Exploring Social Media Data to Understand How Stakeholders Value Local Food: A Canadian Study Using Twitter

The consumption of local food, a major trend in industrialized countries around the world has experienced an unprecedented craze in the pandemic context that we are experiencing. Since the beginning of the crisis and in various media, communication about local food seems inconsistent. However, companies would have every interest in better communicating the multifaceted areas of the locality that customers value or adopting the same language if they wish to collaborate with each other. This research aims to identify and evaluate the “fit” or the “gap” of the different local food’ meanings of Canadian agri-food stakeholders through data mining of one of their communication media: Twitter. Using tweets by over 1300 Twitter accounts from Canadian agri-food companies and a popular hashtag, we analyze a sample of their tweets in 2019 and 2020 by creating and using a local food’ keyword dictionary based on the concept of proximity. Term frequency and multivariate analysis of variance of 16,585 tweets about local food show significant differences in dimensions of proximity used in communications. This study shows the interest of using the concept of proximity to better define and understand the valuation of local food products. In addition, it offers a methodology capable of distinguishing the nuances of meaning of the locality of products using natural data that is accessible via social media.

A Study of Grammatical Case Forms and their Directionality in Fulfulde: The Transformational Generative Approach

Case Theory interacts with Government Theory in its operation and so, cases are assigned to the complements of governors. Case assigners are the governors of their dependent clauses while the case receivers are the governed NPs. So, the purpose of the study is to survey case assignment in Fulfulde generally by identifying and analysing the elements of Fulfulde structures and their relationship in terms of structural case. Unstructured observation was the method used for eliciting data for this study. Adequate and natural data were recorded and analysed sentence by sentence, the way they were uttered by the native speakers. The Theoretical Framework adopted for data analysis by this study is Principle and Parameters Theory. The study discovered that in Government, apart from (V)erbs, (P)repositions and tensed INFL, (N)ouns, (A)djectives and Focus Markers FMs can also govern and assign case to their complements in Fulfulde. The study has proved that in Fulfulde, cases can be assigned either to the left or to the right, depending on the relation.

The main drivers for the occurrence of six red-listed epiphytic bryophytes and lichens in the boreo-nemoral forest landscape, Latvia

Forest landscape plays a significant role in rare cryptogam distribution. However, data about the environmental demands of rare epiphytic bryophytes and lichens in boreo-nemoral forest landscapes are not complete. In this study, we focused on finding the main environmental predictors influencing the occurrence of three red-listed epiphytic bryophytes and three red-listed epiphytic lichens in the Latvian boreo-nemoral forest landscape. We obtained the records of species from the Natural Data Management System OZOLS database, which is a national information system on all rare taxa. We analyzed the occurrence of species in relation to forest stand age and area, forest type, heterogeneity and tree bark pH class. We found that selected red-listed bryophyte and lichen occurrence was mainly influenced by forest stand age and area. However, each of the red-listed epiphytic bryophyte and lichen has their own ecological demands in the boreo-nemoral landscape.

Global trends in novel stable isotopes in basalts: theory and observations

The geochemistry of global mantle melts suggests that both mid-ocean ridge basalts (MORB) and ocean island basalts (OIB) sample lithological and temperature heterogeneities originating in both the upper and lower mantle. Recently, non-traditional stable isotopes have been suggested as a new tool to complement existing tracers of mantle heterogeneity (e.g., major and trace elements, radiogenic isotopes), because mineral- and redox-specific equilibrium stable isotope fractionation effects can link the stable isotope ratios of melts to their source mineralogy and melting degree. Here, we investigate five stable isotope systems (Mg-Ca-Fe-V-Cr) that have shown promise in models or natural samples as tracers of mantle temperature and/or lithological heterogeneity. We use a quantitative model, combining thermodynamically self-consistent mantle melting and equilibrium isotope fractionation models, to explore the behaviour of the isotope ratios of these elements during melting of three mantle lithologies (peridotite, and silica-excess and silica-deficient pyroxenites), responding to changes in mantle mineralogy, oxygen fugacity, temperature and pressure.We find that, given current analytical precision, the stable isotope systems examined here are not predicted to be sensitive to mantle potential temperature variations through equilibrium isotope fractionation processes. By contrast, source lithological heterogeneity is predicted to be detectable in some cases in the stable isotope ratios of erupted basalts, although generally only at proportions of > 10% MORB-like pyroxenite in the mantle source, given current analytical precision. Magnesium and Ca stable isotopes show most sensitivity to a garnet-bearing source lithology, and Fe and Cr stable isotopes are potentially sensitive to the presence of MORB-like pyroxenite in the mantle source, although the behaviour of Cr isotopes is comparatively under-constrained and requires further work to be applied with confidence to mantle melts. When comparing the magnitude and direction of predicted equilibrium isotopic fractionation of peridotite and pyroxenite melts to natural MORB and OIB data, we find that aspects of the natural data (including the mean Mg-Ca-Fe-V isotopic composition of MORB, the range of Mg-Ca isotopic compositions seen in MORB data, the mean Mg-Ca-Cr isotopic composition of OIB, and the range of Mg-V-Cr isotopic compositions in OIB data) can be matched by equilibrium isotope fractionation during partial melting of peridotite and pyroxenite sources -- with pyroxenite required even for some MORB data. However, even when considering analytical uncertainty on natural sample measurements, the range in stable isotope compositions seen across the global MORB and OIB datasets suggests that kinetic isotope fractionation, or processes modifying the isotopic composition of recycled crustal material such that it is distinct from MORB, may be required to explain all the natural data. We conclude that the five stable isotope systems considered here have potential to be powerful complementary tracers to other geochemical tracers of the source lithology of erupted basalts. However, continued improvements in analytical precision in conjunction with experimental and theoretical predictions of isotopic fractionation between mantle minerals and melts are required before these novel stable isotopes can be unambiguously used to understand source heterogeneity in erupted basalts.

