Miracle-dz/UniFAR-FTUs huggingface dataset:
Corporate governance structure and bank performance: evidence from an emerging economy

PurposeThe purpose of the paper is to explore the association between corporate governance mechanisms and the performance of listed banks in Bangladesh.Design/methodology/approachDynamic panel data of two-step System Generalized Method of Moments (SGMM) estimators are used to analyze the influence of corporate governance characteristics on the performance of banks operating in Bangladesh over a period of eleven years from 2008 to 2018.FindingsBy employing the two-step SGMM, the authors find statistical evidence to conclude that board size has a positive impact on banks' accounting performance. However, it does not influence the market performance of banks operating in Bangladesh. The authors’ results also suggest that outside independent directors, managerial ownership and females' participation on the board are not linked with the performance of the listed banks in Bangladesh. It signifies that the mere presence of outside directors and female directors in the board does not guarantee the enhancement of banks' performance and the minimization of agency conflict between shareholders and management. The persistent characteristic of bank performance is one of the crucial findings of this paper.Research limitations/implicationsThis research has some limitations as the study's findings may not be generalized to other countries or industries because the current study considered only the small sample size based on the availability of the data and focused only on the banks listed in the DSE. Moreover, this study may not represent the whole financial industry because it includes all listed and non-listed banks and non-bank financial institutions. Hence, the findings may not be applicable to the other industries operating in different business ecosystems.Practical implicationsThe findings of this analysis have some managerial implications. This study provides managers empirical evidence regarding the influence of corporate governance elements on banks' performance, and they can now identify the factors that should emphasize enhancing the bank performance. The findings demonstrate that policymakers, regulatory bodies and bank management should pay more attention to the banks' overall corporate governance structures, especially in the case of appointing independent and female directors to challenge the executive power and to prevent the repetition of financial irregularities and loan scams in the banking industry of Bangladesh. Furthermore, the regulatory authorities should ensure the banks follow the corporate governance guidelines precisely for building a resilient banking industry to attain sustainable development goals in the long run.Originality/valueThis paper is the first empirical in-depth analysis applying the most recent data that examines the effect of bank governance elements on the performance of all the banks listed in the Dhaka Stock Exchange to the best of our knowledge.
Development versus Adaptation? Facing Climate Change in Ca Mau, Vietnam

Climate change poses a dire threat to the Mekong River Delta, an important supplier of shrimp and rice to global markets. The southernmost province, Ca Mau, is threatened by sea level rise and land subsidence. Little is known of the expected combined impact of these processes, or of the perceptions of farmers towards these threats. This study first projected the combined effects using the most accurate extant elevation data. Next, to assess perceptions, we interviewed 53 farmers from six communes within the province. We found that 43% of the province could be at risk of submersion by 2030, and 75% by 2050. The interviews revealed that the farmers were largely unaware of the imminence of submersion and did not fully comprehend the nature and magnitude of the underlying processes. Constrained by the requirements of their developmental trajectory, they were focused on short term threats to their livelihood (weather, salinization, pollution). Consequently, far from adapting to the larger threats, they are engaged in practices, such as groundwater extraction for aquaculture, that are hastening the demise of the region. Their plight offers warnings to similar regions around the world. We hope that our findings can inform the development of future outreach programs.
A Systematic Literature Review on Pricing Strategies in the Sharing Economy

As an emerging business model, the sharing economy has gained a large amount of academic attention; the pricing problem in the sharing economy has also been widely investigated. Aiming to capture the current state-of-the-art research on pricing strategies in the sharing economy and foreseeing directions for future research, this article conducts a systematic literature review and content analysis of 158 articles from the Scopus and Web of Science databases. As a result, first, this review proposes an extended definition covering B2C and C2C models and a model structure covering the entire supply chain, based on which 158 articles are categorized into nine sub-models covering 30 scenarios. Second, the general characteristics (i.e., research fields, time and journal distributions, research themes and scenarios) and technical details (i.e., theories, methodologies, approaches, models, and conclusions) of the 158 articles are reviewed and summarized by the pricing party, business mode, and scenario. Finally, this review proposes some future research directions of existing scenarios from the perspectives of information asymmetry, market competition, and empirical approaches, and discusses some extensions, including uninvestigated scenarios and COVID-19-related topics; correspondingly, this review suggests some analytical models and empirical approaches that can be employed to fill these gaps. The proposed research directions and corresponding approaches can be references for future research.
Güvenlik Sistemleri için Silah ve Bıçak Tanıma

