysis over time. We also incorporated a Latent Dirichlet Allocation (LDA) model to conduct topic modelling, identifying five major topics recurring in the discourse. Our correlation analysis uncovers interesting relationships such as a positive correlation between sentiment scores of “low carbon” and “electric cars”, and a negative correlation between “greenhouse gas emissions” and “electric cars". The findings indicate that public sentiment towards environmental issues is not only multifaceted but also evolving, with significant implications for policy-making and stakeholder engagement in the low-carbon transition. These results exemplify sentiment analysis as a powerful tool in understanding public perception, providing actionable insights for researchers, policymakers, and stakeholders involved in environmental issues and the low-carbon economy transition.

Drinking water has long been a free resource, but its cost is rising due to increased pollution of both surface and aquifer water sources. Drinking water requires special treatment to be potable and usable by the general public, treatments that consume a certain amount of energy. In addition, the treatment process of wastewater before it is discharged into the environment consumes energy. According to the study, the energy required for wastewater treatment is significantly greater than the energy required for preparing drinking water. Water treatment is a significant source of GHG emissions due to the use of energy and chemicals, and reducing energy consumption would significantly reduce our overall carbon footprint. Furthermore, the UN’s Sustainable Development Goals encourage access to safe drinking water and sanitation while also calling for greater resource efficiency. This research aims to provide an overview of the energy used in water treatment. This study attempts to depict the energy used in water treatment. Electricity consumption for water supply and wastewater treatment is substantial and has a significant environmental impact, particularly in countries where electricity is generated using fossil fuels.

Decarbonization of the energy sector to mitigate the consequences of climate change is possible by incorporating a greater share of electricity from renewable sources and thus reducing the share of fossil fuels in the energy mix, improving energy efficiency in general and increasing energy storage capacities. Renewable energies are increasingly permeating energy systems, causing significant shifts in the energy production mix. The success of transforming the electricity mix is dependent on the variability of renewable energy sources such as solar photovoltaic, wind, biomass, and hydro. The share of renewable sources in Romania’s energy mix was determined based on real data on electricity generation and consumption in 2019. However, the current electricity consumption has significantly surpassed the electricity produced from renewable sources. Specifically, the combined contribution of hydro, solar photovoltaic, wind, and biomass energy accounted for 39.86% of the total electricity consumption.

Abstract Background Increased physical activity (PA) is recommended after an acute coronary event to prevent recurrences. Whether patients with acute coronary event actually increase their PA has not been assessed using objective methods such as accelerometer. We aimed to assess the subjectively and objectively measured physical activity (PA) levels of patients before and after an acute coronary event. Methods Data from the three follow-up surveys of a prospective study conducted in Lausanne, Switzerland. Self-reported PA was assessed by questionnaire in the first (2009–2012) and second (2014–2017) follow-ups. Objective PA was assessed by a wrist-worn accelerometer in the second and third (2018–2021) follow-ups. Participants who developed an acute coronary event between each survey period were considered as eligible. PA levels were compared before and after the event, and changes in PA levels were also compared between participants who developed an acute event with three gender and age-matched healthy controls. Results For self-reported PA, data from 43 patients (12 women, 64 ± 9 years) were used. No differences were found for all PA levels expressed in minutes/day before and after the event: moderate PA, median and [interquartile range] 167 [104–250] vs. 153 [109–240]; light PA: 151 [77–259] vs. 166 [126–222], and sedentary behaviour: 513 [450–635] vs. 535 [465–642] minutes/day. Comparison with gender- and age-matched healthy controls showed no differences regarding trends in reported PA. For accelerometer-assessed PA, data from 32 patients (16 women, 66 ± 9 years) were used. No differences were found for all PA levels expressed in minutes/day before and after the event: moderate PA: 159 [113–189] vs. 141 [111–189]; light PA: 95.8 [79–113] vs. 95.9 [79–117], and sedentary behaviour: 610 [545–659] vs. 602 [540–624]. Regarding the comparison with gender- and age-matched healthy controls, controls had an increase in accelerometer-assessed sedentary behaviour as % of day: multivariable adjusted average standard error 2.7 ± 0.6, while no increase was found for cases: 0.1 ± 1.1; no differences were found for the other PA levels. Conclusion Patients do not seem to change their PA levels after a first coronary event. Our results should be confirmed in larger samples.

Abstract This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987.

The "waiver of criminal prosecution" institution was introduced into Romanian criminal procedural legislation by Law no. 135/2010 on the Code of Criminal Procedure. It appears as an exception to the principle of the legality of the criminal process - regulated by the Romanian legislator in favor of the principle of expediency. The legislator opted for the introduction of this institution in the legislation, considering the costs involved in the activity of criminal investigation and trial in the case of certain crimes. The appearance of this institution "justifies", to some extent, the non-taking over by the legislator in the new provisions of the content provided by art. 181 of the former Criminal Code (1969). The provisions included in the content of art. 181 of the previous Criminal Code (1969) allowed the judicial bodies to find that some acts provided for by the criminal law did not present the social danger of a crime, which allowed the application to the perpetrator of an administrative measure provided for in Article 91 of the previous Criminal Code (1969).

This study explores the inhibitory potential of the flavonoids resokaempferol and tectochrysin against both wild-type and H1047R mutant forms of PI3Kα, aiming to expand the repertoire of targeted cancer therapies. Employing an array of computational techniques, including Density Functional Theory (DFT), calculations of electronic parameters such as the energies of the frontier molecular orbitals, Molecular Electrostatic Potential (MEP) mapping, and Molecular Docking, we investigate in detail the molecular interactions of these compounds with the PI3Kα kinase. Our findings, corroborated by DFT calculations performed based on the B3LYP (Becke, three-parameter, Lee-Yang-Parr) hybrid functional and the 6-311G++(d,p) basis set, align well with experimental benchmarks and indicate substantial inhibitory efficacy. Further analysis of chemical potential and bioavailability confirmed the drug-like attributes of these flavonoids. Binding affinity and selectivity were rigorously assessed through self-docking and cross-docking against the PIK3CA PDB structures 7K71 and 8TS9. The most promising interactions were validated using Pairwise Structure Alignment and MolProbity analysis of all-atom contacts and geometry. Collectively, these results highlight the flavonoids’ potential as PI3Kα inhibitors and exemplify the utility of natural compounds in the development of precise anticancer treatments.

This paper outlines the development phases of a wave-driven Helicon Plasma Thruster for cutting-edge Low Earth Orbit (LEO) constellations. The two-stage ambipolar electric propulsion (EP) system combines the efficient ionization of an ultra-compact helicon reactor with plasma acceleration based on an ambipolar electric field provided by a magnetic nozzle. This paper reveals maturation challenges associated with an emerging EP system in the hundreds-watt class, followed by outlook strategies. A 3 cm diameter helicon reactor was operated using argon gas under a time-modulated RF power envelope ranging from 250 W to 500 W with a fixed magnetic field strength of 400 G. Magnetically enhanced inductively coupled plasma reactor characteristics based on half-wavelength right helical and Nagoya Type III antennas under capacitive (E-mode), inductive (W-mode), and wave coupling (W-mode) were systematically investigated based on Optical Emission Spectroscopy. The operation characteristics of a wave-heated reactor based on helicon configuration were investigated as a function of different operating parameters. This work demonstrates the ability of two-stage HPT using a compact helicon reactor and a cusped magnetic field to outperform today’s LEO spacecraft propulsion.