Miracle-dz/UniFAR-FTUs huggingface dataset:
Neurotrophic effects of GM1 ganglioside and electrical stimulation on cochlear spiral ganglion neurons in cats deafened as neonates

Previous studies have shown that electrical stimulation of the cochlea by a cochlear implant promotes increased survival of spiral ganglion (SG) neurons in animals deafened early in life (Leake et al. [ 1999 ] J Comp Neurol 412:543–562). However, electrical stimulation only partially prevents SG degeneration after deafening and other neurotrophic agents that may be used along with an implant are of great interest. GM1 ganglioside is a glycosphingolipid that has been reported to be beneficial in treating stroke, spinal cord injuries, and Alzheimer's disease. GM1 activates trkB signaling and potentiates neurotrophins, and exogenous administration of GM1 has been shown to reduce SG degeneration after hearing loss. In the present study, animals were deafened as neonates and received daily injections of GM1, beginning either at birth or after animals were deafened and continuing until the time of cochlear implantation. GM1‐treated and deafened control groups were examined at 7–8 weeks of age; additional GM1 and no‐GM1 deafened control groups received a cochlear implant at 7–8 weeks of age and at least 6 months of unilateral electrical stimulation. Electrical stimulation elicited a significant trophic effect in both the GM1 group and the no‐GM1 group as compared to the contralateral, nonstimulated ears. The results also demonstrated a modest initial improvement in SG density with GM1 treatment, which was maintained by and additive with the trophic effect of subsequent electrical stimulation. However, in the deafened ears contralateral to the implant SG soma size was severely reduced several months after withdrawal of GM1 in the absence of electrical activation. J. Comp. Neurol. 501:837–853, 2007. © 2007 Wiley‐Liss, Inc.
[Pathological study of testicular injury induced by high power microwave radiation in rats].

OBJECTIVE To explore the pathological characteristics and the dynamic change regularity of the testis induced by high power microwave (HPM) radiation. METHODS One hundred and sixty-five male Wistar rats were exposed to 0, 3, 10, 30 and 100 mW/cm2 HPM radiation for five minutes, and changes of testicular morphology and teratogenic ratio of epididymal spermatozoa were observed through light microscope and electron microscope at 6 h, 1, 3, 7, 14, 28 and 90 d after radiation. RESULTS Injury of testicular spermatogenic cells in rats might be induced by 3 to approximately 100 mW/cm2 HPM radiation, and the main pathological changes were degeneration, necrosis, shedding of spermatogenic cells, formation of multinuclear giant cells, decrease or loss of sperm and interstitial edema. Injury of spermatogenic cells underwent such phases as death and shedding, cavitation, regeneration and repair, characterized by being focalized, inhomogenous and phased. And the severity of pathological changes of the testis increased with power density. There was only scattered degeneration, necrosis, shedding of spermatogenic cells in the seminiferous tubule one day after 3 mW/cm2 radiation, and the pathological changes six hours after 10 mW/cm2 radiation was similar to those one day after 3 mW/cm2 radiation, but with the formation of multinuclear giant cells, and the above-mentioned pathological changes aggravated from one day to seven days after radiation. There was a significant increase in degeneration, necrosis, shedding of spermatogenic cells, as well as a significant decrease in spermatozoa and focal necrosis in simple seminiferous tubules six hours after 30 and 100 mW/cm2 radiation, and the subsequent changes were similar to those of 10 mW/cm2 radiation. There was a significant increase in teratogenic ratio of epididymal spermatozoa at 3 d, 1 to approximately 7 d, 6 h to approximately 7 d after 3, 10, 30 and 100 mW/cm2 microwave radiation respectively (P < 0.01 or P < 0.05). CONCLUSION HPM radiation may cause injury of testicular spermatogenic cells in rats, which has a positive correlation to radiation dosage and time.
Simulation techniques for component-based software reliability modeling with project application

