Miracle-dz/UniFAR-FTUs huggingface dataset:
Cholera and Pertussis Toxins Reveal Multiple Regulation of cAMP Levels in the Rabbit Carotid Body

It is known that hypoxia (PO2∼66–18 mm Hg), acting via unknown receptors, increases carotid body cAMP levels in Ca2+‐free solutions, indicating that low PO2 activates adenylate cyclases independently of the action of the released neurotransmitters. The aim of the present work was to investigate the involvement of G proteins in the genesis of the basal level of cAMP and on the increase in cAMP induced by low P02. In carotid body homogenates, cholera toxin‐ and pertussis toxin‐induced [32P] ADP‐ribosylation of two protein bands of =42 and 45 kDa, and =39 and 40 kDa respectively; in both cases, prior incubation of the carotid bodies with the toxins reduced [32P] ADP‐ribosylation by >90%. In intact carotid bodies, cholera toxin treatment increased cAMP levels more in normoxic than in hypoxic organs, indicating that hypoxia releases neurotransmitters acting on receptors negatively coupled to adenylate cyclases. Cholera toxin‐treated carotid bodies incubated in Ca2+‐free solution had identical cAMP levels in normoxia and in hypoxia. In pertussis toxin‐treated normoxic carotid bodies the cAMP level was close to control, but in pertussis toxin‐treated hypoxic carotid bodies cAMP rose to a level similar to those seen in normoxic cholera toxin‐treated organs, indicating that low PO2 releases neurotransmitters acting on receptors positively coupled to adenylate cyclases. Pertussis toxin‐treated carotid bodies incubated in Ca2+‐free solution lost their capacity to increase cAMP in response to hypoxia, indicating that a G protein sensitive to pertussis toxin is needed for this response. This implies that the carotid bodies express a pertussis toxin‐sensitive G protein positively coupled to adenylate cyclases, or that a Gs protein requiring the cooperative action of Go/Gi donated by subunits mediates the increase in cAMP level produced by hypoxia.
Identifying common spectral and asymmetric features in stock returns

This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are formed by looking to the hierarchical structure tree (or dendrogram) and the computed principal coordinates. We employ these techniques to investigate the similarities and dissimilarities between the "blue-chip" stocks used to compute the Dow Jones Industrial Average (DJIA) index. For reference, we investigate also the similarities among stock returns by mean and squared correlation methods.
Exploiting known sound source signals to improve ICA-based robot audition in speech separation and recognition

This paper describes a new semi-blind source separation (semi-BSS) technique with independent component analysis (ICA) for enhancing a target source of interest and for suppressing other known interference sources. The semi-BSS technique is necessary for double-talk free robot audition systems in order to utilize known sound source signals such as self speech, music, or TV-sound, through a line-in or ubiquitous network. Unlike the conventional semi-BSS with ICA, we use the time-frequency domain convolution model to describe the reflection of the sound and a new mixing process of sounds for ICA. In other words, we consider that reflected sounds during some delay time are different from the original. ICA then separates the reflections as other interference sources. The model enables us to eliminate the frame size limitations of the frequency-domain ICA, and ICA can separate the known sources under a highly reverberative environment. Experimental results show that our method outperformed the conventional semi-BSS using ICA under simulated normal and highly reverberative environments.
Identification and antimicrobial resistance prevalence of pathogenic Escherichia coli strains from treated wastewater effluents in Eastern Cape, South Africa

