Specific Plan Research Articles

The Port and Logistics Dimension of the UAE’s Strategy in Africa

The Russian Federation, expanding cooperation with the countries of the “world majority”, pays special attention to cooperation with Africa. Moscow has held two summits and adopted specific action plans for the development of relations with the states of the continent. However, further progress rests on limitations and difficulties of a financial and economic nature, problems of access to the markets of African countries, including our grain products. It is important to study and take into account the proven experience of third countries in these matters. In this regard, a special place is occupied by the study of approaches followed by the UAE, which has a well-developed and proven strategy for promoting its interests in Africa based on the accelerated development of port and logistics infrastructure, assistance to international and intercontinental trade. The article contains an analysis of the UAE’s strategy towards Africa, with an emphasis on its port and logistics dimension. Special attention is paid to the study of the experience of the Emirati port operators. The UAE’s activity in certain sub-regions of Africa is considered; the existing problems and components of the success of specific projects are noted. The question is raised about the possible combining the efforts of the two countries: the UAE - in the field of port and logistics facilities, the Russian Federation - in the field of their physical protection.

Practical Application and Management of Information Communication Technology (ICT) to Enhance the Performance of Ugandan Secondary Schools in West Nile

This study focuses on the contribution that Information and Communication Technology (ICT) can make to improving teacher and student performance in secondary schools in West Nile Region, Uganda. Examines the existing ICT implementation, assesses integration and potential benefits issues, and analyses the relationship between ICT usage and learning outcomes. The research is focused on showing that ICT can go global and how it connects Uganda’s secondary schools in West Nile to global education networks. ICT enhances global learning through active participation, innovation, and flexibility through access to international resources and embracing cross-boundary collaboration and virtual interchanges. This has improved student achievement but also endows students and teachers with the competencies to prosper in a globally connected environment. Ugandan schools have poorly developed ICT facilities, but schools embrace ICT education and facilities for operations. The study centers on specific ICT issues in West Nile schools and explores the possibility of using ICT to raise aggregate performance and efficiency in communication, collaboration, and organizational management. Quantitative and qualitative data were collected from 400 respondents, including teachers and students from 10 secondary schools. Data collection tools included questionnaires and interviews. Quantitative analysis was performed using SPSS, while NVivo was used for qualitative analysis. Ethical considerations were strictly adhered to protect participants' rights. While observing ICT integration in teaching across the ten selected secondary schools in West Nile and surveying 100 teachers, researchers found that 55.6% of them sometimes, 33.3% consistently, and 11% seldom integrate ICT in their teaching. This limited integration is due to a lack of ICT equipment, for example, computers, projectors, and internet connections; inadequate teacher education, where the majority of the teachers are found to be either lacking skills or self-confidence to incorporate ICT in teaching; and limited resource availability where even schools that have procured ICT tools are most often found to be having very few that are inadequacy for the needs of both teacher and students to make effective use of. These results raise concerns regarding the existing disparities in developments and funds for ICT training in West Nile’s secondary schools, with recommendations being made to enhance specific plans to reduce the digital divide. These include making ICT tools a focal area, increasing internet connection, and providing training activities that would increase and develop the competencies of the teaching staff. They seek to devise a technological learning atmosphere to enhance education, teacher, and student learning outcomes

After the battle: Emergent norms and the silencing of dissent in a Norwegian wind power community

In the small municipality of Åfjord on the Norwegian coast, home to one of Europe's largest onshore wind power installations, we observed a shift in critical attitudes towards a specific wind power development plan. Initially considered legitimate standpoints within an ongoing debate over land use, these viewpoints transformed into silenced opinions, or acquiescence, as the project progressed from the planning stage to fully operational wind power plants. A demand for consensus emerged within the local community. Through qualitative analysis of in-depth interviews with concerned stakeholders and community members, we employ a social norm perspective to explore the catalysts behind that shift and discuss potential consequences of the transformation. The article transcends the conventional explanatory approach to opinions on wind power development and provides valuable insights to the field of research on social acceptance. Specifically, it demonstrates that key drivers of acceptance, such as economic spin-off effects, can evolve into codes dictating legitimate behaviour and opinions in host communities. This poses a potential threat to the free exchange of opinions and local democracy.

