Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental Noise Embeddings for Robust Speech Recognition

We propose a novel deep neural network architecture for speech recognition that explicitly employs knowledge of the background environmental noise within a deep neural network acoustic model. A deep neural network is used to predict the acoustic environment in which the system in being used. The discriminative embedding generated at the bottleneck layer of this network is then concatenated with traditional acoustic features as input to a deep neural network acoustic model. Through a series of experiments on Resource Management, CHiME-3 task, and Aurora4, we show that the proposed approach significantly improves speech recognition accuracy in noisy and highly reverberant environments, outperforming multi-condition training, noise-aware training, i-vector framework, and multi-task learning on both in-domain noise and unseen noise.
Estimating the executive demands of a one-back choice reaction time task by means of the selective interference paradigm

The present study proposes a new executive task, the one-back choice reaction time (RT) task, and implements the selective interference paradigm to estimate the executive demands of the processing components involved in this task. Based on the similarities between a one-back choice RT task and the n-back updating task, it was hypothesized that one-back delaying of a choice reaction involves executive control. In three experiments, framed within Baddeley's (1986) working-memory model, a one-back choice RT task, a choice RT task, articulatory suppression, and matrix tapping were performed concurrently with primary tasks involving verbal, visuospatial, and executive processing. The results demonstrate that one-back delaying of a choice reaction interferes with tasks requiring executive control, while the potential interference at the level of the verbal or visuospatial working memory slave systems remains minimal.
Population genetic analysis of a recent range expansion: mechanisms regulating the poleward range limit in the volcano barnacle Tetraclita rubescens

As range shifts coincident with climate change have become increasingly well documented, efforts to describe the causes of range boundaries have increased. Three mechanisms—genetic impoverishment, migration load, or a physical barrier to dispersal—are well described theoretically, but the data needed to distinguish among them have rarely been collected. We describe the distribution, abundance, genetic variation, and environment of Tetraclita rubescens, an intertidal barnacle that expanded its northern range limit by several hundreds of kilometres from San Francisco, CA, USA, since the 1970s. We compare geographic variation in abundance with abiotic and biotic patterns, including sea surface temperatures and the distributions of 387 co‐occurring species, and describe genetic variation in cytochrome c oxidase subunit I, mitochondrial noncoding region, and nine microsatellite loci from 27 locations between Bahia Magdalena (California Baja Sur, Mexico) and Cape Mendocino (CA, USA). We find very high gene flow, high genetic diversity, and a gradient in physical environmental variation coincident with the range limit. We infer that the primary cause of the northern range boundary in T. rubescens is migration load arising from flow of maladapted alleles into peripheral locations and that environmental change, which could have reduced selection against genotypes immigrating into the newly colonized portion of the range, is the most likely cause of the observed range expansion. Because environmental change could similarly affect all taxa in a region whose distributional limits are established by migration load, these mechanisms may be common causes of range boundaries and largely synchronous multi‐species range expansions.
Analyzing human and virtual agent interaction under irrational decision making

The incapability of virtual agents to analyze the irrational behavior in human-virtual agent interactions urges to develop efficient mechanisms to capture the irrationality. Irrational actions in cognitive interactions are employed to attract the opponent's trust or to make future actions harder to anticipate. Recent works mostly investigate interactions of multiple decision makers with perfect knowledge which select optimal actions, a scenario that is not applicable when irrationality comes in. In this paper, the social interaction between a human and a virtual agent over a known utility function is considered while irrational actions are allowed. The existence of correlated equilibria is shown under some mild assumptions. Using the action history of both players, a measure of irrationality, which is variance-optimal, is proposed. Exploiting the irrationality measure, a probabilistic mechanism for decision making is suggested and it is shown that the sequence of decisions chosen under this mechanism leads to equilibria for sufficient number of iterations. Restating the interaction as an iterative game, the existence of equilibria is shown for two types of games i.e. simultaneous games and leader-follower (Stackelberg) games. Even though our method considers human-virtual agent interaction, the results extend to any two-player finite discrete game. An HCI experiment validates our proposed approach and corroborates the efficiency of the proposed method.
Regulatory mechanism of CCN2 production by serotonin (5-HT) via 5-HT2A and 5-HT2B receptors in chondrocytes

