Updated Principles Research Articles

The influence of context on the conceptualization, measurement, and application of the concept of quality of life

AbstractThe influence of context on the conceptualization, measurement, and application of the quality of life concept was acknowledged in the principles contained within the original Quality of Life Consensus Document published in 2002 and validated in 2004. Since that time, there has been a substantial increase in our understanding of both the QOL construct and the multidimensional properties of context. The purpose of this article is to report on a multi‐step process conducted in 2019 by a group of international quality of life experts to review, critique, and update where necessary the QOL principles that were originally developed in 2002. Updated principles for conceptualization, measurement, and application are provided. An understanding of the role of context on the QOL concept allows for measurement guidelines to accompany the measurement principles, an understanding of the application conditions associated with a person‐ or family‐centered approach to QOL, and implementing guidelines regarding both the development of QOL‐related policies and practices and their monitoring and evaluation.

Dynamics of Indicators of Mental Performance of Modern Schoolchildren while Doing Homework

Introduction: Being a mandatory component of the educational process, homework remains its least regulated component. At the same time, recent scientific research findings give evidence of study overload and daily routine disruption in schoolchildren due to, inter alia, a significant amount of homework. The purpose of this work is to assess the functional state of the organism of schoolchildren in the process of doing homework for further optimization of this type of educational activity. Materials and methods: The study was based on testing of mental performance of schoolchildren in grades 1–8, which is an integral indicator of the functional state of the body and is crucial for educational activities. The technique of proofreading tests was used to assess the main parameters of mental performance: the number of characters viewed, the number of mistakes made, and their ratio. The tests were conducted before and after the children completed their homework. Results and discussion: A decline in mental performance was observed in the majority of the examined: the number of viewed characters decreased while the number of errors significantly increased after doing homework. First and second-year primary school children made 9.62 errors against 13.07; fifth graders – 3.49 against 7.85 errors (p < 0.001); and eighth graders – 5.86 against 7.39 (p < 0.05). A significant proportion of schoolchildren (28.6 to 72.7 %) had adverse shifts in mental performance characteristic of severe fatigue. The results show accumulated fatigue by the start of independent work with already deteriorated performance related to previous intensive studies at school; after insufficient rest against the background of a decline in physiological functions of the body, which is consistent with previous findings. Conclusion: It is essential to optimize organization of homework based on updated principles of mental health given its current features.

Quantized iterative learning control for impulsive differential inclusion systems with data dropouts

This paper studies the quantized iterative learning control with encoding–decoding mechanism of a class of impulsive differential inclusion systems with random data dropouts. First, the set-valued mappings in the differential inclusion systems are transformed into single-valued mappings by using the Steiner-type selector. Then, a learning algorithm based on the intermittent update principle is designed to address the data asynchronism problem caused by two-sided data dropouts. If the data are successfully transmitted at the actuator and measurement sides, then the control input is effectively updated. Furthermore, a suitable scaling sequence is introduced to ensure the system output to achieve zero-error tracking performance for a desired trajectory. An upper bound of the quantization level is determined such that the quantization error is always bounded. The results show that the quantization method reduces the burden of network communication at the cost of increasing the amount of computation, and the learning algorithm does not require the data dropouts to satisfy a certain probability distribution. Finally, the effectiveness of the learning algorithm is verified by numerical simulations of the switched reluctance motor system.

Anti-sine-cosine atom search optimization (ASCASO): a novel approach for parameter estimation of PV models.

Nowadays, solar power generation has gradually become a part of electric energy sharing. How to effectively enhance the energy conversion efficiency of solar cells and components has gradually emerged as a focal point of research. This paper presents a boosted atomic search optimization (ASO) with a new anti-sine-cosine mechanism (ASCASO) to realize the parameter estimation of photovoltaic (PV) models. The anti-sine-cosine mechanism is inspired by the update principle of sine cosine algorithm (SCA) and the mutation strategy of linear population size reduction adaptive differential evolution (LSHADE). The working principle of anti-sine-cosine mechanism is to utilize two mutation formulas containing arcsine and arccosine functions to further update the position of atoms. The introduction of anti-sine-cosine mechanism achieves the populations' random handover and promotes the neighbors' information communication. For better evaluation, the proposed ASCASO is devoted to estimate parameters of three PV models of R.T.C France, one Photowat-PWP201 PV module model, and two commercial polycrystalline PV panels including STM6-40/36 and STM6-120/36 with monocrystalline cells. The proposed ASCASO is compared with nine reported comparative algorithms to assess the performance. The results of parameter estimation for different PV models of various methods demonstrate that ASCASO performs more accurately and reliably than other reported comparative methods. Thus, ASCASO can be considered a highly effective approach for accurately estimating the parameters of PV models.