Geographical Analysis of Natural Tourism Potentials in Al-Rutba District/Al-Anbar Governorate

The climate, with its multiple elements, is one of the most important pillars and requirements of the natural tourism industry, as it provides an atmosphere that contributes to strengthening the attraction factors as it determines the general frameworks that draw the type of tourism activity, and since the natural data in the study area are varied and multimodal, I have taken to attracting the tourist activity in an innate, primary way in tourism. Fishing and ecological and natural tourism based on a human and natural compound, if the potential of this industry is available and puts it in a state of geographical integration.

Natural data resources of Polish scientific institutions - variety, history, importance - introduction

Introduction

PEMEROLEHAN BAHASA PENDERITA TUNA RUNGU DAN TUNA WICARA (KAJIAN PRAGMATIK PADA KOSAKATA DAN FONETIS )

Penelitian tentang Pemerolehan Bahasa Penderita Tuna Rungu dan Tuna Wicara menarik untuk dikaji, terutama kajian pragmatik pada kosakata dan fonetis bahasa. Penelitian ini bertujuan untuk mendeskripsikan bagaimana pemerolehan bahasa dan bentuk pragmatik pada kosakata serta fonetis bahasa penderita tuna rungu dan tuna wicara. Metode yang digunakan dalam penelitian ini menggunakan metode kualitatif dengan pendekatan studi kasus yang berlatar natural. Data penelitian ini berupa catatatan lapangan hasil observasi, hasil wawancara, dan rekaman responden. Hasil temuan dalam penelitian ini pemerolehan bahasa penderita tuna rungu dan tuna wicara dipengaruhi oleh lingkungannya yang menggunakan bahasa ibu (bahasa Sunda). Responden hanya mengalami 1 tahun bersekolah di SD untuk mengenal bahasa keduanya (bahasa Indonesia). Responden mampu menguasai kosakata dan mampu mengucapkan hurup-hurup vokal dengan bunyi ujaran yang jelas, seperti vokal /a/i/u/o, tetapi tidak mengucapkan vokal /e/. Responden juga mengalami kesulitan dalam menyebutkan kosakata dan bunyi ujaran hurup-hurup konsonan . Selain itu, responden dapat mengucapkan dua kosakata dengan jelas jika dituturkan dengan dieja. Untuk berkomunikasi dengan lawan bicara sering menggunakan bahasa isyarat agar lawan bicara memahami apa yang disampaikainya, begitu juga sebaliknya. Penguasaan kosakata bahasa Indonesia didapatkan dari menonton televisi dan responden dapat memahami bahasa yang disampaikan lewat ekspresi yang diperlihatkannya. Secara pragmatik, responden memahami makna kata dengan aspeknya yang lain, memahami kosa kata dan fonetis bahasanya walaupun tidak mampu diucapkan secara jelas. Kesulitan dalam pemerolehen bahasa pada penderita tuna rungu dan tuna wicara dapat diatasi jika dapat dikenali sejak dini dan kepedulian orang tua untuk memperkaya pemerolehan bahasa dan kosakata yang diterima responden .

Coreset Clustering on Small Quantum Computers

Many quantum algorithms for machine learning require access to classical data in superposition. However, for many natural data sets and algorithms, the overhead required to load the data set in superposition can erase any potential quantum speedup over classical algorithms. Recent work by Harrow introduces a new paradigm in hybrid quantum-classical computing to address this issue, relying on coresets to minimize the data loading overhead of quantum algorithms. We investigated using this paradigm to perform k-means clustering on near-term quantum computers, by casting it as a QAOA optimization instance over a small coreset. We used numerical simulations to compare the performance of this approach to classical k-means clustering. We were able to find data sets with which coresets work well relative to random sampling and where QAOA could potentially outperform standard k-means on a coreset. However, finding data sets where both coresets and QAOA work well—which is necessary for a quantum advantage over k-means on the entire data set—appears to be challenging.

Big Data Analytics and Natural Data Design for Enterprise Management

The advancement of Internet of Things (IoT), economic globalization, consumer satisfaction and competitive advancements have stimulated companies to transform significantly. In that regard, competitive rivalry among various firms is being replaced by the existing rivalry among businesses and their various enterprises. In the present competitive environments, enterprise experts are focusing on dealing with Big Data (BD) to reach agile, effective, efficient and integrated enterprises. Therefore, explosive development in volume and several data types in the business have presented the need to establish technological advancements that can quickly and intelligently assess large sets of data. The concept of Data Analytics (DA) is one of the most effective remedies that can assist firms to overcome challenges. DA provides an instrument for retrieving insightful data and patterns in massive volumes of information. In that case, this study explores the usage of DA.

Method of Constructing a Nonlinear Approximating Scheme of a Complex Signal: Application Pattern Recognition

A method for identification of structures of a complex signal and noise suppression based on nonlinear approximating schemes is proposed. When we do not know the probability distribution of a signal, the problem of identifying its structures can be solved by constructing adaptive approximating schemes in an orthonormal basis. The mapping is constructed by applying threshold functions, the parameters of which for noisy data are estimated to minimize the risk. In the absence of a priori information about the useful signal and the presence of a high noise level, the use of the optimal threshold is ineffective. The paper introduces an adaptive threshold, which is assessed on the basis of the posterior risk. Application of the method to natural data has confirmed its effectiveness.