Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying energy use efficiency via entropy production: a case study from longleaf pine ecosystems

Abstract. Ecosystems are open systems that exchange matter and energy with their environment. They differ in their efficiency in doing so as a result of their location on Earth, structure and disturbance, including anthropogenic legacy. Entropy has been proposed to be an effective metric to describe these differences as it relates energy use efficiencies of ecosystems to their thermodynamic environment (i.e., temperature) but has rarely been studied to understand how ecosystems with different disturbance legacies respond when confronted with environmental variability. We studied three sites in a longleaf pine ecosystem with varying levels of anthropogenic legacy and plant functional diversity, all of which were exposed to extreme drought. We quantified radiative (effrad), metabolic and overall entropy changes – as well as changes in exported to imported entropy (effflux) in response to drought disturbance and environmental variability using 24 total years of eddy covariance data (8 years per site). We show that structural and functional characteristics contribute to differences in energy use efficiencies at the three study sites. Our results demonstrate that ecosystem function during drought is modulated by decreased absorbed solar energy and variation in the partitioning of energy and entropy exports owing to differences in site enhanced vegetation index and/or soil water content. Low effrad and metabolic entropy as well as slow adjustment of effflux at the anthropogenically altered site prolonged its recovery from drought by approximately 1 year. In contrast, stands with greater plant functional diversity (i.e., the ones that included both C3 and C4 species) adjusted their entropy exports when faced with drought, which accelerated their recovery. Our study provides a path forward for using entropy to determine ecosystem function across different global ecosystems.
The Application of Rukyah and Hisab in Determining the Starting Dates of the Months of Ramadhan and Syawal in Thailand

Thailand is a predominantly Buddhist country, with a small Muslim minority, concentrated primarily in its' southern region, near the Malaysian border. Both countries are said to use the same “Rukyah and Hisab” method to determine the starting dates of Ramadhan and Syawal. Therefore, the months of Ramadhan and Syawal should start on the same days in both countries, which both are used the same method and same time zone. In recent years, however, differences in the starting dates of Ramadhan and Syawal have been observed between the two countries. The following questions arise as the result of this discrepancy: 1) What are the methods currently used by Thailand? and 2) What is the application of rukyah and hisab in determining the starting dates of the months of Ramadhan and syawal in Thailand? The objective of this research is to answer these questions, by identifying and analyzing the method currently being used in Thailand to determine the start of Ramadhan and Syawal. Documented research, semi-structured interviews, and non-participatory observation are used to collect the data, which then undergo qualitative content analysis. The method used to determine the start of Ramadhan and Syawal in Thailand is based on the “rukyah hakiki” method.
Restoration Manual for Annual Grassland Systems in California

Author(s): Gornish, Elise S; Shaw, Julea | Abstract: Widespread development and massive degradation are quickly eroding the persistence and health of annual grassland systems. This guide was developed to give practitioners of any experience level an overview of considerations for grassland restoration design and application that will be right for their situation. Here you’ll find ways to effectively improve grassland conditions in monetarily and logistically feasible ways. This publication focuses on restoration species choice, because species identity can be the dominant driver of achieving a restoration goal—included is an extensive appendix matching geographic area and soil type to appropriate species for consideration. The techniques presented are the result of years of experience from research scientists and non-academic practitioners and synthesizes published and unpublished data in one handy source. Sections include: Identifying Restoration Goals and Desired Outcomes: Biodiversity Pollinator Habitat Wildlife Habitat Erosion Control Forage for Grazing Animals Carbon Storage/Nutrient Cycling Pre-Vegetation Techniques Plant Materials Revegetation Techniques Discussion of 83 species with brief description of pros and cons Extensive references
A Prediction Model based on Data Mining to Forecast the Expectations of Passing from a College Student