Incremental reduction methods based on granular ball neighborhood rough sets and attribute grouping

In the framework of rough sets, incremental algorithms can effectively reduce repetitive computations for dynamic datasets by discovering the update principles of relevant knowledge. Considering the variations in attribute sets, incremental methods based on neighborhood granulation provide fast updates to attribute reduction in continuous-valued information systems. However, most of these methods assume that the sample distribution and neighborhood radius remain fixed with changes in the attribute set, which may mislead the granulation process and affect the model's classification ability. In this paper, a new incremental reduction method based on granular balls and attribute grouping is proposed for dynamic information systems with multiple attribute additions. Different neighborhood radii are adaptively determined when the attribute set changes, and the number of neighborhood granules can also be effectively reduced. Furthermore, the attributes are grouped based on the k-means algorithm, and only attributes from different groups or with small relevance to those in the current reduction set are considered to be incorporated as a reduction attribute, thus reducing the computation time and simultaneously preserving informative attributes. Linear and nonlinear correlation coefficients are used to measure attribute relevance based on which three corresponding incremental reduction algorithms are developed. Finally, extensive experimental results on 12 benchmark datasets are shown to compare the proposed method with non-incremental and typical incremental methods in terms of time cost, classification accuracy, the size of attribute reduction, and coverage of the reduction.

Topology Optimization of Continuum Structures Based on Binary Hunter-Prey Optimization Algorithm

According to BESO’s principle of binarizing continuous design variables and the excellent performance of the standard HPO algorithm in terms of solving continuous optimization problems, a discrete binary Hunter-prey optimization algorithm is introduced to construct an efficient topology optimization model. It was used to solve the problems that the BESO method of topology optimization has, such as easily falling into the local optimal value and being unable to obtain the optimal topology configuration; the metaheuristic algorithm was able to solve the topology optimization model’s low computational efficiency and could easily produce intermediate elements and unclear boundaries. Firstly, the BHPO algorithm was constructed by discrete binary processing using the s-shape transformation function. Secondly, BHPO-BESO topology optimization theory was established by combining the BHPO algorithm with BESO topology optimization. Using the sensitivity information of the objective function and the updated principle of the meta-heuristic of the BHPO algorithm, a semi-random search for the optimal topology configuration was carried out. Finally, numerical simulation experiments were conducted by using the three typical examples of the cantilever beam, simply supported beam, and clamping beam as optimization objects and the results were compared with the solution results of BESO topology optimization. The experimental results showed that compared with BESO, BHPO-BESO could find the optimal topology configuration with lower compliance and maximum stiffness, and it has higher computational efficiency, which can solve the above problems.

Dimension-wise Sequential Update for Learning a Multidimensional Environment in Humans.

When confronted with multidimensional environment problems, humans may need to jointly update multiple state-action-outcome associations across various dimensions. Computational modeling of human behavior and neural activities suggests that such updates are implemented based upon Bayesian update principle. However, it is unclear whether humans perform these updates individually or sequentially. If the update occurs sequentially, the order in which the associations are updated matters and can influence the updated results. To address this question, we tested a few computational models with different update orders using both human behavior and EEG data. Our results indicated that a model undertaking dimension-wise sequential updates was the best fit to human behavior. In this model, ordering the dimensions was decided using entropy, which indexed the uncertainty of associations. Simultaneously collected EEG data revealed evoked potentials that were correlated to the proposed timing of this model. These findings provide new insights into the temporal processes underlying Bayesian update in multidimensional environments.