Preface

Abstract The 3rd International Symposium on Arboriculture in the Tropics (the 3rd ISATrop2024) “Building Resilient Cities: Integrating Arboriculture Practices for Sustainable Development” Online Symposium, Bogor-Indonesia, 1-2 August 2024 Resilient cities are not only able to withstand shocks and pressures but also prioritize environmental, social, and economic sustainability. By integrating sustainable practices into urban planning and development, cities can increase their resilience and ensure a better quality of life for their residents. Developing an urban resilience strategy is very important for cities that want to build resilience. This strategy should include short-term and long-term goals, specific action plans, and performance indicators. This should also involve ongoing monitoring, evaluation, and adaptation to address evolving challenges and opportunities. The sustainability and resilience of urban areas to climate change can be improved by rehabilitating natural systems and integrating nature-based approaches with conventional infrastructure and urban development. This principle especially applies to small and medium-sized cities in Asia that are already struggling to adapt to the threat of climate change and natural disasters. Green infrastructure must be a cornerstone in the planning, developing, and maintaining cities affected by climate change. Local landscapes and natural systems (including green spaces, urban parks, and urban forests), networks, and functions must be maintained or revitalized to exploit their multiple benefits, including building urban resilience and sustainability. The design, construction, management, maintenance, and use of environmentally friendly urban infrastructure is best done with local communities. Cross-sectoral collaboration from various government departments, together with the private sector and communities, can ensure solutions that best suit local needs. List of Symposium Committee, Proceeding Organizing Committee, Moderator, Scientific Committee and Participants are available in this Pdf.

The role of artificial intelligence and machine learning in optimizing U.S. healthcare supply chain management

This paper aims to review the role of Artificial Intelligence and Machine Learning in managing the healthcare supply chain in the United States. Healthcare supply chains face several challenges such as fragmentation, lack of real-time visibility, and inventory management issues. However, there are solutions with the help of AI and machine learning, including the availability of predictive analytics to improve demand forecasting, optimization algorithms for inventory and logistics, and automated quality control. Application areas demand forecasting, supplier selection, logistics optimization, quality control, and real-time tracking. The applications of AI in healthcare supply chains have the potential to improve the healthcare supply chain in terms of reduced costs, increased efficiency, optimized decision-making, and better patient outcomes. However, the implementation experience has shown several challenges such as data quality, privacy concerns, regulatory compliance, and workforce adaptation within organizations. Successful implementations in various health organizations in the US give valuable insights into how AI could be well implemented. The future presents several opportunities for supply chain optimization with the rise of blockchain and Internet of Things (IoT) integration. For healthcare supply chains to adopt AI, organizations should have specific AI plans, start with pilot projects in high-impact areas, invest in data infrastructure, and ensure strong leadership support. As AI becomes increasingly critical for competitive advantage, it has the potential to create more resilient, efficient, and patient-centric supply chains in the US healthcare system.

A Comparative Case Study of Maxillary Temporary Dentures Fabricated Using Two Digital Impression Techniques

The loss of multiple teeth can lead to various issues such as impaired oral function, speech difficulties, and aesthetic concerns, significantly reducing a patient's quality of life. Prosthetic treatment is necessary to address these issues, and the specific treatment plan is determined based on the individual patient's condition. Temporary dentures are used to restore oral function and aesthetics until the final prosthesis is completed, helping patients recover from the functional and esthetic changes caused by tooth loss.Advances in digital technology have enabled the use of CAD-CAM in dental treatments, reducing the number of visits and improving the accuracy of denture fabrication. For the fabrication of the temporary denture in this case, impressions were acquired using two methods: intraoral scanning and a conventional impression method followed by model scanning. The teeth were arranged and the denture was designed using CAD software, and then fabricated using a 3D printer. This case report details the process of creating a temporary denture for a completely edentulous patient using digital technology, and the patient achieved a satisfactory functional and aesthetic outcome.

