Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing School Based Decision Making Capacities in Kentucky: Communication Satisfaction after the Pilot Year

Among several innovations in public school curriculum and financing, the 1990 Kentucky Education Reform Act (KERA) also included a school-governance provision. School-Based Decision Making (SBDM) Councils include administrators, teachers, and parents in addressing school-level curriculum and instructional issues. These groups have not had a history of collaboration. This paper presents findings of a study that described the developing relationships among these constituent groups at the end of the pilot year. Data were derived from a survey that asked 385 pilot-year School Council members to rate their satisfaction with council communication on a Likert-type inventory. Usable responses were received from 211 members (approximately one-third principals, one-third parents, and one--third teachers) for a response rate of 55 percent. In general, res? ondents were optimistic about the potential of School Courcils. However, principals tended to express the most satisfaction. Older members and those with no children in school also tended to report higher levels of satisfaction with communication. Five tables are included. (LMI) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** U.S. DEPARTMENT OF EDUCATION Off.ce of Educahonal ReaftatCh and Improvement "PERMISSION TO REPRODUCE THI`. ; MATERIAL HAS BEEN GRANTED BY EDUCATIONAL RESOURCES INFORMATION CENTER (ERICi Ta.s document has been reproduced as ece'ved Iron, Itte de5On Or OlgentialiOn on.naltnct tt C Nfirtor changes nave Ueert made lo .Intarave reproduction oLtat.ty punts 01 vet* or op.rtt.nns staled . nibs dOCu vent no not neCeSSal.ty ectesenl offic.at OF RI positior pi policy TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC). " DEVELOPING SCHOOL BASED DECISION MAKING CAPACITIES IN KENTUCKY: COMMUNICATION SATISFACTION AFTER THE PILOT YEAR by Jane Clark Lindle, Ph.D. Department of Administration and Supervision College of Education University of Kentucky This research was funded through a special grant from the Office of the ViceChancellor for Research and Graduate Studies with assistance from the University of Kentucky's College -if Education's Institute on Educational Reform and the Kentucky Department of Education, Division for School Based Decision Making. The opinions expressed by the author do not necessarily represent official policy or positions of the Office of the Vice-Chancellor for Research and Graduate Studies, the University of Kentucky, the College of Education's Institute on Educational Reform, the Kentucky Department of Education, or the Division for School Based Decision Making.
The extended regulatory networks of SXT/R391 integrative and conjugative elements and IncA/C conjugative plasmids

Nowadays, healthcare systems are challenged by a major worldwide drug resistance crisis caused by the massive and rapid dissemination of antibiotic resistance genes and associated emergence of multidrug resistant pathogenic bacteria, in both clinical and environmental settings. Conjugation is the main driving force of gene transfer among microorganisms. This mechanism of horizontal gene transfer mediates the translocation of large DNA fragments between two bacterial cells in direct contact. Integrative and conjugative elements (ICEs) of the SXT/R391 family (SRIs) and IncA/C conjugative plasmids (ACPs) are responsible for the dissemination of a broad spectrum of antibiotic resistance genes among diverse species of Enterobacteriaceae and Vibrionaceae. The biology, diversity, prevalence and distribution of these two families of conjugative elements have been the subject of extensive studies for the past 15 years. Recently, the transcriptional regulators that govern their dissemination through the expression of ICE- or plasmid-encoded transfer genes have been described. Unrelated repressors control the activation of conjugation by preventing the expression of two related master activator complexes in both types of elements, i.e., SetCD in SXT/R391 ICEs and AcaCD in IncA/C plasmids. Finally, in addition to activating ICE- or plasmid-borne genes, these master activators have been shown to specifically activate phylogenetically unrelated mobilizable genomic islands (MGIs) that also disseminate antibiotic resistance genes and other adaptive traits among a plethora of pathogens such as Vibrio cholerae and Salmonella enterica.
Text Knowledge Engineering by Qualitative Terminological Learning Text Knowledge Engineering by Qualitative Terminological Learning Text Knowledge Engineering by Qualitative Terminological Learning

We propose a methodology for enhancing domain knowledge bases through natural language text understanding. The acquisition of previously unknown concepts is based on the assessment of the \quality" of linguistic and conceptual evidence underlying the generation and reenement of concept hypotheses. Text understanding and concept learning are both grounded on a terminological knowledge representation and reasoning framework. Abstract. We propose a methodology for enhancing domain knowledge bases through natural language text understanding. The acquisition of previously unknown concepts is based on the assessment of the \qual-ity" of linguistic and conceptual evidence underlying the generation and reenement of concept hypotheses. Text understanding and concept learning are both grounded on a terminological knowledge representation and reasoning framework.
Inter-industry Wage Differentials: How Much Does Rent Sharing Matter?

