Miracle-dz/UniFAR-FTUs huggingface dataset:
Pitx3 Is a Critical Mediator of GDNF-Induced BDNF Expression in Nigrostriatal Dopaminergic Neurons

Pitx3 is a critical homeodomain transcription factor for the proper development and survival of mesodiencephalic dopaminergic (mdDA) neurons in mammals. Several variants of this gene have been associated with human Parkinson's disease (PD), and lack of Pitx3 in mice causes the preferential loss of substantia nigra pars compacta (SNc) mdDA neurons that are most affected in PD. It is currently unclear how Pitx3 activity promotes the survival of SNc mdDA neurons and which factors act upstream and downstream of Pitx3 in this context. Here we show that a transient expression of glial cell line-derived neurotrophic factor (GDNF) in the murine ventral midbrain (VM) induces transcription of Pitx3 via NF-κB-mediated signaling, and that Pitx3 is in turn required for activating the expression of brain-derived neurotrophic factor (BDNF) in a rostrolateral (SNc) mdDA neuron subpopulation during embryogenesis. The loss of BDNF expression correlates with the increased apoptotic cell death of this mdDA neuronal subpopulation in Pitx3−/− mice, whereas treatment of VM cell cultures with BDNF augments the survival of the Pitx3−/− mdDA neurons. Most importantly, only BDNF but not GDNF protects mdDA neurons against 6-hydroxydopamine-induced cell death in the absence of Pitx3. As the feedforward regulation of GDNF, Pitx3, and BDNF expression also persists in the adult rodent brain, our data suggest that the disruption of the regulatory interaction between these three factors contributes to the loss of mdDA neurons in Pitx3−/− mutant mice and perhaps also in human PD.
The self-efficacy of special education directors in the state of Texas

CATINA C. HUBBARD THE SELF-EFFICACY OF SPECIAL EDUCATION DIRECTORS IN THE STATE OF TEXAS MAY 2009 The purpose of this study was to examine the self-efficacy of special education directors serving in public schools in the state of Texas. Within the review of literature the following key components were identified: special education administration, selfefficacy theoretical perspective and self-efficacy and outcomes-based research. A nonexperimental design using survey methods was used. The survey was sent to 235 special education directors identified in the Texas Council for Administrators of Special Education 2007-2008 directory. The response rate was 23% of the surveys were completed and returned. Descriptive analysis provided means and standard deviations of the personal, professional and district characteristics of the respondents under study. Inferential analysis was performed to determine which variables significantly co-varied with each of the 8 items on the self-efficacy scale. The Analysis of Variance (ANOVA) included multiple regressions to determine the magnitude of difference and significance for self-efficacy prediction among the variables. Regression analysis was performed to determine which combination of independent variables predicted self-efficacy. Even though this did not indicate significance in predicting self-efficacy among directors of special education it did allow for examination of demographic variables as vi predictors of self-efficacy among special education directors in the state of Texas. This examination did allow for some topics of discussion. The age, gender, and personal health of the special education directors in the study appeared to predict a high level of self-efficacy on the dependent variable, "I believe I can succeed at most any endeavor to which I set my mind. " In addition, the district characteristics of size and NCLB student sub-populations (African American, Hispanic, Economically Disadvantaged, Special Education) did predict a high level of self-efficacy on the dependent variable, "Compared to other people, I can do most tasks very well. " In addition, when examining the general self-efficacy of the special education directors in the study it was found that those directors with five to nine years of experience in the field indicated a higher level of selfefficacy than those directors with zero to five years of experience and those with 10 or more years of experience on two of the eight self-efficacy dependent variables. The two dependent variables noted were, "When facing difficult tasks, I am certain that I will accomplish them" and "In general, I think I can obtain outcomes that are important to me. " Thus those special education directors with five to nine years of experience perceive themselves as possessing a high level of self-efficacy on dependent variables two and three of the New General Self-Efficacy Scale (Chen, Gully, & Eden, 2001). Implications and recommendations for future research were identified.
Minimax Optimal Convex Methods for Poisson Inverse Problems Under  $\ell_{q}$ -Ball Sparsity

