Miracle-dz/UniFAR-FTUs huggingface dataset:
Balancing the Substantive with the Political Agenda: A Case Study.

This paper presents findings of a case study that examined the influences that shaped an Ohio governor's education reform proposals from a vantage point inside the governor's office, during the late 1980s. Data were obtained through document analysis (of the period from fall 1987 to January 1989), interviews with the governor, and a literature review. Three theoretical frameworks are used to analyze the governor's agenda-setting actions: Light's (1991) analysis of policy costs; Ripley and Franklin's (1980) concept of the subgovernment; and Kingdon's (1984) policy windows. Under the headings of "credit versus content" and "credibility versus control," several conclusions are made. First, policy entrepreneurs who are ready with reform proposals when the policy window opens are likely to get their proposals enacted. Second, the following outcomes are likely when the iron triangle of subgovernment is broken: Education representatives have no more credibility than anyone else; they may have less credibility; nobody is completely in control; and politicians know how to jump ahead of the process and look like leaders. Two tables are included. (LKI) ****************w****************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** Balancing the Agenda BALANCING THR SUBSTANTIVE WITH THE POLITICAL AGENDA: A CASE STUDY Carla Edlefson College of Education The Ohio State University Paper presented to the annual meeting of the Univerisity Council on Educational Administration Houston, Texas
From Dataflow Specification to Multiprocessor Partitioned Time-triggered Real-time Implementation

Our objective is to facilitate the development of complex time-triggered systems by automating the allocation and scheduling steps. We show that full automation is possible while taking into account the elements of complexity needed by a complex embedded control system. More precisely, we consider deterministic functional specifications provided (as often in an industrial setting) by means of synchronous data-flow models with multiple modes and multiple relative periods. We first extend this functional model with an original real-time characterization that takes advantage of our time-triggered framework to provide a simpler representation of complex end-to-end flow requirements. We also extend our specifications with additional non-functional properties specifying partitioning, allocation, and preemptability constraints. Then, we provide novel algorithms for the off-line scheduling of these extended specifications onto partitioned time-triggered architectures a la ARINC 653. The main originality of our work is that it takes into account at the same time multiple complexity elements: various types of non-functional properties (real-time, partitioning, allocation, preemptability) and functional specifications with conditional execution and multiple modes. Allocation of time slots/windows to partitions can be fully or partially provided, or synthesized by our tool. Our algorithms allow the automatic allocation and scheduling onto multi-processor (distributed) systems with a global time base, taking into account communication costs. We demonstrate our technique on a model of space flight software system with strong real-time determinism requirements.
Generating mimicry attacks using genetic programming: A benchmarking study

Mimicry attacks have been the focus of detector research where the objective of the attacker is to generate multiple attacks satisfying the same generic exploit goals for a given vulnerability. In this work, multi-objective Genetic programming is used to establish a “black-box” approach to mimicry attack generation. No knowledge is made of internal data structures of the target anomaly detector, only the anomaly rate reported by the detector. Such a “black box” methodology enables a vulnerability testing approach where both open-source and commodity anomaly detection systems can be tested. The approach successfully identifies exploits when benchmarked over four detectors and four applications.
Categorization of Unstructured Web Data Using Fuzzy Clustering

--The World Wide Web has huge amount of information that is retrieved using information retrieval tool like Search Engine. Page repository of Search Engine contains the web documents downloaded by the crawler. This repository contains variety of web documents from different domains. It becomes tedious for the user to manually extract real required information from this material. The detection of common and distinctive topics within a document set, together with the generation of multi-document summaries, can greatly ease the burden of information management. Cluster analysis divides objects into meaningful groups based on similarity between objects. Copious material is available from the World Wide Web (WWW) in response to any user-provided query. In the dissertation, a technique is proposed called Mining Unstructured Data From Web Using Soft Computing that creates the clusters of web documents using fuzzy clustering which focuses on this problem of mining the useful information from the collected web documents
A Novel On-Road Object Detection Approach Based on Vision

This paper proposed a simple and novel approach for on-road object detection based on vision. Firstly, a simple method is applied to detect the interest pixels of object in images by the defined interest pixels function and a single strategy is applied to reduce the redundant computation in the process of computation gray mean of pixels in squared window; Secondly, all the detected interest pixels neighbored each other are grouped to object interest region; after that, the non-interest pixels in are set to interest pixels and the images are binarized; The binary images could be easily segmented applying simple contour tracking algorithms. Lastly, several images captured from ITS or ALV system are used to test the proposed algorithm, the result indicate that the approach is valid and feasible.
An energy efficient circuit level technique to protect register file from MBUs and SETs in embedded processors

