Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Effect of Seasonal Plant Growth and Development in Three-Dimensional Atmospheric Simulations. Part I: Simulation of Surface Fluxes over the Growing Season

Abstract The authors examine the effect of seasonal crop development and growth on the warm-season mesoscale heat, moisture, and momentum fluxes over the central Great Plains region of North America. The effect of crop growth and development on the atmospheric boundary layer is addressed in a follow-up paper (Part II). Energy, moisture, and momentum fluxes are studied over a maize agroecosystem at the scale of a 90-km atmospheric grid cell. Daily plant development and growth functions incorporated into the surface flux calculations are based on a physiological crop growth model CERES-Maize version 3.0. CERES-Maize simulates daily plant growth and development as a function of both environmental conditions (temperature, precipitation, solar radiation, and soil moisture) and plant-specific genetic parameters. Plant growth and development functions from CERES were incorporated into the Biosphere–Atmosphere Transfer Scheme (BATS), and selected crop parameters [i.e., Leaf Area Index (LAI) and crop height] were .
Assessment of the Neotropical dry forest refugia hypothesis in the light of palaeoecological data and vegetation model simulations

Seasonally dry tropical forests exhibit a markedly discontinuous, disjunct distribution pattern across South America. Previous botanical inventories have revealed that these dry forest areas exhibit close floristic links with one another, which has led to the hypothesis that they constitute modern‐day refugia, resulting from vicariance (i.e. fragmentation) of a formerly more widespread, continuous distribution during more arid climatic conditions associated with the Last Glacial Maximum (LGM). This paper examines the validity of this ‘dry forest refugia’ hypothesis in the light of previously published fossil pollen data and vegetation model simulations. The model simulations suggest that major dry forest areas, such as the Bolivian Chiquitano Dry Forest, are not Pleistocene refugia, but instead developed during the Holocene by population expansions from parts of southern Amazonia presently covered by evergreen rainforest. The limited pollen data available indicate that glacial‐age seasonally dry tropical forests, irrespective of their distribution, were floristically quite different from those of today, with key dry forest species, such as Anadenanthera, only appearing in the Holocene. I suggest that a more parsimonious explanation for the current biogeographic pattern of these South American dry forests is population migration (perhaps by long‐distance dispersal) since the LGM, rather than vicariance. Copyright © 2004 John Wiley & Sons, Ltd.
Title Identifying spatial invasion of pandemics on metapopulationnetworks via anatomizing arrival history

Spatial spread of infectious diseases among populations via the mobility of humans is highly stochastic and heterogeneous. Accurate forecast/mining of the spread pro cess is often hard to be achieved by using statistical or mechanic al models. Here we propose a new reverse problem, which aims to identify the stochastically spatial spread process itse lf from observable information regarding the arrival history of in fectious cases in each subpopulation. We solved the problem by developing an efficient optimization algorithm based on dynamical programming, which comprises three procedures: i, anatomi zing the whole spread process among all subpopulations into disj oint componential patches; ii, inferring the most probable invasion pathways underlying each patch via maximum likelihood esti mation; iii, recovering the whole process by assembling the in vasion pathways in each patch iteratively, without burdens in parameter calibrations and computer simulations. Based on the entrop y theory, we introduced an identifiability measure to assess t he difficulty level that an invasion pathway can be identified. Results on both artificial and empirical metapopulation networks show the robust performance in identifying actual invasion pathways driving pandemic spread.
Novel methods for improved tree breeding

