Planning Tool Research Articles

Strategies for Oxygen Ecosystems in Middle-Income Countries: A Review and Case Study from Lebanon.

The COVID-19 pandemic led to a surge of critically ill patients and a sudden increase in the need for oxygen treatment worldwide. Pre-existing gaps in oxygen systems became apparent, and governments, multilateral agencies, and other partners scrambled to increase the production, supply, and use of oxygen to meet this need. The importance of an oxygen ecosystem that is appropriate for the local context became clear. This review describes strategies for oxygen ecosystems in middle-income countries, with specific experiences from Lebanon, following the authors' extensive assessment of the country's oxygen ecosystem, on behalf of the government and UNICEF. In the assessment, fifteen governmental hospitals were visited and evaluated using the UNICEF Oxygen System Planning Tool, discussions were held with key stakeholders, and documents were reviewed. An optimal oxygen ecosystem needs to take into consideration the production of oxygen and delivery to facilities, the maintenance system within facilities, and the clinical use of oxygen. Lebanon, a lower-middle income country in the Middle East, is contending with an extensive economic crisis affecting the health system. Eighteen recommendations for strengthening the oxygen ecosystem in Lebanon that are relevant for other middle-income countries include the establishment of a National Oxygen Committee, installation of additional oxygen plants, strengthened systems for maintenance and electricity supply, increased production, procurement and supply chain resilience, improved training and human resources, the use of data collection and regular information to guide the ecosystem, and integration of oxygen into the rest of the health system.

Правовой инструментарий стратегического планирования в сфере защиты традиционных российских духовно-нравственных ценностей

The article presents the author’s idea of the establishment of the main legal tools of strategic planning of the state policy of the Russian Federation in the sphere of traditional spiritual and moral values, culture and historical memory.

A Scientometric Examination on Performance-Driven Optimization in Urban Block Design Research: State of the Art and Future Perspectives

The study of performance-driven optimization (PDO) in urban block design is essential in the context of architectural form and urban sustainability. PDO focuses on the integrated and comprehensive optimization of various quantifiable performances of buildings, such as solar energy usage, thermal comfort, and energy efficiency. This method aligns urban spaces with sustainable development principles, ensuring they are not only aesthetically pleasing but also functionally efficient. This study explores the existing deficiency in the literature by conducting an in-depth scientometric analysis of PDO in urban block design. Employing science mapping coupled with bibliometric analysis using Python, this study meticulously analyzes the prevailing literature to map out the current intellectual landscape, understand trends, and identify key themes within this domain. This review identifies the key trends, methodologies, and influential works shaping the dynamic field of PDO. It emphasizes the critical roles of computational simulation, artificial intelligence integration, and big data analytics in refining urban block design strategies. This study highlights the growing importance of energy efficiency, environmental sustainability, and human-centric design elements. This review points to an increasing trend towards using sophisticated modeling techniques and data-driven analysis as essential tools in urban planning, crucial for developing sustainable, resilient, and adaptable urban spaces.

Liberating Structures in Strategic Planning: Methods to Foster Engagement

This paper describe the innovative approach of using liberating structures to the development of the AUR 2023 strategic plan, and lessons learned in their application. The 2023 strategic plan built on the results and approach of the prior 2015 plan. Similar to the 2015 strategic plan, traditional tools such as a SWOT analysis and strategic retreat were used. In addition, the 2023 process included tools called liberating structures and was iteratively co-produced through a series of virtual meetings over 18 months. Advantages of liberating structures included increased creativity and speed in moving through meeting tasks, increased number of meaningful contributions from AUR members and increased engagement from participants during discussions and meetings. The 2023 AUR strategic plan is provided along with examples of completed goals and those under early implementation. Lessons learned from using these tools for strategic planning can be applied to other society and group meetings. Moving forward, the 2023 strategic plan will be a living document, which will be reviewed at each Board of Directors meeting and periodically adapted.