A predictive model for Gamma Knife intermediate dose spill: R50%Analytic-GK.

Minimizing intermediate dose spill in stereotactic radiosurgery (SRS) for brain treatment is crucial. Intermediate dose spill correlates with the exposure of normal brain tissue to high doses, which increases the risk of radionecrosis. R50%, defined as the volume of the 50% of prescription isodose cloud/planning target volume, is one metric for intermediate dose spill. A predictive model for R50% in linear accelerator VMAT-delivered SRS has been developed Desai etal. (2020) and is called R50%Analytic. This study extends the R50%Analytic model to Gamma Knife (GK) delivered SRS, resulting in the R50%Analytic-GK model. Phantom calculations were performed on 11 spherical target volumes ranging from 0.001 to 44cm3 to develop the R50%Analytic-GK model. R50%Analytic-GK was tested against clinical data from 18 brain metastasis cases with one to 11 targets treated on GK Icon and planned in GammaPlan with lightning dose optimizer. Thirty-five targets with volumes between 0.011 and 27.4cm3 were analyzed by extracting the R50% achieved clinically (R50%Clinical) for comparison to the predicted intermediate dose spill from R50%Analytic-GK. The predicted R50%Analytic-GK values generally represent a lower bound for the R50%Clinical values as the model would predict. The Difference, R50%Clinical - R50%Analytic-GK, has a median value of 0.92, which quantifies the lower bound nature of R50%Analytic-GK. The model reflected the character of intermediate dose spill for the clinical cases. A few outliers were likely due to specific planning complexities. The R50%Analytic-GK model for intermediate dose spill successfully extends the theoretical framework of R50%Analytic to GK-delivered SRS. It provides a method to predict the intermediate dose spill for GK Icon treatments. This model can aid in assessing SRS treatment plans by providing a benchmark for the intermediate dose spill for comparison.

Inheritance and Innovation: A Study on the Path of Ancient Village Cultural Tourism Planning and Design

In the global wave of cultural heritage protection, the preservation and reuse of ancient settlements has become increasingly prominent, especially in the context of increasing cultural tourism. Taking Nanmen Village as a case study, this paper can explore how to skillfully integrate technological innovation and contemporary aesthetic concepts while maintaining traditional values, in order to achieve a prosperous innovation process. The first strategy is to investigate and understand the historical origin, cultural characteristics and existing problems of Nanmen Village in detail, so as to clarify the difficulties encountered in the process of inheritance and transformation of this ancient community.Then, this paper puts forward the concrete path from two aspects of inheritance and innovation. In the aspect of inheritance, it focuses on the measures to protect traditional architecture, folk customs and intangible cultural heritage, as well as the methods to strengthen community participation and residents' education; In terms of innovation, it introduces the application of Internet technology and digital twin technology, such as online booking and tour, social media promotion, virtual reality experience and intelligent management. In addition, combined with many successful cases at home and abroad, this paper also analyzes the effect of these innovative designs in practical application, and provides specific planning and design schemes and implementation strategies for Nanmen Village. Finally, this study refines the accumulated insights, highlights the decisive role of cultural inheritance and innovation in the evolution of ancient village cultural tourism, and makes future exploration paths. This study not only contributes theoretical and practical guidance to the cultural tourism development of Nanmen Village, but also provides a reference for the conservation and evolution of other ancient settlements.

