Miracle-dz/UniFAR-FTUs huggingface dataset:
Analytical shape computation of macromolecules: I. molecular area and volume through alpha shape

The size and shape of macromolecules such as proteins and nucleic acids play an important role in their functions. Prior efforts to quantify these properties have been based on various discretization or tessellation procedures involving analytical or numerical computations. In this article, we present an analytically exact method for computing the metric properties of macromolecules based on the alpha shape theory. This method uses the duality between alpha complex and the weighted Voronoi decomposition of a molecule. We describe the intuitive ideas and concepts behind the alpha shape theory and the algorithm for computing areas and volumes of macromolecules. We apply our method to compute areas and volumes of a number of protein systems. We also discuss several difficulties commonly encountered in molecular shape computations and outline methods to overcome these problems. Proteins 33:1–17, 1998. © 1998 Wiley‐Liss, Inc.
The Reaction of Corn and Soybean Futures Markets to USDA Crop Progress and Condition Information

The objective of this study is to investigate the reactions of corn and soybean futures markets to crop progress and condition information of USDA's Crop Progress (CP) reports in an event study methodology over the period 1986 to 2012. Results show, first, significant differences in close-to-open return variability on report release trading days and pre- and postreport days, and second, market prices tend to react rapidly to new crop condition information in the indicated direction by changes in crop condition. Strongest market reactions for reports containing both crop progress and condition information could be found for summer months of July and August when weather conditions (precipitation and temperature) are most critical for the crop. Furthermore, the results show that the reactions of CP reports have increased over time. Overall, price reaction analyses in this study suggest that USDA's CP reports have substantial informational value.
Similarity Measurement among Technologies using Euclidean Distance

Recently, various technologies for conserving and using energy resources efficiently have been developed worldwide, among which wind energy and fuel cells have been receiving much attention as renewable energy, and LED application field has received attention in the aspect of energy usage. This study aims to build an IPC network among technologies using patent information on wind energy, fuel cells, and LED application field, and to investigate the connectivity structure between technologies with network clustering. As a result, it was concluded that technologies in the fields of wind energy, fuel cells, and LED application were interconnected. When analyzing the yearly similarities between technologies using Euclidean distance, it was estimated that the technological similarities in the fields of LED application and fuel cells have been increasing. Keywords—Clustering, Network Analysis, Euclidean
Harmonic Retrieval in Complex Noise Based on Group Delay

Group delay (GD), the negative derivative of Fourier Transform phase, is regarded as a good tool for spectral estimation in additive noise, for its sharp peak and high resolution. However, as far, GD has not been utilized in the case involving complex noises. In this paper, a novel GD is proposed to the time-varying cumulants of harmonics in complex noises, termed as CGD. A simple and practical algorithm is also derived. Numerical results show that, for the problems in complex noises, the new approach outperforms some traditional methods greatly.
Pro-Inflammatory Cytokines Reduce the Proliferation of NG2 Cells and Increase Shedding of NG2 In Vivo and In Vitro

Neuron glial 2 (NG2) cells become strongly activated in injured brain areas. The activation is characterized by increased proliferation as well as increased expression and shedding of the proteoglycan NG2 expressed on their cell surface. It is currently not known how these cells respond to low-grade neuroinflammation provoked by systemic inflammation. To investigate this, we analyzed NG2 cell proliferation as well as soluble NG2 (sNG2) in cerebrospinal fluid (CSF) from rats treated with an acute intraperitoneal (i.p) injection of lipopolysaccharides (LPS) or saline and sacrificed after 2 or 24 hours. The systemically induced neuroinflammation was confirmed as elevated levels of cytokines, including interleukin (IL)-6 and IL-1β, and MHCII expressing microglia were found 24 h after LPS treatment. At this time point NG2 cell proliferation was significantly decreased in both amygdala and hippocampus and sNG2 levels in CSF were increased twofold. We also exposed human NG2 cells in culture to IL-6 and IL-1β for 24 h and found, in line with our in vivo study, a direct impact of these cytokines reducing cell proliferation and increasing shedding of NG2. We conclude that LPS induced systemic inflammation significantly affects NG2 cell proliferation and shedding and that these two events at least in in part are mediated by IL-6 and IL-1β.
Immigration and the import of cultural goods

This research studies the effect of immigration as a determinant of the import of cultural goods to Canada. The period studied covers a time span of 15 years from 1996 to 2010 while utilising data from 15 of Canada’s top trading partners for cultural goods. Empirical results suggest that there are various significant determinants of cultural trade such as economic mass of the exporting country, geographic distance and shared official common language. Furthermore, results suggest that the stock of immigrants has a positive effect on imports of cultural goods to Canada. Empirical results are based on an augmented gravity model while using ordinary least squares method.
A DELLA gene , RhGAI 1 , is a direct target of EIN 3 and mediates ethylene-regulated rose petal cell expansion via repressing the expression of RhCesA 2

