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The article systematizes approaches to the definition of meta-universe essence as multi-dimensional spaces, which integrate multitude of virtual words, where digital copies of the real world (including business) are made, where participants can interact with each other and with surrounding objects. It was found out that meta-universes form a key trend in economy development in Russia in general and its certain branches and industries, which could foster productivity improvement and business-process optimization in the digital world. The authors analyzed examples of mixed reality (VR/AR-technologies), blockchain and crypto-currencies in Russia and abroad. Factors affecting the development of meta-universes, such as normative and legal, economic, technological, social were identified. The article enumerates risks and restrictions connected with the development of meta-universe technologies: cyberthreats and risks of big data protection, risks of the absence of common cash unit in meta-universes or rules of converting exchange means in meta-universes in usual exchange means, complexity of financing of developing technological projects due to prolonged market entering, insufficient number of experts in the field of virtual, augmented and mixed reality, blockchain, crypto-currencies, etc. The authors identified specific impact of metauniverses on the development of business in the digital environment (in virtual multi-dimensional spaces of metauniverses the pass-over to new economy of impressions speeds up and new possibilities for distance interaction are formed, the format of training and developing employees is transformed, digital doubles are built by developing accurate virtual copies of business-organizations and others). Final conclusions and recommendations were formulated concerning the necessity of taking into account the impact of normative and legal, economic, technological and social factors on business development in virtual spaces in meta-universes, as well as effective and potential threats and hazards connected with the development of economic activity in virtual spaces in order to realize potential of business in the field of new technological phenomenon of meta-universes.

Today's cell phones are now smartphones, providing a wide range of possibilities for their use, much more than just simple phones. The custom application for the Android operating system, based on an open-source platform for mobile devices is intended for the examination of cognitive functions: attention, concentration and fine motor skills in children of different age groups. The Neurogame application for mobile devices and web platform development is used for retrieving and analyzing mobile application data, providing relevant indicators for the executive functions of the respondents. Material and methods: The research included 50 children with the developmental disorders ADHD and dyslexia (study group) and 50 healthy children (control group), randomly selected, evenly represented by gender and age. Using the application, we determine attention, concentration and motor skills (reaction speed) as part of the executive functions of the respondents. The web platform has the purpose of gathering and processing the data from the mobile application, as well as their automatic visual representation. Results: The ANOVA test showed that there are no gender differences in all the studied groups. A statistical correlation analysis showed that age does not affect the results in healthy school children. In children with dyslexia, age affects positively for total hits and negatively for total misses. In children with ADHD, there is a positive correlation with age for all variables except total hits (t H). Student's T-test showed that there were significant differences for the variables' total hits (t H) and total reaction time (t h) in milliseconds between healthy school children and children with dyslexia. Additionally, Student's t-test indicated that there were significant differences for the variables' total tries (t T) and total hits (t H) between healthy school children and children with ADHD. Finally, Student's t-test indicated that there were significant differences for the variable total tries (t T) between children with dyslexia and children with ADHD. Multiple Regression Results showed a significant difference between healthy school children, children with ADHD and children with dyslexia for all variables (total tries (t T), total hits (t H), total misses (t M) and total reaction time in milliseconds (t h)). Conclusion: The Neurogame application provides a opportunity to assess the motor skills and concentration level, as well as the focus of the target population by measuring the total number of tries, the total number of hits, the total number of misses and the reaction time expressed in milliseconds which are defined as monitoring variables. The development of the web platform and the connection to the application enabled easier access and distribution of the analyzed results to the stakeholders (parents, teachers, therapists or health professionals) in order to further treat the ascertained condition. [ABSTRACT FROM AUTHOR]

The G2PDeep-v2 server is a web-based platform powered by deep learning, for phenotype prediction and markers discovery from multi-omics data in any organisms including humans, plants, animals, and viruses. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm on high-performance computing resources. Users can visualize the results of phenotype and markers predictions and perform Gene Set Enrichment Analysis for the significant markers to provide insights into the molecular mechanisms underlying complex diseases and other biological processes. The G2PDeep-v2 server is publicly available at https://g2pdeep.org/.

