Programming Framework Research Articles

Beyond The Basics: A Detailed Survey of Advanced Python Applications and Innovations

Abstract: Python is the general purpose, high-level, scriptable, interpreted, object oriented and easy to learn language was developed by Guido van Rossum. Python is a popular programming language because of its simplicity, ease of use, open-source licensing, and accessibility. It provides various libraries and frameworks for learning and real world programming. Python’s versatility and active community make it an ideal language for Machine Learning, Data Science, Artificial Intelligence, Networking, Game Development, Web Development and various other domains. In this paper, we will provide an introduction to the main Python programming software tools used for Web development, Data science, Machine learning techniques, Educational Development, etc. In this paper will first introduce Python as a language, and give introduction about Web Development, Data science, Machine learning, Educational Development & Financial Analysis and then describe packages that are popular in that sector

Neural differentiable modeling with diffusion-based super-resolution for two-dimensional spatiotemporal turbulence

Simulating spatiotemporal turbulence with high fidelity remains a cornerstone challenge in computational fluid dynamics (CFD) due to its intricate multiscale nature and prohibitive computational demands. Traditional approaches typically employ closure models, which attempt to represent small-scale features in an unresolved manner. However, these methods often sacrifice accuracy and lose high-frequency/wavenumber information, especially in scenarios involving complex flow physics. In this paper, we introduce an innovative neural differentiable modeling framework designed to enhance the predictability and efficiency of spatiotemporal turbulence simulations. Our approach features differentiable hybrid modeling techniques that seamlessly integrate deep neural networks with numerical PDE solvers within a differentiable programming framework, synergizing deep learning with physics-based CFD modeling. Specifically, a hybrid differentiable neural solver is constructed on a coarser grid to capture large-scale turbulent phenomena, followed by the application of a Bayesian conditional diffusion model that generates small-scale turbulence conditioned on large-scale flow predictions. Two innovative hybrid architecture designs are studied, and their performance is evaluated through comparative analysis against conventional large eddy simulation techniques with physics-based subgrid-scale closures and purely data-driven neural solvers. The findings underscore the potential of the neural differentiable modeling framework to significantly enhance the accuracy and computational efficiency of turbulence simulations. This study not only demonstrates the efficacy of merging deep learning with physics-based numerical solvers but also sets a new precedent for advanced CFD modeling techniques, highlighting the transformative impact of differentiable programming in scientific computing.

The SINFONIA project repository for AI-based algorithms and health data

The SINFONIA project’s main objective is to develop novel methodologies and tools that will provide a comprehensive risk appraisal for detrimental effects of radiation exposure on patients, workers, caretakers, and comforters, the public, and the environment during the management of patients suspected or diagnosed with lymphoma, brain tumors, and breast cancers. The project plan defines a series of key objectives to be achieved on the way to the main objective. One of these objectives is to develop and operate a repository to collect, pool, and share data from imaging and non-imaging examinations and radiation therapy sessions, histological results, and demographic information related to individual patients with lymphoma, brain tumors, and breast cancers. This paper presents the final version of that repository, a cloud-based platform for imaging and non-imaging data. It results from the implementation and integration of several software tools and programming frameworks under an evolutive architecture according to the project partners’ needs and the constraints of the General Data Protection Regulation. It provides, among other services, data uploading and downloading, data sharing, file decompression, data searching, DICOM previsualization, and an infrastructure for submitting and running Artificial Intelligence models.

Integrating planetary health education into tertiary curricula: a practical toolbox for implementation

