bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of Hexavalent Chromium Pollution in Buriganga and Dhaleshwari River Waterbodies Adjacent to Tannery Estates in Bangladesh
Authors: Rahman Hafizur , Hoque Nabila , Sarker Palash Kumar , Safa Ashrafus
Published: November 2020

Recently, in Bangladesh, all tannery industries have been relocated to a new location exclusively established for leather processing industries with modern manufacturing facilities and effluent treatment plants with standard probations. Effluents generated from the tannery industries are now being disposed of into the surrounding river water bodies. In this study, our goal was to investigate the presence of chemical contaminants like hexavalent chromium (Cr6+) in the water bodies surrounding tannery industries and to understand the possible role played by the tannery effluents in contaminating the river water bodies with Cr6+. Result analysis revealed the presence of an amount of Cr6+ (ranging from 0.01 mg/L to 3.54 mg/L) in the surrounding water bodies, which was far above the maximum permissible limit of Cr6+ (0.05 mg/L for surface water), set by the Environmental Protection Agency. It is, therefore, plausible to assume that effluents from the tanneries play an important role in hexavalent chromium contamination of water bodies surrounding tannery industries.
Mechanisms and Tools for Environmental Protection in Algeria from the Perspective of Sustainable Development
Authors: Abi Walid , Achouri Brahim , Moumene Samira
Published: November 2020

The paper aimed to address the development of the legislative and institutional framework for the protection of the environment in Algeria through monitoring the most important stages of the development of the legislative framework for the protection of the environment in Algeria, as well as the most important ministries and institutions that took care of its protection. The study found that in light of the difficult situation that the environment in Algeria has become, the Algerian legislator has made a set of laws aimed at the good management of urban and environmental development. Law No. 83/03 of February 05, 1983, on the protection of the environment is considered the first legislation related to the environment, this was followed by a series of laws and decrees, as well as the development of an institutional framework for the protection of the environment, the adoption of environmental policy instruments as a mechanism for preserving them, and the ratification of several international environmental conventions.

Despite the existence of many Legislation and laws that provide for the protection of the environment, the environmental situation in Algeria continues to deteriorate due to the lack of effective enforcement of the laws on the ground for its lack of mandatory and deterrent status. The rotation of ministries and agencies to protect the environment has negatively affected the adoption of strict decisions in the field of environmental protection, and not to direct the proceeds of environmental charges imposed on all polluting activities to protect the environment and control pollution.
Analysis and Evaluation of the Tourism Sector in Algeria and Tunisia during the Period (1990-2014)
Authors: Yamina Mefatih
Published: November 2020

This study aims to analyze and compare the tourism sector in Algeria with the tourism sector in Tunisia through tourist indicators (human influx, number of tourist nights, hotel capacity for both countries during the period selected “1990-2014”, and also the comparison in terms of the global ranking of the report issued by the World Economic Forum “WEF” and the report of the World Tourism and Travel Board “WTTC”). The study concluded that Tunisia can improve its competitiveness while Algeria is still in place, this is due to the policy of marginalization adopted by the Algerian state and its dependence on the oil wealth and there is no real intention to advance this sector.
Budget Deficit and Unconventional Financing in Algeria
Authors: Ould Hennia Hadjer
Published: November 2020

The purpose of this study is to analyze the relationship between the budget deficit and unconventional financing in Algeria.

The results of our analysis indicate that the drop in oil prices in mid-2014, resulting in lower oil and gas revenues, which is the main source of financing for the economy, has led to budget deficits, following which officials have tried to find a new alternative financing instrument. So in the face of this financial crisis, the government decided to resort to unconventional internal financing.
Financial Literacy, Financial behaviour and Economic System
Authors: Bouzidi Salem , Benmoussa Mohammed
Published: November 2020

Financial literacy measures how much one comprehends key money related financial concepts, through appropriate short-term decision making, so financial literacy is the essential information and that individuals need so as to make due in modern society. Financial literacy can be affected by environmental issues, such as regional differences and economic systems. The relationship between financial literacy and financial behaviour has been considered in a number of other studies, financial literacy is an important determinant of financial behaviour in developing countries, financial literacy is also associated with increased equity ownership, the use of low-cost mortgages, and retirement planning behaviour.
Barriers to the Application of Islamic Finance (Mode of Musharaka) in Gumhouri Bank in Libya from the Perspective of its Employees
Authors: Aljbiri Atia , Milad Saad
Published: November 2020

This study aims to know the most important barriers faced by the Gumhouri bank in Libya, in the application of partnership (Musharaka), and to achieve the objectives of the study, the researchers adopted the descriptive-analytical analysis using the questionnaire as a tool for study data collection. It is distributed on a sample of (54) individuals, and the data of this study were analyzed, besides, its hypnosis was examined by the application of the most suitable descriptive statistical analysis, using statistical package for social sciences (SPSS), some conclusions were reached which may contribute to the recognition of the barriers and put some recommendations in the same frameworks.
Banking Governance Mechanisms and their Role in Attracting Investment: A Case Study of a Sample of Banks Listed on the Khartoum Stock Exchange
Authors: Al-Mahdi Al-Amir Ahmed Muhammad
Published: November 2020

