Miracle-dz/UniFAR-FTUs huggingface dataset:
Innovation Complexity and the Sequence of Innovating Stages

In case histories of innovation adoption by local governments, seven innovating stages orfunctionsfrom need identification to diffusion were coded on time ofoccurrence. A method using gamma was applied to measure the time sequence offunctions at each site, and their separation from other functions. These data were used to test the hypothesis that the stages will appear more overlapping and the innovating process more "disorderly "for innovations that are more complex. The hypothesis was supported for a measure of technical complexity but not for one of organizational complexity. The innovating process was found to be most orderly when a technically simple innovation was neither "custom-made" nor copied "ready-made, " but was modified or adapted. When the time sequences at each site were grouped into patterns such as problem-oriented versus solution-oriented, few differences on effectiveness were found, although one contingent effect was observed. Perhaps any single-factor explanation of effectiveness is bound to fall short.
How Do People Choose Their Commuting Mode? An Evolutionary Approach to Transport Choices

The issue of transportation is of primary importance in our societies. A large share of greenhouse gases is generated by the transport sector, and road casualties are one among the most common causes of death. In the present work, we study commuter choice between alternative transport modes using an evolutionary- game model, wherein commuters can choose between using their private car or taking the bus. We examine the possible dynamics that can emerge in a homogeneous urban population, where agents are boundedly rational and imitate the others. We obtain a different number of equilibria depending on the values of the parameters of the model. We carry out comparative-static exercises and examine possible policy measures that can be implemented in order to modify the agents' payoff, and consequently the equilibria of the system, leading the society towards more sustainable transportation patterns.
Online Defect Prediction for Imbalanced Data

Many defect prediction techniques are proposed to improve software reliability. Change classification predicts defects at the change level, where a change is the modifications to one file in a commit. In this paper, we conduct the first study of applying change classification in practice. We identify two issues in the prediction process, both of which contribute to the low prediction performance. First, the data are imbalanced -- there are much fewer buggy changes than clean changes. Second, the commonly used cross-validation approach is inappropriate for evaluating the performance of change classification. To address these challenges, we apply and adapt online change classification, resampling, and updatable classification techniques to improve the classification performance. We perform the improved change classification techniques on one proprietary and six open source projects. Our results show that these techniques improve the precision of change classification by 12.2-89.5% or 6.4 -- 34.8 percentage points (pp.) on the seven projects. In addition, we integrate change classification in the development process of the proprietary project. We have learned the following lessons: 1) new solutions are needed to convince developers to use and believe prediction results, and prediction results need to be actionable, 2) new and improved classification algorithms are needed to explain the prediction results, and insensible and unactionable explanations need to be filtered or refined, and 3) new techniques are needed to improve the relatively low precision.
Latent Variable Models for Longitudinal Data with Multiple Continuous Outcomes

Summary. Multiple outcomes are often used to properly characterize an effect of interest. This paper proposes a latent variable model for the situation where repeated measures over time are obtained on each outcome. These outcomes are assumed to measure an underlying quantity of main interest from different perspectives. We relate the observed outcomes using regression models to a latent variable, which is then modeled as a function of covariates by a separate regression model. Random effects are used to model the correlation due to repeated measures of the observed outcomes and the latent variable. An EM algorithm is developed to obtain maximum likelihood estimates of model parameters. Unit‐specific predictions of the latent variables are also calculated. This method is illustrated using data from a national panel study on changes in methadone treatment practices.
Slow Recovery from Inactivation of Na+ Channels Underlies the Activity-Dependent Attenuation of Dendritic Action Potentials in Hippocampal CA1 Pyramidal Neurons

Na+ action potentials propagate into the dendrites of pyramidal neurons driving an influx of Ca2+ that seems to be important for associative synaptic plasticity. During repetitive (10–50 Hz) firing, dendritic action potentials display a marked and prolonged voltage-dependent decrease in amplitude. Such a decrease is not apparent in somatic action potentials. We investigated the mechanisms of the different activity dependence of somatic and dendritic action potentials in CA1 pyramidal neurons of adult rats using whole-cell and cell-attached patch-clamp methods. There were three main findings. First, dendritic Na+ currents decreased in amplitude when repeatedly activated by brief (2 msec) depolarizations. Recovery was slow and voltage-dependent. Second, Na+ currents decreased much less in somatic than in dendritic patches. Third, although K+ currents remained constant during trains, K+ currents were necessary for dendritic action potential amplitude to decrease in whole-cell experiments. These results suggest that regional differences in Na+ and K+ channels determine the differences in the activity dependence of somatic and dendritic action potential amplitudes.
Hippocampal neurogenesis reduces memory interference Adult hippocampal neurogenesis reduces memory interference in 1 humans : opposing effects of aerobic exercise and depression

