Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Influencing Aquatic Invertebrate Diversity in Mine Pit Lakes Along the Mesabi Iron Range

Restoration of mine pit lakes for recreation is going to be very important for the future of Minnesota’s Mesabi Iron Range area. As many as 250 lakes will need to be restored in the future along this 100-kilometer-long swath of mining country. Information regarding the organisms that currently inhabit these lakes is important for future restorations to be a success. The focus of this study was to identify the types of aquatic invertebrates present in pit lakes and to identify some of the factors that influence their abundance and diversity. During this study, invertebrate samples were taken along the shore of 10 pit lakes. It was found that there is a significant difference in diversity and species richness among some lakes. Increasing shoreline vegetation coverage was found to have a positive effect on species richness (P < 0.01). Increasing rock size had a negative effect on invertebrate density (P = 0.03). Increasing macrophytes abundance had a positive effect on species richness (P < 0.01) and a negative effect on diversity (P = 0.02). Substrate consisting of a glacial till had a higher species richness than substrates consisting of hard rocks uncovered by mining (P = 0.04). Hopefully, the results of this study can be used to improve these lake systems for future recreational use.
Climatic Controls on the Kinematics of the Hooskanaden Landslide, Curry County, Oregon

Slow-moving earthflows represent major sources of sediment transport and erosion and are problematic for the management of critical infrastructure. The Hooskanaden Landslide – a slow-moving earthflow on the southwest coast of Oregon – crosses US Highway 101 and has been a site of continued interest to the Oregon Department of Transportation (ODOT) due to the weak lithology, erosive environment, and recurrent surge behavior (every ~15 years). Past surges, including the most recent (2019), have occurred during the winter, suggesting that velocity changes are predominantly controlled by climatic inputs. To examine the response of the Hooskanaden Landslide to seasonal and other periodic climate cycles (El Niño–Southern Oscillation, and Pacific Decadal Oscillation), manual feature tracking on orthorectified aerial photographs and satellite images from PlanetLabs was used to create a surface velocity time series from 1980 to late 2019. In comparing our velocity time series to local precipitation records over the same period, it is clear that periods of seasonal acceleration correspond with above average precipitation. However, periods of surging did not correspond to years with the highest seasonal precipitation, although they do appear to correlate with transitions between warm and cold phase climate cycles. Additionally, extensive surface mapping and carbon dating were performed to understand the morphology and origins of this landslide. Logs exposed by erosion at the toe of the landslide were sampled and used for radiocarbon dating and C wiggle matching. Sample calendar age ranges were constrained using stratigraphic and varve models within OxCal Bayesian statistical modeling software. Based on agreement between
Toward Sustainable Accounting Information: Evidence from IFRS Adoption in Korea

: The harmonization of accounting standards has been an international trend in the past two decades. As of 2018, 144 of 166 proﬁled jurisdictions require the use of International Financial Reporting Standards (IFRS). Nevertheless, there is mixed evidence on the effect of IFRS on sustainable accounting information. This study examines whether IFRS adoption improves earnings sustainability, focusing on emerging markets. Speciﬁcally, it tests the effect of IFRS on earnings quality by comparing earnings management and ﬁnancial statement comparability of Korean listed ﬁrms for the pre- and post-IFRS periods. The results show that ﬁrms report less managed earnings in the post-IFRS period than in the pre-IFRS period. Furthermore, the results suggest the enhancement of ﬁnancial statement comparability in the post-IFRS period compared to the pre-IFRS period. In particular, this paper documents that the effect of IFRS on sustainable accounting information is more pronounced in competitive industries. Moreover, it shows that small ﬁrms beneﬁt more from adopting IFRS. Overall, this study ﬁnds that IFRS adoption in Korea improves the overall sustainability of accounting information.
How Does Policy Perception Affect Green Entrepreneurship Behavior? An Empirical Analysis from China

