Miracle-dz/UniFAR-FTUs huggingface dataset:
Ocean‐scale footprint of a highly mobile fishing fleet: Social‐ecological drivers of fleet behaviour and evidence of illegal fishing

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. People and Nature published by John Wiley & Sons Ltd on behalf of British Ecological Society 1Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, UK 2Institute of Zoology, Zoological Society of London, London, UK 3Interdisciplinary Centre of Social Sciences (CICS.NOVA), School of Social Sciences and Humanities (NOVA FCSH), NOVA University Lisbon, Lisboa, Portugal 4Oceanswell, Colombo, Sri Lanka 5The UWA Oceans Institute, University of Western Australia (M092), Crawley, WA, Australia
Development of Research on Calcium Carbonate for Decomposed Kinetics

The research method and development of decomposed kinetics on calcium carbonate was reviewed.Some methods and conclusions of previous researcher were introduced on decomposed kinetics of CaCO_3. And control mechanism of reaction rate is different by diveristy of many aspect factors ,for example,research method,experiment measure,reaction condition and particle size ,etc. Moreover,more systematic study conlusions on CaCO_3 were mentioned in suspension state,and it was refered that circulating reaction equipment of high solid to gas ratio will be a kind of more suitable reactor for decomposed kinetics of CaCO_3.
A hybrid wavelet-Lyapunov exponent model for river water quality forecast

The use of spectral theory and chaos theory on river water quality modeling is reported in a very limited way. This study proposes a waveletmaximum Lyapunov exponent (WMLE) hybrid model for river water quality dynamics, combining spectral theory and chaos theory. The methodology involves the following major steps: (1) use of wavelet transformation to filter the noisy signal in the water quality time series; (2) reconstruction of phase space to embed the water quality time series and determine the trajectory of the underlying dynamics; and (3) identification of the presence/absence of chaos and prediction using the largest Lyapunov exponent value. Case studies on the Huaihe River in China and the Potomac River in the United States, as representatives of low-frequency and high-frequency forecast, show average relative errors on weekly dissolved oxygen (DO), chemical oxygen demand (COD), and ammonia nitrogen (NH3-N) data are 2.35%, 4.53%, and 18.85%, and on 15-minute based DO data are 1.185%. It also indicates that the hybrid model performs better to some extent when compared to the purely Lyapunov exponent model, ARMA model, and ANN model. This study is a proof that the combination of spectral theory and chaos theory is promising to describe and predict fluctuation of particular water quality indicators in rivers.
Phylogenetic and Codon Usage Analysis for Capsid and Replicase Genes of Porcine Circovirus 3

Porcine circovirus type 3 (PCV3) is a highly contagious virus belonging to the family Circoviridae that causes the severe dermatitis and nephropathy syndrome. To date, PCV3 has a worldwide distribution and bring huge economic loss in swine industry. Replicase protein (Rep) and capsid protein (Cap) are two major proteins of PCV3. Considering that the large number of new PCV3 isolates were reported in the past few years and the research for the codon usage pattern of Rep and Cap genes was still a gap, phylogenetic and codon usage analysis of these two genes was performed. Phylogenetic analysis with all strains showed no clear clusters were displayed, but almost all strains of one genotype were separated into same clade. Relative synonymous codon usage (RSCU) analysis revealed that the codon usage bias existed and effective number of codon (ENC) analysis showed that the bias was slight low. ENC-GC3s plot indicated that mutational pressure and other factors both play a role in PCV3 codon usage and neutrality plot analysis showed that natural selection was the main force influencing the codon usage pattern. In summary, the results provided the important basic data on codon usage pattern of Rep and Cap genes, and a better understanding of the evolution and potential origin of PCV3.
Managing International - Civil Militarized Conflicts (I-CMC): Empirical Patterns

