Investigation of The Sufficiency of Antalya Parks

Urban green spaces are areas established to meet the recreational needs of urban people. Although green spaces vary from country to country and region in terms of plan and design features, they were basically created to allow people to meet with nature. Parks are the basic components of urban landscapes that provide environmental and social functional value. Urban parks, in particular, provide spaces for outdoor physical activities. In order to take advantage of the opportunities of activities in the parks, users must have convenient access to these resources. One of the most important aspects for researching the use and potential benefits of urban green spaces is the assessment of their geographic accessibility. The widespread use of smart city systems and the gradual expansion of their usage areas increase the importance of spatial analysis. Spatial analyses are used in today’s urban management in the processes of determining social needs, identifying current problems, and putting forward solutions. When spatial analyses are used together with GIS, the field of application develops even more, and it supports local governments in responding to the changing demands of the society for a better life. In the study, the adequacy and accessibility of 160 city parks in Konyaaltı District of Antalya Province were examined. In terms of the adequacy of the parks, the area value of 10 m2 per person determined with the Construction Plan numbered 3194 was taken as basis. In terms of accessibility, distance values of 200, 400, 800, 1,200 meters were examined. Neighborhood boundaries and population information were obtained from the relevant units, and Arc-GIS software was used in the analysis. It was determined that the parks in Konyaaltı district were insufficient in terms of adequacy and accessibility. Finally, suggestions were made in terms of increasing the adequacy of the parks and ensuring accessibility.

Včasnostredoveké sídlisko v Brne-Medlánkach

The presented article examines the early medieval settlement in Brno-Medlánky. The archaeological finds were evaluated to obtain settlement spatial development and to reveal the practical, social and natural dimension of the settlement after the synthesis of the evidence. The relevance of the site in relation to early medieval Brno was also considered. The large quantity of ceramics, which was essential for this research, was processed using the database of J. Macháček. This enabled me to date the settlement between the 6th/7th to the 9th/10th century and, based on quantification, to characterise the morphological and technological features of the complex. The archaeological material was also compared with the material from other similar sites. The results of this analysis were acquired from data in the graphs, figures and quantification tables. The other findings were processed using descriptive models. Scientific analyses have proven the presence of blacksmithing and iron metallurgy at the site. Agricultural activities and processing of leather and textile were also documented at the site. The typical cumulative structure was evaluated within the framework of spatial analyses, together with the form and spatial development of the settlement. Moreover, the article deals with the complete skeletons of two dogs and one horse, and the human skeleton found in a storage pit. The complete animal skeletons were probably deposited for hygienic reasons; the human skeleton possibly proves an execution.

Transformation of the city of Split industrial heritage into a science center

Background: Split is a city in the Mediterranean, situated on Croatia’s coastline. Split’s northern coast has a long-stand-ing industrial function and harbors the city’s first electri-cal substation, designed by modernist architect Josip Maria Kodl. Objective: The goal of this work was to envision a science center in Split’s industrial zone in Dujmovača (the northern coast of the Split peninsula), comprising a science museum with a research and congress center. The programmatic and spatial analyses of the science center’s amenities and the proposal as a whole demonstrate the potential of this forgotten space in Split and breathe new life into Kodl’s ar-chitectural heritage. Methods: The proposed solution uses a dialogical narrative between a conservation, contextual, programmatic, and theoretical approach within a strict orthogonal structure, fostering the development of alternative associations and elaboration of architectural details.Results: The proposed solution constitutes a complex of multiple interconnected and flexible elements. This al-lows different parts of the Science Center to function inde-pendently of each other. This paper provides an analysis of design steps and methods, the proposal’s advantages and limitations, and the way the repurposing of industrial heri-tage was approached. Conclusion: The position of the Science Center in Dujmovača would provide one of the first impressions when entering Split on the future metro line. By reconcil-ing landscape and industrial architecture, the proposed building complex offers a framework for presenting various kinds of modifiable content, for both the pres-ent and the future.

Health Disparities and Climate Change: The Intersection of Three Disaster Events on Vulnerable Communities in Houston, Texas

Although evidence suggests that successive climate disasters are on the rise, few studies have documented the disproportionate impacts on communities of color. Through the unique lens of successive disaster events (Hurricane Harvey and Winter Storm Uri) coupled with the COVID-19 pandemic, we assessed disaster exposure in minority communities in Harris County, Texas. A mixed methods approach employing qualitative and quantitative designs was used to examine the relationships between successive disasters (and the role of climate change), population geography, race, and health disparities-related outcomes. This study identified four communities in the greater Houston area with predominantly non-Hispanic African American residents. We used data chronicling the local community and environment to build base maps and conducted spatial analyses using Geographic Information System (GIS) mapping. We complemented these data with focus groups to assess participants’ experiences in disaster planning and recovery, as well as community resilience. Thematic analysis was used to identify key patterns. Across all four communities, we observed significant Hurricane Harvey flooding and significantly greater exposure to 10 of the 11 COVID-19 risk factors examined, compared to the rest of the county. Spatial analyses reveal higher disease burden, greater social vulnerability, and significantly higher community-level risk factors for both pandemics and disaster events in the four communities, compared to all other communities in Harris County. Two themes emerged from thematic data analysis: (1) Prior disaster exposure prepared minority populations in Harris County to better handle subsequent disaster suggesting enhanced disaster resilience, and (2) social connectedness was key to disaster resiliency. Long-standing disparities make people of color at greater risk for social vulnerability. Addressing climate change offers the potential to alleviate these health disparities.