Serotonin (5-hydroxytryptamine: 5-HT) is recognized as a neurotransmitter in the central nerve system and as a regulator of systemic blood pressure in the peripheral tissues. Recently, it was reported that 5-HT2 receptors (5-HT2Rs) were expressed in cartilage tissues lacking both vessels and neurons, suggesting possible novel functions of 5-HT during cartilage development and regeneration. Our previous data indicated that CCN family protein 2/connective tissue growth factor (CCN2/CTGF) plays a central role in cartilage development and regeneration. Therefore, the aim of this study was to investigate the effect of 5-HT on the production of CCN2 in chondrocytes. Firstly, we showed that the mRNAs of 5-HT2R subtypes 5-HT2AR and 5-HT2BR, were expressed in a human chondrocytic cell line, HCS-2/8; however, 5-HT2CR mRNA was not detected. In addition, exogenously added 5-HT did not affect the 5-HT2AR and 5-HT2BR expressions. Next, we demonstrated that CCN2 production was increased by treatment with a 5-HT2AR agonist and the combination of 5-HT and 5-HT2BR antagonist. In contrast, treatment with a 5-HT2BR agonist and the combination of 5-HT and 5-HT2AR antagonist decreased CCN2 production. Furthermore, we showed that phosphorylation of Akt and p38 MAPK were increased by treatment with 5-HT2AR agonist, and that phosphorylation of PKCε, PKCζ, ERK1/2 and JNK were increased by treatment with 5-HT2BR agonist. Finally, we found that 5-HT2AR was localized in the growth plate, whereas 5-HT2BR was localized in the articular cartilage. These findings suggest that 5-HT promotes CCN2 production through the 5-HT2AR in growth plates, and that it represses CCN2 production through the 5-HT2BR in articular cartilage for harmonized development of long bones.
Non-Uniform Survival Rate of Heterodimerization Links in the Evolution of the Yeast Protein-Protein Interaction Network

Protein-protein interaction networks (PINs) are scale-free networks with a small-world property. In a small-world network, the average cluster coefficient () is much higher than in a random network, but the average shortest path length () is similar between the two networks. To understand the evolutionary mechanisms shaping the structure of PINs, simulation studies using various network growth models have been performed. It has been reported that the heterodimerization (HD) model, in which a new link is added between duplicated nodes with a uniform probability, could reproduce scale-freeness and a high . In this paper, however, we show that the HD model is unsatisfactory, because (i) to reproduce the high in the yeast PIN, a much larger number (n HI) of HD links (links between duplicated nodes) are required than the estimated number of n HI in the yeast PIN and (ii) the spatial distribution of triangles in the yeast PIN is highly skewed but the HD model cannot reproduce the skewed distribution. To resolve these discrepancies, we here propose a new model named the non-uniform heterodimerization (NHD) model. In this model, an HD link is preferentially attached between duplicated nodes when they share many common neighbors. Simulation studies demonstrated that the NHD model can successfully reproduce the high , the low n HI, and the skewed distribution of triangles in the yeast PIN. These results suggest that the survival rate of HD links is not uniform in the evolution of PINs, and that an HD link between high-degree nodes tends to be evolutionarily conservative. The non-uniform survival rate of HD links can be explained by assuming a low mutation rate for a high-degree node, and thus this model appears to be biologically plausible.
Towards the identification of the loci of adaptive evolution

