Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Atrazine Administered by Gavage or in Diet on the LH Surge and Reproductive Performance in Intact Female Sprague-Dawley and Long Evans Rats

Atrazine (ATR) blunts the hormone-induced luteinizing hormone (LH) surge, when administered by gavage (50–100 mg/kg/day for 4 days), in ovariectomized rats. In this study, we determined if comparable doses delivered either by gavage (bolus dose) or distributed in diet would reduce the LH surge and subsequently affect fertility in the intact female rat. ATR was administered daily to intact female Sprague-Dawley (SD) or Long Evans (LE) rats by gavage (0, 0.75 1.5, 3, 6, 10, 12, 50, or 100 mg/kg/day) or diet (0, 30, 100, 160, 500, 660, or 1460 ppm) during one complete 4-day estrous cycle, starting on day of estrus. Estrous status, corpora lutea, ova, and LH plasma concentrations were evaluated. A second cohort of animals was mated on the fourth treatment day. Fertility metrics were assessed on gestational day 20. A higher portion of LE rats had asynchronous estrous cycles when compared to SD rats both during pretreatment and in response to ATR (≥50 mg/kg). In contrast, bolus doses of ATR (≥50 mg/kg) inhibited the peak and area under the curve for the preovulatory LH surge in SD but not LE animals. Likewise, only bolus-treated SD, not LE, rats displayed reduced mean number of corpora lutea and ova. There were no effects of ATR administered by gavage on mating, gravid number, or fetus number. Dietary administration had no effect on any reproductive parameter measured. These findings indicate that short duration, high-bolus doses of ATR can inhibit the LH surge and reduce the number of follicles ovulated; however, dietary administration has no effect on any endocrine or reproductive outcomes
Ontology-based Security Policy Translation

The security configuration of large networked ICT systems is a difficult and error-prone task. Quite often attacks are enabled by mis-configurations generated by human errors. Policy- based network management has been proposed to cope with this problem: goals are expressed as high-level rules that are then translated into low-level configurations for network devices. While the concept is clear, there is a lack of tools supporting this strategy. We propose an ontology-based policy translation approach that mimics the behaviour of expert administrators, without their mistakes. Normally administrators are given the high-level security goals and then, through their knowledge of network topology and security best practice, derive the device configurations. In a similar way, we use an ontology to represent the domain knowledge and then perform reasoning (based on best practice rules) to create the configurations for network-level security controls (e.g., firewall and secure channels). If some information is missing from the ontology, the administrator is guided to provide the missing data. The configurations generated by our approach are represented in a vendor-independent format and therefore can be used with several kinds of devices.
Resource Management for Chained Binary Classifiers

Networks of classifiers are capturing the attention of system and algorithmic researchers because they offer improved accuracy over single model classifiers, can be distributed over a network of servers for improved scalability, and can be adapted to available system resources. However, resource management for a network of classifiers, each with a range of operating points, is challenging because limiting one resource (e.g. CPU) may decrease the accuracy for that classifier, and increase other resource requirements (e.g. input bandwidth for downstream classifiers). In this paper we formulate the problem of optimal resource allocation for a chain of binary classifiers under generic resource constraints. We formally define a performance measure for the output of a chain of classifiers. We present our results for state-of-the-art classifiers operating on telephony data and offer interesting future directions based on these results.
Fusepool R5 linked data framework: concepts, methodologies, and tools for linked data

The work reported here was done within the applied research project Fusepool. Fusepool is an international project to develop a set of integrated software components to ease the publishing of open data based on an open-source Linked Data Platform and a set of associated best practices. This article provides researchers and laypersons interested in Linked Open Government Data an overview of the concepts, methodologies, and tools. It introduces the main concepts, such as open government and open government data along with enabling technological approaches such as the semantic web and linked data. It then presents the methodologies for publishing Linked Open Government Data along the R5 framework: Reveal, Refine, Reuse, Release, and Run. The final section discusses the potential impact of the Linked Data Platform as well as areas for further improvement.
A Scalable and Fault Tolerant Architecture for Distributed Web Resource Discovery

Most Internet search engines are built on a centralised design, and will therefore not cope with the expected future growth in information and query volume. A distributed approach to Internet resource discovery seems necessary. Many distributed designs have been proposed, but their scaleability is largely unknown. We propose a distributed design based on the use of classified metadata, which can be proven to be extremely scaleable, and has interesting fault-tolerant properties. We will show the principles of this design, called the Content- Sensitive Infrastructure (CSI), and demonstrate its properties through formal analysis and simulation.
Age at Menarche and Menopause and Breast Cancer Risk in the International BRCA1/2 Carrier Cohort Study