As sustainable development has become a worldwide concern in dealing with tensions between economic development and resource sustainability, green entrepreneurship as a potential solution is gaining popularity. This paper investigates the perceptions of green policies and their impact on green entrepreneurial behavior. Furthermore, green self-efficacy is identified as a psychological mechanism linking green entrepreneurship policies and green entrepreneur behavior and moral reflectiveness as a boundary condition. Building on the policy acceptance model (PAM), the relationships between two policy perceptions and two green entrepreneurial behaviors, the mediating effect of green self-efficacy, and the moderating effect of moral reflectiveness are explored. Results support the mediation and moderation effects, implying that governmental institutions can strive to improve entrepreneurs’ perceived usefulness and ease of use in terms of public policies to strengthen their engagement in green entrepreneurial behaviors.
Prevalence of coinfections with ESKAPE pathogens in COVID-19 patients: A review

The emergence and worldwide spread of the COVID-19 pandemic, which is being caused by a type of coronavirus named as SARS-CoV-2, has unprecedentedly challenged the healthcare system across the globe. To add to the catastrophe brought about by this viral infectious disease, coinfections by other microbial agents including bacteria and fungi further deteriorate the health of COVID-19 patients by developing multiple dreaded diseases, resulting in extended morbidity and high rate of mortality all over the world. There are a number of multidrug resistant bacterial species which cause these coinfections both in community environments and hospital set ups including in the ICUs. Among the multidrug resistant bacterial species that are responsible for tens of thousands of deaths per annum around the globe, the infectious diseases society of America (IDSA) has shortlisted and the world health organization (WHO) has recognized the importance of the most dangerous 'bad bugs' dubbed as 'ESKAPE' pathogens and the members are Enterococcus faecium (E), Staphylococcus aureus (S), Klebsiella pneumoniae (K), Acinetobacter baumannii (A), Pseudomonas aeruginosa (P) and Enterobacter species and Escherichia colt (E). Each one of the above mentioned bacterium has many MDR strains and complex antimicrobial resistance mechanisms. In this review, I try to find out the reported prevalence of these pathogens in COVID-19 patients admitted to various healthcare facilities across the world.
Wage Dynamics: The Role of Learning, Human Capital, and Performance Incentives∗ WORK IN PROGRESS

Using public individual survey data and proprietary firm personnel records, we document that the importance of performance pay declines at the end of a career. This evidence is at odds with the implication of models of implicit and explicit performance incentives that have attempted to explain the life-cycle profile of the variable component of wages. We provide a novel model that integrates uncertainty and learning about individual ability, human capital acquisition, and performance incentives to account for the life-cycle profile of wages and the declining importance of the pay-for-performance component of wages with experience. We analytically characterize the equilibrium wage contract in this environment, derive its qualitative properties, and decompose the pay-for-performance component of the equilibrium wage into four distinct terms. These terms capture the standard trade-off between risk and incentives arising in situations of moral hazard, the desire to hedge against the risk inherent in learning about ability, and the changing strength of reputational and human capital investment motives over time. We prove that the model is identified just based on a panel of wages. We derive estimators of the model’s primitive parameters and use the estimated parameters to measure the relative contribution of the three sources of wage dynamics we nest—learning, human capital acquisition, and performance incentives—to the life-cycle profile of total wages and their variable component. According to our preliminary estimates, performance incentives seem to be qualitatively and quantitatively key to explaining the life-cycle profile of wages and variable pay, despite the declining importance of variable pay relative to fixed pay over time.
Is There Any Difference in the Growth Mindset between Male and Female Students during a Pandemic?