The study aimed at identifying the role of banking corporate governance mechanisms in attracting investments to Sudanese banks, so it followed the descriptive method to realize the objectives of this study, depending on the oriented questionnaire of banks sampling registered in the Khartoum stock market. The study reached some important results such as the banking corporate governance mechanisms application led to attracting foreign direct investments and local capital encouragement of investment in various projects, international and local cash flow guarantee. The study concluded with some recommendations such as the Sudanese banks should concern over the banking corporate governance mechanisms that have an effective impact on attracting investments to be traced.
Quantitative Easing as a Mechanism for Non-Traditional Monetary Policy and Implications of its Adoption in the Algerian Economy: Econometric Study using the ARDL Model
Authors: Ayadi Salah , Serarma Abdelaouahed
Published: November 2020

This study aims to identify some concepts related to non-traditional monetary policy instruments, including the quantitative easing tool, and discuss the main reasons for Algeria's adoption of this instrument.

The study concluded that the adoption of the policy of quantitative easing in Algeria is not to affect economic variables but to finance the budget deficit. In order to estimate the impact of monetary issuance on economic growth for 2003Q1-2018Q4, the ARDL model was used, where the results resulted in a direct relationship between M2 and GDP.
An Economic and Analytical Study of Inflation’s Impact on Performance Indicators of the Financial Market: A Case of Amman Stock Exchange for the Period 1980-2015
Authors: Serrai Salah , Benmerzoug Nabil
Published: November 2020

This study aims to measure the impact of inflation rates in Jordan on the financial performance of the market through the use of the following performance indicators: the trading volume index, the index market value, the general index of shares prices, the index of the share turnover rate during the period (1980-2015) based on annual data. The Authors concluded in this study that there is a statistically significant relationship between the inflation rates and the indicators of financial market performance. This is consistent with the economic theory of Fisher and many previous studies, which refers to the positive relationship between inflation and financial market indicators. Thus, it is possible to use the shares to hedge against inflation risks in the Amman Stock Exchange.
The Impact of Machinery Maintenance on Achieving Quality of Products of the Algerian Economic Institution: A Case of Al-Hodna Mills Company
Authors: Dekkache Semia
Published: November 2020

This study aimed to know the impact of machinery maintenance on achieving the quality of products in the economic establishment by applying this in Al-Hodna mills institution in M'sila. By developing interview questions and directing them to the officials of maintenance and laboratory departments, also, documents were used from various departments of the institution. The study reached the following results: There are practices for preventive maintenance, curative maintenance in the institution unde rstudy, an interest in the quality of products in the institution under study, the identification of nineteen and twenty machines in two different ways that have a direct impact on the quality of products in the institution under study.
As guardiãs da saúde: representações e características socioculturais de enfermeiras domésticas do Rio de Janeiro, 1880-1910
Authors: Ferreira Luiz Otávio
Published: November 2020

O objetivo deste artigo é descrever e analisar as representação e as características socioculturais das mulheres que trabalhavam como enfermeiras em domicílios, hospitais e asilos na cidade do Rio de Janeiro no final do século 19 e início do século 20. Conforme apresentadas em anúncios matéria de oferta e de procura de serviços de enfermagem publicados, entre 1880 e 1910, no conhecido diário carioca o Jornal do Commercio.
Impacts of global NOx inversions on NO2 and ozone simulations
Authors: Qu Zhen , Henze Daven K. , Cooper Owen R. , Neu Jessica L.
Published: November 2020

Abstract. Tropospheric NO2 and ozone simulations have large uncertainties,
but their biases, seasonality, and trends can be improved with NO2
assimilations. We perform global top-down estimates of monthly NOx
emissions using two Ozone Monitoring Instrument (OMI) NO2 retrievals (NASAv3 and DOMINOv2) from 2005
to 2016 through a hybrid 4D-Var/mass balance inversion. Discrepancy in
NO2 retrieval products is a major source of uncertainties in the
top-down NOx emission estimates. The different vertical sensitivities
in the two NO2 retrievals affect both magnitude and seasonal variations
of top-down NOx emissions. The 12-year averages of regional NOx
budgets from the NASA posterior emissions are 37 % to 53 % smaller than
the DOMINO posterior emissions. Consequently, the DOMINO posterior surface NO2
simulations greatly reduced the negative biases in China (by 15 %) and the
US (by 22 %) compared to surface NO2 measurements. Posterior NOx
emissions show consistent trends over China, the US, India, and Mexico
constrained by the two retrievals. Emission trends are less robust over
South America, Australia, western Europe, and Africa, where the two
retrievals show less consistency. NO2 trends have more consistent
decreases (by 26 %) with the measurements (by 32 %) in the US from 2006
to 2016 when using the NASA posterior emissions. The performance of posterior ozone
simulations has spatial heterogeneities from region to region. On a global
scale, ozone simulations using NASA-based emissions alleviate the double
peak in the prior simulation of global ozone seasonality. The higher
abundances of NO2 from the DOMINO posterior simulations increase the global
background ozone concentrations and therefore reduce the negative biases
more than the NASA posterior simulations using GEOS-Chem v12 at remote
sites. Compared to surface ozone measurements, posterior simulations have
more consistent magnitude and interannual variations than the prior
estimates, but the performance from the NASA-based and DOMINO-based
emissions varies across ozone metrics. The limited availability of remote-sensing data and the use of prior NOx diurnal variations hinder
improvement of ozone diurnal variations from the assimilation, and therefore
have mixed performance on improving different ozone metrics. Additional
improvements in posterior NO2 and ozone simulations require more
precise and consistent NO2 retrieval products, more accurate diurnal
variations of NOx and VOC emissions, and improved simulations of ozone
chemistry and depositions.
Carbon storage in phosphorus limited grasslands may
decline in response to elevated nitrogen deposition: a long-term field manipulation and modelling study
Authors: Taylor Christopher R. , Janes-Bassett Victoria , Phoenix Gareth , Keane Ben , Hartley Iain P. , Davies Jessica A. C.
Published: November 2020