Ethylene plays an important role in organ growth. In Arabidopsis, ethylene can inhibit root elongation by stabilizing DELLA proteins. In previous work, it was found that ethylene suppressed cell expansion in rose petals, and five unisequences of DELLA genes are induced by ethylene. However, the mechanism of transcriptional regulation of DELLA genes by ethylene is still not clear. The results showed that the expression of RhGAI1 was induced in both ethylene-treated and ETR gene-silenced rose petals, and the promoter activity of RhGAI1 was strongly induced by RhEIN3-3 in Arabidopsis protoplasts. What is more, RhEIN3-3 could bind to the promoter of RhGAI1 directly in an electrophoretic mobility shift assay (EMSA). Cell expansion was suppressed in RhGAI1-Δ17-overexpressed Arabidopsis petals and promoted in RhGAI1-silenced rose petals. Moreover, in RhGAI1-silenced petals, the expression of nine cell expansion-related genes was clearly changed, and RhGAI1 can bind to the promoter of RhCesA2 in an EMSA. These results suggested that RhGAI1 was regulated by ethylene at the transcriptional level, and RhGAI1 was a direct target of RhEIN3-3. Also, RhGAI1 was shown to be involved in cell expansion partially through regulating the expression of cell expansion-related genes. Furthermore, RhCesA2 was a direct target of RhGAI1. This work uncovers the transcriptional regulation of RhGAI1 by ethylene and provides a better understanding of how ethylene regulates petal expansion in roses.
Do Women Favor Foreign Direct Investment?

Abstract Although some studies show that women are more likely to oppose free trade than men, others demonstrate that economic globalization empowers women. Given this paradox, we examine whether gender shapes individual preferences with respect to foreign direct investment (FDI) in developing countries. We hypothesize that women do not disfavor FDI more than men because multinational corporations (MNCs) bring more jobs for women, provide better working conditions and higher wages than domestic firms, and spread norms and values that favor gender equality. Moreover, this gender gap will be wider in more globalized countries because women can observe such benefits of MNCs. To test our arguments, we used survey data from the 2007 Pew Global Attitudes Project. Overall, women view FDI more positively than men, and this effect is stronger in economically more globalized countries and countries that are less dependent on agriculture. Women have a different view on FDI than that on trade.
Localization and Fitness Inheritance in Solving Noisy Multi-objective Optimization Problems

This paper investigates the use of local models in the context of noisy evolutionary multi-objective optimization. Within this technique, the search space is explicitly divided into several non-overlapping hyper-spheres. The mechanism allows evolution and the process of filtering noise within the local spaces of these hyper-spheres, instead of the global space. A direction of improvement, that is related to the average performance of the spheres is used to make future moves of the spheres. This helps the local models to filter noise; thus become more robust in the presence of noise. A wide range of noisy problems were used to test the performance of the local models, as well as the combination of the local models and fitness inheritance, an approximation method. The experimental results show good performance of the local models in comparison with that of a global model.
SecuSpot: Toward Cloud-Assisted Secure Multi-Tenant WiFi HotSpot Infrastructures

Despite the increasing popularity of WiFi networks and the trend toward automated offloading of cellular traffic to WiFi (e.g., HotSpot 2.0), today's WiFi networks still provide a very poor actual coverage: a WiFi equipped device can typically connect to the Internet only through a very small fraction of the "available" access points. Accordingly, there is an enormous potential for multi-tenant WiFi hotspot architectures, which however also introduce more stringent requirements in terms of scalability and security. The latter is particularly critical, as HotSpots are often deployed in untrusted environments, e.g., physically accessible Access Points deployed in the user's premises (e.g., FON) or cafes. This paper proposes a Cloud-assisted multi-tenant and secure WiFi HotSpot infrastructure, called SecuSpot. SecuSpot is based on a modular access point and features interesting deployment flexibilities. These flexibilities can be exploited, e.g., to move security critical functions to the Cloud, and hence prevent eavesdropping even when deployed across untrusted Access Points. At the heart of SecuSpot lies a novel programmable wireless switch, the wSwitch. The wSwitch allows to (de-)multiplex the different tenants already on the HotSpot and to decouple essential security functions (association, authentication, and cryptography).
Storing AXML documents with ARAXA

Active XML (AXML) documents combine extensional XML data with intentional data defined through Web service calls. The dynamic properties of these documents pose challenges to both storage and data materialization techniques. We present ARAXA, a non-intrusive approach to store AXML documents. It takes advantage of complex objects from object- relational DBMS to represent both extensional and intentional data. By using a DBMS we benefit from efficient storage tools and query engine. We have defined a storage mechanism with a methodology to materialize AXML documents at query time. We have also implemented a prototype of ARAXA. Our experimental results show that our approach is scalable and extensible.
Growth rates of six coccolithophorid strains as a function of temperature