yerelleştirir. Evrişimsel Sinir tabanlı nesne algılama ile bağlantılı olarak, en yüksek performansa sahip silah ve bıçak nesnelerini tespit etmek için Hızlı - Bölgesel Tabanlı Evrişimsel Sinir Ağı yapısı uygulanmıştır. Test görüntüleri üzerinde simülasyon gerçekleştirdikten sonra, geliştirilen sistemin F1 - skor performansı yaklaşık %70 tanıma oranı olarak elde edilmiştir. Eğitilen Faster R- CNN modeli, uçak, otobüs durağı, stadyum ve güvenliğin önemli bir faktör olduğu kamu taşıtları da dâhil olmak üzere farklı halka yerler için kullanılabilir. Ayrıca, geliştirilen yöntem, tehlikeli nesnelerin raporlanması ve bu tür nesnelerin neden olduğu risklerin en aza indirilmesi açısından yerel gözetim sistemine gömülebilir. Abstract This study presents an effective and innovative solution to overcome the security issues/problems in public places. As an alternative video surveillance system, the proposed method detects and localizes gun and knife objects from videos in real-time. In connection with Convolutional Neural Network (CNN) based object detection, the Faster R-CNN structure was applied to detect gun and knife objects with the highest performance. After conducting a simulation on test images, we have found that the F1-score performance of the developed system is about 70% recognition rates. The trained Faster R-CNN model can be utilized for different public places, including airplanes, bus stations, stadiums, and public vehicles, where the security is an important factor. Moreover, the developed method can be embedded in the local surveillance system in terms of reporting dangerous objects as well as minimizing the risks caused by such objects.
The use of infrared thermography in endurance athletes: a systematic review

Infrared thermography (IRT) has become increasingly common in sports assessment and has grown a lot over the past few years. Our objective was to identify the assessment protocols and the skin temperature behavior of practitioners of endurance sports. A systematic review was carried out following the PRISMA recommendations between the 1st and the 31st of March 2020, at MEDLINE, LILACS, SCOPUS, SPORT Discus, CINAHL, Web of Science, Science Direct, Cochrane, and Scielo, using combinations with 11 descriptors for “Thermography” and 6 descriptors for “Endurance training”. It was identified 24 different regions of interest (ROIs) evaluated region in endurance sports. The acclimatization time was respected in 75% of the selected studies, and the thermal images were acquired predominantly in three moments: before the test, immediately after the test, and 10 minutes after the test. It was observed that Tskin decreased in the initial moments and increased after exercise. It can be concluded that the ROIs used were mostly the specific muscle recruited in each modality, with emphasis on the muscle groups of the lower limbs, and after this initial decrease in temperature, the thermal response is mainly dependent on the duration and intensity of exercise. Keywords: endurance training, thermography, cycling, running.
Using evolutionary functional–structural plant modelling to understand the effect of climate change on plant communities

