Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimators for unnormalized statistical models based on self density ratio

A wide family of consistent estimators is introduced for unnormalized statistical models. They do not need normalization of the probability density function (PDF) because they are based on the density ratio between the same PDF at different points; the multiplicative normalization constant is canceled there. We construct a family of estimators based on pair-wise comparison of density ratio and derive several estimators as its special cases. The family includes score matching as its parameter limit and outperforms score matching for the optimal value of the parameter. We share the idea of random transformations with contrastive divergence whereas we do not assume Markov chain and obtain consistent deterministic estimators by analytic averaging.
Posttraining Ablation of Adult-Generated Olfactory Granule Cells Degrades Odor–Reward Memories

Proliferation of neural progenitor cells in the subventricular zone leads to the continuous generation of new olfactory granule cells (OGCs) throughout life. These cells synaptically integrate into olfactory bulb circuits after ∼2 weeks and transiently exhibit heightened plasticity and responses to novel odors. Although these observations suggest that adult-generated OGCs play important roles in olfactory-related memories, global suppression of olfactory neurogenesis does not typically prevent the formation of odor–reward memories, perhaps because residual OGCs can compensate. Here, we used a transgenic strategy to selectively ablate large numbers of adult-generated OGCs either before or after learning in mice. Consistent with previous studies, pretraining ablation of adult-generated OGCs did not prevent the formation of an odor–reward memory, presumably because existing OGCs can support memory formation in their absence. However, ablation of a similar cohort of adult-generated OGCs after training impaired subsequent memory expression, indicating that if these cells are available at the time of training, they play an essential role in subsequent expression of odor–reward memories. Memory impairment was associated with the loss of adult-generated OGCs that were >10 d in age and did not depend on the developmental stage in which they were generated, suggesting that, once sufficiently mature, OGCs generated during juvenility and adulthood play similar roles in the expression of odor–reward memories. Finally, ablation of adult-generated OGCs 1 month after training did not produce amnesia, indicating that adult-generated OGCs play a time-limited role in the expression of odor–reward memories.
Studying the Relationship Between Managerial Skills and Efficiency of Bank Branches

Reaserch as " Studying The Relationship Between Managerial Skills And Efficiency Of Bank Branches " was performed. In order to study management skills in this research, Katz model was used. Statistical Society of this research was all the branches in the Tehran city ,that those who, at least one year has worked as masters of bank and among these branches, with cluster sampling method 43 Branch randomly selected as example statistical research. We used questionnaire for data gathering managerial skills and also documents extracted in mellat bank to calculate the branch efficiency. This research was formed to investigate a main hypothesis and three sub-hypothesis and in the results section with using the Pearson correlation coefficients of all these hypothesis were confirmed. Results showed that there are directly and positively relationship between managerial skills and efficiency in the branches and also result of data analysis revealed that there are positively relationship between components of these skills and efficiency ultimately by using lisrel soft ware conceptual model and research suggestions was presented to improve the current situation
Extragalactic Transients in the Era of Wide-Field Radio Surveys. I. Detection Rates and Light Curve Characteristics

The impending era of wide-field radio surveys has the potential to revolutionize our understanding of astrophysical transients. Here we evaluate the prospects of a wide range of planned and hypothetical radio surveys using the properties and volumetric rates of known and hypothetical classes of extragalactic synchrotron radio transients (e.g., on- and off-axis gamma-ray bursts [GRB], supernovae, tidal disruption events [TDE], compact object mergers). Utilizing these sources and physically motivated considerations we assess the allowed phase-space of radio luminosity and peak timescale for extragalactic transients. We also include for the first time effects such as redshift evolution of the rates, K-corrections, and non-Euclidean luminosity distance, which affect the detection rates of the most sensitive surveys. The number of detected events is calculated by means of a Monte Carlo method, using the various survey properties (depth, cadence, area) and realistic detection criteria that include a cut on the minimum variability of the transients during the survey and an assessment of host galaxy contamination. Near-term GHz frequency surveys (ASKAP/VAST, Very Large Array Sky Survey) will detect few events: <~30-50 on- and off-axis long GRBs and off-axis tidal disruption events, and ~10-20 neutron star binary mergers if ~1% of the mergers result in a stable millisecond magnetar. Low-frequency surveys (e.g., LOFAR) are unlikely to detect any transients, while a hypothetical large-scale mm survey may detect ~40 on-axis long GRBs. On the other hand, SKA surveys at ~0.1-1 GHz have the potential to uncover thousands of transients, mainly on- and off-axis long GRBs, on-axis short GRBs, off-axis TDEs, and neutron star binary mergers with magnetar remnants.
Majorana neutrino mixing

