Miracle-dz/UniFAR-FTUs huggingface dataset:
Middle School Reform Through Data and Dialogue

This report describes a 2-year, longitudinal study of one school district's effort to link site-based, collaborative evaluation with formal, centralized program evaluation. Participants formed a research team in partnership with a local university. Team members assisted leadership teams in identifying issues for informal, site-based assessments and then used the information to monitor progress toward established goals. Participants collaborated in designing and conducting informal assessments of student achievement, school climate and safety, discipline, and parent involvement. Leadership teams used these data in developing their school improvement plans. Researchers and administrators used these data to revise the districtwide survey. At the end of the 2-year cycle, analysis of school improvement plans showed that collaborative evaluation is creating a connection between dialogue and data. These 17 middle schools are approaching school improvement in a more integrated fashion by actively involving key stakeholders (students, parents, and teachers) in the evaluation process.
Speech Coding in the Brain: Representation of Vowel Formants by Midbrain Neurons Tuned to Sound Fluctuations1,2,3

Abstract Current models for neural coding of vowels are typically based on linear descriptions of the auditory periphery, and fail at high sound levels and in background noise. These models rely on either auditory nerve discharge rates or phase locking to temporal fine structure. However, both discharge rates and phase locking saturate at moderate to high sound levels, and phase locking is degraded in the CNS at middle to high frequencies. The fact that speech intelligibility is robust over a wide range of sound levels is problematic for codes that deteriorate as the sound level increases. Additionally, a successful neural code must function for speech in background noise at levels that are tolerated by listeners. The model presented here resolves these problems, and incorporates several key response properties of the nonlinear auditory periphery, including saturation, synchrony capture, and phase locking to both fine structure and envelope temporal features. The model also includes the properties of the auditory midbrain, where discharge rates are tuned to amplitude fluctuation rates. The nonlinear peripheral response features create contrasts in the amplitudes of low-frequency neural rate fluctuations across the population. These patterns of fluctuations result in a response profile in the midbrain that encodes vowel formants over a wide range of levels and in background noise. The hypothesized code is supported by electrophysiological recordings from the inferior colliculus of awake rabbits. This model provides information for understanding the structure of cross-linguistic vowel spaces, and suggests strategies for automatic formant detection and speech enhancement for listeners with hearing loss.
A Feed-Forward 10 × CMOS Current-Ripple Suppressor for Switching Power Supplies

With the advent of wireless microsensors and other microscale applications, switching supplies fully integrated on chip or into the package are desirable and often necessary. The problem with small inductors is that they exhibit low inductance and larger equivalent series resistance (ESR); in other words, they induce larger ripples in the output and higher conduction power losses. This brief presents and verifies a current-ripple suppression technique in which a discrete 2 × 2 × 1 mm 4.7-μH inductor is effectively multiplied by subtracting a replica of the inductor’s ac ripple current, allowing only a residual ripple to reach the output. Experimental results from a complementary metal–oxide–semiconductor integrated circuit prototype demonstrate a currentand output-ripple reduction of 10.8× and 25.8×, respectively. The ESR power savings in the smaller inductor favorably offset the quiescent power lost in the multiplier (128 mW), outperforming its higher nonmultiplied 47-μH counterpart at high loads (above 250 mA).
Constructing non-functionally expressible fuzzy implications

This article discusses a new method for the construction of non-functionally expressible fuzzy implications. In a recent work, we have considered non-functionally expressible fuzzy implications from an implication function acting on the inputs followed by an aggregation process. Now, we first perform an aggregation of the inputs and then an implication function between the aggregated values. The main part is devoted to analyse under which conditions the two construction processes coincide.
A fast Visualization System for Adaptive Grids

Todays data sets arising from computational mathematics are extremely large which poses increasing demands for performance (in the sense of graphics-performance) on interactive visualization systems. ”Real-time” interaction interfaces have proven useful for the analysis of these data sets, but real-time performance has been difficult to achieve with such large amounts of data. This work describes the outcome of a small visualization project dealing with the visualization of large unstructured data sets.
ECONOMIES OF DENSITY AND SERVICE LEVELS ON U.S. RAILROADS: AN EXPERIMENTAL ANALYSIS

Econometric studies have consistently shown that U.S. railroads enjoy susbstantial economies of traffic density, although the underlying causes of these economies are not fully understood. This paper shows how increased density makes it possible to achieve economies in the use of train labor and equipment. Increased density not only allows for longer trains, thus spreading train cost over a larger output, but also makes it economical to provide direct train connections between an increasing number of terminals. This reduces transit time. Reductions in transit time may be a more significant benefit of density than reductions in unit cost. Furthermore, estimates of returns to density are quite sensitive to the level of service provided.
The Outcome of Health Anxiety in Primary Care. A Two-Year Follow-up Study on Health Care Costs and Self-Rated Health

