Miracle-dz/UniFAR-FTUs huggingface dataset:
Using modified DNDC biogeochemical model to optimize 1 field management of multi-crop ( cotton , wheat , maize ) 2 system : a site-scale case study in northern China

It is still a severe challenge to optimize the field management practices for multi-crop system 12 simultaneously aiming at yield sustainability and the minimum negative impacts on climate and 13 qualities of atmosphere and water. This site-scale case study devoted to develop a biogeochemical 14 process model-based approach as a solution to this challenge. The best management practices (BMPs) 15 of a three-crop system growing cotton and winter wheat-summer maize (W-M) in rotation, which is 16 widely adopted in northern China, were identified. The BMPs were referred to the management 17 alternatives with the lowest negative impact potentials (NIPs) among the scenarios satisfying all given 18 constraints. The independent variables to determine the NIPs and those as constrained criteria were 19 simulated by the DeNitrification-DeComposition model modified in this study. Due to the 20 unsatisfactory performance of the model in daily simulations of nitric oxide (NO) emission and net 21 ecosystem exchange of carbon dioxide (NEE), the model was modified to include (i) newly 22 parameterizing the soil moisture effects on NO production during nitrification, and (ii) replacing the 23 original NEE calculation approach with an algorithm based on gross primary production. Validation of 24 the modified model showed statistically meaningful agreements between the simulations and 25 observations in the cotton and W-M fields. Three BMP alternatives with overlapping uncertainties of 26 simulated NIPs were screened from 6000 management scenarios randomly generated by the Latin 27 hypercube sampling. All these BMP alternatives adopted the baseline (currently applied) practices of 28 rotation pattern (3 consecutive years of cotton rotating with 3 years of W-M in each 6-year cycle), 29
Fostering a Reimagined Professional Stability: An Autoethnographic Exploration of How Our (Work) Group Found Hope and Healing During the COVID-19 Pandemic

Recommended Citation Mouton, Ashton; Sánchez Sánchez, Virginia; Renner, Max M. ; and Deutsch Cermin, Ashley (2021) "Fostering a Reimagined Professional Stability: An Autoethnographic Exploration of How Our (Work) Group Found Hope and Healing During the COVID-19 Pandemic," Survive & Thrive: A Journal for Medical Humanities and Narrative as Medicine: Vol. 6 : Iss. 1 , Article 18. Available at: https://repository.stcloudstate. edu/survive_thrive/vol6/iss1/18
ASPIRATION LEVELS AND EXPLORATION-EXPLOITATION: AN ADAPTIVE LEARNING APPROACH

How do high and moderate aspiration levels compare in terms of affecting the trade-off between exploration and exploitation? Recent reviews of empirical work have challenged the widely held belief that high aspiration levels lead to more exploration. Although exploration–exploitation decisions are often viewed as a reinforcement learning process, much prior work explores this question as a choice process, i.e., deciding between relatively more or less risky options. After developing a simple agent-based model to understand how aspiration levels influence adaptive learning from feedback, we report on behavioral laboratory experiments used to test our model’s predictions. In the canonical multi-armed bandit problem, we show that subjects assigned a high aspiration level exploit more – and that, when they do explore, they do so more narrowly – as compared with subjects assigned a moderate aspiration level. A high (moderate) aspiration level reduces (increases) feedback ambiguity about the relative attractiveness of different options, which affects agents’ subsequent sampling and hence their learning. The low levels of exploration engendered by high aspiration levels are advantageous in stable environments, but they impair performance in unstable environments.
Social Exchange and the Reciprocity Roller Coaster: Evidence from the Life and Death of Virtual Teams