We determined growth rates of six coccolithophorid strains (five species) as a function of temperature. We grew four strains (three species: Emiliania huxleyi, Gephyrocapsa oceanica, and two strains of Calcidiscus leptoporus) at six temperatures between 6°C and 25°C, Coccolithus braarudii at four temperatures, and Syracosphaera pulchra at two temperatures. The growth rates were to a large extent consistent with the biogeographical distributions of these species. C. braarudii grows relatively fast at low temperatures, the two strains of C. leptoporus have temperature optima of 12°C and 20°C, E. huxleyi has an optimum at 20°C, and the growth rate of G. oceanica (and S. pulchra) increases up to the highest tested temperature of 25°C. This shows that maximum growth rate is an important factor in controlling distribution in the ocean, but it is not the only one.
BuildBot: A Robotic Software Development Monitor in an Agile Environment

In this paper, we describe BuildBot, a robot developed to assist with continuous integration of a software build in Agile development teams. BuildBot can interact physically with individual members of the team and be an active part of the development process by bringing together human-robot interaction with human group dynamics and knowledge about software engineering concepts. This paper describes the design and implementation of a robot that can sense virtual stimuli, in this case the state of a software build, and react accordingly in a physical way. By increasing awareness of the state of the software build, BuildBot assists in the selfsupervision of teams.
Spectra of random graphs with community structure and arbitrary degrees

Using methods from random matrix theory researchers have recently calculated the full spectra of random networks with arbitrary degrees and with community structure. Both reveal interesting spectral features, including deviations from the Wigner semicircle distribution and phase transitions in the spectra of community structured networks. In this paper we generalize both calculations, giving a prescription for calculating the spectrum of a network with both community structure and an arbitrary degree distribution. In general the spectrum has two parts, a continuous spectral band, which can depart strongly from the classic semicircle form, and a set of outlying eigenvalues that indicate the presence of communities.
The Use of Ontologies in Location-based Services : The Space and Time Ontology in Protégé

As location-based applications become part of our everyday life, ranging from traffic prediction systems to services over mobile phones providing us with information about our surroundings, the call for more semantics and accurate services related to them is emerging. Moreover, the need for integration of multiple data sources calls for an abstract location model, easily understandable to domain experts. In this paper, we study and analyze the concepts involved in Location-Based Services (LBS); three of them, namely space, time and movement are fundamental and have common characteristics in all LBS applications. We first present a systematic analysis and structure of space, time and movement, register their characteristics and their relations. In order to (a) make LBS assumptions that already exist in literature about space, time and movement explicit (b) share common understanding of their structure, and (c) enable reuse of this LBS knowledge, we use long-praised technique of ontologies to organize and design them. More specifically, we introduce an ontology structure for LBSs consisting of the Domain Ontology, the Content Ontology and the Application Ontology. The proposed design of space, time and movement constitute the Domain Ontology. We design the Domain Ontology of LBS in Protégé, an open-source, extensible-code tool, allowing for the easy and understandable representation of ontologies from experts. The presented Domain Ontology is component of the knowledge base of a fleet management system handling traffic in the Athens Metropolitan Area.
Semiconductor Optical Amplifiers and their Application for All Optical Wavelength Conversion

All optical networks and switches are envisioned as a solution to the increasing complexity and power consumption of today’s communication networks who rely on optical fibers for the transmission of information but use electronics at the connecting points on the network (nodes) to perform the switching operation. All optical networks, in contrast, will use simple signalling methods to trigger all optical switches to forward the optical data, from one optical fiber to another, without the need to convert the information carried by the optical signal into an electric one. This may save up to 50% of the total power consumption of the switches and will allow for simple scaling of the transmission rates. While all optical networks may offer significant breakthroughs in power consumption and network design, they fall back on one essential aspect, contention resolution. In traditional communication networks and in particular those who carry data (which has long surpassed voice traffic, in bandwidth), the nodes on the network use huge amounts of electronic random access memory (RAM) to store incoming data while waiting for their forwarding to be carried out. The storage of data, also called buffering, is essential in resolving contention which occurs when two incoming streams of data need to be forwarded to the same output port at the same time. In contrast all optical switches, who do not convert the data signals into the electrical domain, cannot use electronic buffers for contention resolution. They can however use the unique properties of light signals which at moderate power levels can propagate along the same transmission media without interference if they have different wavelengths. This means that if two competing light signals need to be switched to the same output port, their successful forwarding can be accomplished by assigning them different wavelength. This can be done completely in the optical domain by means of all optical wavelength conversion. Large optical networks, require optical amplifiers for signal regeneration, especially so if the signal is not regenerated through optical to electrical to optical conversion. Semiconductor Optical Amplifiers (SOAs) are a simple, small size and low power solution for optical amplification. However, unlike fiber based amplifiers such as EDFAs, they suffer from a larger noise figure, which severely limits their use for long haul optical communication networks. Nevertheless, SOAs have found a broad area of applications in non-linear all optical processing, as they exhibit ultra fast dynamic response and strong non-linearities,
Combining Syntactic Knowledge and Visual Text Recognition: A Hidden Markov Model for Part of Speech Tagging In a Word Recognition Algorithm

