Miracle-dz/UniFAR-FTUs huggingface dataset:
Snowpack Contributions and Temperature Characterization of Landfalling Atmospheric Rivers in the Western Cordillera of the United States

Atmospheric rivers (ARs) are regions of high water vapor transport in the lower atmosphere. When these air masses encounter mountain ranges, they can produce significantly enhanced orographic precipitation. AR events may substantially influence seasonal mountain snow, an important ecologic and economic resource for Washington, Oregon, and California. To better understand how ARs affect the montane snowpack of these U.S. West Coast states, we used 33 years of Snow Telemetry and Topography Weather data to examine AR and non‐AR storm day temperatures and impacts on snow water equivalent (SWE). We found mean daily minimum temperatures of AR storm days to be 1 to 4 °C warmer and mean daily increases in SWE to be 23% to 57% higher than non‐AR storm days. AR storm days have contributed an average of 23% of effective snowfall to seasonal SWE in the California Sierra Nevada and 34% of effective snowfall to seasonal SWE in the Washington and Oregon Cascades.
Integrating fire-scar, charcoal and fungal spore data to study fire events in the boreal forest of northern Europe

Fire is a major disturbance agent in the boreal forest, influencing many current and future ecosystem conditions and services. Surprisingly few studies have attempted to improve the accuracy of fire-event reconstructions even though the estimates of the occurrence of past fires may be biased, influencing the reliability of the models employing those data (e.g. C stock, cycle). This study aimed to demonstrate how three types of fire proxies – fire scars from tree rings, sedimentary charcoal and, for the first time in this context, fungal spores of Neurospora – can be integrated to achieve a better understanding of past fire dynamics. By studying charcoal and Neurospora from sediment cores from forest hollows, and the fire scars from tree rings in their surroundings in the southern Fennoscandian and western Russian boreal forest, we produced composite fire-event data sets and fire-event frequencies, and estimated fire return intervals. Our estimates show that the fire return interval varied between 126 and 237 years during the last 11,000 years. The highest fire frequency during the 18th–19th century can be associated with the anthropogenic influence. Importantly, statistical tests revealed a positive relationship between other fire event indicators and Neurospora occurrence allowing us to pinpoint past fire events at times when the sedimentary charcoal was absent, but Neurospora were abundant. We demonstrated how fire proxies with different temporal resolution can be linked, providing potential improvements in the reliability of fire history reconstructions from multiple proxies.
A pragmatic approach to computational narrative understanding

Narrative understanding is a hard problem for artificial intelligence that requires deep semantic understanding of natural language and broad world knowledge. Early research in this area stalled due to the difficulty of knowledge engineering and a trend in the field towards robustness at the expense of depth. This work explores how a practical integration of more recent resources and theories for natural language understanding can perform deep semantic interpretation of narratives when guided by specific pragmatic constraints. It shows how cognitive models can provide pragmatic context for narrative understanding in terms of well-defined reasoning tasks, and how those tasks can be used to guide interpretation and evaluate understanding. This work presents an implemented system, EA NLU, which has been used to interpret narrative text input to cognitive modeling simulations. EA NLU integrates existing large-scale knowledge resources with a controlled grammar and a compositional semantic interpretation process to generate highly expressive logical representations of sentences. Delayed disambiguation and representations from dynamic logic are used to separate this compositional process from a querydriven discourse interpretation process that is guided by pragmatic concerns and uses world knowledge. By isolating explicit points of ambiguity and using limited evidential abduction, this query-driven process can automatically identify the disambiguation choices that entail relevant interpretations. This work shows how this approach maintains computational tractability without sacrificing expressive power. EA NLU is evaluated through a series of experiments with two cognitive models, showing that it is capable of meeting the deep reasoning requirements those models pose, and that the constraints provided by the models can effectively guide the interpretation process. By enforcing consistent interpretation principles, EA NLU benefits the cognitive modeling experiments by reducing the opportunities for tailoring the input. This work also explores the use of a theory of narrative functions as a heuristic guide to interpretation in EA NLU. In contrast to potentially global task-specific queries, these narrative functions can be inferred on a sentence-by-sentence basis, providing incremental disambiguation. This method is evaluated by interpreting a set of Aesop's fables, and showing that the interpretations are sufficient to capture the intended lesson of each fable.
Methodology and Findings for the Exposure Analysis of the Chinese Wastewater Sector to Flooding and Earthquakes Hazards

