Miracle-dz/UniFAR-FTUs huggingface dataset:
Publicity and perceptions of risk: The effects of HRO naming and shaming on sovereign credit rating

Abstract Previous scholarship has demonstrated that shaming by human rights organizations produces economic consequences. For example, human rights shaming by international organizations negatively affects foreign direct investment (FDI), decreases exports, and redirects foreign aid received. The relationship between shaming and sovereign credit, however, has yet to be studied. States greatly rely on their ability to access cheap international credit, as evidenced by the fact that newly issued sovereign debt outpaced new foreign investment by almost $3 trillion in 2017. Understanding the relationship between human rights-related advocacy efforts and a state’s access to this valuable source of capital is critical for recognizing the effects naming and shaming can have on creditors. We therefore ask: Does naming and shaming by human rights organizations have a negative impact on the target state’s sovereign credit rating? We find that increased naming and shaming leads to a decrease in a state’s sovereign credit rating.
Network‐wide traffic speed forecasting: 3D convolutional neural network with ensemble empirical mode decomposition

Accurate traffic speed forecasting is one of the most critical tasks in proactive traffic management and the deployment of advanced traveler information systems. This paper proposes a hybrid forecasting approach named DeepEnsemble by integrating the three‐dimensional convolutional neural network (3D CNN) with ensemble empirical mode decomposition (EEMD). There are four steps in this hybrid approach. First, EEMD is adopted to decompose the complex traffic speed time series data with noise into several intrinsic mode functions (IMFs) and a residue. Second, a three‐dimensional tensor is established and fed into 3D CNN for prediction. Third, the output of 3D CNN prediction is obtained by a linear combination of the results of all components. Finally, the 3D CNN prediction output, external features, and historical features are fused to predict the network‐wide traffic speed simultaneously. The proposed DeepEnsemble approach is tested on the three‐month traffic speed series data of a real‐world large‐scale urban expressway network with 308 traffic flow detectors in Beijing, China. The experimental results indicate that DeepEnsemble outperforms the state‐of‐the‐art network‐wide traffic speed forecasting models. 3D CNN learns temporal, spatial, and depth information better than 2D CNN. Moreover, forecasting accuracy can be improved by employing EEMD. DeepEnsemble is a promising model with scalability and portability for network‐wide traffic speed prediction and can be further extended to conduct traffic status monitoring and congestion mitigation strategies.
Science Mapping of the Knowledge Base on Sustainable Leadership, 1990–2018

The rise of sustainable development as a field of applied research has been observed across a wide range of disciplines. Successful change towards sustainability in organizations and societies requires leadership to provide a vision, set direction, and motivate people to move towards new goals. Thus, sustainable leadership is emerging as a new domain of study within the field of management. This review of research employed science mapping tools to examine 952 Scopus-indexed documents explicitly concerned with sustainable leadership. The goals of the review were to document the size, growth trajectory, and geographic distribution of this literature, identify key journals, authors, and documents, analyze the intellectual structure of this knowledge base, and highlight emerging topics. The review documented a modest-sized knowledge base of recent vintage, concentrated in Western developed societies but global in scope. Six Schools of Thought were identified within this knowledge base, one of which—Sustainable Leadership—was singled out for attention. As the first bibliometric review of research on sustainable leadership, this review provides a reference for scholars entering this domain, as well as guidance with respect to high value frameworks, foci for future research, and practical implications.
Characterizing ventilation events in an anoxic coastal basin: Observed dynamics and the role of climatic drivers

Restricted horizontal exchange and vertical stratification restrict ventilation of bottom waters in many coastal systems, leading to stagnant basin water conditions. Dense inflows from oceanic sources can lead to dramatic changes in basin‐scale properties over very short timescales. Here, we used a semi‐enclosed coastal basin with deep‐anoxia (Lough Furnace) as a test bed, in order to discern estuary‐ocean exchange dynamics that lead to irregular and ephemeral deep‐water ventilations. Measured densities and current profiler‐based estimates of volume fluxes were used to compute typical renewal times of individual water masses in the stratified inner basin. Renewal timescales were primarily determined by freshwater flux and the spring‐neap tidal cycle. The deployment period culminated with observations of a ventilation of the basin water which had been stagnant for over 2.5 yr. Entrainment of ambient resident water doubled the volume of the dense plume and diluted its oxygen content. Following ventilation, the volumetric extent of anoxia expanded by 20% within several months, owing to uplifting of old basin water and oxygen consumption in the new basin water. Founded on these observations, a predictive model was constructed relying only on freshwater, atmospheric pressure, and wind data and successfully recreated ventilation events over the past decade. Hindcasting the model back multiple decades implied contrasting periods of higher and lower frequency variability in ventilation occurrence. This model offers a diagnostic tool for assessing how climatic change may influence the oxygen climate in systems that experience contrasting regimes of suboxia and ventilation.
User Centric ICT Model for Supply Chain of Horticultural Crops in India

