Miracle-dz/UniFAR-FTUs huggingface dataset:
UB-165: A Novel Nicotinic Agonist with Subtype Selectivity Implicates the α4β2* Subtype in the Modulation of Dopamine Release from Rat Striatal Synaptosomes

Presynaptic nicotinic acetylcholine receptors (nAChRs) on striatal synaptosomes stimulate dopamine release. Partial inhibition by the α3β2-selective α-conotoxin-MII indicates heterogeneity of presynaptic nAChRs on dopamine terminals. We have used this α-conotoxin and UB-165, a novel hybrid of epibatidine and anatoxin-a, to address the hypothesis that the α-conotoxin-MII-insensitive subtype is composed of α4 and β2 subunits. UB-165 shows intermediate potency, compared with the parent molecules, at α4β2* and α3-containing binding sites, and resembles epibatidine in its high discrimination of these sites over α7-type and muscle binding sites. (±)-Epibatidine, (±)-anatoxin-a, and (±)-UB-165 stimulated [3H]-dopamine release from striatal synaptosomes with EC50 values of 2.4, 134, and 88 nm, and relative efficacies of 1:0.4:0.2, respectively. α-Conotoxin-MII inhibited release evoked by these agonists by 48, 56, and 88%, respectively, suggesting that (±)-UB-165 is a very poor agonist at the α-conotoxin-MII-insensitive nAChR subtype. In assays of 86Rb+ efflux from thalamic synaptosomes, a model of an α4β2* nAChR response, (±)-UB-165 was a very weak partial agonist; the low efficacy of (±)-UB-165 at α4β2 nAChR was confirmed in Xenopus oocytes expressing various combinations of human nAChR subunits. In contrast, (±)-UB-165 and (±)-anatoxin-a were similarly efficacious and similarly sensitive to α-conotoxin-MII in increasing intracellular Ca2+ in SH-SY5Y cells, a functional assay for native α3-containing nAChR. These data support the involvement of α4β2* nAChR in the presynaptic modulation of striatal dopamine release and illustrate the utility of exploiting a novel partial agonist, together with a selective antagonist, to dissect the functional roles of nAChR subtypes in the brain.
Biogeosciences Natural and human-induced hypoxia and consequences for coastal areas : synthesis and future development

Hypoxia has become a world-wide phenomenon in the global coastal ocean and causes a deterioration of the structure and function of ecosystems. Based on the collective contributions of members of SCOR Working Group #128, the present study provides an overview of the major aspects of coastal hypoxia in different biogeochemical provinces, including estuaries, coastal waters, upwelling areas, fjords and semi-enclosed basins, with various external forcings, ecosysCorrespondence to: J. Zhang (jzhang@sklec.ecnu.edu.cn) tem responses, feedbacks and potential impact on the sustainability of the fishery and economics. The obvious external forcings include freshwater runoff and other factors contributing to stratification, organic matter and nutrient loadings, as well as exchange between coastal and open ocean water masses. Their different interactions set up mechanisms that drive the system towards hypoxia. Coastal systems also vary in their relative susceptibility to hypoxia depending on their physical and geographic settings. It is understood that coastal hypoxia has a profound impact on the sustainability of ecosystems, which can be seen, for example, by the change in the food-web structure and system function; other Published by Copernicus Publications on behalf of the European Geosciences Union. 1444 J. Zhang et al.: Natural and human-induced hypoxia and consequences for coastal areas influences include compression and loss of habitat, as well as changes in organism life cycles and reproduction. In most cases, the ecosystem responds to the low dissolved oxygen in non-linear ways with pronounced feedbacks to other compartments of the Earth System, including those that affect human society. Our knowledge and previous experiences illustrate that there is a need to develop new observational tools and models to support integrated research of biogeochemical dynamics and ecosystem behavior that will improve confidence in remediation management strategies for coastal hypoxia.
On the Exact Model Matching of linear singular multi-delay systems via measurement output feedback