The ‘holy grail’ of trait-based ecology is to predict the fitness of a species in a particular environment based on its functional traits, which has become all the more relevant in the light of global change. However, current ecological models are ill-equipped for this job: they rely on statistical methods and current observations rather than the mechanisms that determine how functional traits interact with the environment to determine plant fitness, meaning that they are unable to predict ecological responses to novel conditions. Here, I advocate the use of a 3D mechanistic modelling approach called functional–structural plant (FSP) modelling in combination with evolutionary modelling to explore climate change responses in natural plant communities. Gaining a mechanistic understanding of how trait–environment interactions drive natural selection in novel environments requires consideration of individual plants with multidimensional phenotypes in dynamic environments that include abiotic gradients and biotic interactions, and their combined effect on the different vital rates that determine plant fitness. Evolutionary FSP modelling explicitly simulates the trait–environment interactions that drive eco-evolutionary dynamics from individual to community scales and allows for efficient navigation of the large, complex and dynamic fitness landscapes that emerge from considering multidimensional plants in multidimensional environments. Using evolutionary FSP modelling as a tool to study climate change responses of plant communities can further our understanding of the mechanistic basis of these responses, and in particular, the role of local adaptation, phenotypic plasticity and gene flow.
O Ensino Remoto Emergencial nos Cursos Presenciais: Uma Experiência das Instituições Privadas de Ensino Superior no Rio De Janeiro

Resumo A proposta deste estudo e de discutir como as Instituicoes de Ensino Superior privadas (IES) utilizaram o ensino remoto emergencial como solucao a quarentena imposta pela pandemia proporcionada pela COVID-19. Esta foi a alternativa encontrada para evitar a interrupcao do calendario academico, com a continuidade de aulas ao vivo ministradas em diferentes plataformas de videoconferencias. Para isto, foi realizada uma pesquisa qualitativa por meio de entrevistas realizadas com coordenadores de cursos presenciais no Estado do Rio de Janeiro. As informacoes coletadas foram organizadas com o auxilio do programa Atlas TI, que auxiliou posteriormente a analise de conteudo. Os resultados apontam que a implementacao foi exitosa em virtude do gerenciamento dos seus recursos intangiveis. Destacam-se: a resiliencia do corpo docente, a padronizacao de processos, o uso de plataformas digitais, a alianca estrategica com empresas de tecnologia e a capacidade de negociacao das IES com seu corpo discente. Palavras-Chave : Gestao Universitaria. Ensino Remoto Emergencial. Tomada de Decisao em IES. ABSTRACT The study proposal is to discuss how Private Higher Education Institutions (IES) used emergency remote teaching as a solution to the quarantine imposed by the pandemic provided by COVID-19. This was the alternative found to avoid interrupting the academic calendar, with the continuity of live classes taught on different videoconference platforms. For this, a qualitative research was carried out through an attribution carried out with coordinators of on-site courses in the State of Rio de Janeiro. The information collected was organized with the help of the Atlas TI program, which subsequently assisted in the content analysis. The results show that the implementation was successful due to the management of intangible resources. The highlights are: the resilience of the faculty, the standardization of processes, the use of digital platforms, a strategic alliance with technology companies and the ability of HEIs to negotiate with their students. Keywords : University Management. Emergency Remote Learning. Decision Making in IES.
Efeito de diferentes períodos de cultivo na micropropagação de brotações de Luehea divaricata

O objetivo do presente trabalho foi avaliar o efeito do período de cultivo na micropropagação de brotações de Luehea divaricata. Os tratamentos foram compostos pelos períodos de cultivo in vitro: 14; 21; 28; 40; 56; 70; 84; 102; 116; 130; 154, 186 ou 200 dias, sem realizar subcultivo ou transferência para outro meio nutritivo fresco. A sobrevivência e o estabelecimento ficaram em torno de 90% até 84 dias de cultivo. A partir deste período, a mortalidade foi mais acentuada. Para as variáveis número total de folhas e folhas com senescência, o período de cultivo de 56 dias foi o que mostrou uma proporção mais adequada, em que para cada nove folhas formadas apenas uma estava senescente. Em relação à formação de raízes primárias, médias superiores a 50% foram observadas após 70 dias de cultivo in vitro, chegando aos melhores resultados (60%) aos 200 dias. Para raízes secundárias, as maiores médias foram observadas após 102 dias (41,5%), alcançando 45,3% aos 200 dias. A micropropagação de Luehea divaricata é afetada significativamente pelo período de cultivo in vitro, que pode ser estendido até aproximadamente 60 dias. A partir desse período, são registradas altas mortalidades.
Robust practical tracking control of an underactuated hovercraft

