Miracle-dz/UniFAR-FTUs huggingface dataset:
Student Academic Self‐Concept and Perception of Classroom Environment in Single‐Sex and Coeducational Middle Grades Mathematics Classes

In this article, we present findings from a study that investigated the relationship between all-girls classes, all-boys classes, and coeducational classes on student mathematics self-concept and student perception of classroom environment. Further, we compared responses of girls in all-girls classes to girls in coeducational classes and responses of boys in all-boys classes to boys in coeducational classes. Using the Mathematics Attitude Scale and the What Is Happening in This Class? questionnaire, we found no significant differences in student responses on any of the subscales or domains for any of the subgroups, except for Math as a Male Domain. Our findings indicate that student mathematics self-concept and student perception of the classroom environment are similar regardless of whether students are in a single-sex or a coeducational class.
NEARLY INTEGRABLE SO(3) STRUCTURES ON 5-DIMENSIONAL LIE GROUPS

Recent work (5) on 5-dimensional Riemannian manifolds with an SO(3) struc- ture prompts us to investigate which Lie groups admit such a geometry. The case in which the SO(3) structure admits a compatible connection with torsion is considered. This leads to a classification under special behaviour of the connection, which enables to recover all known examples, plus others bearing torsion of pure type. Suggestive relations with spe- cial structures in other dimensions are highlighted, with attention to eight-dimensional SU(3) geometry.
Decision Support Systems And Unfiltered Information: Evidence From Conference Calls

Numerous financial decision support systems have been proposed in the literature that analyze corporate disclosures or financial news. However, these sources of corporate information are likely to be filtered before being published, either by investor relations departments or journalists. This bears the risk that the language is adapted to bias a decision support systems’ evaluations. Thus, unfiltered verbal communication should be a useful input for financial decision support systems since it is harder to manipulate. Using a sample of 200 earnings conference calls of German DAX firms, we analyze the relation of linguistic aspects of verbal management communication and the capital market reactions during the conference call. The results suggest that language aspects in the form of both sentiment and certainty assessments expressed by management influence the consequent capital market reaction. Our results show that unfiltered information released during conference calls is informative to the market and should therefore be considered as an input in decision support systems. As a consequence, these systems may profit from an increased robustness against impression management and from the possibility to react faster to new corporate information.
Developmental Status: Impact of Short-Term Ischemia on Follicular Survival of Whole Ovarian Transplantation in a Rabbit Model

Ischemia is the first mechanism that provokes the loss of follicles in ovarian grafts over the long term. In whole ovarian transplantation, it remains unknown, however, how changes in follicular development are influenced by short-term ischemia. Fresh whole ovarian orthotopic auto-transplantation was performed in rabbits with 45 min ischemia, and the impact of ischemia on follicular survival and development status was evaluated at different time-points (1 day, 3 days, 1 week, 2 weeks and 1 month). Assessment of follicular quantity and morphology was carried out via histologic analysis. Follicle proliferating status was evidenced by immunostaining with proliferating cell nuclear antigen (PCNA), and the Hedgehog signaling pathway (Patched and Gli); was verified via TUNEL assay. Quantitative PCR was carried out to quantify the mRNA of target genes including PCNA, Patched, Gli, Caspase 3, Bax, and Bcl-2. Compared with its contralateral fresh controls, the morphology, proliferation and apoptosis of the follicles in the grafts showed no significant differences and most primordial follicles were quiescent. However, morphology and proliferation status were significantly decreased 1 week after grafting, in comparison with the longitudinal grafting time. Patched and Gli in the Hedgehog signaling pathway were activated in only the follicles of the grafts. Short-term ischemia slightly impacts follicular survival and development status in whole ovarian grafting. Receiving intervention in the first week post-transplantation might be helpful.
Weak convergence of Metropolis algorithms for non-i.i.d. target distributions

In this paper, we shall optimize the efficiency of Metropolis algorithms for multidimensional target distributions with scaling terms possibly depending on the dimension. We propose a method for determining the appropriate form for the scaling of the proposal distribution as a function of the dimension, which leads to the proof of an asymptotic diffusion theorem. We show that when there does not exist any component with a scaling term significantly smaller than the others, the asymptotically optimal acceptance rate is the well-known 0.234.
A flexible automatic source-level instrumentation framework for dynamic program analysis

As programs become increasingly complex, tools for monitoring and performing dynamic analysis of running software are very much desirable. A flexible program source-level instrumentation framework is proposed in the paper. Unlike most of the existing tools, the proposed instrumentation framework has the ability to instrument for various events, the flexibility to instrument (or not to instrument) specific events and mechanisms to control instrumentation overhead, and it also provides convenience for applications to process the collected runtime instrumentation information for performing dynamic analysis. A prototype of this instrumentation framework is implemented and evaluated on the KLEE Symbolic Virtual Machine.
Complete Coverage D* Algorithm for Path Planning of a Floor-Cleaning Mobile Robot