Establishing the genetic and molecular basis underlying adaptive traits is one of the major goals of evolutionary geneticists in order to understand the connection between genotype and phenotype and elucidate the mechanisms of evolutionary change. Despite considerable effort to address this question, there remain relatively few systems in which the genes shaping adaptations have been identified. Here, we review the experimental tools that have been applied to document the molecular basis underlying evolution in several natural systems, in order to highlight their benefits, limitations and suitability. In most cases, a combination of DNA, RNA and functional methodologies with field experiments will be needed to uncover the genes and mechanisms shaping adaptation in nature.
Study of the SMO algorithm based on data mining in shot-term power load forecasting model

A new methodology on the algorithm of sequential minimal optimization for the electric power system load was presented. In order to solve the problem that support vector machines can not deal with large scale data. First, this paper utilizes the advantage of data mining technology in processing large data and eliminating redundant information. The system mines the historical daily loading which has the same meteorological category as the forecasting day in order to compose data sequence with highly similar meteorological features, with this method it can decrease SVR training data; Second, this paper introduces the modified algorithm of sequential minimal optimization (SMO) to increase operational speed by use of a single threshold value. With this method it can decrease SVR training data and overcome the disadvantage of very large data and accelerates processing speed when constructing SVM model. The forecasted results are compared with those SVR employing QP optimization algorithm and BP artificial neural method, and it is shown that the presented forecasting method is more accurate and efficient.
Extreme Variations of pCO2 and pH in a Macrophyte Meadow of the Baltic Sea in Summer: Evidence of the Effect of Photosynthesis and Local Upwelling

The impact of ocean acidification on benthic habitats is a major preoccupation of the scientific community. However, the natural variability of pCO2 and pH in those habitats remains understudied, especially in temperate areas. In this study we investigated temporal variations of the carbonate system in nearshore macrophyte meadows of the western Baltic Sea. These are key benthic ecosystems, providing spawning and nursery areas as well as food to numerous commercially important species. In situ pCO2, pH (total scale), salinity and PAR irradiance were measured with a continuous recording sensor package dropped in a shallow macrophyte meadow (Eckernförde bay, western Baltic Sea) during three different weeks in July (pCO2 and PAR only), August and September 2011.The mean (± SD) pCO2 in July was 383±117 µatm. The mean (± SD) pCO2 and pHtot in August were 239±20 µatm and 8.22±0.1, respectively. The mean (± SD) pCO2 and pHtot in September were 1082±711 µatm and 7.83±0.40, respectively. Daily variations of pCO2 due to photosynthesis and respiration (difference between daily maximum and minimum) were of the same order of magnitude: 281±88 µatm, 219±89 μatm and 1488±574 µatm in July, August and September respectively. The observed variations of pCO2 were explained through a statistical model considering wind direction and speed together with PAR irradiance. At a time scale of days to weeks, local upwelling of elevated pCO2 water masses with offshore winds drives the variation. Within days, primary production is responsible. The results demonstrate the high variability of the carbonate system in nearshore macrophyte meadows depending on meteorology and biological activities. We highlight the need to incorporate these variations in future pCO2 scenarios and experimental designs for nearshore habitats.
Autologous natural killer cell therapy for human recurrent malignant glioma.

BACKGROUND Natural killer (NK) cells are highly efficient in the cellular immune response against malignant tumors without restriction of major histocompatibility complex. However clinical studies using autologous NK cells have been reported in only a very limited number of cases, due to the fact that selective NK expansion is difficult to achieve in this patient population. Here, we report the results of adoptive immunotherapy in patients with recurrent malignant gliomas using autologous NK cells that were expanded ex vivo by a novel method. PATIENTS AND METHODS Peripheral blood mononuclear cells (PBMCs) were prepared from patients with malignant gliomas, and were co-cultured with an irradiated human feeder cell line (HFWT) in RHAM-alpha medium supplemented with 5% autologous plasma and interleukin-2. The resulting NK cell-rich effector cells were injected into 9 patients (16 courses) with recurrent malignant glioma (6 cases of WHO grade-3 glioma and 3 cases of grade-4 glioma). RESULTS The mean frequency of NK cells among lymphocytes was 82.2 +/- 10.5%. A combination of focal and intravenous injections was peformed in 10 courses. Intravenous injection alone was performed in 6 courses. Further, intravenous injection of low-dose interferon beta (6x10(6) IU/week) was performed as an adjuvant therapy in all courses to achieve maximum benefit for enrolled patients. Clinical evaluation demonstrated 3 PR, 2 MR, 4 NC and 7 PD in a total of 16 courses of treatment. Severe neurological toxicity was not observed in any of the patients. CONCLUSION It was demonstrated that NK cell-rich effector cells were expanded ex vivo from PBMCs in all nine cases of recurrent malignant glioma and that NK cell therapy was safe and partially effective in patients with recurrent malignant gliomas.
An overview of healthcare perspective based security issues in Wireless Sensor Networks

