Miracle-dz/UniFAR-FTUs huggingface dataset:
The Almon M-estimator for the distributed lag model in the presence of outliers

Abstract The Almon technique is a widely used estimation procedure for the distributed lag model (DLM) to encounter the problems associated with direct application of the ordinary least squares method to this model. The Almon estimator may be sensitive to outliers in the y-direction. This study is aimed to propose a robust estimator for parameter vector of the DLM when data set is contaminated with outliers. Moreover, this study proposes the robust t-tests and confidence intervals for the lag coefficients. Performance of our proposed estimator is evaluated through the Monte Carlo simulations by comparing the estimated mean squared error while the performance of t-tests and confidence intervals is evaluated using the null rejection rates and coverage, respectively. The simulation results reveal an attractive performance of the proposed methods in the presence of outliers in the y-direction.
Convergence theorems of a new multiparametric family of Newton-like method in Banach space

In this work, we have considered a new multi-parametric family of modified Newton-like methods(MNL) of order three to approximate a zero of a nonlinear operator in $mathbb{B}$-space (Banach space). Here, we studied the semilocal convergence analysis of this family of methods by using a new type of majorant condition. Note that this majorant condition generalizes the earlier majorant conditions used for studying convergence analysis of third order methods. Moreover, by using second-order directional derivative of the majorizing function we obtained an error estimate. We also established relations between our majorant condition and assumption based on Kantorovich, Smale-type and Nesterov-Nemirovskii-type, that will show our result generalize these earlier convergence results.
Consistent Representation Learning Across Modalities for Zero-Shot Image Recognition

Zero-shot learning (ZSL) recently has drawn widespread attention due to the demand for scalability of object recognition in real scenes. Existing approaches typically focus on directly learning various mapping functions from the visual space to the semantic space or vice versa. However, these methods fail to explicitly capture consistent representations reflecting the nature of different modalities of the same object, which results in the deterioration of the domain shift problem in the ZSL context during the testing stage. To this end, a consistent representation learning mechanism across visual modalities and the associated semantic modalities based on common subspace learning is proposed in this paper. We further impose an orthogonal constraint on the subspace for informative representations, as well as ℓ21-norm regularization terms on projection matrices for automatic feature selection. Finally, an iterative process based on the ALM algorithm with an alternating direction strategy is displayed to resolve the proposed formulation. Extensive experimental results on four popular datasets demonstrate that our algorithm is promising.
Carbon dioxide fluxes and carbon balance of an agricultural grassland in southern Finland

Abstract. A significant proportion of the global carbon emissions to the atmosphere originate from agriculture. Therefore, continuous long-term monitoring of CO2 fluxes is essential to understand the carbon dynamics and balances of different agricultural sites. Here we present results from a new eddy covariance flux measurement site located in southern Finland. We measured CO2 and H2O fluxes at this agricultural grassland site for 2 years, from May 2018 to May 2020. In particular the first summer experienced prolonged dry periods, which affected the CO2 fluxes, and substantially larger fluxes were observed in the second summer. During the dry summer, leaf area index (LAI) was notably lower than in the second summer. Water use efficiency increased with LAI in a similar manner in both years, but photosynthetic capacity per leaf area was lower during the dry summer. The annual carbon balance was calculated based on the CO2 fluxes and management measures, which included input of carbon as organic fertilizers and output as yield. The carbon balance of the field was −57 ± 10 and −86 ± 12 g C m−2 yr−1 in the first and second study years, respectively.
Explainable AI methods in cyber risk management

Artificial intelligence (AI) methods are becoming widespread, especially when data are not sufficient to build classical statistical models, as is the case for cyber risk management. However, when applied to regulated industries, such as energy, finance, and health, AI methods lack explainability. Authorities aimed at validating machine learning models in regulated fields will not consider black‐box models, unless they are supplemented with further methods that explain why certain predictions have been obtained, and which are the variables that mostly concur to such predictions. Recently, Shapley values have been introduced for this purpose: They are model agnostic, and powerful, but are not normalized and, therefore, cannot become a standardized procedure. In this paper, we provide an explainable AI model that embeds Shapley values with a statistical normalization, based on Lorenz Zonoids, particularly suited for ordinal measurement variables that can be obtained to assess cyber risk.
Effects of Non-Speech Auditory Cues on Control Transition Behaviors in Semi-Automated Vehicles: Empirical Study, Modeling, and Validation