Feeding behavior of blue whales (Balaenoptera musculus) during austral summer in northern Chilean Patagonia

Over recent decades, the feeding strategies of the blue whale (Balaenoptera musculus) in the northern Chilean Patagonia have been studied mainly through visual observation and anatomical dissection, with limited direct behavioral analyses and measurements of prey distribution due to the difficulty of sampling. Here, we investigated the foraging ecology of this species during six annual research cruises (2014–2019) in the northern Chilean Patagonia, an important feeding and nursery area. We deployed 28 sound and movement recording tags (DTAGs), attached by suction cups, to measure fine-scale behaviors of this species. In addition, from 2016 to 2019, prey density and distribution were simultaneously recorded with tag data utilizing a scientific echosounder. A total of 949 foraging dives and 3,183 feeding events were detected from movement sensors throughout more than 190 hr of data, during both day and nighttime. Blue whales exhibited both shallow and deep foraging events utilizing different strategies in response to changing conditions of prey depth and density, with foraging dives recorded continuously for the whole duration of the deployments. Whales showed a higher feeding rate at night as they foraged on shallow and dispersed krill, but they exhibited a higher rate of foraging events per dive during the day, as they foraged on deep and dense krill patches. The whales used less energetically costly maneuvers when foraging near the surface, with lower values of pitch and speed. Both strategies are consistent with optimal foraging theory, as the whales minimizing energetic costs associated with feeding while simultaneously maximizing energy intake. These results provide valuable insights into the behavioral and foraging ecology of blue whales to promote specific conservation plans in the northern Chilean Patagonia.

A Statistical Approach for Characterizing the Behaviour of Roughness Parameters Measured by a Multi-Physics Instrument on Ground Surface Topographies: Four Novel Indicators

With a view to improve measurements, this paper presents a statistical approach for characterizing the behaviour of roughness parameters based on measurements performed on ground surface topographies (grit #080/#120). A S neoxTM (Sensofar®, Terrassa, Spain), equipped with three optical instrument modes (Focus Variation (FV), Coherence Scanning Interferometry (CSI), and Confocal Microscopy (CM)), is used according to a specific measurement plan, called Morphomeca Monitoring, including topography representativeness and several time-based measurements. Previously applied to the Sa parameter, the statistical approach based here solely on the Quality Index (QI) has now been extended to a multi-parameter approach. Firstly, the study focuses on detecting and explaining parameter disturbances in raw data by identifying and quantifying outliers of the parameter’s values, as a new first indicator. This allows us to draw parallels between these outliers and the surface topography, providing reflection tracks. Secondly, the statistical approach is applied to highlight disturbed parameters concerning the instrument mode used and the concerned grit level with two other indicators computed from QI, named homogeneity and number of modes. The applied method shows that a cleaning of the data containing the parameters values is necessary to remove outlier values, and a set of roughness parameters could be determined according to the assessment of the indicators. The final aim is to provide a set of parameters which best describe the measurement conditions based on monitoring data, statistical indexes, and surface topographies. It is shown that the parameters Sal, Sz and Sci are the most reliable roughness parameters, unlike Sdq and S5p, which appear as the most unstable parameters. More globally, the volume roughness parameters appear as the most stable, differing from the form parameters. This investigated point of view offers thus a complementary framework for improving measurement processes. In addition, this method aims to provide a global and more generalizable alternative than traditional methods of uncertainty calculation, based on a thorough analysis of multi-parameter and statistical indexes.

Using Artificial Intelligence for Personalized Cancer Treatment

The rapid evolution of artificial intelligence and the tools it has created gives rise to significant opportunities for precision oncology and promises a brighter future for the development of the sector. Precision oncology is a modern and advancing branch of cancer treatment and it is a renovated approach which specializes on specific treatment plans rather than “one-size-fits”; with advanced technology including but not limited to genomics, proteomics and bioinformatics, precision oncology focuses on optimizing therapeutic efficacy by targeting the specific molecular and cellular characteristics of a patient's cancer. This review paper explores the sophisticated and complex potential roles of artificial intelligence in cancer treatment, emphasizing on its impact in personalized treatment plans, immunotherapy and diagnostic accuracy. The immense database that AI has access to enables medical professionals to analyze imaging results and detect similarities of symptoms, genetic patterns, offering enhanced prognostic and diagnostic capabilities by eliminating human error and increasing cost effectiveness. This paper also dives into applications such as immune checkpoint inhibitors, digital pathology and demonstrations of the remarkable capability of artificial intelligence in multi-omics integration. Nonetheless, the advent of such advanced artificial intelligence tools, although promising, have not yet become the “gold standard” in oncology due to many rising agitations regarding reliability, since treatment decisions made by opaque AI algorithms are prone to error due to potential biases in AI systems and design errors. By critically examining these points, this paper evaluates both the advantages and disadvantages of the future implementation of artificial intelligence in the field of precision oncology, aiming to devise optimal integration in clinical practice.