This paper presents a circuit level soft errortolerant- technique, called RRC (Robust Register Caching), for the register file of embedded processors. The basic idea behind the RRC is to effectively cache the most vulnerable registers in a small highly robust register cache built by circuit level SEU and SET protected memory cells. To decide which cache entry should be replaced, the average number of read operations during a register ACE time is used as a criterion to judge. In fact, the victim cache entry is one which has the maximum read count. To minimize the power overhead of the RRC, the clock gating technique is efficiently exploited for the main register file resulting in significantly low power consumption. The RRC is able to protect the register file not only against Single Bit Upsets (SBUs) but also against Multiple Bit Upsets (MBUs) and Single Event Transients (SETs). The RRC is experimentally evaluated using the LEON processor. The experimental results show that, if the cache size is selected properly, the Architectural Vulnerability Factor (AVF) of the register file becomes about 1% while it imposes low power, area and performance overheads to the processor.
A space-time constant modulus algorithm for SDMA systems

We consider the problem of blind recovery of p synchronous i.i. d. communication signals that are transmitted through a linear spatio-temporal channel and captured by an m-element array. Such a situation may arise for example in a space-division-multiple-access (SDMA) mobile communication system. We propose an approach of the constant-modulus (CM) type in order to construct optimization criteria that may allow joint blind recovery of the transmitted signals with low computational complexity. Several aspects of the proposed algorithms related to their convergence and implementation are discussed and computer simulations are provided as experimental evidence to the algorithms' performance.
The inactivation of RNase G reduces the Stenotrophomonas maltophilia susceptibility to quinolones by triggering the heat shock response

Quinolone resistance is usually due to mutations in the genes encoding bacterial topoisomerases. However, different reports have shown that neither clinical quinolone resistant isolates nor in vitro obtained Stenotrophomonas maltophilia mutants present mutations in such genes. The mechanisms so far described consist on eﬄux pumps’ overexpression. Our objective is to get information on novel mechanisms of S. maltophilia quinolone resistance. For this purpose, a transposon-insertion mutant library was obtained in S. maltophilia D457. One mutant presenting reduced susceptibility to nalidixic acid was selected. Inverse PCR showed that the inactivated gene encodes RNase G. Complementation of the mutant with wild-type RNase G allele restored the susceptibility to quinolones. Transcriptomic and real-time RT-PCR analyses showed that several genes encoding heat-shock response proteins were expressed at higher levels in the RNase defective mutant than in the wild-type strain. In agreement with this situation, heat-shock reduces the S. maltophilia susceptibility to quinolone. We can then conclude that the inactivation of the RNase G reduces the susceptibility of S. maltophilia to quinolones, most likely by regulating the expression of heat-shock response genes. Heat-shock induces a transient phenotype of quinolone resistance in S. maltophilia.
A Whole-Genome Analysis of a Transgenic Rice Seed-Based Edible Vaccine Against Cedar Pollen Allergy

Genetic modification (GM) by Agrobacterium-mediated transformation is a robust and widely employed method to confer new traits to crops. In this process, a transfer DNA is delivered into the host genome, but it is still unclear how the host genome is altered by this event at single-base resolution. To decipher genomic discrepancy between GM crops and their host, we conducted whole-genome sequencing of a transgenic rice line OSCR11. This rice line expresses a seed-based edible vaccine containing two major pollen allergens, Cry j 1 and Cry j 2, against Japanese cedar pollinosis. We revealed that genetic differences between OSCR11 and its host a123 were significantly less than those between a123 and its precedent cultivar Koshihikari. The pattern of nucleotide base substitution in OSCR11, relative to a123, was consistent with somaclonal variation. Mutations in OSCR11 probably occurred during the cell culture steps. In addition, strand-specific mRNA-Seq revealed similar transcriptomes of a123 and OSCR11, supporting genomic integrity between them.
Mining commonalities and variabilities from natural language documents

A company who wishes to enter an established marked with a new, competitive product is required to analyse the product solutions of the competitors. Identifying and comparing the features provided by the other vendors might greatly help during the market analysis. However, mining common and variant features of from the publicly available documents of the competitors is a time consuming and error-prone task. In this paper, we suggest to employ a natural language processing approach based on contrastive analysis to identify commonalities and variabilities from the brochures of a group of vendors. We present a first step towards a practical application of the approach, in the the context of the market of Communications-Based Train Control (CBTC) systems.
Missing Teeth Predict Incident Cardiovascular Events, Diabetes, and Death