Giuseppe Antonio Palmiotti,1 Donato Lacedonia,1 Vito Liotino,2 Pietro Schino,3 Francesco Satriano,4 Pier Luigi Di Napoli,3 Eugenio Sabato,5 Vincenzo Mastrosimone,6 Alfredo Scoditti,7 Mauro Carone,8 Elio Costantino,9 Emanuela Resta,2 Ettore Attolini,10 Maria Pia Foschino Barbaro1 1Department of Medical and Surgical Sciences, Institute of Respiratory Diseases, University of Foggia, Foggia, Italy; 2Department of Cardiac, Thoracic, and Vascular Science, Institute of Respiratory Diseases, School of Medicine, University of Bari, Bari, Italy; 3Physiopathology Respiratory Unit, F Miulli General Hospital, Acquaviva delle Fonti, Bari, Italy; 4Pneumology Clinic, Vito Fazzi Hospital, Lecce, Italy; 5UOC of Pneumology, “N Melli” Hospital, San Pietro Vernotico, Italy; 6Division of Pulmonary Disease, Medical Center of Rehabilitation, Foundation Salvatore Maugeri, IRCCS, Marina di Ginosa, Italy; 7Department of Respiratory Diseases, San Camillo Clinic, Taranto, Italy; 8Division of Pulmonary Disease, Medical Center of Rehabilitation, Foundation Salvatore Maugeri, IRCCS, Cassano delle Murge, Italy; 9UOC of Pneumology, Hospital “Madonna delle Grazie”, Matera, Italy; 10Regional Health Agency (ARES), Bari, Italy Background: COPD is a disease associated with significant economic burden. It was reported that Global initiative for chronic Obstructive Lung Disease (GOLD) guideline-oriented pharmacotherapy improves airflow limitation and reduces health care costs. However, several studies showed a significant dissociation between international recommendations and clinicians’ practices. The consequent reduced diagnostic and therapeutic inappropriateness has proved to be associated with an increase in costs and a waste of economic resources in the health sector. The aim of the study was to evaluate COPD management in the Puglia region. The study was performed in collaboration with the pulmonology centers and the Regional Health Agency (AReS Puglia). Methods: An IT platform allowed the pulmonologists to enter data via the Internet. All COPD patients who visited a pneumological outpatient clinic for the first time or for regular follow-ups or were admitted to a pneumological department for an exacerbation were considered eligible for the study. COPD’s diagnosis was confirmed by a pulmonologist at the moment of the visit. The project lasted 18 months and involved 17 centers located in the Puglia region. Results: Six hundred ninety-three patients were enrolled, evenly distributed throughout the region. The mean age was 71±9 years, and 85% of them were males. Approximately 23% were current smokers, 63% former smokers and 13.5% never smokers. The mean post-bronchodilator forced expiratory volume in 1 second was 59%±20% predicted. The platform allowed the classification of patients according to the GOLD guidelines (Group A: 20.6%, Group B: 32.3%, Group C: 5.9% and Group D: 39.2%), assessed the presence and severity of exacerbations (20% of the patients had an exacerbation defined as mild [13%], moderate [37%] and severe [49%]) and evaluated the appropriateness of inhalation therapy at the time of the visit. Forty-nine percent of Group A patients were following inappropriate therapy; in Group B, 45.8% were following a therapy in contrast with the guidelines. Among Group C patients, 41.46% resulted in triple combination therapy, while ~14% of Group D patients did not have a therapy or were following an inappropriate therapy. In conclusion, 30% of all patients evaluated had been following an inadequate therapy. Subsequently, an online survey was developed to inquire about the reasons for the results obtained. In particular, we investigated the reasons why 30% of our population did not follow the therapy suggested by the GOLD guidelines: 1) why was there an excessive use of inhaled corticosteroids, 2) why a significantly high percentage was inappropriately treated with triple therapy and 3) why a consistent percentage (11%) of Group D patients were not treated at all. Conclusion: The data provides an overview on the management of COPD in the region of Puglia (Italy) and represents a resource in order to improve appropriateness and reduce the waste of health resources. Keywords: COPD, appropriateness, web platform, health care spending, online survey

Forest operations engineering deals with all the essential infrastructure operations aiming at the efficient management of forested areas, which constitutes a prerequisite for the development of mountainous economies. Thus, the need for addressing this objective in an effective way, in conjunction with other issues associated with the protection and preservation of forest wealth, is of utmost importance. There are a whole range of forest operations for which a decision-making web-tool can potentially be utilized. This paper introduces an online decision-making tool for managing forest roads, which uses information derived from rainfall-runoff simulation. The proposed tool can be used to provide information about forest works maintenance and damage prevention in a forest environment. Furthermore, the tool assists in visualizing forest operations and achieves the optimization of their management. The development of the decision-making tool is also described, and a real case study (the Koupa watershed) is presented in detail to demonstrate its application and resulting advantages. The rainfall-runoff simulation was conducted for ten sub-basins in order to evaluate the efficiency of the corresponding culverts in the Koupa watershed.