A hybrid foresight study of the environmental reference laboratory system in Finland: a foresight study for the Government of Finland

This article presents a hybrid foresight study using the Delphi methodology. The study is part of a strategic research project of the Finnish state named “Foresight in Environmental Reference Laboratory Operations.” The main starting point for this study was the Policy Delphi method, which was supplemented with other Delphi variants and decision support methods. In this hybrid foresight application, Delphi methodology was combined with decision-making and strategic planning tools, namely (1) SWOT analysis, (2) Boston Consulting Group Matrix, (3) research infrastructure (RI) analysis, (4) platform analysis, and (5) integrative foresight workshop. This article draws strongly on the hybrid foresight methodology perspective of foresight tool orchestration. The authors argue that the Delphi methodology gains reliability and appeal with hybrid methodological orchestration. The function of reference laboratories includes services for the verification and maintenance of the quality and validity of environmental measurements, such as the maintenance of reference measurement equipment, expertise, and training, and the organization of national reference measurements as well as participation in international reference measurements, method development, and standardization. The study shows the importance of environmental reference laboratories addressing the following challenges by 2030: (1) new measurement targets, such as the diffusion of nanomaterials, microplastics, and drugs in both nature and the food chain and the environmental impact of recycled materials and indoor air issues; (2) automation of measurement activities and transition to technologically advanced measurement systems; (3) citizens’ opportunities to participate in the production of information about their environment through new technologies; (4) preparing for the incorporation and internationalization of laboratory operations; and (5) the concentration of measurement service business.

Fibre orientation atlas guided rapid segmentation of white matter tracts.

Fibre tract delineation from diffusion magnetic resonance imaging (MRI) is a valuable clinical tool for neurosurgical planning and navigation, as well as in research neuroimaging pipelines. Several popular methods are used for this task, each with different strengths and weaknesses making them more or less suited to different contexts. For neurosurgical imaging, priorities include ease of use, computational efficiency, robustness to pathology and ability to generalise to new tracts of interest. Many existing methods use streamline tractography, which may require expert neuroimaging operators for setting parameters and delineating anatomical regions of interest, or suffer from as a lack of generalisability to clinical scans involving deforming tumours and other pathologies. More recently, data-driven approaches including deep-learning segmentation models and streamline clustering methods have improved reproducibility and automation, although they can require large amounts of training data and/or computationally intensive image processing at the point of application. We describe an atlas-based direct tract mapping technique called 'tractfinder', utilising tract-specific location and orientation priors. Our aim was to develop a clinically practical method avoiding streamline tractography at the point of application while utilising prior anatomical knowledge derived from only 10-20 training samples. Requiring few training samples allows emphasis to be placed on producing high quality, neuro-anatomically accurate training data, and enables rapid adaptation to new tracts of interest. Avoiding streamline tractography at the point of application reduces computational time, false positives and vulnerabilities to pathology such as tumour deformations or oedema. Carefully filtered training streamlines and track orientation distribution mapping are used to construct tract specific orientation and spatial probability atlases in standard space. Atlases are then transformed to target subject space using affine registration and compared with the subject's voxel-wise fibre orientation distribution data using a mathematical measure of distribution overlap, resulting in a map of the tract's likely spatial distribution. This work includes extensive performance evaluation and comparison with benchmark techniques, including streamline tractography and the deep-learning method TractSeg, in two publicly available healthy diffusion MRI datasets (from TractoInferno and the Human Connectome Project) in addition to a clinical dataset comprising paediatric and adult brain tumour scans. Tract segmentation results display high agreement with established techniques while requiring less than 3 min on average when applied to a new subject. Results also display higher robustness than compared methods when faced with clinical scans featuring brain tumours and resections. As well as describing and evaluating a novel proposed tract delineation technique, this work continues the discussion on the challenges surrounding the white matter segmentation task, including issues of anatomical definitions and the use of quantitative segmentation comparison metrics.