The development and implementation of statistical tools to improve inference in sustainable forest tree breeding are presented here. By combining classical quantitative genetic theory and novel statistical methods, a number of parameters are optimized. The results obtained are compared to those achieved by traditional methods for visualizing improvements to genetic parameters. The methods are tested on both simulated data and on a real Scots pine pedigree. Modeling non-additive gene action using a finite loci model indicates that the development of the additive variance component does not decay initially as the underlying theory predicts. This phenomenon is shown for different sets of genetic components and models. In addition, variable numbers of loci were used so that different numbers of interactions could be captured. To draw inferences about the genetic parameters, a powerful Bayesian Markov chain Monte Carlo method was developed. The method utilizes transformation of the genetic covariance structure to improve computational speed. By combining two different Bayesian Gibbs samplers, a useful hybrid sampler was developed; this was found to enhance convergence statistics and computational speed. A method that finds the number of trees and their respective mating proportions that will maximize genetic gain was implemented and modified to handle a large number of selection candidates. When testing the selection method on a real pedigree an increase in genetic gain of up to 30 % was found compared to traditional methods in which the same restrictions were placed on relatedness. In order to provide a long-term breeding perspective, the selection method was combined with various mating schemes to examine the development of genetic parameters. A modified minimum coancestry mating scheme resulted in a level of genetic gain closest to the theoretically achievable limit while reducing the level of inbreeding in the population.
Identification of yeast species from uncultivated soils by sequence analysis of the hypervariable D1/D2 domain of LSU–rDNA gene in Kermanshah province, Iran

Yeasts are a polyphyletic group of ascomycete and basidiomycete fungi characterized by having a unicellular growth phase and sexual stages that are not enclosed in fruiting bodies. An attempt was made to identify yeast species in uncultivated soils collected from different areas of Kermanshah province, Iran, by analyzing hypervariable D1/D2 domain of the large subunit (LSU) rDNA gene sequenceand comparing the sequences with that available in NCBI database. In this study, 25 soil samples were analyzed and eight species including Rhodotorula toruloides (KP324973)*, Trichosporon coremiiforme (KP055040)*, Naganishia uzbekistanensis (KP324959), Candida catenulata (KP324968), C. paracilopsis (KP324965)*, C. boidinii (KP324 962)*, Lecythophora sp. (KP336745)* and Meyerozyma guilliermondii (KPKP324971, KP324978)were identified. Phylogenetic analysis based on D1/D2 regions allowed us to establish the precise taxonomic placement of each species. The Canonical correspondence analysis (CCA) indicated that elevation, EC, pH, and clay were important environmental parameters influencing basidiomycete yeast distribution in uncultivated soils. In this study, the presence of eight species is confirmed that asterisk species are the new records for the mycobiota of Iran.
The Benchmark Macroeconomic Models of the Labour Market

This technical note aims to provide a practical overview of the labour market’s benchmark macroeconomic models. The matching models are the primary and most popular theoretical tools used by economists to evaluate various labour market policies and to study the problem of unemployment. These models explain the co-existence in equilibrium of unemployment and vacancies through frictions in matching workers and firms and generate predictions that have the right direction: unemployment goes up in recession and down in boom, while job vacancies shift in the opposite direction. The central role of these models in imperfect labour markets has recently been confirmed by the 2010 Nobel Prize for economy awarded to the founders of this approach: Peter Diamond, Dale Mortensen and Christopher Pissarides.
DESEMBER 2003 ADOPTION OF VARIABLE RATE TECHNOLOGY

Site Specific Management (SSM), which also variously referred to as Variable Rate Technology (VRT), is an emerging technology that enables producers to make more precise input application decisions based on soil and field characteristics. This study analyzes factors influencing the adoption of VRT for fertilizer application for cash grain production in Ohio. Results show that producer and field characteristics might influence the adoption decision on various SSM components differently. It also provides insight as to the sequence of adoption of SSM component technologies and how this sequence might differ for producers of differing characteristics.
The Vicissitudes of Education Policy : Assessing Top-down Change on English Language Education in Japanese High Schools

