Miracle-dz/UniFAR-FTUs huggingface dataset:
A View From the Top: Superintendents’ Perceptions of Mental Health Supports in Rural School Districts

Purpose: A chasm exists between the expanding mental health needs of school-aged youth and the school resources available to address them. Education agencies must efficiently allocate their limited resources by adopting innovative public health models. The need for these effective approaches is acute in rural regions, where resources tend to be scarce. This mixed-methods study of school superintendents illuminates key opportunities to optimize access to care for students struggling with mental health needs in rural communities. Method: Superintendents serving rural California school districts were targeted for a web-based, mixed response–type, 53-item survey designed to examine their perceptions across three school mental health–related categories: (a) strengths and gaps in community ethos and district infrastructure, (b) school personnel groups’ knowledge and skills, and (c) predominant barriers. Of the targeted respondents, 16.7% completed the survey (N = 62). Quantitative data were analyzed using a series of descriptive analyses and paired-sample t tests. Qualitative data were analyzed using a constant comparative method with an open-coding approach. Findings and Implications: Budget constraints and access to trained school-based and community-based mental health personnel are the most frequently cited barriers to addressing mental health in schools. Knowledge and skills related to mental health are perceived to be more pronounced in district and school leadership than in other personnel groups, including staff typically responsible for providing mental health services, such as school psychologists. Our findings suggest a need to improve superintendent knowledge of innovative public health models for delivering mental health services within the constraints of rural school district settings.
Equalization and Carrier Phase Recovery of CMA and MMA in Blind Adaptive Receivers

This paper derives general formulae for normalized error surface curvatures by using the constant modulus algorithm (CMA), the multimodulus algorithm(MMA), and two well known blind carrier phase recovery algorithms (CPRA) at the stationary points with arbitrary two-dimensional symmetric signal constellations. Based on the derived error surface curvatures, both the performance of the CMA followed by a blind CPRA and the performance of the MMA are forecasted and evaluated in terms of blind equalizer convergence and carrier phase recovery.
Engaging Men as Fathers: How Gender Influences Men’s Involvement in Australian Family Health Services

Despite claims of “new” and “involved” fathers, research shows men’s actual fathering practices remain relatively unchanged. Increasing attention is being paid to the influence of child and family services on father engagement with calls from researchers and practitioners for a game change in parenting interventions. In this article, we draw on case study data to examine how gender impacts on maternal and child health services’ engagement with new fathers in respectful relationships programs. Our analysis shows that gender shapes men’s fathering and consequently their involvement in programs that seek to engage men as fathers. These gendered behaviors intersect with the practices, policies, and orientation of the Maternal and Child Health Service. The findings hold important implications for designing strategies to engage men in family services.
A Framework for E-Mentoring in Doctoral Education

The upward trend in online graduate degrees, the mobility of graduate students, and the increase in the number of dissertations completed at a distance from universities poses several challenges for faculty who supervise research virtually, students being mentored virtually, and institutions invested in the quality of doctoral education. At the same time, emerging communication technologies present new opportunities for mentoring approaches that build upon those used in traditional on-campus environments. Based on qualitative research with 29 graduates who completed their dissertations at a distance, this chapter presents a framework for the e-mentoring of research and dissertations that encompasses strategies and support at the institutional, mentor, small group, and mentee levels.
Image Registration: A Review of Elastic Registration Methods Applied to Medical Imaging

Image registration is mapping different images of the same scene which have undergone changes due to time, position or inherent changes in the image. In medical images these may be due to motion artifact, breathing, heartbeat, etc which are difficult to register only by rigid registration and need a local transformation to correct the deformations that are elastic in nature at the local level. This is corrected by applying elastic registration applied to the initially rigid registered images. Such mapping of coordinates of the image that has undergone transformation on account of one or a combination of these factors calls for hybrid registration. A number of elastic registration methods as applied to medical imaging have been discussed in this paper and results for hybrid registration of pre contrast and post contrast abdominal CT images are shown. The resulting images show increase in correlation coefficient and Mutual information after hybrid registration, a decrease in Mean square error with differences being minimised after registration. This helps in improving diagnostic accuracy. General Terms
Gate Sizing Minimizing Delay and Area

In this work we present a gate sizing tool based on Geometric Programming. The optimization can be done targeting both, delay and power minimization. In order to qualify our approach, the ISCAS'85 benchmark circuits are mapped for 45nm technologies using standard cell library. Next, the mapped circuit is sized using our tool and the result is compared to the original mapped circuit. Speed increases 21%, on average, by delay minimization, keeping the same area and power values of the sizing provided by standard-cells library. For area optimization, where the delay was restricted to the delay value found at delay minimization, the reduction was 28.2% in area and 27.3% in power consumption, on average.
Mechanical Loading Synergistically Increases Trabecular Bone Volume and Improves Mechanical Properties in the Mouse when BMP Signaling Is Specifically Ablated in Osteoblasts