The most natural see-saw explanation of the smallness of neutrino masses is based on the assumption that the total lepton number is violated at large scale and neutrinos with definite masses are Majorana particles. In this review we consider in detail the difference between Dirac and Majorana neutrino mixing and the possibilities of revealing the Majorana nature of neutrinos with definite masses.
Omega-3 fatty acids (fish-oil) and depression-related cognition in healthy volunteers

Abstract Omega-3 polyunsaturated fatty acid (n-3 PUFA) supplementation may be beneficial in the treatment of several psychiatric disorders, including depression. A small number of studies have suggested that there may also be cognitive and mood effects in healthy samples. The purpose of the present study was to investigate the effects of n-3 PUFA on depression-relevant cognitive functioning in healthy individuals. Fifty-four healthy university students were randomized to receive either n-3 PUFA supplements or placebo for 4 weeks in a double-blind design. The test battery included measures of cognitive reactivity, attention, response inhibition, facial emotion recognition, memory and risky decision-making. Results showed few effects of n-3 PUFAs on cognition and mood states. The n-3 PUFA group made fewer risk-averse decisions than the placebo group. This difference appeared only in non-normative trials of the decision-making test, and was not accompanied by increased impulsiveness. N-3 PUFAs improved scores on the control/perfectionism scale of the cognitive reactivity measure. No effects were found on the other cognitive tasks and no consistent effects on mood were observed. The present findings indicate that n-3 PUFA supplementation may have a selective effect on risky decision making in healthy volunteers, which is unrelated to impulsiveness.
RegViz: visual debugging of regular expressions

Regular expressions are a widely used programming technique, but seem to be neglected by software engineering research. Encoding complex string parsing in a very compact notation, their complexity and compactness, however, introduce particular challenges with respect to program comprehension. In this paper, we present RegViz, an approach to visually augment regular expressions without changing their original textual notation. The visual encoding clarifies the structure of the regular expressions and clearly discerns included tokens by function. The approach also provides advanced visual highlighting of matches in a sample text and defining test cases therein. We implemented RegViz as a Web-based tool for JavaScript regular expressions. Expert feedback suggests that the approach is intuitive to apply and increases the readability of regular expressions.
Remission of Cognitive Deficits in Parkinson's Disease: Recovery from a Nonamnestic Mild Cognitive Impairment or Psychiatric Symptoms Remission?

Mild cognitive impairment is a clinical condition more frequent in patients with Parkinson's disease than in general population. The nonamnestic presentations, usually characterized by executive dysfunction, are most prevalent. We present a case report of a Parkinson's disease patient diagnosed with nonamnestic mild cognitive impairment that showed complete remission of cognitive symptoms after one year. We discuss the possible causes for the remission, focusing on the treatment of medical conditions such as a major depressive episode and vitamin B12 deficiency, in addition to the change of pharmacological treatment. In a third assessment, cognitive performance remained normal. The case report highlights the importance of controlling clinical comorbidities on the assessment and followup of mild cognitive impairment, especially on Parkinson's disease.
Towards Financial Planning as a Service

The financial crisis has recalled the importance of proper financial planning. Companies which are organized as a multitude of legal entities are in particular affected by planning irregularities. To optimize the financial planning process and to cope with the challenges, we propose our service model "Financial Planning as a Service" (FiPlaaS). This approach allows companies to redesign their planning processes according to SOA principles and to achieve substantial improvements in performance.
A Parallel Programming Model for a Multi-FPGA Multiprocessor Machine by

Recent research has shown that FPGAs can execute certain applications significantly faster than state-of-the-art processors. The penalty is the loss of generality, but the reconfigurability of FPGAs allows them to be reprogrammed for other applications. Therefore, an efficient programming model and a flexible design flow are paramount for FPGA technology to be more widely accepted. In this thesis, a lightweight subset implementation of the MPI standard, called TMD-MPI, is presented. TMD-MPI provides a programming model capable of using multiple-FPGAs and embedded processors while hiding hardware complexities from the programmer, facilitating the development of parallel code and promoting code portability. A message-passing engine (TMD-MPE) is also developed to encapsulate the TMD-MPI functionality in hardware. TMD-MPE enables the communication between hardware engines and embedded processors. In addition, a Network-on-Chip is designed to enable intra-FPGA and inter-FPGA communications. Together, TMD-MPI, TMD-MPE and the network provide a flexible design flow for Multiprocessor System-on-Chip design.
Naive Bayes for regression