This paper describes the methodology and findings for the extreme hazard exposure analysis of the Chinese wastewater sector to flooding and earthquakes hazards. This analysis is undertaken for changing flooding, under climate scenarios, and earthquake exposure of a spatially accurate wastewater treatment plants (WWTP) database for China, covering a total of 1,346 assets with additional attributes quantifying the treatment capacity and users dependent on each plant. For flooding, we apply and downscale a global river routing (CaMa-Flood) model that quantifies the change degree of flood exposures from the present time-period (1980-2005) to the near future time-period (2016-2035) to a far future time period (2036-2055). We find evidence that most climate models project increasing number of WWTP assets face climate-induced flood hazards in both the near and far future, potentially affecting as many as 208 million users by 2050. However, there are spatial and temporal variations from these projections which means that planning for resilient wastewater infrastructure requires more detailed understanding of the vulnerability attributes of WWTPs including their exact location, the number of users they serve as well as their flood protection standards. For earthquakes, we examine the exposure of WWTPs to earthquake hazards through both seismic shaking and induced liquefaction. Overall, we demonstrate the significant risk that earthquakes can have on the WWTP process -- especially on centralized systems. By considering liquefaction susceptibility in combination with shaking, we expose a number of WWTPs that face an increased level of exposure to damages following earthquakes compared to looking at shaking in isolation.
Electrical Properties of Skin and SAR Calculation in a Realistic Human Model for Microwave Exposure

Electrical Properties of Skin and SAR Calculation in a Realistic Human Model for Microwave Exposure Osamu Fujiwara, Member and Kiyofumi Takai, Non-member (Nagoya Institute of Technology) The skin tissue of a human head can play an electromagnetic shielding role in protecting the central organs from microwave exposure. For the electrical properties, however, the publication data are being widely scattered from fat (low water content) to muscle (high water content), and thus various electrical properties of the skin tissue are used for SAR calculations in a heterogeous head model. This paper examines numerically how variations in electrical properties of the skin tissue have an effect on the SAR in a human head. Skin tissue properties are newly estimated from a Debye equation with two relaxation time constants, which are used to calculate the SAR in an our developed heterogeous head model for 1.5-Glfz microwave exposure. The SAR details are compared with the following cases : the results computed for the skin tissue having the same electrical properties as those of fat, our previously obtained results and the results computed for the Furse's tissue properties. The effects of tissue mass densities on the SAR calculation are also examined.
Exterior Orientation Revisited: A Robust Method Based on Iq-norm

Camera exterior orientation is essential in many photogramme-try and computer vision applications, including 3D reconstruction, digital orthophoto map ( DOM ) generation, and localization. In this paper, we propose a new formulation of exterior orientation that is robust against gross errors (outliers). Different from classic optimization methods whose cost function is based on the l 2 -norm of residuals, we use l q -norm ( 0< q <1 ) instead. We reformulate the new cost function as an augmented Lagrangian function because it is not strictly convex. In addition, we employ the alternating direction method of multipliers ( ADMM ) to decompose the augmented Lagrangian function into three simple sub-problems and solve them iteratively. Our work recovers the orientation and position of a camera from outliers contaminating observations without any gross error detection stage such as random sample consensus ( RANSAC ). Extensive experiments on both synthetic and real data demonstrate that the proposed method significantly outperforms state-of-the-art methods and can easily handle situations with up to 85 percent outliers. The source code of the proposed algorithm is made public.
Detection of rainstorm pattern in arid regions using MODIS NDVI time series analysis

Abstract The normalized difference vegetation index (NDVI) was used to delineate potential water suppliers west of the Arabian Peninsula. Time series NDVI data extracted from the moderate resolution imaging spectroradiometer NDVI product were used to develop a robust estimate of rainstorm frequency and intensity. A total of 216 NDVI images were acquired between February 2000 and January 2018 to carry out this investigation. As NDVI values of negative records correspond to water, it was possible to address and delineate the occurrence and duration of temporal ponded water. Results showed that at least 7 locations are potential to harvest water from flashfloods. Some locations witnessed 10, 11 and 13 rainstorms and ponding of water ranged from 1 to 20 months. These locations, if properly managed, could sustain a fresh water resource for local uses. The study demonstrates that NDVI time series curves could help identify the time/duration of previous rainstorms.
Novel algorithm for filling incomplete data of internet of things based on attribute reduction

Traditional data filling algorithms take the unified method to fill the incomplete data,leading to the low efficiency for filling large incomplete data of the Internet of Things.A novel algorithm for filling incomplete data based on attribute reduction is proposed.At first,the presented algorithm uses the attribute reduction to distinguish the important attribute from unimportant attribute,and then fills the two kinds of data attributes using different filling technologies,which the number of important attributes is decided by the needs of the user.Experiments show that this algorithm can effectively and quickly fill the large-scale incomplete data of the Internet of Things.
Nonstationary Relationship Between Autumn Arctic Sea Ice and the Winter North Atlantic Oscillation