Antimicrobial resistance (AMR) is a global problem impeding the effective prevention/treatment of an ever‐growing array of infections caused by pathogens; a huge challenge threatening the achievements of modern medicine. In this paper, we report the occurrence of multidrug resistance (MDR) in Escherichia coli strains isolated from discharged final effluents of two wastewater treatment facilities in the Eastern Cape Province of South Africa. Standard disk diffusion method was employed to determine the antibiotic susceptibility profile of 223 polymerase chain reaction (PCR)‐confirmed E. coli isolates against 17 common antibiotics in human therapy and veterinary medicine. Seven virulence associated and fourteen antibiotic resistance genes were also evaluated by molecular methods. Molecular characterization revealed five pathotypes of E. coli in the following proportions: enterotoxigenic ETEC (1.4%), enteropathogenic EPEC (7.6%), enteroaggregative EAEC (7.6%), neonatal meningitis (NMEC) (14.8%), uropathogenic (41.7%), and others (26.9%). Isolates showed varying (1.7–70.6%) degrees of resistance to 15 of the test antibiotics. Multidrug resistance was exhibited by 32.7% of the isolates, with the commonest multiple antibiotic‐resistant phenotype (MARP) being AP‐T‐CFX (12 isolates), while multiple antibiotic‐resistant indices (MARI) estimated are 0.23 (Site 1) and 0.24 (Site 2). Associated antibiotic resistance genes detected in the isolates include: strA (88.2%), aadA (52.9%), cat I (15%), cmlA1 (4.6%), blaTEM (56.4%), tetA (30.4%), tetB (28.4%), tetC (42.2%), tetD (50%), tetK (11.8%), and tetM (68.6%). We conclude that municipal wastewater effluents are important reservoirs for the dissemination of potentially pathogenic E. coli (and possibly other pathogens) and antibiotic resistance genes in the aquatic milieu of the Eastern Cape and a risk to public health.
Studying statistical properties of regulatory DNA sequences, and their use in predicting regulatory regions in the eukaryotic genomes

There are no well-known properties in regulatory DNA analogous to those in coding sequences; their spatial location is not regular, the consensus regulatory elements are often degenerate and there are no understandable rules governing their evolution. This makes it difficult to recognize regulatory regions within genome. We review developments in the statistical characterization of regulatory regions and methods of their recognition in eukaryotic genomes.
Systolic array implementation of a real-time symbol-optimum multiuser detection algorithm

This paper presents the systolic array implementation of a real-time symbol-optimum multiuser detection (MUD) algorithm for a direct-sequence code-division multiple-access system by truncating the backward recursions in the generalized forward/backward schedule. Simulation results show that the real-time algorithm provides negligible performance loss compared to the original symbol-optimum detection algorithm. The systolic array implementation is derived in this paper through the factor graph language of the real-time algorithm in order to exploit the suitability of the algorithm for parallel signal processing.
Polarization diversity in indoor scenarios: an experimental study at 1.8 and 2.5 GHz

The paper presents the results of a set of measurements carried out in order to research the behaviour of a polarization diversity scheme in indoor environments in the 1.8 and 2.5 GHz bands. To this end, parameters such as the cross-correlation coefficient and the cross-polarization discrimination between the individual signals received in each of the combiner branches are analysed. By simulating various types of combiners, the improvement produced by the combination in the statistical behaviour of the signal, and the decrease of the bit error rate after the combination are also analysed.
Using Dynamic Neural Network to Model Team Performance for Coordination Algorithm Configuration and Reconfiguration of Large Multi-Agent Teams

Coordination of large numbers of agents for performing complex tasks in complex domains is a rapidly progressing area of research. Because of the high complexity of the problem, approximate and heuristic algorithms are typically used for key coordination tasks. Such algorithms usually require tuning of algorithm parameters to get the best performance in particular circumstances. Manually tuning of parameters is sometime difficult. In this paper, we introduce a new concept of dynamic features for a neural network, called dynamic networks, to model the way a coordination algorithm will work under particular circumstances. Genetic algorithms are used to train the networks from an abstract simulation, TeamSim. At the end, the model is used to rapidly determine an appropriate configuration of the algorithm for a particular domain. Users specify required tradeoffs in algorithm performance and use the neural network to find the best configuration for those tradeoffs. Algorithm reconfiguration can even be performed online to improve the performance of an executing team as situation changes. We present preliminary results showing the approach promisingly facilitating users to configure and control a large team executing sophisticated teamwork algorithms. INTRODUCTION AND PREVIOUS WORK Sophisticated, complex coordination allows large groups of agents to perform complex tasks in domains such as space (Kortenkamp et al., 2000) and the military (Glade, 2000). Cooperation between heterogeneous robot teams is very complex when the tasks cannot be completely divided up and assigned a priori and robots must work together, dynamically interacting to achieve common goals, for example see work of Parker et al (2001). In a large team (Scerri et al., 2004), the teamwork algorithms include with several coordination algorithms, such as algorithms for task allocation, communication, and planning. The relationships between these algorithms to the behaviors of team are highly non-linear, stochastic, and extremely complex. Knowing very well only in a part of the system is not likely to understand how the team can be controlled and get the best performance out of them. Therefore, it is critical for human operators to have better understanding of overall teamwork algorithms. However, this broadly understanding can not easily obtain by running a few of the real missions. In multi-robot systems, it is usually impossible to have lots of physical experiments, therefore simulation is used to gain understanding about the developing system ((Dixon et al., 1999), (Fu et al., 2003)). On the other hand, using simulation is difficult when the
Maxim Violation In Real Steel Movie : A Pragmatics Approach