Current Status and Progress in Integrative Treatment of Acute Ischemic Cerebrovascular Disease

Acute ischemic cerebrovascular disease (AICD) poses a severe threat to human health, characterized by high incidence and disability rates. Western medicine currently offers multiple treatment methods, such as thrombolysis, anticoagulation, and cerebral circulation improvement, while traditional Chinese medicine demonstrates unique advantages in herbal prescriptions, proprietary Chinese medicines, acupuncture, and massage therapies. Integrative treatment approaches combining Chinese and Western medicine have become widespread in clinical practice, yet challenges remain in optimizing specific treatment plans and elucidating mechanisms of action. This paper aims to comprehensively analyze the current status of integrative treatment for AICD, outline its developmental trajectory, and provide insights for enhancing treatment efficacy.

The effectiveness of implementing the HACCP system to ensure the quality of food products in regions with ecological problems

This study developed and implemented a specific HACCP plan for the meat pate “Phirmennyi” at the small meat processing enterprise “Alteev” in Semey, Kazakhstan. The research, conducted in collaboration with the Department of Food Production Technology and Biotechnology at Shakarim University, was carried out in an area affected by the ecological consequences of the former Semipalatinsk Nuclear Test Site. The study aimed to identify critical control points (CCPs) and assess potential risks following the Technical Regulations of the Customs Union. Additionally, it evaluated the effectiveness of the HACCP plan in reducing contaminants, such as heavy metals, radionuclides, and pesticides, while considering the region’s environmental impact on food safety and quality. Standard procedures were followed for hazard analysis, CCP identification, setting critical limits, monitoring, corrective actions, verification, and record-keeping. Heavy metals were measured using inductively coupled plasma mass spectrometry, while Cs-137 radionuclides were analyzed with scintillation and semiconductor gamma spectrometers. Statistical analysis was conducted in Microsoft Excel to compute mean values, standard deviations, and correlations, with significance defined at p ≤ 0.05. Five CCPs were identified during the production of an experimental batch of meat pâté, including raw material acceptance, blanching, cooking, cooling, and packaging/storage. Implementing this plan resulted in a reduction in contaminants, including a decrease in lead from 0.55 to 0.51 mg/kg, arsenic from 0.12 to 0.07 mg/kg, and Cs-137 from 7.2 to 6.8 Bq/kg. By addressing both the contaminants and the specific environmental context of the region, this research demonstrates the critical role of a well-structured food safety plan. The HACCP system not only improved food quality but also ensured compliance with safety standards, providing reassurance to consumers. This case study advocates for broader adoption of food safety management in regions with similar ecological challenges, promoting a more sustainable and secure food supply chain.

A Workshop and Toolkit to Support Late-Career Transitions for Faculty.

Twenty percent of medical school faculty are 60 years or older. These senior-career academic faculty often find a paucity of support for decision-making about late-career transitions. To help fill this professional development gap, we developed and tested an interactive workshop to facilitate deliberation and discussion among mid- and late-career faculty in various stages of career transition planning. The workshop included individual and small-group activities and a takeaway packet/toolkit for career transition planning. We conducted mixed methods analyses of postworkshop survey data to evaluate the workshop content, methods, and toolkit. The workshop was implemented six times, at four national conferences, one state-level conference, and one single institution, for a total of 207 participants. Evaluations were completed by 60% of participants. Thirty-one percent were thinking generally about transition, 40% were making specific plans for transition within 1-5 years, 15% were currently in transition, and 10% had fully transitioned. Perception of workshop objectives met received a median ranking of 4 (rated on a 5-point Likert scale). Participants reported positive outcomes, including taking time to think/reflect, finding starting points for transition planning, and sharing conversations. This highly rated, interactive workshop provides support and practical tools for faculty considering late-career transitions. In addition to providing resources for individual faculty, this workshop has value for an institution to support their senior-level faculty. We encourage the incorporation of this workshop into institutional faculty development programming to ensure a career lifespan approach to faculty development.