The general class of linear singular neutral multi delay systems is introduced. The controller is of the general proportional multi delay measurement output feedback type. For the case of regularizable linear singular multi delay systems the design problem of Exact Model Matching (EMM) is solved under the assumption that the ideal model is left invertible. The necessary and sufficient conditions for the problem to admit a realizable controller solution are established and the general solution of the realizable controllers is derived.
Tarski's System of Geometry

Abstract This paper is an edited form of a letter written by the two authors (in the name of Tarski) to Wolfram Schwabhäuser around 1978. It contains extended remarks about Tarski's system of foundations for Euclidean geometry, in particular its distinctive features, its historical evolution, the history of specific axioms, the questions of independence of axioms and primitive notions, and versions of the system suitable for the development of 1-dimensional geometry.
THE IMPACT OF GESTALT PRINCIPLES ON SOLVING GEOMETRIC PROPORTIONAL ANALOGIES

Analogy making is a highly sophisticated task and requires intelligence, since analogous patterns in two given stimuli are often not obvious and require a certain conceptualization. In this paper, we investigate solution strategies for ambiguous proportional geometric analogies. We constructed different analogies which were varied in such a way that they trigger different perceptions. Different solutions were constructed when subjects perceived different dominant structural patterns. The experiment investigates preferred solutions for these analogy variations, analyzes the influence of Gestalt principles on the perception of structural patterns in geometric figures, and examines how this influence leads to different solutions for the same analogy problem.
Anemia and iron deficiency in gastrointestinal and liver conditions

Iron deficiency anemia (IDA) is associated with a number of pathological gastrointestinal conditions other than inflammatory bowel disease, and also with liver disorders. Different factors such as chronic bleeding, malabsorption and inflammation may contribute to IDA. Although patients with symptoms of anemia are frequently referred to gastroenterologists, the approach to diagnosis and selection of treatment as well as follow-up measures is not standardized and suboptimal. Iron deficiency, even without anemia, can substantially impact physical and cognitive function and reduce quality of life. Therefore, regular iron status assessment and awareness of the clinical consequences of impaired iron status are critical. While the range of options for treatment of IDA is increasing due to the availability of effective and well-tolerated parenteral iron preparations, a comprehensive overview of IDA and its therapy in patients with gastrointestinal conditions is currently lacking. Furthermore, definitions and assessment of iron status lack harmonization and there is a paucity of expert guidelines on this topic. This review summarizes current thinking concerning IDA as a common co-morbidity in specific gastrointestinal and liver disorders, and thus encourages a more unified treatment approach to anemia and iron deficiency, while offering gastroenterologists guidance on treatment options for IDA in everyday clinical practice.
Hydroxyectoine Is Superior to Trehalose for Anhydrobiotic Engineering of Pseudomonas putida KT2440

ABSTRACT Anhydrobiotic engineering aims to increase the level of desiccation tolerance in sensitive organisms to that observed in true anhydrobiotes. In addition to a suitable extracellular drying excipient, a key factor for anhydrobiotic engineering of gram-negative enterobacteria seems to be the generation of high intracellular concentrations of the nonreducing disaccharide trehalose, which can be achieved by osmotic induction. In the soil bacterium Pseudomonas putida KT2440, however, only limited amounts of trehalose are naturally accumulated in defined high-osmolarity medium, correlating with relatively poor survival of desiccated cultures. Based on the enterobacterial model, it was proposed that increasing intracellular trehalose concentration in P. putida KT2440 should improve survival. Using genetic engineering techniques, intracellular trehalose concentrations were obtained which were similar to or greater than those in enterobacteria, but this did not translate into improved desiccation tolerance. Therefore, at least for some populations of microorganisms, trehalose does not appear to provide full protection against desiccation damage, even when present at high concentrations both inside and outside the cell. For P. putida KT2440, it was shown that this was not due to a natural limit in desiccation tolerance since successful anhydrobiotic engineering was achieved by use of a different drying excipient, hydroxyectoine, with osmotically preconditioned bacteria for which 40 to 60% viability was maintained over extended periods (up to 42 days) in the dry state. Hydroxyectoine therefore has considerable potential for the improvement of desiccation tolerance in sensitive microorganisms, particularly for those recalcitrant to trehalose.
Classification with emotional faces via a robust sparse classifier