This research aims at describing the violation of Grice Maxim‟s Cooperative Principle in conversation of Real Steel Movie. It‟s conducted in order to know what maxims which are violated by the characters of Real Steel Movie and the implicature of speaker‟s utterance when violating the maxims. The type of this research is descriptive qualitative, the several steps are done to analyze the data. In analyzing the kinds of maxims which are violated the steps are: describing the data in the form of dialogue, describing the context and analyzing how the characters used cooperative principle in his dialogue. In analyzing the implicature the steps are: describing the data in the form of dialogue and Describing the intended meaning of speaker utterance The study shows that 1) the maxim which often violated by the characters is maxim of Quality, as many as 9 data, Maxim Quantity is violated as many as 1 data, Maxim of Relation is violated as many as 5 data and Maxim of Manner is violated as many as 5 data. 2) The implicature of speaker‟s utterances are to convincing someone, to clarifying something, to refuse, to make a joke, and to shift the topic.
Dicarboxylic Amino Acid Influx across Brush Border of Rabbit Ileum

Glutamate and aspartate influxes across the brush border of rabbit intestine are saturable processes that are subject to competitive inhibition and are markedly influenced by the Na concentration in the mucosal solution. Lowering the Na concentration increases the amino acid concentration needed to elicit a half-maximal influx but does not significantly affect the maximal influx. The interaction between Na and anionic amino acid influx can be described by the same kinetic model that has been applied to the influxes of neutral amino acids and lysine. Comparison of the kinetic parameters for anionic, neutral, and cationic amino acids suggests that amino acid charge influences (a) the stability of the binary (amino acid-site) complex and (b) the affinity of this binary complex for the subsequent binding of Na. A mechanistic interpretation of these interactions is proposed.
Maximization of Throughput in Cognitive Radio using non-persistent CSMA combined with Reinforcement Learning

The Cognitive Radio project aims to develop radios that can sense the existing spectrum and identify and use free frequency bands. Primary users using time division multiple access (TDMA) are licensed users who are assigned with certain channels, and secondary users using carrier sense multiple access (CSMA) are unlicensed users who are allowed to use the channels assigned to a primary user when it is free. This paper introduces a novel spectrum sharing protocol for secondary users combining multichannel non-persistent carrier sense multiple accesses (CSMA) and reinforcement learning. Simulation results show that the throughput performance improves when reinforcement learning is applied in conjunction with non-persistent CSMA.
Schedulability-driven frame packing for multicluster distributed embedded systems

We present an approach to frame packing for multicluster distributed embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In our approach, the application messages are packed into frames such that the application is schedulable, thus the end-to-end message communication constraints are satisfied. We have proposed a schedulability analysis for applications consisting of mixed event-triggered and time-triggered processes and messages, and a worst-case queuing delay analysis for the gateways, responsible for routing inter-cluster traffic. Optimization heuristics for frame packing aiming at producing a schedulable system have been proposed. Extensive experiments and a real-life example show the efficiency of our frame-packing approach.
Culture and drama