Abstract Inspired by the path transform (PT) algorithm of Zelinsky et al. the novel algorithm of complete coverage called complete coverage D* (CCD*) algorithm is developed, based on the D* search of the two-dimensional occupancy grid map of the environment. Unlike the original PT algorithm the CCD* algorithm takes the robot's dimension into account, with emphasis on safety of motion and reductions of path length and search time. Additionally, the proposed CCD* algorithm has ability to produce new complete coverage path as the environment changes. The algorithms were tested on a Pioneer 3DX mobile robot equipped with a laser range finder.
Weighting Distributional Features for Automatic Semantic Classification of Words

The paper is concerned with weighting distributional features of words with the aim of improving their automatic semantic classification, a task relevant to a number of NLP applications such as lexicon acquisition or named entity recognition. The purpose of the paper is to bring attention to differences between two major weighting strategies: Discriminative Feature Weighting and Characteristic Feature Weighting. The comparative study includes three popular discriminative weighting functions (Mutual Information, Information Gain, and Gain Ratio), and three characteristic weighting functions (Term Strength, and the two newly introduced Local Term Strength and Confidence). We find that the two strategies, on the one hand, are characterized by their own optimal settings, and, on the other hand, similarly interact with the parameter optimization of the learning algorithm.
The Effect of Locally Delivered Doxycycline in the Treatment of Chronic Periodontitis. A Clinical and Microbiological Cohort Study

ABSTRACT Objectives To evaluate the efficacy of locally delivered doxycycline as an adjunct to non-surgical treatment with the use of an ultrasonic device compared to scaling and root planing using hand instruments, by means of clinical and microbiological criteria. Material and Methods Thirty three patients with chronic periodontitis participated in this cohort study and were divided into two groups. Patients in control group received scaling and root planing using hand instruments, whereas patients in control group received ultrasonic debridement and 8.8% doxycycline gel was applied after initial therapy and at 3 months at preselected sites. Clinical recordings concerning probing pocket depth, clinical attachment level, plaque index and gingival bleeding index were performed at baseline, 3 and 6 months after baseline. Subgingival samples were analysed using the "checkerboard" DNA-DNA hybridisation technique for Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola. Results Both treatments resulted in significant improvement in all clinical recordings. Six months after the treatment a statistically significant decrease was observed for Porphyromonas gingivalis in both of groups and Treponema denticola in the control group (P < 0.05). No inter-group differences were observed (P < 0.05). Conclusions Both treatment modalities provided comparable clinical and microbiological results in the treatment of chronic periodontitis.
Accuracy of Airborne Lidar-Derived Elevation: Empirical Assessment and Error Budget

As part of a countywide large-scale mapping effort for Richland County, South Carolina, an accuracy assessment of a recently acquired lidar-derived data set was conducted. Airborne lidar (2-m nominal posting) was collected at a flying height of 1207 meters above ground level (AGL) using an Optech ALTM (Airborne Laser Terrain Mapper) 1210 system. Unique to this study are the reference point elevations. Rather than using an interpolation approach for gathering observed elevations at reference points, the x-y coordinates of lidar points were located in the field and these elevations were surveyed. Using both total-station-based and rapid-static GPS techniques, observed vertical heights were measured at each reference lidar posting. The variability of vertical accuracy was evaluated for six land-cover categories. Root-meansquared error (RMSE) values ranged from a low of 17 to 19 cm (pavement, low grass, and evergreen forests) to a high of 26 cm (deciduous forests). The unique error assessment of lidar postings also allowed for the creation of an error budget model. The observed lidar elevation error was decomposed into errors from lidar system measurements, horizontal displacement, interpolation error, and surveyor error. A crossvalidation approach was used to assess the observed interpolated lidar elevation error for each field-verified reference point. In order of decreasing importance, the lidar system measurements were the dominant source of error followed by interpolation error, horizontal displacement error, and surveyor error. Observed elevation error in steeper slopes (e.g., 25°) was estimated to be twice as large as those on low slopes (e.g., 1.5°).
Algorithm of Two-Dimensional DOA Estimation for Correlative Signals

Estimation of Direction of Arrival (DOA) signal is one important function of adoptive antenna. The fuzzy angle in correlative signal environment of DOA estimation could seriously affect the estimation precision. Based on 1-D spatial smoothing theory the paper analyzes the algorithm for 2-D angle estimation in correlative source environment of hexagonal array and simulations were carried out. A method transforming the hexagonal array to two mutual-vertical sub arrays successfully applied spatial smoothing technique to 2-D angle estimation of hexagonal array. Simulation results shows that the transforming method can eliminate the fuzzy angle in coherent signal environment.
Emprical study on Reducing Energy of Parallel Programs using Slack Reclamation by DVFS in a Power-scalable High Performance Cluster