In this paper, we consider to combine analytical models with simulation techniques for software reliability measurements. We have implemented a set of failure-rate-based simulation techniques which can capture the characteristic of software process and structure in a way that permits us to obtain quantified results for software reliability measures. We address two methods to take into account the functional dependency and error correlation among components, so that we can treat a software system as a combination of interdependent components. This offers a more appropriate approach for analyzing reliability measurements of component-based software systems. The results from a project application indicate that the incorporation of simulation techniques into analytical models has the advantages of accurate analyses, early predictions, and comprehensive evaluations for software reliability engineering.
An Approach for Semantic Business Process Model Matching using Supervised Machine Learning

Matching business process models and their node labels plays an important role for business process management. Many matching algorithms using natural language processing (NLP) techniques exist but do not exploit the opportunities of machine learning though it is generally agreed that a learning approach has great potential in the field of NLP. Therefore, we develop a matching approach based on supervised learning using a language-driven similarity function in order to reproduce a human judgement. Additionally, we implement and evaluate our approach using established quality measures, consisting of precision, recall and F-measure. We conduct an evaluation based on real world process models that demonstrates the potential and the limitations of our machine learning approach. The results show a significant learning effect for matching unknown models without predefined rules. The matching quality is comparable to existing matchers. However, the matching quality seems to depend on the one hand on the available training data and on the other hand on the complexity of the chosen similarity function. Further research efforts have to be undertaken in order to improve our approach. This will include developing a more elaborate similarity function containing more linguistic characteristics of a label as well as integrating contextual information.
Exposure to Drinking Water Trihalomethanes and Their Association with Low Birth Weight and Small for Gestational Age in Genetically Susceptible Women

Little is known about genetic susceptibility to individual trihalomethanes (THM) in relation to adverse pregnancy outcomes. We conducted a nested case-control study of 682 pregnant women in Kaunas (Lithuania) and, using individual information on drinking water, ingestion, showering and bathing, and uptake factors of THMs in blood, estimated an internal THM dose. We used logistic regression to evaluate the relationship between internal THM dose, birth outcomes and individual and joint (modifying) effects of metabolic gene polymorphisms. THM exposure during entire pregnancy and specific trimesters slightly increased low birth weight (LBW) risk. When considering both THM exposure and maternal genotypes, the largest associations were found for third trimester among total THM (TTHM) and chloroform-exposed women with the GSTM1–0 genotype (OR: 4.37; 95% CI: 1.36–14.08 and OR: 5.06; 95% CI: 1.50–17.05, respectively). A test of interaction between internal THM dose and GSTM1–0 genotype suggested a modifying effect of exposure to chloroform and bromodichloromethane on LBW risk. However, the effect on small for gestational age (SGA) was not statistically significant. These data suggest that THM internal dose may affect foetal growth and that maternal GSTM1 genotype modifies the THM exposure effects on LBW.
Uniform segmentation in online signature verification

In this paper, an online signature verification system based on the segmentation of online signature is proposed. The two set of features i.e shape features and dynamic features are extracted and a feature vector concatenating these two set of features is obtained. Euclidean distance is used as a classifier and a writer dependent threshold is used for verification purpose. In order to evaluate the effectiveness of the proposed online signature verification system, several experiments are carried out. Public database SVC 2004 is used for all the tests for online signature verification. The accuracy of proposed system with ten signatures in the training set and ten segments per signature is 91.75 % for skilled forgery. Experimentation is carried out separately for skilled forgery and random forgery. Experimental results on SVC2004 Task 2 show good performance of the proposed online signature verification system.
Weighted averaging fusion for multi-view skeletal data and its application in action recognition

Existing studies in skeleton-based action recognition mainly utilise skeletal data taken from a single camera. Since the quality of skeletal tracking of a single camera is noisy and unreliable, however, combining data from multiple cameras can improve the tracking quality and hence increase the recognition accuracy. In this study, the authors propose a method called weighted averaging fusion which merges skeletal data of two or more camera views. The method first evaluates the reliability of a set of corresponding joints based on their distances to the centroid, then computes the weighted average of selected joints, that is, each joint is weighted by the overall reliability of the camera reporting the joint. Such obtained, fused skeletal data are used as the input to the action recognition step. Experiments using various frame-level features and testing schemes show that more than 10% improvement can be achieved in the action recognition accuracy using these fused skeletal data as compared with the single-view case.
Taking a new TAK on tat transactivation.