In this review, we present few perspective applications in the healthcare background and describe the security challenges in WSNs. It has created new domain of WBANs and Wireless Sensor Networks healthcare applications is increasing array of location tags and wearable vital sign sensors. In real-time mode it is continuously trace both healthcare personnel (physiological and behavioural studies) and patient status location. Generally, Wireless Sensor Network devices are immensely slight in terms of computation, power and communication. In this review, we describe detailed discussions of WSN security mechanisms and privacy issues from the demanding perspective of e-healthcare systems and viable techniques for these issues.
Optical photometry of the GRB 010222 afterglow

The optical afterglow of GRB 010222 was observed using the recently installed 2-m telescope at the Indian Astronomical Observatory, Hanle, and the telescopes at the Vainu Bappu Observatory, Kavalur, beginning ~0.6 day after the detection of the event. The results based on these photometric observations combined with others reported in the literature are presented in this paper. The R band light curve shows an initial decline of intensities proportional to t -0.542 which steepens, after 10.3 hours, to t -1.263 . Following the model of collimated outflow, the early break in the light curve implies a very narrow beam angle (~2° ~3°). The two decay rates are consistent with the standard jet model in a uniform density ambient medium, but require a hard spectrum of electron power density with p~1.5. The R band light between 14 and 17 hours since outburst departs from the power law fit by 0.1 mag and shows some evidence for fluctuations over timescales of an hour in the observer's frame. Such deviations are expected due to density inhomogeneities if the ambient medium is similar to the local interstellar medium. GRB 010222 is thus an example of a highly collimated outflow with a hard spectrum of electron energy distribution in normal interstellar environment.
Cutaneous scalp metastases from retroperitoneal leiomyosarcoma: a case report

A 71‐year‐old woman presented with five scalp nodules that were clinically suspicious for pilar cysts. Histopathologic examination showed a proliferation of mitotically active pleomorphic spindle cells arranged into intersecting fascicles in the dermis and subcutis. Tumor cells displayed deeply eosinophilic cytoplasm and expressed desmin but were negative for S100 protein by immunohistochemistry. Before 10 years, the patient was diagnosed with high‐grade retroperitoneal leiomyosarcoma and underwent resection with intraoperative radiation. Metastatic disease involving the lungs, liver and soft tissue developed, requiring treatment with resections, radiation and chemotherapy. Owing to the presentation of multiple scalp nodules with microscopic features of leiomyosarcoma in conjunction with the clinical history of retroperitoneal leiomyosarcoma, a diagnosis of metastatic leiomyosarcoma was made. Scalp metastasis from retroperitoneal leiomyosarcoma is extremely rare and portends a poor prognosis. To our knowledge, only two other cases have been reported in the English literature, and a further search discovered only nine additional cases of scalp metastasis from soft tissue leiomyosarcoma of any non‐gynecologic anatomic site. This case highlights the striking microscopic similarity between primary cutaneous and metastatic leiomyosarcoma and illustrates the necessity of adequate clinical information and an appropriate index of suspicion in excluding the possibility of cutaneous metastases of leiomyosarcoma from somatic soft tissue.
Performance comparison of compact UWB antennas through multi-objective optimization