Abstract. In many temperate ecosystems, nitrogen (N) limits productivity, meaning anthropogenic N deposition can stimulate plant growth and subsequently carbon (C) sequestration. Phosphorus (P) and N-P co-limited grasslands are widespread, yet there is limited understanding of their responses to N deposition, which may transition more ecosystems toward P-limited or N-P co-limited states. Here, we investigate the consequences of enhanced N addition on the C-N-P pools of grasslands in different states of nutrient limitation. We explored the response of a long-term nutrient-manipulation experiment on two N-P co-limited grasslands; an acidic grassland of stronger N-limitation and a calcareous grassland of stronger P-limitation, by combining data with an integrated C-N-P cycling model (N14CP). To explore the role of P-access mechanisms in determining ecosystem state, we allowed P-access to vary, and compared the outputs to plant-soil C-N-P data. Combinations of organic P access and inorganic P availability most closely representing data were used to simulate the grasslands and quantify their temporal response to nutrient manipulation. The model suggested N additions have increased C stocks in the acidic grassland, but decreased them in the calcareous, where N provision exacerbated P-limitation and reduced biomass input to the soil. Furthermore, plant acquisition of organic P may play an important role in reducing P-limitation, as both simulated grasslands increased organic P uptake to meet P demand. We conclude that grasslands of differing limiting nutrients may respond to N deposition in contrasting ways, and stress that as N deposition shifts ecosystems toward P-limitation, a globally important carbon sink risks degradation.
Central Europe, 1531–1540 CE: The driest summer decade of the past five centuries?
Authors: Brázdil Rudolf , Dobrovolný Petr , Bauch Martin , Camenisch Chantal , Kiss Andrea , Kotyza Oldřich , Oliński Piotr , Řezníčková Ladislava
Published: November 2020

Abstract. Based on three drought indices (SPI, SPEI, Z-index)
reconstructed from documentary evidence and instrumental records, the
summers of 1531–1540 were identified as the driest summer decade
during the 1501–2015 period in the Czech Lands. Based on documentary data,
extended from the Czech scale to central Europe, dry patterns of various
intensities (represented, for example, by dry spells, low numbers of
precipitation days, very low rivers, and drying-out of water sources)
occurred in 1532, 1534–1536, 1538, and particularly 1540, broken by wetter
or normal patterns in 1531, 1533, 1537, and 1539. Information relevant to
summer droughts extracted from documentary data in central Europe was
confirmed in summer precipitation totals from a multi-proxy reconstruction
for Europe by Pauling et al. (2006) and further by self-calibrated summer
Palmer Drought Severity Index (PDSI) reconstruction from tree ring widths in Old World Drought Atlas (OWDA) by Cook et al. (2015). The
summer patterns described are consistent with the distribution of sea level
pressure deviations from a modern reference period. Summer droughts were
responsible for numerous negative impacts, such as bad harvests of certain
crops, reduction and lack of water sources, and frequent forest fires, while
in the wetter summers central Europe was affected by floods. However, there
are no indications of severe impacts of a multi-country or multi-year effect.
Reconstructions based on documentary data indicate that the summers of
1531–1540 constitute the driest summer decade in central Europe for the
past five centuries between 1501 and 2010 CE.
Half-hourly changes in intertidal temperature at nine wave-exposed locations along the Atlantic Canadian coast: a 5.5-year study
Authors: Scrosati Ricardo A. , Ellrich Julius A. , Freeman Matthew J.
Published: November 2020