Background: Early menarche and late menopause are important risk factors for breast cancer, but their effects on breast cancer risk in BRCA1 and BRCA2 carriers are unknown. Methods: We assessed breast cancer risk in a large series of 1,187 BRCA1 and 414 BRCA2 carriers from the International BRCA1/2 Carrier Cohort Study. Rate ratios were estimated using a weighted Cox-regression approach. Results: Breast cancer risk was not significantly related to age at menopause {hazard ratio [HR] for menopause below age 35 years, 0.60 [95% confidence interval (95% CI), 0.25-1.44]; 35 to 40 years, 1.15 [0.65-2.04]; 45 to 54 years, 1.02 [0.65-1.60]; ≥55 years, 1.12 [0.12-5.02], as compared with premenopausal women}. However, there was some suggestion of a reduction in risk after menopause in BRCA2 carriers. There was some evidence of a protective effect of oophorectomy (HR, 0.56; 95% CI, 0.29-1.09) and a significant trend of decreasing risk with increasing time since oophorectomy, but no apparent effect of natural menopause. There was no association between age at menarche and breast cancer risk, nor any apparent association with the estimated total duration of breast mitotic activity. Conclusions: These results are consistent with other observations suggesting a protective effect of oophorectomy, similar in relative effect to that in the general population. The absence of an effect of age at natural menopause is, however, not consistent with findings in the general population and may reflect the different natural history of the disease in carriers. (Cancer Epidemiol Biomarkers Prev 2007;16(4):740–6)
Management and Conservation of Tree Squirrels: The Importance of Endemism, Species Richness, and Forest Condition

Tree squirrels are excellent indicators of forest health yet the taxon is understudied. Most tree squirrels in the Holarctic Region are imperiled with some level of legal protection. The Madrean Archipelago is the epicenter for tree squirrel diversity in North America with 5 endemic species and 2 introduced species. Most species of the region are poorly studied in keeping with an international dearth of data on this taxon; 3 of the 5 native species are the subject of <3 publications. Herein, I review literature on the response of squirrels to forest management from clearcutting to less comprehensive operations. Major threats to squirrel diversity in the Madrean Archipelago's Sky Islands are the introduction of species, altered fire regimes, and inappropriate application of forestry practices.
Predicate-based Indexing of Enterprise Web Applications

Searching the Web has become a commodity. However, extending applications with search capabilities is still an open research topic [2]. Large enterprise applications such as SAP and Oracle Finance implement their own search engines. Vendors of small applications cannot afford such an investment and, as a result, small applications either do not provide search facilities or have very imprecise search capabilities. The main problem is to efficiently and completely index dynamic pages which are not physically on disk. This demo shows a generic approach to enhancing enterprise web applications with search capabilities. The approach is independent of the language in which pages are written and it does not require to start the web container. It is based on extended inverted files and it is applied to the PetStore application, a popular Web-based application based on the J2EE framework.
Host use and Resource Sharing by Fruit/Seed-Infesting Insects on Schoepfia schreberi (Olacaceae)

ABSTRACT The interactions between the fruit fly Anastrepha spatulata Stone (Diptera: Tephritidae) and two species of moths, the gelechiid Coleotechnites sp. and an unidentified tortricid species, were examined on their effects on seed production in terms of their exploitation within fruits of Schoepfia schreberi J.F. Gmel (Santalales: Olacaceae). The study was carried out in three experimental sites during 3 yr. Under conditions of abundant fruit, A. spatulata was the dominant exploiter at the population level, as shown by its ability to infest the largest number of fruits of the three herbivores and substantially displace its moth competitors. In a separate experiment, when resource-partitioning species were excluded, A. spatulata infested twice as many fruits as the two moth species (44.3%). Field observations examined the ability of A. spatulata to locate suitable fruits. We found that, the variation in fruit characters influenced fruit suitability in relation to its size (4.1261 ± 0.0272 mm [mean ± SE]) and weight (0.0618 ± 0.0005 mg [mean ± SE]). Uninfested fruits produce viable seed but the interaction of all species (exploiting for the fruits) led to limited seed formation.
MDA-based development in the DECOS integrated architecture - modeling the hardware platform

Reduced time-to-market in spite of increasing the system's functionality, reuse of software on different hardware platforms, and the demand for performing validation activities earlier in the development phase raise the need for revising the state-of-the-art development methodologies for distributed embedded systems. The model driven architecture is a design methodology addressing these emerging requirements. Developing embedded systems according to this model-based paradigm requires a platform-independent representation of the functionality of the application as well as a precise model of the targeted hardware platform. In this paper we introduce a meta-model for capturing the resources of hardware platforms realizing the DECOS architecture, which is an integrated time-triggered architecture aimed at the development of distributed embedded systems. Furthermore, we present a tool chain based on this meta-model that speeds up the modeling process and reduces the likelihood of human errors by facilitating the reuse of hardware building blocks from libraries
Visual Timing in Hitting An Accelerating Ball