ObjectiveTo present a series of case studies from our respective countries and disciplines on approaches to implementing the Planetary Health Education Framework in university health professional education programs, and to propose a curriculum implementation and evaluation toolbox for educators to facilitate the adoption of similar initiatives in their programs. We emphasize the importance of applying an Indigenous lens to curriculum needs assessment, development, implementation, and evaluation.MethodsCase studies from Australia and United States were collated using a six-stage design-based educational research framework (Focus, Formulation, Contextualization, Definition, Implementation, Evaluation) for teaching planetary health and methods of curriculum evaluation. These components were then mapped to derive the curriculum implementation toolbox reflecting the six-stage design-based educational research framework.ResultsThe case studies demonstrated different approaches to successful integration of the Planetary Health Education Framework in medicine, nursing, public health, and allied health disciplines. This integration often involved Indigenous perspectives on environmental stewardship, holistic health, and community well-being into the curriculum. The case studies also highlighted the importance of community engagement, cultural competency, and interdisciplinary collaboration in curriculum development. Findings from case studies were used to propose a curriculum implementation toolbox to assist educators in adapting and integrating planetary health education into their own programs.DiscussionWhile valuable frameworks for teaching planetary health in health science programs exist, challenges remain in implementing these frameworks in real-world educational environments. The proposed curriculum implementation toolbox offers practical strategies and resources for educators to incorporate these principles into their teaching. Additionally, the case studies reported here contribute to the growing body of literature on planetary health education pertinent to addressing the triple planetary crisis.

Building bridges - Fostering collaborative education in training dental informaticians.

Dental informatics is an emerging discipline. Although the accreditation agency governing dental education programs asserts the importance of informatics as foundational knowledge, no well-defined dental informatics courses currently exist within the standard predoctoral dental curriculum. There is a nationwide lack of dental informatics academic programs. This training gap is due to a lack of qualified dental informaticians to impart knowledge on dental informatics. This paper aims to introduce a novel conceptual framework for an interdisciplinary dental informatics program in preparing students to become dental informaticians. In 2023, we developed a standalone graduate certificate program in dental informatics at Indiana University (IU) School of Dentistry in collaboration with IU Luddy School of Informatics, Computing, and Engineering and IU Fairbanks School of Public Health. Feedback was collected through online surveys to assess course quality from students who took Introduction to Health Information in Dentistry. Feedback was analyzed qualitatively, utilizing a thematic analysis approach. Common responses relevant to dental informatics education were grouped into themes. Five major themes emerged during our analysis of the students' feedback: foundational knowledge and skills; experiential learning: learning by doing; access to resources and working on clinical information systems; health promotion through team-based learning; and retention of knowledge assessment and application. A conceptual framework was formulated through these themes as a guideline for future program improvement. This interdisciplinary educational program framework showed how students and faculty from various disciplines could collaborate, learn from each other, and bring in expertise from different domains. The collaboration happens in clinical, laboratory, and virtual settings to acquire hands on learning through practice and research projects. The developed conceptual framework aligned with the interdisciplinary nature of dental informatics. It can potentially be adopted by other interdisciplinary informatics programs in health and non-health care disciplines.

Подходы в совершенствовании нормативной базы в отношении применения мультифокальных интраокулярных линз при хирургическом лечении катаракты

Ultrasound phacoemulsification with intraocular lens (IOL) implantation is the “gold standard” for cataract treatment. Considering the existing requirements for the quality of vision after surgery, there is an increasing demand from patients for IOL implantation, which provides comfortable vision not only at a long distance, but also at a short one without the use of reading glasses (IOL with multifocal properties). The analysis of the existing regulatory framework regarding the possibility and obligation of using this medical product in the provision of specialized medical care – surgical treatment of cataract within the framework of the state guarantee program shows the possibility of using this consumable material without the obligation of the medical organization to consider the wishes of the patient. The change in the structure of the payment tariff for medical care for patients with cataract in 2023, the reduction in the tariff for providing specialized medical care to patients with uncomplicated forms affected the availability of multifocal IOL for patients without specifying the way to obtain this type of service, which makes it relevant to analyze approaches to improving the regulatory framework regarding the use of multifocal intraocular lenses in cataract surgical treatment. There are unsettled clinical, organizational, and economic issues regarding the use of multifocal intraocular lenses (artificial lenses) in the surgical treatment of cataract. There are various approaches (clinical-organizational, economic, legal, information) to improving the regulatory framework, but the approach of decision makers should be complex based on a comprehensive assessment of the economic, clinical, and technological components. Approaches are only a means to achieve a goal: the development of a multifunctional system of state guarantees in the provision of medical services, rational use of available resources.