Abstract. Intertidal habitats are unique because they spend alternating
periods of submergence (at high tide) and emergence (at low tide) every day.
Thus, intertidal temperature is mainly driven by sea surface temperature
(SST) during high tides and by air temperature during low tides. Because of
that, the switch from high to low tides and vice versa can determine rapid
changes in intertidal thermal conditions. On cold-temperate shores, which
are characterized by cold winters and warm summers, intertidal thermal
conditions can also change considerably with seasons. Despite this
uniqueness, knowledge on intertidal temperature dynamics is more limited
than for open seas. This is especially true for wave-exposed intertidal
habitats, which, in addition to the unique properties described above, are
also characterized by wave splash being able to moderate intertidal thermal
extremes during low tides. To address this knowledge gap, we measured
temperature every half hour during a period of 5.5 years (2014–2019) at nine
wave-exposed rocky intertidal locations spanning 415 km of the Atlantic
coast of Nova Scotia, Canada. This data set is freely available from the
figshare online repository (Scrosati and Ellrich, 2020a;
https://doi.org/10.6084/m9.figshare.12462065.v1). We summarize the main
properties of this data set by focusing on location-wise values of daily
maximum and minimum temperature and daily SST, which we make freely
available as a separate data set in figshare (Scrosati et al., 2020;
https://doi.org/10.6084/m9.figshare.12453374.v1). Overall, this
cold-temperate coast exhibited a wide annual SST range, from a lowest
overall value of −1.8 ∘C in winter to a highest overall value of
22.8 ∘C in summer. In addition, the latitudinal SST trend along
this coast experienced a reversal from winter (when SST increased
southwards) to summer (when SST decreased southwards), seemingly driven by
alongshore differences in summer coastal upwelling. Daily temperature maxima
and minima were more extreme, as expected from their occurrence during low
tides, ranging from a lowest overall value of −16.3 ∘C in winter
to a highest overall value of 41.2 ∘C in summer. Daily maximum
temperature in summer varied little along the coast, while daily minimum
temperature in winter increased southwards. This data set is the first of
its kind for the Atlantic Canadian coast and exemplifies in detail how
intertidal temperature varies in wave-exposed environments on a
cold-temperate coast.
Identifying the optimal spatial distribution of tracers for optical sensing of stream surface flow
Authors: Pizarro Alonso , Dal Sasso Silvano F. , Perks Matthew T. , Manfreda Salvatore
Published: November 2020

Abstract. River monitoring is of particular interest as a society that faces increasingly complex water management issues. Emerging technologies have contributed to opening new avenues for improving our monitoring capabilities but have also generated new challenges for the harmonised use of devices and algorithms. In this context, optical-sensing techniques for stream surface flow velocities are strongly influenced by tracer characteristics such as seeding density and their spatial distribution. Therefore, a principal research goal is the identification of how these properties affect the accuracy of such methods. To this aim, numerical simulations were performed to consider different levels of tracer clustering, particle colour (in terms of greyscale intensity), seeding
density, and background noise. Two widely used image-velocimetry algorithms
were adopted: (i) particle-tracking velocimetry (PTV) and (ii) particle image velocimetry (PIV). A descriptor of the seeding characteristics (based on seeding density and tracer clustering) was introduced based on a newly developed metric called the Seeding Distribution Index (SDI). This index can be approximated and used in practice as SDI=ν0.1/ρρcν1, where ν, ρ, and ρcν1 are the spatial-clustering level, the seeding density, and the reference seeding density at ν=1, respectively. A reduction in image-velocimetry errors was systematically observed for lower values of the SDI; therefore, the optimal
frame window (i.e. a subset of the video image sequence) was defined as the
one that minimises the SDI. In addition to numerical analyses, a field case
study on the Basento river (located in southern Italy) was considered as a
proof of concept of the proposed framework. Field results corroborated
numerical findings, and error reductions of about 15.9 % and 16.1 % were calculated – using PTV and PIV, respectively – by employing the optimal frame window.
USAR simulation system: presenting spatial strategies in agents'
task allocation under uncertainties
Authors: Hooshangi Navid , Alesheikh Ali Asghar , Panahi Mahdi , Lee Saro
Published: November 2020

Abstract. Task allocation in uncertainty conditions is a key problem for agents attempting to achieve harmony in disaster environments. This paper presents an agent- based simulation to investigate tasks allocation through the consideration of appropriate spatial strategies to deal with uncertainty in urban search and rescue (USAR) operation. The proposed method is presented in five phases: ordering existing tasks, finding coordinating agent, holding an auction, applying allocation strategies, and implementation and observation of environmental uncertainties. The methodology was evaluated in Tehran's District 1 for 6.6, 6.9, and 7.2 magnitude earthquakes. The simulation started by calculating the number of injured individuals, which was 28856, 73195 and 111463 people for each earthquake, respectively. The Simulations were performed for each scenario for a variety of rescuers (1000, 1500, 2000 rescuer). In comparison with contract net protocol (CNP), the standard time of rescue operations in the proposed approach includes at least 13% of improvement and the best percentage of recovery was 21 %. Interval uncertainty analysis and the comparison of the proposed strategies showed that an increase in uncertainty leads to an increased rescue time for CNP of 67.7 hours, and for strategies one to four an increased rescue time of 63.4, 63.2, 63.7, and 56.5 hours, respectively. Considering strategies in the task allocation process, especially spatial strategies, resulted in the optimization and increased flexibility of the allocation as well as conditions for fault tolerance and agent-based cooperation stability in USAR simulation system.
Sub-permafrost methane seepage from open-system pingos in Svalbard
Authors: Hodson Andrew J. , Nowak Aga , Hornum Mikkel T. , Senger Kim , Redeker Kelly , Christiansen Hanne H. , Jessen Søren , Betlem Peter , Thornton Steve F. , Turchyn Alexandra V. , Olaussen Snorre , Marca Alina
Published: November 2020