To investigate the timing of actions relative to events in the environment, we observed subjects leaping to punch a falling ball. We analysed their knee and elbow angles as functions of time for three ball-drop heights, finding that the differences in the functions for the different heights could be explained on the basis that the subjects were gearing their actions to a particular optic variable. This variable specifies the time remaining before contact with an object if the closing velocity is constant; for the falling ball it gives an increasingly accurate estimate of the time-to-contact. Our visuo-moto control model incorporates a delay parameter, the value of which was estimated from the data. In addition, correlations indicated that the knee and elbow were generally quite tightly coupled. The relationship of this task to laboratory tracking tasks and to the timing of actions in everyday life is described.
Who Benefits—Or Does not—From South Africa’s Old Age Pension? Evidence from Characteristics of Rural Pensioners and Non-Pensioners

Social protection grants play a critical role in survival and livelihoods of elderly individuals in South Africa. Rarely is it possible to assess how well a social program reaches its target population. Using a 2010 survey and Agincourt Health Demographic Surveillance System census data we conduct multivariate logistic regression to predict pension receipt in rural South Africa. We find only 80% of age-eligible individuals report pension receipt. Pension non-recipients tend to be male, have poor socio-economic status, live in smaller households, be of Mozambican origin, and have poorer physical function; while older persons living in households receiving other grants are more likely to report pension receipt. We conclude that a reservoir of older persons exists who meet eligibility criteria but who are not yet receiving pensions. Ensuring that they and their households are properly linked to all available social services—whether for child or old-age social grants—is likely to have beneficial and synergistic effects.
Rapid Determination of the Bacterial Composition of Commercial Probiotic Products by Terminal Restriction Fragment Length Polymorphism Analysis

Label claims on probiotic products often do not represent the true constituents. With the increased use of probiotics in clinical studies, it is necessary to know the true composition of probiotic products to better interpret study outcomes. We used terminal restriction fragment length polymorphism analysis to rapidly determine the overall bacterial composition of 14 commercial probiotic products and validated the results with species-specific polymerase chain reaction. The results show that many probiotic products contain unadvertised additional lactobacilli and bifidobacteria, whereas others are missing species listed on the product label. In summary, terminal restriction fragment length polymorphism is a rapid method for profiling the microbial contents of probiotic products used in clinical studies.
The contextual nature of the market orientation and organisational performance relationship: an Australian and New Zealand study

As part of a broader study of the relationship between traditional and online marketing mix elements and organisational performance, the study reported in this paper utilised structural equation modelling to examine the relationship between market orientation and organisational performance. The study found that there was an insignificant relationship between market orientation and organisational performance, thereby lending support to studies conducted in the UK, Ghana, and the US (since the studies in the US by Narver and Slater (1990)), which found that there may be a contextual nature to the relationship between the two constructs. The study, therefore, does not support Pulendran et al. (2000).
Context-aware intentional service framework for service adaptation

Intentional-based approaches aim at fulfilling user's requirements in order to facilitate his interaction with information systems. Those approaches take into account the user's goals and try to select the appropriate service based on it. However, nowadays, users are constantly moving and the context in which they interact with an information system changes from a situation to another. By consequence, user's intentions may vary according to his current context. Actually, the user's context can influence the service selection process, a service being more appropriate in a given situation then another one. Therefore, with the growth of the new technologies, we need to build reactive and proactive systems that take into account user's goals in ubiquitous environment. In order to provide dynamic adaptation of intentional services on ubiquitous environments, we propose in this paper, a context-aware intentional framework for a personalized service adaptation. In this framework, we propose to keep a trace of the user's context and past intentions in order to support a proactive selection of services. This is done through a set of interconnected models, namely context model and user's behavior schema, which are explored by a rule-based system allowing the dynamic selection of services.
On anonymizing social network graphs