This paper investigates inter-industry wage differentials in Belgium, taking advantage of access to a unique matched employer-employee data set covering all the years from 1999 to 2005. Findings show the existence of large wage differentials among workers with the same observed characteristics and working conditions, employed in different sectors. These differentials are persistent and no particular downward or upward trend is observed. Further results indicate that ceteris paribus, workers earn significantly higher wages when employed in more profitable firms. The time dimension of our matched employer-employee data allows us to instrument firms' profitability by its lagged value. The instrumented elasticity between wages and profits is found to be quite stable over time and varies between 0.034 and 0.043. It follows that Lester’s range of pay due to rent sharing fluctuates between about 24 and 37 percent of the mean wage. This rent-sharing phenomenon accounts for a large fraction of the industry wage differentials. We find indeed that the magnitude, dispersion and significance of industry wage differentials decreases sharply when controlling for profits.
Repetitive Transcranial Magnetic Stimulation of Motor Cortex after Stroke: A Focused Review

ABSTRACT Repetitive Transcranial Magnetic Stimulation (rTMS) is known to modulate cortical excitability and has thus been suggested to be a therapeutic approach for improving the efficacy of rehabilitation for motor recovery after stroke. In addition to producing effects on cortical excitability, stroke may affect the balance of transcallosal inhibitory pathways between motor primary areas in both hemispheres: the affected hemisphere (AH) may be disrupted not only by the infarct itself but also by the resulting asymmetric inhibition from the unaffected hemisphere, further reducing the excitability of the AH. Conceptually, therefore, rTMS could be used therapeutically to restore the balance of interhemispheric inhibition after stroke. rTMS has been used in two ways: low-frequency stimulation (⩽1 Hz) to the motor cortex of the unaffected hemisphere to reduce the excitability of the contralesional hemisphere or high-frequency stimulation (>1 Hz) to the motor cortex of the AH to increase excitability of the ipsilesional hemisphere. The purpose of this systematic review is to collate evidence regarding the safety and efficacy of high-frequency rTMS to the motor cortex of the AH. The studies included investigated the concurrent effects of rTMS on the excitability of corticospinal pathways and upper-limb motor function in adults after stroke. This review suggests that rTMS applied to the AH is a safe technique and could be considered an effective approach for modulating brain function and contributing to motor recovery after stroke. Although the studies included in this review provide important information, double-blinded, sham-controlled Phase II and Phase III clinical trials with larger sample sizes are needed to validate this novel therapeutic approach.
Modular body of the multi arm snake-like robot

The goal in minimally-invasive surgery like NOTES (natural orifice transluminal endoscopic surgery), or single-port surgery, through one artificial incision, is to reduce the operative and post-operative stresses for the patients. Today's challenges for physicians during procedures are the missing mobility of the used flexible instruments inside the human body. Primarily the missing ability to manipulate tissue from different sides (triangulation of instruments) needs to be obtained. This article proposes the next prototype of our Multi Arm Snake-Like Robot and focuses on the kinematic development of the overtube body-frame for the flexible endoscope. We are following a new way developing a system for minimally- invasive surgery by using additive manufacturing methods like selective laser sintering (SLS). By using SLS it is feasible to create stiff structures with local flexure hinges monolithically that are custom made adapted for different patients and surgeries. To adapt our systems to different standard endoscopic equipment, procedures and patients we use a unique puzzle-clip mechanism. In the experiment the modularization of the system through the puzzle-clip system is shown. The used raw material PA 2200, a polyamide based thermoplastic polymer, is certificated as biocompatible according to DIN EN ISO 10993. This proves that the proposed Multi Arm Snake-Like SLS Robot system gets more advances towards the use during minimally-invasive procedures. And has a high chance to reach the final goal the clinical certification.
A Corticotropin Releasing Factor Pathway for Ethanol Regulation of the Ventral Tegmental Area in the Bed Nucleus of the Stria Terminalis

A growing literature suggests that catecholamines and corticotropin-releasing factor (CRF) interact in a serial manner to activate the bed nucleus of the stria terminalis (BNST) to drive stress- or cue-induced drug- and alcohol-seeking behaviors. Data suggest that these behaviors are driven in part by BNST projections to the ventral tegmental area (VTA). Together, these findings suggest the existence of a CRF-signaling pathway within the BNST that is engaged by catecholamines and regulates the activity of BNST neurons projecting to the VTA. Here we test three aspects of this model to determine: (1) whether catecholamines modify CRF neuron activity in the BNST; (2) whether CRF regulates excitatory drive onto VTA-projecting BNST neurons; and (3) whether this system is altered by ethanol exposure and withdrawal. A CRF neuron fluorescent reporter strategy was used to identify BNST CRF neurons for whole-cell patch-clamp analysis in acutely prepared slices. Using this approach, we found that both dopamine and isoproterenol significantly depolarized BNST CRF neurons. Furthermore, using a fluorescent microsphere-based identification strategy we found that CRF enhances the frequency of spontaneous EPSCs onto VTA-projecting BNST neurons in naive mice. This action of CRF was occluded during acute withdrawal from chronic intermittent ethanol exposure. These findings suggest that dopamine and isoproterenol may enhance CRF release from local BNST sources, leading to enhancement of excitatory neurotransmission on VTA-projecting neurons, and that this pathway is engaged by patterns of alcohol exposure and withdrawal known to drive excessive alcohol intake.
Valuation of a spark spread: an LM6000 power plant

