Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypocrisy, State Policy, and African American Students With Disabilities: The Guise of Access

We critically examined the odds of earning a college preparatory diploma for African American high school seniors receiving special education services under Texas’s Top 10% Policy (TTPP). Critical policy analysis was used to explore the meritocratic guise of college access for African American youth with disabilities, and through DisCrit, theorized TTPP’s broader effect on the social stratification and creation of policy “winners” and “losers. ” Results from multilevel logistic regression models indicate African American students are nearly twice as likely to be identified with disabilities as their peers and are the least likely to earn a college preparatory diploma in Texas.
The Charlson Comorbidity Index Can Be Used Prospectively to Identify Patients Who Will Incur High Future Costs

Background Reducing health care costs requires the ability to identify patients most likely to incur high costs. Our objective was to evaluate the ability of the Charlson comorbidity score to predict the individuals who would incur high costs in the subsequent year and to contrast its predictive ability with other commonly used predictors. Methods We contrasted the prior year Charlson comorbidity index, costs, Diagnostic Cost Group (DCG) and hospitalization as predictors of subsequent year costs from claims data of fund that provides comprehensive health benefits to a large union of health care workers. Total costs in the subsequent year was the principal outcome. Results Of the 181,764 predominantly Black and Latino beneficiaries, 70% were adults (mean age 45.7 years; 62% women). As the comorbidity index increased, total yearly costs increased significantly (P<.001). At lower comorbidity, the costs were similar across different chronic diseases. Using regression to predict total costs, top 5th and 10th percentile of costs, the comorbidity index, prior costs and DCG achieved almost identical explained variance in both adults and children. Conclusions and Relevance The comorbidity index predicted health costs in the subsequent year, performing as well as prior cost and DCG in identifying those in the top 5% or 10%. The comorbidity index can be used prospectively to identify patients who are likely to incur high costs. Trial Registration ClinicalTrials.gov NCT01761253
Second-level testing revisited and applications to NIST SP800-22

The use of second-level testing to reduce Type II errors in RNG validation was suggested from the very beginning though rarely employed in real-world cases. Yet, as security requirements become more critical and the availability of even faster RNG more commonplace, second-level testing will be key to distinguishing RNGs based on the quality of very large chunks of their output. This paper addresses some principles governing the proper design of second-level tests (i.e. how to divide available data into chunks and how to compute second-level p-values) as well as its implications on the design of the underlying basic tests.
Reprints Available Directly from the Publishers Photocopying Permitted by License Only the Thickness of Pitch: Crossmodal Metaphors in Farsi, Turkish, and Zapotec

AbstrAct speakers use vocabulary for spatial verticality and size to describe pitch. A high–low contrast is common to many languages, but others show contrasts like thick–thin and big–small. We consider uses of thick for low pitch and thin for high pitch in three languages: Farsi, turkish, and Zapotec. We ask how metaphors for pitch structure the sound space. In a language like English, high applies to both high-pitched as well as high-amplitude (loud) sounds; low applies to low-pitched as well as low-amplitude (quiet) sounds. Farsi, turkish, and Zapotec organize sound in a different way. Thin applies to high pitch and low amplitude and thick to low pitch and high amplitude. We claim that these metaphors have their sources in life experiences. Musical instruments show
EFL Virtual Learning Environments: Perception, Concerns and Challenges.

Virtual Learning Environment (VLE) is a fad in the 21 st century academic landscape. A number of studies found out that students perceive VLEs positively and that VLEs facilitate learning English as a Foreign Language (EFL) and provide an avenue for educators to extend a helping hand to their EFL students. Sustaining VLEs is not an easy task as it raises various concerns and challenges, particularly in the domain of EFL learning. This paper reports on the results of a qualitative study aimed to shed light on the stakeholders’ perception towards VLE as well as the significant concerns and challenges encountered by EFL lecturers and their students on their actual use of VLEs in a higher education institution. Furthermore, the study unveiled the practical tips to create efficient and effective VLEs, based on the suggestions of both the EFL students and their lecturers.
Understanding Students of Poverty in the Multicultural Classroom

case for culturally relevant pedagogy. Theory into Practice, 34(3), 159–165. Lewin, K. (2007). Improving access, equity and transitions in education: Creating a research agenda (create pathways to access research monograph, Vol. 1). Brighton, UK: University of Sussex. Lopez, G. R. (2003). The (racially neutral) politics of education: A critical race theory perspective. Educational Administration Quarterly, 39(1), 68–94. Manning, M. L. (1996). Addressing the fears of diversity. Kappa Delta Pi Record, 33(1), 4–7. McCarthy, S. K. (2009). Communist multiculturalism: Ethnic revival in southwest China (1st ed.). Seattle, WA: University of Washington Press. Nussbaum, M. (2002). Education for citizenship in an era of global connection. Studies in Philosophy and Education, 21, 289–303. Paris, D. (2012). Culturally sustaining pedagogy: A needed change in stance, terminology, and practice. Educational Researcher, 41(3), 93–97. Villegas, A. , & Lucas, R. (2007). The culturally responsive teacher. Educational Leadership, 64(6), 28–33.
SIMULATIONS OF BARYON ACOUSTIC OSCILLATIONS. II. COVARIANCE MATRIX OF THE MATTER POWER SPECTRUM

