Miracle-dz/UniFAR-FTUs huggingface dataset:
The Good Judge of Meta-perception

Is meta-accuracy an individual difference that people carry with them wherever they go, or is it context-specific? Previous research assumes that meta-accuracy is an individual difference, but has not explicitly tested this assumption. Using seven samples, I tested whether meta-accuracy is an individual difference by conducting three tests that examined whether there is a good judge of meta-perception across different 1) contexts, 2) traits, and 3) targets. The Good Judge Hypothesis predicts that there are individuals who are consistently meta-accurate across contexts, traits, and targets. In contrast, the Context Hypothesis predicts that there are no consistently meta-accurate individuals across contexts, traits, or targets. The present results support the Good Judge Hypothesis. However, while there was a good judge across various traits and targets, and within specific contexts, there was no evidence of a good judge across contexts. Theoretical implications, practical applications, and future directions of the current work are discussed.
Characterizing and Improving Logging Practices in Java-based Open Source Software Projects - A Large-scale Case Study in Apache Software Foundation

Log messages (generated by logging code) contain rich information about the runtime behavior of software systems. Although more logging code can provide more context of the system’s behavior, it is undesirable to include too much logging code. Yuan et al. performed the first empirical study on characterizing the logging. In the first part of the thesis, we conduct a large-scale replication study on characterizing the logging practices on Java-based open source projects. A significantly higher portion of log updates are for enhancing the quality rather than co-changes with feature implementations. However, there are no well-defined coding guidelines for performing effective logging. In the second part, we studied the problem of characterizing and detecting the anti-patterns in the logging code. We have encoded these anti-patterns into a static code analysis tool, LCAnalyzer. Case studies show that LCAnalyzer has an average recall of 95% and precision of 60% .
File Updates Under Random/Arbitrary Insertions and Deletions

The problem of one-way file synchronization, henceforth called “file updates”, is studied in this paper. Specifically, a client edits a file, where the edits are modeled by insertions and deletions (InDels). An old copy of the file is stored remotely at a data-centre, and is also available to the client. We consider the problem of throughput- and computationally-efficient communication from the client to the data-centre, to enable the data-centre to update its old copy to the newly edited file. Two models for the source files and edit patterns are studied: the random pre-edit sequence left-to-right random InDel (RPES-LtRRID) process, and the arbitrary pre-edit sequence arbitrary InDel (APES-AID) process. In both models, we consider the regime, in which the number of insertions and deletions is a small (but constant) fraction of the length of the original file. For both models, information-theoretic lower bounds on the best possible compression rates that enable file updates are derived (up to first order terms). Conversely, a simple compression algorithm using dynamic programming (DP) and entropy coding (EC), henceforth called DP-EC algorithm, achieves rates that are within constant additive gap (which diminishes as the alphabet size increases) to information-theoretic lower bounds for both models. For the RPES-LtRRID model, a dynamic-programming-run-length-compression (DP-RLC) algorithm is proposed, which achieves a compression rate matching the information-theoretic lower bound up to first order terms. Therefore, when the insertion and deletion probabilities are small (such that first order terms dominate), the achievable rate by DP-RLC is nearly optimal for the RPES-LtRRID model.
THE EFFECT OF WORK ENVIRONMENT ON FLEXIBLE WORKING HOURS, EMPLOYEE ENGAGEMENT AND EMPLOYEE MOTIVATION

Employee engagement is one of the concentrations of the human resources department. Many programs are run to increase employee engagement value from year to year. This study aims to analyze the influence of work environment and flexible working hours on employee engagement with employee motivation as an intervening variable. The respondents of this study focus on millenials supervisor up from manufacture and service company in Java Island, Indonesia. The type of research used is quantitative with survey method. Research respondents were 110 people and the data were analyzed using SEM-AMOS (Structural Equation Model - Analysis of Moment Structures). The results show that there is an influence of work life balance and flexible working hours on employee engagement. We also used Sobel test to see that employee motivation have a function as a mediating or not in this study. According to the results, employee motivation has the effect of mediating between work environment and flexible working hours on employee engagement.
Sheeple? The need for more research on sheep cognition

Marino & Merskin (2019) provide a comprehensive review of the cognitive abilities of sheep. If research with other animals is any guide, there may be justification for the view that the abilities of sheep have been underestimated, and their review will likely stimulate more research into sheep cognition. Michael Colombo, Professor in the Department of Psychology, University of Otago, conducts comparative cognition research as well as research on the neural basis of learning and
A Freely Available, Self-Calibrating Software for Automatic Measurement of Freezing Behavior