- The present work has as objective to apply data mining techniques to develop a predictive model to forecast the chance of passing that will have a college student at the time of enrolling in a particular subject. Given that the academic record of the student can be known, and based on that information, we propose an Artificial Neural Network (ANN) that allows, using various configurations, to predict and assess our goal. The model has been applied to a compulsory subject of higher education of a University and given the results obtained. This model can be applied to any other subject analogous with satisfactory results.
Query Based Topic Modeling: An Information-Theoretic Framework for Semantic Analysis in Large-Scale Collections

Creating topic models of text collections is an important step towards more adaptive information access and retrieval applications. Such models encode knowledge of the topics discussed on a collection, the documents that belong to each topic and the semantic similarity of a given pair of topics. So far, the dominant paradigm to topic modeling has been the Probabilistic Topic Modeling approach in which topics are represented as probability distributions of terms. Although such models are theoretically sound, their high computational complexity makes them difficult to use in very large-scale collections. In this work the authors propose an alternative collection-modeling paradigm based on a simpler representation of topics as freely overlapping clusters of semantically similar documents, thus being able to take advantage of highly-scalable clustering algorithms. Then, the authors propose the Query-based Topic Modeling framework (QTM), an information-theoretic method that assumes the existence of a “golden” set of queries that can capture most of the semantic information of the collection and produce models with maximum semantic coherence. The QTM method uses information-theoretic heuristics to find a set of “topical-queries” which are then co-clustered along with the documents of the collection and transformed to produce overlapping document clusters. The QTM framework was designed with scalability in mind and is able to be executed in parallel over commodity-class machines using the Map-Reduce approach.
Detection Probability Modeling of Sensor Network Based on Information Sharing

To study the promotion effect of networked sensor cooperative detection on detection probability,a model of detection probability was built up based on information sharing.Firstly,the formula for calculating the detection probability of single sensor in independent detection was presented.Then,the algorithm for calculating the single sensor detection probability based on information sharing was given,and the sensor network detection probability was calculated out by using K/N judgment model.Finally,the influence of several parameters on the detection probability under information sharing was analyzed through simulation,and some significative conclusions were gained.
Knowledge-based Algorithm for Multi-Agent Communication

Using a knowledge-based approach, we derive a protocol for the sequence transmission problem from one agent to a group of agents. The knowledge-based protocol is correct for communication media where deletion and reordering errors may occur. Furthermore, it is shown that after k rounds the agents in the group attain depth k general knowledge about the members of the group and the values of the messages. Thus, the knowledge-based protocol may be used in cooperative problem solving in order to attain an approximation of common belief among agents in a team.
Skeletal Remains of Phoebodus politus Newberry, 1889 (Chondrichthyes: Elasmobranchii) from a Famennian Konservatlagerstätte in the Eastern Anti-Atlas (Morocco) and its Ecology

The Devonian chondrichthyan Phoebodus (Newberry 1889) has long been known from isolated teeth recovered from a wide variety of fossil localities, ranging from the Middle Devonian to the Upper Missippian (Ginter et al. 2010). Here we provide a preliminary report of the first discovery of substantial, partly articulated skeletal and dental remains of a phoebodont, Phoebodus politus, from Famennian outrops of the eastern Anti-Atlas of Morocco. Initial comparisons support the hypothesized close relationship of pheobodonts with the Upper Mississippian chondrichthyan Thrinacodus gracia (Grogan & Lund 2008, Ginter et al. 2010). Both taxa exhibit an anguiliform body and elongate slender cranium. However, P. politus also exhibits dorsal fins with ctenacanth-like fin spines, echoing informal records of similar fin spine and tooth associations from the Famennian of Alaska (Maisey, in Ginter et al. 2010). This Moroccan material represents an important addition to the limited data set of Devonian chondrichthyans. As such, these data will provide a valuable test of recent phylogenetic hypotheses (Pradel et al. 2011; Coates et al. 2017) and addition to analyses of early gathostome diversity and disparity before and after the end Devonian Hangenberg Event (Friedman & Sallan 2012). Among living elasmobranchs, Chlamydoselachus uniquely displays a body shape, snout form and tooth morphology resembling those of P. politus. Acknowledging that the structure and likely biomechanics of the axial skeletons and jaws of these widey separated genera differ considerably, we nevertheless suggest that Chlamydoselachus (Ebert & Compagno 2009) provides the best available living model for understanding the ecomorphology of this remarkable, late Devonian comparator.
Recent Advances In Example Based Machine Translation