Organizations are riddled with cooperation problems, that is, instances in which workers need to voluntarily exert effort to achieve efficient collective outcomes. To sustain high levels of cooperation, the experimental literature demonstrates the centrality of reciprocal preferences but has also overlooked some of its negative consequences. In this paper, we ran lab-in-the-field experiments in the context of open-source software development teams to provide the first field evidence that highly reciprocating groups are not necessarily more successful in practice. Instead, the relationship between high reciprocity and performance can be more accurately described as U-shaped. Highly reciprocal teams are generally more likely to fail and only outperform other teams conditional on survival. We use the dynamic structure of our data on field contributions to demonstrate the underlying theoretical mechanism. Reciprocal preferences work as a catalyst at the team level: they reinforce the cooperative equilibrium in good times but also make it harder to recover from a negative signal (the project dies). Our results call into question the idea that strong reciprocity can shield organizations from cooperation breakdowns. Instead, cooperation needs to be dynamically managed through relational contracts.
Do you speak ‘kid’? The role of experience in comprehending child speech

Child speech deviates from adult speech in predictable ways. Are listeners who routinely interact with children implicitly aware of these systematic deviations, and thereby better at comprehending children? In Experiment 1, we explore this possibility by testing three types of participants with variable experience interacting with children: undergraduates with minimal experience with children (N=48), mothers of young children (N=48), and early childcare educators (N=36). Participants transcribed single-word utterances produced by the same set of children at 2.5-, 4-, and 5.5-years-old. In Experiment 2, mothers (N=50) completed a similar transcription task that featured speech by their own, and another, 2.5-year-old child. Participants performed similarly regardless of their experience with children, while mothers demonstrated a Familiar Talker Advantage with their own child’s speech. Our findings suggest that while experience with children may not facilitate improved comprehension of child speech in general, it may lead to enhanced comprehension of those children in particular.
Association of Troponin-I Level on Admission with 6-month Clinical Consequences in Acute Coronary Syndrome Patients: A Preventive Approach in Patient Care

Background: Cardiovascular diseases are the leading cause of mortality worldwide. Therefore, it is important to predict the future consequences of the disease in patients who have recovered. Objectives: We sought to determine the relationship between troponin-I level and 6-month clinical consequences (i.e., re-infarction, death, re-angiography and coronary artery bypass grafting) in patients with acute coronary syndrome (ACS). Methods: This prospective cross-sectional study was performed among 60 patients with ACS admitted to Ayatollah Mousavi Hospital in Zanjan, Iran. The participants were chosen using the convenience sampling method. Troponin-I level in these patients was initially evaluated. Afterwards, they were followed up for six months in terms of clinical consequences. A checklist was prepared to collect the required data. The receiver operating characteristic (ROC) analysis was conducted to determine the predictive power of high-sensitivity troponin I for the mentioned consequences. Iodine index was calculated to determine the cutoff point for this enzyme in order to predict the consequences. Results: In general, 66.2% of the participants were male and the mean age was 60.46 ± 12.78 years. We found that 21.2% of the participants experienced one of the four clinical consequences in the follow-up period of 6 months. The sub-curved surface was calculated to be 0.705 for the prediction of consequences. The cutoff point for the prediction of consequences was 32.5; the negative predictive value for the cutoff point was 32.5, which was equal to 89.8%. Conclusion: Troponin-I has an acceptable predictive power to identify 6-month consequences of ACS. Moreover, considering the negative predictive value of troponin-I, it is recommended to use this biomarker in patients with ACS. In addition, healthcare providers should pay more attention to the follow-up of patients after discharge and design preventive programs.
Speaking rate and language-specific voice onset time effects on burst amplitude: Cross-linguistic observations and implications for sound change

The relationship between speaking rate and burst amplitude in voiceless plosives was investigated in two languages with differing oro-laryngeal timing implementations of phonological voicing, North American English and Indian Tamil. Burst amplitude (reflecting both intraoral pressure and flow geometry of the oral channel) was hypothesized to decrease in CV syllables with increasing speaking rate, which imposes temporal constraints on both intraoral pressure buildup behind the oral occlusion as well as respiratory air flow. Increased speaking rate led to decreased burst amplitude (relative to vowel amplitude) in both languages, with the magnitude of the effect being considerably weaker in Tamil, which has short-lag implementation of voice onset time. Bilabials in both languages were affected disproportionately relative to other places of articulation. Additionally, burst amplitudes were lower overall in Tamil, reflecting lower intraoral pressure which promotes faster vocalic onset. Results are discussed in terms of language-internal and extra-linguistic phonetic phenomena potentially serving as perceptual triggers for historical sound change.
The Effect of pH and Temperature on Phenol Coefficients of Two Common Disinfectants Using Clinical Isolates of Escherichia coli and Staphylococcus aureus