We use 5000 cosmological N-body simulations of 1 h−3 Gpc3 box for the concordance ΛCDM model in order to study the sampling variances of a nonlinear matter power spectrum. We show that the non-Gaussian errors can be important even on large length scales relevant for baryon acoustic oscillations (BAOs). Our findings are the following: (1) the non-Gaussian errors degrade the cumulative signal-to-noise ratios (S/Ns) for the power spectrum amplitude by up to a factor of 2 and 4 for redshifts z = 1 and 0, respectively; (2) there is little information on the power spectrum amplitudes in the quasi-nonlinear regime, confirming the previous results; (3) the distribution of power spectrum estimators at BAO scales, among the realizations, is well approximated by a Gaussian distribution with variance that is given by the diagonal covariance component. (4) For the redshift-space power spectrum, the degradation in S/N by non-Gaussian errors is mitigated due to nonlinear redshift distortions; (5) for an actual galaxy survey, the additional shot noise contamination compromises the cosmological information inherent in the galaxy power spectrum, but also mitigates the impact of non-Gaussian errors. The S/N is degraded by up to 30% for a Wide-Field Fiber-Fed Optical Multi-Object Spectrograph-type survey; (6) the finite survey volume causes additional non-Gaussian errors via the correlations of long-wavelength fluctuations with the fluctuations we want to measure, further degrading the S/N values by about 30% even at high redshift z = 3.
Proteomic Analyses Reveal that Sky1 Modulates Apoptosis and Mitophagy in Saccharomyces cerevisiae Cells Exposed to Cisplatin

Sky1 is the only member of the SR (Serine–Arginine) protein kinase family in Saccharomyces cerevisiae. When yeast cells are treated with the anti-cancer drug cisplatin, Sky1 kinase activity is necessary to produce the cytotoxic effect. In this study, proteome changes in response to this drug and/or SKY1 deletion have been evaluated in order to understand the role of Sky1 in the response of yeast cells to cisplatin. Results reveal differential expression of proteins previously related to the oxidative stress response, DNA damage, apoptosis and mitophagy. With these precedents, the role of Sky1 in apoptosis, necrosis and mitophagy has been evaluated by flow-cytometry, fluorescence microscopy, biosensors and fluorescence techniques. After cisplatin treatment, an apoptotic-like process diminishes in the ∆sky1 strain in comparison to the wild-type. The treatment does not affect mitophagy in the wild-type strain, while an increase is observed in the ∆sky1 strain. The increased resistance to cisplatin observed in the ∆sky1 strain may be attributable to a decrease of apoptosis and an increase of mitophagy.
Freeblock Scheduling Outside of Disk Firmware

Freeblock scheduling replaces a disk drive’s rotational latency delays with useful background media transfers, potentially allowing background disk I/O to occur with no impact on foreground service times. To do so, a freeblock scheduler must be able to very accurately predict the service time components of any given disk request — the necessary accuracy was not previously considered achievable outside of disk firmware. This paper describes the design and implementation of a working external freeblock scheduler running either as a user-level application atop Linux or inside the FreeBSD kernel. This freeblock scheduler can give 15% of a disk’s potential bandwidth (over 3.1MB/s) to a background disk scanning task with almost no impact (less than 2%) on the foreground request response times. This can increase disk bandwidth utilization by over 6 .
The limited effect of increasing educational attainment on childlessness trends in twentieth-century Europe, women born 1916–65

During the twentieth century, trends in childlessness varied strongly across European countries while educational attainment grew continuously across them. Using census and large-scale survey data from 13 European countries, we investigated the relationship between these two factors among women born between 1916 and 1965. Up to the 1940 birth cohort, the share of women childless at age 40+ decreased universally. Afterwards, the trends diverged across countries. The results suggest that the overall trends were related mainly to changing rates of childlessness within educational groups and only marginally to changes in the educational composition of the population. Over time, childlessness levels of the medium-educated and high-educated became closer to those of the low-educated, but the difference in level between the two better educated groups remained stable in Western and Southern Europe and increased slightly in the East.
Performance analysis of efficient coding schemes for wireless sensor networks