Abstract. Methane release from beneath lowland permafrost represents an
important uncertainty in the Arctic greenhouse gas budget. Our current
knowledge is arguably best developed in settings where permafrost is being
inundated by rising sea level, which means much of the methane is oxidised
in the water column before it reaches the atmosphere. Here we provide a
different process perspective that is appropriate for Arctic fjord valleys
where local deglaciation causes isostatic uplift to out pace rising sea
level. We describe how the uplift induces permafrost aggradation in former
marine sediments, whose pressurisation results in methane escape directly to
the atmosphere via groundwater springs. In Adventdalen, central
Spitsbergen, we show how the springs are historic features responsible for
the formation of open-system pingos and capable of discharging brackish
waters enriched with high concentrations of mostly biogenic methane (average
18 mg L−1). Thermodynamic calculations show that the methane
concentrations sometimes marginally exceed the solubility limit for methane
in water at 0 ∘C (41 mg L−1). Year-round emissions from the pingos
are described. During winter, rapid methane loss to the atmosphere occurs
following outburst events from beneath an ice blister. During summer, highly
variable emissions occur due to complex surface processes at the seepage
point and its inundation by surface runoff. In spite of this complexity, our
observations confirm that sub-permafrost methane migration deserves more
attention for the improved forecasting of Arctic greenhouse gas emissions.
Effect of gut microbiome on minor complications after a colonoscopy
Authors: Kim Jae Hyun , Choi Youn Jung , Kwon Hye Jung , Jung Kyoungwon , Kim Sung Eun , Moon Won , Park Moo In , Park Seun Ja
Published: November 2020

Background/Aims: Minor complications that might occur after colonoscopy, including abdominal discomfort, bloating, diarrhea, and constipation, could a barrier for patients to undergo a screening colonoscopy. In this study, we aimed to identify the effect of gut microbial diversity and composition on minor complications after colonoscopy.Methods: A total of 24 healthy subjects provided their stools before bowel preparation and on the 7th and 28th day after colonoscopy. On the 7th day after colonoscopy, the presence of minor complications was investigated using a questionnaire. We divided patients into 2 groups, the no complication group and complications group. The fecal microbial diversity, distribution, and composition were then compared between the groups.Results: Five of the 24 subjects reported that they had undergone minor complications after colonoscopy. Most of the symptoms were mild and self-limited, but 1 patient needed medication. Interestingly, the Firmicutes/Bacteroidetes ratio of the initial stool samples before bowel preparation in the complication group was significantly higher than that in no complication group. After bowel preparation, the Firmicutes/Bacteroidetes ratio of the complication group decreased, but not in the no complication group. The microbial diversity of the no complication group decreased after bowel preparation, but not in the complication group.Conclusions: The gut microbial composition and diversity before and after bowel preparation could be considered as one of the causes of minor complications after colonoscopy. Further studies are needed to delineate the role of gut microbiota in the occurrence of minor complications after colonoscopy.
Utilization of Trade Preferences in Zambia: Firm Specific Issues
Authors: Mulenga Mulenga Chonzi
Published: November 2020

Preferential agreements are intended to increase trade between countries involved. However, in reality, although the overarching purpose of these agreements in terms of market opening is often achieved, increases in trade is seldom realized. For countries like Zambia where data on trade via the preferential route are rarely captured, it is pertinent to analyze, from a firm’s perspective, the utilization of the existing agreements. This study set out to analyze the extent of Zambia’s utilization of trade preferences using both secondary and primary data sources. The secondary data establishes that despite these agreements having granted almost all Zambian exports duty-free and quota-free access, the country’s utilization rates have been low. This result is affirmed by the exporters and further validated by the key informants as both surveys establish that Zambian firms have not utilized the trade preferences effectively. They have attributed the low utilization of these preferences to internal and external challenges. The internal challenges include: lack of production capacity, poor infrastructure, poor knowledge of markets, and high transport costs. Externally, the challenges include: difficulties in meeting sanitary and phyto-sanitary measures, costly rules of origin, technical barriers to trade and cumbersome paperwork requirements. The country therefore, needs to address these challenges if it is to utilize these agreements effectively.
Personality, Parental Behavior, and Attachment to Close Friends
Authors: Ivanec Tea Pavin , Babojelić Antonia
Published: November 2020

The aim of this study was to examine the relationship between young women’s personality traits, perceived parental behavior of their parents, and the dimensions of attachment to close friends. Results generally indicated significant effects of personality traits and parental behavior on attachment to close friends. More specifically, agreeableness was a negative predictor of attachment anxiety, and neuroticism was a positive predictor of the same attachment dimension. Both agreeableness and extraversion were negative predictors of attachment avoidance. Parental behavior was predictive for attachment avoidance in close friendship, while there were no effects of parental behavior on attachment anxiety. Mothers’ supportiveness and restrictive control were negative predictors of attachment avoidance, whereby fathers’ support was a positive predictor of this attachment dimension. The results imply the importance of both personality and parental behavior as determinants of attachment to close friends and also suggest the need for further research of specific associations within the context of these broad theoretical constructs.
Kansschade: een bewogen leerstuk
Authors: den Hoed J.
Published: November 2020