PROCEDURAL ASPECTS OF GENERATION AND IMPLEMENTATION OF STRATEGIES FOR MANAGING SALES ACTIVITIES OF PROCESSING ENTERPRISES

The article is devoted to developing conceptual foundations and procedures for generating and implementing strategies for managing the sales activities of processing enterprises. The study substantiates a model for the formation of the strategy of a processing enterprise, covering the key stages of strategic planning. It is recommended that the strategic marketing planning process be reviewed to ensure efficiency in the sales activities of processing enterprises. A strategic set of processing enterprises has been defined and characterized, which is a system of strategies of various types that are developed by an enterprise for a certain period, which reflects the specifics of the functioning and development of the enterprise, as well as the level of its claim to a place and role in the external environment. In order to introduce the most effective tools of strategic planning in the sales activities of a processing enterprise, a revision of the strategic marketing planning process is proposed. The main stages of marketing strategic planning of processing enterprises are the formation of the mission, the transformation of the mission into goals, the analysis of the external and internal environment, the conduct of SWOT analysis, the definition of marketing goals, the formation of marketing strategies, the development of a marketing program, the organization and implementation of marketing, as well as marketing control. Thanks to these milestones, the company can formulate its mission and goals and develop effective strategies and programs to achieve these goals. The basic principles of forming a strategic set are emphasized, considering the orientation towards the ultimate goals, the balance of strategies, and clarity in understanding the need for their application. Strategic priorities for increasing the competitiveness of processing enterprises have been identified, such as increasing the concentration of capital, investment attractiveness, reinvestment of profits, increasing the size of enterprises, and introducing innovations. Implementing these strategies should contribute to increasing economic efficiency and adapting to the challenges of sales markets.

Land Management Drifted: Land Use Scenario Modeling of Trancura River Basin, Araucanía, Chile

Modeling land use scenarios is critical to understand the socio-environmental impacts of current decisions and to explore future configurations for management. The management of regulations and permits by central and local governments plays an important role in shaping land use, with different complexities arising from site-specific socioeconomic dynamics. In Chile, the complexity is even more evident due to insufficient binding land regulations, fragmented government procedures, and the primacy of cities over rural areas. Yet land use must be managed to support sustainable development. This research integrates several state management dynamics into scenario modeling to support decision making at the basin scale through 2050. We employed a mixed qualitative-quantitative approach using interviews with state officials and local stakeholders as the basis for the Conversion of Land Use and its Effects (CLUE) model, which resulted in three scenarios with spatially explicit maps. Key findings indicate that opportunities for developing normative planning tools are limited, leaving state management without clear direction. However, current management practices can address problematic activities such as second-home projects and industrial monocultures while promoting small-scale agriculture. Scenario modeling is useful for understanding how the specifics that arise from the scalar dynamics of state management affect land use change and how existing management resources can be leveraged to achieve positive outcomes for both the ecosystem and society.

Career Counselling Chatbot on Facebook Messenger using AI

Work instructions have always been necessary, but in recent times they have only gained the respect they deserve and now that they are in high demand and available worldwide, it is important to have a simple understanding of the various tasks that need to be done. Career counsellors are responsible for providing high school students with the experience and skills they need to make informed career decisions, education, and long-term goals. Music; It is a social event that unites people regardless of market, age, history, language, interests, political affiliation and income. Music and streaming apps are in demand because they are versatile and compatible with daily life, travel, sports and other activities. The rise of mobile phones and digital multimedia technology has made digital music a consumer favourite for many young people. Although career orientation has always been important, it has recently become widely recognized as a key element in today's career change research. High school students, in particular, need early and sustained exposure to many popular careers around the world. This information allows them to make decisions that patiently pursue their educational preferences. Music is a unifying force that transcends borders and barriers and plays a special role in this field. Music and streaming services are integrated into daily life, travel and entertainment, resulting in a universal love of music. The growth of mobile phones and digital technology has brought digital music even more to the forefront of youth content. However, many students do not have enough guidance to bridge the gap between their education, passions, and future career goals. This often leads to frustration and inability to take action. To meet this need, our web career counselling program, based on the ASP.NET Framework, provides students with career planning tools, skills development and opportunity guidance through a Google Dialog flow-powered counselling chatbot. By exploring music as a potential career path and leveraging its global appeal, we aim to inspire and guide students into a successful and rewarding career.