Energy consumption in sensor nodes and Link reliability are two of the major challenges in Wireless Sensor Networks (WSNs). The data exchanged between nodes and base station are vulnerable to corruption by errors induced by random noise, signal fading and other factors. In this regard, error control coding (ECC) is an efficient technique used to increase link reliability and to reduce the required transmitted power. In this context, the choice of energy efficient ECC with a suitable modulation scheme is a crucial task at the link and physical layer of wireless sensor networks to improve their lifetime. Since the WSNs are energy constraint in nature, both the probability of bit error rate (BER) and power consumption have to be taken into account. A performance analysis of error control coding schemes referring to BPSK modulation through a Gaussian channel (AWGN) is presented in this paper. Our results show that the RS(31,21) outperforms other ECC schemes and can be the optimal choice for wireless sensor network environment.
Renal Hemodynamic and Morphological Changes after 7 and 28 Days of Leptin Treatment: The Participation of Angiotensin II via the AT1 Receptor

The role of hyperleptinemia in cardiovascular diseases is well known; however, in the renal tissue, the exact site of leptin’s action has not been established. This study was conducted to assess the effect of leptin treatment for 7 and 28 days on renal function and morphology and the participation of angiotensin II (Ang II), through its AT1 receptor. Rats were divided into four groups: sham, losartan (10 mg/kg/day, s.c.), leptin (0.5 mg/kg/day for the 7 days group and 0.25 mg/kg/day for the 28 days group) and leptin plus losartan. Plasma leptin, Ang II and endothelin 1 (ET-1) levels were measured using an enzymatic immuno assay. The systolic blood pressure (SBP) was evaluated using the tail-cuff method. The renal plasma flow (RPF) and the glomerular filtration rate (GFR) were determined by p-aminohippuric acid and inulin clearance, respectively. Urinary Na+ and K+ levels were also analyzed. Renal morphological analyses, desmin and ED-1 immunostaining were performed. Proteinuria was analyzed by silver staining. mRNA expression of renin-angiotensin system (RAS) components, TNF-α and collagen type III was analyzed by quantitative PCR. Our results showed that leptin treatment increased Ang II plasma levels and progressively increased the SBP, achieving a pre-hypertension state. Rats treated with leptin 7 days showed a normal RPF and GFR, but increased filtration fraction (FF) and natriuresis. However, rats treated with leptin for 28 showed a decrease in the RPF, an increase in the FF and no changes in the GFR or tubular function. Leptin treatment-induced renal injury was demonstrated by: glomerular hypertrophy, increased desmin staining, macrophage infiltration in the renal tissue, TNF-α and collagen type III mRNA expression and proteinuria. In conclusion, our study demonstrated the progressive renal morphological changes in experimental hyperleptinemia and the interaction between leptin and the RAS on these effects.
Understanding complex infrastructure systems: the case of SimPort-MV2

Planning and design of infrastructures is a complicated process, which is caused by the complexity of the subject matter. The theory of Complex Adaptive Systems offers insights that can be of use in the design process. However, translating theory into practice is difficult. Gaming is proposed as a tool to bridge this gap by simulating complex adaptive systems. The objective of the paper is to analyze whether gaming can simulate the behavior of a complex adaptive system. We use the game SimPort-MV2 as a case study. Based on this example, we conclude that games can simulate complex adaptive systems. However, we raise specific concerns about the validity of the outcome and use of the game.
Analysis of distributed peak power tracking in photovoltaic systems

It has been demonstrated that performing localized maximum peak power tracking (MPPT) on each photovoltaic (PV) panel, instead of using a single MPPT controller across the PV string can substantially increase the total harvested power, since each panel experiences unique illumination and temperature conditions. In this work, the effect of the dc-dc converter efficiency on the power savings from distributed MPPT (DMPPT) is analyzed for a wide range of test cases and different PV panel parameters. The benefit of DMPPT for a practical system is shown to be up to 25% for a standard deviation of σ= 0.2. A set of modular hardware-based PV panel emulators (ePVs) is presented. The ePVs can be programmed to match the unique i/v curves of real panels under various conditions and can therefore be used to optimize future DMPPT systems.
From cognitive models to neurofuzzy systems—the mind space approach

Phenomenological theory based on simple concepts related to human cognition is introduced. These concepts are directly related to neurophysiological brain events but may also be extended to explain higher cognitive functions realized by the mind. This theory on the one hand solves fundamental problems in cognitive sciences, explaining puzzling behavior of human conscious experience, and on the other hand leads to useful models of mind in form of neurofuzzy systems. Such systems can compete in pattern recognition and classification tasks with neural networks and can compete in reasoning tasks with the expert systems.
Three-Dimensional Interaction of a Large Number of Dense DEP Particles on a Plane Perpendicular to an AC Electrical Field †

