Miracle-dz/UniFAR-FTUs huggingface dataset:
A framework for relationship extraction from unstructured text via link grammar parsing

A major task in information extraction is to extract relations between named entities. Relation extraction not only builds and extends knowledge bases and ontologies but also supports downstream application processing such as graph mining. In this paper, we report a relation extraction framework based on the natural language theory of link grammar. Our methodology uses and extends Akbik and Broß’s Wanderlust approach, where linguistic paths that are defined over the dependency grammar of sentences guide the relation extraction process. In particular, our framework splits a document into sentences, creates a dependency tree of each sentence, tags and categorizes entities, and extract relations between these entities. The accuracy of our framework is parametrized with the choice of linguistic paths, and accuracy scores as high as 95% precision, 36% recall, and 44% f-score are obtained. We also envision natural extensions of our work, where cross-sentence references are resolved and/or the context and content of the sentence constrains the linguistic paths.
Implementation issues in core competence strategy making

This article focuses on implementation of the core competence approach to strategy making: The results from a sample of 20 managers and consultants with experience applying this approach are presented. Factors critical for successful implementation are discussed: including the critical resource inputs, strategy process factors, major contextual influences, and the outputs produced. Issues causing major problems with implementation of this approach are outlined. Further research is proposed. Copyright © 2000 John Wiley & Sons, Ltd.
Influence of RMB Internationalization on International Crude Oil Price Fluctuation

In recent years, China has been gradually improving its international status. As far as monetary policy is concerned, China has been gradually promoting the internationalization of the RMB, aiming to reduce its dependence on the international financial market dominated by the US dollar and reduce the impact of the Federal Reserve's political measures on the domestic economy. Under the influence of global economic and financial market factors such as COVID-19, the international financial system dominated by the US dollar is unstable and dangerous, and the international financial system has become more volatile. In contrast, the implementation of this measure will have an impact on some international financial transactions, such as stock market price fluctuations, commodity prices and foreign exchange transactions. For a long time, the oil price has been dominated by the US dollar due to the linkage between the US dollar and oil, and has increased with the appreciation of the US dollar. However, the process of people's internationalization affected the oil price by changing this traditional logic and impacted the global status of the US dollar, thus reducing the oil price by triggering the decline of the US dollar. This paper would like to focus on elaborating the influence of RMB internationalization on international crude oil price fluctuation.
Optimal Energy Storage Strategies in Microgrids

Microgrids are small-scale distribution networks that provide a template for large-scale deployment of renewable energy sources, such as wind and solar power, in close proximity to demand. However, the inherent variability and intermittency of these sources can have a significant impact on power generation and scheduling decisions. Distributed energy resources, such as energy storage systems, can be used to decouple the times of energy consumption and generation, thereby enabling microgrid operators to improve scheduling decisions and exploit arbitrage opportunities in energy markets. The integration of renewable energy sources into the nation's power grid, by way of microgrids, holds great promise for sustainable energy production and delivery; however, operators and consumers both lack effective strategies for optimally using stored energy that is generated by renewable energy sources. This dissertation presents a comprehensive stochastic optimization framework to prescribe optimal strategies for effectively managing stored energy in microgrids, subject to the inherent uncertainty of renewable resources, local demand and electricity prices. First, a Markov decision process model is created to characterize and illustrate structural properties of an optimal storage strategy and to assess the economic value of sharing stored energy between heterogeneous, demand-side entities. Second, a multistage stochastic programming (MSP) model is formulated and solved to determine the optimal storage, procurement, selling and energy flow decisions in a microgrid, subject to storage inefficiencies, distribution line losses and line capacity constraints. Additionally, the well-known stochastic dual dynamic programming (SDDP) algorithm is customized and improved to drastically reduce the computation time and significantly improve solution quality when approximately solving this MSP model. Finally, and more generally, a novel nonconvex regularization scheme is developed to improve the computational performance of the SDDP algorithm for solving high-dimensional MSP models. Specifically, it is shown that these nonconvex regularization problems can be reformulated as mixed-integer programming problems with provable convergence guarantees. The benefits of this regularization scheme are illustrated by way of a computational study that reveals significant improvements in the convergence rate and solution quality over the standard SDDP algorithm and other regularization schemes.
Managing Marketing Decision-Making with Sentiment Analysis: An Evaluation of the Main Product Features Using Text Data Mining