Interpretable machine learning model for prediction of overall survival in laryngeal cancer

Background: The mortality rates of laryngeal squamous cell carcinoma cancer (LSCC) have not significantly decreased in the last decades. Objectives: We primarily aimed to compare the predictive performance of DeepTables with the state-of-the-art machine learning (ML) algorithms (Voting ensemble, Stack ensemble, and XGBoost) to stratify patients with LSCC into chance of overall survival (OS). In addition, we complemented the developed model by providing interpretability using both global and local model-agnostic techniques. Methods: A total of 2792 patients in the Surveillance, Epidemiology, and End Results (SEER) database diagnosed with LSCC were reviewed. The global model-agnostic interpretability was examined using SHapley Additive exPlanations (SHAP) technique. Likewise, individual interpretation of the prediction was made using Local Interpretable Model Agnostic Explanations (LIME). Results: The state-of-the-art ML ensemble algorithms outperformed DeepTables. Specifically, the examined ensemble algorithms showed comparable weighted area under receiving curve of 76.9, 76.8, and 76.1 with an accuracy of 71.2%, 70.2%, and 71.8%, respectively. The global methods of interpretability (SHAP) demonstrated that the age of the patient at diagnosis, N-stage, T-stage, tumor grade, and marital status are among the prominent parameters. Conclusions: A ML model for OS prediction may serve as an ancillary tool for treatment planning of LSCC patients.

Application of International Classification of Functioning, Vital Disabilities and Health to assess the effectiveness of rehabilitation in a psychiatric hospital

BACKGROUND: The International Classification of Functioning, Disability and Health ICF is an important tool for planning, implementing and evaluating the effectiveness of the rehabilitation process. In addition, the use of the ICF makes it possible to objectify the level of quality of medical care. However, this classification is not quite enough used in practice still, including psychiatric practice, where (due to the specifics of these patients) a certain adaptation is required (in terms of choosing the set of the most informative domains).
 AIM: To evaluate the effectiveness of the rehabilitation of patients with mental disorders based on the use of the ICF.
 MATERIALS AND METHODS: Using data from case histories and special questionnaires, 500 patients of the psychiatric hospital were studied — a number of domains included in the ICF were identified and analyzed (domains characterizing “body functions”, “activity and participation”, “environmental factors”): upon admission, on 10th day of treatment, upon discharge. The study was conducted for 6 months by an all-over method. The exclusion criteria were: age under 18 and over 80; the presence of acute psychotic symptoms at the time of examination; the presence of severe cognitive dysfunctions that prevent the assessment of functional limitations, vital activity and health; duration of hospitalization less than 10 days. Statistical analysis of the collected material was carried out using application programs in Microsoft Office Excel.10.
 RESULTS: Among the examined patients, women accounted for 52.6% (263 people). In the age structure, 30.8% (154 people) were patients under 30 years of age; 24.2% (121 people) — 30–39 years old; 13.2% (96 people) — 40–49 years old; 12.8% (64 people) are 50–59 years old and 13.0% (65 people) are 60 years old and older. Average age — 39.5±0.6 years. In the nosological structure, 16.8% (84 people) were patients with organic mental disorders; 12.8% (64 people) — with mental and behavioral disorders associated with the use of psychoactive substances; 19.8% (99 people) — with schizophrenia, schizotypal and delusional disorders; 16.2% (81 people) — with mood disorders; 17.0% (85 people) — with stress-related neurotic disorders and somatoform disorders; 17.4% (87 people) with personality and behavior disorders in adulthood. Upon admission, the following disorders were the most pronounced: mental stability (which occurred in 80.6% of patients — 403 people); regulation of emotions — 390 people (78.0%); control of impulsive impulses — 382 people (76.4%); stability of attention — 388 people (77.6%); switching of attention — 376 people (75.2%); separation of attention — 374 people (74.8%); concentration of attention — 371 people (74.2%); psychomotor control — 354 people (70.8%). During the treatment, the prevalence of all identified disorders significantly decreased (differences in the proportion of patients with various disorders upon admission — on 10th day of treatment — upon discharge are statistically significant with a reliability of more than 95.5%).
 CONCLUSION: This dynamic proves the effectiveness of rehabilitation in general and the importance of nursing intervention in particular.