本論文では、日本の高等学校の英語教育における英語教育改革を教育における変化・変容というより広い文脈に位置づけて考察を加える。 日本の教育改革における際立つ特徴として、筆者らは中央の権威によって主導される変革という意味で、官僚主義的であり、役割モデル的な側面を指摘する。 文部科学省が公刊した文書に示されている現在進行中の英語教育改革(例えばアクション・プラン)に関連づけて述べるならば、そのような改革の成否は「コミュニケーション志向の英語教育改革という流れの詳細な分析、考察」「教師に対する研修機会の提供」「試験やその他の手段による学習者の適切な評価」という3つの事柄にかかっていると考える。 より具体的に言えば、日本の英語教育改革を理念的に支えているコミュニケーション志向のアプローチは、確立した一つの教授法という性格は有しておらず、教師が自らの教育方法や指導技術を同僚らと議論し、内省的に評価しうる場が必要であること、そのための物理的な時間を現場の教師は保証されるべきであると考える。 また、学習者の評価に関わっては多肢選択型の入試が学校教育にもたらすマイナス作用というものをコミュニケーション志向の英語教育改革という基本的な方向性とより整合性を有する他の評価手段(たとえばポートフォリオを用いた評価)を採用することによって相殺する必要があることも指摘する。
Relocating resource peripheries to the core of economic geography's theorizing: rationale and agenda

Theorizing in economic geography has focused on core regions, industrial and non-industrial, old and new. Indeed, contemplation of the idea of globalization has reinforced this quest. This paper disputes this blinkered thinking that peripheralizes resource peripheries, and seeks to re-position and emphasize resource peripheries within economic geography’s theoretical agenda, specifically that associated with the new ‘institutional’ approach. A truly ‘global’ economic geography cannot afford to ignore resource peripheries. In particular, we argue that characterizing resource peripheries, and making them distinct from cores, is the intersection of four sets of institutional values or dimensions which we summarize in terms of industrialism (economic dimension), environmentalism (environmental dimension), aboriginalism (cultural dimension) and imperialism (geopolitical dimension). This admittedly preliminary framework underlies our hypothesis that resource peripheries around the world have become deeply contested spaces, much more so than those found in cores.
Title The evolving landscape of healthcare-associated infections : Recent advances in prevention and a road map for research Permalink

This white paper identifies knowledge gaps and new challenges in healthcare epidemiology research, assesses the progress made toward addressing research priorities, provides the Society for Healthcare Epidemiology of America (SHEA) Research Committee’s recommendations for high-priority research topics, and proposes a road map for making progress toward these goals. It © 2014 by The Society for Healthcare Epidemiology of America. All rights reserved. Address correspondence to Nasia Safdar, MD, 600 Highland Avenue, H4/574, Madison, WI 53792 (ns2@medicine.wisc.edu). Potential conflicts of interest. All other authors report no conflicts of interest relevant to this article. HHS Public Access Author manuscript Infect Control Hosp Epidemiol. Author manuscript; available in PMC 2015 May 01. Published in final edited form as: Infect Control Hosp Epidemiol. 2014 May ; 35(5): 480–493. doi:10.1086/675821. A uhor M anscript
Self-Reconfigurable Control - Part II: Executing Based on Model Checking

This paper presents a formal framework for reconfigurable control, based on model checking. This framework first generates a flexible model (i.e., an execution structure) according to the diagnosis, then defines a temporal specification language to deal with the problems due to infinite execution cycles and non-determinism, and finally provides the algorithms that will automatically verify whether the updated model satisfies the desired specification. Our entire procedure of reconfigurable control is as follows: for a given series of observations and diagnoses, if there are faults in system, then a revised system model is constructed flexibly, according to the diagnoses, observations and available system descriptions. Next, model checking is applied to verify whether or not the current system model satisfies the desired objectives. This automatic reconfigurability calculation is one of the most important steps in our framework. If the given control objectives are achievable, the system will run according to the observations and current system model. Otherwise, the reconfiguration is considered as failed. Keywords-STRIPS; Model checking; Automated Planning; Reconfigurable Control; Cause-effect
The Impact of Uncertain Ecological Knowledge on a Water Suitability Model of Riverine Vegetation