Bone homeostasis is affected by several factors, particularly mechanical loading and growth factor signaling pathways. There is overwhelming evidence to validate the importance of these signaling pathways, however, whether these signals work synergistically or independently to contribute to proper bone maintenance is poorly understood. Weight-bearing exercise increases mechanical load on the skeletal system and can improves bone quality. We previously reported that conditional knockout (cKO) of Bmpr1a, which encodes one of the type 1 receptors for Bone Morphogenetic Proteins (BMPs), in an osteoblast-specific manner increased trabecular bone mass by suppressing osteoclastogenesis. The cKO bones also showed increased cortical porosity, which is expected to impair bone mechanical properties. Here, we evaluated the impact of weight-bearing exercise on the cKO bone phenotype to understand interactions between mechanical loading and BMP signaling through BMPR1A. Male mice with disruption of Bmpr1a induced at 9 weeks of age, exercised 5 days per week on a motor-driven treadmill from 11 to 16 weeks of age. Trabecular bone volume in cKO tibia was further increased by exercise, whereas exercise did not affect the trabecular bone in the control genotype group. This finding was supported by decreased levels of osteoclasts in the cKO tibiae. The cortical porosity in the cKO bones showed a marginally significant decrease with exercise and approached normal levels. Exercise increased ductility and toughness in the cKO bones. Taken together, reduction in BMPR1A signaling may sensitize osteoblasts for mechanical loading to improve bone mechanical properties.
Managing collective effervescence: ‘Zomsumption’ and postemotional fandom

Based on an analysis of the YouTuber–fan community, we theorize the ‘living dead’ nature of collective effervescence under postemotional conditions. We introduce the concept of zomsumption, whereby ‘dead’ emotions are carefully synthesized, governed and presented as ‘living’ throughout the communal consumption of a totem. Here, we explore fans’ efforts to ensure the stability and longevity of their community through the lifelessness of their emotional behaviour. By forfeiting genuine and unfiltered emotions in favour of their rationalization and governance, fans access the illusory potential for more manageable forms of sociability and totemic worship. This outlook prompts us to reconsider the nature of the relationship between consumption communities and dominant structures of feeling. We suggest that consumption communities should not be presumed liberatory retreats from such structures as, contrarily, some may function as microcosms for reflecting and even incubating the wider postemotional order.
Text-Based Affect Detection in Intelligent Tutors

Affect-sensitive Intelligent Tutoring Systems are an exciting new educational technology that aspire to heighten motivation and enhance learning gains in interventions that are dynamically adaptive to learners’ affective and cognitive states. Although state of the art affect detection systems rely on behavioral and physiological measures for affect detection, we show that a textual analysis of the tutorial discourse provides important cues into learners’ affective states. This chapter surveys the existing literature on textbased affect sensing and focuses on how learners’ affective states (boredom, flow/engagement, confusion, and frustration) can be automatically predicted by variations in the cohesiveness of tutorial dialogues during interactions with AutoTutor, an intelligent tutoring system with conversational dialogues. We discuss the generalizability of our findings to other domains and tutoring systems, the possibility of constructing real-time cohesion-based affect detectors, and implications for text-based affect detection for the next generation affect-sensitive learning environments.
Preprocessing Methods for Word Alignment Annonymous

This paper compares four preprocessing approaches for word alignment: 1) sentence removal approach, 2) good points approach, 3) sentence duplication approach, and 4) removal of doubtful alignments approach. Two are statistically motivated and the other two are heuristics. We focus on the ability of a word aligner of IBM Model 4 that it should often face with troubles when handling paraphrase, multi-words and non-literal translation. We assume that IBM Model 4 works 90 % correct, while only around 5 % wrong.
Distributed computations driven by resource consumption

Millions of computers are now connected together by the Internet. At a fast pace, applications are taking advantage of these new capabilities, and are becoming parallel and distributed, e.g. applets on the WWW or agent technology. As we live in a world with finite resources, an important challenge is to be able to control computations in such an environment. For instance, a user might like to suspend a computation because another one seems to be more promising. We present a paradigm that allows the programmer to monitor and control computations, whether parallel or distributed, by mastering their resource consumption. We describe an implementation on top of the thread library PPCR (M. Weiser et al., 1989) and the message passing library Nexus (I. Foster et al., 1996).
Probabilistic modeling of sensor properties in generic fusion systems for modern driver assistance systems

Modern driver assistance and safety systems need a reliable and precise description of the environment. Fusing the measurement data of two or more sensors can improve the performance of the perception system. A generic fusion system which is independent of the attached sensors could be reused in multiple fusion systems and sensor combinations. This could be very helpful because sensor data fusion is a demanding and complex task. In this contribution, we present the algorithmic basics for a generic fusion system, detailed ways on how to model sensor specific properties and which benefits we can achieve by using these models.
Using Design Pattern for Micro Level Software Design