Freezing behavior is commonly used as a measure of associative fear memory. It can be measured by a trained observer, but this task is time-consuming and subject to variation. Commercially available software packages can also be used to quantify freezing; however, they can be expensive and usually require various parameters to be adjusted by the researcher, leading to additional work and variability in results. With this in mind, we developed Phobos, a freely available, self-calibrating software that measures freezing in a set of videos using a brief manual quantification performed by the user to automatically adjust parameters. To optimize the software, we used four different video sets with different features in order to determine the most relevant parameters, the amount of videos needed for calibration and the minimum criteria to consider it reliable. The results of four different users were compared in order to test intra- and interobserver variability in manual and automated freezing scores. Our results suggest that Phobos can be an inexpensive, simple and reliable tool for measurement of fear-related behavior, with intra- and interuser variability similar to that obtained with manual scoring.
Optimal Non-Prosecution Agreements and the Reputational Effects of Convictions

Abstract Many claim that non-prosecution agreements (NPAs) reduce deterrence by mitigating the reputational sanctions that would otherwise be imposed on corporations through plea-bargains. They suggest, based on this claim, that NPAs ought to be used infrequently. This article presents a signalling model wherein reputational sanctions emerge as a result of noisy signals produced through a firm's prosecution. It is shown that, if, as claimed, NPAs provide third parties with less information regarding a firm's wrongdoings, then firms would be willing to pay an NPA premium to avoid convictions. Thus, the NPA premium can be chosen to induce only those firms which would otherwise be over-deterred to accept NPAs. Therefore, offering NPAs with high premia is superior to the option of not using NPAs. The article also characterizes optimal NPAs, and identifies relationships between deterrence; frequency of NPA use; firms’ characteristics; and NPA terms. It explains how these relationships can be exploited to form and test hypotheses on whether convictions obtained through plea-bargains cause greater reputational harm to firms than NPAs.
Interaction between Securitization Gains and Abnormal Loan Loss Provisions: Credit Risk Retention and Fair Value Accounting

This study investigates whether managers use asset securitization gains to substitute loan loss provision (LLP) management for earnings management, and, if so, whether the percentage of credit risk retained affects such a relationship. The literature provides evidence that managers have used securitization transactions to boost earnings. Using 2001‒2014 data for a sample of bank holding companies, I find that managers use securitization gains and LLPs as partial substitutes and that earnings management from securitization gains grows at an increasing rate to substitute income increasing LLP management as the level of risk retention increases. These findings are consistent with the argument that the higher the level of risk retention, the greater the potential impact on achieving earnings targets, given banks’ exercise of discretion over securitization gains through estimation of fair value of retained interest. In addition, I document that the substitution effect between the two tools is non‐existent in the post‐SFAS 166/167 period. Taken together, the findings have timely implications for accounting standards by informing the effect of risk retention that I measure through earnings management techniques. Moreover, my findings provide additional support for improved disclosures on assets‐backed securities.
Distinct Properties of Layer 3 Pyramidal Neurons from Prefrontal and Parietal Areas of the Monkey Neocortex

In primates, working memory function depends on activity in a distributed network of cortical areas that display different patterns of delay task-related activity. These differences are correlated with, and might depend on, distinctive properties of the neurons located in each area. For example, layer 3 pyramidal neurons (L3PNs) differ significantly between primary visual and dorsolateral prefrontal (DLPFC) cortices. However, to what extent L3PNs differ between DLPFC and other association cortical areas is less clear. Hence, we compared the properties of L3PNs in monkey DLPFC versus posterior parietal cortex (PPC), a key node in the cortical working memory network. Using patch-clamp recordings and biocytin cell filling in acute brain slices, we assessed the physiology and morphology of L3PNs from monkey DLPFC and PPC. The L3PN transcriptome was studied using laser microdissection combined with DNA microarray or quantitative PCR. We found that in both DLPFC and PPC, L3PNs were divided into regular spiking (RS-L3PNs) and bursting (B-L3PNs) physiological subtypes. Whereas regional differences in single-cell excitability were modest, B-L3PNs were rare in PPC (RS-L3PN:B-L3PN, 94:6), but were abundant in DLPFC (50:50), showing greater physiological diversity. Moreover, DLPFC L3PNs display larger and more complex basal dendrites with higher dendritic spine density. Additionally, we found differential expression of hundreds of genes, suggesting a transcriptional basis for the differences in L3PN phenotype between DLPFC and PPC. These data show that the previously observed differences between DLPFC and PPC neuron activity during working memory tasks are associated with diversity in the cellular/molecular properties of L3PNs. SIGNIFICANCE STATEMENT In the human and nonhuman primate neocortex, layer 3 pyramidal neurons (L3PNs) differ significantly between dorsolateral prefrontal (DLPFC) and sensory areas. Hence, L3PN properties reflect, and may contribute to, a greater complexity of computations performed in DLPFC. However, across association cortical areas, L3PN properties are largely unexplored. We studied the physiology, dendrite morphology and transcriptome of L3PNs from macaque monkey DLPFC and posterior parietal cortex (PPC), two key nodes in the cortical working memory network. L3PNs from DLPFC had greater diversity of physiological properties and larger basal dendrites with higher spine density. Moreover, transcriptome analysis suggested a molecular basis for the differences in the physiological and morphological phenotypes of L3PNs from DLPFC and PPC.
The Disappearing Solar Filament of 2013 September 29 and Its Large Associated Proton Event: Implications for Particle Acceleration at the Sun