In this paper, we study the minimax rates and provide an implementable convex algorithm for Poisson inverse problems under weak sparsity and physical constraints. In particular, we assume the model <inline-formula> <tex-math notation="LaTeX">$y_{i} \sim \mathrm {Poisson}(Ta_{i}^{\top }f^{*})$ </tex-math></inline-formula> for <inline-formula> <tex-math notation="LaTeX">$1 \leq i \leq n$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$T \in \mathbb {R}_{+}$ </tex-math></inline-formula> is the intensity, and we impose weak sparsity on <inline-formula> <tex-math notation="LaTeX">$f^{*} \in \mathbb {R}^{p}$ </tex-math></inline-formula> by assuming <inline-formula> <tex-math notation="LaTeX">$f^{*}$ </tex-math></inline-formula> lies in an <inline-formula> <tex-math notation="LaTeX">$\ell _{q}$ </tex-math></inline-formula>-ball when rotated according to an orthonormal basis <inline-formula> <tex-math notation="LaTeX">$D \in \mathbb {R}^{p \times p}$ </tex-math></inline-formula>. In addition, since we are modeling real-physical systems, we also impose positivity and flux-preserving constraints on the matrix <inline-formula> <tex-math notation="LaTeX">$A = [a_{1}, a_{2},\ldots, a_{n}]^{\top }$ </tex-math></inline-formula> and the function <inline-formula> <tex-math notation="LaTeX">$f^{*}$ </tex-math></inline-formula>. We prove minimax lower bounds for this model, which scale as <inline-formula> <tex-math notation="LaTeX">$R_{q} ({\log p}/{T})^{1 - ({q}/{2})}$ </tex-math></inline-formula> where it is noticeable that the rate depends on the intensity <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> and not the sample size <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>. We also show that an <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-based regularized least-squares estimator achieves this minimax lower bound, provided a suitable restricted eigenvalue condition is satisfied. Finally, we prove that provided <inline-formula> <tex-math notation="LaTeX">$n \geq \tilde {K} \log p$ </tex-math></inline-formula> where <inline-formula> <tex-math notation="LaTeX">$\tilde {K} = \Theta (R_{q} ({\log p}/{T})^{- ({q}/{2})})$ </tex-math></inline-formula> represents an approximate sparsity level, and our restricted eigenvalue condition and physical constraints are satisfied for random bounded ensembles. We also provide numerical experiments that validate our mean-squared error bounds. Our results address a number of open issues from prior work on Poisson inverse problems that focuses on strictly sparse models and does not provide guarantees for convex implementable algorithms.
Best-First Frontier Search with Delayed Duplicate Detection

Best-first search is limited by the memory needed to store the Open and Closed lists, primarily to detect duplicate nodes. Magnetic disks provide vastly more storage, but random access of a disk is extremely slow. Instead of checking generated nodes immediately against existing nodes in a hash table, delayed duplicate detection (DDD) appends them to a file, then periodically removes the duplicate nodes using only sequential disk accesses. Frontier search saves storage in a best-first search by storing only the Open list and not the Closed list. The main contributions of this paper are to provide a scalable implementation of DDD, to combine it with frontier search, and to extend it to more general best-first searches such as A*. We illustrate these ideas by performing complete breadth-first searches of sliding-tile puzzles up to the 3×5 Fourteen Puzzle. For the 4-peg Towers of Hanoi problem, we perform complete searches with up to 20 disks, searching a space of over a trillion nodes, and discover a surprising anomaly concerning the problem-space diameter of the 15 and 20-disk problems. We also verify the presumed optimal solution lengths for up to 24 disks. In addition, we implement A* with DDD on the Fifteen Puzzle. Finally, we present a scalable implementation of DDD based on hashing rather than sorting.
Methods for acceleration of learning process of Reinforcement Learning Neuro-Fuzzy Hierarchical Politree model

This paper presents two methods for accelerating the learning process of Reinforcement Learning - Neuro-Fuzzy Hierarchical Politree model (RL-NFHP): policy Q-DC-Roulette and early stopping. This model is used to provide an agent with intelligence, making it autonomous, due to the capacity of ratiocinate (infer actions) and learning, acquired knowledge through interaction with the environment. The characteristics of the RL-NFHP allow the agent to learn automatically its structure and action for each state. The RL-NFHP model was evaluated in an application benchmark known in the area of autonomous agents: car mountain problem. The results demonstrate the acceleration of learning process and the potential of this model, which works without any prior information, such as number of rules, rules of specification, or number of partitions that the input space should possess.
CARBON ISOTOPE FRACTIONATION IN PROTOPLANETARY DISKS

We investigate the gas-phase and grain-surface chemistry in the inner 30 AU of a typical protoplanetary disk (PPD) using a new model which calculates the gas temperature by solving the gas heating and cooling balance and which has an improved treatment of the UV radiation field. We discuss inner-disk chemistry in general, obtaining excellent agreement with recent observations which have probed the material in the inner regions of PPDs. We also apply our model to study the isotopic fractionation of carbon. Results show that the fractionation ratio, 12C/13C, of the system varies with radius and height in the disk. Different behavior is seen in the fractionation of different species. We compare our results with 12C/13C ratios in the solar system comets, and find a stark contrast, indicative of reprocessing.
Sentiment Analysis of Students' Comment using Long-Short Term Model