Background Hypochondriasis is prevalent in primary care, but the diagnosis is hampered by its stigmatizing label and lack of valid diagnostic criteria. Recently, new empirically established criteria for Health anxiety were introduced. Little is known about Health anxiety's impact on longitudinal outcome, and this study aimed to examine impact on self-rated health and health care costs. Methodology/Principal Findings 1785 consecutive primary care patients aged 18–65 consulting their family physicians (FPs) for a new illness were followed-up for two years. A stratified subsample of 701 patients was assessed by the Schedules for Clinical Assessment in Neuropsychiatry interview. Patients with mild (N = 21) and severe Health anxiety (N = 81) and Hypochondriasis according to the DSM-IV (N = 59) were compared with a comparison group of patients who had a well-defined medical condition according to their FPs and a low score on the screening questionnaire (N = 968). Self-rated health was measured by questionnaire at index and at three, 12, and 24 months, and health care use was extracted from patient registers. Compared with the 968 patients with well-defined medical conditions, the 81 severe Health anxiety patients and the 59 DSM-IV Hypochondriasis patients continued during follow-up to manifest significantly more Health anxiety (Whiteley-7 scale). They also continued to have significantly worse self-rated functioning related to physical and mental health (component scores of the SF-36). The severe Health anxiety patients used about 41–78% more health care per year in total, both during the 3 years preceding inclusion and during follow-up, whereas the DSM-IV Hypochondriasis patients did not have statistically significantly higher total use. A poor outcome of Health anxiety was not explained by comorbid depression, anxiety disorder or well-defined medical condition. Patients with mild Health anxiety did not have a worse outcome on physical health and incurred significantly less health care costs than the group of patients with a well-defined medical condition. Conclusions/Significance Severe Health anxiety was found to be a disturbing and persistent condition. It is costly for the health care system and must be taken seriously, i.e. diagnosed and treated. This study supports the validity of recently introduced new criteria for Health anxiety.
Reconceptualizing variable rater assessments as both an educational and clinical care problem.

The public is calling for the U.S. health care and medical education system to be accountable for ensuring high-quality, safe, effective, patient-centered care. As medical education shifts to a competency-based training paradigm, clinician educators' assessment of and feedback to trainees about their developing clinical skills becomes paramount. However, there is substantial variability in the accuracy, reliability, and validity of the assessments faculty make when they directly observe trainees with patients. These difficulties have been treated primarily as a rater cognition problem focusing on the inability of the assessor to make reliable and valid assessments of the trainee.The authors' purpose is to reconceptualize the rater cognition problem as both an educational and clinical care problem. The variable quality of faculty assessments is not just a psychometric predicament but also an issue that has implications for decisions regarding trainee supervision and the delivery of quality patient care. The authors suggest that the frame of reference for rating performance during workplace-based assessments be the ability to provide safe, effective, patient-centered care. The authors developed the Accountable Assessment for Quality Care and Supervision equation to remind faculty that supervision is a dynamic, complex process essential for patients to receive high-quality care. This fundamental shift in how assessment is conceptualized requires new models of faculty development and emphasizes the essential and irreplaceable importance of the clinician educator in trainee assessment.
An Industrial Case Study of Customizing Operational Profiles Using Log Compression

Large customers commonly request on-site capacity testing before upgrading to a new version of a mission critical telecom application. Customers fear that the new version cannot handle their current workload. These on-site engagements are costly and time consuming. These engagements prolong the upgrade cycle for products and reduce the revenue stream of rapidly growing companies. We present an industrial case study for a lightweight simple approach for customizing the operational profile for a particular deployment. The approach flags sequences of repeated events out of millions of events in execution logs. A performance engineer can identify noteworthy usage scenarios using these flagged sequences. The identified scenarios are used to customize the operational profile. Using a customized profile for performance testing alleviates customer's concerns about the performance of a new version of an application, and results in more realistic performance and reliability estimates. The simplicity of our approach ensures that customers can easily grasp the results of our analysis over other more complex analysis approaches. We demonstrate the feasibility and applicability of our approach by customizing the operational profile of an enterprise telecom application.
Instrumental Gestural Mapping Strategies as Expressivity Determinants in Computer Music Performance