Freshwater aquatic ecosystems are increasingly under threat due to climate change and river regulation. Water management is considered important for maintaining and restoring freshwater aquatic ecosystems in Australia. A habitat model based on the water requirements of four riverine vegetation species was developed to assess the suitability of water regimes for the maintenance and regeneration of these species in the Namoi Catchment, Australia. This model identifies characteristics of flooding events (e.g. duration, timing and inter-flood dry period) from hydrological data or models, and generates suitability indices based on the species’ water requirement preference curves. These preference curves are central to the model and were established based on expert knowledge. Two comprehensive sources are available on the water requirements of vegetation species in the Murray-Darling Basin, Australia: Rogers and Ralph [2010] and Roberts and Marston [2011]. Both of these sources are based on extensive review of studies on species’ response to flooding in the Murray-Darling Basin. The water requirements proposed in these two sources differ due to differences in literature selection and interpretation of the literature by the authors. In this paper, we examine how these interpretations affect the outcomes of the Namoi ecological model. Two sets of preference curves are produced based on Rogers and Ralph [2010] and Roberts and Marston [2011], respectively, and the model outputs are compared. The goal is to understand the robustness of the model and how the model behaves in face of imperfect knowledge and information in ecosystem’s response to water regime. Significant differences in model outputs were found for periods with large winter floods and for less commonly studied species such as water couch where there is higher uncertainty associated with water requirements. This understanding is critical to guide data collection and future model development.
How positive is the feedback between climate change and the carbon cycle?

Future climate change induced by atmospheric emissions of greenhouse gases is believed to have a large impact on the global carbon cycle. Several offline studies focusing either on the marine or on the terrestrial carbon cycle highlighted such potential effects. Two recent online studies, using ocean—atmosphere general circulation models coupled to land and ocean carbon cycle models, investigated in a consistent way the feedback between the climate change and the carbon cycle. These two studies used observed anthropogenic CO2 emissions for the 1860–1995 period and IPCC scenarios for the 1995–2100 period to force the climate – carbon cycle models. The study from the Hadley Centre group showed a very large positive feedback, atmospheric CO2 reaching 980 ppmv by 2100 if future climate impacts on the carbon cycle, but only about 700 ppmv if the carbon cycle is included but assumed to be insensitive to the climate change. The IPSL coupled climate – carbon cycle model simulated a much smaller positive feedback: climate impact on the carbon cycle leads by 2100 to an addition of less than 100 ppmv in the atmosphere. Here we perform a detailed feedback analysis to show that such differences are due to two key processes that are still poorly constrained in these coupled models: first Southern Ocean circulation, which primarily controls the geochemical uptake of CO2, and second vegetation and soil carbon response to global warming. Our analytical analysis reproduces remarkably the results obtained by the fully coupled models. Also it allows us to identify that, amongst the two processes mentioned above, the latter (the land response to global warming) is the one that essentially explains the differences between the IPSL and the Hadley results.
Syntactic Annotation of Learner Corpora

Syntactic annotation of learner corpora is useful for investigating the grammatical properties of learner language. We discuss two approaches to syntactic annotation based on different methodological choices. One approach, recently proposed in the literature, is the manual annotation of learner language with dependency relations. Another approach, which we present as an alternative, is based on automatic parsing of a ‘correct’ version with an L2
Education and Labor Market Policies in an Offshoring Global Economy 1

With rising unemployment and increasing income inequality, the labor market consequences of globalization and offshoring are back in the headlines. This paper summarizes recent research using Danish matched worker-firm data to examine how offshoring affects labor market outcomes. First, a rise in offshoring leads to a shift in the composition of labor demand toward particular occupation types within skill groups. Second, workers displaced from offshoring firms suffer more significant income losses than workers displaced for other reasons. Finally, training programs are used more intensively by workers initially employed by offshoring firms and these workers reemploy with manufacturing firms at a faster pace than other workers. These findings are used to draw some education and labor market policy implications.
Cluster detection and clustering with random start forward searches

ABSTRACT The forward search is a method of robust data analysis in which outlier free subsets of the data of increasing size are used in model fitting; the data are then ordered by closeness to the model. Here the forward search, with many random starts, is used to cluster multivariate data. These random starts lead to the diagnostic identification of tentative clusters. Application of the forward search to the proposed individual clusters leads to the establishment of cluster membership through the identification of non-cluster members as outlying. The method requires no prior information on the number of clusters and does not seek to classify all observations. These properties are illustrated by the analysis of 200 six-dimensional observations on Swiss banknotes. The importance of linked plots and brushing in elucidating data structures is illustrated. We also provide an automatic method for determining cluster centres and compare the behaviour of our method with model-based clustering. In a simulated example with eight clusters our method provides more stable and accurate solutions than model-based clustering. We consider the computational requirements of both procedures.
The Addition of High Intensity Interval Training Reduces Cardiovascular Disease Risk Factors and Enhances Strength in Active, Healthy Adults

The guidelines for cardiovascular exercise intensity are not clear with respect to the optimal training protocols to reduce cardiovascular disease risk (CVD) as well as to enhance strength. At this time, it is impossible to deduce the independent effects of vigorous-intensity exercise from past studies as the volume of either physical activity duration or energy expended differed in comparison to moderate-intensity exercise. Our goal was to augment the literature focused on the potential benefits of high intensity training with novel methodology that includes trained adults in a group fitness environment. Vigorous intensity training may be a critical component of the physical activity prescription if active adults demonstrate decreases in CVD risk factors and increases in strength. We hypothesize that a 6-week high intensity group fitness intervention will produce beneficial effects on CVD risk factors by reducing body mass, total cholesterol, LDL-C, triglyceride concentration, and by enhancing lean body mass percentage, HDL-C, glucose tolerance, and maximal oxygen consumption as well as both upper and lower body strength. Eighty-four healthy adults, 50 women and 34 men, completed the 6-week intervention. Participants were randomly assigned to one of two groups; the first was a high intensity interval-training (GRIT) program, while the second was a moderate intensity-training (FIT) program. All participants completed 5 hours of fitness classes per week. We collected musculoskeletal and physiological data at the start and finish of the study. In support of our hypotheses, the GRIT group significantly reduced body mass, triglyceride concentration and enhanced lean body percentage, glucose tolerance, and maximal oxygen consumption in addition to all of the strength measures. These results illustrate a novel finding that individuals who already participate in the recommended physical activity guidelines can improve their health, fitness and strength with the addition of 2, 30-minute sessions of high intensity interval training per week.
Geographical epidemiology of common methods of suicide and suicide attempts during the years 2010-2013 in Fars Province, Iran

Received: November 2015, Accepted: February 2016 Background: One of the important aspects of the epidemiologic study of suicide and its related behaviors is the identification of suicide methods. This study aimed to investigate the geographical epidemiology of common methods of suicide and suicide attempts in Fars Province located in Southwestern Iran during the years 2010-2013. Materials and Methods: The present study was conducted on 17,342 suicide and suicide attempt cases in Fars Province. To collect the data, the monthly suicide prevention program checklist was used. Data were analyzed using the SPSS software, R software, and ArcGIS software. Using Bayesian hierarchical models, the standardized mortality ratios (SMRs) were prepared and calculated according to the common suicide and suicide attempt methods. Results: On average, the suicide rate in Fars Province was 3.85 in one hundred thousand people per year. The geographic pattern of suicide in the mentioned province showed that the highest rates of hanging were reported in the cities of Firuzabad, Farashband, and Larestan, Iran, and the highest rates of self-immolation were reported in cities of Mamasani, Shiraz, and Firuzabad, Iran. Conclusions: Despite the low rate of suicide in the cities of Fars Province, the rate of suicide-related behaviors, including suicide attempt and suicide by violent and deadly methods, was high in some areas of the province. Therefore, restricting access to lethal means and methods of suicide and planning to identify areas with high risk for suicide in the province is necessary.