In this paper, an optimization-based procedure for performance comparison of alternative compact UWB antenna topologies is discussed. Our approach allows for fast assessment of compact antenna performance by identifying the best possible trade-offs between the antenna size and its reflection responses. Analysis of such Pareto-optimal designs obtained for various antenna topologies allows for their fair comparison, particularly in terms of the minimum size they can be designed for (assuming acceptable reflection response levels) or the best attainable reflection characteristics. The multi-objective optimization algorithm utilized in this work exploits sequential domain patching technique and variable-fidelity EM simulation models. The proposed approach is demonstrated using two topologies of compact UWB monopole antennas.
Bayesian Network Models for Generation of Crisis Management Training Scenarios

We present a noisy-OR Bayesian network model for simulation-based training, and an efficient search-based algorithm for automatic synthesis of plausible training scenarios from constraint specifications. This randomized algorithm for approximate causal inference is shown to outperform other randomized methods, such as those based on perturbation of the maximally plausible scenario. It has the added advantage of being able to generate acceptable scenarios (based on a maximum penalized likelihood criterion) faster than human subject matter experts, and with greater diversity than deterministic inference. We describe a field-tested interactive training system for crisis management and show how our model can be applied offline to produce scenario specifications. We then evaluate the performance of our automatic scenario generator and compare its results to those achieved by human instructors, stochastic simulation, and maximum likelihood inference. Finally, we discuss the applicability of our system and framework to a broader range of modeling problems for computer-assisted instruction.
Estimator Variance in Reinforcement Learning: Theoretical Problems and Practical Solutions

In reinforcement learning, as in many on-line search techniques, a large number of estimation parameters (e.g. Q-value estimates for 1-step Q-learning) are maintained and dynamically updated as information comes to hand during the learning process. Excessive variance of these estimators can be problematic, resulting in uneven or unstable learning, or even making effective learning impossible. Estimator variance is usually managed only indirectly, by selecting global learning algorithm parameters (e.g. A for TD(A) based methods) that axe a compromise between an acceptable level of estimator perturbation and other desirable system attributes, such as reduced estimator bias. In this paper, we argue that this approach may not always be adequate, particularly for noisy and non-Markovian domains, and present a direct approach to managing estimator variance, the new ccBeta algorithm. Empirical results in an autonomous robotics domain are also presented showing improved performance using the ccBeta method.
Individualisierung der Jugendphase in den 80er Jahren?

Zusammenfassung Beiträge zur Untersuchung von Jugendbiographien konzentrieren sich vor dem Hintergrund der Individualisierungsthese häufig auf die Frage der subjektiven, sinnhaften Konstruktion biographischer Identität. Im vorliegenden Beitrag wird, ausgehend von Bourdieus Ansatz der „biographischen Illusion“ die These vertreten, daß bei diesem Vorgehen die Einbeziehung struktureller Rahmenbedingungen biographischen Handelns nur unzulänglich erfolgt. Mit Hilfe des Verfahrens der Ereignisanalyse werden an Hand zweier Jugendkohorten aus der 1981er und 1992er Shell-Jugendstudie drei Hypothesen zur Individualisierung biographischer Prozesse untersucht, die sich auf eine Vorverlagerung biographischer Entscheidungen, die zunehmende Varianz um spezifische Statusübergänge und ein Nachlassen der Determinationskraft sozio-demographischer Variablen im Zeitvergleich beziehen. Es zeigte sich eine deutliche Beschleunigung ästhetischer und politischer Verselbständigung im Vergleich beider Kohorten. Eine durch die Zunahme der Varianz indizierte Individualisierung von Jugendbiographien konnte bei männlichen Jugendlichen durchgängig festgestellt werden, wogegen weibliche Befragte öffentliche Statusübergänge standardisierter vollzogen. Im Gegensatz zu den hypothetischen Annahmen nahm insbesondere die Determinationskraft der Schulbildung für diejenigen jugendbiographische Übergänge deutlich zu, die eine Verselbständigung von elterlicher Kontrolle anzeigen.