The use of a hidden Markov model (HMM) for the assignment of part-of-speech (POS) tags to improve the performance of a text recognition algorithm is dis- cussed. Syntactic constraints are described by the tran- sition probabilities between POS tags. The confusion between the feature string for a word and the various tags is also described probabilislically. A modification of the Viterbi algorithm is also presented that finds a fixed number of sequences of tags for a given sentence that have the highest probabilities of occurrence, given the feature strings for the words. An experimental application of this approach is demonstrated with a word hypothesizalion algorithm that produces a number of guesses about the identity of each word in a running text. The use of first and second order transition probabili- lies is explored. Overall performance of between 65 and 80 percent reduction in the average number of words that can match a given image is achieved. A computational theory for word recognition has been proposed that overcomes some of the constraints of other methodologies (6). The design of this tech- nique is based on human performance in reading which suggests that the feature analysis of word images includes a wholistic analysis of word shape. Also, feature extraction from a word image is only; one part of a complex process of developing an understanding of a text. Furthermore, the model suggests that to achieve high levels of performance in text recognition for a range of input qualities it may be necessary to understand the text as well. One part of the understanding process that underlies word recognition is an analysis of the syn- tax of the text. This paper discusses aspects of a Markov model for POS tagging where the probability of observing any POS tag is dependent on the tag of the previous word (8, 9). This model is applied to text recognition by first using a word recognition algorithm to supply a number of alternatives for the identity of each word. The tags of the alternatives for the words in a sentence are then input to a modilied Viterbi algorithm that determines sequences of syntactic classes that include each word. An alternative for a word decision is out- put only if its part of speech tag is included in at least one of these sequences. The Markov model improves word recognition performance if the number of altema- lives for a word are reduced without removing the correct choice. The rest of this paper briefly introduces the com- putational model for word recognition. This is followed by a description of how a Markov model for language syntax is incorporated in the model. The modified Viterbi algorithm proposed in this paper is then described. The performance of this technique in reduc- ing the number of alternatives for words in a sample of text is then discussed. The effect of employing the first and second order Markov assumptions and different methods of estimating the probabilities are explored.
Improving the performance of trace-based systems by false loop filtering

Trace-based compilation is a promising technique for language compilers and binary translators. It offers the potential to expand the compilation scopes that have traditionally been limited by method boundaries. Detecting repeating cyclic execution paths and capturing the detected repetitions into traces is a key requirement for trace selection algorithms to achieve good optimization and performance with small amounts of code. One important class of repetition detection is cyclic-path-based repetition detection, where a cyclic execution path (a path that starts and ends at the same instruction address) is detected as a repeating cyclic execution path. However, we found many cyclic paths that are not repeating cyclic execution paths, which we call false loops. A common class of false loops occurs when a method is invoked from multiple call-sites. A cycle is formed between two invocations of the method from different call-sites, but which does not represent loops or recursion. False loops can result in shorter traces and smaller compilation scopes, and degrade the performance. We propose false loop filtering, an approach to reject false loops in the repetition detection step of trace selection, and a technique called false loop filtering by call-stack-comparison, which rejects a cyclic path as a false loop if the call stacks at the beginning and the end of the cycle are different. We applied false loop filtering to our trace-based Java™ JIT compiler that is based on IBM's J9 JVM. We found that false loop filtering achieved an average improvement of 16% and 10% for the DaCapo benchmark when applied to two baseline trace selection algorithms, respectively, with up to 37% improvement for individual benchmarks. In the end, with false loop filtering, our trace-based JIT achieves a performance comparable to that of the method-based J9 JVM/JIT using the corresponding optimization level.
Goal Setting and Performance Management in the Public Sector

ABSTRACT The public sector in North America as well as parts of Europe is increasingly adopting a performance management system that includes goal setting, coaching, and the evaluation of an employee on goal attainment. The purpose of this article is three-fold. First, the extant literature on goal setting for individual employees is summarized in terms of its applicability to the public sector. Second, the importance of context to goal setting and performance management in the United States and Italy is discussed. Third, coaching techniques, based on theory and empirical evidence, for increasing the probability of goal attainment by public sector employees are examined.