We present observations of a notable example of a disappearing solar filament (DSF) on 2013 September 29 that was associated with a large solar proton event (SPE) and discuss this event in the context of four recent studies that compare flare and SPE size parameters. The DSF-associated flare was characterized by weak radio and soft X-ray emissions and a low reconnection flux. It was accompanied by a fast coronal mass ejection (CME) and a decametric-hectometric type II burst. We assembled a list of eight such events that are outliers in plots of SPE versus flare size parameters. These events were characterized by weak magnetic field source regions (predominantly DSFs but including one case of a transequatorial loop and another of a decaying active region), fast CMEs, type II bursts with low starting frequencies, high proton yields (ratio of proton intensity to 1 MHz radio fluence), and low high-energy Fe/O ratios. The last of these attributes suggests quasi-parallel shock acceleration. The relationship between SPE and flare size parameters in large (gradual), well-connected proton events can be illustrated by a schematic diagram with three principal regions: (1) a DSF zone of weak flares and large SPEs, (2) a big flare syndrome main sequence of loosely correlated flare and SPE parameters, and (3) a zone of moderate to large flares with no SPEs. The existence of regions 1 and 3 argues against a significant role for flares in large proton events: region 1 implies that flares are not necessary for such SPEs, and region 3 indicates that they are not sufficient.
Quantifying Path Exploration in the Internet

Previous measurement studies have shown the existence of path exploration and slow convergence in the global Internet routing system, and a number of protocol enhancements have been proposed to remedy the problem. However, existing measurements were conducted only over a small number of testing prefixes. There has been no systematic study to quantify the pervasiveness of Border Gateway Protocol (BGP) slow convergence in the operational Internet, nor any known effort to deploy any of the proposed solutions. In this paper, we present our measurement results that identify BGP slow convergence events across the entire global routing table. Our data shows that the severity of path exploration and slow convergence varies depending on where prefixes are originated and where the observations are made in the Internet routing hierarchy. In general, routers in tier-1 Internet service providers (ISPs) observe less path exploration, hence they experience shorter convergence delays than routers in edge ASs; prefixes originated from tier-1 ISPs also experience less path exploration than those originated from edge ASs. Furthermore, our data show that the convergence time of route fail-over events is similar to that of new route announcements and is significantly shorter than that of route failures. This observation is contrary to the widely held view from previous experiments but confirms our earlier analytical results. Our effort also led to the development of a path-preference inference method based on the path usage time, which can be used by future studies of BGP dynamics.
Quackgrass (Agropyron repens) Control in Potatoes (Solanum tuberosum) by Fluazifop

In greenhouse and field studies, fluazifop {(±)-2-[4-[[5-(trifluoromethyl)-2-pyridinyl]oxy]phenoxy] propanoic acid} controlled quackgrass [Agropyron repens (Beauv.) # AGRRE] in potato (Solanum tuberosum L. ‘Russet Burbank’). Quackgrass control with fluazifop at 0.25 and 0.5 kg ai/ha in the greenhouse was greatest with application at the two-leaf stage compared with the four-and six-leaf stages. Control was not affected by rhizome length, with similar control obtained of plants grown from 2- and 10-node rhizome pieces. Removal of quackgrass shoots at 6 or 24 h after treatment resulted in decreased control at application rates of 0.25 and 0.5 kg/ha. Fluazifop at 0.5 kg/ha controlled quackgrass treated at the four-leaf stage. The active enantiomer of fluazifop at half the rate of the racemic mixture controlled the quackgrass to the same extent. Fluazifop did not affect potato yield.
The Exceptional 2018 European Water Seesaw Calls for Action on Adaptation