Plastics in the oceans: an analysis via the Bootstrap method

Plastics have been an important contaminant of the oceans. As a result, several countries have been developing public environmental policies to mitigate the presence of this contaminant in the food chain. Statistical planning must be present in environmental decision-making, being capable of providing robust answers through the analysis of the data obtained. Therefore, choosing an appropriate statistical method contributes significantly to obtaining reliable results. The Bootstrap Method (BM) has been widely used in several environmental studies, constituting an excellent statistical tool for analyzing data with anomalous values. This is very important because, when collecting data from the natural environment, values vary from background to extremely high values. Therefore, and within this context, the objective of the present work was to use the MB in the statistical analysis of data on the global per capita quantity of plastics emitted into the oceans. The data was collected from the free Our World in Data Platform. The results obtained showed that the MB is a very efficient statistical tool in environmental planning, when there is a need to analyze data sets with discrepant values originating from the natural environment.

Optimal Allocation of Water Reservoirs for Sustainable Wildfire Prevention Planning via AHP-TOPSIS and Forest Road Network Analysis

The sustainable management of forest ecosystems is directly linked to the management of forest fires. The increasing occurrence of wildfires has prompted the need for the establishment of infrastructure aimed at addressing them. The placement of anti-fire water reservoirs can address the lack of water intake points. This study introduces a decision support system (DSS) tailored for the optimal allocation of anti-fire water reservoirs in Mediterranean forest ecosystems, ensuring a reliable water supply for firefighting operations. The methodology integrates the analytical hierarchy process (AHP) and the technique of order of preference by similarity to ideal solutions (TOPSIS) methods, facilitating precise location determination through comprehensive criteria analysis. Additionally, the analysis of the forest road network is incorporated to optimize the placement of water reservoirs. In the forest complex of Taxiarchis, Chalkidiki, Greece, 100 potential reservoir sites were identified and prioritized based on factors such as fire risk, proximity to existing water sources, and coverage area using optimal pathways. The study’s findings demonstrate that by establishing 34 water reservoirs, firefighting forces can access a replenishment point within a 5-min travel time. The conclusions underscore the efficacy of this methodology as a valuable decision-making tool for sustainable wildfire prevention planning. This approach contributes to allocating resources judiciously, effectively mitigating the wildfire risk in Mediterranean forest ecosystems, and therefore promoting sustainability.

Covid19Vaxplorer: A free, online, user-friendly COVID-19 vaccine allocation comparison tool.

There are many COVID-19 vaccines currently available, however, Low- and middle-income countries (LMIC) still have large proportions of their populations unvaccinated. Decision-makers must decide how to effectively allocate available vaccines (e.g. boosters or primary series vaccination, which age groups to target) but LMIC often lack the resources to undergo quantitative analyses of vaccine allocation, resulting in ad-hoc policies. We developed Covid19Vaxplorer (https://covid19vaxplorer.fredhutch.org/), a free, user-friendly online tool that simulates region-specific COVID-19 epidemics in conjunction with vaccination with the purpose of providing public health officials worldwide with a tool for vaccine allocation planning and comparison. We developed an age-structured mathematical model of SARS-CoV-2 transmission and COVID-19 vaccination. The model considers vaccination with up to three different vaccine products, primary series and boosters. We simulated partial immunity derived from waning of natural infection and vaccination. The model is embedded in an online tool, Covid19Vaxplorer that was optimized for its ease of use. By prompting users to fill information through several windows to input local parameters (e.g. cumulative and current prevalence), epidemiological parameters (e.g basic reproduction number, current social distancing interventions), vaccine parameters (e.g. vaccine efficacy, duration of immunity) and vaccine allocation (both by age groups and by vaccination status). Covid19Vaxplorer connects the user to the mathematical model and simulates, in real time, region-specific epidemics. The tool then produces key outcomes including expected numbers of deaths, hospitalizations and cases, with the possibility of simulating several scenarios of vaccine allocation at once for a side-by-side comparison. We provide two usage examples of Covid19Vaxplorer for vaccine allocation in Haiti and Afghanistan, which had as of Spring 2023, 2% and 33% of their populations vaccinated, and show that for these particular examples, using available vaccine as primary series vaccinations prevents more deaths than using them as boosters.