1 2 Since the remarkable discovery of adult neurogenesis in the mammalian hippocampus, 3 considerable effort has been devoted to unravelling the functional significance of these new 4 neurons. Our group has proposed that a continual turnover of neurons in the DG could contribute 5 to the development of event-unique memory traces that act to reduce interference between highly 6 similar inputs. To test this theory, we implemented a continuous recognition task containing 7 some objects that were repeated across trials as well as some objects that were highly similar, but 8 not identical, to ones previously observed. The similar objects, termed lures, overlap 9 substantially with previously viewed stimuli, and thus, may require hippocampal neurogenesis in 10 order to avoid catastrophic interference. Lifestyle factors such as aerobic exercise and stress have 11 been shown to impact the local neurogenic microenvironment, leading to enhanced and reduced 12 levels of DG neurogenesis, respectively. Accordingly, we hypothesized that healthy young adults 13 who take part in a long-term aerobic exercise regime would demonstrate enhanced performance 14 on the visual pattern separation task, specifically at correctly categorizing lures as “similar”. 15 Indeed, those who experienced a proportionally large change in fitness demonstrated a 16 significantly greater improvement in their ability to correctly identify lure stimuli as “similar”. 17 Conversely, we expected that those who score high on depression scales, an indicator of chronic 18 stress, would exhibit selective deficits at appropriately categorizing lures. As expected, those 19 who scored high on the Beck Depression Inventory (BDI) were significantly worse than those 20 with relatively lower BDI scores at correctly identifying lures as “similar”, while performance on 21 novel and repeated stimuli was identical. Taken together, our results support the hypothesis that 22 adult-born neurons in the DG contribute to the orthogonalization of incoming information. 23 24
Training in Statistical Reasoning Inhibits the Formation of Erroneous Group Stereotypes

Erroneous group stereotypes can result from people's failure to engage in sufficiently sophisticated reasoning strategies. Three experiments tested the hypothesis that training in statistical reasoning inhibits the formation of these stereotypes. In Study 1, 60 students were assigned randomly to a control condition or one of two training conditions in which they received training in the logic of analysis of covariance. Approximately 1 week later, they were presented with a group impression formation task. Control participants formed erroneous stereotypes, but those who received statistical training formed more accurate group impressions. Study 2 (N = 82) replicated these results, addressed concerns with experimental demand, and provided preliminary evidence concerning possible moderating effects of motivation. Study 3 (N = 44) tested a different alternative explanation and provided further clues about the inferential processes through which statistical training influences group impressions.
Some Notes on the Nonnegative Garrote

Some notes on the use of the nonnegative garrote (NG) are given in this article. The main result is that, compared with other penalized least-squares methods, the NG has a natural selection of penalty function according to an estimator of prediction risk. Furthermore, two natural estimators of the tuning parameter which only involve very simple computations are proposed corresponding to the Akaike information criterion (AIC) and Bayesian information criterion (BIC), respectively. This indicates that to select tuning parameters, it may be unnecessary to optimize a model selection criterion repeatedly. Several reasonable NG estimators with natural tuning parameters are proposed for multicollinearity problems and other problems. Simulation results and a real data analysis are reported for testing the results obtained previously.
The Research Article as a Foundation for Subject-Centered Learning and Teaching Public Sociology: Experiential Exercises for Thinking Structurally About Child Care Fatalities

This paper is the latest installment in a series that is designed to bridge the gap between teaching and practice by developing classroom applications based on a current research article from the American Sociological Review. We discuss the ways in which a recent ASR paper on child care fatalities can be used to help students explore Burawoy's conception of “public” sociology in a manner that is consistent with a subject-centered pedagogical approach. To illustrate this approach, we offer three experiential exercises designed to facilitate the active engagement of students' hearts, as well as their minds, thereby linking our subject-centered approach to the increasingly popular notion of character education.
Secure vehicular communication systems: design and architecture

Significant developments have taken place over the past few years in the area of vehicular communication systems. Now, it is well understood in the community that security and protection of private user information are a prerequisite for the deployment of the technology. This is so precisely because the benefits of VC systems, with the mission to enhance transportation safety and efficiency, are at stake. Without the integration of strong and practical security and privacy enhancing mechanisms, VC systems can be disrupted or disabled, even by relatively unsophisticated attackers. We address this problem within the SeVeCom project, having developed a security architecture that provides a comprehensive and practical solution. We present our results in a set of two articles in this issue. In this first one, we analyze threats and types of adversaries, identify security and privacy requirements, and present a spectrum of mechanisms to secure VC systems. We provide a solution that can be quickly adopted and deployed. In the second article we present our progress toward the implementation of our architecture and results on the performance of the secure VC system, along with a discussion of upcoming research challenges and our related current results.
Modeling CPU Energy Consumption of HPC Applications on the IBM POWER7