This paper analyzes a power plant powered by two General Electric LM6000 gas turbines combined with a steam generator that allows combined cycle operations. We consider four distinct operating modes for the plant. Such a plant can be characterized as a real option on a spark spread: optimally converting natural gas to electricity. We use a Margrabe approach by using the market heat rate (the ratio of the electricity price to the natural gas price) as our underlying stochastic variable. We estimate a stochastic model for market heat rates that incorporates time of day, day of week, month, and the incidence or otherwise of a spike in heat rates. We use the model and its residuals in a bootstrap process simulating future market heat rates, and use a least-squares Monte Carlo approach to determine the optimal operating policy. We find that the annual average market heat rate is a good explanatory variable for the time integral of the plant operating margin, denominated in the natural gas numeraire. This allows us to express plant values in terms of the numeraire and convert to dollars by multiplying this by the natural gas forward curve and a forward curve of riskless discount rates. We also provide information about the optimal operating modes selected, the number of transitions between modes and how they relate to transition costs and the average heat rate for the year.
GRN model of probabilistic databases: construction, transition and querying

Under the tuple-level uncertainty paradigm, we formalize the use of a novel graphical model, Generator-Recognizer Network (GRN), as a model of probabilistic databases. The GRN modeling framework is capable of representing a much wider range of tuple dependency structure. We show that a GRN representation of a probabilistic database may undergo transitions induced by imposing constraints or evaluating queries. We formalize procedures for these two types of transitions such that the resulting graphical models after transitions remain as GRNs. This formalism makes GRN a self-contained modeling framework and a closed representation system for probabilistic databases - a property that is lacking in most existing models. In addition, we show that exploiting the transitional mechanisms allows a systematic approach to constructing GRNs for arbitrary probabilistic data at arbitrary stages. Advantages of GRNs in query evaluation are also demonstrated.
A communication kernel of a cluster system for distributed simulation

Parallel discrete event simulation (PDES) is a basic approach for evaluation of the complex systems. A PDES attempts to speed up the execution of a simulation by distributing the simulation's workload between multiple processors (DS). A network of workstations is a widely available platform for DS. This paper explores an implementation's details of a communication subsystem for DS. The techniques for reducing of interprocessor communication overload are presented.
Local integrity constraints for structure detection and segmentation in high-resolution earth observation images

Considering the idea that objects in images have a higher local structural integrity than the background they lie into, we propose a method that learns a supervised distance characterizing the membership of a pair of elements to the target structure. We test our ideas by applying them to the task of extracting semantic structures in high resolution Earth Observation images. The results show that the method works well in many situations when there is no training dataset. The limits of the method are also discussed.
Self-adaptive Ant Algorithm for Solving Real Estate Portfolio Optimization

As efficient methods of reducing the investment risks, the real estate portfolio optimization methods and models have some defects. The information entropy was used as the risk measuring index, and a self-adaptive ant algorithm with a changing index was proposed to overcome the deficiency of the basic ant algorithm. Then the improved algorithm was introduced into the real estate portfolio. And the application results indicated that this method has better convergence, stability and robustness in solving the combinatorial optimization problems.
ViCoMo: visual context modeling for scene understanding in video surveillance

Abstract. The use of contextual information can significantly aid scene understanding of surveillance video. Just detecting people and tracking them does not provide sufficient information to detect situations that require operator attention. We propose a proof-of-concept system that uses several sources of contextual information to improve scene understanding in surveillance video. The focus is on two scenarios that represent common video surveillance situations, parking lot surveillance and crowd monitoring. In the first scenario, a pan–tilt–zoom (PTZ) camera tracking system is developed for parking lot surveillance. Context is provided by the traffic sign recognition system to localize regular and handicapped parking spot signs as well as license plates. The PTZ algorithm has the ability to selectively detect and track persons based on scene context. In the second scenario, a group analysis algorithm is introduced to detect groups of people. Contextual information is provided by traffic sign recognition and region labeling algorithms and exploited for behavior understanding. In both scenarios, decision engines are used to interpret and classify the output of the subsystems and if necessary raise operator alerts. We show that using context information enables the automated analysis of complicated scenarios that were previously not possible using conventional moving object classification techniques.
Integration of spatial join algorithms for processing multiple inputs