Considering the immediate need to integrate the supply chain of horticultural crops by providing needbased information to different players mainly farmers, the paper has analyzed various aspects like information needs, sources of information and their reliability, factors responsible for willingness to pay for information and parameters of an ideal information dissemination system under the Indian conditions. The study is based on a sample of farmers from three districts of Madhya Pradesh and has revealed that farmers are the vital link in the supply chain of horticultural crops with a vast range of information requirements. This information may be delivered effectively using ICT, mainly mobile phones, which are being utilized by two-thirds of the farmers in the study area. Age, education level and irrigation have been found the factors defining the willingness of a farmer to pay for having access to information. To promote use of ICT for the effective and timely dissemination of information, a user-centric model has been envisaged which has suggested adoption of an integrated approach for information delivery to farmers. The study has also made some recommendations like increasing the reach of mobile phones, making ICT more farmer-friendly, and encouraging the corporate sector in having revenue model for information dissemination as majority of the farmers’ are willing to pay.
Struggles Around Representation and in/Visibility in Everyday Migrant Irregularity in Sweden

Abstract This article explores tensions between visibility and invisibility of irregularity in Sweden. It focuses on irregular migrants’ social rights and their self-representation. The analysis builds mainly on ethnographic material mapping migrants’ and activists’ experiences of seeking asylum, living in irregularity and/or getting involved in struggles for migrants’ rights in Sweden. Furthermore, material from news media and political debate on migration and asylum rights is used to contextualise the interview material. The analysis suggests that the lived experiences of irregularity are shaped not only between systematic invisibility and violent forms of visibility but also visibility in terms of increased self-representation and autonomy. Furthermore, the analysis shows a shift towards increased social rights for irregular migrants from mid-2000s to 2013 and the establishment of irregular migrants as a social category and as political actors in their own right. However, the article also points towards increased repression against this ‘new’ category.
Plant‐mediated methane transport in emergent and floating‐leaved species of a temperate freshwater mineral‐soil wetland

Methane flux from freshwater mineral‐soil (FWMS) wetlands and its variability among sites is largely modulated by plant‐mediated transport. However, plant‐mediated transport processes are rarely resolved in land surface models and are poorly parametrized for plants commonly found in FWMS wetlands. Here, relationships between methane flux and CO2 uptake, as well as plant conductance of methane were evaluated for three plant species and two characteristic functional types: emergent (narrow‐leaved cattail) and floating‐leaved (American lotus and water lily). We found significant but contrasting correlations between methane flux and CO2 uptake in cattails (r2 = 0.51, slope = −0.16, during morning) and water lily (r2 = 0.32, slope = 0.064, after midday). This relationship was not significant in American lotus, showing that stomata regulation of methane fluxes is species‐specific and not generalizable across the floating‐leaved plant functional type. Conductance of methane per leaf area showed distinct seasonal dynamics across species. Conductance was similar among the floating‐leaved species (6.2 × 10−3 m d−1 in lotus and 7.2 × 10−3 m d−1 in water lily) and higher than conductance in the emergent species (2.7 × 10−3 m d−1). Our results provide direct observations of plant conductance rates and identify the vegetation parameters (leaf area, stomatal conductance) that modify them. Our results further suggest that models of methane emissions from FWMS should parameterize plant‐mediated transport in different plant functional types, scaled by leaf area and with variable seasonal phenological dynamics, and consider possible species‐specific mechanisms that control methane transport through plants.
Maternal Pre-Pregnancy Body Mass Index and Gestational Weight Gain Are Associated with Differences in Infant Gut Microbiota: Results from Brazilian Prospective Birth Cohort