The International Conference «Transport Obligations in the context of Technological Development» Dedicated to the Memory of Professor A. G. Kalpin

The paper is a brief overview of the international conference «Transport Obligations in the context of Technological Development» held on June 18, 2024 at Department of Civil Law of Kutafin Moscow State Law University (MSAL) and dedicated to the memory of Professor A.G. Kalpin. More than 30 speakers—representatives of leading Russian universities, business and government authorities—attended the conference. The conference was supported by the Digital Valleys Platform Foundation for the Support and Development of Information Technologies and Digitalization of the Economy, which is the general partner of the Technopravo project implemented within the framework of the Priority-2030 academic equality program. Four out of five Dr. Sci.— experts in transport law — attended the conference. The paper provides an overview of the main speeches and reports of leading Russian lawyers on transport law in the Russian Federation. Following the results of the conference, it was emphasized that many problems of transport law identified by Professor A. G. Kalpin have not yet been solved. This circumstance, as well as the rapid technological development of the Russian Federation, necessitates the continued modernization of domestic legislation in the field of transport law, including the formation of new legal regimes in the transport industry of the Russian Federation.

To Act or Wait: The Impact of Disruption Duration Estimates on Manufacturer’s Response Strategies

In the event of a disruption at a primary supplier, the manufacturer’s sourcing and production operations are inevitably affected, necessitating a response strategy based on the estimated disruption duration. This paper derives the optimal production policy for each response strategy, aiming to minimize total costs over a planning horizon within a dynamic programming framework. We characterize these production policies across various model parameters, particularly focusing on the estimated disruption duration and initial inventory level. Our analysis identifies when the passive acceptance strategy and the backup strategy each hold an advantage, and how the cost benefits of each strategy vary with different model parameters. Additionally, we examine the consequences of overestimating or underestimating the disruption duration, providing insights into how the chosen response strategy and production policy, based on the estimated duration, diverge from the true optimal ones as the actual duration unfolds. We also highlight the cost implications of these discrepancies. Finally, in scenarios where the true duration follows a probabilistic distribution, our numerical experiments demonstrate how strategy selection and the cost of misestimation are influenced by the mean of the true disruption duration and the initial inventory level. These analyses offer decision-makers valuable guidance on when to act or wait in the face of disruptions.

Mechanisms of epigenomic and functional convergence between glucocorticoid- and IL4-driven macrophage programming

Macrophages adopt distinct phenotypes in response to environmental cues, with type-2 cytokine interleukin-4 promoting a tissue-repair homeostatic state (M2IL4). Glucocorticoids (GC), widely used anti-inflammatory therapeutics, reportedly impart a similar phenotype (M2GC), but how such disparate pathways may functionally converge is unknown. We show using integrative functional genomics that M2IL4 and M2GC transcriptomes share a striking overlap mirrored by a shift in chromatin landscape in both common and signal-specific gene subsets. This core homeostatic program is enacted by transcriptional effectors KLF4 and the glucocorticoid receptor, whose genome-wide occupancy and actions are integrated in a stimulus-specific manner by the nuclear receptor cofactor GRIP1. Indeed, many of the M2IL4:M2GC-shared transcriptomic changes were GRIP1-dependent. Consistently, GRIP1 loss attenuated phagocytic activity of both populations in vitro and macrophage tissue-repair properties in the murine colitis model in vivo. These findings provide a mechanistic framework for homeostatic macrophage programming by distinct signals, to better inform anti-inflammatory drug design.

The Experiences and Perceptions of Telehealth in Patients Living With Advanced Chronic Obstructive Pulmonary Disease: A Qualitative Evidence Synthesis.