This paper presents ongoing work on gesture mapping strategies and applications to sound synthesis by signal models controlled via a standard MIDI wind controller. Our approach consists in considering different mapping strategies in order to achieve "fine" (therefore in the authors' opinion, potentially expressive) control of additive synthesis by coupling originally independent outputs from the wind controller. These control dignals are applied to nine different clarinet data files obtained from analysis of clarinet sounds, which are arranged in an expressive timbral subspace and interpolated in real-time, using FTS 1.4, IRCAM's digital signal processing environment. An analysis of the resulting interpolation is also provided and topics related to sound morphing are discussed.
PSNR-Based Estimation of Subjective Time-Variant Video Quality for Mobiles

With low-rate video services over packet networks, the topic of video quality measuring became even more popular. In the presence of packet loss, the video quality becomes highly time-variant. The subjective quality evaluation is in general correlated with the metrics based on the difference between the degraded sequence and the reference. However, it can diffe r significantly in some cases, thus it provides limited means for the appropriate quality estimation. In this work we focus on the relation between the peak to signal-to-noise ratio (PSNR) and the mean opinion score for the video streams with time variant quality. We study simple human perception rules and use them to correct the PSNR accordingly, to achieve suitable subjective quality estimation, based on objective parameters. We focus on mobile terminals and video applications. Thus, we performed the assessments on mobile terminals using our proposed methodology. The results show considerable improvement of the estimation quality with respect to the PSNR.
A New Look at Frequency Resolution in Power Spectral Density Estimation

The problem of frequency resolution in non-parametric power spectrum density estimation (PSDE) for noisy signals is considered. In this setting, finite length of data as well as the additive noise, both contribute to a decreased frequency resolution. The existing PSDE approaches offer different forms of averaging and windowing of the available data only to improve statistical properties of the estimates, however, at the expense of reducing frequency resolution. In these approaches, the additive noise and the finiteness of data which are the causes of the original loss of the frequency resolution are not treated separately. In this paper, we suggest a new approach which takes advantages of these two different causes of the problem. Therefore, the new nonparametric approach to spectrum estimation tackles the problem of resolution in two steps. First, the method optimally reduces noise interference with the signal via minimum noiseless description length (MNDL). The new power spectrum estimation MNDL-periodogram (PMNDL) of the denoised signal is then computed via conventional indirect periodogram to improve frequency resolution
A QoS Based MAC Protocol For Wireless Ad-hoc Network

Multimedia communication over wireless Ad-hoc networks has become the driving technology for many of the important applications, experiencing dramatic market growth and promising revolutionary experiences in personal communication, gaming, entertainment, military, security, environment monitoring, and more. The advances in wireless communications and growth of real-time applications have necessitated the development of wireless networks that can support high Quality of Service (QoS) and power control. A node in an ad hoc network is normally battery operated which poses a huge constraint on the power consumption of such a node. Hence, designing a power efficient MAC protocol for ad hoc wireless networks is a major challenge. In this paper, we propose a CDMA based power controlled medium access protocol for mobile and ad hoc network (MNA). The protocol conserves power and provides QoS guarantees for multimedia traffics. In that network one of the fundamental challenger in MANETs is how to increase the overall network throughputs well as reading the delay while maintaining how energy consumption for packet processing in communication. simulation results shows that the performance of the protocol with increase in traffic while QoS is better in terms of Energy consumption, throughput, & communication delay than existing protocol.
High frequency waking EEG: reflection of a slow ultradian rhythm in daytime arousal

The ultradian dynamics of the human waking EEG was studied using a short visual fixation task repeated every 10 min throughout the daytime. The EEG spectra obtained from the tasks were assessed for time effect and ultradian periodicity. Fronto-central EEG high frequency powers (22.5–44.5 Hz) decreased at the time of the midafternoon vigilance dip (14.00–17.00 h) along with slight concomitant increases in parietal alpha (7.5-13.5 Hz) and delta (1–3 Hz) powers. A slow ultradian rhythm with a 3–4 h periodicity strongly modulated EEG power in all frequency bands between 1 and 44.5 Hz. The high frequency waking EEG may well reflect the activity of a brain arousal process underlying maintenance of the waking state probably throughout the 24 h cycle.
Seven Design Challenges for Fully-realized Experience Management

Drama Managers, a specific type of the more general Experience Manager, have become a common subject of study in the interactive narrative literature. With a range of representational and computational approaches, authors have repeatedly developed techniques that enable computers to generate, reason about, and adapt narratives in an interactive virtual setting. In order to fully realize an experience manager, seven representational and computational problems need to be solved, generally on a case-by-case basis. In other words, the choice to use an Experience Manager is the choice to model the design as, and implement solutions to, seven inter-dependent design problems. We explicitly articulate those design problems and provide a number of examples of methods that both motivate the design problems as well as illustrate a range of approaches to solving them.
Diffusion-weighted MRI in head and neck radiology: applications in oncology