Companies have realized the importance of “big data” in creating a sustainable competitive advantage, and user-generated content (UGC) represents one of big data’s most important sources. From blogs to social media and online reviews, consumers generate a huge amount of brand-related information that has a decisive potential business value for marketing purposes. Particularly, we focus on online reviews that could have an influence on brand image and positioning. Within this context, and using the usual quantitative star score ratings, a recent stream of research has employed sentiment analysis (SA) tools to examine the textual content of reviews and categorize buyer opinions. Although many SA tools split comments into negative or positive, a review can contain phrases with different polarities because the user can have different sentiments about each feature of the product. Finding the polarity of each feature can be interesting for product managers and brand management. In this paper, we present a general framework that uses natural language processing (NLP) techniques, including sentiment analysis, text data mining, and clustering techniques, to obtain new scores based on consumer sentiments for different product features. The main contribution of our proposal is the combination of price and the aforementioned scores to define a new global score for the product, which allows us to obtain a ranking according to product features. Furthermore, the products can be classified according to their positive, neutral, or negative features (visualized on dashboards), helping consumers with their sustainable purchasing behavior. We proved the validity of our approach in a case study using big data extracted from Amazon online reviews (specifically cell phones), obtaining satisfactory and promising results. After the experimentation, we could conclude that our work is able to improve recommender systems by using positive, neutral, and negative customer opinions and by classifying customers based on their comments.
Reading the Fine Print: Issue Advertisements and the Persuasive Effects of Campaign Finance Disclosures

There is an expectation among practitioners that advertising disclosures work to inform voters about who is speaking and whether they should trust the information in the advertisement. However, existing research suggests that current disclosure regulations may not perform as reformers expect. These studies indicate that voters may be deceived by strategically chosen interest group names that falsely project knowledge or trustworthiness. In this study, I measure how actual campaign names and interest groups are perceived by individuals in terms of their knowledge and trustworthiness. I then experimentally vary the campaign finance disclosure within a ballot initiative advertisement to see how these disclosures affect respondents’ issue preferences. This study found that in some cases, there was no difference between an advertisement with no disclosure and one with a veiled disclosure message. In other cases, this level of disclosure reduced support for the issue. In most cases, respondents appear to condition their support on the credibility of the campaign donor disclosed. In some cases, respondents are deceived by the perceived credibility of campaign names when less comprehensive disclosure is used.
Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems

The Autonomous Agents and MultiAgent Systems (AAMAS) conference series brings together researchers from around the world to share the latest advances in the field. It provides a highprofile and high-quality forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS 2002, the first of the series, was held in Bologna, followed by Melbourne (2003), New York (2004), Utrecht (2005), Hakodate (2006), Honolulu (2007), Estoril (2008), Budapest (2009), Toronto (2010), Taipei (2011), Valencia (2012), and Saint Paul (2013). This volume constitutes the proceedings of AAMAS 2014, the thirteenth conference in the series, held in Paris in May 2014. In line with previous editions, AAMAS 2014 attracted submissions for a general track and four special tracks: robotics, virtual agents, innovative applications, and a challenges and visions track. The special tracks were chaired by leaders in their corresponding fields: Noa Agmon and Luiz Chaimowicz chaired the robotics track, Elisabeth Andre and Sarit Kraus the virtual agents track, Tom Holvoet and Rajiv Maheswaran the innovative applications track, and Munindar Singh the challenges and visions track. The special track chairs worked with Program Committee Members (PC), Senior Program Committee (SPC) members, and the Program Chairs to select the papers submitted to the special tracks. Full paper (8 pages), challenges and vision (4 pages), and extended abstract (2 pages) submissions were solicited for AAMAS 2014. The papers were selected by means of a thorough review and discussion process, which included an opportunity for authors to respond to reviewer comments. All SPC members followed and contributed to the technical discussions on the papers they were overseeing and participated in a conference call with the program chairs, where each paper in their allocation was discussed. In addition to this, the special track chairs held conference calls with the program chairs to further discuss the papers in the special tracks. Full papers were presented orally in 20 minute slots; all full papers and extended abstracts were presented as posters during the conference. Out of the 709 submissions, 425 (60%) had a student as the primary author, 86 of these were accepted as full papers (12%), and a further 109 (15%) were accepted as extended abstracts.
Modeling Runoff-Formation and Soil Erosion after Pumice Excavation at Forested Andosol-Sites in SW-Germany Using WEPP

