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With rapid urbanization, cities are facing various ecological and environmental problems. Living in harmony with nature is more important than ever. This paper aims to evaluate the ecosystem and ecological features of Azheke village, a key component of the Hani Rice Terraces World Cultural Heritage in China. The focus is on exploring effective ways to improve the relationship between humans and the natural environment through urban design in order to create a livable and sustainable city that can promote the development of sustainable smart urban ecology design.

This study conducted a systematic literature review to answer the following research questions: (1) How does Azheke design achieve harmony between humans and nature? (2) What are the effective approaches to improve the relationship between humans and nature within urban ecosystems? (3) How can urban design learn and integrate from Azheke’s ecological features to improve the relationship between humans and nature?

Azheke sustains long-term human-nature harmony through traditional ecological knowledge (TEK) and efficient natural resource use. By incorporating biophilic design and nature-based solutions from Azheke, along with biodiversity-friendly urban planning, we can boost urban ecosystem health and create unique Azheke-inspired urban designs.

This research primarily focuses on the human-nature relationship, exploring design strategies based on biodiversity without delving into the interactions between other components of urban ecosystems, such as social-cultural and economic components.

This paper provides a new perspective and strategies for developing sustainable and smart urban ecology design. These findings can provide theoretical references for urban planners, designers and decision-makers.

The purpose of this paper is to analyze Spain’s success in developing mass tourism between 1950 and 1965.

This analysis will be carried out from a marketing point of view using the paradigm of the four Ps: product, price, promotion and place, but focusing on the product since, as will be seen, the three other variables had a much lesser impact at that early stage. The product, in holiday tourism, is the destination, a combination in which the main protagonist is the hotel. The authors will analyse the main characteristics of the tourist accommodation on offer in Majorca and Ibiza in two ways: by studying the general statistics on the one hand, and on the other, through the detailed description of two hotel projects focused on the same tourist market but conceptually very different. In the first, a British design from 1956, we see the seed of what could have been and was not. Spain could have been filled with enclave-type tourist destinations with little connection to the local economic network. The second hotel design, on the other hand, shows us the ideal establishment for the exploitation of mass tourism in open destinations.

In Spain, mass tourism was explosively successful because the local business community was able to offer a very attractive product.

The authors use the architectural designs of two hotels as the central axis of the description of the Spanish tourism product.

The purpose of this paper is to investigate the effect of different levels of place understanding (primarily typo-morphological analysis) on the nature of interventions within historic urban setting and buildings within the City of Amman.

The research methodology depended on an extensive thematic survey and analysis. The typo-morphological analysis addressed several of Amman's residential hills and their connections with the downtown area. The thematic place survey tool included different units of analysis (e.g. buildings, public spaces, streets and sloped lands between streets) and addressed the values of these various buildings and spaces, their typology, typo-morphology and relation to the urban context, nature of change and transformations over time to mention a few. The extensive survey also included semi-structured interviews about these buildings addressing their emergence, historic context and values.

The paper presents an architectural typology for Amman's architecture and its relationship with the city's morphology stressing the specificity of Amman's historic core and residential hills. The paper also discusses the effect of this level of place understanding on the nature and levels of interventions within historic settings and buildings.

This level of place understanding (typo-morphological analysis) can have a positive impact on the practice of architectural and urban conservation by informing the nature of interventions within historic urban setting and buildings within the city. More specifically, this level of place understanding can, first, inform the development of urban and heritage guidelines within conservation areas in one of Amman's residential neighborhoods (Weibdeh) and, second, inform the nature of interventions to existing historic buildings based on respect of building typology.

This paper contributes to the disciplines of architectural and urban conservation illustrating how place understanding can inform practices of heritage conservation and future policies and strategies concerning new intervention within such heritage places.

Nature’s contribution to people (NCP) is a concept that specifically recognizes the relationship of “humans and the natural environment” similarly to concepts of “cultural landscapes” and consistent to “heritage.” These concepts are essential in incorporating a diverse range of stakeholders from different scales, which is important for policy and practice. The paper aims to review the existing peer-reviewed papers in the Philippines, using meta-analysis and systematic review. We addressed the significant interlinkages that help facilitate the transition and strengthen the correlation of cultural ecosystem services (CES) and NCP in a cultural landscape setting.

To distinguish and support claims for NCP from CES, we conducted a meta-analysis and systematic review based on the 30-existing peer-reviewed articles on the Philippine cultural ES in the lenses of “heritage” and “cultural landscape.”

The results generated a few numbers of the Philippine CES studies, yet it has increased cumulatively year by year consistent with previous international studies. We found that most studies are focused on topics associated with “Indigenous People, Ancestral Domains, Protected Areas/Landscapes, and Indigenous and Local Knowledge” on the linkages concurrently distinguishing NCP to CES, and may signify stronger economic valuation in uncovering the sociocultural dimensions of these scholarships through its relational values in the lenses of cultural landscape and heritage.