The interaction of dielectrophoresis (DEP) particles in an electric field has been observed in many experiments, known as the “particle chains phenomenon”. However, the study in 3D models (spherical particles) is rarely reported due to its complexity and significant computational cost. In this paper, we employed the iterative dipole moment (IDM) method to study the 3D interaction of a large number of dense DEP particles randomly distributed on a plane perpendicular to a uniform alternating current (AC) electric field in a bounded or unbounded space. The numerical results indicated that the particles cannot move out of the initial plane. The similar particles (either all positive or all negative DEP particles) always repelled each other, and did not form a chain. The dissimilar particles (a mixture of positive and negative DEP particles) always attracted each other, and formed particle chains consisting of alternately arranged positive and negative DEP particles. The particle chain patterns can be randomly multitudinous depending on the initial particle distribution, the electric properties of particles/fluid, the particle sizes and the number of particles. It is also found that the particle chain patterns can be effectively manipulated via tuning the frequency of the AC field and an almost uniform distribution of particles in a bounded plane chip can be achieved when all of the particles are similar, which may have potential applications in the particle manipulation of microfluidics.
Sign language recognition using sub-units

This paper discusses sign language recognition using linguistic sub-units. It presents three types of sub-units for consideration; those learnt from appearance data as well as those inferred from both 2D or 3D tracking data. These sub-units are then combined using a sign level classifier; here, two options are presented. The first uses Markov Models to encode the temporal changes between sub-units. The second makes use of Sequential Pattern Boosting to apply discriminative feature selection at the same time as encoding temporal information. This approach is more robust to noise and performs well in signer independent tests, improving results from the 54% achieved by the Markov Chains to 76%.
Visualization of evolutionary process in genetic programming

Genetic programming (GP) is a process of finding solutions of a problem through the evolution of population of computer programs to solve that problem. As the pattern of searching for solutions in a problem landscape can be quite complicate, it is difficult to explain, in many cases, some phenomena that happened during the evolutionary process. This work describes an attempt to visualize that evolutionary process based on a case study of using GP to solve a problem in robot learning. There are many parameters in the system that affected its performance. We are especially interested in how the genetic operations affected individuals in the population. The result from “understanding” of the evolutionary process via visualization has been used to explain some phenomena in our GP experiments.
Experimental Analysis of a Wireless Sensor Network Setup Strategy Provided by an Agent-Oriented Middleware

This paper presents simulation results of a setup strategy for wireless sensor networks, based on an agent-oriented middleware. A great problem that has to be tackled in sensor networks is how to setup them to provide the data required from the user with a minimal overhead. Having this goal in mind, the proposed approach abstracts the network setup as missions, which are handled within the network by intelligent agents that disseminate and divide the work related to the missions. Several experiments using this approach are provided, showing its efficiency and the low overhead that it imposes to the network.
Evacuation shelter and route selection based on multi-objective optimization approach

Evacuation shelter and route selection are indispensable parts of emergency planning. An efficient plan can effectively evacuate people from a dangerous place to a safer location. Meanwhile, it is crucial to improve risk management. This article presents a multi-objective optimization algorithm based on social media and GIS to optimize shelter usage and personnel distribution considering social relationship. The proposed algorithm is examined using a case study for the Zhongguancun district in Beijing. The district is modeled by the graph theory. Traffic route data and population distribution are synthesized to form a risk map. Furthermore, the Floyd-Warshall algorithm is adopted to find a shortest path route in order to relocate evacuees to a safer place effectively. Efficiency, fairness and social relation are taken into consideration in this context.
Flexible Spoken Dialogue System based on User Models and Dynamic Generation of VoiceXML Scripts

We realize a telephone-based collaborative natural language dialogue system. Since natural language involves very various expressions, a large number of VoiceXML scripts need to be prepared to handle all possible input patterns. We realize flexible dialogue management for various user utterances by generating VoiceXML scripts dynamically. Moreover, we address appropriate user modeling in order to generate cooperative responses to each user. Specifically, we set up three dimensions of user models: skill level to the system, knowledge level on the target domain and the degree of hastiness. The models are automatically derived by decision tree learning using real dialogue data collected by the system. Experimental evaluation shows that the cooperative responses adapted to individual users serve as good guidance for novice users without increasing the dialogue duration for skilled users.
Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: elmar.lang@biologie.uni-regensburg.de