Bangladesh’s recent doorway to the spectacular growth trajectory is largely associated with the shared contributions of globalization, FDI, trade, economic growth, urbanization, energy consumption, ...innovation, and institutional quality that affect its natural environment. Earlier studies hardly incorporated these dynamics together especially innovation and institutional quality to examine their impacts on environmental degradation in Bangladesh. This study attempts to scrutinize the effect of globalization, foreign direct investment, economic growth, trade, innovation, urbanization, and energy consumption on CO
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emissions in the presence of institutional quality in Bangladesh over the period 1972–2016 by utilizing dynamic ARDL simulations’ model by Jordan and Philips (
2018
). The investigated results depict that globalization; foreign direct investment, and innovation have a negative effect on CO
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emissions in improving environmental quality while economic growth, trade, energy consumption, and urbanization positively impact CO
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emissions and hence stimulate environmental degradation both in the long and short run. Besides, institutional quality measured by the political terror scale (PTS) affects CO
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emissions positively and thereby degrades the quality of the environment in both the long and short run. Therefore, policy implication should go toward encouraging globalization, foreign direct investment and innovation; and the sensible utilization of income growth, trade potentials, energy consumption, urbanization and institution is required for the sake of environmental quality in Bangladesh.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Nowadays, more and more images are available. However, to find a required image for an ordinary user is a challenging task. Large amount of researches on image retrieval have been carried out in the ...past two decades. Traditionally, research in this area focuses on content based image retrieval. However, recent research shows that there is a semantic gap between content based image retrieval and image semantics understandable by humans. As a result, research in this area has shifted to bridge the semantic gap between low level image features and high level semantics. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) which extracts semantic features using machine learning techniques. In this paper, we focus on this latest development in image retrieval and provide a comprehensive survey on automatic image annotation. We analyse key aspects of the various AIA methods, including both feature extraction and semantic learning methods. Major methods are discussed and illustrated in details. We report our findings and provide future research directions in the AIA area in the conclusions
► Comprehensive covering of feature representations in AIA research. ► Comprehensive review of classification and annotation methods in AIA. ► Graphic illustration and interpretation of variety of annotation methods in AIA. ► Findings and future direction of research in AIA.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Neutrophils are the principal trouper of the innate immune system. Activated neutrophils undergo a noble cell death termed NETosis and release a mesh-like structure called neutrophil extracellular ...traps (NETs) as a part of their defensive strategy against microbial pathogen attack. This web-like architecture includes a DNA backbone embedded with antimicrobial proteins like myeloperoxidase (MPO), neutrophil elastase (NE), histones and deploys in the entrapment and clearance of encountered pathogens. Thus NETs play an inevitable beneficial role in the host’s protection. However, recent accumulated evidence shows that dysregulated and enhanced NET formation has various pathological aspects including the promotion of sepsis, pulmonary, cardiovascular, hepatic, nephrological, thrombotic, autoimmune, pregnancy, and cancer diseases, and the list is increasing gradually. In this review, we summarize the NET-mediated pathophysiology of different diseases and focus on some updated potential therapeutic approaches against NETs.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Just after the Indian government issued the first lockdown rule to cope with the increasing number of COVID-19 cases in March 2020, the energy consumption in India plummeted dramatically. However, as ...the lockdown relaxed, energy consumption started to recover. In this study, we investigated how COVID-19 cases affected Indian energy consumption during the COVID-19 crisis by testing if the lockdown release had a positive impact on energy consumption and if richer regions were quicker to recover their energy consumption to the level before the lockdown. Using the autoregressive distributed lag (ARDL) model, the study reveals that a long-run relationship holds between the COVID-19 cases and energy consumption and that the COVID-19 cases have a positive effect on Indian energy consumption. This result indicates that as lockdown relaxed, energy consumption started to recover. However, such a positive impact was not apparent in the Eastern and North-Eastern regions, which are the poorest regions among the five regions investigated in the study. This implies that poorer regions need special aid and policy to recover their economy from the damage suffered from the COVID-19 crisis.
Imbalanced learning problems contain an unequal distribution of data samples among different classes and pose a challenge to any classifier as it becomes hard to learn the minority class samples. ...Synthetic oversampling methods address this problem by generating the synthetic minority class samples to balance the distribution between the samples of the majority and minority classes. This paper identifies that most of the existing oversampling methods may generate the wrong synthetic minority samples in some scenarios and make learning tasks harder. To this end, a new method, called Majority Weighted Minority Oversampling TEchnique (MWMOTE), is presented for efficiently handling imbalanced learning problems. MWMOTE first identifies the hard-to-learn informative minority class samples and assigns them weights according to their euclidean distance from the nearest majority class samples. It then generates the synthetic samples from the weighted informative minority class samples using a clustering approach. This is done in such a way that all the generated samples lie inside some minority class cluster. MWMOTE has been evaluated extensively on four artificial and 20 real-world data sets. The simulation results show that our method is better than or comparable with some other existing methods in terms of various assessment metrics, such as geometric mean (G-mean) and area under the receiver operating curve (ROC), usually known as area under curve (AUC).