Controlling-based organizational and economic mechanism of enterprise activity planning

In this article, the authors prove how introducing a control system for enterprises will, firstly, increase the level of business controllability and reduce the time for making managerial decisions. Secondly, it will help to control the company's assets and manage costs more effectively. Thirdly, it will significantly increase the profitability of joint-stock companies and ensure risk control and risk mitigation to increase the investment attractiveness of the business. Due to the variety of external and internal factors influencing the organization, there cannot be a one-size-fits-all recommendation for establishing a controlling function within a company. Empirical research shows that the most important influencing factors in controlling an organization are the size of the company and the dynamics of changes in the external business environment. In small enterprises, the chief accountant typically performs the controlling function, whose responsibilities include analytical accounting and budgeting. In larger enterprises, specialized departments are created with various tasks related to coordinating management processes and control. The relationship between control functions and environmental dynamics is quite interesting. In companies operating in a stable environment, the controller is seen as a recorder. In a limited variability of the external environment, the controller performs the role of a navigator, providing the company's departments with the most rational planning and control tools. In a turbulent environment, the number of problems that need to be addressed increases significantly. In such a situation, the controller emerges as an innovator who directly participates in problem-solving. In essence, controlling does not necessarily require a separate controller position. Instead, it implies the presence of specific tasks that the company's executives or management can perform. Initially, it is necessary to determine whether the controlling functions can be distributed among existing departments or if creating an independent controlling department is better.

Discovering ME: An innovative planning tool for students with significant disabilities

BACKGROUND: The Individuals with Disabilities Act (IDEA) requires transition plans for students with disabilities to be based on high-quality, age-appropriate transition assessments. However, educators struggle to garner reliable assessment results for students with significant disabilities, because so few assessments are designed or validated for students with these barriers. OBJECTIVE: The purpose of this practice brief is to share details on the process, called Discovering ME, which provides an effective transition assessment and planning tool that is critical to increasing students’ employment outcomes, especially for those who face the most significant barriers to employment. METHODS: Sixty-one students across rural, urban, and suburban school districts participated in Discovering ME. Data were collected across five years, including demographic information and examples of students’ top career cluster areas for future employment. In addition, a statewide survey was conducted with educators participating in Discovering ME on the effectiveness of this early career planning process. RESULTS: The Discovering ME process provides career-related opportunities for students with significant barriers in the home, school, and community in a variety of career clusters based on their expressed interests. Educators report that the focus of this process on students and their interests helped to create positive experiences for them by creating opportunities for success. CONCLUSION: The Discovering ME process provides students with disabilities with authentic, coordinated career awareness and development activities and the building of self-determination, work readiness, and community integration skills.

Short-term power load forecasting based on AC-BiLSTM model

The practice of ultra-short-term power load forecasting serves as a critical strategy for enabling rapid response and real-time dispatch in power systems. By improving the accuracy of load forecasting, both the safety of power systems and the efficiency of electricity usage can be significantly enhanced. Addressing the challenges posed by the non-linear and temporal characteristics of grid load data, this study introduces a novel ultra-short-term power load forecasting model, integrating Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory networks (BiLSTM), and an Attention mechanism, referred to as the AC-BiLSTM model. This innovative approach harnesses the power of CNN and BiLSTM to extract spatio-temporal features of load data, while the Attention mechanism allocates optimal weights to the hidden states of the BiLSTM model, thereby amplifying crucial historical load sequence data and minimizing information loss. The final output of the model is then determined through a fully connected layer. To validate the efficacy of this approach, an empirical study was conducted using real load data from a specific region. The results, obtained from two contrasting experimental scenarios, demonstrate a significant enhancement in forecasting accuracy. This finding underscores the potential of the AC-BiLSTM model as a reliable tool for both strategic planning and maintaining operational stability in power systems.