Energy consumption optimization of HPC applications inherently requires measurements for reference and comparison. However, most of today's systems lack the necessary hardware support for power or energy measurements. Furthermore, in-band data availability is preferred for specific optimization techniques such as auto-tuning. For this reason, we present in-band energy consumption models for the IBM POWER7 processor based on hardware counters. We demonstrate that linear regression is a suitable means for modeling energy consumption, and we rely on already available, high-level benchmarks for training instead of self-written or hand-tuned micro-kernels. We compare modeling efforts for different instruction mixes caused by two compilers (GCC and IBM XL) as well as various multi-threading usage scenarios, and validate across our training benchmarks and two real-world applications. Results show mean errors of approximately 1% and overall max errors of 5.3% for GCC.
Phenotype and genotype expression in pseudohomozygous factor VLEIDEN : the need for phenotype analysis.

The presence of a DNA mutation is frequently used to define a disease or a risk state. Because DNA typing has become easy and convenient in contrast to protein characterization, it is generally assumed that a mutation if present (or not) at the DNA level will be also present (or not) in the corresponding protein. However, discrepancies between phenotype and genotype can occur. A point mutation in the coagulation factor V gene (G1691-->A, resulting in an Arg506-->Gln amino acid substitution in the factor V molecule [factor VLEIDEN], leading to activated protein C resistance) is the most common genetic risk factor for familial thrombophilia. A pseudohomozygous factor VLEIDEN phenotype would occur if a heterozygous individual for factor VLEIDEN also did not express the "normal" (non-Leiden) factor V allele. However, to date, no data have been available to confirm the presence of only the factor VLEIDEN form in the plasma of these individuals. Platelet mRNA from 2 presumed pseudohomozygous patients and their family members was isolated, the amplified partial cDNAs were sequenced or restricted, and the allelic bands were quantified. Both patients were found to be heterozygous for the G1691-->A substitution at both the DNA and mRNA levels. The presence of either the normal or mutated form of factor V in the patients' plasmas was investigated using a monoclonal antibody to factor V that recognizes an epitope located between residues 307 and 506 of the factor Va heavy chain. No normal factor V could be detected in the plasmas of the 2 propositi. The present data demonstrate absence of a correlation between genotype at position 1691 (at the DNA and mRNA levels) and the corresponding phenotype data found in the plasmas of patients with pseudohomozygous factor VLEIDEN. Overall, these data suggest the existence of heterogeneous genetic "lesions," which interfere with factor V expression, processing, secretion, and/or stability. Because the presence of the factor VLEIDEN molecule in plasma is directly related to pathology, identification and quantification of the circulating forms of factor V in plasma may be required for the diagnosis of individuals with activated protein C resistance.
Exudate detection for diabetic retinopathy with convolutional neural networks

Exudate detection is an essential task for computer-aid diagnosis of diabetic retinopathy (DR), so as to monitor the progress of DR. In this paper, deep convolutional neural network (CNN) is adopted to achieve pixel-wise exudate identification. The CNN model is first trained with expert labeled exudates image patches and then saved as off-line classifier. In order to achieve pixel-level accuracy meanwhile reduce computational time, potential exudate candidate points are first extracted with morphological ultimate opening algorithm. Then the local region (64 × 64) surrounding the candidate points are forwarded to the trained CNN model for classification / identification. A pixel-wise accuracy of 91.92%, sensitivity of 88.85% and specificity of 96% is achieved with the proposed CNN architecture on the test database.
Synchronous Seasonal Change in Fin Whale Song in the North Pacific

Fin whale (Balaenoptera physalus) song consists of down-swept pulses arranged into stereotypic sequences that can be characterized according to the interval between successive pulses. As in blue (B. musculus) and humpback whales (Megaptera novaeangliae), these song sequences may be geographically distinct and may correlate with population boundaries in some regions. We measured inter-pulse intervals of fin whale songs within year-round acoustic datasets collected between 2000 and 2006 in three regions of the eastern North Pacific: Southern California, the Bering Sea, and Hawaii. A distinctive song type that was recorded in all three regions is characterized by singlet and doublet inter-pulse intervals that increase seasonally, then annually reset to the same shorter intervals at the beginning of each season. This song type was recorded in the Bering Sea and off Southern California from September through May and off Hawaii from December through April, with the song interval generally synchronized across all monitoring locations. The broad geographic and seasonal occurrence of this particular fin whale song type may represent a single population broadly distributed throughout the eastern Pacific with no clear seasonal migratory pattern. Previous studies attempting to infer population structure of fin whales in the North Pacific using synchronous individual song samples have been unsuccessful, likely because they did not account for the seasonal lengthening in song intervals observed here.
Data hiding of motion information in chroma and luma samples for video compression