The North Atlantic Oscillation (NAO) has a dominating influence on wintertime weather in the North Atlantic region, and therefore, it is of great interest to predict the NAO several months ahead. While state‐of‐the‐art dynamical forecast models appear to be increasingly skillful in predicting the NAO, statistical methods with comparable or higher predictive skill are still often used. An inherent problem with statistical methods is that any empirical relationship between predictors and the NAO may be valid for some periods but subject to change over time. Here we use a set of new centennial reanalyses and large‐ensemble simulations with multiple climate models to discover clear evidence of nonstationarity in the lagged correlation between autumn Barents‐Kara sea ice and the winter NAO. This nonstationarity leads us to question the causality and/or robustness of the ice‐NAO link. We caution against indiscriminately using Barents‐Kara sea ice to predict the NAO.
Application of Diatom-Based Indices in River Quality Assessment: A Case Study of Lower Ogun River (Abeokuta, Southwestern Nigeria) Using Epilithic Diatoms

Diatom indices have been extensively applied in the bioassessment of surface waters and wetlands in many countries except Nigeria. This pioneer study aimed at investigating the use of epilithic diatom-based indices in the assessment of the Ogun River quality. Water and epilithic diatom samples were collected fortnightly from four sampling stations for a period of four consecutive months (March–June 2015). Water samples were analysed for pH, temperature, electrical conductivity, total dissolved solids (TDS), dissolved oxygen, chemical oxygen demand (COD), nitrite, nitrate, ammonium, phosphate, sulphide, chloride, iron, manganese, silicate, total alkalinity, total hardness, total suspended solids (TSS), transparency and total organic carbon using standard methods. Epilithic diatom samples were collected by scraping the surfaces of rocks or stones using an 18 mm toothbrush and analysed following the standard methods. Data collected were subjected to descriptive (frequency, mean) and inferential statistics (diatom indices, Pearson correlation) using OMNIDIA and SPSS statistical packages. Results showed that the water quality of the Lower Ogun River ranged between bad and high qualities during the study period. The diatom indices (trophic diatom index (TDI), biological diatom index (IBD), generic salinity index (GSI1), generic trophic index (GTI), generic saprobity index (GTI)) were correlated with physical and chemical parameters, thereby indicating their effec - tiveness in water quality ranking.
CO2-induced climate forcing on the fire record during the initiation of Cretaceous oceanic anoxic event 2

Cretaceous oceanic anoxic event 2 (OAE2) is thought to have been contemporary with extensive volcanism and the release of large quantities of volcanic CO2 capable of triggering marine anoxia through a series of biogeochemical feedbacks. High-resolution reconstructions of atmospheric CO2 concentrations across the initiation of OAE2 suggest that there were also two distinct pulses of CO2 drawdown coeval with increased organic carbon burial. These fluctuations in CO2 likely led to significant climatic changes, including fluctuations in temperatures and the hydrological cycle. Paleofire proxy records suggest that wildfire was a common occurrence throughout the Cretaceous Period, likely fueled by the estimated high atmospheric O2 concentrations at this time. However, over geological time scales, the likelihood and behavior of fire are also controlled by other factors such as climate, implying that CO2-driven climate changes should also be observable in the fossil charcoal record. We tested this hypothesis and present a high-resolution study of fire history through the use of fossil charcoal abundances across the OAE2 onset, and we compared our records to the estimated CO2 fluctuations published from the same study sites. Our study illustrates that inferred wildfire activity appears to relate to changes in CO2 occurring across the onset of OAE2, where periods of CO2 drawdown may have enabled an increase in fire activity through suppression of the hydrological cycle. Our study provides further insight into the relationships between rapid changes in the carbon cycle, climate, and wildfire activity, illustrating that CO2 and climate changes related to inferred wildfire activity can be detected despite the estimated high Cretaceous atmospheric O2 concentrations.
A Survey of Recommender System

In recent years, recommender system gets unprecedented attention and development. As the core of e-commerce technology, the recommender system helps consumers easily find potential commodity and also promotes the sale of goods for consumers and producers. Recommender system can utilize user behavior information, social network information, tag data, etc. to enhance the quality of the recommender system. With the rapid development of the recommender system, how to evaluate the system and how to improve the interpretability recommendation system has also become a hot research topic. Makes detailed introduction and analysis of recommendation algorithm, evaluation indicators and interpretability of recommender system.
Biodiversity survey method for detecting species of conservation concern in Nova Scotia protected wilderness areas and nature reserves

