GIScience and Neighborhood Change: Toward and Understanding of Processes of Change

Processes of neighborhood change are the result of the unfolding of events and decisions by multiple actors operating at varying spatial and temporal scales, enabled and constrained upon an unequal urban landscape. The contributions of GIScience towards understanding these processes has evolved from the simple mapping of static, cross-sectional maps towards an embrace of novel data and methods that enable longitudinal trajectories to be extracted and neighborhood futures to be predicted. In this article, I review these advancements and chart a course forward that considers a future research agenda that is critically cognizant of the potentials and perils of new data sources and method, is representative of the full spectrum of processes operating both visibly and invisibly that give rise to observed neighborhood outcomes, and considers their varying spatial and temporal scales.

The Use of Big Data in Tourism: Current Trends and Directions for Future Research

The aim of this research is to examine the new landscape that is taking shape in the tourism economy, due to the adoption of technological innovations. The technologies and systems used to make the most of the resulting interdisciplinary and multilingual big data, the methods by which heterogeneous elements from different sources are incorporated to bring new knowledge, and the modern services that are ultimately implemented and provided to the public, as well as the people involved in this process, and those who benefit from the new services are among the issues analyzed. The work is not limited to a simple mapping of space but concludes with an evaluation of the systems already implemented and the various methods of analysis and exploitation of large-scale data for this industry, which is based on detailed research of the current literature to identify the potential gaps for future research. This is a literature review. The authors have identified the content of this research on well-known online databases which include scholar, google and Scopus. They used the appropriate keywords such as “big data” & “tourism innovation” to reach the publications used in this research, also given attention on using recent papers which are derived from reliable journals. The research has concluded that the use of big data in the tourism sector is a rising trend. Big data creates expectations for a better understanding of tourism demand and the adjustment of supply by tourism companies to meet the demands of tourists and the profitable activity of tourism businesses. There is a need to examine how can big data help the hotels to deal with Covid-19 pandemic, which can be a topic for future research. Big data is one of the most recent trends on innovation, Information Communication Technologies (ICT) and knowledge management. Hence, there is a need to gather and analyze the existing publications which concern the tourist industry. The originality of this research stems from making an analysis of the current situation as well as it is a bridge to the future by making suggestions on how future research can be shaped. The key limitation of this research resides on that it focuses on the existing literature and used secondary data. However, it gives directions for the future research which can take place with primary data collection. Received: 3 July 2021 / Accepted: 19 August 2021 / Published: 5 September 2021

Dehydration Alters Behavioral Thermoregulation and the Geography of Climatic Vulnerability in Amazonian Lizards

Since high temperatures and low water availability often strike organisms in parallel, observing how they behaviorally thermohydroregulate may help us to better understand their climatic vulnerability. This understanding is especially important for tropical lizards, purportedly under greater climatic risk. We observed the influence of hydration level on the Voluntary Thermal Maximum (VTM) of two small amazonian lizard species: Loxopholis ferreirai (semiaquatic and scansorial) and Loxopholis percarinatum (leaf litter parthenogenetic dweller), accounting for several sources of variation (turn, body weight, start temperature and heating rate). Then, we used two modelling approaches (simple mapping of thermal margins and NicheMapR), to examine the effects of dehydration, decrease in rainfall, ability to burrow, and tree cover availability, on the geography of climatic vulnerability. Dehydration decreased the VTM in both species, which also reacted to start temperature and heating rates. Our two modelling approaches show that dehydration, changes the intensity, extent and duration of thermal risk across the Amazon basin. Based on our results and previous studies, we identify new evidence needed to better understand thermohydroregulation and model the geography of climatic risk, more realistically.

Master Device With Bending Safety for Flexible Surgical Robots

Flexible robots have been widely studied for application to minimally invasive surgery because of their dexterity and miniaturization ability. Conventional master devices developed to manipulate rigid link-type robots are difficult to apply to flexible robots due to structural difference. In addition, the different kinematic structures of the master device and flexible slave robot cause complex mapping issues. Furthermore, most high-redundancy flexible robots inserted through an over-tube have limited bending angles depending on the insertion depth. Conventional master devices were not designed to comply with this limitation of flexible robots. We developed an isosceles master device that provides intuitive and simple mapping factors for controlling and maintaining the wire tension of a flexible robot in a safe range. We applied a variable isosceles triangle mechanism that structurally limits the bending angle according to the insertion depth. Experimental results showed that our master device can control a flexible slave robot with an error of less than 1.5 mm. Because of the limited bending angle, excessive tension and the resulting damage to the wire were prevented. The isosceles master device can also hold its position and orientation with a passive holding mechanism.