Despite its simplicity, the naive Bayes learning scheme performs well on most classification tasks, and is often significantly more accurate than more sophisticated methods. Although the probability estimates that it produces can be inaccurate, it often assigns maximum probability to the correct class. This suggests that its good performance might be restricted to situations where the output is categorical. It is therefore interesting to see how it performs in domains where the predicted value is numeric, because in this case, predictions are more sensitive to inaccurate probability estimates. This paper shows how to apply the naive Bayes methodology to numeric prediction (i.e., regression) tasks by modeling the probability distribution of the target value with kernel density estimators, and compares it to linear regression, locally weighted linear regression, and a method that produces “model trees”—decision trees with linear regression functions at the leaves. Although we exhibit an artificial dataset for which naive Bayes is the method of choice, on real-world datasets it is almost uniformly worse than locally weighted linear regression and model trees. The comparison with linear regression depends on the error measure: for one measure naive Bayes performs similarly, while for another it is worse. We also show that standard naive Bayes applied to regression problems by discretizing the target value performs similarly badly. We then present empirical evidence that isolates naive Bayes’ independence assumption as the culprit for its poor performance in the regression setting. These results indicate that the simplistic statistical assumption that naive Bayes makes is indeed more restrictive for regression than for classification.
HOBACGEN: database system for comparative genomics in bacteria.

We present here HOBACGEN, a database system devoted to comparative genomics in bacteria. HOBACGEN contains all available protein genes from bacteria, archaea, and yeast, taken from SWISS-PROT/TrEMBL and classified into families. It also includes multiple alignments and phylogenetic trees built from these families. The database is organized under a client/server architecture with a client written in Java, which may run on any platform. This client integrates a graphical interface allowing users to select families according to various criteria and notably to select homologs common to a given set of taxa. This interface also allows users to visualize multiple alignments and trees associated to families. In tree displays, protein gene names are colored according to the taxonomy of the corresponding organisms. Users may access all information associated to sequences and multiple alignments by clicking on genes. This graphic tool thus gives a rapid and simple access to all data required to interpret homology relationships between genes and distinguish orthologs from paralogs. Instructions for installation of the client or the server are available at http://pbil.univ-lyon1. fr/databases/hobacgen.html.
Wavelets and Multiscale Methods in Image Processing

Multiscale methods have become an important tool in mathematical analysis and applications, in particular in the area of signal and image processing as well as in numerical analysis. The mathematical background has been reinforced with the introduction of wavelet bases in the mid-1980's. Our goal is to give a short survey of these methods and show their speciic advantages, as well as their inherent limitations for applications to image processing. We shall in particular discuss the problems of denoising and image compression.
Phosphorus responses of C 3 and C 4 species

An hypothesis was formulated that phosphorus (P) partitioning in tissues of C4 leaves would permit C4 plants to resist P deficiency better than C3 plants. To test this hypothesis, 12 C3, C4, and C3-C4 intermediate species were grown at adequate, deficient, and severely deficient P supply in a solid-phase-buffered sand culture system to characterize photosynthetic and growth responses. Species differed considerably in response to P stress. The growth of C3 species was more sensitive to P supply than C4 species, but C3 and C4 species had similar photosynthetic P use efficiency, and C4 species did not have low leaf P content, contrary to our hypothesis. In fact, leaf photosynthetic rates were not correlated with growth responses. Moncots had lower leaf P content and better maintenance of leaf production under P stress than dicots, because of greater inhibition of branching (dicots) than of tillering (monocots). The most P efficient species in this survey was Brachiaria, a C4 monocot that increased root biomass allocation under stress while maintaining P allocation to the shoot. It is concluded that C4 species are not inherently more P efficient than C3 species, but that monocots are more P efficient than dicots, because of contrasting P and biomass allocation under stress.
Application of a High-speed Stereovision Sensor to 3D Shape Acquisition of Flying Bats

D shape acquisition of fast-moving objects is an emerging area with many potential applications. This paper presents a novel application of 3D acquisition for studying the dynamic external morphology of live bats in flight. The 3D acquisition technique is based on binocular stereovision. Two high-speed (500 fps) calibrated machine vision cameras are employed to capture intensity images from the bats simultaneously, and 3D shape information of the bats is derived from the stereo video recording. Since the high-speed stereovision system and the bat dynamic morphology study application are both novel, it was unknown to what extent the system could perform 3D acquisition of the bats' shapes. We carried out experiments to evaluate the performance of the system using artificial objects in various controlled conditions, and the knowledge gained helped us deploy the system in the on-site data acquisition. Our analysis of the real data demonstrates the feasibility of gathering 3D dynamic measurements on bats' bodies from a few selected feature points and the possibility of recovering dense 3D shapes of bat heads from the stereo video data acquired. Issues are revealed in the 3D shape recovery, most notably related to motion blur and occlusion.
Alzheimer disease in the US population: prevalence estimates using the 2000 census.