This study investigates the effects of pumice excavation on runoff formation and soil erosion processes in a forested catchment in SW-Germany. The underlying questions are, if (a) backfilled soils have different properties concerning runoff generation and erodibility and if (b) clear-cutting prior to excavation triggers runoff and erosion. Four adjacent sub-areas were observed, which represented different pre- and post-excavation-stages. The basis of the investigation was a comprehensive field sampling that delivered the data for physical erosion modeling using the Water Erosion Prediction Project (WEPP). Modeling took place for standardized conditions (uniform slope geometry and/or uniform land management) and for actual slope geometry and land management. The results show that backfilled soils exhibited 53% increase of annual runoff and 70% increase of annual soil loss under standardized conditions. Storm runoff was increased by 6%, while storm soil loss was reduced by 9%. Land management changes also triggered shifts in annual runoff and soil erosion: Clear-cut (+1.796% runoff, +4.205% soil loss) and bare (+5.958% runoff, +21.055% soil loss) surfaces showed the most distinct changes when compared to undisturbed forest. While reforestation largely diminished post-excavation runoff and soil erosion, the standardized results statistically prove that soil erodibility and runoff generation remain increased after backfilling.
The effect of comparison on the perceived similarity of complex visual stimuli

Comparison has been shown to decrease the perceived similarity of artificial face stimuli that are difficult to discriminate (Mundy, Honey, & Dwyer, 2007). This thesis presents seven experiments that examined the effect of comparison on the perceived similarity of a wider range of unfamiliar face stimuli. Participants were asked to compare two faces before either rating their perceived similarity, or deciding whether they are the same person. In the first five experiments participants were shown face pairs that ranged in phenotypic similarity—the degree to which the two faces look alike. With the exception of highly similar face morphs comparison was found to increase the perceived similarity of both phenotypically similar and dissimilar face pairs, relative to a no-comparison control. This finding suggests that for most naturally occurring face stimuli, comparison results in an increase in perceived similarity. In the last two experiments the quality of one of the stimuli in each pair was degraded to simulate the effects of poor quality video footage. A comparisonrelated decrease in perceived similarity was found in both experiments. This finding suggests that pictorial differences between face stimuli—including differences in image quality, camera distance and lighting, variations in pose and facial expression, and the presence of disguises such as hats and sunglasses—play an important role in mediating the effect of comparison on perceived similarity.
A Benefit Accrual Model For Distributed Real-Time Computers

In distributed real-time computing systems, the laws of physics and the intrinsic nature of the applications are contrary to the premises which underlie most traditional real-time computing principles and technology. This necessitates a more general model of real-time which accommodates non-stochastically non-deterministic activities that nonetheless have mission-critical completion time constraints. Our model expresses result completion time constraints in terms of: the benefit to the system that the results yield, individually and collectively, as a function of their completion times (and other parameters); together with application-specific predicates for correctness optimization based on accruing benefit. To exploit this generality, we have devised experimental best-effort real-time scheduling algorithms which analysis, simulation, and measurement have shown to accrue higher benefit than do traditional algorithms, and which have the greater dynamic situational coverage required in distributed real-time computing systems.
Higher-layer issues: Ad hoc and sensor networks

Ultra-wide-band (UWB) radio has the potential of allowing simultaneous communication of a large number of users at high bit rates [1–3]. In addition, the high temporal resolution inherent to UWB provides robustness against multipath fading and is particularly attractive for indoor local area network (LAN) applications. UWB is also capable of recovering distance information with great precision. As we will show later in this chapter, distance and position data can lead to better organization of wireless networks, for instance, through better resource management and routing [4]. UWB signals spread, however, over very large bandwidths and overlap with narrowband services. As a consequence, regulatory bodies impose severe limitations on UWB power density in order to avoid interference provoked byUWBonto coexisting narrowband systems [5]. It is therefore necessary to take into account power considerations when designing UWB systems. Throughout this chapter we will show how the distance information made available by the UWB technology can be exploited to achieve low power levels and increase network lifetime in the long term, while providing an adequate network performance (in terms of data throughput) in the short term. In the last few years, the increasing interest in applications based on the deployment of ad hoc networks triggered significant research efforts regarding the introduction of the energy-awareness concept in the design of medium access control (MAC) and routing protocols. Ad hoc networks are in fact considered as a viable solution for scenarios in which fixed infrastructure, and consequently unlimited power sources, are not available. In such scenarios, an efficient management of the limited power supply available in each terminal is a key element for achieving acceptable network lifetimes. This is particularly true for sensor networks, for which long battery duration is one of the basic requirements, given the typical size of such networks (up to thousands of terminals), as will be analyzed in Section 4.2. Location information is another valuable way of achieving energy-awareness in ad hoc networks. In Section 4.3 we first review location-aware routing protocols
Future Hot and Dry Years Worsen Nile Basin Water Scarcity Despite Projected Precipitation Increases