To evaluate the association of pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) on infant gut microbiota diversity and abundance and the role of breastfeeding on this association. Prospective cohort conducted in Rio de Janeiro, Brazil. Maternal pre-pregnancy BMI (< 25; ≥ 25 kg/m², normal/excessive) and GWG adequacy (adequate; excessive) were the exposures and breastfeeding practice status (exclusively breastfeeding EBF; predominant/complementary feeding PCF) was analyzed as an effect modifier. Infant stool samples were collected for 56 infants between 26–45 days. Samples were sequenced using 16S rRNA gene sequencing (MiSeq). Analysis included alpha diversity indexes (Shannon, Faith-PD, and Observed species), beta diversity metrics and Wilcoxon-Mann-Whitney Test, linear regression, permutational multivariate analysis of variance and linear discriminant analysis effect size. A higher median alpha diversity in infants born from mothers with excessive GWG was observed (Mann-Whitney Test: P = 0.005) and infants born from mothers with excessive GWG were positively associated with alpha diversity (β = 0.351; SE = 0.146; p-value = 0.020). Gut microbiota of infants born from mothers with excessive pre-pregnancy BMI were enriched with Dialister genus and Lactobacillus Ruminis, Haemophilus Parainfluenzae and Veillonella Parvula species and those born from mother with excessive GWG had higher abundance of Staphylocococcus genus, Staphylococcaceae family, Bacillales order and Bacilli class. Infant gut microbiota diversity and abundance did not differ according to combined categories of pre-pregnancy BMI and breastfeeding status and GWG and breastfeeding. Maternal gestational weight gain was associated with diversity of the infant gut microbiota. Breastfeeding did not an effect modifier in this association. Foundation for the Support of Research of the State of Rio de Janeiro, National Council for Scientific and Technological Development and Columbia University Grant.
onist Large Vocabulary Speech Recognition

:Abstract: ln this paper, the problem of large vocabulary word recognition is addressed from a :conneclionisl perspective. The problem is not only of practical interest but also ol scientific importance, §ince a workable solulion must integrate pattern recognition under consideration ol sequential, symbolic constraints. We have developed two large vocabulary word recognition systems based on different speech recognition philosophies. One of the systems exploits ihe power of neural nehvorks in performing accurate classification, lhe other the power of producing good non-linear function approximation and signal prediction. We present each system's operation and evaluate ils performance. Both achieved respectable recognition scores in excess of 907o correct lor vocabularies of up to 5000 words. We suggesl further avenues towards improvement of either system and in the process discuss the relative strengths ol either approach.
Subsidize farmers or bioenergy producer? The design of a government subsidy program for a bioenergy supply chain

The success of the bioenergy industry will depend, in part, on enough biomass feedstocks being grown. To increase the reliability of feedstocks supply, a government can offer two types of subsidy program: a farmer subsidy program (FSP) and a bioenergy producer subsidy program (PSP). We develop models to analyze the optimal subsidy program by capturing the interactions between the government, the bioenergy producer, and the farmers. The models incorporate the subsidy budget constraint, the environmental benefits from the use of bioenergy, the farmer's risk aversion and land capacity constraint, as well as the yield uncertainty of feedstocks. The findings reveal that both FSP and PSP are effective as long as the farmers' land capacity exceeds a threshold. If both the subsidy budget and the land capacity are sufficiently large, PSP outperforms FSP; if only the subsidy budget is limited, FSP is better; if only the land capacity is limited, FSP and PSP are equivalent. Counter‐intuitively, we find that PSP always favors farmers more, while FSP favors the bioenergy producer more under certain conditions. Also, we find that FSP can better mitigate risk than PSP when yield uncertainty is high. Lastly, insights for policy makers to promote bioenergy development are highlighted.
Software Defect Regions Identification Based on Behavior Mining

Random testing is a widely used testing technique, and adaptive random testing has enhanced the performance of random testing recently. The research results demonstrate that the improvement depends on the characters of the software defect region. A method that depicts the distribution of software defect region in the input region based on testing is proposed in this paper, and the method that describes the characteristics of the software defect region. The experimental results show that testing constraint reveals the mechanism of software defect trigging and propagation.
Export vs. FDI Behavior of Heterogenous Firms in Heterogenous Markets: Evidence from Sovenia

This paper adds a new dimension to the recent literature on relationship beween firm's heterogeneity in terms of total factor productivity and its dynamic exports vs. FDI decision, namely the heterogeneity of export markets. We show that higher productivity of investing firms relative to just exporters is not inevitably uniform. Exploiting a complete set of Slovenian exporting firms in the period 1994 - 2002, we confirm the tendency of higher productivity firms to engage in FDI only for FDI conducted in high wage countries. In addition, we find no evidence in favor of either market-seeking (horizontal) or factor-seeking (vertical) motive for FDI. While survey results suggest trade-promotion motive to be just as important, we find little evidence in favor of efficiency of this strategy.
Research on variable mass control of series manipulator based on linear active disturbance rejection control