Several problems can arise while developing an interactive or web based systems containing mixture of data access, business logic, and presentation code. Such applications are difficult to maintain, because interdependencies between all of the components cause strong ripple effects whenever a change is made anywhere. High coupling makes classes difficult or impossible to reuse because they depend on so many other classes. While developing such system, one should think beyond traditional, structured or object oriented methods as they offer limited means of reasoning about the validity of specifications. Finding the right abstractions of classes and defining the collaboration between them will be easier if design pattern is integrated with object oriented method of software engineering. With the help of pattern a system can be designed for change. Even though the use of a design pattern increases the reusability of the software, it is not practiced to its strength, largely because of the unfamiliarity of the benefits a design pattern offers. The present paper demonstrates how an interactive or web based system( including Web2.0) can be developed with the help of a well accepted design pattern, Model-View-Controller (MVC), that has been used in popular frameworks like Java Swing, Struts, spring and . Net.
Evaluation of balloon and satellite water vapour measurements in the Southern tropical UTLS during the HIBISCUS campaign

Balloon water vapour in situ and remote measurements in the tropical upper troposphere and lower stratosphere (UTLS) obtained during the HIBISCUS campaign around 20 S in Brazil in February–March 2004 using a tunable diode laser ( μSDLA), a surface acoustic wave (SAW) and a Vis-NIR solar occultation spectrometer (SAOZ) on a long duration balloon, have been used for evaluating the performances of satellite borne remote water vapour instruments available at the same latitude and measurement period. In the stratosphere, HALOE displays the best precision (2.5%), followed by SAGE II (7%), MIPAS (10%), SAOZ (20–25%) and SCIAMACHY (35%), all of which show approximately constant H2O mixing ratios between 20–25 km. Compared to HALOE of ±10% accuracy between 0.1–100 hPa, SAGE II and SAOZ show insignificant biases, MIPAS is wetter by 10% and SCIAMACHY dryer by 20%. The currently available GOMOS profiles of 25% precision show a positive vertical gradient in error for identified reasons. Compared to these, the water vapour of the Reprobus Chemistry Transport Model, forced at pressures higher than 95 hPa by the ECMWF analyses, is dryer by about 1 ppmv (20%). In the lower stratosphere between 16–20 km, most notable features are the steep degradation of MIPAS precision below 18 km, and the appearance of biases between instruments far larger than their quoted total uncertainty. HALOE and Correspondence to: N. Montoux (nadege.montoux@latmos.ipsl.fr) SAGE II (after spectral adjustment for reducing the bias with HALOE at northern mid-latitudes) both show decreases of water vapour with a minimum at the tropopause not seen by other instruments or the model, possibly attributable to an increasing error in the HALOE altitude registration. Between 16–18 km where the water vapour concentration shows little horizontal variability, and where the μSDLA balloon meaurements are not perturbed by outgassing, the average mixing ratios reported by the remote sensing instruments are substantially lower than the 4–5 ppmv observed by the μSDLA. Differences between μSDLA and HALOE and SAGE II (of the order of−2 ppmv), SCIAMACHY, MIPAS and GOMOS (−1 ppmv) and SAOZ ( −0.5 ppmv), exceed the 10% uncertainty of μSDLA, implying larger systematic errors than estimated for the various instruments. In the upper troposphere, where the water vapour concentration is highly variable, AIRS v5 appears to be the most consistent within its 25% uncertainty with balloon in-situ measurements as well as ECMWF. Most of the remote measurements show less reliability in the upper troposphere, losing sensitivity possibly because of absorption line saturation in their spectral ranges (HALOE, SAGE II and SCIAMACHY), instrument noise exceeding 100% (MIPAS) or imperfect refraction correction (GOMOS). An exception is the SAOZ-balloon, employing smaller H 2O absorption bands in the troposphere. Published by Copernicus Publications on behalf of the European Geosciences Union. 5300 N. Montoux et al.: Balloon and satellite H2O measurements in the tropical UTLS
Non-cooperative Monetary and Fiscal Policy: The Value of Leadership

We consider leadership equilibria in dynamic linear rational expectations models with specific reference to monetary and fiscal policy interactions. We pay particular attention to the strategic relationships between policymakers and the private sector. We find that in a dynamic game that although leadership may not matter much, giving leadership to a constrained policymaker should be avoided.
CTGEN - a Unit Test Generator for C