The development of small molecules that selectively target the cannabinoid receptor subtype 2 (CB2R) is emerging as an intriguing therapeutic strategy to treat neurodegeneration, as well as to contrast the onset and progression of cancer. In this context, in-silico tools able to predict CB2R affinity and selectivity with respect to the subtype 1 (CB1R), whose modulation is responsible for undesired psychotropic effects, are highly desirable. In this work, we developed a series of machine learning classifiers trained on high-quality bioactivity data of small molecules acting on CB2R and/or CB1R extracted from ChEMBL v30. Our classifiers showed strong predictive power in accurately determining CB2R affinity, CB1R affinity, and CB2R/CB1R selectivity. Among the built models, those obtained using random forest as algorithm proved to be the top-performing ones (AUC in validation ≥0.96) and were made freely accessible through a user-friendly web platform developed ad hoc and called ALPACA (https://www.ba.ic.cnr.it/softwareic/alpaca/). Due to its user-friendly interface and robust predictive power, ALPACA can be a valuable tool in saving both time and resources involved in the design of selective CB2R modulators., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Progress towards sustainable development ultimately depends on policy makers’ and practitioners’ capacities to protect Natural Capital (NC) stocks so that they are not exploited beyond Earth’s capability to renew them. This involves a sound understanding of the benefits and values derived by society from NC and ecosystem services (ES). Scientific evidence to support this understanding is growing rapidly, but access to the data, methods, tools and expertise that underpins this evidence base is fragmented, particularly at the science – policy – practice interfaces. Two large EU research projects have therefore developed a joint knowledge platform – called Oppla – aimed at providing access to a wide range of resources on NC and ES. This new approach in the EU Research Area aims not only at integrating knowledge into one single platform, but also at making this knowledge operational amongst communities of science, policy and practice. Furthermore, it fosters the more efficient use of research funds by providing an open and freely available platform in which existing and new NC and ES projects can integrate their outcomes. This paper focuses on the knowledge integration and some guidance tools within Oppla to help users to find research outcomes. [ABSTRACT FROM AUTHOR]

In our study, we present a proactive decision support tool able to compute the impacts of different possible scenarios for territories impacted by mountain risks. The objective of this work was to develop and test various hazard and risk assessment methods, and to implement them into a web-application platform able to show possible risks induced by global change on ecosystems and society. Four case studies were selected for their representativeness: One located in a Pyrenean valley, others in the French Alps. Methodology addressed several points. The first one was on the identification of the impacts of global environmental changes (climatic situations, land use, and socio-economic systems) on identified hazards. The second one was on the analysis of these impacts in terms of vulnerability (e.g., the places and the physical modifications of impacted stakes, as well as levels of perturbation). The third one was on the integration of developed methodologies in a single coherent framework in order to investigate and map indicators of vulnerability. The last one was on the development of a demonstration platform with GIS (Geographic Information System) capabilities and usable on the web. The architecture and the main features of the web-platform are detailed within several cases for which hazard and impact assessments are evaluated for not only past and present, but also future periods. This web-tool, mostly dedicated to stakeholders, has proven its usefulness to test various socio-economical pathways, because multiple scenarios, considered as probable in inhabited valleys, can be benchmarked, analyzed, and compared.

Background: Available methods to simulate nucleotide or amino acid data typically use Markov models to simulate each position independently. These approaches are not appropriate to assess the performance of combinatorial and probabilistic methods that look for coevolving positions in nucleotide or amino acid sequences. Results: We have developed a web-based platform that gives a user-friendly access to two phylogenetic-based methods implementing the Coev model: the evaluation of coevolving scores and the simulation of coevolving positions. We have also extended the capabilities of the Coev model to allow for the generalization of the alphabet used in the Markov model, which can now analyse both nucleotide and amino acid data sets. The simulation of coevolving positions is novel and builds upon the developments of the Coev model. It allows user to simulate pairs of dependent nucleotide or amino acid positions. Conclusions: The main focus of our paper is the new simulation method we present for coevolving positions. The implementation of this method is embedded within the web platform Coev-web that is freely accessible at http://coev.vital-it.ch/, and was tested in most modern web browsers. [ABSTRACT FROM AUTHOR]

Forest operations engineering deals with all the essential infrastructure operations aiming at the efficient management of forested areas, which constitutes a prerequisite for the development of mountainous economies. Thus, the need for addressing this objective in an effective way, in conjunction with other issues associated with the protection and preservation of forest wealth, is of utmost importance. There are a whole range of forest operations for which a decision-making web-tool can potentially be utilized. This paper introduces an online decision-making tool for managing forest roads, which uses information derived from rainfall-runoff simulation. The proposed tool can be used to provide information about forest works maintenance and damage prevention in a forest environment. Furthermore, the tool assists in visualizing forest operations and achieves the optimization of their management. The development of the decision-making tool is also described, and a real case study (the Koupa watershed) is presented in detail to demonstrate its application and resulting advantages. The rainfall-runoff simulation was conducted for ten sub-basins in order to evaluate the efficiency of the corresponding culverts in the Koupa watershed. [ABSTRACT FROM AUTHOR]

The field of breath analysis lacks a fully automated analysis platform that enforces machine learning good practice and enables clinicians and clinical researchers to rapidly and reproducibly discover metabolite patterns in diseases. We present BALSAM—a comprehensive web-platform to simplify and automate this process, offering features for preprocessing, peak detection, feature extraction, visualization and pattern discovery. Our main focus is on data from multi-capillary-column ion-mobility-spectrometry. While not limited to breath data, BALSAM was developed to increase consistency and robustness in the data analysis process of breath samples, aiming to expand the array of low cost molecular diagnostics in clinics. Our platform is freely available as a web-service and in form of a publicly available docker container. [ABSTRACT FROM AUTHOR]

This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts.