Miracle-dz/UniFAR-FTUs huggingface dataset:
Past and future changes in frost day indices in Catskill Mountain region of New York

Changes in frost indices in the New York's Catskill Mountains region, the location of water supply reservoirs for New York City, have potentially important implications. Frost day is defined as a day with Tmin < 0 °C. The objective of this study was to investigate past and predicted changes in minimum temperature (Tmin) and six frost indices in the Catskill Mountains covering six reservoir watersheds. Studied frost indices included (1) number of frost days, (2) number of months with frost, (3) last spring freeze date (LSF), (4) first fall freeze date (FFF), (5) growing season length (GSL), and (6) frost season length. Past changes in the frost indices were studied using observed daily Tmin for each watershed for the periods 1960–2008. Future changes in frost indices for the periods (2045–2065 and 2080–2100) were studied for emission scenarios (A1B, A2, and B1) downscaled from global climate models (GCMs). Results indicated a general increase in average Tmin and GSL and a decrease in number of frost days, months with frost, frost season length, earlier LSF, and later FFF from the historical to the future periods, and the magnitude of change varied among the watersheds and GCMs. For the period 1960–2000, in all watersheds (except Cannonsville), LSF occurred earlier by 2.6–4.3 days/decade, FFF occurred later by 2.7–3.2 day/decade, and GSL was longer by 2.4–4 day/decade. Among the scenarios and GCMs, LSF occurred earlier by 4–11 and 4.5–15 days/decade for the periods 2045–2065 and 2081–2100, respectively; FFF occurred later by 1–10 and 4–13 days/decade for the periods 2045–2065 and 2081–2100, respectively; and GSL was longer by 10–25 and 13–40 days/decade for the periods 2045–2065 and 2081–2100, respectively. The increase in GSL is expected to affect hydrologic, ecosystem, and biogeochemical processes with increased net primary productivity and a resulting increase in total annual evapotranspiration. Copyright © 2013 John Wiley & Sons, Ltd.
Building A Healthy Online Student Community Through Education Environ- ment Design

Studies have highlighted social interaction and collaborative effort within a student community as important elements that contribute to successful learning. College students in face-to-face settings build a sense of community and bond through real-time interpersonal interactions during classroom experiences and co-curricular activities. Online college students often do not enjoy such substantive community experiences, and, in part because of this, they achieve lower rates of persistence to degree completion. Studies have examined this discrepancy in persistence to degree and found that the physical separation between an online student and their educational institution can lead to a sense of isolation. This sense of isolation in turn can lead to an online student’s sense of alienation from their institution and powerlessness to change their situation. Numerous underlying factors appear to contribute to these feelings, including the usability of the technology tools that power the online education environment and the quality of student-faculty and student-student interactions that those tools enable. As online education becomes increasingly pervasive, educational institutions should consider how best to design online programs to foster healthy student communities. The literature suggests several methods for achieving such communities and improving student retention. First, students (and faculty) should be carefully introduced to effective online education tools that facilitate interaction. Second, effective channels of student-faculty communication should be outlined and encouraged so that students and faculty interact in a timely, clear, and positive manner. Third, educationrelated student-student avenues for online interaction should be introduced so that a sense of student community can develop. The activities reported here build upon the literature, which has generally focused upon asynchronous online learning environments, by considering development of student community in a synchronous online environment. While the underlying strategies are similar, the particular solutions vary. This paper describes a recently developed online learning environment for engineering education and student use of the tools of that environment to forge bonds with one another, their faculty instructors, and the broader engineering community. The strengths and opportunities for improvement from the perspective of the student were captured in a survey administered to students participating in the online engineering program. This survey serves as a baseline from which to measure the development of community and to determine which resources offer the most effective means for communication and community development.
Entropy and river meander planform

This study departs from the hypothesis that the often striifing geometric similarity and regularity of meanders is the result of the second law of thermodynamics applied to open dissipative systems. It is argued that along a meandering river the continuous production of entropy is as low and as uniform as possible. An expression of entropy production in a moderately meandering river is derived. A dimensioniess form of Odgaard's Meander flow model (1986a) is used to evaluate this expression along different meander bends described by the class of third order sine-generated curves. The results show a minimum variance of entropy production for a fattened curve with upvalley skewing, indicating that meander asymmetry described by Carson and Lapointe (1983) is in correspondence with the Theory of minimum variance (Langbein and Leopold, 1966).
1 Exploring the spatial heterogeneity of individual 2 preferences for ambient heating systems 3

The estimation and policy use of spatially explicit discrete choice models has yet to receive 15 serious attention from practitioners. In this study we aim to analyze how geographical variables 16 influence individuals’ sensitivity to key features of heating systems, namely investment cost and 17 CO2 emissions. This is of particular policy interest as heating systems are strongly connected to two 18 major current environmental issues: emissions of pollutants and increased use of renewable 19 resources. We estimate a Mixed logit model (MXL) to spatially characterize preference 20 heterogeneity in the mountainous North East of Italy. Our results show that geographical variables 21 are significant sources of variation of individual’s sensitivity to the investigated attributes of the 22 system. We generate maps to show how the willingness to pay to avoid CO2 emissions varies across 23 the region and to validate our estimates ex-post. We discuss why this could be a promising approach 24 to inform applied policy decisions. 25
Modeling Mode and Time-of-Day Choice with Joint RP and SC Data

Trip departure time has become a more important theme in practice as urban congestion problems are increasingly addressed by travel demand management (TDM) strategies. In this paper, the authors formulate and estimate a joint mode-departure time choice model using combining revealed preference (RP) and stated choice (SC) data about commuting trips in Santiago. The information was gathered through a series of surveys (RP, SC and attitudinal survey) applied to some 500 commuters in the Santiago Metropolitan Area. The travel time, cost and cost divided by wage rate coefficients were fairly similar in both environments (RP and SC), while schedule delay (SD) penalties associated with early or late arrival to work differed between each data. The degree of flexibility that workers have to adjust their arrival time to work resulted to be statistically significant when interacted with SD terms, suggesting that the level of work flexibility indeed influences temporal choices. The use of different time-resolution intervals showed that goodness of fit of the estimated models increased when higher time resolutions (i.e. length of departure time intervals) were considered, but values of time could differ when using distinct aggregation of trip departure time alternatives.
Extinction and the importance of history and dependence in conservation

ABSTRACT Many extinct species have had profound effects on other species through their interactions. In themselves, these interactions or functions are an integral part of biodiversity. The influence of species upon others operates in a variety of ways, independently or synchronously, and includes dispersal, habitat creation and maintenance, provision of nutrients or food resources, and reduction in competition from other species. In particular, large and/or abundant vertebrates that are now extinct or threatened have contributed to extensive environmental heterogeneity. This heterogeneity, or diversity, found in the form of spatial and temporal patches, has generally increased biodiversity. Loss of these vertebrates has major impacts on the species left behind. These impacts range from extinction to various levels of decline. The extinct and extirpated species discussed include the Passenger Pigeon (Ectopistes migratorius), Carolina Parakeet (Conuropsis caroliniensis), Dodo (Raphus cucullatus), American Bison (Bison bison), bears (Ursus spp.), Black-tailed Prairie Dog (Cynomys ludovicianus), gophers (Thomomys spp.), Elephants (Loxodonta africana), White Rhinos (Ceratotherium simum) and the Pleistocene megafauna including mammoths (Mammuthus spp.), horses (Equus spp.), camels (Camelops spp.), and Ground Sloths (Nothrotheriops shastense).
Macroeconomic Forecasting with Independent Component Analysis

This paper considers a factor model in which independent component analysis (ICA) is employed to construct common factors out of a large number of macroeconomic time series. The ICA has been regarded as a better method to separate unobserved sources that are statistically independent to each other. Two algorithms are employed to compute the independent factors. The first algorithm takes into account the kurtosis feature contained in the sample. The second algorithm accommodates the time dependence structure in the time series data. A straightforward forecasting model using the independent factors is then compared with the forecasting models using the principal components in Stock and Watson (2002). The results of this research can help us to gain more knowledge about the underlying economic sources and their impacts on the aggregate variables. The empirical findings suggest that the independent component method is a powerful method of macroeconomic data compression. Whether the ICA method is superior over the principal component method in forecasting the U.S. real output and inflation variables is however inconclusive
Display-sites selection by houbara bustard (Chlamydotis [undulata] macqueenii) in Mori, Xinjiang, People's Republic of China

Display-site selection by houbara bustards was studied in Mori, Xinjiang, China during the breeding seasons from April to June 2000. Most of the habitats chosen for displaying were short sub-shrubby and open areas close to high shrub patches. The displaying males clearly prefer low covered areas and avoid densely covered and high vegetation sites. The vegetation density and number of plant species at display sites were significantly lower from that at randomly selected sites. The average distance to the closest shrub patch was significantly shorter at display sites than at random sites. Plant species richness, vegetative density, vegetative cover and distance to the shrub patches are possibly the most important factors that determined the display-sites selection of houbara bustard.
A weekly, continually updated dataset of the probability of large wildfires across western US forests and woodlands