ABSTRACT In semi-automated vehicles, non-speech sounds have been prevalently used as auditory displays for control transitions since these sounds convey urgency well. However, there are no standards of specifications for warning sounds so that diverse non-speech sounds are being employed. To shed light on this, the effects of different non-speech auditory warnings on driver performance were investigated and quantified through the experimental study and human performance modeling approaches. Twenty-four young drivers drove in the driving simulator and experienced both handover and takeover transitions between manual and automated modes while performing a secondary task. The reaction times for handover and takeover, mental workload, and subjective responses were reported. Overall, a traditional warning sound with many repetitions and an indicator sound with decreasing polarity outperformed and were preferred. Additionally, a mathematical model, using the Queuing Network-Model Human Processor (QN-MHP) framework, was applied to quantify the effects of auditory warnings’ acoustic characteristics on drivers’ reaction times in response to takeover request displays. The acoustic characteristics, including the fundamental frequency, the number of repetitions, and the range of dominant frequencies were utilized in modeling. The model was able to explain 99.7% of the experimental data with a root mean square error (RMSE) of 0.148. The present study can contribute to establishing standards and design guidelines for takeover request displays in semi-automated vehicles.
Artificial Intelligence for Student Assessment: A Systematic Review

Artificial Intelligence (AI) is being implemented in more and more fields, including education. The main uses of AI in education are related to tutoring and assessment. This paper analyzes the use of AI for student assessment based on a systematic review. For this purpose, a search was carried out in two databases: Scopus and Web of Science. A total of 454 papers were found and, after analyzing them according to the PRISMA Statement, a total of 22 papers were selected. It is clear from the studies analyzed that, in most of them, the pedagogy underlying the educational action is not reflected. Similarly, formative evaluation seems to be the main use of AI. Another of the main functionalities of AI in assessment is for the automatic grading of students. Several studies analyze the differences between the use of AI and its non-use. We discuss the results and conclude the need for teacher training and further research to understand the possibilities of AI in educational assessment, mainly in other educational levels than higher education. Moreover, it is necessary to increase the wealth of research which focuses on educational aspects more than technical development around AI.
Between approval and disapproval: Citizens’ views on the invasive tree Ailanthus altissima and its management

While cities are invasion hotspots, the view of urban residents on non-native species is critically understudied – an important knowledge gap since strategies on biological invasions could gain power by integrating human values, attitudes and perceptions. How citizens perceive the non-native tree Ailanthus altissima (tree of heaven) is unknown despite its abundance in many cities globally and its classification as invasive in many countries. In a quantitative survey with closed questions, we analysed (i) whether residents of Berlin, Germany knew the widespread species, (ii) how they perceived it in different urban situations, (iii) how they accepted different management strategies of it, and (iv) how the sociodemographic background of respondents predicted their preference and acceptability ratings. In total, we surveyed 196 respondents. Most respondents recognized the tree in a photograph, but few provided its correct name. Citizens’ preferences differed significantly among four urban contexts in which the species was shown, with prevailing approval for trees as a component of designed green spaces and less pronounced preferences for wild-grown trees in other urban spaces. When respondents were asked to indicate how the tree should be managed (three options), we found the most support for removal in problematic cases (‘adaptive on-site’ strategy); some support was found for the ‘leave alone’ strategy and least support for the ‘complete removal’ management strategy. Practitioners with expertise in urban landscaping were more critical of Ailanthus than laypeople. Ordinal logistic regression analyses showed that respondents with a ‘close to nature’ behaviour and attitude had a more positive view on Ailanthus and expressed more support for ‘leave alone’ management. Results demonstrate the importance of citizens’ context dependent views about a widespread invasive species, spanning from approval to disapproval in NeoBiota 66: 1–30 (2021) doi: 10.3897/neobiota.66. 63460 https://neobiota.pensoft. net Copyright Ingo Kowarik et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. RESEARCH ARTICLE Advancing research on alien species and biological invasions A peer-reviewed open-access journal
Measurements of Total OH Reactivity During CalNex‐LA

Total OH reactivity was measured during the California Research at the Nexus of Air Quality and Climate Change field campaign at the Pasadena ground site using a turbulent flow tube reactor with laser‐induced fluorescence detection of the OH radical. Collocated measurements of volatile organic compounds (VOCs), inorganic species, and meteorological parameters were made and used to calculate the total OH reactivity, which was then compared to the measured values. An analysis of the OH reactivity measurements finds that although the measured reactivity correlated well with the calculated reactivity, the measurements were consistently greater than the calculations for all times during the day, with an average missing OH reactivity of 8–10 s−1, accounting for approximately 40% of the measured total OH reactivity. An analysis of correlations with both anthropogenic tracers of combustion and oxygenated VOCs as well as air trajectories during the campaign suggest that the missing OH reactivity was likely due to a combination of both unmeasured local emissions and unmeasured oxidation products transported to the site. Approximately 50% of the missing OH reactivity may have been due to emissions of unmeasured volatile chemical products, such as pesticides, cleaning agents, and personal care products.
Precisely Applying TiO2 Overcoat on Supported Au Catalysts Using Atomic Layer Deposition for Understanding the Reaction Mechanism and Improved Activity in CO Oxidation