ABSTRACT This study examines international-civil militarized conflicts (I-CMCs), those that lie at the intersection of violent intra- and interstate conflict. The data compilation identifies I-CMCs and the different conflict management approaches specifically used to manage them (i.e., negotiation, mediation, legal, peacekeeping, sanctions, and military intervention). We describe the patterns of conflict management in I-CMCs over the period 1946–2010, with respect to both serious civil and interstate conflicts. Among the key findings are that conflict management in general is very frequent (about 18 attempts per interstate confrontation and much more for serious internal conflict) and mediation is by far the most frequent approach.
Electrophoretic Deposition of a Hybrid Graphene Oxide/Biomolecule Coating Facilitating Controllable Drug Loading and Release

Two-dimensional (2D) graphene oxide (GO) exhibits a high drug loading capacity per unit mass due to its unique structure and hydrophilicity and has been widely researched for drug-delivery systems. Here, we modified the surfaces of metal implants; we applied GO-based coatings that controlled drug loading and release. We used electrophoretic deposition (EPD) to apply the coatings at room temperature. The EPD coatings were analyzed in terms of their components, physical properties such as hardness and hydrophilicity, and in vitro cell tests of their biological properties. Uniform GO-EPD coatings improved surface hydrophilicity and hardness and greatly improved the bone differentiation properties of the metal substrate. Drug loading and release increased greatly compared to when the drug was adsorbed to only the surface of a coating. GO facilitated deposition of a drug-containing coating via EPD, and the surface modification, and drug loading and release, were controlled by the thickness of the coating.
Captured and captioned: Representing family life on Instagram

This article examines how practices of family photography are being transformed in the digital sphere, specifically on Instagram. While research on ‘digital intimacies’ focusses on romantic or peer interactions, the digital practices of families – especially intergenerational interactions – remain understudied. We use Janet Finch’s notion of ‘family display’ to consider how Instagram affords new modes of performing and sharing family life. This concept has exciting potential for media-rich online spaces, but so far, only a few studies examine how social media platforms extend the display of family practices. To explore family photography on Instagram, we analyse a sample of 200 Instagram posts. We argue that features specific to photo-sharing in digital spaces, such as hashtags, emojis and captions, open up new aspects of and audiences for family display. Our analysis paves the way for future research about how relationships are displayed across a range of digital platforms.
Modeling of COVID-19 Epidemic Growth Curve in Indonesia

Aim of this study is to make parametric modeling of the COVID-19 epidemic growth curve so that the maximum value and time at that point can be obtained from the cumulative cases of COVID-19. The data used in this study is the cumulative number of positive confirmed cases of COVID-19 from https://covid19.go. id/. The method used in this study is fitting data with the Logistic and Gompertz models. Result of this study are (1) the Logistic and Gompertz models are very fit in modeling the COVID-19 epidemic growth curve, indicated from the value of R2 (coefficient of determination) which reaches more than 99%; (2) From the Logistics model it is obtained that the estimated amount of the maximum cumulative case at the end of the COVID-19 epidemic is 7,714 positive confirmed cases, achieved in about 82 days (May 22, 2020) from Mar 2, 2020, when the first positive COVID-19 case was announced by the government; and (3) From the Gompertz model, it is obtained that the estimated maximum cumulative case at the end of the COVID-19 epidemic is 33,975 positive confirmed cases, achieved in about 152 days (Jul 30, 2020) from Mar 2, 2020. The results of this study can be used as input to the government to take steps in controlling the spread of COVID-19.
Assessment of the risk of foreign divestment in Poland during the COVID-19 pandemic

