scholarly journals Underground Land Administration from 2D to 3D: Critical Challenges and Future Research Directions

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1101
Author(s):  
Bahram Saeidian ◽  
Abbas Rajabifard ◽  
Behnam Atazadeh ◽  
Mohsen Kalantari

The development and use of underground space is a necessity for most cities in response to rapid urbanisation. Effective underground land administration is critical for sustainable urban development. From a land administration perspective, the ownership extent of underground assets is essential for planning and managing underground areas. In some jurisdictions, physical structures (e.g., walls, ceilings, and utilities) are also necessary to delineate the ownership extent of underground assets. The current practice of underground land administration focuses on the ownership of underground space and mostly relies on 2D survey plans. This inefficient and fragmented 2D-based underground data management and communication results in several issues including boundary disputes, underground strikes, delays and disruptions in projects, economic losses, and urban planning issues. This study provides a review of underground land administration from three common aspects: legal, institutional, and technical. A range of important challenges have been identified based on the current research and practice. To address these challenges, the authors of this study propose a new framework for 3D underground land administration. The proposed framework outlines the future research directions to upgrade underground land administration using integrated 3D digital approaches.

Author(s):  
Gerald R. Ferris ◽  
B. Parker Ellen ◽  
Charn P. McAllister ◽  
Liam P. Maher

Organizational politics has been an oft-studied phenomenon for nearly four decades. Prior reviews have described research in this stream as aligning with one of three categories: perceptions of organizational politics (POPs), political behavior, or political skill. We suggest that because these categories are at the construct level research on organizational politics has been artificially constrained. Thus, we suggest a new framework with higher-level categories within which to classify organizational politics research: political characteristics, political actions, and political outcomes. We then provide a broad review of the literature applicable to these new categories and discuss the possibilities for future research within each expanded category. Finally, we close with a discussion of future directions for organizational politics research across the categories.


2021 ◽  
Vol 12 ◽  
Author(s):  
Giulia Baldi ◽  
Francesca Soglia ◽  
Massimiliano Petracci

Spaghetti meat (SM) is a recent muscular abnormality that affects the Pectoralis major muscle of fast-growing broilers. As the appellative suggests, this condition phenotypically manifests as a loss of integrity of the breast muscle, which appears soft, mushy, and sparsely tight, resembling spaghetti pasta. The incidence of SM can reach up to 20% and its occurrence exerts detrimental effects on meat composition, nutritional value, and technological properties, accounting for an overall decreased meat value and important economic losses related to the necessity to downgrade affected meats. However, due to its recentness, the causative mechanisms are still partially unknown and less investigated compared to other muscular abnormalities (i.e., White Striping and Wooden Breast), for which cellular stress and hypoxia caused by muscle hypertrophy are believed to be the main triggering factors. Within this scenario, the present review aims at providing a clear and concise summary of the available knowledge concerning SM abnormality and concurrently presenting the existing research gaps, as well as the potential future developments in the field.


Author(s):  
Mengyuan Qiu ◽  
Ji Sha ◽  
Noel Scott

Visiting natural environments could restore health and contribute to human sustainability. However, the understanding of potential linkages between restoration of visitors and nature-based tourism remains incomplete, resulting in a lack of orientation for researchers and managers. This study aimed to explore how visitors achieve restoration through nature by analyzing published literature on tourism. Using a systematic review method, this study examined destination types, participant traits, theoretical foundations, and potential restorative outcomes presented in 34 identified articles. A new framework that synthesizes relevant research and conceptualizes the restorative mechanisms of nature-based tourism from a human–nature interaction perspective was developed. Owing to the limitations in the theories, methods, cases, and the COVID-19 pandemic, interdisciplinary methods and multisensory theories are needed in the future to shed further light on the restoration of visitors through nature-based tourism. The findings provide a theoretical perspective on the consideration of nature-based tourism as a public-wellness product worldwide, and the study provides recommendations for future research in a COVID-19 or post-COVID-19 society.


2022 ◽  
Vol 73 ◽  
pp. 277-327
Author(s):  
Samer Nashed ◽  
Shlomo Zilberstein

Opponent modeling is the ability to use prior knowledge and observations in order to predict the behavior of an opponent. This survey presents a comprehensive overview of existing opponent modeling techniques for adversarial domains, many of which must address stochastic, continuous, or concurrent actions, and sparse, partially observable payoff structures. We discuss all the components of opponent modeling systems, including feature extraction, learning algorithms, and strategy abstractions. These discussions lead us to propose a new form of analysis for describing and predicting the evolution of game states over time. We then introduce a new framework that facilitates method comparison, analyze a representative selection of techniques using the proposed framework, and highlight common trends among recently proposed methods. Finally, we list several open problems and discuss future research directions inspired by AI research on opponent modeling and related research in other disciplines.


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