Thank you very much for downloading recent advances in example based machine translation. Maybe you have knowledge that, people have look numerous times for their chosen novels like this recent advances in example based machine translation, but end up in infectious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some infectious virus inside their computer.
Approach to an integral valuation of mangrove’s ecosystem services in a marine protected area. Colombian Pacific region

ABSTRACT Colombian Pacific region is a global biodiversity hotspot. Mangroves are among the most dynamic and productive ecosystem on earth and serve many important functions providing a range of fundamental goods and services which contribute to the livelihoods, well – being, and local community’s security. Integral mangroves valuation seeks to understand the socio-ecological interaction and the relationship between functional ecosystems (ecosystem services – ES), market interaction and the ability to support human well – being. Despite the importance, mangroves are continuing to be threatened and degraded because of socio-environmental conflicts such as land use change and port infrastructure which will impact on ecosystem services quality and offer. This article identifies an approach to the potential ecological, sociocultural and economic impact of a Deepwater port on the Tribugá Gulf mangroves ecosystem services offer and its effects on the well – being of Nuquí communities.
Validating measurement-based composite load model

Since the digital simulation is one of the basic tools in understanding the modern complex power systems, its veracity has direct effects on the decision making on the power system operation and control. However, the accuracy of the digital simulation is dependant heavily on the model validity. Among all the dynamic components of the power system, the load is one of the most difficult one to be modeled. The difficulty lies in the fact that the scenario when the load model is built is always different from the real situation raised by the faults. So the question naturally arises that whether the measurement-based load model could be applied in the digital simulation when analyzing different operation scenarios. And to what extent does the model keep valid? It is hard to answer these questions because the field data, which constitute the basis of the measurement-based load modeling, are limited. This paper reports our work on validating the load model via RTDS. By simulating various fault situations on a model of a real provincial power system in RTDS, we could get a great amount of data to build the model as well as research its validity. Two greatly concerned problems related to the measurement-based load model are addressed in this paper; one is the possibility of applying the load model for various fault scenarios and the other is the validity of the load model when the load composition changes. Suggestions for the measurement-based load modeling practice are also given from the model validation work. (6 pages)
Optimal Coverage Algorithm of Sensor Nodes Set Selection in Wireless Sensor Network

With respect to the high-density deployment of wireless sensor networks,a NPcomplete problem is to be solved,i.e.,how to find out the minimal number of nodes with the target region fully covered simultaneously.A new optimal algorithm for selecting the set of nodes is thus designed on the basis of genetic algorithm.With the full network coverage provided and part of redundant nodes entering into dormancy,an optimal coverage set of nodes is formed.A simulation test was done to evaluate the performance of the algorithm for network coverage,and the result showed that it can achieve an optimal selection of the set of nodes in hundreds at low cost,thus prolonging efficiently the network lifetime.
M-Commerce in Bangladesh –Status, Potential and Constraints

Mobile Commerce often referred to as “MCommerce” or “mCommerce” is a new dimension or extension of e-Commerce that is performed by mobile devices and Personal Digital Assistants (PDA) using mobile phone networks. As the number of mobile users is increasing dramatically the prospect of m-commerce is also increasing day by day in developing countries like Bangladesh. Though there are a lot of researchers has written about the prospect and adoption of M-commerce but in my research, I tried to find out the statistical analysis of mobile users, mobile internet users; Mcommerce current status in Bangladesh. Research also has been done for a number of visitors of stakeholder’s site, using the ranking tools, uses of mobile apps by customers and limitation of mobile commerce adoption in Bangladesh those were not discussed earlier. Here, I collected data through web and phone call from various stakeholders, in the top line m-commerce business, studied and identified the problem, shown the current status and major barriers of M-commerce and suggested a methodological framework.
Simulação do Regime Hidrológico da Cabeceira do Rio São Francisco a Partir da Utilização dos Modelos SMAP e RegCM