We consider the problem of emotion recognition in faces as well as subject identification in the presence of emotional facial expressions. We propose alternative solutions for this identification and recognition problems using the idea of sparsity, in terms of Sparse Representation based Classifier (SRC) paradigm. In both cases, the problem is formulated as finding the most parsimonious set of representatives from a training set, which will best reconstruct the test image. For emotion classification, we considered the six fundamental states and the SRC performance was compared with that of the Active Appearance Model (AAM) algorithm [1]. For face recognition displaying various emotions, in order to test the robustness of SRC, we considered gallery faces of subjects having one or more expression variety while the probe faces had a different expression. We experimented with both the whole faces or faces observed with multiple blocks. The SRC algorithm, while not demanding any training, performed surprisingly well in both emotion identification across subjects and subject identification across emotions.
Control of Nonlinear Stochastic Systems: Model-Free Controllers versus Linear Quadratic Regulators

Classical linear controllers are widely used in the control of nonlinear stochastic systems and thus there is concern about the ability of the controller to adequately regulate the system. An alternative approach to cope with such systems is to avoid the need to build the traditional "open-loop" model for the system. Through the avoidance of model, controllers can be built for arbitrarily complex nonlinear systems via neural-networks trained by simultaneous perturbation stochastic approximation so that only the output error (between the plant and target outputs) is needed. In this paper, we discuss basic characteristics and limitations of both approaches and formally analyze this comparison in the case of linear quadratic regulators. The comparison is illustrated numerically on a simulated nonstationary multiple input, multiple output wastewater treatment system with stochastic effects
Race to the Top of the Corporate Ladder: What Minorities Do When They Get There

Racing to the top of the corporate hierarchy is difficult, no matter how qualified or capable the candidate. Producing more widgets than one's competitors is not enough. Negotiating the political landscape of the institution is also required. More specifically, individual corporate officers have to be appeased, powerful interest groups have to be co-opted and made allies, and competitors have to be undermined or eliminated. The more bureaucratic the organization and the more opaque the promotion process, the more important this institutional game to climbing the corporate ladder. This chapter identifies the kind of racial minorities or racial types who are likely to play this game well and, consequently, race to the top of the corporation. It then explains why these racial types might not have the racial commitment, or feel institutionally empowered, to lift other people of color as they climb the corporate ladder.
A Fast Iterated Orthogonal Projection Framework for Smoke Simulation

We present a fast iterated orthogonal projection (IOP) framework for smoke simulations. By modifying the IOP framework with a different means for convergence, our framework significantly reduces the number of iterations required to converge to the desired precision. Our new iteration framework adds a divergence redistributor component to IOP that can improve the impeded convergence logic of IOP. We tested Jacobi, GS and SOR as divergence redistributors and used the Multigrid scheme to generate a highly efficient Poisson solver. It provides a rapid convergence rate and requires less computation time. In all of our experiments, our method only requires 2-3 iterations to satisfy the convergence condition of 1e-5 and 5-7 iterations for 1e-10. Compared with the commonly used Incomplete Cholesky Preconditioned Conjugate Gradient(ICPCG) solver, our Poisson solver accelerates the overall speed to approximately 7- to 30-fold faster for grids ranging from <inline-formula><tex-math notation="LaTeX"> $128^3$</tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="yang-ieq1-2446474.gif"/></alternatives> </inline-formula> to <inline-formula><tex-math notation="LaTeX">$256^3$</tex-math><alternatives> <inline-graphic xlink:type="simple" xlink:href="yang-ieq2-2446474.gif"/></alternatives></inline-formula>. Our solver can accelerate more on larger grids because of the property that the iteration count required to satisfy the convergence condition is independent of the problem size. We use various experimental scenes and settings to demonstrate the efficiency of our method. In addition, we present a feasible method for both IOP and our fast IOP to support free surfaces.
Hybrid Genetic-Based Support Vector Regression with Feng Shui Theory for Appraising Real Estate Price

