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This exploratory study seeks to design a service logic business model framework for novice entrepreneurs launching startups in the transformational tourist clusters considering the key stakeholders' interests and understanding the interests of those tourism customers seeking „conscious travel‟ to reinvent themselves and the world around them. The research combines phenomenographical and constructive approaches. Based on thematic content analysis of in-depth interviews with 12 entrepreneurs, 5 host providers of tourism services, and 30 travelers, as well as 7 co-creative workshops, we argue that a three-dimensional perspective on transformative tourism services suits the tasks of value co-creation in a collaborative peer-to-peer cluster-type networks. The key stakeholders in this framework are a service provider (startup), a host partner at the destination and local tourist clusters (“salt of the earth”), and a target customer. The proposed business model framework will enable novice transformative tourism entrepreneurs to experiment with finding a profitable business model in a lean format. The article also examines the impact of digital travel services on the development of the tourism industry.

Dear Colleagues!We are glad to present the 11th Edition of the Standards of Specialized Diabetes Care. These evidence-based guidelines were designed to standardize and facilitate diabetes care in all regions of the Russian Federation.The Standards are updated on the regular basis to incorporate new data and relevant recommendations from national and international clinical societies, including World Health Organization Guidelines (WHO), International Diabetes Federation (IDF), European Association for the Study of Diabetes (EASD), American Diabetes Association (ADA), American Association of Clinical Endocrinologists (AACE), International Society for Pediatric and Adolescent Diabetes (ISPAD) and Russian Association of Endocrinologists (RAE). Current edition of the “Standards” also integrates results of completed randomized clinical trials, as well as findings from the national studies of diabetes mellitus (DM), conducted in close partnership with a number of Russian hospitals.Latest data indicates that prevalence of DM in the world increased during the last decade more than two-fold, reaching some 537 million patients by the end of 2021. According to the current estimation by the International Diabetes Federation, 643 million patients will be suffering from DM by 2030 and 783 million by 2045.Like many other countries, Russian Federation experiences a sharp rise in the prevalence of DM. According to Russian Federal Diabetes Register, there are at least 4 962 762 patients with DM in this country on 01.01.2023 (3,42% of population) with 92,3% (4 581 990) – Type 2 DM, 5,6% (277 092) – Type 1 DM and 2,1% (103 680) – other types of DM, including 8 758 women with gestational DM. However, these results underestimate real quantity of patients, because they consider only registered cases. Results of Russian epidemiological study (NATION) confirmed that 54% of patients with Type 2 DM are undiagnosed. So real number of patients with DM in Russia is 11-12 million patients (about 7% of population). This is a great long-term problem, because a lot of patients are not diagnosed, so they don’t receive any treatment and have high risk of vascular complications.Severe consequences of the global pandemic of DM include its vascular complications: nephropathy, retinopathy, coronary, cerebral and peripheral vascular disease. These conditions are responsible for the majority of cases of diabetes-related disability and death.In accordance with the Federal Law № 489-FZ of 25.12.2018 medical care should be provided on the basis of the clinical recommendations. Therefore, clinical recommendations posted in the rubricator of the Ministry of Health of the Russian Federation (https://cr.minzdrav.gov.ru) being the priority.This edition of the Algorithms for Specialized Care for Patients with Diabetes Mellitus contains the main information from the clinical guidelines for the management of diabetes mellitus in adults and children (“Type 1 Diabetes in Children (2022)”, “Type 1 Diabetes in Adults (2022)”, “Type 2 diabetes mellitus in children (2021)”, “Type 2 diabetes mellitus in adults (2022)”), as well as the updated data.New information has been added about indications for using of antihyperglycemic drugs and their instructional restrictions; algorithm of treatment of type 2 diabetes mellitus has been updated; clarifications have been made on the range of glycemic control in pregnant women; information on the treatment of diabetic complications and the management of pediatric patients has been added. In 2023, Russian diabetology suffered an unbearable loss - Alexander Yuryevich Mayorov, who was the executive editor of the previous issues and an active participant of the work on all the previous editions of “Algorithms” from the moment they were founded, passed away. This publication is dedicated to the memory of Alexander Yuryevich, who was an example of the service to patients and medicine, a friend, teacher, mentor, generously sharing his knowledge and the sample of the execution of the medical duty to all of us. On behalf of the Working Group