The proliferation of social networks as a means of seamless communication between multiple parties across vast geographical distances has driven an increased interest from government organizations and companies. Government organizations typically seek access to these pools of personal data for statistical purposes while companies tend to look at this data from a marketing perspective. Users typically post information containing personal data during social network interactions with other users because the aim is to share this information only with persons that are authorized to access the information. However, the growing desire to exploit this information for statistical and marketing purposes, for instance, raises the question of privacy. It is therefore increasingly important to come up with ways of anonymizing personal data in order to circumvent privacy violations. Previous work has focused on two major approaches to anonymizing data namely, clustering and graph modifications. Both techniques aim to preserve the utility of the data for analysis and keep the identities of the users secret. We postulate however, that both approaches are in fact vulnerable to privacy violations and so do not enforce the property of anonymity. In addition, we argue that this problem is in fact NP-Hard and that the difficulty is in identifying as well as anonymizing all the possible channels that might leak information about a person's true identity.
Fabricating translucent materials using continuous pigment mixtures

We present a method for practical physical reproduction and design of homogeneous materials with desired subsurface scattering. Our process uses a collection of different pigments that can be suspended in a clear base material. Our goal is to determine pigment concentrations that best reproduce the appearance and subsurface scattering of a given target material. In order to achieve this task we first fabricate a collection of material samples composed of known mixtures of the available pigments with the base material. We then acquire their reflectance profiles using a custom-built measurement device. We use the same device to measure the reflectance profile of a target material. Based on the database of mappings from pigment concentrations to reflectance profiles, we use an optimization process to compute the concentration of pigments to best replicate the target material appearance. We demonstrate the practicality of our method by reproducing a variety of different translucent materials. We also present a tool that allows the user to explore the range of achievable appearances for a given set of pigments.
Medical diagnosis support and accuracy improvement by application of total scoring from feature selection approach

Melanoma is the most deadly form of skin cancer. Early detection and successful treatment of this disease often is possible. The main goal of this paper is to present results of application of feature selection method to find the most important or all important features that characterize melanocytic spots on the skin and in this way defining of a new Total Dermatoscopy Score formula. Thus, it is possible to decrease dimensionality of that problem. Results gathered during research focus on about six from thirteen descriptive attributes which are the most relevant and are stated as core attributes. Based on these attributes a simple total scoring method could be applied to improve prediction (diagnosis) results, additionally also reducing complexity of problem. Results were acquired by application of six different machine learning algorithms and estimated using several evaluation measures.
Markov random fields for pattern extraction in analog wafer test data

In semiconductor industry it is of paramount importance to check whether a manufactured device fulfills all quality specifications and is therefore suitable for being sold to the customer. The occurrence of specific spatial patterns within the so-called wafer test data, i.e. analog electric measurements, might point out on production issues. However, the shape of these critical patterns is unknown. In this paper different kinds of process patterns are extracted from wafer test data by an image processing approach using Markov Random Field models for image restoration. The goal is to develop an automated procedure to identify visible patterns in wafer test data to improve pattern matching. This step is a necessary precondition for a subsequent root-cause analysis of these patterns. The developed pattern extraction algorithm yields a more accurate discrimination between distinct patterns, resulting in an improved pattern comparison than in the original dataset. In a next step pattern classification will be applied to improve the production process control.
Give Agents Some REST: A Resource-oriented Abstraction Layer for Internet-scale Agent Environments

In this paper, we claim that the World Wide Web provides a suitable middleware for Internet-scale, open, and human-centric multi-agent systems. The novelty of our approach is to design the agent environment as a hypermedia application. We apply REST, the architectural style of the Web, to introduce a resource-oriented abstraction layer that decouples the application environment from its deployment context. Higher-level environment abstractions can then be implemented on top of this lower-level abstraction layer. To demonstrate our approach, we implemented a multi-agent application for the Internet of Things in which software agents can seamlessly navigate, use, and cooperate in an environment deployed over multiple Web services (e.g., Facebook, Twitter) and constrained devices.
Data Mining Applications for Space Mission Operations System Health Monitoring

Recent developments in data mining techniques for anomaly detection make it possible to use the wealth of available archived spacecraft system data to produce advanced system health monitoring applications. These “data driven” applications are capable of characterizing and monitoring interactions between multiple parameters and can complement existing practice to provide valuable decision support for mission controllers. Data driven software tools, including Orca and the Inductive Monitoring System (IMS), have been successfully applied to mission operations for both the Space Shuttle and the International Space Station. Orca uses a nearest-neighbor approach to search for unusual data points in multivariate data sets by calculating the distance of each data point from neighboring points. The IMS tool uses a data mining technique called clustering to analyze archived spacecraft data and characterize nominal interactions between selected parameters. This characterization, or model, is compared with real time or archived system data to detect off nominal behavior. Augmenting traditional mission control software with advanced monitoring tools, such as Orca and IMS, can provide controllers with greater insight into the health and performance of the space systems under their watch. We will describe how such techniques have been applied to NASA mission control operations and discuss plans for future mission control system health monitoring software.