Biodiversity transect surveys have been undertaken in protected Wilderness Areas and Nature Reserves in Nova Scotia, Canada since 2002. They document plant communities as well as plant and animal species of conservation concern. The Protected Areas Branch wished to have an assessment of the value of these surveys. Fourteen years of sampling data in 80 Wilderness Areas and Nature Reserves were used to determine detectability, density and distribution of species of conservation concern. Two hundred and twenty-two occurrences of species of interest were re- corded. Nine bird species and 19 plant and lichen species were recorded 2 or more times. Densities for bird species ranged from 0.023 individuals per km of transect (± 0.012) for the Boreal Chickadee to 0.727-km (± 0.007) for the Eastern Wood Pewee. Plants densities ranged from 0.02 individuals per km (± 0.01) for the Round-Leaved Orchid to 27.1 individuals per km (± 10.4) for the Bulblet Bladder Fern. Most of the species of conservation concern were rare with 66% being found only once. The method used for the current biodiversity transect surveys appears to be adequate for the more common species of conservation concern when a single protected area is examined. However, less than half the species analyzed had a 95% confidence of being detected within the mean sample length of the transect (4.5 km). All species analyzed were within the sample length when all protected areas were combined suggesting that the present methodology is more useful as a system wide survey rather than for individual protected areas. Twenty-eight of eighty-three species of conservation concern detected during the survey occurred frequently enough for density calculations. Methods that might increase the value of the surveys include grouping species, using species richness measures, using occupancy or accepting lower confidence intervals and confidence limits.Keywords: biodiversity survey, species of conservation concern, species at risk, protected areas
The collaborative creation of video games: A marriage for love?

Play is social. However, the operation of play is often a physically solitary act (Brand et al., 2014: 18). Notwithstanding this fact, the creation of the gaming experience is inherently social. Co-creating Videogames and Battlefields of Negotiation deal with the collective creation of this communal experience. With their entrance into classical museums, video games have come far along their long road toward legitimization as a leisure activity and a cultural object. Envisioned as a cultural object, video games are now being studied as such and, therefore, relationships among the actors of this creation are being analyzed. These books adopt a distinct standpoint about this topic. Reading Co-creating Videogames takes you behind the screen for an industry viewpoint, whereas Battlefields of Negotiation puts you in the shoes of a player of World of Warcraft (Blizzard, 2004). The processes described recall Plato’s idea of human life as a pilgrimage from appearance to reality. Indeed, participants in the creation of the video gaming experience seek to make their ideas come true. By shedding light on this collective committed creative activity, these works commonly argue that sharing playing activity enriches the gaming experience in which players get engaged. The profiles of the two researchers differ in age, experience and field of expertise. As an experienced sociologist, John Banks gives priority to his field, displaying thrilling case studies of a few titles run by Auran, mainly Trainz and Fury. Calling on complementary sources from manifold disciplines to analyze the discourses he collected, Banks’ work goes beyond the scope of sociology and succeeds in bringing new knowledge. René Glas’ doctoral dissertation is entrenched in the game studies tradition and its references. Descriptions displayed throughout the book richly help the reader to get into the core experience of playing the famous game. The data collection ranges from a myriad of sources, but little is said about how the data were analyzed. 574029 NMS0010.1177/1461444815574029new media & societyBook Review Review Essay2015
Modelling Choice of Mobile Technology for M-Banking

Research in the adoption of mobile services has not offered a comprehensive explanation of low demand for the service. This paper proposes a more comprehensive framework to account for the explanations of consumer choice in the context of m-banking. The model underlies th e cognitive processes of reasoning, referencing and contextualizing, as postulated in the behavioral de cision making. The proposed theoretical framework i s based on a review of literature from marketing, behavioral eco nomics and information systems.
Thermal imaging analysis of local climate in relation to air quality in surroundigs of the paper mill industry

The objective of this study was to explore a new method of using thermography to analyze the local climate of industrialized areas by observing the main source of pollution and finding correlations between pictures from a thermographic camera and selected climatic conditions and pollution data. We converted pictures into numerical data expressing the number of pixels in different shades of greyscale. We used these to create a ratio and observed its relation to selected climatic conditions including aerosols, humidity, temperature, carbon dioxide, carbon oxide, sulphur dioxide, benzene, nitrogen dioxide, and surface ozone. The detection of significant correlations suggests that this method is applicable in the area of environmental research.