The importance of foreign direct investment (FDI) to the economic development of Poland cannot be overestimated, both at the regional level and in relation to the economy as a whole. Since FDIs are powered by capital sensitive to various national and international crises, it seems natural to ask whether the situation connected with the global COVID-19 pandemic is reflected in the reduction of FDI inflows to Poland. The aim of the paper is to identify the determinants of the foreign divestment process in the Polish economy as a whole and in its main sectors during the COVID-19 pandemic. The article analyses scenarios of foreign divestment in Poland in an annual perspective, starting from the outbreak of the epidemic in March 2020 up to February 2021. The study used data from a survey conducted in April and May 2020 among nearly 500 enterprises realising FDI in Poland. The benchmark for the surveyed companies was the level of their involvement in FDIs covering a one-year period prior to the announcement of the epidemic. The application of logit models allowed the identification of the most important factors of foreign divestment during COVID-19, including the location of FDIs in the services sector, industry, the IT sector, increased market openness and interactions of variables taking into account the restrictions introduced to the economy due to the pandemic. The level of risk of divestment of these variables depends, however, on the volume of FDI reductions declared by investors and on the sector of the economy. If considerable divestment is assumed, FDIs in the services sector are then burdened with a higher risk of divestment than FDIs in the processing industry. Assuming small divestments, FDIs in the IT sector constitute a factor bearing the greatest risk of FDI reduction in the entire economy.
Classification of Human and Vehicles with The Deep Learning Based on Transfer Learning Method

Son yillarda derin ogrenme algoritmalarinin kullaniminda onemli bir artis gorulmektedir. Uygulamalarda derin ogrenme modellerinden evrisimli sinir agi (ESA) ozellikle goruntu islemede insan ve arac gibi onemli nesneleri diger nesnelerden ayirmak icin siklikla kullanilmaktadir. Goruntu isleme donanimlarinin gelismesiyle goruntu isleme sureci onemli olcude azaltilmaktadir. Bu gelismeler sayesinde derin ogrenme uzerine yapilan calismalarin performansi artmaktadir. Bu calismada, dronlar tarafindan elde edilen goruntulerden nesneleri (insan, araba ve motosiklet/bisiklet) tespit etmek ve siniflandirmak icin derin ogrenmeye dayali bir sistem gelistirilmistir. Derin sinir aginin transfer ogrenme yontemiyle egitilmesi ve test edilmesi icin acik kaynak olan Stanford Universitesi goruntu seti ve Afyon Kocatepe Universitesi (AKU)’nde olusturulan drone goruntu seti olmak uzere iki veri seti kullanilmistir. GoogleNet, VggNet ve ResNet50 derin ogrenme algoritmalari kullanilarak insan, araba ve motosiklet/bisiklet siniflarini tespit etme ve siniflandirma islemine gore kesinlik, duyarlilik ve f1 skor degerleri degerlendirilmistir. Bu degerlendirme sonucuna gore ResNet50 modelinde 0,916 kesinlik, 0,895 hassasiyet ve 0,906 f1 skor degeriyle performansi yuksek sonuclar elde edilmistir. Anahtar Kelimeler: Derin ogrenme, Nesne tespiti, CNN
Concept Analysis of Emotional Intelligence in Nursing

Purpose: This study was done to clarify and analyze the concept of emotional intelligence in Nursing. Methods: Using the framework of Walker and Avant’s concept analysis, 60 articles on emotional intelligence were selected for this study. Results: Emotional intelligence was defined as aspects of individual recognition of emotion and relational activities of emotion. The attributes of emotional intelligence are competency to be aware, regulate, express and use nurses’ own and patients’ emotions in a therapeutic manner. The antecedents of emotional intelligence include meeting with patients, cognitive ability, empathy, modulating emotion and interpersonal skills. Consequences of emotional intelligence are forming relationship between nurse and patients, personal growth, achievement in workplace, high job satisfaction, low burnout and high quality of nursing care. The concept was clarified by presentation of model, borderline, contrary and related cases. Conclusion: This study is meaningful in that the concept and attributes of emotional intelligence are identified in the nursing area by reflecting the characteristic and the purpose of nursing. In addition, based on the results of this study, development of standardized tools to measure emotional intelligence and development of educational programs to enhance nurses’ emotional intelligence are recommended.
Evaluation of cactus pear clones subjected to salt stress