CONTEXT Current and future estimates of Alzheimer disease (AD) are essential for public health planning. OBJECTIVE To provide prevalence estimates of AD for the US population from 2000 through 2050. DESIGN Alzheimer disease incidence estimates from a population-based, biracial, urban study, using a stratified random sampling design, were converted to prevalence estimates and applied to US Census Bureau estimates of US population growth. SETTING A geographically defined community of 3 adjacent neighborhoods in Chicago, Ill, applied to the US population. PARTICIPANTS Alzheimer disease incidence was measured in 3838 persons free of AD at baseline; 835 persons were evaluated for disease incidence. Main Outcome Measure Current and future estimates of prevalence of clinically diagnosed AD in the US population. RESULTS In 2000, there were 4.5 million persons with AD in the US population. By 2050, this number will increase by almost 3-fold, to 13.2 million. Owing to the rapid growth of the oldest age groups of the US population, the number who are 85 years and older will more than quadruple to 8.0 million. The number who are 75 to 84 years old will double to 4.8 million, while the number who are 65 to 74 years old will remain fairly constant at 0.3 to 0.5 million. CONCLUSION The number of persons with AD in the US population will continue to increase unless new discoveries facilitate prevention of the disease.
Structure of Sagittarius A* at 86 GHz using VLBI Closure Quantities

At radio wavelengths, images of the compact radio source Sagittarius A* (Sgr A*) in the Galactic center are scatter broadened with a λ2 dependence due to an intervening ionized medium. We present VLBI observations of Sgr A* at 86 GHz using a six station array, including the VLBA antennas at Pie Town, Fort Davis, and Los Alamos, the 12 m antenna at Kitt Peak, and the millimeter arrays at Hat Creek and Owens Valley. To avoid systematic errors due to imperfect antenna calibration, the data were modeled using interferometric closure information. The data are best modeled by a circular Gaussian brightness distribution of FWHM 0.18 ± 0.02 mas. The data are also shown to be consistent with an elliptical model corresponding to the scattering of a point source. The source structure in the north-south direction, which is less well determined than in the east-west direction because of the limited north-south u-v coverage of the array, is constrained to be less than 0.27 mas by these measurements. These results are consistent with extrapolations of intrinsic structure estimates obtained with VLBI at a 7 mm wavelength, assuming the intrinsic size of Sgr A* has a greater dependence than λ0. 9 with wavelength.
Intervention: Reality TV, Whiteness, and Narratives of Addiction

Purpose – Reality TV shows that feature embodied “transformations” are popular, including Intervention, a program that depicts therapeutic recovery from addiction to “health. ” The purpose of this chapter is to address the ways whiteness constitutes narratives of addiction on Intervention. Methodology – This analysis uses a mixed methodology. I conducted a systematic analysis of nine (9) seasons of one hundred and forty-seven (147) episodes featuring one hundred and fifty-seven individual “addicts” (157) and logged details, including race and gender. For the qualitative analysis, I watched each episode more than once (some, I watched several times) and took extensive notes on each episode. Findings – The majority of characters (87%) are white, and the audience is invited to gaze through a white lens that tells a particular kind of story about addiction. The therapeutic model valorized by Intervention rests on neoliberal regimes of self-sufficient citizenship that compel us all toward “health” and becoming “productive” citizens. Such regimes presume whiteness. Failure to comply with an intervention becomes a “tragedy” of wasted whiteness. When talk of racism erupts, producers work to re-frame it in ways that erase systemic racism. Social implications – The whiteness embedded in Intervention serves to justify and reinforce the punitive regimes of controlling African American and Latina/o drug users through the criminal justice system while controlling white drug users through self-disciplining therapeutic regimes of rehab. Originality – Systematic studies of media content consistently find a connection between media representations of addiction and narratives about race, yet whiteness has rarely been the critical focus of addiction.