The series manipulator of the demolition robot has different working postures and large self-weight so that the bearing mass of the joint hydraulic cylinder is a variable value, and the change of mass affects the dynamic characteristics of the valve-controlled hydraulic cylinder system. In this paper, an equivalent mass estimation method of the big-arm joint hydraulic cylinder is given, and the natural frequency range of the big-arm hydraulic cylinder-load system is calculated. In order to suppress the influence of the change of the natural frequency and external disturbance of the hydraulic cylinder on the system, the linear active disturbance rejection control is adopted in the closed-loop position control. The simulation results show that the change of load mass of the joint hydraulic cannot be ignored when designing the joint position controller of multi-joint hydraulic manipulator. And the simulation tests prove that the linear active disturbance rejection control strategy keeps good dynamic characteristic and steady-state accuracy for the change of natural frequency and external disturbance of hydraulic cylinder and has good tracking performance for periodic sinusoidal signal. Linear active disturbance rejection control is robust in the variable mass control of the manipulator and meets the requirements of the joint position control of the heavy-duty hydraulic manipulator.
Can Machines Learn to Detect Fake News? A Survey Focused on Social Media

Through a systematic literature review method, in this work we searched classical electronic libraries in order to ﬁnd the most recent papers related to fake news detection on social medias. Our target is mapping the state of art of fake news detection, deﬁning fake news and ﬁnding the most useful machine learning technique for doing so. We concluded that the most used method for automatic fake news detection is not just one classical machine learning technique, but instead a amalgamation of classic techniques coordinated by a neural network. We also identiﬁed a need for a domain ontology that would unify the different terminology and deﬁnitions of the fake news domain. This lack of consensual information may mislead opinions and conclusions.
REFINED TCP PERFORMANCE EVALUATION WITH SIMPLE MODELING

This paper presents analytical results of a TCP (Transmission Control Protocol) model based on a Markov chain, refining the previous works on performance evaluation of one bulk transfer TCP flow among exogeneous traf- fic. While most of these works are mainly focused on the mean throughput evaluation, our model allows with low cost, a study of many other performance measures and thus a more detailed study of the TCP behavior.
Is It Human? The Role of Anthropomorphism as a Driver for the Successful Acceptance of Digital Voice Assistants

The market of digital voice has grown significantly over the recent years. Big players like Amazon, Google, Apple, Microsoft and Samsung are focusing on the development and expansion of their assistants. Especially smart speakers are on the rise but also in smartphone integrated voice applications are getting more popular. The main characteristics of this new technology are both elements of human-computerinteraction and especially the attribution of human characteristics. Although there is an increase of the number of current users as well as of consumers intending to use digital voice assistants in the future, drivers and barriers of digital voice assistants have not yet been sufficiently empirically investigated, especially concerning the phenomenon of anthropomorphism. This study points to additional key factors that are important to foster broader acceptance. Our empirical study is based on the UTAUT2 and highlights the importance of anthropomorphism in relation to other determinants known from the literature.
Motion Primitives for Human Manipulation Actions and their Role in Multimodal Human-Robot Communication

Communication is critical when humans and robots collaborate. But for the communication to be effective it needs to be multimodal. In this work we study manipulation actions and their role in human-robot communication. First, we propose a set of motion primitives that can be seen as the building blocks from which the manipulation actions are composed. We next show that these primitives describe a large proportion of activities of daily living observed in a corpus we collected. Next, the average motion trajectories for the proposed primitives are obtained by conducting another human study. These profiles can be used to determine the sequence of the human motions within a given action. By considering the primitives within the Motion Description Language (MDL) framework, we discuss how our approach can be applied to enable robots to understand human actions and to appropriately respond to them.
Noteworthy records of Jaguar Panthera onca in Guatemala

The jaguar is the largest terrestrial carnivore in America. According to the International Union for the Conservation of Nature, its conserva- tion status is “Near Threatened” in its distribution range. In Guatemala, the jaguar is mainly distributed in the Maya Biosphere Reserve (MBR). In the years 2016 and 2018, camera-trapping studies were conducted in the San Miguel La Palotada-El Zotz Protected Biotopo (BPSMPZ) and in Yaxha Nakum Naranjo National Park (PNYNN), respectively; both core zones of the MBR. Eight camera-trap stations were installed in BPSMPZ and 5 in PNYNN during the dry season, with at least 90 trap-days/nights in each site. In BPSMPZ, one adult jaguar of undetermined sex was recorded in one of the eight sampling stations installed; in PNYNN, there were 22 records (independent events) of at least 6 adult individuals (1 female, 3 males, 2 of undetermined sex) in three of the five sampling stations installed. This work reports important records on the presence of jaguars in core zones currently under pressure from human activities conducted within the southern limits of the MBR. Maintaining the integrity of these two areas is imperative to preserve this species in the MBR.