Cactus pear is an important source of fodder for herbivores, though its production is affected by soil salinity. This work aimed to evaluate the development of cactus pear clones subjected to salt stress as a measure of their salinity tolerance. The experimental design was a randomized block with 6 replications. Twenty genotypes of cactus pear were used from the Active Germplasm Bank, with variability in resistance to carmine cochineal [Dactylopius opuntiae (Cockerell)] as this insect species destroys many stands of cactus on farms. One cladode was planted per pot containing 12 kg of sandy soil. Water with a salinity of 3.6 dS/m was applied at 14-day intervals. The clones were scored at 28-day intervals for degree of damage to cladodes (1‒5) and were harvested when they reached a score of 5, showing 100% damage (chlorosis and dehydration) to the whole plant. The Liso Forrageiro clone took 419 days to reach Score 5, indicating its greater tolerance to salinity. Highest dry matter yields were achieved by Orelha de Elefante Mexicana and Orelha de Elefante Africana clones with 51.5 and 50.8 g/plant, respectively, while Liso Forrageiro yielded only 36.1 g/plant, despite having similar surface area and weight of roots to these 2 clones. Further studies in the field involving these better-performing clones seem warranted to determine how the pot trial results are repeated in the field, especially in areas where carmine cochineal insect is prevalent.
The Ecosystem of VAT Administration in E-Commerce: Case of the Eastern Europe Countries

Quarantine economic conditions put forward new demands to tax administration’s efficiency as a priority source of the EU financial resources. The relationship between fair, efficient, sustainable taxation and budget revenues’ adequacy to finance social and economic investment, innovation, and development needs is evident. Therefore, ensuring tax administration’s efficiency and effectiveness in any EU country is of theoretical and practical importance.The study aims to deepen the VAT administration’s theoretical and applied provisions in e-commerce operations in a global convergence of the national economic systems. The analysis of the state and forecast of the VAT mobilization in the EU countries’ e-commerce operations are presented. The research’s specific is to assess the VAT tax base’s future size in the context of changes in the EU tax legislation. According to the scientific literature analysis, in forecasting the studied tax, it is advisable to use econometric forecasting methods based on time series models.As the result of the study, the forecast volumes of the VAT base of Eastern Europe and the amount of approximate future tax revenues are presented. The obtained results confirm the relationship between the growth of e-commerce and VAT tax revenues under such transactions. It led to the presentation of the author’s vision of the VAT administration ecosystem for e-commerce transactions and the allocation of its functional entities.The directions on achieving the VAT mobilization’s maximum volumes following the EU tax legislation requirements in European integration and globalization were substantiated. The submitted conclusions are entitled to be used in tax administration processes to forecast other tax payments.
Application of response surface methodology and artificial neural network on pyrolysis of safflower seed press cake

ABSTRACT In this study, mathematical correlation between the process variables and product yields for pyrolysis of safflower seed press cake (SPC) in fixed-bed reactor was investigated by using the response surface methodology (RSM) and artificial neural networks (ANNs). The RSM results showed that the second-order response model can be used to describe the relationship between the various factors and the response. Several feed-forward fully connected neural networks were investigated and optimal configuration of the ANN model was obtained. The results revealed that the ANN model could be considered as an alternative to RSM and practical modeling technique for the pyrolysis product yields.
In-vitro Digestibility Methods and Factors Affecting Minerals Bioavailability: A Review

ABSTRACT Micronutrient deficiencies are known to affect many people worldwide. Among the factors contributing to this situation, the poor bioavailability of foods micronutrients is key. This review aims at highlighting the factors affecting minerals bioavailability and their assessment methods. The numeric approach was used during data collection. The results show that the bioavailability of minerals is key to assess the amount that is released for body metabolism. Different factors including inhibitors and promoters affect their bioavailability. There are different methods to assess the digestibility of minerals, which generally involve oral, gastric, and intestinal phases.
Flavonoid Constituents in Some Species of Salvia L. (Lamiaceae) in Iran