Abstract Extracranial application of diffusion-weighted magnetic resonance imaging (MRI) has gained increasing importance in recent years. As a result of technical advances, this new non-invasive functional technique has also been applied in head and neck radiology for several clinical indications. In cancer imaging, diffusion-weighted MRI can be performed for tumour detection and characterization, monitoring of treatment response as well as the differentiation of recurrence and post-therapeutic changes after radiotherapy. Even for lymph node staging promising results have been reported recently. This review article provides overview of potential applications of diffusion-weighted MRI in head and neck with the main focus on its applications in oncology.
Serial Killing of Tumor Cells by Human Natural Killer Cells – Enhancement by Therapeutic Antibodies

Background Natural killer cells are an important component of the innate immune system. Anti-cancer therapies utilizing monoclonal antibodies also rely on the cytotoxicity of NK cells for their effectiveness. Here, we study the dynamics of NK cell cytotoxicity. Methodology/Principal Findings We observe that IL-2 activated human NK cells can serially hit multiple targets. Using functional assays, we demonstrate that on an average, a single IL-2 activated NK cell can kill four target cells. Data using live video microscopy suggest that an individual NK cell can make serial contacts with multiple targets and majority of contacts lead to lysis of target cells. Serial killing is associated with a loss of Perforin and Granzyme B content. A large majority of NK cells survive serial killing, and IL-2 can replenish their granular stock and restore the diminished cytotoxicity of ‘exhausted’ NK cells. IL-2 and IL-15 are equally effective in enhancing the killing frequency of resting NK cells. Significantly, Rituximab, a therapeutic monoclonal antibody increases the killing frequency of both resting and IL-2 activated NK cells. Conclusion/Significance Our data suggest that NK cell-based therapies for overcoming tumors rely on their serial killing ability. Therefore, strategies augmenting the killing ability of NK cells can boost the immune system and enhance the effectiveness of monoclonal antibody-based therapies.
Temporal Extension to OWL Ontologies

— Ontologies play an important role in semantic web applications and are often developed by different groups and continues to evolve over time. The knowledge in ontologies changes very rapidly that make the applications outdated if they continue to use old versions or unstable if they jump to new versions. Temporal frames using frame versioning and slot versioning are used to take care of dynamic nature of the ontologies. The paper proposes new tags and restructured OWL format enabling the applications to work with the old or new version of ontologies. Gene Ontology, a very dynamic ontology, has been used as a case study to explain the OWL Ontology with Temporal Tags.
A modular reinforcement learning model for human visuomotor behavior in a driving task

We present a task scheduling framework for studying human eye movements in a realistic 3D driving simulation. Human drivers are modeled using a reinforcement learning algorithm with “task modules” that make learning tractable and provide a cost metric for behaviors. Eye movement scheduling is simulated with a loss minimization strategy that incorporates expected reward estimates given uncertainty about the state of environment. This work extends a previous model that was applied to a simulation of walking; we extend this approach using a more dynamic state space and adding task modules that reflect the greater complexity in driving. We also discuss future work in applying this model to navigation and fixation data from human drivers.
Multiparameter two-dimensional inversion of scattered teleseismic body waves 1. Theory for oblique incidence

This is the first paper in a three-part series that examines formal inversion of the teleseismic P wave coda for discontinuous variations in elastic properties beneath dense, three-component, seismic arrays. In this paper, we develop the theoretical framework for a migration method that draws upon the tenets of inverse scattering theory and is amenable to practical implementation. The forward problem is formulated for two-dimensional (2-D) heterogeneity in observance of formal sampling requirements and currently accessible instrumentation. A ray theoretic Green's function, corresponding to a line source with axial component of forcing, is employed within the 2-D Born approximation to accommodate planar, incident wave fields at arbitrary back azimuths. Both the forward scattered response generated by the upgoing incident wave field and the backscattered response created by its reflection at the free surface are included within the formulation. In accordance with the high-frequency and single-scattering approximations employed in the forward problem the inverse problem is cast as a generalized Radon transform. The resulting back projection operator is well suited to the teleseismic context in several respects. It is tolerant of irregularities in array geometry and source distribution and allows a full complement of global seismicity to be utilized through its accommodation of oblique incidence. By permitting both independent and simultaneous treatment of different scattering modes (reflections, transmissions, conversions) the inversion formula facilitates a direct appraisal of individual mode contributions to the recovery of structure. In particular, it becomes evident that incorporation of backscattered modes leads to (1) a better localization of structure than possible using forward scattered energy and (2) the imposition of complementary constraints on elastic properties.