The proliferation of digital literary discourse has led to a competitive, and often times antagonistic, relationship between this new form and its traditional paper-based counterpart. The success of this new critical literary media has come as a result of major global changes to social consciousness and societal pressures to utilize communication systems that can keep pace with the speed of social action. Discussions on the legitimacy of digital literary discourse are often limited by the use of conciliatory debates that merely present moderate viewpoints. This research addresses the issue using a socio-discursive lens, focusing on a critical exploration of the underlying reasoning for the technological wariness of paper-based literary practitioners. Contrary to the views of many traditionalists, digital literature does not derive its discursive identity, nor its legitimacy, from a combative relationship with paper-based criticism. Instead, this analysis indicates that the use of digital media marks a significant turning point in the institution of literary discourse, formed as a response to shifting individual and collective needs of an accelerating pace of life. Therefore, digital literary discourse is not simply a form or idea that can be accepted or rejected. Rather, it is a forced formation of a new and constantly evolving expressive and inferential space, created by the combination of existing and innovative media, producing new meanings that were impossible to generate under the dominance of old media.
This research aims to solve the research problems regarding the most important value of an object in the form of the wedangan phenomenon. This research objectives to expose the superiority of the communities’ food consumption tradition in the form of wedangan. This research belongs to a qualitative study and uses ethnomethodology as an initial approach. It is because the initial data findings are in the form of an indexical conversation that explicitly refers to the concept of wedangan. The concept refers to wedangan in real life, which is in the form of eating and drinking activities while chatting. The research findings are: 1) the most profound structure of wedangan’s tradition is food provision and food eating; 2) wedangan accommodates three forms (food stall, street food, and restaurant); 3) wedangan also accommodates three food values (delightful, useful, and meritorious); and 4) there is an egalitarian consumption pattern in wedangan, people regardless their social class visiting the same place, eat the same food, being simple and be ordinary (or usually we call it as food marriage). Wedangan is a social activity with advantages from a social, economic, and political perspective. Therefore, this phenomenon requires more serious attention from the government.
The Consumer Price Index (CPI) is a vital gauge of economic performance, reflecting fluctuations in the costs of goods, services, and other commodities essential to consumers. It is a cornerstone measure used to evaluate inflationary trends within an economy. In Saudi Arabia, forecasting the Consumer Price Index (CPI) relies on analyzing CPI data from 2013 to 2020, structured as an annual time series. Through rigorous analysis, the SARMA (0,1,0) (12,0,12) model emerges as the most suitable approach for estimating this dataset. Notably, this model stands out for its ability to accurately capture seasonal variations and autocorrelation patterns inherent in the CPI data. An advantageous feature of the chosen SARMA model is its self-sufficiency, eliminating the need for supplementary models to address outliers or disruptions in the data. Moreover, the residuals produced by the model adhere closely to the fundamental assumptions of least squares principles, underscoring the precision of the estimation process. The fitted SARMA model demonstrates stability, exhibiting minimal deviations from expected trends. This stability enhances its utility in estimating the average prices of goods and services, thus providing valuable insights for policymakers and stakeholders. Utilizing the SARMA (0,1,0) (12,0,12) model enables the projection of future values of the Consumer Price Index (CPI) in Saudi Arabia for the period from June 2020 to June 2021. The model forecasts a consistent upward trajectory in monthly CPI values, reflecting ongoing economic inflationary pressures. In summary, the findings underscore the efficacy of the SARMA model in predicting CPI trends in Saudi Arabia. This model is a valuable tool for policymakers, enabling informed decision-making in response to evolving economic dynamics and facilitating effective policies to address inflationary challenges.
Coordination and integration among farms within agri-food chains are crucial to tackle the issue of fragmentation within the primary sector, both at the European and national level. The Italian agri-food system still complains about the need to aggregate supply to support market dynamics, especially for niche and quality products that characterize the Made in Italy. It is well known that the Italian agri-food sector is closely linked to the relationship between agriculture on one hand and culture/tradition on the other, which is reflected in the high number of quality products that have obtained EU PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) recognition. The development of vertical forms of coordination has found significant support in recent years from the integrated supply chain design approach, which is increasingly becoming an essential tool for implementing rural development policies. In this context, the study provides a comparison between companies that have joined the Integrated Supply Chain Projects of the Rural Development Program and those that have not applied. The aim is to highlight any differences in order to understand policy impact. The analysis is based on the Emilia-Romagna region Farm Accountancy Data Network (FADN) data, and the sample consists of more than 2 thousand farms. The statistical analysis conducted compares treated and non-treated using the Welch-t-test for independent unmatched samples. The main results show higher values for treated farms when structural variables are analyzed, like the utilized agricultural area or the agricultural work unit. In general, higher balance sheet performances emerged for treated farms. In conclusion, this study shows that the Integrated Supply Chain Projects represent a worthwhile tool both to increase cooperation, food quality, and to enhance a competitive agricultural sector.
This article describes a classification tool to cluster SARAL/AltiKa waveforms. The tool was made using Python scripts. Radar altimetry systems (e.g., SARAL/AltiKa) measures the distance from the satellite centre to a target surface by calculating the satellite-to-surface round-trip time of a radar pulse. An altimeter waveform represents the energy reflected by the earth’s surface to the satellite antenna with respect to time. The tool clusters the altimetric waveforms data into desired groups. For the clustering, we used evolutionary minimize indexing function (EMIF) with k-means cluster mechanism. The idea was to develop a simple interface which takes the altimetry waveforms data from a folder as inputs and provides single value (using EMIF algorithm) for each waveform. These values are further used for clustering. This is a simple light weighted tool and user can easily interact with it.
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