Aims: The aim of this study is to evaluate the efficacy of two disinfectants, Jik and Roberts, under use-conditions against some hospital isolates using their phenol coefficient. The effects of pH and temperature on the phenol coefficients were also tested. Phenol coefficient still remains a valuable means of determining the effectiveness of disinfectants, even though phenol is no longer commonly used for disinfection. Materials and Methods: Bacteria were isolated and identified using standard microbiological procedures from samples collected from the skin of patients and hospital environments like beddings, floors and trawlers. A 5% (w/v) solution of phenol and 5% (v/v) solution of disinfectants were used for determination of their phenol coefficients on standardized organisms containing about 1.5x10 8 cfu/ml. The effect of temperature was determined at 4oC and 45oC, while that of pH was Original Research Article Ononugbo et al.; JAMB, 10(2): 1-7, 2018; Article no.JAMB. 41376 2 determined at pH 1 and 13. Results: The results showed that Staphylococcus aureus was more susceptible to both disinfectants. Jik had a higher phenol coefficient for the test organisms (16 and 8) compared to Roberts (4 and 2) for S. aureus and Escherichia coli respectively. Both temperature and pH had a direct effect on the antibacterial activities of the disinfectants. The phenol coefficient was higher for both organisms at 45oC than at 4oC for Roberts. In the case of Jik, the phenol coefficient reduced as the temperature was increased to 45oC. At pH 13, Jik gave a higher phenol coefficient, while Roberts gave a higher phenol coefficient at pH 1. Conclusions: Temperature enhances the performance of Roberts but has a negative effect on that of Jik. Roberts performs better at acidic pH while Jik performs better at alkaline pH. For disinfection purposes, it is recommended that different types of disinfectants be employed in the rotation to help prevent the development of resistant strains of microorganisms.
Review of Cross-Border E-Commerce and Directions for Future Research

The emergence of cross-border e-commerce (CBeC) has brought substantial changes to both businesses and consumers. Although CBeC businesses have existed for less than a decade, many academic researchers addressed important issues in this context. It is essential to evaluate what has been studied through a structured review of the literature and derive meaningful insights given that research on this topic is new and largely fragmented. Therefore, this study conducts a review of CBeC literature to find the current gaps and fragmentation to provide guidelines for future research. The review shows that research in this domain needs more attention and enforcement to address the current research gaps. Addressing the current gaps helps academia build a rigorous body of knowledge and enables practitioners to solve challenging business problems.
Individual Differences and Expectations of Automated Vehicles

ABSTRACT Despite the benefits of automated vehicles (AVs), there are still barriers to their widespread adoption. Expectations about AVs have been identified as one of the most important factors in understanding AV adoption. Therefore, by understanding the public’s expectations of AVs, we can better understand whether or when AVs are likely to be adopted on a wide scale. Individual differences, including demographics and personality, have been identified as factors that impact technology expectations and adoption. However, it is not clear whether and how individual differences can influence expectations of AVs. To examine this, we conducted an online survey with 443 U.S. drivers who were recruited and divided into subpopulations by age, gender, ethnicity, census region, educational level, marital status, income, driving frequency, driving experience, and personality traits. Results revealed that drivers’ expectations of AVs differ significantly by age, gender, ethnicity, education levels, marital status, drive frequency, drive experience, and personality. More specifically, higher expectations are more often generated by drivers who are younger, men, White non-Hispanic, more highly educated, never married, with a higher frequency of driving, with less driving experience, and who are high in extraversion, agreeableness, conscientiousness, and emotional stability. The results of this study provide a foundation for future research related to expectations and have important implications on future design and development of AVs.
Real Time News Headlines Classification Using Machine Learning