Objectives: Teacher’s evaluation in education system is quite important to improve the learning experience ininstitutions. For this purpose, sentiment analysis model is developedto identify the student sentiments from the piece of text. Methods/ Statistical Analysis: Long Short-Term Memory Model (LSTM) is used for analyzing the sentiments expressed by students through textual feedback. For this purpose, dataset has been built through student’s feedback and then divided into 70% and 30% for training and testing. The proposed model has been trained using softmax and adam along with drop out values 0.1 and 0.2. Obtained results showed that our model provides 99%, and 90% accuracy over training and validation with 0.2 and 0.5 losses respectively. Findings: It was found that proposed model provides an efficient way for sentiment analysis for teacher’s evaluation. Model used input as word embedding over the LSTM for mapping the words. Andmoreover, the model is collected significant semantic and syntactic information by implementing pre-trained word vector model. Hence, this model has the prospective to overcome several flaws in traditional methods e.g., bag-of-words, n-gram, Naïve Bayes and SVM models where order and information about word is vanished. The experimental results show that the model can achieve state-ofthe-art accuracy on student feedback dataset. Application/Improvements: The study helps for improving the quality of teaching in education system. And moreover,it will be upgrade by increasing the data samples of neutral comments in dataset. *Author for correspondence
A theoretical framework for capacity-achieving multi-user waterfilling in OFDMA

This paper introduces a theoretical framework for subcarrier and power allocation algorithms in rate-adaptive OFDMA systems. The focal point is locating “capacity-achieving” waterlevels for a given allocation in order to minimize the distance to the boundary of the capacity region. We prove that it is possible to restrict the choice of waterlevels to an optimality polyhedron. This paper introduces weighted subcarrier allocations which have a natural correspondence to this polyhedron, and are therefore promising candidates for the above problem. Based on the introduced theory, a low-complexity algorithm is designed and shown to reliably locate capacity-achieving waterlevels.
An Educational Resource Retrieval Mechanism Based on Lucene and Topic Index

In order to improve the retrieval performance in the educational resource database, this paper designs an retrieval mechanism called ERRM based on Lucene and topic index. Firstly, this paper introduces the full-text search engine – Lucene, and studies in depth its internal implementation. Then by the way of the topic index which is learned by the topic model, this paper researches how to successfully expand query semantics. Based on Lucene and topic index, this paper proposes a new retrieval mechanism for educational resources. After expanding the user query, the retrieval mechanism submits the enriched query condition to Lucene for full-text retrieval. The experimental results show that the proposed mechanism could obviously improve the retrieval performance and precision.
Rapid evolution of quantitative traits: theoretical perspectives

An increasing number of studies demonstrate phenotypic and genetic changes in natural populations that are subject to climate change, and there is hope that some of these changes will contribute to avoiding species extinctions (‘evolutionary rescue’). Here, we review theoretical models of rapid evolution in quantitative traits that can shed light on the potential for adaptation to a changing climate. Our focus is on quantitative‐genetic models with selection for a moving phenotypic optimum. We point out that there is no one‐to‐one relationship between the rate of adaptation and population survival, because the former depends on relative fitness and the latter on absolute fitness. Nevertheless, previous estimates that sustainable rates of genetically based change usually do not exceed 0.1 haldanes (i.e., phenotypic standard deviations per generation) are probably correct. Survival can be greatly facilitated by phenotypic plasticity, and heritable variation in plasticity can further speed up genetic evolution. Multivariate selection and genetic correlations are frequently assumed to constrain adaptation, but this is not necessarily the case and depends on the geometric relationship between the fitness landscape and the structure of genetic variation. Similar conclusions hold for adaptation to shifting spatial gradients. Recent models of adaptation in multispecies communities indicate that the potential for rapid evolution is strongly influenced by interspecific competition.
Dali/FSSP classification of three-dimensional protein folds

The FSSP database presents a continuously updated structural classification of three-dimensional protein folds. It is derived using an automatic structure comparison program (Dali) for the all-against-all comparison of over 6000 three-dimensional coordinate sets in the Protein Data Bank (PDB). Sequence-related protein families are covered by a representative set of 813 protein chains. Hierachical clustering based on structural similarities yields a fold tree that defines 253 fold classes. For each representative protein chain, there is a database entry containing structure-structure alignments with its structural neighbours in the PDB. The database is accessible online through World Wide Web browsers and by anonymous ftp (file transfer protocol). The overview of fold space and the individual data sets provide a rich source of information for the study of both divergent and convergent aspects of molecular evolution, and define useful test sets and a standard of truth for assessing the correctness of sequence-sequence or sequence-structure alignments.
From Data to Speech: a Generic Approach Ipo: Center for Research on User-system Interaction Ipo: Center for Research on User-system Interaction