Compound extremes—particularly hot and dry years—can reduce crop yields and result in acute water scarcity. These risks are particularly pronounced in the Upper Nile Basin, a chronically water stressed agricultural region that includes western Ethiopia, South Sudan, and Uganda. While the causes of humanitarian crises in the Nile Basin are complex and involve governance, conflict, and climate, we demonstrate that nearly all recent regional crop failures have occurred amid hot and dry conditions and low runoff supplies. Using an observational ensemble, we find that such hot and dry years have been more frequent in recent decades, driven by increasing regional temperatures. This trend is likely to continue despite climate model projections of increasing regional precipitation. By the late 21st century, the frequency of hot and dry years may rise by a factor of 1.5–3, even if warming is limited to 2 °C. Regional water scarcity will continue to be a chronic issue for the Upper Nile from population growth alone, but runoff deficits during future hot and dry years will amplify this effect, leaving an additional 5–15% of the future population facing water scarcity. Climate change, along with the region's complex water politics, dependence on subsistence agriculture, and history of geopolitical instability, places the region at risk of severe food and water shortages as hot and dry years become more frequent. Adaptation and climate‐resilient water management policies informed by an understanding of compound extremes will be essential to manage these risks.
Fear of Incompetence in Intergenerational Relationships with a Family Member with Dementia

ABSTRACT Particularly in intergenerational relationships, family members feel they lack the knowledge and skills necessary for successful interaction with their loved ones with dementia, which leads to fear of incompetence. We examined the antecedents and outcomes of fear of incompetence, defined as the fear of being unable to interact, communicate, or take care of a close family member with dementia. Ninety-two participants completed a questionnaire about a family member with dementia. Fear of incompetence was predicted by severity of dementia symptoms and predicted increased negative stereotyping and decreased desired sensory interaction. We offered recommendations for designing effective intergenerational interaction strategies.
Low-cost multi-camera module and processor array for the ultra-fast framerate recognition, location, and characterization of explosive events

In the image processing world the detection, location, and identification of explosive events is accomplished usually by single detectors, single element detector arrays, or higher cost cameras (primarily infrared). Imaging systems have been limited by the too few event frames, high costs of components, and poor false alarm rates. For the last three years NRL’s Advanced Techniques Digital Technologies section has been researching ultra-fast framerate explosive event detection. NRL has designed, fabricated, and tested a multi-sensor array of low cost camera modules, each with its own field programmable gate array processor, which are then networked together to implement a system capable of imaging explosive events at 16-30kHz framerates in real time. These camera modules work in the visible band and open up the possibility of exploiting 30-60 frames of an explosive event. With this array it is possible not only to image burning gases and high intensity flashes but also low signature moving effluent and airborne particles. By using processors behind each camera module it is possible to leverage different parts of the algorithm to accomplish computationally expensive operations on individual frames. Networking the array together allows further distribution of the processing for further temporal analysis. Finally all of the resulting images are sent to a central processor where the final parts of the algorithm are completed. The cost of this system once optimized for production will be close to that of acoustic systems but with much higher precision.
Research on Hedging Ratio of Power Futures Based on 0LS Model

With the further development of power market reform, the demand for energy trading entities to avoid the risk of electricity price is becoming more and more prominent. This paper uses the method of minimizing the variance of the portfolio return rate combined with the electricity futures price data from the European Energy Exchange to estimate the optimal hedging ratio and perform the residual test. Finally, the decision of power producers to use the power futures hedging strategy to avoid the risk of spot price fluctuations will be discussed.
The Contingent Value of Entrepreneurs’ Political Capital: Evidence from China

ABSTRACT Who benefit from a transitioning economy, entrepreneurs who are politically connected or disconnected? Market transition theory and power conversion theory offer two divergent answers. Our study seeks to contribute to this debate by examining the contingent value of entrepreneurs’ political capital. We draw from social network theories and investigate whether and how entrepreneurs’ social networks influence the relationship between their political capital and social mobility. Using the data on Chinese entrepreneurs, we find that the impact of political capital on entrepreneurs’ social mobility is contingent on their network centrality. Practical implications and suggestions for future research are also discussed.