Periodontitis, the main cause of tooth loss in the middle-aged and elderly, associates with the risk of atherosclerotic vascular disease. The objective was to study the capability of the number of missing teeth in predicting incident cardiovascular diseases (CVDs), diabetes, and all-cause death. The National FINRISK 1997 Study is a Finnish population–based survey of 8,446 subjects with 13 y of follow-up. Dental status was recorded at baseline in a clinical examination by a trained nurse, and information on incident CVD events, diabetes, and death was obtained via national registers. The registered CVD events included coronary heart disease events, acute myocardial infarction, and stroke. In Cox regression analyses, having ≥5 teeth missing was associated with 60% to 140% increased hazard for incident coronary heart disease events (P < 0.020) and acute myocardial infarction (P < 0.010). Incident CVD (P < 0.043), diabetes (P < 0.040), and death of any cause (P < 0.019) were associated with ≥9 missing teeth. No association with stroke was observed. Adding information on missing teeth to established risk factors improved risk discrimination of death (P = 0.0128) and provided a statistically significant net reclassification improvement for all studied end points. Even a few missing teeth may indicate an increased risk of CVD, diabetes, or all-cause mortality. When individual risk factors for chronic diseases are assessed, the number of missing teeth could be a useful additional indicator for general medical practitioners.
An Empirical Investigation into Factors Influencing the Intention to Use E -learning System: An Extended Technology Acceptance Model

Aims :The aim of this research is to investigate the factors affecting the intention towards using e-learning in a Jordanian universi ty, through an extension of the technology acceptance model (TAM). Place and Duration of Study:Amman University College between May and July 2013. Study Design: Adapted theoretical framework. This study incorporates perceived system quality and perceivedself-efficacy into the TAM model in order to investigate the role of perceived system quality and perceived self
Convergence of Children’s Depression Rating Scale-revised Scores and Clinical Diagnosis in Rating Adolescent Depressive Symptomatology

The Children’s Depression Rating Scale-Revised (CDRS-R) is a widely used instrument for research on depression in minors. A raw score of ≥40 has often been used as indicator of depressive symptomatology. As a validated German version of the CDRS-R has recently became available, we assessed CDRS-R raw summary scores of a video taped interview session in two different rater groups and compared them with clinical ratings of International Classification of Diseases (ICD-10) depression diagnosis as observed by a third independent group. We found that for the German version a raw score between 35 and 40 is indicative for mild depressive symptomatology as described by the ICD-10. CDRS-R scores show potential clinical applicability to deduct levels of depression.
Intermediate depth warming in the tropical Atlantic related to weakened thermohaline circulation: Combining paleoclimate data and modeling results for the last deglaciation

[1] Benthic foraminiferal oxygen isotope ratios from two sediment cores recovered at 426 and 1299 m water depth in the eastern and western tropical Atlantic show that a slowdown of the thermohaline circulation (THC) during Heinrich event H1 and the Younger Dryas was accompanied by rapid and intense warming of intermediate depth waters. Millennial-scale covariations of low paleosalinities in the subpolar North Atlantic with decreased benthic oxygen isotope ratios in the eastern tropical Atlantic throughout the past 10,000 years suggest that THC weakening might be related to middepth warming during the Holocene period as well. Climate model experiments simulating a strong reduction of the THC in the Atlantic Ocean under present-day and glacial conditions reveal that the increase of temperature in the middepth tropical and South Atlantic is a common feature for both climatic states, caused by a reduced ventilation of cold intermediate and deep waters in conjunction with downward mixing of heat from the thermocline. From the similarity of the paleoclimatic records with the model simulations, we infer that the characteristic pattern of temperature change in the Atlantic Ocean related to weakened thermohaline circulation can serve as an indicator of present-day and future THC slowdown.
The transition to conservation agriculture: an insularization process towards sustainability

Part of the Sustainability Transition Studies, this work addresses the question of the relationship between niches and regimes by examining the transition to conservation agriculture. It seeks to understand how farmers’ transition to conservation agriculture can contribute to a better understanding of the transition of agro-food systems towards sustainability. Based on an analysis of farmers’ trajectories in the Walloon region in Belgium, the paper develops the notion of insularization in order to characterize the emergence of conservation agriculture as a niche that is a dynamic process, growing from within and progressively detaching itself from the conventional agricultural regime. The analysis of farmers’ transition shows how, after an initial phase of destabilization of the conventional ploughing regime, learning and experiencing processes can lead to a transformation in soil and soil quality management perceptions. Our hypothesis is that this cognitive transformation constitutes a tipping point in the insularization process because of its effects on agricultural practices, which increase the detachment of conservation agriculture from the regime and thus embed the irreversibility and sustainability of the transition. Insularization describes an ecologizational pathway of agricultural practices endogenous to the regime that can not only lead to adaptive changes on the periphery of the system, but might also induce a deep and systemic transformation of conventional agricultural practices.
Enrollment and Registration Behaviors as Predictors of Academic Outcomes for Full -Time Students in a Rural Community College