The pandemic that occurred until July 2021 still had an impact on the implementation of education in Indonesia. We examine how the growth mindset of students in the teaching and education faculties is during the pandemic. One hundred eighteen students participated in this study by filling out an online growth mindset questionnaire with the help of a Google form. Descriptive statistical tests were conducted to see the percentage of growth mindset, which included two dimensions, namely intelligence mindset and moral mindset. In addition, we tested the differences on both dimensions of growth mindset based on gender and GPA. The results showed that the percentage of intelligence mindset and moral mindset was at points 3 and 4 based on a Likert scale of 1 to 6. This was in the moderate category. There is no difference in the intelligence and Moral mindset based on gender and GPA. This result proves that both men and women have the same tendency of growth mindset position. Keywords: growth mindset, fixed mindset, gander, education school.
From self-enforcing agreements to self-sustaining norms

Self-enforcing agreements, such as relational contracts and international agreements, prescribe actions and rules enforcing these actions, but typically ignore agents’ ability to change these rules. This paper studies self-sustaining norms, which prescribe how individuals react to one another’s actions but also to proposals to change the rules. We characterize the set of self-sustaining norms when agents interact frequently, which has a remarkably simple structure. Inefficient norms may arise even when all actions are public and frequent and agents can credibly commit to rules.
Data-driven quality improvement approach to reducing waste in manufacturing

PurposeData-driven quality management systems, brought about by the implementation of digitisation and digital technologies, is an integral part of improving supply chain management performance. The purpose of this study is to determine a methodology to aid the implementation of digital technologies and digitisation of the supply chain to enable data-driven quality management and the reduction of waste from manufacturing processes.Design/methodology/approachMethodologies from both the quality management and data science disciplines were implemented together to test their effectiveness in digitalising a manufacturing process to improve supply chain management performance. The hybrid digitisation approach to process improvement (HyDAPI) methodology was developed using findings from the industrial use case.FindingsUpon assessment of the existing methodologies, Six Sigma and CRISP-DM were found to be the most suitable process improvement and data mining methodologies, respectively. The case study revealed gaps in the implementation of both the Six Sigma and CRISP-DM methodologies in relation to digitisation of the manufacturing process.Practical implicationsValuable practical learnings borne out of the implementation of these methodologies were used to develop the HyDAPI methodology. This methodology offers a pragmatic step by step approach for industrial practitioners to digitally transform their traditional manufacturing processes to enable data-driven quality management and improved supply chain management performance.Originality/valueThis study proposes the HyDAPI methodology that utilises key elements of the Six Sigma DMAIC and the CRISP-DM methodologies along with additions proposed by the author, to aid with the digitisation of manufacturing processes leading to data-driven quality management of operations within the supply chain.
Attributing correlation skill of dynamical GCM precipitation forecasts to statistical ENSO teleconnection using a set-theory-based approach

Abstract. Climate teleconnections are essential for the verification of valuable precipitation forecasts generated by global climate models (GCMs). This paper develops a novel approach to attributing correlation skill of dynamical GCM forecasts to statistical El Niño–Southern Oscillation (ENSO) teleconnection by using the coefficient of determination (R2). Specifically, observed precipitation is respectively regressed against GCM forecasts, Niño3. 4 and both of them, and then the intersection operation is implemented to quantify the overlapping R2 for GCM forecasts and Niño3. 4. The significance of overlapping R2 and the sign of ENSO teleconnection facilitate three cases of attribution, i.e., significantly positive anomaly correlation attributable to positive ENSO teleconnection, attributable to negative ENSO teleconnection and not attributable to ENSO teleconnection. A case study is devised for the Climate Forecast System version 2 (CFSv2) seasonal forecasts of global precipitation. For grid cells around the world, the ratio of significantly positive anomaly correlation attributable to positive (negative) ENSO teleconnection is respectively 10.8 % (11.7 %) in December–January–February (DJF), 7.1 % (7.3 %) in March–April–May (MAM), 6.3 % (7.4 %) in June–July–August (JJA) and 7.0 % (14.3 %) in September–October–November (SON). The results not only confirm the prominent contributions of ENSO teleconnection to GCM forecasts, but also present spatial plots of regions where significantly positive anomaly correlation is subject to positive ENSO teleconnection, negative ENSO teleconnection and teleconnections other than ENSO. Overall, the proposed attribution approach can serve as an effective tool to investigate the sources of predictability for GCM seasonal forecasts of global precipitation.
Reflective Noise Filtering of Large-Scale Point Cloud Using Multi-Position LiDAR Sensing Data