Consensus for Flow Cytometry Clinical Report on Multiple Myeloma: A Multicenter Harmonization Process Merging Laboratory Experience and Clinical Needs

Flow cytometry is a highly sensitive and specific approach for discriminating between normal and clonal plasma cells in multiple myeloma. Uniform response criteria after treatment have been established by the International Myeloma Working Group and the EuroFlow Group; however, the way in which flow cytometry data are reported has suffered from no collaborative or multicentre efforts. This study, involving 8 expert laboratories and 12 clinical hematology units of the Lazio region in Italy, aims to produce a uniform and shared report among the various Centres. From the pre-analytical phase to sample processing, data acquisition, analysis, and evaluation of the potential limitations and pitfalls of the entire process, the study reaches a final conclusion shared by laboratories and clinicians according to the most updated principles and recommendations. The aim was to identify the necessary data to be included in the clinical report by using multiple-choice questionnaires at every single stage of the process. An agreement of more than 75% of the laboratories was considered mandatory for the data to be included in the report. By ensuring the operational autonomy of each laboratory, this study provides a clear report that limits subjective interpretations and highlights possible bias in the process, better supporting clinical decision-making.

Emerging robust and data‐driven control methods for uncertain learning systems

Emerging robust and data‐driven control methods for uncertain learning systems

A common scenario database for Automated Vehicles validation and certification

Scenarios are extensively used throughout the safety validation and verification of automated vehicles, therefore creating a list of scenarios as a common reference for the manufacturers and Type Approval Authorities is needed to ensure an even-handed type approval process. The present paper offers solutions for this need, addressing issues related to the establishment, population and update principles of a common scenario database. It describes the positioning of this database in the verification framework of automated vehicles and presents the different scenario types implied. Going deeper in the details, the possible layers needed for the definition of a scenario are also presented. Finally, the paper introduces the first steps made on the definition of a scenarios catalogue for the validation of L3 highway applications, established at UNECE level, and for L4 applications, established at EU level.

Реставрация матрицы традиционного сознания в России: возможности и перспективы

The article deals with the topical socio-philosophical and socio-anthropological problem of restoration of the matrix of traditional consciousness in modern Russian society. With the help of structural and functional analysis of Russian traditional consciousness and socio-anthropological model of 10 degrees of freedom as autonomy the system of basic practical principles is presented. These principles are actualized precisely in emergency situations and contribute to the reduction of the degree of freedom of the whole society. Restoration of the matrix of traditional consciousness becomes a complicated, dialectical problem for the Russian power (“paternal”) vertical, since it requires a significant restriction of opportunities for free self-realization of most citizens and even comes into conflict with the basic values of the “mother vertical” - preservation and continuation of the race. The long-term presence of society in such forced tension can cause social upheaval, while the short-term experience of an emergency situation suggests the development of ways of ideological adaptation in the form of such practical attitudes as “moderate fatalism,” “personal non-resistance to evil,” “harmony with nature” and “I can be useful to others. These attitudes allow us to build our own variable model of adaptation to the sharp decrease in the degree of personal and social freedom and to preserve the inner potential for a further return to a full creative life. The article also considers the possible prospects of the modern implementation of the updated principles of the matrix of traditional consciousness, and identifies the most problematic and dangerous trends.

Finite‐level uniformly quantized learning control with random data dropouts

AbstractIn this study, a quantized iterative learning control method with an encoding–decoding mechanism is investigated for networked control systems with constrained transmission bandwidths and random data dropouts at both the measurement and actuator sides. The intermittent update principle is used to address the problem of data asynchronism caused by two‐sided data dropouts. Then, a new “process” concept is introduced for the convergence analysis. The input sequence is guaranteed to achieve asymptotic zero‐error convergence to the unknown desired input for the given reference through an appropriate selection of scaling sequences. Furthermore, the quantization errors are shown bounded, where the upper bounds of the quantization level are precisely determined for selecting a finite‐level uniform quantizer. To verify the proposed scheme, an example of a permanent magnet linear motor is simulated.