Kansschade: een bewogen leerstuk. HR 19 juli 2019, ECLI:NL:HR:2019:1223 en Rb. Den Haag 8 januari 2020, ECLI:NL:RBDHA:2020:4

Zowel in het Srebrenica-arrest als in het Faro-vonnis, twee tamelijk verschillende zaken, is een veroordeling tot vergoeding van kansschade uitgesproken voor onzorgvuldig handelen. In zijn Srebrenica-uitspraak stelde de Hoge Raad de kleine, maar niet verwaarloosbare kans voor de bewuste groep mannelijke vluchtelingen om uit handen te blijven van Bosnische Serviërs (als Dutchbat naar behoren zou zijn opgetreden) vast op 10%, waar het hof nog was uitgekomen op 30%. De rechtbank kwam in de Faro-zaak tot een kleine, maar niet verwaarloosbare kans van 20% op een beter resultaat bij de destijds met Martinair gevoerde onderhandelingen als de Raad voor de Luchtvaart niet onzorgvuldig zou hebben gehandeld. Een algemeen, voor alle gevallen toepasbaar, minimumpercentage voor kansschade lijkt niet aanwijsbaar.
Tomada de decisão multicritério aplicada à biocombustíveis
Authors: Missaggia André Brum , Caetano Nattan Roberto , Silva Deoclécio Junior Cardoso da , Ruppelt Marcos Augusto Nogueira
Published: November 2020

Este artigo tem como objetivo analisar a aplicação de métodos multicritério em processos do setor de biocombustíveis. Foram identificados os segmentos nos biocombustíveis em que os métodos multicritérios têm sido aplicados, as palavras-chave mais utilizadas, os autores mais citados, o número de trabalhos publicados por ano, quantidade de periódicos citados, fator de impacto dos periódicos e detalhamento dos trabalhos mais relevantes por meio do uso de técnica bibliométrica. Entre as conclusões, verificou-se que o Analytic Hierarchy Process (AHP) é o método multicritério mais empregado, sendo utilizado de forma isolada e/ou combinada com outros métodos. Averiguou-se, também, que o segmento de aplicação mais proeminente é na avaliação de sistemas de cultivo de algas para a produção de biocombustível.
Spatial distribution and seasonal dynamics of non-biting moth flies (Diptera, Psychodidae) in confound conditions of a stable
Authors: Semelbauer Marek , Oboňa Jozef , Barta Marek , Mangová Barbara , Kozánek Milan
Published: November 2020

Many small Diptera adopted at some level endophilic life style, including man-made buildings. Stables create a specific type of microhabitat, which provides shady and relatively humid conditions in combination with excess of organic matter. Unlike the parasites (mosquitos, biting midges, etc.), the commensal fauna of stables is poorly studied. Moth flies (Psychodidae) were collected in cow stable located in Šenkvice, SW Slovakia. Special traps (derived from Malaise traps) were installed along the stable internal wall and in three different heights. In total, we recorded 6325 moth flies belonging to 8 species. The flight period lasted from spring to autumn. Seasonal dynamics was strongly influenced by rainfall and mean week temperature, e.g. high temperature in mid-summer caused drop in moth flies captures. The moth flies clearly preferred the ground and moderately preferred the interior of stable.
Stock Trading Classifier with Multichannel Convolutional Neural Network
Authors: Nascimento Davi , Costa Anna , Bianchi Reinaldo
Published: November 2020

Stock market forecasting has been a quite popular challenge in machine learning research. Recently, studies have been using deep learning techniques, such as Convolutional Neural Networks (CNN), to perform regression on the prices or classification on trading signal as an operation indication. However, they did not reach a satisfactory financial result. In this work we aim to design a financially profitable stock market method by proposing a novel approach called Multichannel CNN Trading Classifier (MCNN-TC). The model was evaluated using data from the Brazilian stock market. The results indicate a satisfactory financial trading performance compared to the Buy and Hold strategy and good classification metrics.
Classificação de Páginas de Petições iniciais Utilizando Redes Neurais Convolucionais Multimodais
Authors: Mota Caio , Lima Andressa , Nascimento André , Miranda Péricles , De Mello Rafael
Published: November 2020

A classificação e separação de documentos é uma etapa de extrema importância na análise de processos judiciais. Algoritmos de aprendizado profundo têm alcançado resultados promissores nesta tarefa, extraindo informações relevantes a partir dos textos destes documentos. No entanto, os documentos de processos judiciais têm se tornado cada vez mais heterogêneos, i.e. fotos, recibos, documentos de texto, etc., impactando diretamente a precisão na classificação. Este trabalho investiga o uso de redes convolucionais multimodais, combinando características extraídas de textos e imagens, para classificação de páginas de processos. Duas abordagens multimodais foram comparadas com quatro monomodais. Todos os algoritmos foram avaliados, em termos em acurácia e kappa, em uma base de dados composta por 117 processos judiciais. Os resultados mostraram que a abordagem que atingiu o melhor desempenho é multimodal, apresentando eficácia e eficiência na classificação de páginas de processos.
Death Registry Prediction in Brazilian Male Prisons with a Random Forest Ensemble
Authors: Formentin Nathan , Borges Eduardo , Lucca Giancarlo , Santos Helida , Dimuro Gracaliz
Published: November 2020

