Γ.-Φοίβος Σαργέντης. Γλυπτική. Επιλεγμένα έργα

<p>Στόχος αυτού του καταλόγου είναι η αρχειοθέτηση και παρουσίαση γλυπτών, μικρογλυπτών και κοσμημάτων που έχω δημιουργήσει και κατασκευάσει και η χρονολογική τους ταξινόμηση.  <br>  <br> Η ταξινόμηση αυτή έγινε σε χρονικές περιόδους που ένιωθα ότι υπήρχε κάποια εννοιολογική ομοιομορφία και κάποιο κοινό (ενδεχομένως ασαφές) στοιχείο στην έμπνευση των έργων.   <br>  <br> Σημειώνεται ότι πολλά είναι τα έργα που έχουν φύγει από εμένα αλλά δεν έχουν φωτογραφηθεί. Έτσι, παρ’ όλο που από σχετικά νωρίς προσπάθησα να αρχειοθετήσω και να ταξινομήσω χρονολογικά τα έργα μου, δεν έχω την ελπίδα πως ο κατάλογος αυτός θα είναιποτέ πλήρης γιατί είναι βέβαιο ότι κάποια έργα θα λείπουν.  <br>  <br> Ελπίζω όμως, ότι ο κατάλογος αυτός θα είναι μια δυναμική έκδοση που θα συμπληρώνεται με την πάροδο του χρόνου.  <br>  </p&gt

Entropy and Wealth

While entropy was introduced in the second half of the 19th century in the international vocabulary as a scientific term, in the 20th century it became common in colloquial use. Popular imagination has loaded “entropy” with almost every negative quality in the universe, in life and in society, with a dominant meaning of disorder and disorganization. Exploring the history of the term and many different approaches to it, we show that entropy has a universal stochastic definition, which is not disorder. Hence, we contend that entropy should be used as a mathematical (stochastic) concept as rigorously as possible, free of metaphoric meanings. The accompanying principle of maximum entropy, which lies behind the Second Law, gives explanatory and inferential power to the concept, and promotes entropy as the mother of creativity and evolution. As the social sciences are often contaminated by subjectivity and ideological influences, we try to explore whether maximum entropy, applied to the distribution of a wealth-related variable, namely annual income, can give an objective description. Using publicly available income data, we show that income distribution is consistent with the principle of maximum entropy. The increase in entropy is associated to increases in society’s wealth, yet a standardized form of entropy can be used to quantify inequality. Historically, technology has played a major role in the development of and increase in the entropy of income. Such findings are contrary to the theory of ecological economics and other theories that use the term entropy in a Malthusian perspective

A Stochastic View of Varying Styles in Art Paintings

A physical process is characterized as complex when it is difficult to analyze and explain in a simple way, and even more difficult to predict. The complexity within an art painting is expected to be high, possibly comparable to that of nature. Herein, we apply a 2D stochastic methodology to images of both portrait photography and artistic portraits, the latter belonging to different genres of art, with the aim to better understand their variability in quantitative terms. To quantify the dependence structure and variability, we estimate the Hurst parameter, which is a common dependence metric for hydrometeorological processes. We also seek connections between the identified stochastic patterns and the desideratum that each art movement aimed to express. Results show remarkable stochastic similarities between portrait paintings, linked to philosophical, cultural and theological characteristics of each period

The role of technology in the water–energy–food nexus. A case study: Kerinthos, North Euboea, Greece

The water–energy–food (WEF) nexus is a basic element of prosperity, yet it is not equally distributed on the land. Human progress has optimized the function of the WEF nexus to bridge the inequality gap. In order to understand this progress, this study compares the preindustrial and modern agricultural practices in an area in Greece. Interviews were conducted with an elderly man who lived in the 1950s, and the process was quantified in units of WEF. The same procedure was also carried out with modern farmers for modern agricultural practices. In comparing the past and present agricultural processes, it is observed that today, a farmer can feed approximately 100 times more people. This feat has been achieved as modern practices push the land with energy sources in multiple ways (fuels and fertilizers). However, energy indices such as energy ratio, net energy gain, specific energy, and energy productivity do not seem to be improved. Furthermore, farmers prefer to pump underground water for irrigation, instead of utilizing the nearby river, as was done in the past when the river provided both energy to the watermill and an abundance of water for irrigation. In addition, as the price of wheat is dependent on the stock market, even in 2023, there are risks to food security, the cultivation of wheat was not economically efficient for farmers in this area in 2023

Spatial Hurst–Kolmogorov Clustering

The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is introduced as a robust means to identify, model and simulate the Hurst–Kolmogorov (HK) dynamics, ranging from small (fractal) to large scales exhibiting the clustering behavior (else known as the Hurst phenomenon or long-range dependence). The HK clustering is an attribute of a multidimensional (1D, 2D, etc.) spatio-temporal stationary stochastic process with an arbitrary marginal distribution function, and a fractal behavior on small spatio-temporal scales of the dependence structure and a power-type on large scales, yielding a high probability of low- or high-magnitude events to group together in space and time. This behavior is preferably analyzed through the second-order statistics, and in the scale domain, by the stochastic metric of the climacogram, i.e., the variance of the averaged spatio-temporal process vs. spatio-temporal scale