Clustering analysis of soil gas chemical ratios as a potential geochemical tool for surface geothermal exploration

<p>Geochemistry is a fundamental tool in surface geothermal exploration. In particular, the analysis of the composition of the soil atmosphere, the measurement of diffuse CO<sub>2</sub> flux and of the gas <sup>222</sup>Rn activity are important parameters to detect and characterize the contribution of volcanic/hydrothermal sources in the diffuse soil degassing.</p><p>The analysis of the soil atmosphere usually consists of determining the chemical and isotopic composition of the gases, including concentrations and molar ratios of multiple chemical species (e.g. He, H<sub>2</sub>, N<sub>2</sub>, Ar, Ne, O<sub>2</sub>, CH<sub>4</sub>, CO<sub>2</sub>), as well as the C isotopic ratios (<sup>13</sup>C/<sup>12</sup>C). In practice a single geochemical survey provides tens of different parameters for each sampling point. Taking into account that a typical survey is composed of hundreds of sampling points, the huge amount of collected data requires effective data mining tools to perform analyses going beyond the simple mapping of concentrations and/or ratios and to detect hidden patterns in the dataset.</p><p>Among the most effective multivariate statistical tools is clustering analysis. This technique allows determining the presence of groups of points showing a given degree of similarity. In this work we used and compared two different clustering techniques: the K-means and the DBSCAN algorithms, applying them to a geochemical dataset related to surveys realized in 2010 in the southern part of the island of Tenerife (Canary Islands Spain) with the aim of geothermal exploration. We show how the clustering analysis allows determining the presence of areas characterized by a similar chemical and isotopic composition. The use of standard geochemical tools allows interpreting the nature of these areal groups in terms of their relevance for the purposes of surface geothermal exploration.</p>

A demonstration of using the model reference principle to develop the function-oriented adaptive pulse-coded neural network

How can one design an adaptive pulsed neural network that is based on psycho-phenomenological foundations? In other words, how can one migrate the adaptive capability of a psychologically modeled neural network to a pulsed network? Neural networks that model psychological phenomena are at a larger scale than physiological models. There is a common presumption that pulse-coded neural network analogs to non-pulsing networks can be obtained by a simple mapping and scaling process of some sort. But the actual in vivo environment of pulse-coded neural network systems produces a much more diverse set of firing patterns. Thus, functional mapping from traditional neural network systems to pulse-coded neural network systems is much more challenging than has been presumed. This paper demonstrates that the employment of model reference adaptation as a method for applying scientific reduction is a powerful design tool for the development of a function-oriented adaptive pulse-coded neural network. The performance surface is empirically obtained by comparing the performance of the pulsed network to the non-pulsing network. Based on this surface, the adaptive algorithm is a combination of gain scheduling and steepest-descent method. Therefore, the adaptive property of the pulse-coded neural network is built upon a psycho-physiological foundation.

Serving the culture: Spatial interactions between cultural industries and advanced producer services in mainland China

The location patterns and organizational networks of both advanced producer services (APS) and cultural industries have attracted extensive attention in geography and other related disciplines. However, most research on these two sectors has examined each one in isolation, without paying attention on how they are engaged with each other. Drawing on a network analysis of the inter-firm service provision relationships between 245 cultural firms and their APS providers during the firms’ public listing processes in mainland China, this paper presents a pilot study of the functional interactions between cultural industries and APS from a geographical perspective. Our purpose is to expand the research on these two economic sectors from the simple mapping and ranking of their individual industrial activities to an investigation of the city-based spatial relationships between them. The outcome reveals that while the leading cultural firms and their APS intermediaries have demonstrated similar location patterns across major Chinese cities, the spatial interactions and connections between them are much more complicated than their co-location tends to suggest. This paper enriches our understanding of the functions of local clusters and trans-local networks in the establishment of inter-industrial linkages between the different sectors of knowledge economies. The paper also sheds light on the impacts of institutional context on the (spatial) development of cultural industries in a transitional economy.