To systematically identify, appraise and synthesise qualitative research evidence which examined the impact of telehealth on the experiences and perceptions of patients living with advanced chronic obstructive pulmonary disease, to inform the development of patient-centred telehealth. Qualitative evidence synthesis. CINAHL, Cochrane, Embase, PUBMED, MEDLINE, EThOS, Web of Science, PsycINFO, Lenus, DART, RIAN and ProQuest were searched for primary qualitative studies undertaken between 2008 and 2023. A thematic synthesis of studies was undertaken to identify descriptive themes relating to patient views. Methodological quality was assessed using the Critical Appraisal Skills Programme framework, and confidence in review findings was assessed using the GRADE-CERQual approach. Nine studies met the inclusion criteria and were included in the final synthesis. Four analytical themes were generated (1) telehealth as a facilitator of independence, (2) the influence of patient and healthcare provider relationship on successful engagement with telehealth, (3) usability of telehealth to patients living with advanced chronic obstructive pulmonary disease and (4) trusting virtual health services and facilitating confidence in the patient/service user. Five descriptive themes emerged: (i) individualised telehealth chronic obstructive pulmonary disease care (ownership and control), (ii) managing chronic obstructive pulmonary disease exacerbations, (iii) being heard and feeling understood, (iv) telehealth as an education aid and (v) aging and virtual technology. Understanding the experiences of patients with chronic obstructive pulmonary disease and their engagement with telehealth is a necessary determinant of how best to utilise telehealth in this population and may serve to inform policymakers to further develop and implement telehealth into practice. Future research on patients and healthcare professionals' views on telehealth use in the palliative stage of this illness may also be valuable. Findings add value by providing healthcare providers with additional evidence to improve understanding of both telehealth complexity and human experiences and perceptions. It is anticipated that a deeper understanding of chronic obstructive pulmonary disease patients' experiences and perceptions will inform the development of strategies to maximise and enhance the application of patient-centred telehealth within the context of coping and living with a debilitating condition. No patient or public contribution was utilised in this study.

Tourist-recreational impact on the Moscow–St. Petersburg macroregion: a multi-scale assessment using Big Data

The possibilities of using one of the varieties of Big Data – geolocalized photographs – as an objective indicator of the spatial distribution and intensity of tourist and recreational load within the macroregion “From Moscow to St. Petersburg” allocated within the framework of the State Program for Tourism Development are considered. The study uses an original geoinformation model assembled on the basis of freely distributed OpenStreetMap layers and photo points localized in space and time. It allows, on the one hand, to characterize the features of the placement of attractors (natural, cultural) and tourist and recreational infrastructure, on the other – to objectively assess the spatial distribution of the presence of tourists and recreants within the macroregion and describe the specifics of their intra-annual (seasonal) “attraction”. Aggregation of photography points into polygons, taking into account the differentiated clustering distance, made it possible to form areas of seasonal (summer, winter and spring-autumn) stay of tourists, as well as to get an idea of the minimum year-round and maximum episodic areas within the macroregion and individual areas exposed to the potential impact of tourists and recreants. The differences between the minimum and maximum areas of stay of tourists and recreants are proposed to be used to assess the effectiveness of the functioning of the industry in the areas of the macroregion. The obtained spatial areas and patterns of tourists’ presence open up opportunities for an objective assessment of the potential load on natural and cultural heritage sites. The uneven inclusion of both natural and cultural attractors in the sphere of tourism and recreation has been revealed, which leads to a situation where some objects of natural and cultural heritage experience significant industry pressure, while others remain almost or completely unaffected by the presence of tourists and recreants.

The Role of Nutrition in the Nursing Management of Pressure Ulcers in Adult Community Settings: A Systematic Review Protocol.

The aging population drives a growing demand for care, particularly in Europe. It is estimated that approximately 1.5-2 million individuals have a chronic wound. Among these, pressure ulcers (PUs) are one of the most prevalent complications in vulnerable individuals. Malnutrition is a primary risk factor, yet it can be mitigated through proper nutrition and adequate community support. The community nurse plays a crucial role in managing chronic conditions and nutrition through constant and professional monitoring. This article presents a comprehensive systematic review (SR) protocol to examine the role of community nursing of nutritional intervention of frail population with wound care. A SR will be conducted according to international standards and reported following the PRISMA Guidelines for SRs. The search will be conducted in PubMed/Medline, Scopus, Embase, and CINAHL, supplemented by grey literature sources. The methodological quality and risk of bias will be assessed using the Critical Appraisal Skills Programme (CASP) framework. The protocol has been registered in the Open Science Framework (OSF). It is anticipated that the findings of this SR will provide new evidence on the relationships between nutritional nursing interventions and wound care management primarily in the community setting.