The authors limited the search to peer-reviewed journal articles published from online databases and did not consider Philippine University based and local publications to have a systematic review. This is to prevent underestimating the vast amount of CES literature and avoid gray literature that is not peer-reviewed; hence, being able to analyze and produce focused, yet, credible data.

In a generalizing perspective, NCP 1, 6, 8, 12, 13, 15, 16, 17 and 18 have the most realized positive correlations of the reporting categories to the Philippine CES studies. The majority of the context-specific perspective NCP has strong conceptual claims in the existing Philippine CES literature through the studies’ variables aside from NCP 3, 4, 5, 7, 8 and 11 that are still mostly in the nature of generalizing perspective.

In conclusion, our results imply that the previous and existing CES studies in the Philippines harbor more attributes presented by the NCP reporting categories. This is deemed more suitable, and may signify stronger economic valuation in uncovering the sociocultural dimensions of these scholarships through its relational values in the lenses of cultural landscape and heritage.

Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition of RSI, and feature fusion is a research hotspot for its great potential to boost performance. However, RSI has a unique imaging condition and cluttered scenes with complicated backgrounds. This larger difference from nature images has made the previous feature fusion methods present insignificant performance improvements.

This work proposed a two-convolutional neural network (CNN) fusion method named main and branch CNN fusion network (MBC-Net) as an improved solution for classifying RSI. In detail, the MBC-Net employs an EfficientNet-B3 as its main CNN stream and an EfficientNet-B0 as a branch, named MC-B3 and BC-B0, respectively. In particular, MBC-Net includes a long-range derivation (LRD) module, which is specially designed to learn the dependence of different features. Meanwhile, MBC-Net also uses some unique ideas to tackle the problems coming from the two-CNN fusion and the inherent nature of RSI.

Extensive experiments on three RSI sets prove that MBC-Net outperforms the other 38 state-of-the-art (STOA) methods published from 2020 to 2023, with a noticeable increase in overall accuracy (OA) values. MBC-Net not only presents a 0.7% increased OA value on the most confusing NWPU set but also has 62% fewer parameters compared to the leading approach that ranks first in the literature.

MBC-Net is a more effective and efficient feature fusion approach compared to other STOA methods in the literature. Given the visualizations of grad class activation mapping (Grad-CAM), it reveals that MBC-Net can learn the long-range dependence of features that a single CNN cannot. Based on the tendency stochastic neighbor embedding (t-SNE) results, it demonstrates that the feature representation of MBC-Net is more effective than other methods. In addition, the ablation tests indicate that MBC-Net is effective and efficient for fusing features from two CNNs.

This paper aims to examine how the interrelation between architecture and the physical environment came to prominence and influenced the pioneering modernist architects to acquire the features of modern architecture that the British modernists later adopted. How the post-war urban poor of Britain, suffering from ill-health and dire need of sun, air and a good environment, played an essential role in alleviating the environmental concerns of the modern movement architects.

The methodology of this research involves a comprehensive architectural analysis of the Finsbury Health Centre alongside an in-depth historical investigation of modernist design principles. This review article examines books, articles and some archival materials, such as recordings, pictures, etc. on the early phase of British modernism and its environmental dimension by looking at the works of historians, architects and critics.

Design based on modernist principles. While it can be seen as the political agenda of the Labor Party, this building was not only functionally efficient but also represented the biometric concerns of modern architecture with the most natural means.

While this study provides valuable insights, it may be limited by historical documents and data availability.

The originality and value of this paper lie in its examination of the Finsbury Health Centre as a case study, shedding light on the environmental rhetoric of modernism in historic architecture. By providing a holistic assessment of the building’s environmental aspects, this research contributes to both architectural history and contemporary sustainable design practices.

As climate change increasingly affects rural food production, there is an urgent need to adopt agricultural adaptation strategies. Because the agricultural sector in Nepal is one of the most vulnerable to the effects of climate change, the adaptation strategies of household farmers in rural areas are crucial. This study aims to address the impacts of agricultural climate change adaptation strategies in Nepal. The research empirically analyzed climate hazards, adaptation strategies and local adaptation plans in Mangalsen Municipality, Achham District, Sudurpashchim Province, Nepal.

This study used a purposive sampling of household lists, categorized as resource-rich, resource-poor and intermediate households. The analysis used primary data from 110 household surveys conducted among six focus groups and 30 informants were selected for interviews through purposive random sampling.

Climate change significantly impacts rainfall patterns and temperature, decreasing agriculture productivity and increasing household vulnerability. To overcome these negative impacts, it is crucial to implement measures such as efficient management of farms and livestock. A comprehensive analysis of Nepalese farmers' adaptation strategies to climate change has been conducted, revealing important insights into their coping mechanisms. By examining the correlation between farmers' strategies and the role of the local government, practical policies can be developed for farmers at the local level.

This study represents a significant breakthrough in the authors' understanding of this issue within the context of Nepal. It has been conclusively demonstrated that securing land tenure or land security and adopting appropriate agricultural methods, such as agroforestry, can be instrumental in enabling Nepalese households to cope with the effects of climate change effectively.

This is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.

The random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.

Results show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.

The findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.

Although machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.