Abstract. There is broad consensus that wildfire activity is likely to increase in western US forests and woodlands over the next century. Therefore, spatial predictions of the potential for large wildfires have immediate and growing relevance to near- and long-term research, planning, and management objectives. Fuels, climate, weather, and the landscape all exert controls on wildfire occurrence and spread, but the dynamics of these controls vary from daily to decadal timescales. Accurate spatial predictions of large wildfires should therefore strive to integrate across these variables and timescales. Here, we describe a high spatial resolution dataset (250 m pixel) of the probability of large wildfires ( > 405 ha) across forests and woodlands in the contiguous western US, from 2005 to the present. The dataset is automatically updated on a weekly basis using Google Earth Engine and a continuous integration pipeline. Each image in the dataset is the output of a random forest machine-learning algorithm, trained on random samples of historic small and large wildfires and represents the predicted conditional probability of an individual pixel burning in a large fire, given an ignition or fire spread to that pixel. This novel workflow is able to integrate the near-term dynamics of fuels and weather into weekly predictions while also integrating longer-term dynamics of fuels, the climate, and the landscape. As a continually updated product, the dataset can provide operational fire managers with contemporary, on-the-ground information to closely monitor the changing potential for large wildfire occurrence and spread. It can also serve as a foundational dataset for longer-term planning and research, such as the strategic targeting of fuels management, fire-smart development at the wildland–urban interface, and the analysis of trends in wildfire potential over time. Weekly large fire probability GeoTiff products from 2005 to 2017 are archived on the Figshare online digital repository with the DOI https://doi.org/10.6084/m9.figshare. 5765967 (available at https://doi.org/10.6084/m9.figshare.5765967.v1). Weekly GeoTiff products and the entire dataset from 2005 onwards are also continually uploaded to a Google Cloud Storage bucket at https://console.cloud. google.com/storage/wffr-preds/V1 (last access: 14 September 2018) and are available free of charge with a Google account. Continually updated products and the long-term archive are also available to registered Google Earth Engine (GEE) users as public GEE assets and can be accessed with the image collection ID users/mgray/wffr-preds within GEE.
Toda and Yamamoto Causality Tests Between Per Capita Saving and Per Capita GDP for India

This paper looks at the relationship between per capita saving and per capita GDP for India using the Toda and Yamamoto tests of Granger causality. Data are for 1950-2004. We distinguish between three types of saving. These are household saving, corporate saving and public saving. The results show that there is no causality between per capita GDP and per capita household saving/per capita corporate saving in either direction. However, there is bi-directional causality between per capita household saving and per capita corporate saving.
The Effect of FDI on Economic Growth in Oil Exporting Countries

This paper investigates the causal relationship between Foreign Direct Investment (FDI) and non-oil GDP in a panel of 11 selected oil exporting countries by using panel unit root tests and panel cointegration analysis for the period 19702010. A three-variable model is formulated with oil exports as the third variable. The results show a strong causality from oil revenues and economic growth to FDI in the oil exporting countries. Yet, FDI does not have any significant effects on non-oil GDP in short- and long-run. It means that it is the oil and non-oil GDP that drives FDI in mentioned countries, not vice versa. However, in these countries the bulk of FDI is focused on and targeted largely at extractive industries, particularly the oil sector. According to the results, decision makings should be employed to exploit FDI more efficiently toward higher productivity and economic base diversification in the future
Product Aspect Ranking Techniques: ASurvey

A product may have hundred of aspects. Some of the product aspects are more important than the others and have strong influence on the eventual consumer’s decision making as well as firm’s product development strategies. Identification of important product aspects become necessary as both consumers and firms are benefited by this. Consumers can easily make purchasing decision by paying attention to the important aspects as well as firms can focus on improving the quality of these aspects and thus enhance product reputation efficiently. This paper provides the description of various techniques for product aspect identification and classification.
Mapping the electron correlation in two-electron photoemission

Electronic correlations are manifested in many-body effects like superconductivity and magnetism. Established theoretical concepts show that the Coulomb and exchange interaction result in a tendency of two electrons to avoid each other, leading to an exchange-correlation xc hole. We will report on double photoemission DPE experiments using a time-of-flight setup consisting of a small central collector surrounded by a resistive anode. The first allows detection only within a narrow solid angle, therefore fixing the momentum. The resistive anode covers a solid angle of 1 sr, the determination of the impact position results in momentum resolution. As a pulsed light source we used synchrotron radiation and we studied a NaCl 100 surface upon excitation with 34 eV photons. The very existence of coincidences is already a manifestation of the correlation. The onset of pair emission occurs when energy conservation allows the ejection of two electrons from the highest occupied level. We have made two key observations. If E1 and E2 are fixed such that a pair emission from the top of the valence band is possible, a zone of reduced intensity with a diameter of 1.1 A−1 is visible. Recent calculations on DPE from a Cu 100 surface display exactly such a feature due to the xc hole. Hence we prove experimentally the very existence of the xc hole in double photoemission. The zone of reduced intensity disappears whenever emission below the top of the valence band becomes possible, indicating the sensitivity of the xc hole to inelastic scattering.
Molecular epidemiology of rabies virus isolated of herbivores from Brazilian Amazon