For TiO2 supported Au catalysts, the Au particle size and the interfacial perimeter sites between Au particles and the TiO2 support both play important roles in CO oxidation reaction. However, changing the Au particle size inevitably accompanied by the change of the perimeter length makes it extremely difficult to identify their individual roles. Here we reported a new strategy to isolate them by applying TiO2 overcoat to Au/Al2O3 and Au/SiO2 catalysts using atomic layer deposition (ALD) where the new Au–TiO2 interfacial length was precisely tuned to different degrees while preserving the particle size. High resolution transmission electron microscopy (HRTEM), atomic force microscopy (AFM), and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) measurements of CO chemisorption all confirmed that the TiO2 overcoat preferentially decorates the low-coordinated sites of Au nanoparticles and generates Au–TiO2 interfaces. In CO oxidation, we demonstrated a remarkable improvement of the catalyt.
Executive Power Sharing in the Face of Civil War

Scholars have debated whether executive power sharing can secure peace in multiethnic states, but concerns about endogeneity due to reverse causation render this a difficult problem for empirical analyses. In the absence of a suitable instrumental variable, I explore an actor-based approach by studying a simple formal model. This highlights the conditions under which governments are likely to share power with a domestic challenger depending on the threat of violence. I then formulate a statistical “strategic selection” model that closely mirrors the theoretical model, thereby directly incorporating endogeneity. Applied to data at the level of ethnic groups, the estimation results indicate that power sharing is indeed enacted strategically by governments in anticipation of the risk of conflict. However, shedding new light on an ongoing debate, I find that the critics have overstated the case against power sharing: rather than spurring it, power sharing robustly reduces civil conflict.
Antioxidant activity and total phenolic content of medicinal plants associated with prevention and treatment of cardiovascular and cerebrovascular diseases

In order to find new resources of natural antioxidants, antioxidant activities of 40 medicinal plants associated with prevention and treatment of cardiovascular and cerebrovascular diseases were evaluated using ferric reducing antioxidant power (FRAP) and Trolox equivalent antioxidant capacity (TEAC) assays, respectively, and their total phenolic contents were measured by the Folin-Ciocalteu method. Most of these plants were analyzed for the first time for their antioxidant activities. Generally, these plants had high antioxidant capacities and total phenolic contents. A significant correlation between the FRAP value and the TEAC value suggested that antioxidant components in these plants were capable of reducing oxidants and scavenging free radicals. A high correlation between antioxidant capacity and total phenolic content indicated that phenolic compounds could be the main contributor of the antioxidant activity of these plants. Several plants, such as Sanguisorba offivinalis, Rosa chinensis, Millettia dielsiana, Polygonum cuspidatum, Caesalpinia sappan and Sophora japonica, showed the highest antioxidant activities and total phenolic contents. These plants could be potential rich resources of natural antioxidants and could be developed into functional food or drug for prevention and treatment of diseases caused by oxidative stress.
Unusual West Arctic Storm Activity During Winter 2020: Another Collapse of the Beaufort High?

Weather and sea ice forecasts provided in support of the U.S. Navy's Ice Exercise winter 2020 campaign in the Beaufort Sea noted frequent storms in the absence of the climatological Beaufort High which coincided with anomalous eastward drift of the region's ice cover. To place the 2020 Beaufort‐Chukchi regional atmospheric conditions in historical context, we evaluated winter low sea‐level pressure (SLP) extremes and storm characteristics in the region over the 1948–2020 period. March 2020 SLP in the Beaufort‐Chukchi region was the lowest of the modern reanalysis era (1009.07 hPa) with record counts of passing storms and days with SLP at least two standard deviations below the climatological mean. The Beaufort High collapse in winter 2020 continued a recent pattern of Beaufort High collapses dating back to 2010. Unlike other recent collapses, such as 2017, most of the late‐winter 2020 cyclones originated locally over the western Arctic Ocean.
Firm Ownership Characteristics and Long-run Return on Equity Issued: A Case of the Nairobi Securities Exchange