A Stochastic View of Varying Styles in Art Paintings

A physical process is characterized as complex when it is difficult to analyze and explain in a simple way, and even more difficult to predict. The complexity within an art painting is expected to be high, possibly comparable to that of nature. Herein, we apply a 2D stochastic methodology to images of both portrait photography and artistic portraits, the latter belonging to different genres of art, with the aim to better understand their variability in quantitative terms. To quantify the dependence structure and variability, we estimate the Hurst parameter, which is a common dependence metric for hydrometeorological processes. We also seek connections between the identified stochastic patterns and the desideratum that each art movement aimed to express. Results show remarkable stochastic similarities between portrait paintings, linked to philosophical, cultural and theological characteristics of each period

Values and Costs in History: A Case Study on Estimating the Cost of Hadrianic Aqueduct’s Construction

The pursuit of wealth has been a basic occupation of humans; as it turns out, wealth increases life expectancy. Analyzing global data, we show that money, probably connected with medical care, increase life expectancy. However, the base of real wealth is access to the Water–Energy–Food nexus, and the access to this also increases life expectancy. The first objective of this study was to compare the present values of wealth with antiquity, and we showed that about 1.4 billion people live in the present under the average lower wages of antiquity. As a case study, we analyze the construction of the Hadrianic aqueduct. We present a detailed description of the construction and the used methods, and we identify the total requirement of labor–time. Then, we investigate the wages of various occupations in the first century AD. The second objective of this study was the estimation of the total cost of daily wages for the construction of the project and the effect of the aqueduct on Athenians’ quality of life. Finally, we show that, today, about two billion people live with less available water than Athenians had with the Hadrianic aqueduct in the second century A.D

Spatial Hurst–Kolmogorov Clustering

The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is introduced as a robust means to identify, model and simulate the Hurst–Kolmogorov (HK) dynamics, ranging from small (fractal) to large scales exhibiting the clustering behavior (else known as the Hurst phenomenon or long-range dependence). The HK clustering is an attribute of a multidimensional (1D, 2D, etc.) spatio-temporal stationary stochastic process with an arbitrary marginal distribution function, and a fractal behavior on small spatio-temporal scales of the dependence structure and a power-type on large scales, yielding a high probability of low- or high-magnitude events to group together in space and time. This behavior is preferably analyzed through the second-order statistics, and in the scale domain, by the stochastic metric of the climacogram, i.e., the variance of the averaged spatio-temporal process vs. spatio-temporal scale

Landscape Planning of Infrastructure through Focus Points’ Clustering Analysis. Case Study: Plastiras Artificial Lake (Greece)

Even though landscape quality is largely a subjective issue, the integration of infrastructure into landscapes has been identified as a key element of sustainability. In a spatial planning context, the landscape impacts that are generated by infrastructures are commonly quantified through visibility analysis. In this study, we develop a new method of visibility analysis and apply it in a case study of a reservoir (Plastiras dam in Greece). The methodology combines common visibility analysis with a stochastic tool for visual-impacts evaluation; points that generate high visual contrasts in landscapes are considered Focus Points (FPs) and their clustering in landscapes is analyzed trying to answer two questions: (1) How does the clustering of Focus Points (FPs) impact the aesthetic value of the landscape? (2) How can the visual impacts of these FPs be evaluated? Visual clustering is calculated utilizing a stochastic analysis of generated Zones of Theoretical Visibility. Based on the results, we argue that if the visual effect of groups of FPs is positive, then the optimal sitting of FPs should be in the direction of faint clustering, whereas if the effect is negative, the optimal sitting of FPs should be directed to intense clustering. In order to optimize the landscape integration of infrastructure, this method could be a useful analytical tool for environmental impact assessment or a monitoring tool for a project’s managing authorities. This is demonstrated through the case study of Plastiras’ reservoir, where the clustering of positively perceived FPs is found to be an overlooked attribute of its perception as a highly sustainable infrastructure project

Evolution of Clustering Quantified by a Stochastic Method—Case Studies on Natural and Human Social Structures

Clustering structures appearing from small to large scales are ubiquitous in the physical world. Interestingly, clustering structures are omnipresent in human history too, ranging from the mere organization of life in societies (e.g., urbanization) to the development of large-scale infrastructure and policies for meeting organizational needs. Indeed, in its struggle for survival and progress, mankind has perpetually sought the benefits of unions. At the same time, it is acknowledged that as the scale of the projects grows, the cost of the delivered products is reduced while their quantities are maximized. Thus, large-scale infrastructures and policies are considered advantageous and are constantly being pursued at even great scales. This work develops a general method to quantify the temporal evolution of clustering, using a stochastic computational tool called 2D-C, which is applicable for the study of both natural and human social spatial structures. As case studies, the evolution of the structure of the universe, of ecosystems and of human clustering structures such as urbanization, are investigated using novel sources of spatial information. Results suggest the clear existence both of periods of clustering and declustering in the natural world and in the human social structures; yet clustering is the general trend. In view of the ongoing COVID-19 pandemic, societal challenges arising from large-scale clustering structures are discussed