It has become important to improve the energy efficiency of high performance PC clusters. In PC clusters, high-performance microprocessors have a dynamic voltage and frequency scaling (DVFS) mechanism, which allows the voltage and frequency to be set for reduction in energy consumption. In this paper, we proposed a new algorithm that reduces energy consumption in a parallel program executed on a power-scalable cluster using DVFS. Whenever the computational load is not balanced, parallel programs encounter slack time, that is, they must wait for synchronization of the tasks. Our algorithm reclaims slack time by changing the voltage and frequency, which allows a reduction in energy consumption without impacting on the performance of the program. Our algorithm can be applied to parallel programs represented by a directed acyclic task graph (DAG). It selects an appropriate set of voltages and frequencies (called the gear) that allow the tasks to execute at the lowest frequency that does not increase the overall execution time, but at the same time allows the tasks to be executed as uniformly as possible in frequency. We built two different types of power-scalable clusters using AMD Turion and Transmeta Crusoe. For the empirical study on energy reduction in PC clusters, we designed a toolkit called PowerWatch that includes power monitoring tools and the DVFS control library. This toolkit precisely measures the power consumption of the entire cluster in real time. The experimental results using benchmark problems show that our algorithm reduces energy consumption by 25% with only a 1 % loss in performance
Robust Image Matching Preserving Global Consistency

We present a new method for detecting point matches between two images. The main issue is how to preserve the global consistency of individual matches. Existing methods propagate local smoothness by relaxation or do combinatorial search for an optimal solution. Our method imposes non-local constraints that should be approximately satisfied across the image. We define the “confidence” of such “soft constraints” to all potential matches. The confidence is progressively updated by “mean-field approximation”. Finally, the “hard” epipolar constraint is imposed by RANSAC. Using real images, we demonstrate that our method is robust to camera rotations and zooming changes.
Computer-assisted pronunciation training: From pronunciation scoring towards spoken language learning

This paper reviews the research approaches used in computer-assisted pronunciation training (CAPT), addresses the existing challenges, and discusses emerging trends and opportunities. To complement existing work, our analysis places more emphasis on pronunciation teaching and learning (as opposed to pronunciation assessment), prosodic error detection (as opposed to phonetic error detection), and research work from the past five years given the recent rapid development in spoken language technology.
multithreaded context for robust conversational interfaces: Context-sensitive speech recognition and interpretation of corrective fragments

We focus on the issue of robustness of conversational interfaces that are flexible enough to allow natural "multithreaded" conversational flow. Our main advance is to use context-sensitive speech recognition in a general way, with a representation of dialogue context that is rich and flexible enough to support conversation about multiple interleaved topics, as well as the interpretation of corrective fragments. We explain, by use of worked examples, the use of our "Conversational Intelligence Architecture" (CIA) to represent conversational threads, and how each thread can be associated with a language model (LM) for more robust speech recognition. The CIA uses fine-grained dynamic representations of dialogue context, which supersede those used in finite-state or form-based dialogue managers. In an evaluation of a dialogue system built using this architecture we found that 87.9% of recognized utterances were recognized using a context-specific language model, resulting in an 11.5% reduction in the overall utterance recognition error rate, and a 13.4% reduction in concept error rate. Thus we show that by using context-sensitive recognition based on the predicted type of the user's next dialogue move, a more flexible dialogue system can also exhibit an improvement in speech recognition performance.
A broad vision of ProjectIT-Requirements, a new approach for Requirements Engineering

The development of information systems is a complex task, involving technical, human and organizational issues. The results of this activity are not always successful, and are apparent in the lack of software quality and in costs and schedules overruns. The first initiatives developed to solve these problems were concerned with the implementation issues. It is now widely accepted that the real problem comes from the early activities and information gathered in the beginning of the projects, the most important being those connected with system requirements. Although the efforts made and the initiatives proposed, there is not a widely accepted practice or standard in this area, comparable to what we have achieved, for example, in the modeling activities. This paper presents a brief description of the state of the art in the area of requirements specification, explains the motivation to develop a new initiative, which we have called “ProjectIT-Requirements” and describes the goals we want to achieve with the project and the global context in which it integrates.
COLDER AND HOTTER: INTERFEROMETRIC IMAGING OF β CASSIOPEIAE AND α LEONIS