A common rate-limiting step in the transcription of inducible eukaryotic genes is the release of RNA polymerase II (RNAPII) molecules from stalled elongation complexes that accumulate shortly after the initiation of RNA synthesis (Blair et al. 1996; Blau et al. 1996; for review, see Greenblatt et al. 1993; Bentley 1995). In the absence of the inducer protein, transcription at these genes is usually initiated by RNAP complexes that pause at sites 20–60 nucleotides downstream of the promoter. Promoter–proximal pausing is then counteracted by DNAor RNA-binding activators that are capable of recruiting or stimulating positive-acting transcription elongation factors. Control at the level of elongation allows for the rapid induction of transcription in response to a specific activator, in part by bypassing the need to assemble stable preinitiation complexes and also by maintaining the promoter in an open conformation that is immediately accessible to regulatory factors. The induction of the human immunodeficiency virus (HIV-1 and HIV-2) promoters by the essential virus-encoded Tat protein has proven to be a very useful model system for studies of the mechanisms that regulate the assembly and release of early elongation complexes. In this issue of Genes & Development, three exciting new papers provide the strongest evidence to date that the HIV Tat proteins act to target host cell kinases that enhance the processivity of RNAPII at an early elongation step. First, Zhu et al. (this issue) demonstrate that Tat binds with high affinity and specificity to a novel carboxy-terminal domain (CTD) kinase complex, the positive transcriptional elongation factor b (P-TEFb) known to function at an early elongation step, and that the protein kinase responsible for P-TEFb activity is a previously known cdc2-related kinase called PITALRE (Grana et al. 1994; Garriga et al. 1996). Second, Mancebo et al. (this issue) report that potent new chemical inhibitors of Tat isolated from random drug screens appear to target the active site of the PITALRE kinase. This remarkable convergence of evidence on the role of a new CTD kinase marks a major advance in our understanding of the mechanism of Tat activation as well as the underlying processes regulating elongation. The events that lead to promoter clearance and to the formation of early elongation complexes are intricately connected, and the third new report in this issue by Cujec et al. supports and extends the recent findings of two other groups (Parada and Roeder 1996; Garcia-Martinez et al. 1997b) that the TFIIH kinase complex also plays an important role in Tat activation. Collectively, these studies highlight a critical and still largely undefined step in transcriptional control that constitutes a major regulatory checkpoint for the HIV-1 promoter as well as for many cellular genes.
Changes in Plasma and Extracellular Fluid Volumes in Patients with Essential Hypertension During Long‐Term Treatment with Hydrochlorothiazide

In 13 untreated patients with essential hypertension, the plasma volume (T-1824) and the extracellular fluid volume (82Br- distribution space) were determined three times. During treatment with 50 to 100 mg of hydrochlorothiazide daily, determinations of plasma volume and extracellular fluid volume were repeated after treatment for 1 mo (13 patients), 2 mo (13 patients), 4 mo (eight patients), and 6 mo (seven patients). In all cases the average plasma and extracellular fluid volumes were reduced compared with the averages of three control values. The plasma volume was significantly reduced at the 5% level after treatment for 1, 2, and 4 mo.Corresponding studies from the literature have been reviewed and, on the basis of these studies and our own results, it is concluded that thiazides have a volume-depleting effect which is continued during long-term treatment of patients with essential hypertension.
The impact of adversarial knowledge on adversarial planning in perimeter patrol