This investigation looked at the link between firm ownership characteristics and long-run return on firms that issued equity at the Nairobi Securities Exchange (NSE) in Kenya. The study covered 12 firms that issued shares in the NSE market from 2006-2008. Ownership characteristics included (state ownership, institutional Ownership, foreign Ownership, big five shareholders, market capitalization, age of the firm and Leverage of the firm) in relation to the average return. The study tested whether each of the firm ownership characteristics influenced long-run performance. Annual return for these companies was based on market return for five years after the firm’s equity shares were issued. The long-run performance was compared with three benchmarks, namely, NSE index, CAPM and Matching firms. Seven hypotheses were developed for the study. Simple-liner and multi-linear regression analyses based on panel data were carried out to relate the extended run return on shares issued. The result of the survey showed that issuing firms performed better than non-issuing firms. These issuing firms also performed better in comparison to CAPM. However, the issuing firms performed worse than NSEI. In conclusion, the long-run performance of equity issued at the NSE does not necessarily underperform relative to non-issuing establishments.
Who Has the Last Word? Understanding How to Sample Online Discussions

In online debates, as in offline ones, individual utterances or arguments support or attack each other, leading to some subset of arguments (potentially from different sides of the debate) being considered more relevant than others. However, online conversations are much larger in scale than offline ones, with often hundreds of thousands of users weighing in, collaboratively forming large trees of comments by starting from an original post and replying to each other. In large discussions, readers are often forced to sample a subset of the arguments being put forth. Since such sampling is rarely done in a principled manner, users may not read all the relevant arguments to get a full picture of the debate from a sample. This paper is interested in answering the question of how users should sample online conversations to selectively favour the currently justified or accepted positions in the debate. We apply techniques from argumentation theory and complex networks to build a model that predicts the probabilities of the normatively justified arguments given their location in idealised online discussions of comments and replies which we represent as trees. Our model shows that the proportion of replies that are supportive, the distribution of the number of replies that comments receive, and the locations of comments that do not receive replies (i.e., the “leaves” of the reply tree) all determine the probability that a comment is a justified argument given its location. We show that when the distribution of the number of replies is homogeneous along the tree length, for acrimonious discussions (with more attacking comments than supportive ones), the distribution of justified arguments depends on the parity of the tree level which is the distance from the root expressed as number of edges. In supportive discussions, which have more supportive comments than attacks, the probability of having justified comments increases as one moves away from the root. For discussion trees which have a non-homogeneous in-degree distribution, for supportive discussions we observe the same behaviour as before, while for acrimonious discussions we cannot observe the same parity-based distribution. This is verified with data obtained from the online debating platform Kialo. By predicting the locations of the justified arguments in reply trees, we can therefore suggest which arguments readers should sample, to grasp the currently accepted opinions in such discussions. Our models have important implications for the design of future online debating platforms.
Effects of Biochar Produced from Cornstalk, Rice Husk and Bamboo on Degradation of Flumioxazin in Soil

ABSTRACT Application of biochar provide a novel approach against organic contaminated soil issues. The objective of this study was to evaluate the effect of biochars amendment on flumioxazin degradation using batch experiments. A simple and accurate pretreatment method coupled with liquid chromatography tandem with mass spectrometry was developed and successfully applied on the assessment trials of the effect of biochar amendment on the degradation of flumioxazin in soil. Three different types of biochar were characterized in terms of the degradation of flumioxazin in soil. The results demonstrated that flumioxazin degraded fast in four nonbiochar soil sample (half-lives of 11.1–20.8 days) but slower in biochar soils (half-lives of 15.4–30.7 days), and the effect varied with the nature of feedstock and pyrolysis temperature. Biochars prepared at 500°C (CB500 and RB500) could remove flumioxazin more effectively than the biochar prepared at 700°C (BB700). In addition, biochar content also affected the remediation. When the biochar content changed, the degradation rate of flumioxazin varied significantly. The degradation of flumioxazin was faster in soil samples with 0.5% cornstalk biochar than those in nonbiochar soil samples. As the biochar content increased, the degradation rate decreased because of the dominant adsorption efficiency. The results in this study support the environmental risk assessment of flumioxazin in soil and provide some guidance for biochar amendment in soil contaminated with flumioxazin.
Generation of Multiple Vector Optical Bottle Beams

We propose binary diffractive optical elements, combining several axicons of different types (axis-symmetrical and spiral), for the generation of a 3D intensity distribution in the form of multiple vector optical ‘bottle’ beams, which can be tailored by a change in the polarization state of the illumination radiation. The spatial dynamics of the obtained intensity distribution with different polarization states (circular and cylindrical of various orders) were investigated in paraxial mode numerically and experimentally. The designed binary axicons were manufactured using the e-beam lithography technique. The proposed combinations of optical elements can be used for the generation of vector optical traps in the field of laser trapping and manipulation, as well as for performing the spatial transformation of the polarization state of laser radiation, which is crucial in the field of laser-matter interaction for the generation of special morphologies of laser-induced periodic surface structures.