In this paper, we proposed a novel house prediction model that integrated hybrid genetic-based support vector regression (HGA-SVR) model and Feng Shui theories for developing a high accuracy appraising real estate price system in Taiwan. In Taiwan, Feng Shui theory applies in choosing good days, divination and house selection. From the past researches, many factors might affect the real estate price which are the announced land values, the building room age, building total number of floor, the transportation condition and surrounding environment of house etc. However, few studies have been considered the Feng Shui effects in appraising real estate price. Therefore, the present study pioneers in applying Feng Shui theories for developing a high accuracy real estate price prediction system with back-propagation neural network(BPN), fuzzy neural network (FNN) and Hybrid Genetic-based SVR (HGA-SVR) to compare.Our results obtained from the comparison between two house price models with various artificial neural network models. By comparing the accuracy with various network architectures, the result demonstrates that HGA-SVR is the best network architecture and the Feng Shui model has a better performance in BPN, FNN and HGA-SVR. Our house price prediction system discovers some real estate price much higher than the reasonable prices. This result shows these unreasonable price needs adjusting to become more reasonable to conform the housing market.
Word Sense Disambiguation Based on Feature Ranking Graph

Research in the field of WSD has been conducted in computational linguistics as a specific task for many years. Language and context features have been shown to be very helpful for the task of word sense disambiguation. In this paper, we investigate the effectiveness of the graph-based ranking method on features from limited language data of word sense disambiguation. Contrary to existing method, we adopt different features and the result shows graph-based re-ranking approach improves the effective of word sense disambiguation systems.
Bayesian Audio Alignment based on a Unified Model of Music Composition and Performance

Thispaperpresentsanewprobabilisticmodelthatcanalign multiple performances of a particular piece of music. Conventionally, dynamictimewarping(DTW)andleft-to-right hidden Markov models (HMMs) have often been used for audio-to-audio alignment based on a shallow acoustic similarity between performances. Those methods, however, cannot distinguish latent musical structures common to all performances and temporal dynamics unique to each performance. To solve this problem, our model explicitly represents two state sequences: a top-level sequence that determines the common structure inherent in the music itself and a bottom-level sequence that determines the actual temporal fluctuation of each performance. These two sequences are fused into a hierarchical Bayesian HMM and can be learned at the same time from the given performances. Since the top-level sequence assigns the same state for note combinations that repeatedly appear within a piece of music, we can unveil the latent structure of the piece. Moreover, we can easily compare different performances of the same piece by analyzing the bottom-level sequences. Experimental evaluation showed that our method outperformed the conventional methods.
Soft switching active-clamped dual series-resonant converter

A soft switching active-clamp dual series-resonant converter is proposed in this paper. Two small transformers are used at the proposed topology to provide more load power. An active-clamp circuit is used to absorb the energy stored in the leakage inductor of transformer, to clamp voltage stresses across switches, and to realize the ZVS turn-on of switches in order to alleviate the switching losses. In order to remove the reverse-recovery problem on output diodes, the ZCS turn-off is realized by choosing the properly angle frequency on the secondary side. Analysis of mode operation, design considerations and experimental results of the proposed ZVZCS converter are described in detail. Finally, a 200W ZVZCS prototype treated under Vin=48V, Vo=200V is implemented to verify the practicability of the proposed converter.
Dynamic TXOP allocation for multimedia QoS providing over wireless networks