Estudos realizados nas ultimas decadas demonstram que os diferentes processos ambientais que ocorrem no planeta sao, geralmente, de natureza bastante complexa, o que reforca a necessidade de desenvolvimento e aprimoramento de tecnologias de modelagem numerica de sistemas ambientais. Tendo em vista as possiveis alteracoes causadas pelas mudancas climaticas e ciente da importância da bacia do Rio Sao Francisco na geracao hidreletrica nacional, o presente estudo utilizou o modelo hidrologico de chuva-vazao SMAP (Soil Moisture Accounting Procedure) para comparar as vazoes Medias de Longo Termo (MLT) observadas da cabeceira da bacia, a montante da usina hidreletrica de Tres Marias, com as simuladas pelo modelo de circulacao geral da Atmosfera MIROC, regionalizadas pelo modelo climatico regional RegCM, ambos utilizados pelo Painel Intergovernamental sobre Mudancas Climaticas, IPCC. Para a avaliacao destas simulacoes foi comparado o comportamento da vazao simulada na bacia, tendo como dado de entrada a precipitacao prevista pelo modelo climatico e tambem a precipitacao observada no periodo de 2001 a 2009. Para calibracao do modelo SMAP foram utilizados dados de precipitacao observada no periodo de junho de 1991 a maio de 2001. Posteriormente, foi analisado o comportamento do modelo hidrologico utilizando dados de precipitacao simulados pelo modelo climatico RegCM, com e sem aplicacao de tecnicas estatisticas de remocao de vies. A modelagem utilizando a chuva real observada na bacia apresentou uma boa aderencia com a vazao real observada no periodo, demonstrando que o modelo SMAP e capaz de reproduzir a MLT da bacia. No entanto, a modelagem utilizando a precipitacao simulada pelo RegCM apresentou indices baixos de eiciencia, sendo necessaria uma analise para remocao de vies da precipitacao do modelo. Apos isso, as simulacoes apresentaram melhora significativa nos indices estatisticos de desempenho, que ainda foram inferiores aos indices da precipitacao real. Com isso, o estudo verificou que os modelos climaticos apresentam potencial para serem utilizados neste tipo de analise, mas necessitam de uma verificacao minuciosa de suas simulacoes em situacoes climaticas passadas conhecidas, para que sejam identificados possiveis erros sistematicos e seus prognosticos possam ser utilizados de forma correta pela sociedade, principalmente em processos mitigadores dos efeitos das mudancas climaticas.
Midlevel Cloud‐Base Turbulence: Radar Observations and Models

Midlevel Cloud‐base Turbulence (MCT) caused by ice/snow precipitation from midlevel clouds falling into dry air below the cloud base and sublimating is investigated. MCT phenomena in the lower troposphere as revealed by the Middle and Upper atmosphere (MU) radar in Shigaraki, Japan, during the Shigaraki unmanned aerial vehicle and radar Experiment campaigns in the spring‐summer of 2015 and 2016 are described. The MU radar was operated in a high‐resolution (~20‐m) range imaging mode and hence revealed the structure of these MCTs in great detail. These MCT layers grew to hundreds of meters in thickness, often reaching nearly 2,000 m in depth, lasting often for as much as 24 hr. A simple analytical model and a second‐moment closure‐based turbulent mixing model are used to estimate the levels of turbulence kinetic energy and its dissipation rate in the MCT layer and compare them to those measured by the MU radar. The study shows that MCT can give rise to moderate levels of turbulence of potential interest to aviation, confirming conclusions reached by earlier pioneering studies. However, to our knowledge, this important process has not received the attention it deserves by the atmospheric community so far, and therefore, it is the principal goal of this paper to not only present some observations and preliminary modeling results, but also redraw the attention of atmospheric scientists to this important process.
Retrieving Volcanic Ash Information Using COMS Satellite (MI) and Landsat-8 (OLI, TIRS) Satellite Imagery: A Case Study of Sakurajima Volcano