Temperature and precipitation are the most important factors responsible for agricultural productivity variations. In 2018 spring/summer growing season, Europe experienced concurrent anomalies of both. Drought conditions in central and northern Europe caused yield reductions up to 50% for the main crops, yet wet conditions in southern Europe saw yield gains up to 34%, both with respect to the previous 5‐year mean. Based on the analysis of documentary and natural proxy‐based seasonal paleoclimate reconstructions for the past half millennium, we show that the 2018 combination of climatic anomalies in Europe was unique. The water seesaw, a marked dipole of negative water anomalies in central Europe and positive ones in southern Europe, distinguished 2018 from the five previous similar droughts since 1976. Model simulations reproduce the 2018 European water seesaw in only 4 years out of 875 years in historical runs and projections. Future projections under the RCP8.5 scenario show that 2018‐like temperature and rainfall conditions, favorable to crop growth, will occur less frequent in southern Europe. In contrast, in central Europe high‐end emission scenario climate projections show that droughts as intense as 2018 could become a common occurrence as early as 2043. While integrated European and global agricultural markets limited agro‐economic shocks caused by 2018's extremes, there is an urgent need for adaptation strategies for European agriculture to consider futures without the benefits of any water seesaw.
Comparison-based Image Quality Assessment for Parameter Selection

Image quality assessment (IQA) is traditionally classified into full-reference (FR) IQA and no-reference (NR) IQA according to whether the original image is required. Although NR-IQA is widely used in practical applications, room for improvement still remains because of the lack of the reference image. Inspired by the fact that in many applications, such as parameter selection, a series of distorted images are available, the authors propose a novel comparison-based image quality assessment (C-IQA) method. The new comparison-based framework parallels FR-IQA by requiring two input images, and resembles NR-IQA by not using the original image. As a result, the new comparison-based approach has more application scenarios than FR-IQA does, and takes greater advantage of the accessible information than the traditional single-input NR-IQA does. Further, C-IQA is compared with other state-of-the-art NRIQA methods on two widely used IQA databases. Experimental results show that C-IQA outperforms the other NR-IQA methods for parameter selection, and the parameter trimming framework combined with C-IQA saves the computation of iterative image reconstruction up to 80%.
Automatic Summarization

It has now been 50 years since the publication of Luhn’s seminal paper on automatic summarization. During these years the practical need for automatic summarization has become increasingly urgent and numerous papers have been published on the topic. As a result, it has become harder to find a single reference that gives an overview of past efforts or a complete view of summarization tasks and necessary system components. This article attempts to fill this void by providing a comprehensive overview of research in summarization, including the more traditional efforts in sentence extraction as well as the most novel recent approaches for determining important content, for domain and genre specific summarization and for evaluation of summarization. We also discuss the challenges that remain open, in particular the need for language generation and deeper semantic understanding of language that would be necessary for future advances in the field. We would like to thank the anonymous reviewers, our students and Noemie Elhadad, Hongyan Jing, Julia Hirschberg, Annie Louis, Smaranda Muresan and Dragomir Radev for their helpful feedback. This paper was supported in part by the U.S. National Science Foundation (NSF) under IIS-05-34871 and CAREER 09-53445. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. Full text available at: http://dx.doi. org/10.1561/1500000015
Translocation of Glyphosate, Quizalofop, and Sucrose in Quackgrass (Elytrigia repens) Biotypes

The translocation pattern and distribution in rhizomes of 14C-glyphosate, 14C-quizalofop, and 14C-sucrose was examined in five quackgrass biotypes. Translocation of radioactivity in the different plant parts varied among biotypes. Translocation in the whole plant after treatment with the three 14C-chemicals varied among biotypes but was not correlated with their tolerance to herbicides. Detailed analysis of distribution of radioactivity in the primary rhizome showed that more 14C was found in the apical sections after treatment with 14C-sucrose. A similar pattern was observed after 14C-glyphosate application with all biotypes except one. Very low radioactivity was found in rhizomes after 14C-quizalofop application, but a preferential accumulation in apical sections of the primary rhizome was detected in two biotypes. The tolerance of one biotype to glyphosate was explained by the absence of radioactivity accumulation in the apical sections of the rhizome.
A review of plant options for mitigating nitrous oxide emissions from pasture-based systems

ABSTRACT In grazed pasture-based systems, urinary-nitrogen (N) voided in concentrated patches is a key source of nitrous oxide (N2O), a potent greenhouse gas (GHG). Development of strategies for reducing emissions from urine patches is an ongoing focus of international research. Plants can help mitigate N2O emissions by reducing urinary-N excretion or by lowering the N2O emission factor of urine. This paper reviews the current understanding of plant-effects on urinary-N2O emissions and confirms that plants can influence emissions. Recent New Zealand studies suggest that plantain and fodder beet show particular potential for grazed systems. A key mechanism by which plantain affects the N2O emission factor could be root exudates that inhibit nitrification and/or increase N immobilisation. Further studies are needed to elucidate the mechanisms involved, and to help maximise the GHG reduction potential from plant management options in pasture-based systems.