Eight Salvia L. species including S. spinosa L. , S. reuterana Boiss. , S. macrosiphon Boiss. , S. syriaca L. , S. nemorosa L. , S. virgata Jacq. , S. sharifii Rech. f. & Esfand. and S. mirzayanii Rech. f. & Esfand. were studied for flavonoid compounds. These constituents were analyzed using two-dimensional maps on silica gel 60F thin layer chromatography. The flavonoid compounds of each species were purified using column chromatography with sephadex LH20 and the type of flavonoid compounds was determined using UV spectra. Based on the findings, the highest flavonoid variations were related to hydroxylation and methoxylation patterns. Five flavonoid classes namely flavones, flavanones, flavonols, isoflavones and chalcones were determined. The flavones (92%) and isoflavones (15.6%) were the highest and the lowest flavonoid classes the eight Salvia species. In addition, a total of 60 flavonoid compounds were identified. Some flavonoid compounds in studied Salvia species were first reported for Iran. The amount of flavonoid compounds in S. reuterana, S. nemorosa and S. mirzayani (27, 24, 22 compounds, respectively) was more than the other Salvia species. In conclusion, the flavonoid compounds appear to be an appropriate marker in taxonomic status of Salvia.
Spatial Effect Analysis of Total Factor Productivity and Forestry Economic Growth

This paper takes 31 provinces in China from 2009 to 2018 as the research object. The three-stage data envelopment analysis (DEA) model was used to measure the total factor productivity of forestry, and the entropy method was used to measure the level of economic development and ecological construction. We used the global Moran index to explore the spatial correlation of forestry economic growth, and the local Moran index to explore the spatial agglomeration of forestry economic growth. On this basis, the spatial Durbin model was constructed to explore the spatial spillover effect between forestry total factor productivity and forestry economic growth. The conclusion is as follows: the total factor productivity of forestry in China is increasing continuously, and there are obvious spatial differences. Forestry economic growth has a significant spatial autocorrelation, and an overall upward trend. However, the spatial agglomeration effect was relatively weak and in the beginning stage of its formation. Total factor productivity of forestry has significant direct effect on the growth of forestry economy and forms an indirect spillover effect. Based on this, the countermeasures and suggestions to promote the benign and coordinated development of the forestry economy were put forward.
A transition copula model for analyzing multivariate longitudinal data with missing responses

ABSTRACT In multivariate longitudinal studies, several outcomes are repeatedly measured for each subject over time. The data structure of these studies creates two types of associations which should take into account by the model: association of outcomes at a given time point and association among repeated measurements over time for a specific outcome. In our approach, because of some advantageous arisen from features like flexibility of marginal distributions, a copula-based approach is used for joint modeling of multivariate outcomes at each time points, also a transition model is used for considering the association of longitudinal measurements over time. For the problem of incomplete data, missingness mechanism is assumed to be ignorable. Some simulation results are reported in different scenarios using the Gaussian, t and several commonly used copulas of the family of Archimedean copulas. Akaike information criterion (AIC) is used to select the best copula function. The proposed approach is also used for analyzing a real obesity data set.
Transformer network-based word embeddings approach for autonomous cyberbullying detection

PurposeNowadays people are connected by social media like Facebook, Instagram, Twitter, YouTube and much more. Bullies take advantage of these social networks to share their comments. Cyberbullying is one typical kind of harassment by making aggressive comments, abuses to hurt the netizens. Social media is one of the areas where bullying happens extensively. Hence, it is necessary to develop an efficient and autonomous cyberbullying detection technique.Design/methodology/approachIn this paper, the authors proposed a transformer network-based word embeddings approach for cyberbullying detection. RoBERTa is used to generate word embeddings and Light Gradient Boosting Machine is used as a classifier.FindingsThe proposed approach outperforms machine learning algorithms such as logistic regression, support vector machine and deep learning models such as word-level convolutional neural networks (word CNN) and character convolutional neural networks with short cuts (char CNNS) in terms of precision, recall, F1-score.Originality/valueOne of the limitations of traditional word embeddings methods is context-independent. In this work, only text data are utilized to identify cyberbullying. This work can be extended to predict cyberbullying activities in multimedia environment like image, audio and video.