This paper considers the problem of multi-robot patrolling around a closed area, in the presence of an adversary trying to penetrate the area. Previous work on planning in similar adversarial environments addressed worst-case settings, in which the adversary has full knowledge of the defending robots. It was shown that non deterministic algorithms may be effectively used to maximize the chances of blocking such a full-knowledge opponent, and such algorithms guarantee a "lower bound" to the performance of the team. However, an open question remains as to the impact of the knowledge of the opponent on the performance of the robots. This paper explores this question in depth and provides theoretical results, supported by extensive experiments with 68 human subjects concerning the compatibility of algorithms to the extent of information possessed by the subjects. First, we analytically examine the case of a zero-knowledge opponent---a different extreme---and show that surprisingly, this seemingly best-case scenario (from the point of view of defending robots) is optimally addressed by a deterministic, non-randomizing patrol. Moreover, we show empirically that an optimal algorithm for the full-knowledge opponent fails miserably in this case. We then address the case in which the adversary gained partial information, propose the Combine algorithm that maximizes the expected probability of penetration detection along with minimizing the deviation between the probabilities of penetration detection along the perimeter, and support the performance of this algorithm in the experiments.
Efficient Data Projection for Visual Analysis of Large Data Sets Using Neural Networks

The most classical visualization methods, including multidimensional scaling and its particular case  Sammon's mapping, encounter difficulties when analyzing large data sets. One of possible ways to solve the problem is the application of artificial neural networks. This paper presents the visualization of large data sets using the feed-forward neural network  SAMANN. This back propagation-like learning rule has been developed to allow a feed-forward artificial neural network to learn Sammon's mapping in an unsupervised way. In its initial form, SAMANN training is computation expensive. In this paper, we discover conditions optimizing the computational expenditure in visualization even of large data sets. It is shown possibility to reduce the original dimensionality of data to a lower one using small number of iterations. The visualization results of real-world data sets are presented.
Paving the path for habit change: cognitive shielding of intentions against habit intrusion.

OBJECTIVE The objective of the current study was to examine the cognitive processes that make it possible to use intentions to change one's habitual health-related behaviour. DESIGN The study used an idiosyncratic approach to investigate personal existing habits and non-habitual behaviours in a within-participants experiment. METHOD Participants first generated habitual and non-habitual behaviours for various daily-life goals (e.g., having lunch, playing sports). Next, they formed intentions to perform non-habitual behaviours in order to attain these goals. Finally, we measured the cognitive accessibility of participants' habitual and non-habitual behaviours with a behaviour recognition task. RESULTS The findings showed that habitual behaviours were more accessible than the non-habitual behaviours when no intentions were formed (control goals), showing that habits are more readily accessed in mind. However, when participants had formed intentions to use non-habitual behaviours, habitual behaviours for the same goals were inhibited in mind. This could be the cognitive mechanism that shields intentions from habit intrusion and thus enables the pursuit of non-habitual behaviours. CONCLUSION The current study demonstrates the role of inhibitory processes in shielding non-habitual intentions in memory. These findings are discussed in the context of success and failure in changing health-related habits.
The Halo Effect and Technology Licensing: The Influence of Institutional Prestige on the Licensing of University Inventions

Sociologists and organizational theorists have long claimed that the processes of knowledge creation and distribution are fundamentally social. Following in this tradition, we explore the effect of institutional prestige on university technology licensing. Empirically, we examine the influence of university prestige on the annual rate of technology licensing by 102 universities from 1991--1998. We show that institutional prestige increases a university's licensing rate over and above the rate that is explained by the university's past licensing performance. Because licensing success positively impacts future invention production, we argue that institutional prestige leads to stratification in the creation and distribution of university-generated knowledge.
Combining Partial Directed Coherence and Graph Theory to Analyse Effective Brain Networks of Different Mental Tasks