Efficient risk-based inspection framework: Balancing safety and budgetary constraints

Efficient equipment maintenance is paramount across various industries to mitigate energy wastage and avert potential disasters such as hazardous emissions, fires, and explosions. Within this context, the adoption of risk-based inspection strategies has emerged as a crucial method for assessing equipment integrity. This study integrates the principles of Risk-Based Inspection (RBI) with a novel two-objective mathematical model, resulting in a comprehensive framework for equipment inspection programs. The primary aim of this framework is to reduce overall risk exposure while optimizing inspection expenditures. Unlike conventional approaches, this methodology eliminates the necessity to define threshold risk levels. By integrating inspection costs into the model, the assessment of Failure Consequences, and thereby, the decision-making process has been streamlined. This innovative algorithm effectively balances the reduction of failure likelihood with the minimization of inspection costs, enhancing decision-making capabilities. Importantly, this approach offers significant protection against energy wastage and the occurrence of leaks through robust risk management strategies. The algorithm employs specialized operators to expedite the discovery of optimal solutions. Empirical validation through a case study conducted at a Petrochemical Plant highlights the practicality and effectiveness of the proposed framework.

Finite-time optimal control for a class of nonlinear systems with performance constraints via critic-only ADP: Theory and experiments

This paper addresses the optimal control problem within the framework of adaptive dynamic programming (ADP) for a class of nonlinear systems subjected to performance constraints. A new finite-time optimal control scheme is developed to stabilize the system by using the critic-only neural network ADP method. Compared with the existing ADP-based optimal control methods with uniformly ultimately bounded stability, the provided control scheme ensures that the controlled system's state and neural network weight estimation error are finite-time stable. It can ensure optimality, prescribed performance, and finite-time stability of the closed-loop control system simultaneously through an integration of ADP, the prescribed performance control technique, and Lyapunov theory. The designed adaptive neural network weight update law can relax the persisting excitation condition. The proposed control scheme is implemented on a robotic experiment platform to achieve trajectory tracking and verify its effectiveness.

Robust day-ahead scheduling of cooperative energy communities considering multiple aggregators

Future cities must play a vital role in reducing energy consumption and decarbonizing the electricity sector, thus evolving from passive structures towards more efficient smart cities. This transition can be facilitated by energy communities. This emerging paradigm consists of collectivizing a set of residential installations equipped with onsite renewable generators and storage assets (i.e., prosumers), which can eventually share resources to pursue collective welfare. This paper focuses on cooperative communities, where prosumers share resources without seeking selfish monetary counterparts. Despite their apparent advantages, energy management and scheduling of energy communities suppose a challenge for conventional tools due to the high level of uncertainty (especially due to intermittent renewable generation and random demand), and privacy concerns among prosumers. This paper addresses these issues. Specifically, a novel management structure based on multiple aggregators is proposed. This paradigm preserves users' confidential features while allowing them to extract the full potential of their assets. To efficiently manage the variety of assets available under uncertainty, an adaptive robust day-ahead scheduling model is developed, which casts as a solvable and portable Mixed Integer Linear Programming framework, which eases its implementation in real-world cases. The new proposal concerns uncertain generation and demand using a polyhedral representation of the uncertainty set. A case study is conducted to validate the developed model, showing promising results. Moreover, different results are obtained and analysed. Finally, it is worth remarking on how the level of robustness impacts the collective bill, incrementing it by 75 % when risk-averse conditions are assumed. In addition, the role of storage assets under pessimistic conditions is remarked, pointing out that these assets rule the scheduling plan of the community instead of renewable generators.

Developing health-saving competence of pre-service teachers in Kazakhstan

This study's significance lies in the need for a perspective teacher who can solve educational objectives to preserve children's and teenagers’ health. In this context, it is crucial to cultivate the health-saving competence of pre-service teachers during the educational process at the university. The study has aimed to develop, implement and experimentally test educational conditions for developing health-saving competence of a pre-service teacher within the framework of the educational program of the pedagogical direction. The participants were 37 university teachers of physical education and 145 students from two universities in Kazakhstan. The proposed approaches and methods represent a process of future teacher training which includes the stages: initial, main and final. Instructional intervention was employed at the final stage: the authors developed and introduced a special course for prospective teachers titled "Development of Schoolchildren's Health and Modern Health-promoting Technologies”. Tests, surveys, and questionnaires have been used during the intervention to test the course efficiency. The majority of respondents (79%) consider it necessary to utilize health-promoting methods and techniques at different stages of the lesson in the process of teaching the discipline. The essential aspect in the study of the elective course was building upon students' existing knowledge in the fields of physical education, pedagogy, psychology, and subject-specific teaching methods, as well as enhancing their health-saving competencies. Keywords: health-saving, competence, physical education, teacher, activity.