- The online news portals consist of several types of information entering from various sources. In most real-life scenarios, it is greatly desirable to classify this information in an appropriate set of categories and it is important to have an efficient system of segregating news into different groups. Machine Learning is used to enhance and improve the system of classification. Research in the domain of news headlines classification is superficial, and this leads to an opportunity to analyze this topic in greater depth. This paper focuses on real time news classification on the basis of its headlines. A system has been designed to classify each news headline to its pre-defined category. The model is trained such that the machine is be able to predict the category of the news item accurately. A hybrid model based on different algorithms has been created to increase the accuracy of standalone algorithms. The news headline will be fetched in real time and will be passed through this classifier. This whole process will not only lead to a better working model but also show a comparative study of different models for classifying news headline.
An Analysis of the Relationship between College Football Fans and their Rival Teams

Name: Morgan Young Date of Degree: August 12, 2016 Institution: Mississippi State University Major Field: Sports Administration Major Professor: Younghan Lee Title of Study: An analysis of the relationship between college football fans and their rival teams Pages in Study: 65 Candidate for Degree of Master of Science The current study explored how fan identification and negative rival perception affect the decision to blast or support the rival in indirect competition in college football. 258 participants (M age=24.15, 51.16% female) responded after being targeted via social media, email, and in person. Fans higher in identification had a more negative rival perception, were more likely to blast the rival, and were less likely to support the rival in indirect competition. A negative rival perception increased blasting and decreased rival support. The results contribute to current literature on rivalry and fan identification and aid marketers in marketing segmentation and targeting new segments to increase viewership and attendance.
Towards instance-optimized data systems

In recent years, we have seen increased interest in applyingmachine learning to system problems. For example, there has been work on applying machine learning to improve query optimization, indexing, storage layouts, scheduling, log-structured merge trees, sorting, compression, and sketches, among many other data management tasks. Arguably, the ideas behind these techniques are similar: machine learning is used to model the data and/or workload in order to derive a more efficient algorithm or data structure. Ultimately, these techniques will allow us to build “instance-optimized” systems: that is, systems that self-adjust to a given workload and data distribution to provide unprecedented performance without the need for tuning by an administrator. While many of these techniques promise orders-of-magnitude better performance in lab settings, there is still general skepticism about how practical the current techniques really are. The following is intended as a progress report on ML for Systems and its readiness for real-world deployments, with a focus on our projects done as part of the Data Systems and AI Lab (DSAIL) at MIT. By no means is it a comprehensive overview of all existing work, which has been steadily growing over the past several years not only in the database community but also in the systems, networking, theory, PL, and many other adjacent communities. PVLDB Reference Format: Tim Kraska. Towards instance-optimized data systems. PVLDB, 14(12):
Import Competition, Quality Upgrading, and Exporting: Evidence from the Peruvian Apparel Industry

This paper studies quality upgrading to escape competition from low-wage countries and proposes a new channel that does not rely on access to new inputs or markets. Informed by Peruvian apparel firms' response to China's WTO accession, I introduce factor specificity in a multi-product-firm model. Profitability losses due to competition in low-quality segments induce Firms to reallocate specific factors to produce high-quality varieties for high-income countries. Gains from this channel are large. Using an observed quality measure, I show that import competition substantially increases domestic firms' exports and high-quality export shares. Firms also reduce prices, resulting in additional welfare gains.
Judicial Recentralization as Political Control: A Difference-in-Differences Analysis of Judicial Leader Rotation in China

This study analyzes how authoritarian leaders use the judicial system to solve the principal-agent problem in the government hierarchy. We argue that autocrats recentralize court personnel to enhance the central government's monitoring power over local officials. We test this executive constraint theory using panel data on Chinese provincial-level court leaders who served from 2003 to 2012. Our empirical analysis takes advantage of a quasi-natural experiment in which the Chinese Communist Party recentralized court personnel by rotating provincial-level court leaders in 17 out of 31 provinces. We find that judicial recentralization increased adjudicated administrative lawsuits by nearly 30%, but it did not impact the approval of other lawsuits. We also show that judicial rotation increased the appearance of the executive in administrative lawsuits, providing additional support for the executive constraint theory.
Can a Global Legal Misfit be Fixed? Shareholder Stewardship in a Controlling Shareholder and ESG World