This paper is an investigation of the interrelationship between organisational culture and financial control systems (FCS). A comparison is made between three local government organisations using an interpretive research methodology. Several researchers have advocated the adoption of an interpretive approach, among others, to accounting research. The first part of the paper discusses the relevant literature and outlines the research framework used to analyse the empirical data. This framework is based on the approach to studying organisational culture developed by Whipp et al. in 1989 which views culture in terms of a set of core beliefs and four modes of expression of these beliefs. Further, the framework acknowledges the dynamic nature of culture and uses the concept of social dramas to study the interrelationship between culture and the FCS. The second part describes the cultures and the financial control systems of the three organisations and discusses the interrelationship between them using the research framework. The final part summarises the findings, discusses a general model of the interrelationships and suggests some directions for more research in this area.
Gradients of Eph-A6 expression in primate retina suggest roles in both vascular and axon guidance

Purpose Recently we identified high levels of expression of Eph-A6 in the macula of developing human retina and showed localization of Eph-A6 to ganglion cells (GC). In the present study we investigated the expression of some members of the ephrin family in developing primate retina, including the topography of Eph-A6 expression, and its ligands, in developing macaque retinas. Methods We extracted RNA from human fetal retinas and probed for Eph-A5–A7, Eph-B1, ephrin-B2, and ephrin-A1-A5 by RT–PCR, then prepared riboprobes for Eph-A5-A7, Eph-B1 and ephrin-A1, -A4 and -B2. Paraffin sections of fetal macaque retinas were used to localize expression of Ephs and ephrins by in situ hybridization and immunohistochemistry. Results We identified prominent gradients of Eph-A6 mRNA expression in the ganglion cell layer (GCL) of fetal macaque retinas of different ages. The gradient of Eph-A6 expression was high near the optic disc and low at the developing macula at fetal day (Fd) 55. At Fd 70 and 80, the gradient of Eph-A6 expression was reversed, being higher temporal to the macula, and low at the disc. By Fd 110, when the fovea begins to form, a pattern of expression was established that persisted into the postnatal period, in which the highest levels of expression were detected at the developing fovea, and progressively lower levels of expression were detected at increasing distance from the fovea. Beginning at Fd 70, we also detected a gradient of Eph-A6 expression running perpendicular to the retinal surface within the GCL of central retina that was high in the inner GCL and low in the outer GCL. This second pattern persisted into the neonatal period. We found the two ligands for Eph-A6, ephrin-A1 and ephrin-A4, expressed by Pax2-immunoreactive astrocytes, in the optic nerve head and in the retina, by in situ hybridization and immunohistochemistry. We propose that during development of the retinal vasculature, migration of ligand-bearing astrocytes is slowed along this Eph-A6 expression gradient through repellent Eph-A6 - ephrin-A1 and -A4 signaling. Conclusions Patterns of Eph-A6 expression in the developing macaque retina suggest that Eph-A6 - ephrin-A1 and -A4 repellent signaling has a role in retinal vascular patterning, and in the postnatal maintenance of projections from macular and foveal GC.
Personalized Image-based User Authentication using Wearable Cameras

Personal devices (e.g. laptops, tablets, and mobile phones) are conventional in daily life and have the ability to store users' private data. The security problems related to these appliances have become a primary concern for both users and researchers. In this paper, we analyse first-person-view videos to develop a personalized user authentication mechanism. Our proposed algorithm generates provisional image-based passwords which benefit a variety of purposes such as unlocking a mobile device or fallback authentication. First, representative frames are extracted from the egocentric videos. Then, they are split into distinguishable segments before a clustering procedure is applied to discard repetitive scenes. The whole process aims to retain memorable images to form the authentication challenges. We integrate eye tracking data to select informative sequences of video frames and suggest a blurriness-based method if an eye-facing camera is not available. To evaluate our system, we perform experiments in different settings including object-interaction activities and traveling contexts. Even though our mechanism produces variable graphical passwords, the log-in effort for the user is comparable with approaches based on static challenges. We verified the authentication challenges in the presence of a random and an informed attacker who is familiar with the environment and observed that the time required and the number of attempts are significantly higher than for the legitimate user, making it possible to detect attacks on the authentication system.
Spherical designs as a tool for derandomization: The case of PhaseLift