The Formation and Preservation of Urban Heritage Through Urban Landscape Transformation: A Case Study of Pittsburgh

This study examines the potential of urban landscape transformation to generate and develop new heritage and the role of heritage urbanism in an industrial city. It explores whether the changeover of urban heritage districts in Pittsburgh (PA, USA) can give rise to a novel type of urban heritage. Pittsburgh experienced urban development primarily driven by the presence and accessibility of natural resources, rather than favorable geographical conditions: topography characterized by rugged hills, rock formations, rivers, and stream valleys. The integration of the American-style grid within this unique natural environment resulted in intriguing juxtapositions. Consequently, elements such as bridges, viaducts, stairs, tunnels, and historical inclines gained paramount importance in shaping the urban fabric. The city’s remaining preserved or transformed urban heritage is protected through historic districts designated by the Department of City Planning, which enforces specific planning and design guidelines. The study employs a multi-faceted approach combining the concepts of historic stratification (urban palimpsest), integrated urban morphology, space syntax (integration analysis), and heritage urbanism. During the personally conducted long-term fieldwork, the selected case studies described herein (historic districts, university campus, and traditional neighborhood) proved to be the most suitable for demonstrating urban heritage formation through urban landscape transformation.

Картографическое обеспечение задач определения границ городской агломерации

Urban agglomeration in the modern context of urbanization is becoming one of the key forms of population settlement. However, the issue of accurately identifying the boundaries of the urban agglomeration remains open. The problems reflected in this scientific study are based on a variety of approaches and methods to determine the boundaries of emerging agglomerations, which leads to discrepancies and difficulties in organizing administrative and managerial measures for the development of the territory. The article is devoted to the development of cartographic support for solving the problem of delimitation of the Kazan urban agglomeration. The accuracy of the delimitation of the agglomeration zone is necessary to identify and justify specific planning decisions in the interests of the development of not a single city, but the entire agglomeration. This scientific article provides the developed cartographic material that provides the tasks of determining the boundary of the Kazan agglomeration both on the basis of existing scientific methods and based on the analysis of the functional differentiation of the territory. The solution of the primary task of determining the boundary of the Kazan urban agglomeration was provided through the development of intermediate cartographic material reflecting the socio-economic criteria for identifying the agglomeration in combination with 60-minute transport accessibility from the city of Kazan. Further, on the basis of the carried out functional differentiation, marker functions were identified that reflect the most intense connections in the “city–agglomeration zone” system. Comparing the developed cartographies with the analysis of the functional organization of the space, including the functional framework of the agglomeration, the boundary of the Kazan urban agglomeration was clarified. The conducted research reflects the breadth of scientific approaches and methods to identify urban agglomerations and allows us to deepen local research by applying the analysis of functional organization in identifying the boundaries of other emerging agglomerations.