Brazil has the third-largest prison population globally, and it has been growing steadily for more than two decades. Constant growth and low jail investment generated significant problems, such as overcrowding and widespread diseases. This study proposes the construction of a Random Forest classifier to predict the occurrence of deaths in prisons. We extracted data from the National Survey of Penitentiary Information for the years 2015 to 2016. The best-fitted classifier achieved accuracy equals 87% being able to identify correctly up to 84% of deaths occurrences. In the present work, it was possible to establish a relationship between prisons' reality and the data mined, determining areas in need of investment in the penitentiary system.
Interaffection of Multiple Datasets with Neural Networks in Speech Emotion Recognition
Authors: Da Silva Ronnypetson , M. Filho Valter , Souza Mario
Published: November 2020

Many works that apply Deep Neural Networks (DNNs) to Speech Emotion Recognition (SER) use single datasets or train and evaluate the models separately when using multiple datasets. Those datasets are constructed with specific guidelines and the subjective nature of the labels for SER makes it difficult to obtain robust and general models. We investigate how DNNs learn shared representations for different datasets in both multi-task and unified setups. We also analyse how each dataset benefits from others in different combinations of datasets and popular neural network architectures. We show that the longstanding belief of more data resulting in more general models doesn’t always hold for SER, as different dataset and meta-parameter combinations hold the best result for each of the analysed datasets.
From Bag-of-Words to Pre-trained Neural Language Models: Improving Automatic Classification of App Reviews for Requirements Engineering
Authors: Araujo Adailton , Golo Marcos , Viana Breno , Sanches Felipe , Romero Roseli , Marcacini Ricardo
Published: November 2020

Popular mobile applications receive millions of user reviews. Thesereviews contain relevant information, such as problem reports and improvementsuggestions. The reviews information is a valuable knowledge source for soft-ware requirements engineering since the analysis of the reviews feedback helpsto make strategic decisions in order to improve the app quality. However, due tothe large volume of texts, the manual extraction of the relevant information is animpracticable task. In this paper, we investigate and compare textual represen-tation models for app reviews classification. We discuss different aspects andapproaches for the reviews representation, analyzing from the classic Bag-of-Words models to the most recent state-of-the-art Pre-trained Neural Languagemodels. Our findings show that the classic Bag-of-Words model, combined witha careful analysis of text pre-processing techniques, is still a competitive model.However, pre-trained neural language models showed to be more advantageoussince it obtains good classification performance, provides significant dimension-ality reduction, and deals more adequately with semantic proximity between thereviews’ texts, especially the multilingual neural language models.
Aprendizado Profundo Aplicado na Previsão de Receita Tributária Utilizando Variáveis Endógenas
Authors: Silva Priscila , Figueiredo Karla
Published: November 2020

A previsão de receita tributária para a gestão de um estado em situação de crise econômico-financeira, caso do estado do Rio de Janeiro, tornou-se uma tarefa fundamental e desafiadora para as secretarias de fazenda e planejamento dos Estados, pois há incertezas econômicas e políticas que afetam a série temporal. Nesse sentido, este trabalho inicia o projeto de investigação e uso de modelos mais novos e acurados de Machine Learning, como Long Short-Term Memory (LSTM), para prever a receita de tributos. Os resultados apresentam erro relativo menor que 1%, para previsão do ICMS, indicando desempenho superior às previsões realizadas pela SEFAZ-RJ e aos modelos MLP, usados para efeitos de comparação.
Temporal Analysis and Visualisation of Music
Authors: Misael Luan , Forster Carlos , Fontelles Emanuel , Sampaio Vinicius , França Mardônio
Published: November 2020

This paper proposes a temporal analysis for music metadata using a generative probabilistic model for collections the discrete datasets such as text corpora. This method is also a topic model that is used for discovering abstract topics from a collection of documents. The method is then applied to audio metadata and song lyrics extracted with Echo Nest® engine, Spotify® Lyrics Genius® API. Song data time series are generated by grouping data items by release date, genre and dominant topics (from LDA analysis). Using a technique from Network Theory we visualise how these topics, in this case, genres, are related to each other through time.
The Winograd Schemas from Hell
Authors: Cozman Fábio , Munhoz Hugo
Published: November 2020

The Winograd Challenge has been advocated as a test of computer understanding with respect to commonsense reasoning. The challenge is based on Winograd Schemas: sentences that contain correferential ambiguities. Most Winograd Schemas are relatively easy for human subjects, and today the best computer systems for the Winograd Challenge can work close to human performance. In this paper, we examine the assumptions behind the Winograd Challenge, and investigate how far we can push the difficulty level of Winograd Schemas, proposing various strategies to build really challenging schemas.
Comparative Study of Photovoltaic Power Forecasting Methods
Authors: Pelisson Angelo , Covoes Thiago , Spengler Anderson , Jaskowiak Pablo
Published: November 2020