Purpose: The aim of this study is to qualify the network properties of the brain networks between two different mental tasks (play task or rest task) in a healthy population. Methods and Materials: EEG signals were recorded from 19 healthy subjects when performing different mental tasks. Partial directed coherence (PDC) analysis, based on Granger causality (GC), was used to assess the effective brain networks during the different mental tasks. Moreover, the network measures, including degree, degree distribution, local and global efficiency in delta, theta, alpha, and beta rhythms were calculated and analyzed. Results: The local efficiency is higher in the beta frequency and lower in the theta frequency during play task whereas the global efficiency is higher in the theta frequency and lower in the beta frequency in the rest task. Significance: This study reveals the network measures during different mental states and efficiency measures may be used as characteristic quantities for improvement in attentional performance.
On the Resiliency of Static Forwarding Tables

Fast reroute and other forms of immediate failover have long been used to recover from certain classes of failures without invoking the network control plane. While the set of such techniques is growing, the level of resiliency to failures that this approach can provide is not adequately understood. In this paper, we embarked upon a systematic algorithmic study of the resiliency of forwarding tables in a variety of models (i.e., deterministic/probabilistic routing, with packet-header-rewriting, with packet-duplication). Our results show that the resiliency of a routing scheme depends on the “connectivity” <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> of a network, i.e., the minimum number of link deletions that partition a network. We complement our theoretical result with extensive simulations. We show that resiliency to four simultaneous link failures, with limited path stretch, can be achieved without any packet modification/duplication or randomization. Furthermore, our routing schemes provide resiliency against <inline-formula> <tex-math notation="LaTeX">$k-1$ </tex-math></inline-formula> failures, with limited path stretch, by storing <inline-formula> <tex-math notation="LaTeX">$\log (k)$ </tex-math></inline-formula> bits in the packet header, with limited packet duplication, or with randomized forwarding technique.
Models of Self-Organizing Ontogenetic Development for Autonomous Adaptive Systems ( SODAS )

1 1. RESEARCH OBJECTIVES 1 1.1. DYNAMICAL MODELS OF SENSORY FUSION 2 1.2. EMBODIED CATEGORY FORMATION 2 1.3. ACTION-ORIENTED REPRESENTATIONS 2 1.4. ONTOGENETIC DEVELOPMENT 3 2. SCIENTIFIC RELEVANCE 3 2.1. DYNAMICAL BRAIN MODELS 3 2.2. EMBODIED COGNITION 5 2.3. NEURAL DARWINISM 5 3. TECHNICAL APPROACH 6 3.1. PRINCIPLES OF COGNITIVE DYNAMICS 6 3.2. THE L IMBIC SYSTEM MODEL OF INTENTIONAL BEHAVIOR 8 3.3. SELECTIONAL MECHANISMS 9 3.4. VALUE SYSTEMS, PLASTICITY AND HOMEOSTATIC REGULATION 10 3.5. COMPUTATIONAL APPROACH 10 4. EXPECTED RESULTS 11 4.1. CONCEPTUAL DESIGN 11 4.2. MOTOR COORDINATION TASKS 11 4.3. REAL-TIME TASK ENVIRONMENTS 12 4.4. MOBILE ROBOTIC SIMULATORS 12 4.5. AUTONOMOUS AGENTS 13
Autocorrelation — MTM: A compound detector for spectrum hole identification in low SNR

After digital switch over of TV transmission FCC has reported that Cognitive Radios (CR) can opportunistically use the free TV band under certain constraint among which primary user (PU) detection at low SNR is of vital importance not to create interference to the TV receivers. Since then spectrum sensing at low SNR has become the prime research issue to find spatiotemporal information of the available spectrum hole into the TV band for CR applications. In this paper we have proposed an Autocorrelation-MTM for spectrum hole identification. It has been found that detection performance can be improved significantly in low SNR by the proposed Autocorrelation-MTM compared to MTM with added complexity.