Forensic support of the prosecutor’s activities in criminal proceedings: Concept, content, tasks

Increasing the effectiveness of the prosecutor’s activity in criminal proceedings is an extremely urgent task, taking into account the changes taking place in the legal life of the state, the development of scientific and technical progress, and the processes of reforming law enforcement agencies. There are also negative circumstances that today require rethinking and adapting the activities of the prosecutor’s office to new, extreme conditions, namely the need to counter the armed aggression of the Russian Federation. These and other circumstances determine the formation of updated principles of the prosecutor’s activity. Purpose of the article is to highlight the theoretical foundations and form practical recommendations regarding the forensic support of the prosecutor’s activities in criminal proceedings. By using the method of dialectics, special legal methods, and processing the source base, it was established that the goal of forensic support of the prosecutor’s activities is to achieve the tasks defined in Art. 2 of the Criminal Procedure Code of Ukraine. The realization of this goal depends on the solution of specific tasks, which consist in the development of new and improvement of existing technical means, methods and techniques for working with forensically significant information; building systems of tactical techniques; the formation of organizational foundations and the development of methodological recommendations for the implementation of criminal proceedings regarding various types of criminal offenses. Forensic support of the prosecutor’s activities is implemented in accordance with the technical, tactical, and methodical forensic direction, techniques, means, and methods developed by forensics are used

A Method for Autonomous Multi-Motion Modes Recognition and Navigation Optimization for Indoor Pedestrian.

The indoor navigation method shows great application prospects that is based on a wearable foot-mounted inertial measurement unit and a zero-velocity update principle. Traditional navigation methods mainly support two-dimensional stable motion modes such as walking; special tasks such as rescue and disaster relief, medical search and rescue, in addition to normal walking, are usually accompanied by running, going upstairs, going downstairs and other motion modes, which will greatly affect the dynamic performance of the traditional zero-velocity update algorithm. Based on a wearable multi-node inertial sensor network, this paper presents a method of multi-motion modes recognition for indoor pedestrians based on gait segmentation and a long short-term memory artificial neural network, which improves the accuracy of multi-motion modes recognition. In view of the short effective interval of zero-velocity updates in motion modes with fast speeds such as running, different zero-velocity update detection algorithms and integrated navigation methods based on change of waist/foot headings are designed. The experimental results show that the overall recognition rate of the proposed method is 96.77%, and the navigation error is 1.26% of the total distance of the proposed method, which has good application prospects.

Gastroduodenal neuroendocrine neoplasms including gastrinoma - update of the diagnostic and therapeutic guidelines (recommended by the Polish Network of Neuroendocrine Tumours) [Nowotwory neuroendokrynne żołądka i dwunastnicy z uwzględnieniem gastrinoma - uaktualnione zasady postępowania (rekomendowane przez Polską Sieć Guzów Neuroendokrynnych)

After another meeting of experts of the Polish Network of Neuroendocrine Tumours, updated recommendations for the management of patients with gastric and duodenal neuroendocrine neoplasms, including gastrinoma, have been issued. As before, the epidemiology, pathogenesis and clinical symptoms of these neoplasms have been discussed, as well as the principles of diagnostic procedures, including biochemical and histopathological diagnostics and tumour localisation, highlighting the changes introduced in the recommendations. Updated principles of therapeutic management have also been presented, including endoscopic and surgical treatment, and the options of pharmacological and radioisotope treatment. The importance of monitoring patients with gastric and duodenal NENs, including gastrinoma, has also been emphasised.

Updated Principles of Sustainable Engineering

A change in human development patterns is needed, including mankind’s environmental, economic, and social behavior. Engineering methods and practices have a substantial impact on the way to sustainable development. An overview of the guiding principles of sustainability, sustainable design, green engineering, and sustainable engineering is presented first. Sustainable engineering principles need to be updated to include the present state of the art in human knowledge. Therefore, the updated principles of sustainable development are presented, including traditional and more recent items: a holistic approach, sustainability hierarchies, sustainable consumption, resource scarcity, equalities within and between generations, all stakeholders’ engagement, and internalizing externalities. Environmental, social, and economic impacts that respect humans’ true needs and well-being are of importance to the future. The updated 12 principles include the tridimensional system’s approach, precautionary and preventive approaches, and corporate reporting liability. The environmental principles comprise a circular economy with waste minimization, efficient use of resources, increased share of renewables, and sustainable production. The social pillar includes different views of equality, the engagement of stakeholders, social responsibilities, and decent work. Economic principles embrace human capital, creativity, and innovation in the development of products, processes and services, cost-benefit analysis using the Life Cycle Assessment, and the polluters must pay principle. The principles will require further development by engaging individual engineers, educators, and their associations.

Inflammatory Bowel Disease: Clinical Diagnosis and Surgical Treatment-Overview.