A high percentage of failures of new products is considerably associated with management issues at the initial, with a large amount of uncertainty, stage of product development. Taking into account the fact that the characteristics and functionality of the future product are determined exactly at the initial stage, the management of the process here is of decisive importance. In the digital transformation process, companies rethink the product development management process and, correspondingly, the competence model of product managers. The purpose of the paper is to identify the key competencies (qualities, personal characteristics and abilities allowing to carry out professional activity key tasks) of the digital era product managers, as well as testing the design and project approaches in developing their competencies. Getting primary information about the main professional tasks was provided through in-depth interviews with successful product managers from the following industries: internet and telecommunications, software, pharma and finance. Two typical profiles/types of product managers were identified and called «technologically-oriented» and «business-oriented». As a result of the empirical research the key universal competencies of product managers to manage innovative products development effectively have been revealed. The partial overlap with the competences of innovation entrepreneurs, identified earlier, was discovered. for the development of key competencies, the innovation training program was developed and tested. The statistical analysis results showed that project based learning in combination with design thinking, Lean Startup & Customer Development, as well as modern digital rapid prototyping technique application, provide positive dynamics in the development of revealed key competencies for beginning product managers.

Place cells and grid cells in the hippocampal formation are thought to integrate sensory and self-motion information into a representation of estimated spatial location, but the precise mechanism is unknown. We simulated a parallel attractor system in which place cells form an attractor network driven by environmental inputs and grid cells form an attractor network performing path integration driven by self-motion, with inter-connections between them allowing both types of input to influence firing in both ensembles. We show that such a system is needed to explain the spatial patterns and temporal dynamics of place cell firing when rats run on a linear track in which the familiar correspondence between environmental and self-motion inputs is changed. In contrast, the alternative architecture of a single recurrent network of place cells (performing path integration and receiving environmental inputs) cannot reproduce the place cell firing dynamics. These results support the hypothesis that grid and place cells provide two different but complementary attractor representations (based on self-motion and environmental sensory inputs, respectively). Our results also indicate the specific neural mechanism and main predictors of hippocampal map realignment and make predictions for future studies., (Copyright © 2019 Laptev and Burgess.)

The classification of sleep stages is the first and an important step in the quantitative analysis of polysomnographic recordings. Sleep stage scoring relies heavily on visual pattern recognition by a human expert and is time consuming and subjective. Thus, there is a need for automatic classification. In this work we developed machine learning algorithms for sleep classification: random forest (RF) classification based on features and artificial neural networks (ANNs) working both with features and raw data. We tested our methods in healthy subjects and in patients. Most algorithms yielded good results comparable to human interrater agreement. Our study revealed that deep neural networks (DNNs) working with raw data performed better than feature-based methods. We also demonstrated that taking the local temporal structure of sleep into account a priori is important. Our results demonstrate the utility of neural network architectures for the classification of sleep.

To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with a consensus of human expert annotations. The winning team had no prior experience with EM images, and employed a convolutional network. This "deep learning" approach has since become accepted as a standard for segmentation of EM images. The challenge has continued to accept submissions, and the best so far has resulted from cooperation between two teams. The challenge has probably saturated, as algorithms cannot progress beyond limits set by ambiguities inherent in 2D scoring and the size of the test dataset. Retrospective evaluation of the challenge scoring system reveals that it was not sufficiently robust to variations in the widths of neurite borders. We propose a solution to this problem, which should be useful for a future 3D segmentation challenge.