Amostras do virus da raiva (n = 17) isoladas de bovinos (n = 11), equinos (n = 4) e bubalinos (n = 2) procedentes do Para (n = 7), Tocantins (n = 6) e Rondonia (n = 4) foram submetidas a tecnica de RT-PCR para amplificacao parcial dos genes da Nucleoproteina (N) e Glicoproteina (G). As sequencias nucleotidicas obtidas foram analisadas pelo metodo de reconstrucao filogenetica Neighbor-Joining com o modelo evolutivo Kimura 2-parâmetros. Todas as 17 amostras pertenceram ao cluster A, que se encontrou na linhagem associado com morcego hematofago Desmodus rotundus. A analise filogenetica baseada nos genes N e G, sugere a presenca de cinco sublinhagens (A1-A5) e sete sublinhagens (A1-A7), respectivamente. Quando se compara ambas as filogenias, as sublinhagens A1 ate A3 mostram composicao e distribuicao geografica concordante, ja a diversidade observada na composicao das sublinhagens restantes e atribuida ao uso de sequencias de diferentes alinhamentos. A glicoproteina mostrou marcadores moleculares nas sublinhagens A2, A3, A4 e A7, o que fornece elementos para melhor compreensao da epidemiologia molecular da raiva das linhagens circulantes na Amazonia Brasileira.
PROTEIN FRACTIONATION AND UTILIZATION OF SOYBEAN AND REDBEAN AT DIFFERENT DRYING TEMPERATURES

The objective of this study was to investigate the effect of drying temperatures on chemical composition, rumen fermentation, and digestibility of soybean and redbean (in vitro). Soybean and redbean were dried in an oven set at four different drying temperatures: 50, 60, 70, and 80oC for 24 h in three replicates. The dried samples were then grilled and used further for chemical composition determination (proximate analysis, Van Soest analysis, and protein fraction) and in vitro rumen fermentation assay. Parameters measured in the in vitro assay were gas production, digestibility, pH, ammonia, and volatile fatty acids (VFA). Data obtained were analyzed by using analysis of variance and a posthoc test namely Duncan’s multiple range test. Results showed that neutral detergent insoluble crude protein (NDICP) content was increased at higher drying temperature (70 or 80oC) for both soybean and redbean (P<0.05). Similar to NDICP, higher temperature led to a greater acid detergent insoluble crude protein (ADICP) of soybean as well as those of redbean (P<0.05). Higher temperature decreased gas production rate (GPR) of both beans (P<0.05). Drying of soybean at 70 or 80oC decreased crude protein digestibility (CPD) of soybean more than those of dried at 50 or 60oC (P<0.05). Higher drying temperature resulted in a lower NH3 concentration of both beans (P<0.05). In conclusion, drying temperature at 50 or 60oC was considered to be safe to maintain the nutritional quality of soybean and redbean. (
A rticle European model for inhabited areas – ERMIN 2

The European Model for Inhabited Areas (ERMIN) evaluates strategies for the remediation of inhabited areas contaminated by air-borne radioactive material. The enhancements in the new version, ERMIN 2, were motivated by the new ICRP recommendations for a system of radiological protection, and by user feedback. The underlying model has not changed but the interface has been enhanced to allow the user to easily compare recovery strategies and to select appropriate countermeasure options within the context of ICRP recommendations on the residual dose.
THE ADDED VALUE OF SUSTAINABILITY MOTIVATIONS IN UNDERSTANDING SUSTAINABLE FOOD CHOICES

Understanding consumer food choices is crucial to stimulate sustainable food consumption. Food choice motives are shown to be relevant in understanding consumer food choices. However, there is a focus on product motives, such as price and taste, whereas process motives (i.e. environmental welfare) are understudied. The current study aims to add to the existing literature by investigating the added value of sustainable process motives (environmental welfare, animal welfare and social justice) above product motives. Two on-line surveys of representative Dutch samples tested whether process motives increase the explained variance of sustainable consumption. The results indicate that sustainable process motives are of added value above product motives in the understanding of consumer food choices. In addition, product categories differ in the sustainable process motives that are most useful in explaining sustainable purchases in that category (Study 1), and different types of sustainable products (organic versus fair trade) differ in the sustainable process motives that are most useful in explaining these purchases (Study 2). In conclusion, this paper shows that understanding of sustainable consumption can be improved by considering sustainable process motives above product motives. Thereby, it is important to take the sustainability dimension (e.g., social justice versus environmental welfare) and the product category (e.g., meat versus fruit) into account.