Implementation and application of cell-based S-FEM based on the object-oriented programming framework

Implementation and application of cell-based S-FEM based on the object-oriented programming framework

Automatic Refactoring Approach for Asynchronous Mechanisms with CompletableFuture

To address the inherent limitations of Future in asynchronous programming frameworks, JDK 1.8 introduced the CompletableFuture class, which features approximately 50 different methods for composing and executing asynchronous computations and handling exceptions. This paper proposes an automatic refactoring method that integrates multiple static analysis techniques, including visitor pattern analysis, alias analysis, and executor inheritance structure analysis, to conduct precondition checks. Distinct from existing Future refactoring methods, this approach considers custom executor types, thereby extending its applicability. Using this method, the ReFuture automatic refactoring plugin was implemented within the Eclipse JDT framework. The method was evaluated in terms of the number of refactorings, refactoring time, and error introduction, alongside a side-by-side comparison with the existing method. The refactoring outcomes for nine large applications, including ActiveMQ, Hadoop, and Elasticsearch, show that ReFuture successfully refactored 639 out of 813 potential code structures, achieving a refactoring success rate of 64.70% without introducing errors. This tool effectively facilitates the refactoring to CompletableFuture and enhances refactoring efficiency compared to manual methods.

Monitoring of 260 pesticides in extra virgin olive oil and risk assessment for consumers within the framework of the European multiannual control program

The aim of the present research was to develop and validate a robust analytical method for the monitoring of 260 pesticide residues in Extra Virgin Olive Oil (EVOO) expanding the 185 molecules requested by the multiannual control program. The analytical procedure included an ultrasound-assisted liquid-liquid microextraction followed by low-pressure gas chromatography (LP-GC) and ultra-high-performance liquid chromatography (UHPLC), both coupled to triple quadrupole mass spectrometry. Matrix-matched calibration curves showed good linearity with coefficients of determination greater than 0.999. Accuracy values ranged from 65.5 % to 122.3 % and from 61.1 % to 133.3 % for LP-GC and UHPLC, respectively. The recoveries ranged from 14.0 % to 177.9 %.Fifty commercial EVOO, from Italian and EU production, were analyzed to assess pesticide contamination during the 2021–2023 harvesting seasons. The research focused on evaluating consumer risk by assessing both chronic and acute dietary exposure, using the Pesticide Residue Intake Model developed by the EFSA.

Contact-implicit Model Predictive Control: Controlling diverse quadruped motions without pre-planned contact modes or trajectories

This paper presents a contact-implicit model predictive control (MPC) framework for the real-time discovery of multi-contact motions, without predefined contact mode sequences or foothold positions. This approach utilizes the contact-implicit differential dynamic programming (DDP) framework, merging the hard contact model with a linear complementarity constraint. We propose the analytical gradient of the contact impulse based on relaxed complementarity constraints to further the exploration of a variety of contact modes. By leveraging a hard contact model-based simulation and computation of search direction through a smooth gradient, our methodology identifies dynamically feasible state trajectories, control inputs, and contact forces while simultaneously unveiling new contact mode sequences. However, the broadened scope of contact modes does not always ensure real-world applicability. Recognizing this, we implemented differentiable cost terms to guide foot trajectories and make gait patterns. Furthermore, to address the challenge of unstable initial roll-outs in an MPC setting, we employ the multiple shooting variant of DDP. The efficacy of the proposed framework is validated through simulations and real-world demonstrations using a 45 kg HOUND quadruped robot, performing various tasks in simulation and showcasing actual experiments involving a forward trot and a front-leg rearing motion.