The problem of retrieving phase information from amplitude measurements alone has appeared in many scientific disciplines over the last century. PhaseLift is a recently introduced algorithm for phase recovery that is computationally tractable and numerically stable. However, initial rigorous performance guarantees relied specifically on Gaussian random measurement vectors. To date, it remains unclear which properties of the measurements render the problem well-posed. With this question in mind, we employ the concept of spherical t-designs to achieve a partial derandomziation of PhaseLift. Spherical designs are ensembles of vectors which reproduce the first 2t moments of the uniform distribution on the complex unit sphere. As such, they provide notions of “evenly distributed” sets of vectors, ranging from tight frames (t = 1) to the full sphere, as t approaches infinity. Beyond the specific case of PhaseLift, this result highlights the utility of spherical designs for the derandomization of data recovery schemes.
Energy-Efficient Intrusion Detection with a Barrier of Probabilistic Sensors: Global and Local

Intrusion detection is a significant application in wireless sensor networks (WSNs). S. Kumar et al have introduced the concept of barrier coverage, which deploys sensors in a narrow belt region to guarantee that any intrusion across the region is to be detected. However, the practical issues have not been investigated such as scheduling sensors energy-efficiently while guaranteeing the detection probability of any intrusion across the region based on probabilistic sensing model. Besides, the intruders may be humans, animals, fighter planes or other things, which obviously have diverse moving speeds. In this paper, we analyze the detection probability of arbitrary path across the barrier of sensors theoretically and take the maximum speed of possible intruders into consideration since the sensor networks are designed for different intruders in different scenarios. Based on the theoretical analysis of detection probability, we formulate Minimum Weight ε-Barrier Problem about how to schedule sensors energy-efficiently and prove it is NP-hard. We propose both global and local solutions to the problem. The global solution called Minimum Weight Barrier Algorithm is a bounded approximation algorithm, based on which a localized protocol for energy-efficient scheduling is designed. To evaluate our design, we analyze the performance of our approaches theoretically and also perform extensive simulations to demonstrate the effectiveness of our proposed algorithm.
Flupirtine: A Review of Its Neuroprotective and Behavioral Properties

Flupirtine is a centrally acting non-opioid analgesic; it has been in clinical use since 1984. The pharmacological and therapeutic properties of flupirtine in pain states have been reviewed extensively (7). The present review addresses new and challenging data that have been published during recent years. In particular, it has been discovered that flupirtine, in a clinically relevant dosage range, has potent cytoand neuroprotective potential as well as anticonvulsant, and myorelaxant effects. Flupirtine reverses akinesia and rigidity in dopamine-depleted animals. These findings, and the reported reversal of N-methyl-D-aspartate (NMDA)-receptor-mediated effects, point to a functional NMDA antagonism by flupirtine. No binding of this drug at any known receptor has yet been demonstrated, but there are hints about a possible mechanism of action. Flupirtine maleate (hereafter referred to as flupirtine) was synthesized by Homburg, Degussa Pharma Group of Frankfurt, Germany in 1981 (1) and is available in Europe under the trademark of Katadolon ® (ASTA Medica AG, Frankfurt, Germany). Flupirtine can be described as a pyridine derivative that is substituted in the 2-, 3and 6-positions with different amino groups, (2-amino-3-ethoxy-carbonylamino-6-4-fluoro-benzylamino-pyridine maleate). It was originally selected for clinical evaluation as the most active compound in a group of analgesic amino-substituted pyridine derivatives. The molecular structure of flupirtine (Fig. 1) does not resemble that of any analgesic currently on the market. Its synthesis is a four-step process starting from 2,6-dichloro-3-nitro-pyridine (4). CNS Drug Reviews Vol. 4, No. 2, pp. 149–164 © 1998 Neva Press, Branford, Connecticut