Signals, such as point clouds captured by light detection and ranging sensors, are often affected by highly reflective objects, including specular opaque and transparent materials, such as glass, mirrors, and polished metal, which produce reflection artifacts, thereby degrading the performance of associated computer vision techniques. In traditional noise filtering methods for point clouds, noise is detected by considering the distribution of the neighboring points. However, noise generated by reflected areas is quite dense and cannot be removed by considering the point distribution. Therefore, this paper proposes a noise removal method to detect dense noise points caused by reflected objects using multi-position sensing data comparison. The proposed method is divided into three steps. First, the point cloud data are converted to range images of depth and reflective intensity. Second, the reflected area is detected using a sliding window on two converted range images. Finally, noise is filtered by comparing it with the neighbor sensor data between the detected reflected areas. Experiment results demonstrate that, unlike conventional methods, the proposed method can better filter dense and large-scale noise caused by reflective objects. In future work, we will attempt to add the RGB image to improve the accuracy of noise detection.
Logophoricity and Mandarin Exempt Reflexives

Anaphors in many languages do not obey the 'canonical' Binding Condition A (Chomsky 1986), such as Icelandic 'sig' and Mandarin 'ziji'. Two main competing approaches have been proposed to capture binding beyond the local domain: (i) The LONG-DISTANCE BINDING (LDB) theory derives non-local binding via covert cyclic movement and turns non-local binding into local binding which always obeys Condition A. (Pica 1987, Huang & Tang 1991) (ii) The LOGOPHORICITY (LOG) theory explains exempt anaphors by logophoric rather than pure structural constraints (Sells 1987, Huang & Liu 2001, Charnavel 2019). The two theories make distinct predictions on the referential dependencies between reflexives and their antecedents. The LDB theory predicts that antecedents should always c-command the reflexives, while the LOG theory predicts that reflexives need not be c-commanded by their antecedents if they are logophoric. This paper aims to experimentally test the two competing theories by investigating the binding conditions of Chinese reflexive 'ziji' and 'taziji' using acceptability judgment tasks. The results about 'ziji' support the LOG theory against the LDB theory. Furthermore, our results reveal that 'taziji', though usually considered as a local anaphor (e.g., Cole, Hermon & Huang 2006), can in fact similarly be exempt from binding under logophoric conditions. This working paper is available in University of Pennsylvania Working Papers in Linguistics: https://repository.upenn. edu/pwpl/vol26/iss1/18
Parents’ Schooling & Intergenerational Human Capital: Evidence from India

This paper examines the impact of a national-level school construction program in India on educational outcomes of direct beneficiaries and their children. Between the years 19932004, the District Primary Education Programme (DPEP) served over 50 million children and prioritized districts with below-average female literacy rates. I use a fuzzy regression discontinuity design to estimate the causal impact of the programme by comparing outcomes of school-age children in districts on either side of the average female literacy cutoff. To uncover the difference in timing of programme implementation across districts, I use unique archival information that I collected and digitized. The results show that DPEP increased school access, enrollment, literacy and years of education for both male and female direct beneficiaries. I then provide one of the first evidence of intergenerational effects of a school construction policy. Using test score data spanning the years 2007-2014, I find that children whose mothers were DPEP beneficiaries had higher scores on math (0.18 S.D.), vernacular (0.19 S.D.) and English (0.09 S.D.) tests. Daughters’ test scores went up by more than 10 to 15 percentage points higher than that of sons. Father’s DPEP exposure had no effect on children’s learning. I find evidence that the intergenerational impacts may be mediated through mother’s increased bargaining power, higher investments in children’s education and better health/health related behaviors. JEL classification: I21, I25, O15, J16, J24
Effect of Natural Disaster-Related Prenatal Maternal Stress on Child Development and Health: A Meta-Analytic Review