Hydraulic Modelling for Leakage Reduction in Water Distribution Systems Through Pressure Control

Background Leakage in a water distribution network makes up a significant amount of loss. In certain countries, this loss represents 40% to 50% of the supplied water, whereas the global average for most systems is estimated at around 30%. Furthermore, water demand is increasing as a result of population growth, while resources are dwindling. Methodology This study used hydraulic modelling for leakage reduction through pressure control. For this purpose, a hydraulic model was created using the software EPANET for a selected water distribution network in a district-metered zone in Jeddah. The model was calibrated and validated for the district-metered zone using data obtained by SCADA. Pressure management using a pressure-reduction valve was then implemented to control the amount of leakage in water distribution systems. Results The preliminary findings show that pressure optimization was required as there were nodes within the network that had excessive pressure. Application of pressure management to the district metered zone showed that the reduction in water pressure from 5 bar to 2 bar resulted in an immediate reduction in water losses. The leakage volume through the district-metered area at the time of maximum pressure dropped by 10% after pressure reduction. Simultaneously, the minimum required pressure was upheld at each demand node, preventing any lack of pressure in the water distribution system. Conclusion The results indicated that pressure control should be integrated with hydraulic modelling for effective leakage reduction. This research could help water-supply companies as a support tool for planning and managing leakage in water distribution systems.

Establishing an Ecological Network to Enhance Forest Connectivity in South Korea’s Demilitarized Zone

This investigation delineated an ecological network within South Korea’s Demilitarized Zone (DMZ) to enhance ecosystem functionality, with a focus on forest landscape connectivity. The study employed spatial autocorrelation analysis and the minimum cumulative resistance model to identify key source patches. These patches are vital for maintaining connectivity across various topographies and land uses in the DMZ. Morphological spatial pattern analysis in the DMZ’s forest area showed a variation in forest patch types. The core class, less affected by external influences, was more prevalent in the eastern part. In contrast, the edge class, influenced by different environmental boundaries, was dominant in the western part. A 452.36 km long ecological network was constructed, serving as an essential corridor linking habitats of endangered species. This network covers a total forest area of 730.17 km2, which includes an existing forest protection area of 165.84 km2 (22.7%). The study also identified 564.33 km2 (77.3%) of previously non-designated forest regions as potential conservation areas. This aims to significantly increase forest connectivity within the DMZ. The research highlights the effectiveness of spatial planning tools in promoting ecosystem integrity in politically sensitive and restricted-access areas.

Mixed reality holograms for percutaneous lead extraction of cardiac implantable electronic devices

To assess the potential of mixed reality holograms (MixR) based on CT images to improve percutaneous lead extraction (PLE) planning and intraoperative assistance. This was a prospective, controlled, single-centre study. Five patients with CIED infection for PLE were included in the study. Conventional imaging (chest radiograph and CT) and MixR holograms were evaluated for preoperative planning to identify common complications such as vascular thrombosis, broken leads, loops, kinking, fibrosis along the wires, and perforation of cardiovascular structures. The degree of difficulty of the procedure was estimated based on potential complications. After the PLE procedure, the level of concordance between conventional imaging and MixR holograms with intraoperative findings was evaluated. The utility of MixR intraoperative guidance was also assessed. MixR holograms demonstrated a very high correlation in predicting the presence of loops, kinking, and fibrosis compared to conventional imaging, which showed a low-to-high correlation. MixR also showed a high correlation in estimating the degree of difficulty of the procedure compared to conventional imaging, which tended to underestimate it. The surgeon who performed the PLE agreed that MixR was helpful during intraoperative assistance. MixR holograms based on CT images are an effective tool for understanding cardiovascular anatomy and detecting potential areas of complications. MixR may be used as a complementary tool for both preoperative planning and intraoperative assistance in PLE procedures.Graphical abstractMixed reality holograms for intraprocedural intervention assistance.