Mice identify subgoal locations through an action-driven mapping process

Mammals instinctively explore and form mental maps of their spatial environments. Models of cognitive mapping in neuroscience mostly depict map-learning as a process of random or biased diffusion. In practice, however, animals explore spaces using structured, purposeful, sensory-guided actions. Here we test the hypothesis that executing specific exploratory actions is a key strategy for building a cognitive map. Previous work has shown that in arenas with obstacles and a shelter, mice spontaneously learn efficient multi-step escape routes by memorizing allocentric subgoal locations. We thus used threat-evoked escape to probe the relationship between ethological exploratory behavior and allocentric spatial memory. Using closed-loop neural manipulations to interrupt running movements during exploration, we found that blocking runs targeting an obstacle edge abolished subgoal learning. In contrast, blocking other movements while sparing edge-directed runs had no effect on memorizing subgoals. Finally, spatial analyses suggest that the decision to use a subgoal during escape takes into account the mouse's starting position relative to the layout of the environment. We conclude that mice use an action-driven learning process to identify subgoals and that these subgoals are then integrated into a map-based planning process. We suggest a conceptual framework for spatial learning that is compatible with the successor representation from reinforcement learning and sensorimotor enactivism from cognitive science.

How far do they go?: A spatial examination of missing persons from hospitals

PurposeMissing person cases are a global issue impacting policing. Among these, those who abscond from hospitals are especially concerning because these reports require collaboration across services, often strain already limited police and hospital resources and present an elevated level of possible harm due to high prevalence of mental illness, disability and/or addiction. Despite this, to-date, there has been a lack of scholarly attention on this phenomenon from a policing perspective. The present study aims to fill this gap by exploring how far missing hospital patients travel and where they are commonly found.Design/methodology/approachUsing a sample of 731 closed case files (2014–2018) from one police service, we identify spatial behaviour patterns specific to this group of missing persons.FindingsResults suggest that most do not leave the hospital grounds or stay within a 5-km radius. Others were found close to the hospital, within city limits and/or returned of their own volition. By identifying these spatial behaviour patterns associated with missing hospital patients, police can refine probable search areas, allocate resources more efficiently, find the missing faster and develop better-informed responses and collaborative policies.Originality/valueOur research represents the first empirical investigation into missing persons from hospital settings through a spatial perspective. Through descriptive statistical and spatial analyses, we determine the distance between the hospital a given individual was reported missing from and the location of where they were ultimately found.

Doklady bojovej činnosti z obdobia 2. svetovej vojny v priestore medzi Trnavou a Trstínom (juhozápadné Slovensko). Možnosti aplikácie metódy KOCOA

At the recent time, the battlefield archaeology belongs to the slowly developing and establishing branches of Slovak archaeology. Thank to only few zealous researches gains this field of interest consistently more attractiveness among researchers. The main efforts are concentrated on describing and documentation of military activities or preservation and protection of battlefield relics. Nevertheless, researchers abroad focus on different issues and use spatial analyses to reconstruct or understand strategies of combatants. In the following text we try to demonstrate one of these analyses known as KOCOA. An area between Trnava and Trstín (South-western Slovakia) where on April 1945 German military troops tried to stop advancing Soviet units was chosen as a model area. By means of KOCOA analysis we will try to predict locations which were considered appropriate for defence. These locations, confronted with LiDAR-derived images, can provide evidence of field fortifications which can be subjected to subsequent scientific research, preservation and protection.

The Bayesian Inferential Paradigm in Archaeology

Archaeologists often use data and quantitative statistical methods to evaluate their ideas. Although there are various statistical frameworks for decision-making in archaeology and science in general, in this chapter, we provide a simple explanation of Bayesian statistics. To contextualize the Bayesian statistical framework, we briefly compare it to the more widespread null hypothesis significance testing (NHST) approach. We also provide a simple example to illustrate how archaeologists use data and the Bayesian framework to compare hypotheses and evaluate their uncertainty. We then review how archaeologists have applied Bayesian statistics to solve research problems related to radiocarbon dating and chronology, lithic, ceramic, zooarchaeological, bioarchaeological, and spatial analyses. Because recent work has reviewed Bayesian applications in archaeology from the 1990s up to 2017, this work considers the relevant literature published since 2017.