We present a new unit test generator for C code, CTGEN. It generates test data for C1 structural coverage and functional coverage based on pre-/post-condition specifications or internal assertions. The generator supports automated stub generation, and data to be returned by the stub to the unit under test (UUT) may be specified by means of constraints. The typical application field for CTGEN is embedded systems testing; therefore the tool can cope with the typical aliasing problems present in low-level C, including pointer arithmetics, structures and unions. CTGEN creates complete test procedures which are ready to be compiled and run against the UUT. In this paper we describe the main features of CTGEN, their technical realisation, and we elaborate on its performance in comparison to a list of competing test generation tools. Since 2011, CTGEN is used in industrial scale test campaigns for embedded systems code in the automotive domain.
Noise Robust Phonetic Classificationwith Linear Regularized Least Squares and Second-Order Features

We perform phonetic classification with an architecture whose elements are binary classifiers trained via linear regularized least squares (RLS). RLS is a simple yet powerful regularization algorithm with the desirable property that a good value of the regularization parameter can be found efficiently by minimizing leave-one-out error on the training set. Our system achieves state-of-the-art single classifier performance on the TIMIT phonetic classification task, (slightly) beating other recent systems. We also show that in the presence of additive noise, our model is much more robust than a well-trained Gaussian mixture model.
Pharmaceutical Packaging Color and Drug Expectancy

Pharmaceutical markets are expanding considerably due to the aging population, higher development costs and also direct-to-consumer advertising which entails more demands from consumers and prescriptions from physicians. Pharmaceutical packaging as a visual communication tool is promised to a mounting importance, because of growing blister packaging, safety standards upgrading, expansion of OTC drugs and developing television advertising. This study examines the impact of packaging color on consumers' expectancies towards the drug and seeks determining if prototypical color codes exist for drug categories. Results show a significant influence of color and Darkness on perceived drug potency. Gender differences are discussed.
Autocalibration for virtual environments tracking hardware

We describe two instances in which precise mechanical calibration of virtual environments equipment has been replaced by automated algorithmic calibration through software that encapsulates the hardware design and uses a goal-based approach to adjust calibration parameters. We describe a back-projection system for adjusting the assumed locations of beacons in a head-mounted display tracking system; the calculated errors in the navigation system are used to compute adjustments to the beacon positions to reduce such errors. In a second application, a piggyback headtracking/hand-tracking system is calibrated by a similar reduction of computed errors.
Non-Born-Oppenheimer correction to the H3+ potential from experimental data.

The spectrum of D[sub 3][sup +] is analyzed using a spectroscopically determined effective H[sub 3][sup +] potential [B. M. Dinelli, S. Miller, and J. Tennyson, J. Molec. Spectrosc. 163, 71 (1994)] and an accurate [ital ab] [ital initio] potential [G. C. Lie and D. Frye, J. Chem. Phys. 96, 6784 (1992)]. Calculations suggest that the major error in the potential of Lie and Frye is due to the Born-Oppenheimer approximation. D[sub 3][sup +] spectroscopic data are used to construct both Born-Oppenheimer and mass-dependent adiabatic surfaces for the H[sub 3][sup +] system by fitting only one parameter. These surfaces reproduce the fundamental rovibrational transitions of H[sub 3][sup +] and D[sub 3][sup +] to within 0.03 cm[sup [minus]1]. An accurate adiabatic surface has been determined for a polyatomic molecule.
Using CARE to construct verified software

The CARE project investigated integration of well understood formal development principles into an industrial organisation's software development methodology. The result was a method for construction and verification of programs from formal specifications, using libraries of pre proven, formally specified components. Tools help the user build products by selecting and instantiating components to fit the problem at hand and generating and discharging correctness of fit proof obligations. The paper illustrates the method on part of the development of a software module for logging events in a medical embedded device.
How to track and assess genotyping errors in population genetics studies

Genotyping errors occur when the genotype determined after molecular analysis does not correspond to the real genotype of the individual under consideration. Virtually every genetic data set includes some erroneous genotypes, but genotyping errors remain a taboo subject in population genetics, even though they might greatly bias the final conclusions, especially for studies based on individual identification. Here, we consider four case studies representing a large variety of population genetics investigations differing in their sampling strategies (noninvasive or traditional), in the type of organism studied (plant or animal) and the molecular markers used [microsatellites or amplified fragment length polymorphisms (AFLPs)]. In these data sets, the estimated genotyping error rate ranges from 0.8% for microsatellite loci from bear tissues to 2.6% for AFLP loci from dwarf birch leaves. Main sources of errors were allelic dropouts for microsatellites and differences in peak intensities for AFLPs, but in both cases human factors were non‐negligible error generators. Therefore, tracking genotyping errors and identifying their causes are necessary to clean up the data sets and validate the final results according to the precision required. In addition, we propose the outline of a protocol designed to limit and quantify genotyping errors at each step of the genotyping process. In particular, we recommend (i) several efficient precautions to prevent contaminations and technical artefacts; (ii) systematic use of blind samples and automation; (iii) experience and rigor for laboratory work and scoring; and (iv) systematic reporting of the error rate in population genetics studies.