A practical framework for applied forestry assisted migration

Recent and projected changes in climate over this century pose an unprecedented threat to the health, diversity, and productivity of forest ecosystems. Forests have migrated and adapted to long-term changes in climate over thousands to millions of years; however, natural migration rates and adaptive responses of tree populations cannot match the rapid pace of current climate change. Consequently, more climate-informed approaches to reforestation are needed as current reforestation strategies using local seed sources may no longer be adequate to meet forest management objectives. Assisted migration is a climate change adaptation technique that can help maintain the ecosystem services and economic value that forests provide. Forestry assisted migration (FAM) focusses on the movement of populations of widespread, commercially, or ecologically important forest tree species within or just beyond their current ranges as a way to maintain forest productivity and health in the face of climate change. Although the forestry community recognizes FAM as a reforestation tool, guidance for planning and implementation of FAM is lacking and a framework that provides this guidance can prove useful to land managers with limited time and resources available who want to undertake FAM. We developed a practical framework (the FAM Framework) to provide a structured approach to ensure the most important considerations and best available science are utilized by land managers wanting to implement FAM on their land base. The FAM Framework incorporates multiple factors for the application of FAM in four sequential phases: assessment and analysis, climate-based plant material selection, seed procurement and deployment, and documentation and monitoring. The FAM Framework was tested by developing an assisted migration plan for the Superior National Forest, Minnesota (MN), and lessons learned from the development of this specific plan were used to revise and improve the FAM Framework for suitability across all lands. While originally designed to meet the needs of National Forest System land managers, it is relevant and applicable across the spectrum of land ownership because it incorporates consideration of critical elements in planning and implementing FAM on any landscape while facilitating adaptive management for active learning and future implementation.

The Investigation of Machine Learning and Deep Learning Classification of Internet of Things (IoT) Enabled Medical Devices

The present cross-sectional, quantitative study investigates the classification capabilities of ML and DL in processing data from IoT-enabled medical devices: heart rate variability (HRV), blood pressure, blood glucose levels, and physical activity in patients with diabetes and cardiovascular diseases. Eight patients from AIIMS, New Delhi participated in this study. In the current investigation, two types of measurements are taken into consideration: cardiovascular measures and diabetes management metrics, which include BMI, blood pressure, blood glucose, physical activity, and HRV. The outcomes showed a positive association with blood glucose level and age (0.55), negative correlation between blood glucose and physical activity (-0.68), which had significant significance towards exercising importance in diabetes management. Blood glucose correlated moderately favorably with BMI with 0.45, while age and BMI correlated at 0.32. These results show how ML and DL techniques can improve the interpretation of complex health parameters from IoT-enabled devices to better manage patients and develop specific healthcare plans in chronic diseases.

Leisure planning process: systematic adhocracy

ABSTRACT Research Question Guided by literature, a leisure planning typology was developed with four phases to identify how ARCs were planned. The typology guided the deductive analysis to address our research question, How is a leisure planning process applied in ARC planning? Methodology A qualitative multiple-case study design was applied. Data from document analysis (n = 264) and semi-structured interviews (n = 19) were deductively analyzed based on a leisure planning typology. Findings A lack of adherence to specific planning models was evident. Instead, an ad hoc planning approach was applied, where planners relied on data collected to assist how an ARC should be planned. The characteristics associated with ad hoc planning led to this approach termed “systemic adhocracy”. Practical implications Planning, guided by a structured framework is crucial for maximising community benefits and addressing needs. Our study provides insight to the ARC planning process and the opportunity to apply the leisure planning typology to guide future investments, optimise planning, and enhance community outcomes.

Digital Transformation Strategy of Macys: Addressing Challenges and Achieving Revival

Abstract: This study explores the challenges faced by Macys in the United States and its strategy for digital transformation. Firstly, it introduces the rise and fall of the U.S. department store industry and the challenges Macys faces as a representative of the traditional department store industry, such as the rise of e-commerce and changes in consumer shopping habits. Then, taking Macys as a case study, it describes its digital transformation strategy, Polaris, including cost reduction, accelerated digitization, reshaping the supply chain and other initiatives and the results achieved. It then proposes specific plans for staffing adjustments, enterprise transaction process optimization and online business model modifications. Finally, the challenges that may be faced in implementing digital transformation programs, such as data silos, change management and financial overheads, are analyzed, and solutions are proposed. By summarizing and learning from the successful experiences of modern enterprises, this study proposes a series of feasible digital transformation plans for Macy's to emerge from the predicament of the traditional department store industry, meet the challenges of the digital era, and achieve a renaissance.