Electricity consumption is growing rapidly worldwide. Renewable energy resources, such as solar energy, play a crucial role in this scenario, contributing to satisfy demand sustainability. Although the share of Photovoltaic (PV) power generation has increased in the past years, PV systems are quite sensitive to climatic and meteorological conditions, leading to undesirable power production variability. In order to improve energy grid stability, reliability, and management, accurate forecasting models that relate operational conditions to power output are needed. In this work we evaluate the performance of regression methods applied to forecast short term (next day) energy production of a PV Plant. Specifically, we consider five regression methods and different configurations of feature sets. Our results suggest that MLP and SVR provide the best forecasting results, in general. Also, although features based on different solar irradiance levels play a key role in predicting power generation, the use of additional features can improve prediction results.
Inducing selfish agents towards social efficient solutions
Authors: Schapke João , Bazzan Ana
Published: November 2020

Many multi-agent reinforcement learning (MARL) scenarios lead towards Nash equilibria, which is known to not always be socially efficient. In this study we aim to align the social optimization objective of the system with the individual objectives of the agents by adopting a central controller which can interact with the agents. In details, our approach establishes a communication channel between reinforcement learning agents, and a controller implemented with metaheuristics. The interaction benefit the convergence of both algorithms. Further, we evaluate our method in repeated games with high price of anarchy and show that our approach is able to overcome much of the issues caused by the non-cooperative behaviour of the agents and the non-stationary effects they cause.
Impact of Unusual Features in Credit Scoring Problem
Authors: Vercosa Luiz Felipe , Lira Rodrigo , Monteiro Rodrigo , Silva Kleber , Magalhaes Jailson , Maciel Alexandre , Bezerra Byron L. D. , Bastos-Filho Carmelo
Published: November 2020

Standard features used for Credit Scoring includes mainly registration and financial data from customers. However, exploring new features is of great interest for financial companies, since slight improvements in the person score directly impact the company revenue. In this work, we categorize features from open credit scoring datasets and compare them with the features found in a real company dataset. The company dataset contains unusual feature groups such as historical, geolocation, web behavior, and demographic data. We performed bivariate tests using the Kolmogorov-Smirnov metric and features to assess the performance of the particular feature groups. We also generated a score of good payer by using AdaBoost, Multilayer Perceptron, and XGBoost algorithms. Then, we analyzed the results with different metrics and compared them with the real company results. Our main finding was that these features added a small improvement to current datasets. We also identified the most promising feature groups and noticed that the tuned XGBoost performed better than the company solution in three out of four deployed metrics.
Evaluating an Aspect Extraction Method for Opinion Mining in the Portuguese Language
Authors: Cardoso Breno , Pereira Denilson
Published: November 2020

The opinion issued by consumers of products and services has become increasingly valued, both by other consumers and by companies. The automatic interpretation of review texts to generate information is of paramount importance. With opinion mining at the aspect level, it is possible to extract and summarize opinions about different components of a product or service. This paper evaluates the behavior of a method for extracting aspects using natural language processing tools for the Portuguese language. The aim is to investigate the maturity of the tools for Portuguese compared to the already consolidated tools for the English language. The evaluation was carried out in three datasets from two different domains with original texts in Portuguese and their translations into English, and vice versa, and the results indicate that there is no difference between languages.
Labor Accidents in Brazil: a Descriptive Analysis
Authors: Giacomelli Daniela , Naldi Murilo , Faria Elaine
Published: November 2020

Labor accidents cause several misfortunes, such as inconvenience to the injured ones, loss of laborproductivity, and public spending on aid and accident compensation. This work aims to search and characterize groupsof labor accidents, granting interpretability to the obtained results, to extract information that can be relevant to publicmanagers. The method proposed in this work consists of the following steps: data pre-processing; the applicationof two hierarchical clustering algorithms, HDBSCAN * and COBWEB; the evaluation of results using the SimplifiedSilhouette. The research demonstrated the susceptibility of male workers, focused on ages between 18 and 34 years old,with labor accidents that caused injuries on the fingers, by handling machines and equipment or manual tools, followedby those activities such as fishing. Considering clusters majorly composed by female victims, those related to work incellulose, paper, and related products stand out. Moreover, fingers are the most affected part, featured for incidentscaused by the handling of chemical, biological, or hand tools.
A Sentiment Analysis of Brazilian Elections Tweets
Authors: Cristiani André , Lieira Douglas , Camargo Heloisa
Published: November 2020

The internet connection is present in people’s lives all the time, through smartphones, tablets, computers, among others. The use of social networks is increasingly common around the world. Many companies and people use them to spread products and services and publish opinions, facts that have turned the social networks into powerful sources of information on various topics. Identifying these feelings is a great strategy for many types of decision making. Thus, the purpose of this paper is to collect messages from a specific social network, in this case Twitter, referring to the 2018 Brazilian presidential elections and classify them as: positive, negative and neutral, in order to discover a possible relationship between opinions of social network users and the final outcome of the elections. For this, a corpus was built, preprocessed and evaluated by two different machine learning approaches: Naive Bayes and SVM (Support Vector Machine). The results showed that this social network is a good source of information to perform sentiment analysis and that the number of tweets classified as positive have a strong relationship with the researchers and the final result of the 2018 elections.