Several techniques that compute the join between two spatial datasets have been proposed during the last decade. Among these methods, some consider existing indices for the joined inputs, while others treat datasets with no index, providing solutions for the case where at least one input comes as an intermediate result of another database operator. In this paper we analyze previous work on spatial joins and propose a novel algorithm, called slot index spatial join (SISJ), that efficiently computes the spatial join between two inputs, only one of which is indexed by an R-tree. Going one step further, we show how SISJ and other spatial join algorithms can be implemented as operators in a database environment that joins more than two spatial datasets. We study the differences between relational and spatial multiway joins, and propose a dynamic programming algorithm that optimizes the execution of complex spatial queries.
Precise and Efficient Call Graph Construction for C Programs with Function Pointers

The use of pointers presents serious problems for software productivity tools for software understanding, restructuring, and testing. Pointers enable indirect memory accesses through pointer dereferences, as well as indirect procedure calls (e.g., through function pointers in C). Such indirect accesses and calls can be disambiguated with pointer analysis. In this paper we evaluate the precision of one specific pointer analysis (the FA pointer analysis by Zhang et al.) for the purposes of call graph construction for C programs with function pointers. The analysis is incorporated in a production-strength code-browsing tool from Siemens Corporate Research in which the program call graph is used as a primary tool for code understanding. The FA pointer analysis uses an inexpensive, almostlinear, flowand context-insensitive algorithm. To measure analysis precision, we compare the call graph constructed by this analysis with the most precise call graph obtainable by a large category of existing pointer analyses. Surprisingly, for all our data programs the FA analysis achieves the best possible precision. This result indicates that for the purposes of call graph construction, even inexpensive pointer analyses may provide precision comparable to the precision of expensive pointer analyses, and therefore the use of more expensive analyses may be unnecessary.
Magnetic Nanomaterials and Their Applications

This Special Issue of Nanomaterials is dedicated to the development of new magnetic nanomaterials and their applications in biomedicine, catalysis, spintronics and other areas. The publications in this Issue demonstrate that the interest in magnetic nanomaterials is continuously growing and their realm is expanding rapidly. Some highlights of the publications in this issue are discussed below. [. ].
A Combined Clustering Scheme for Protecting Location Privacy and Query Privacy in Pervasive Environments

Privacy protection in pervasive environments has attracted great interests in recent years. Two kinds of privacy issues, location privacy and query privacy, are threatening the security of the users. In this paper, a novel combined clustering algorithm for protecting location privacy and query privacy, namely ECC, is proposed. ECC applies a iterative K-means clustering method to group the user requests into clusters for providing location safety while utilizing a hierarchical clustering method for preserving the query privacy. ECC provides the mobile users with their desired anonymity levels and spatial tolerances. Experimental results manifest that the ECC algorithm shows merits in shorter cloaking time and is able to preserve location privacy and query privacy in continuous location based services.
Tuning genetic algorithms for underwater acoustics using a priori statistical information

We present a new technique for the evaluation/selection procedures of genetic algorithms, to be used in the context of parameter estimation problems. The proposed algorithm uses a priori information about the structure of the surface of which an extremum is being searched. For parameter estimation problems, the availability, at each iteration of a genetic algorithm, of a collection of samples of the ambiguity surface of the problem, enables the determination of the correlation between the observed ambiguity surface (at the sampled points) and the predicted ambiguity surface. The consideration of this information allows early detection of secondary extrema (which yield an ambiguity surface which does not correlate well with the observed one) and thus contributes to speed the convergence of the algorithm to the global optimal values. The paper applies the proposed technique to a source localization problem.
Replication of an Egfr-Wing Shape Association in a Wild-Caught Cohort of Drosophila melanogaster

Linkage disequilibrium mapping has been used extensively in medical and evolutionary genetics to map causal polymorphisms within genes associated with disease status or phenotypic variation for a trait. However, the initial findings of most nonhuman studies have not been replicated in subsequent studies, due in part to false positives, as well as additional factors that can render true positives unreplicable. These factors may be more severe when the initial study is performed using an experimental population of organisms reared under controlled lab conditions. We demonstrate that despite considerable phenotypic differences for wing shape between a lab-reared experimental population and a wild-caught cohort of Drosophila melanogaster, an association between a putative regulatory polymorphism in Egfr and wing shape can be replicated. These results are discussed both within the framework of future association-mapping studies and within the context of the evolutionary dynamics of alleles in populations.