This paper studies the robust practical tracking control problem of an underactuated hovercraft with unknown external disturbances. Controlling such a system is difficult and challenging due to inherent modeling properties such as underactuated nature and nonholonomic constraint. State transformation technique and cascade method, combined with a transverse function, are used to develop a novel control law that globally practically stabilizes the hovercraft to any smooth reference trajectory, either feasible or non‐feasible. The Lyapunov theory is applied to the analysis of overall closed‐loop stability. Simulation results illustrate the control design.
Learning to Classify the Consumer Confidence Indicator (in Portugal)

The literature paid some attention, some time ago, to the relationship that, supposedly, should exist between the level of consumer confidence and the unemployment rate. This relationship is interesting, both from a scientific point of view, given the inherently subjective character of that level of confidence, but also from the point of view of economic policy, given the importance of the unemployment rate. In this article, that relationship is revisited, using learning models, namely regression and classification trees. Using, for example, the case of Portugal, the unemployment rate presents itself as an adequate classifier of the consumer confidence level. The use of classification trees shows that the separation between low and high values of the consumer confidence indicator is made from an adequate threshold value of the unemployment rate. The use of regression trees shows that the levels of consumer confidence are inversely related to the levels of the unemployment rate. In terms of policy lessons, this confirms that, in the face of economic crises, such as the one we are experiencing, in which confidence levels tend to fall and the unemployment rate increases, the relationship between these two variables cannot be ignored.
Earth's Albedo 1998–2017 as Measured From Earthshine

The reflectance of the Earth is a fundamental climate parameter that we measured from Big Bear Solar Observatory between 1998 and 2017 by observing the earthshine using modern photometric techniques to precisely determine daily, monthly, seasonal, yearly and decadal changes in terrestrial albedo from earthshine. We find the inter‐annual fluctuations in albedo to be global, while the large variations in albedo within individual nights and seasonal wanderings tend to average out over each year. We measure a gradual, but climatologically significant ∼ 0.5 W/m2 decline in the global albedo over the two decades of data. We found no correlation between the changes in the terrestrial albedo and measures of solar activity. The inter‐annual pattern of earthshine fluctuations are in good agreement with those measured by CERES (data began in 2001) even though the satellite observations are sensitive to retroflected light while earthshine is sensitive to wide‐angle reflectivity. The CERES decline is about twice that of earthshine.
Predicting Bond Strength of Steel Reinforcement in Self-Compacting Concrete (SCC) Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

The advantages of using self-compacting concrete (SCC) are reducing the time of construction and the number of employments, reducing noise that can disturb the surrounding environment, and increasing the density of hardened concrete structural elements, automatically affecting bond strength reinforcement in SCC. The bond strength is a parameter as an essential factor affecting the behavior of reinforced concrete. In this manuscript, the Adaptive Neuro-Fuzzy Inference System (ANFIS) model was built to predict the bond strength in SCC. For showing the performance of the ANFIS model, the level of accuracy-based correlation coefficient (R2) and Root Mean Square Error (RMSE) were determined. Learning process data consists of input and output. The input in this study includes compressive strength of concrete (f'c), the diameter of steel reinforcement (db), and development of length (Ld), while the output bond strength ( ). The results of the proposed model were in good agreement with the experimental results, as evidenced by an R2 of 0.71 and an RMSE of 3.31 MPa in the testing data, indicating that the proposed ANFIS model is capable of accurately predicting steel reinforcement bond strength in SCC.
No. 44, The Mysterious Stranger: Mark Twain’s critique of progressive era meritocracy