2010 appears to be the launching date for new compression activities intended to challenge the current video compression standard H.264/AVC. Several improvements of this standard are already known like competition-based motion vector prediction. However the targeted 50% bitrate saving for equivalent quality is not yet achieved. In this context, this paper proposes to reduce the signaling information resulting from this vector competition, by using data hiding techniques. As data hiding and video compression traditionally have contradictory goals, a study of data hiding is first performed. Then, an efficient way of using data hiding for video compression is proposed. The main idea is to hide the indices into appropriately selected chroma and luma transform coefficients. To minimize the prediction errors, the modification is performed via a rate-distortion optimization. Objective improvements (up to 2.3% bitrate saving) and subjective assess ment of chroma loss are reported and analyzed for several sequences.
Changing characters' point of view in interactive storytelling

Virtual characters are at the epicentre of Interactive Storytelling systems and in recent years multiple AI planning approaches have been described to specify their autonomous behaviour. This demonstrator provides an overview of our novel approach to the definition of virtual characters aimed at achieving a balance between character autonomy and global plot structure which proposes the notion of a character's Point of View. Additionally, the demonstrator offers the active spectator the ability to discover the story described from the perspective of a number of different characters. We present our fully-implemented Interactive Narrative based on Shakespeare's Merchant of Venice. The system, which features a novel AI planning approach to story generation, can generate very different stories depending on the Point of View adopted and support dynamic modification of the story world which results in different story consequences.
The cognitive neuroscience of memory and consciousness

In this chapter, we delineate the neural activity associated with conscious memories characterized by different degrees of ‘retrieval content’ (i.e. sensory/contextual detail). Based primarily on neuroimaging evidence, we identify the neural regions that are associated most consistently with the following conscious memory processes: retrieval success versus retrieval attempt, remembering versus knowing, and true recognition versus false recognition. A number of patterns emerge from the comparison of memories with high retrieval content (i.e., retrieval success, remembering, and true recognition) and memories with low retrieval content (i.e., retrieval attempt, knowing, and false recognition). Memories with both high and low retrieval content are associated with activity in the prefrontal and parietal cortex, indicating that these regions are generally associated with retrieval. There is also evidence that memories with low retrieval content are associated with activity in the prefrontal cortex to a greater degree than memories with high retrieval content, suggesting that low retrieval content memories are associated with greater postretrieval monitoring (although this activity does not necessarily reflect differential retrieval content per se). Finally, memories with high retrieval content, to a greater degree than memories with low retrieval content, are associated with activity in the parietal cortex and sensory cortex (along with the medial temporal lobe for retrieval success > attempt and remembering > knowing). This increased activity in sensory cortex (and medial temporal lobe) for memories with high retrieval content indicates that conscious memories are constructed by reactivation of encoded item features at retrieval.
Retinoids as important regulators of terminal differentiation: examining keratin expression in individual epidermal cells at various stages of keratinization

When human epidermal cells were seeded on floating rafts of collagen and fibroblasts, they stratified at the air-liquid interface. The suprabasal cells synthesized the large type II (K1) and type I (K10/K11) keratins characteristic of terminal differentiation in skin. At earlier times in culture, expression of the large type II keratins appeared to precede the expression of their type I partners. At later times, all suprabasal cells expressed both types, suggesting that the accumulation of a critical level of K1 keratin may be a necessary stimulus for K10 and K11 expression. Expression of the terminal differentiation-specific keratins was completely suppressed by adding retinoic acid to the culture medium, or by submerging the cultures in normal medium. In submerged cultures, removal of vitamin A by delipidization of the serum restored the keratinization process. In contrast, calcium and transforming growth factor-beta did not influence the expression of the large keratins in keratinocytes grown in the presence of retinoids, even though they are known to induce certain morphological features of terminal differentiation. Retinoic acid in the raft medium not only suppressed the expression of the large keratins, but, in addition, induced the synthesis of two new keratins not normally expressed in epidermis in vivo. Immunofluorescence localized one of these keratins, K19, to a few isolated cells of the stratifying culture. In contrast, the other keratin, K13, appeared uniformly in a few outer layers of the culture. Interestingly, K13 expression correlated well with the gradient of retinoid-mediated disruptions of intercellular interactions in the culture. These data suggest that K13 induction may in some way relate to the reduction in either the number or the strength of desmosomal contacts between suprabasal cells of stratified squamous epithelial tissues.