As demonstrated by one of the authors elsewhere, UK-style shareholder stewardship is a ‘global legal misfit’ because it was designed for a jurisdiction with dispersed shareholding where institutional investors collectively control a majority of the shares; however, it has been transplanted into jurisdictions where controlling shareholders predominate and institutional shareholders are collectively minority shareholders. This Chapter addresses an important question that naturally flows from this reality: what ought to be the role of shareholder stewardship in a world dominated by controlling shareholders? This question is answered by analyzing the effectiveness of shareholder stewardship as a mechanism for advancing ESG in controlled jurisdictions – especially when compared to other viable alternatives. It then operationalizes this analysis by evaluating the effectiveness of the only stewardship code in the world – the Singapore Family Code – that has attempted to reorient UK-style stewardship to a controlling shareholder environment. This Chapter concludes that the prospects for shareholder stewardship in jurisdictions where controlling shareholders predominate will likely be limited. Although a reoriented approach to shareholder stewardship may play a role in nudging controlling shareholders towards ESG, hard law will likely be necessary to bring about real change. Unfortunately, this suggests that shareholder stewardship may be used as a ‘smoke screen’ by controlling shareholders and governments to send a formal signal that they are addressing ESG in controlled jurisdictions – when, in reality, functional change will be limited in practice.
The Macroeconomic Effects of Tax Shocks: The Cost Channel

I develop a simple analytical New Keynesian model with a cost channel to gain new insights into the general properties of tax shocks. In this paper, I formally show that the cost channel itself can rule out the sunspot liquidity traps and secure a unique equilibrium with tax shocks. I also contribute to the tax-related literature that the absolute magnitudes of output gap and inflation multipliers due to a cost channel with/without the zero lower bound binding are heterogeneous compared with the standard model and the multipliers can be reproduced with a wide range of estimates. Finally, the multipliers are robust with the medium run tax cut policy except the consumption tax.
Land-use change and Biogeochemical controls of soil CO2, N2O and CH4 fluxes in Cameroonian forest la

Deforestation and land-use change are accelerating in the Congo Basin and elsewhere in the tropics affecting the soil-atmosphere exchange of greenhouse gases (GHG). There is a lack of data from Central Africa. We quantified fluxes of CO2, CH4, and N2O at the soilatmosphere interface in a secondary forest, a cocoa agroforest, and an unfertilized cropland. Soil respiration was highest in the secondary forest (15.37 ± 3.42 Mg C ha y), intermediate in the cacao agroforest (12.26 ± 2.91 Mg C ha y) and the lowest in the unfertilized cropland (8.74 ± 2.62 Mg C ha y). Likewise, N2O fluxes were highest in the secondary forest (2.17 ± 0.20 kg N ha y), intermediate in the cacao agroforest (1.40 ± 0.08 kg N ha y) and lowest in the unfertilized cropland (1.04 ± 0.15 kg N ha y). Soils were a sink for atmospheric CH4 and sink strength was high in the secondary forest (−3.60 ± 1.83 kg CH4 ha −1 y) and cacao agroforest (−3.61 ± 2.09 kg CH4 ha −1 y) and low in the unfertilized cropland (−1.9 ± 1.59 kg CH4 ha −1 y). Variation in soil water content rather than temperature was the dominant driver of seasonal variations of the fluxes at all study sites and N availability affected both N2O and CH4 fluxes. Our results suggest that tropical land-use change is decreasing soil respiration, decreasing the strength of the soil CH4 sink and decreasing N2O emissions, in landscapes that do not practice agriculture with chemical fertilization. ARTICLE HISTORY Received 27 September 2019 Accepted 29 May 2020