The evidence supporting the idea that natural disaster-related prenatal maternal stress (PNMS) influences the child’s development has been accumulating for several years. We conducted a meta-analytical review to quantify this effect on different spheres of child development: birth outcomes, cognitive, motor, physical, socio-emotional, and behavioral development. We systematically searched the literature for articles on this topic (2756 articles retrieved and 37 articles included in the systematic review), extracted the relevant data to calculate the effect sizes, and then performed a meta-analysis for each category of outcomes (30 articles included across the meta-analyses) and meta-regressions to determine the effect of some factors of interest on the association between PNMS and child development: type of PNMS (objective, psychological, cognitive, diet), type of natural disaster (ice storm, flood/cyclone), type of report (maternal, third-party observer, medical), timing of exposure (preconception exposure included or not) and child age at assessment (under 10 or 10 years and older). We found that PNMS significantly influences all spheres of child development. Higher PNMS levels were associated with longer gestational age, larger newborns, and higher BMI and adiposity levels, as well as worse cognitive, motor, socio-emotional, and behavioral outcomes.
Pedestrian identification in infrared images using visual saliency detection technique

Visual saliency detection is an important part in various vision-based applications. There are a myriad of techniques for saliency detection in color images. However, the number of methods for saliency detection in infrared images is inadequate. In this paper, we introduce a simple approach for pedestrian identification in infrared images using saliency. The input image is thresholded into several Boolean maps, an initial saliency map is then calculated as a weighted sum of created Boolean maps. The initial map is further refined by using thresholding, morphology operation, and Gaussian filter to produce the final, high-quality saliency map. The experiment showed that the proposed method produced high performance results when applied to real-life data.
Reply on RC2

There is increasing evidence that hot spots of biogeochemical activity exert profound effects on ecosystems that are disproportionate relative to the physical footprint of the hotspots. Geophysical techniques have a role to play in locating such hotspots. Induced polarization is an interesting method as it may be sensitive to indicators of enhanced biogeochemical activity, such as the precipitation of metallic minerals where anaerobic and aerobic waters interact.
Public Perception Survey Study on Air Quality Issues in Wuhan, China

In 2013, a survey on air quality (AQ) was conducted in Wuhan, China. The aim was to investigate public awareness of air pollution, and its epidemiological effect. This survey targeted both suburban and central city regions of Wuhan city, between August and December of 2013, where it engaged 1225 participants. Approximately 65% perceived AQ in Wuhan to be “bad”. Over 95% recognized a causal association between air pollution and human health. About 65% were unaware of any action taken by the government to mitigate the air pollution situation. 84% indicated that the government should shut down highly polluting enterprises, while 95% expressed willingness to reduce private use of vehicles if required. The results demonstrate that the citizens of Wuhan are concerned about air pollution issues, and agree that improving AQ is the obligation of all citizens. Further, they called for concrete actions to improve AQ. The survey emphasized the need for better education and more activities to raise environmental awareness. The innovative aspects of this survey were the exploration of participants’ perceptions of AQ issues and the survey results may influence local government to impose stricter regulations, and to develop more effective programs involving citizens.
Examining the Effect of Social Network on Prediction Markets through a Controlled Experiment ∗

This paper examines the effect of a social network on prediction markets using a controlled laboratory experiment that allows us to identify causal relationships between a social network and the performance of an individual participant, as well as the performance of the prediction market as a whole. Through a randomized experiment, we first confirm the theoretical predictions that participants with more social connections are less likely to invest in information acquisition from outside information sources and perform significantly better than other participants in prediction markets through free-riding. We further show that when the cost of information acquisition is low, a social-network-embedded prediction market outperforms a non-networked prediction market. We also find strong support for peer effects in prediction accuracy among participants.