화산재는 화산쇄설물 중 2 mm 이하의 크기를 가지는 작은 미세 암편으로 화산 분화 이후 낙하에 의해 여러 가지 피해를 가져온다. 화산재 피해는 운송업과 생산업 그리고 동 식물 및 인간의 호흡기 활동에 영향을 줄 수 있다. 따라서 이러한 화산재의 피해를 예방하기 위해서는 화산재 확산 정보가 중요하며 광범위하게 확.
Energy Awareness and Scheduling in Mobile Devices and High End Computing.

Energy Awareness and Scheduling in Mobile Devices and High End Computing Sachin S. Pawaskar, Ph.D. University of Nebraska, 2013 Advisor: Dr. Hesham Ali In the context of the big picture as energy demands rise due to growing economies and growing populations, there will be greater emphasis on sustainable supply, conservation, and efficient usage of this vital resource. Even at a smaller level, the need for minimizing energy consumption continues to be compelling in embedded, mobile, and server systems such as handheld devices, robots, spaceships, laptops, cluster servers, sensors, etc. This is due to the direct impact of constrained energy sources such as battery size and weight, as well as cooling expenses in cluster-based systems to reduce heat dissipation. Energy management therefore plays a paramount role in not only hardware design but also in user-application, middleware and operating system design. At a higher level Datacenters are sprouting everywhere due to the exponential growth of Big Data in every aspect of human life, the buzz word these days is Cloud computing. This dissertation, focuses on techniques, specifically algorithmic ones to scale down energy needs whenever the system performance can be relaxed. We examine the significance and relevance of this research and develop a methodology to study this phenomenon. Specifically, the research will study energy-aware resource reservations algorithms to satisfy both performance needs and energy constraints. Many energy management schemes focus on a single resource that is dedicated to real-time or nonreal-time processing. Unfortunately, in many practical systems the combination of hard and soft real-time periodic tasks, a-periodic real-time tasks, interactive tasks and batch tasks must be supported. Each task may also require access to multiple resources. Therefore, this research will tackle the NP-hard problem of providing timely and simultaneous access to multiple resources by the use of practical abstractions and nearoptimal heuristics aided by cooperative scheduling. We provide an elegant EAS model which works across the spectrum which uses a run-profile based approach to scheduling. We apply this model to significant applications such as BLAT and Assembly of gene sequences in the Bioinformatics domain. We also provide a simulation for extending this model to cloud computing to answers “what if” scenario questions for consumers and operators of cloud resources to help answers questions of deadlines, single v/s distributed cluster use and impact analysis of energy-index and availability against revenue and ROI.
Creativity and Artificial Intelligence

With CD-ROM. Creativity and Artificial Intelligence: A Conceptual Blending Approach takes readers into a computationally plausible model of creativity. Inspired by a thorough analysis of work on creativity from the areas of philosophy, psychology, cognitive science, cognitive linguistics and artificial intelligence, the author deals with the various processes, principles and representations that lie underneath the act of creativity. Focusing on Arthur Koestler's Bisociations, which eventually lead to Turner and Fauconnier's conceptual blending framework, the book proposes a theoretical model that considers blends and their emergent structure as a fundamental cognitive mechanism. The author thus discusses the computational implementation of several aspects of conceptual blending theory, namely composition, completion, elaboration, frames and optimality constraints. Informal descriptions and examples are supplied to provide non-computer scientists as well as non-cognitive linguists with clear insights into these ideas. Several experiments are made, and their results are discussed, with particular emphasis on the validation of the creativity and conceptual blending aspects. Written by a researcher with a background in artificial intelligence, the book is the result of several years of exploration and discussion from different theoretical perspectives. As a result, the book echoes some of the criticism made on conceptual blending and creativity in artificial intelligence, and thus proposes improvements in both areas, with the aim of being a constructive contribution to these very intriguing, yet appealing, research orientations.