This study investigates the relationships among community college student characteristics, student enrollment and registration behaviors, and academic outcomes. The report examines whether there are interrelationships among the enrollment and registration behaviors studied and interrelationships among the academic outcomes studied. Also it investigates if enrollment and registration behaviors can predict student academic outcomes. The report investigates five student characteristic variables: age, gender, ethnicity, academic intent, and financial aid eligibility. Five enrollment and registration (predictor) variables were also studied: when students enrolled, number of changes made to their course schedule, how many schedule changes were drops and how many were adds, and when changes were made. It explores three outcomes: fall semester grade point average, fall semester course completion, and attrition (whether the students enrolled for the spring semester). Significant relationships were found between several student characteristics and enrollment and registration behaviors. Significant interrelationships among the enrollment and registration behaviors and academic outcomes were found. A combination of four enrollment and registration behaviors could predict 37.6% of the variation in fall semester GPA and 48.6% of the variation in course completion. A combination of three enrollment and registration behaviors was included in a model that could best predict the odds of attrition. A combination of three enrollment and registration behaviors could predict 13.7% of the variation in GPA beyond the 10.3% predicted by student characteristics. A combination of four enrollment and registration behaviors could predict 43.9% of the variation in course completion beyond the 10.3% predicted by student characteristics. (VWC) Reproductions supplied by EDRS are the best that can be made from the original document. The 42nd Annual Conference of the Council for the Study of Community Colleges April 7, 2000 Washington, D.C. Enrollment and Registration Behaviors as Predictors of Academic Outcomes for Full-Time Students in a Rural Community College
A single stage solar PV array based water pumping system using SRM drive

The present paper describes the solution for cost effective and efficient single stage photovoltaic (PV) generator powered water pumping using a Switched Reluctance motor (SRM). An optimal selection of a perturbation size (ΔD) and an initial duty ratio (D) in incremental conductance (IC) MPPT (Maximum Power Point Tracking) algorithm facilitate soft starting to SRM by building up the voltage across split capacitors of a SRM converter with a reduced rate. The speed of SRM drive is controlled by output maximum power point (MPP) current of PV array. This avoids the current and voltage sensors on motor side. The proposed single stage system is operated under pulse width modulation (PWM) switching of a mid-point converter and gives privileged to reduce the bulky DC link split capacitors with small capacitors. A turn- off angle dependent control algorithm to self start a proposed SRM drive is also introduced in present system. Moreover, the present paper also discussed the details of system design and analysis of its performance under varying environmental conditions. The suitability of proposed system is validated using MATLAB simulation and test results on a hardware prototype.
New angular competition index and tree crown projection model

Tree architecture plasticity enables individuals to maximize filling of the available space and minimize the competition effect; tree crowns can be distributed more regularly than stem bases. We conducted a study in a temperate mixed forest (Krakow, Poland) to test the idea of a new angular competition index (CI) and its application in modeling crown radii (CR) and crown projections (CPs) of 30 Quercus robur trees. The statistical method used was random forest algorithm. The model allows the prediction of the CP shape on the basis of stem spatial distribution and diameter, measurement of two CR per target tree and local topography; it can be used to compare the inter- and intra-specific architectural plasticity of the canopy trees.
Potential limits to anthropogenic mortality for harbour porpoises in the Baltic region

We estimated potential limits to anthropogenic mortality for harbour porpoises in the Baltic region (the Skagerrak, Kattegat, Great Belt and Little Belt Seas, the Kiel and Mecklenburg Bights, and the Baltic Sea) using conservation objectives set by the Agreement on the Conservation of Small Cetaceans in the Baltic and North Seas (ASCOBANS). Mortality limits (ML) were calculated as the product of: a minimum estimate of abundance, one-half the maximum rate of increase and an uncertainty factor. Previous models show that if anthropogenic mortality is less than ML, a depleted population should recover to more than 80% of carrying capacity, meeting the conservation objectives of ASCOBANS. Minimum estimates of by-catches exceed ML for the population structure hypothesis tested, indicating that these catches will impede recovery. The same result was also evident for other hypothetical population structures. We conclude that immediate management actions are necessary to reduce the magnitude of by-catches to meet the conservation objectives of ASCOBANS. # 2001 Elsevier Science Ltd. All rights reserved.
MARKET ACTIVITY AND VOLATILITY IN THE EURO / DOLLAR FOREIGN EXCHANGE MARKET

This paper deals with the impact of nine categories of scheduled and unscheduled news announcements on the Euro/Dollar return volatility. We highlight and analyze the pre-announcement, contemporaneous and postannouncement reactions. Using high-frequency intraday data and within the framework of ARCH-type and realized volatility models, we show that volatility increases in the pre-announcement periods, particularly before scheduled events. Market activity also significantly impacts return volatility as expected by the theoretical literature on order flow.