Near-infrared interferometers have recently imaged a number of rapidly rotating A-type stars, finding levels of gravity darkening inconsistent with theoretical expectations. Here, we present new imaging of both a cooler star β Cas (F2IV) and a hotter one α Leo (B7V) using the CHARA array and the MIRC instrument at the H band. Adopting a solid-body rotation model with a simple gravity darkening prescription, we modeled the stellar geometric properties and surface temperature distributions, confirming that both stars are rapidly rotating and show gravity darkening anomalies. We estimate the masses and ages of these rapid rotators on L–Rpol and H-R diagrams constructed for non-rotating stars by tracking their non-rotating equivalents. The unexpected fast rotation of the evolved sub-giant β Cas offers a unique test of the stellar core–envelope coupling, revealing quite efficient coupling over the past ∼0.5 Gyr. Lastly, we summarize all our interferometric determinations of the gravity darkening coefficient for rapid rotators, finding that none match the expectations from the widely used von Zeipel gravity darkening laws. Since the conditions of the von Zeipel law are known to be violated for rapidly rotating stars, we recommend using the empirically derived β = 0.19 for such stars with radiation-dominated envelopes. Furthermore, we note that no paradigm exists for self-consistently modeling heavily gravity-darkened stars that show hot radiative poles with cool convective equators.
Area coverage using distributed randomized methods

In this paper, a method is presented to solve distributed coverage using cooperative sensors. These sensors are aware of their surroundings and can act according to their state. Since the capabilities of these sensors are limited a central communication is not possible. Therefore distributed algorithms are provided which can be executed by the sensors independently. These sensors will enter the area through one point and the algorithm has to provide dispersion which will lead to the coverage. In my work several algorithms are presented in order to minimize the number of steps required by the sensors to reach full coverage. To compare these algorithms a simulator is also created which will be able to visualize and test the performance of these methods.
Influence of Oreocnide integrifolia (Gaud.) Miq on IRS-1, Akt and Glut-4 in Fat-Fed C57BL/6J Type 2 Diabetes Mouse Model

Oreocnide integrifolia (OI) leaves are used as folklore medicine by the people of northeast India to alleviate diabetic symptoms. Preliminary studies revealed hypoglycemic and hypolipidemic potentials of the aqueous leaf extract. The present study was carried out to evaluate whether the OI extract induces insulin secretion in vivo and in vitro and also whether it is mediated through the insulin-signaling pathway. The experimental set-up consisted of three groups of C57BL/6J mice strain: (i) control animals fed with standard laboratory diet, (ii) diabetic animals fed with a high-fat diet for 24 weeks and (iii) extract-supplemented animals fed with 3% OI extract along with high-fat diet for 24 weeks. OI-extract supplementation lowered adiposity and plasma glucose and insulin levels. Immunoblot analysis of IRS-1, Akt and Glut-4 protein expressions in muscles of extract-supplemented animals revealed that glucoregulation was mediated through the insulin-signaling pathway. Moreover, immunostaining of pancreas revealed increased insulin immunopositive cells in OI-extract-treated animals. In addition, the insulin secretogogue ability of the OI extract was demonstrated when challenged with high glucose concentration using isolated pancreatic islets in vitro. Overall, the present study demonstrates the possible mechanism of glucoregulation of OI extract suggestive of its therapeutic potential for the management of diabetes mellitus.
Salaries and Race in Professional Baseball: Discrimination 10 Years Later

A series of multiple regression analyses using the most recent publicly available data on the salaries of veteran hitters in major league baseball uncovers little evidence of economic discrimination by race. Comparisons of unstandardized regression coefficients for player variables, by race and position, reveal a number of instances of inequality. However, these inequalities do not occur consistently with respect to the same type of performance, nor do they always place blacks at a disadvantage. Furthermore, blacks who do not enjoy the market power granted to players by the advent of free agency are not uniformly victimized by discrimination in salaries. Instead, the newest evidence suggests that signs of salary discrimination that were found in data on hitters from the 1977 season are not manifest 10 years later.
Scattering of gravitational radiation - Second order moments of the wave amplitude

Gravitational radiation that propagates through an inhomogeneous mass distribution is subject to random gravitational tensing, or scattering, causing variations in the wave amplitude and temporal smearing of the signal. A statistical theory is constructed to treat these effects. The statistical properties of the wave amplitude variations are a direct probe of the power spectrum of the mass distribution through which the waves propagate. Scattering temporally smears any intensity variations intrinsic to a source emitting gravitational radiation, rendering variability on time scales shorter than the temporal smearing time scale unobservable, and potentially making the radiation much harder to detect. Gravitational radiation must propagate out through the mass distribution of its host galaxy before it can be detected at the Earth. Plausible models for the distribution of matter in an L. host galaxy suggest that the temporal smearing time scale is at least several milliseconds due to the gas content alone, and may be as large as a second if dark matter also scatters the radiation. The smearing time due to scattering by any galaxy interposed along the line of sight is a factor similar to10(5) times larger. Gravitational scattering is an excellent probe of matter on parsec and sub-parsec scales, and has the potential to elucidate the nature of dark matter.