Many researchers investigate the socio-demographic and economic factors-induced energy consumption, particularly fossil fuel-based non-renewable energy consumption, but there exists a scarcity to ...study on the same factors-driven renewable energy consumption along with institutional quality factor. Given this, our research strives to analyse the relative influence of income growth, foreign direct investment, domestic investment, urbanization, physical infrastructure, and institutional quality on renewable and non-renewable energy consumption in Bangladesh for the period of 1990–2019 using the dynamic ARDL (DARDL) simulations method. The empirical findings divulge that income growth shows positive and negative effect on renewable and non-renewable energy consumption, respectively. Domestic investment has positive effect for renewable and non-renewable energy consumption. Foreign direct investment is found to have positive influencing factor for renewable energy consumption. Urbanization negatively impacts renewable energy consumption but urbanization affects non-renewable energy consumption positively. Physical infrastructure is a negative and positive determinant of renewable and non-renewable energy consumption, respectively. Institutional quality positively affects renewable energy consumption. The robustness of the results is comparatively exhibited using the DARDL simulations area plots where 20% positive and negative shocks to the predictors on the predicted variables are presented.
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•Influencing factors of renewable and non-renewable energy consumption are discussed.•Economic growth promotes renewable energy consumption.•Domestic investment adds to renewable energy consumption.•Foreign direct investment promotes and declines non-renewable energy consumption.•Physical infrastructure is a negative and significant determinant of renewable energy consumption.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Global energy transitions entangled with a paradigm shift from fossil fuel to renewable energy consumption elevates the demand for clean energy technologies, such as solar photovoltaics (PV), wind ...turbines, electric vehicles (EV) and power storage systems etc., which require significant volumes of minerals as raw materials. We measure the import-demand function of minerals by incorporating the role of renewable energy production capacity for selected OECD countries. We apply the cross-sectional autoregressive distributed lag (CS-ARDL) approach to analyse the panel time-series data due to common correlation, country heterogeneity, non-stationarity and potential endogeneity over the period 1990–2020. Our findings confirm that the overall renewable energy production, including installed solar and wind capacities, fosters the import demands for both the aggregate and disaggregate minerals (copper and nickel) in the long run. We also observe that the copper price elasticity of demand holds the Marshallian demand hypothesis, while the nickel price violates it in the long run. Besides, we find a heterogeneous effect of the income factor on the mineral import demand. Therefore, our findings recommend optimizing mineral resources to reinforce the global agenda of energy transitions toward a decarbonized or a net-zero emissions trajectory by the 21st century.
•We test the response of minerals import demand to the clean energy transitions.•We find an eloquent reply of minerals import demand to solar and wind energy capacities.•The copper price holds, and nickel price contradicts the Marshallian demand hypothesis.•We unveil income's heterogeneous effect on minerals demand in 29 OECD countries.•We suggest optimizing imported minerals to reach the set goal of clean energy transitions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Like many other countries, the economy and society of Japan have been severely affected by the COVID-19 outbreak, and the fishery sector particularly seafood is no exception. Among seafood, since ...luxury seafood is more commonly consumed at restaurants it has a higher possibility of getting affected by the pandemic compared with cheap popular seafood for the masses. Considering this motivation, this study investigates the variations in the COVID-19 impact on luxury and cheap seafood prices in the Tokyo Toyosu wholesale market. Using the non-linear autoregressive distributed lag model (NARDL), the study identifies that an increase in the hours of stay-at-home during the initial stage of the pandemic is causing a negative influence on both cheap and luxury seafood prices and that this negative impact was severer in the luxury seafood prices. The study also finds a positive influence from the hours of stay-at-home on some cheap popular seafood like horse mackerel and sardine during the third state of emergency (SOE) where at least most of the elderly people have received their first vaccine dose but the negative impact from the SOE measure remained on luxury seafood. It is evident from the findings that the luxury seafood market is heavily dependent on the restaurant sector, which will likely suffer adverse effects when human mobility is restricted. In the event of a pandemic like COVID-19, policymakers should stabilize the price and provide subsidies to the luxury seafood stakeholders.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This paper presents a new feature selection (FS) algorithm based on the wrapper approach using neural networks (NNs). The vital aspect of this algorithm is the automatic determination of NN ...architectures during the FS process. Our algorithm uses a constructive approach involving correlation information in selecting features and determining NN architectures. We call this algorithm as constructive approach for FS (CAFS). The aim of using correlation information in CAFS is to encourage the search strategy for selecting less correlated (distinct) features if they enhance accuracy of NNs. Such an encouragement will reduce redundancy of information resulting in compact NN architectures. We evaluate the performance of CAFS on eight benchmark classification problems. The experimental results show the essence of CAFS in selecting features with compact NN architectures.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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