This article is an overview of guidelines for the clinical diagnosis and surgical treatment of predominantly colonic inflammatory bowel diseases (IBD). This overview describes the systematically and comprehensively multidisciplinary recommendations based on the updated principles of evidence-based literature to promote the adoption of best surgical practices and research as well as patient and specialized healthcare provider education. Colonic IBD represents idiopathic, chronic, inflammatory disorders encompassing Crohn’s colitis (CC) and ulcerative colitis (UC), the two unsolved medical subtypes of this condition, which present similarity in their clinical and histopathological characteristics. The standard state-of-the-art classification diagnostic steps are disease evaluation and assessment according to the Montreal classification to enable explicit communication with professionals. The signs and symptoms on first presentation are mainly connected with the anatomical localization and severity of the disease and less with the resulting diagnosis “CC” or “UC”. This can clinically and histologically be non-definitive to interpret to establish criteria and is classified as indeterminate colitis (IC). Conservative surgical intervention varies depending on the disease phenotype and accessible avenues. The World Gastroenterology Organizations has, for this reason, recommended guidelines for clinical diagnosis and management. Surgical intervention is indicated when conservative treatment is ineffective (refractory), during intractable gastrointestinal hemorrhage, in obstructive gastrointestinal luminal stenosis (due to fibrotic scar tissue), or in the case of abscesses, peritonitis, or complicated fistula formation. The risk of colitis-associated colorectal cancer is realizable in IBD patients before and after restorative proctocolectomy with ileal pouch-anal anastomosis. Therefore, endoscopic surveillance strategies, aimed at the early detection of dysplasia, are recommended. During the COVID-19 pandemic, IBD patients continued to be admitted for IBD-related surgical interventions. Virtual and phone call follow-ups reinforcing the continuity of care are recommended. There is a need for special guidelines that explore solutions to the groundwork gap in terms of access limitations to IBD care in developing countries, and the irregular representation of socioeconomic stratification needs a strategic plan for how to address this serious emerging challenge in the global pandemic.

Updated principles of prevention, diagnosis and treatment of COVID-19 in children in Poland – recommendations for paediatricians and family medicine doctors

Updated principles of prevention, diagnosis and treatment of COVID-19 in children in Poland – recommendations for paediatricians and family medicine doctors

Updated Principles of Surgical Management of Pancreatic Neuroendocrine Tumours (pNETs): What Every Surgeon Needs to Know.

Simple SummaryIn this narrative review, we update the surgical management of pancreatic neuroendocrine tumours (pNETs) and highlight key elements in view of the recent literature. These tumours are rare and suffer from a lack of data and randomized controlled trials. The pNETs management is difficult due to their heterogeneity and the risks associated with pancreatic surgery. Innovative managements such as “watch and wait” strategies, parenchymal sparing surgery and minimally invasive approach are emerging. The correct use of all these therapeutic options requires a good selection of patients but also a constant update of knowledge.Pancreatic neuroendocrine tumours (pNETs) represent 1 to 2% of all pancreatic neoplasm with an increasing incidence. They have a varied clinical, biological and radiological presentation, depending on whether they are sporadic or genetic in origin, whether they are functional or non-functional, and whether there is a single or multiple lesions. These pNETs are often diagnosed at an advanced stage with locoregional lymph nodes invasion or distant metastases. In most cases, the gold standard curative treatment is surgical resection of the pancreatic tumour, but the postoperative complications and functional consequences are not negligible. Thus, these patients should be managed in specialised high-volume centres with multidisciplinary discussion involving surgeons, oncologists, radiologists and pathologists. Innovative managements such as “watch and wait” strategies, parenchymal sparing surgery and minimally invasive approach are emerging. The correct use of all these therapeutic options requires a good selection of patients but also a constant update of knowledge. The aim of this work is to update the surgical management of pNETs and to highlight key elements in view of the recent literature.

Обновленные принципы обучения врачей-интернов разных специальностей по модулю «Неотложные состояния»

Подготовка врачей-интернов различных специальностей к лицензионному экзамену «Крок-3» является важной проблемой современного последипломного образования. С целью оптимизации этого процесса пересмотрен и обновлен ряд педагогических принципов. Внедрение этих принципов в учебный процесс позволило значительно улучшить результаты лицензионного экзамена.