We present a combination of techniques for the creation of diierent data-to-speech systems. These are implemented in a generic system called D2S, which is suuciently general to be used as a basis for applications in diierent languages and domains. Language and speech generation in D2S is done by means of techniques which are aimed at nding a balance between theoretical attractiveness and practical usability. In our hybrid language generation technique the use of syntactically enriched templates is guided by knowledge of the discourse context, and for speech generation prerecorded phrases are combined in a prosodically sophisticated manner, using linguistic information provided by language generation. This makes it possible to create linguistically sound but eecient systems with a high quality language and speech output.
Dicarboxylic acids, ketocarboxylic acids, α-dicarbonyls, fatty acids and benzoic acid in PM 2.5 aerosol collected during CAREBeijing-2007: an effect of traffic restriction on air quality

Abstract. Thirty water-soluble organic species, including dicarboxylic acids, ketocarboxylic acids, α-dicarbonyls, fatty acids and benzoic acid were determined as well as organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC) in PM2.5 samples collected during the Campaign of Air Quality Research in Beijing 2007 (CAREBeijing-2007) in the urban and suburban areas of Beijing. The objective of this study is to identify the influence of traffic emissions and regional transport to the atmosphere in Beijing during summer. PM2.5 samples collected with or without traffic restriction in Beijing are selected to evaluate the effectiveness of local traffic restriction measures on air pollution reduction. The average concentrations of the total quantified bifunctional organic compounds (TQBOCs), total fatty acids and benzoic acid during the entire sampling period were 1184±241, 597±159 and 1496±511 ng m−3 in Peking University (PKU), and 1050±303, 475±114 and 1278±372 ng m−3 in Yufa, Beijing. Oxalic acid (C2) was found as the most abundant dicarboxylic acid at PKU and Yufa followed by phthalic acid (Ph). A strong even carbon number predominance with the highest level at stearic acid (C18:0), followed by palmitic acid (C16:0) was found for fatty acids. According to the back trajectories modeling results, the air masses were found to originate mainly from the northeast, passing over the southeast or south of Beijing (heavily populated, urbanized and industrialized areas), during heavier pollution events, whereas they are mainly from the north or northwest sector (mountain areas without serious anthropogenic pollution sources) during less pollution events. The data with wind only from the same sector (minimizing the difference from regional contribution) but with and without traffic restriction in Beijing were analyzed to evaluate the effectiveness of local traffic restriction measures on the reduction of local air pollution in Beijing. The results suggested that the traffic restriction measures can reduce the air pollutants, but the decrease of pollutants is generally smaller in Yufa compared to that in PKU. Moreover, an enhancement of EC value indicates more elevated primary emissions in Yufa during restriction periods than in non-restriction periods. This study demonstrates that even when primary exhaust was controlled by traffic restriction, the contribution of secondary organic species formed from photochemical processes was critical with long-range atmospheric transport of pollutants.
Integration of Code Scheduling, Memory Allocation, and Array Binding for Memory-Access Optimization

In many embedded systems, particularly those with high data computations, the delay of memory access is one of the major bottlenecks in the system's performance. It has been known that there are high variations in memory-access delays depending on the ways of designing memory configurations and assigning arrays to memories. Furthermore, embedded-DRAM technology that provides efficient access modes is actively being developed, possibly becoming a mainstream in future embedded-system design. In that context, in this paper, the authors propose an effective solution to the problem of (embedded DRAM) memory allocation and mapping in memory-access-code generation with the objective of minimizing the total memory-access time. Specifically, the proposed approach, called memory-access-code optimization (MACCESS-opt), solves the three problems simultaneously: 1) determination of memories; 2) mapping of arrays to memories; and 3) scheduling of memory-access operations, so that the use of DRAM-access modes is maximized while satisfying the storage size constraint of embedded systems. Experimental data on a set of benchmark designs are provided to show the effectiveness of the proposed integrated approach. In short, MACCESS-opt reduces the total memory-access latency by over 18%, from which the authors found that the memory mapping and scheduling techniques in MACCESS-opt contribute about 12% and 6% reductions of the total memory-access latency, respectively
Dynamics of Sheep Production in Brazil

Sheep production is present on all continents and has been practiced in Brazil since the colonization. In this study, the multitemporal dynamics of sheep production in Brazil is examined using official government data (Brazilian Institute for Geography and Statistics-IBGE) from 1976 to 2010. Maps of flock growth rates and growth acceleration maps by municipality were elaborated. The Southern states are seen to show a reduction in production mainly due to the wool crisis in the 1970s and 80s. The Northeast is seen to be important for meat production. More recently, centerwest and northern states have shown an increase in growth rates but this is still incipient. The maps of growth, acceleration and midpoint for sheep production showed a noticeable return to an increase in production in the South in recent years. The midpoint of production flow was in the northeast direction, which has stagnated. There was great dynamics in sheep production over the whole Brazilian territory, which affected supply chains due to the expansion of domestic and foreign markets. Areas with higher fluctuations in production are more vulnerable in terms of investment policies.