ABSTRACT This paper argues that Mark Twain’s under-studied final work No. 44, The Mysterious Stranger – left incomplete upon his death – is an exploration of the author’s engagement with the question of the relationship between individual intelligence, brain science, and the emerging, Progressive Era discourse of ‘merit’. I show how Twain’s novel critiques ‘merit’ and the political structures of ‘meritocracy’ by presenting the reader with two characters who are in fact the same person (August and Forty-Four) to expose different facets of the meritocratic personality. These facets (a belief in innate ability and a commitment to impressibility and growth) might seem contradictory, but Twain’s novel demonstrates how in a moment of advanced capitalism and industrialism that predicts our own both are deployed consciously by the meritocrat in the transfer of power from the collective to the bourgeois individual. With No. 44, The Mysterious Stranger, Twain refines his vision of American social values into a critique of the Enlightenment more broadly, abandoning his earlier reformist impulses to imagine more radical challenges to American power.
Causes, Consequences, and Conservation of Ungulate Migration

Our understanding of ungulate migration is advancing rapidly due to innovations in modern animal tracking. Herein, we review and synthesize nearly seven decades of work on migration and other long-distance movements of wild ungulates. Although it has long been appreciated that ungulates migrate to enhance access to forage, recent contributions demonstrate that their movements are fine tuned to dynamic landscapes where forage, snow, and drought change seasonally. Researchers are beginning to understand how ungulates navigate migrations, with the emerging view that animals blend gradient tracking with spatial memory, some of which is socially learned. Although migration often promotes abundant populations—with broad effects on ecosystems—many migrations around the world have been lost or are currently threatened by habitat fragmentation, climate change, and barriers to movement. Fortunately, new efforts that use empirical tracking data to map migrations in detail are facilitating effective conservation measures to maintain ungulate migration. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 52 is November 2021. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Joy Thomas: Legacy, Foundation and the IT Society

In this article, we commemorate Joy Thomas, who sadly passed away in 2020. Joy is best known for his seminal textbook Elements of Information Theory, coauthored with his Ph.D. advisor the late Thomas Cover. We also catalog some of Joy’s technical contributions to information theory and to its practice. Joy also made an impact on industry through several successful startups. In recognition of Joy’s contribution to the exposition of information theory, the IEEE Information Theory Society Board of Governors has agreed to establish the Joy Thomas IEEE Information Theory Society Tutorial Paper Award. The Joy Thomas Foundation, established to honor Joy’s legacy of excellence and giving back, will sponsor this award.
Enfermedad del hígado graso asociada con la disfunción metabólica. Una nueva propuesta para una dolencia en auge

La enfermedad por hígado graso no alcohólica se caracteriza por la acumulación de grasa hepática que excede el 5 % de su peso. El espectro de esta condición incluye la esteatosis hepática, esteatohepatitis y fibrosis progresiva con cirrosis. Además, existe la posibilidad de desarrollar hepatocarcinoma sin el antecedente de cirrosis. Su fisiopatología se basa actualmente en el componente metabólico y se considera como la manifestación hepática de una disfunción metabólica sistémica.
A Generic Pipeline for Machine Learning Users in Energy and Buildings Domain

One of the biggest problems in applying machine learning (ML) in the energy and buildings field is the lack of experience of ML users in implementing each ML algorithm in real-life applications the right way, because each algorithm has prerequisites to be used and specific problems or applications to be implemented. Hence, this paper introduces a generic pipeline to the ML users in the specified field to guide them to select the best-fitting algorithm based on their particular applications and to help them to implement the selected algorithm correctly to achieve the best performance. The introduced pipeline is built on (1) reviewing the most popular trails to put ML pipelines for the energy and building, with a declaration for each trial drawbacks to avoid it in the proposed pipeline; (2) reviewing the most popular ML algorithms in the energy and buildings field and linking them with possible applications in the energy and buildings field in one layout; (3) a full description of the proposed pipeline by explaining the way of implementing it and its environmental impacts in improving energy management systems for different countries; and (4) implementing the pipeline on real data (CBECS) to prove its applicability.