IEEE 802.11e has established a new access mechanism called the Hybrid Coordination Function (HCF) as a step toward provisioning Quality of Service (QoS) support in the wireless networks. However IEEE 802.11e scheduler shows poor performance for multimedia traffics. To solve this problem, we propose a Dynamic Transmission Opportunity (TXOP) allocation scheme in providing QoS for multimedia application, which assign the variable length of TXOP to different traffics based on the number of Service Data Units (SDUs) to be transmitted. Through the performance evaluations, we prove that our proposed scheme improves the packet delivery ratio, throughput, and the end-to-end delay.
Indirect Weighted Association Rules Mining for Academic Network Collaboration Recommendations

Collaborative research is increasingly important and popular in academic circles. However for young researchers identifying new research collaborators to form joint research and analyzing the level of cooperation of the current partners can be a very complex task. Thus recommendation of new collaborations would be important for young researchers. This paper presents a new approach to recommend collaborators in an academic social network using the co-authorship network. We propose a weighted indirect rule mining approach using a novel weighting mechanism called sociability.
MULTIPLE DICTIONARIES FOR BAG OFWORDS LARGE SCALE IMAGE SEARCH

We explore building better dictionaries of visual words in Bag of Words (BoW) systems for searching large scale image collections. We propose a novel way to use more visual words in the BoW algorithm that significantly increases the recognition performance: combining multiple dictionaries built from different subsets of the features. We report improvement in performance by 40-45% over the baseline method and discuss how it can be parallelized on multiple machines to achieve faster run time. Finally, we show that our method is flexible, and provides 25-38% improvement over the startof-the-art Hamming Embedding method.
Inferring Epidemiological Control Strategies from Complex Network Models of Disease Propagation

Severe acute respiratory syndrome (SARS) exhibits several interesting transmission characteristics: spread within specific, but disjoint, geographical regions; and, so-called super-spreader events (SSE). We describe a complex network model which is capable of reproducing these features and apply it to the SARS transmission data from Hong Kong during 2003. We find that the observed data is typical of the models, and that the models are capable of a wide range of behaviours. However, we conclude that transmission within hospitals was a crucial factor for the severity of the SARS outbreak in Hong Kong. Moderately restrictive control practices in the early stages of an outbreak would be sufficient to contain infection and limit contagion
Transcriptional Regulation of Pyruvate Dehydrogenase Kinase

The pyruvate dehydrogenase complex (PDC) activity is crucial to maintains blood glucose and ATP levels, which largely depends on the phosphorylation status by pyruvate dehydrogenase kinase (PDK) isoenzymes. Although it has been reported that PDC is phosphorylated and inactivated by PDK2 and PDK4 in metabolically active tissues including liver, skeletal muscle, heart, and kidney during starvation and diabetes, the precise mechanisms by which expression of PDK2 and PDK4 are transcriptionally regulated still remains unclear. Insulin represses the expression of PDK2 and PDK4 via phosphorylation of FOXO through PI3K/Akt signaling pathway. Several nuclear hormone receptors activated due to fasting or increased fat supply, including peroxisome proliferator-activated receptors, glucocorticoid receptors, estrogen-related receptors, and thyroid hormone receptors, also participate in the up-regulation of PDK2 and PDK4; however, the endogenous ligands that bind those nuclear receptors have not been identified. It has been recently suggested that growth hormone, adiponectin, epinephrine, and rosiglitazone also control the expression of PDK4 in tissue-specific manners. In this review, we discuss several factors involved in the expressional regulation of PDK2 and PDK4, and introduce current studies aimed at providing a better understanding of the molecular mechanisms that underlie the development of metabolic diseases such as diabetes.
South Africa's Trade and Growth

This paper examines key trade and trade related issues facing South Africa. It describes South Africa‘s re-entry into the global trade architecture and its economic growth in the context of its trade performance, as well as the composition and performance of South African exports at the product and sector level in the period from the early 1990s to 2006. The study also assesses South Africa‘s comparative trade performance based on a gravity model of international trade and discusses some key historical and recent trade policy developments. Finally, the study provides an econometric assessment of the impact of South Africa‘s trade liberalisation during the period from 1988 to 2003 on labour and total factor productivity across its industrial sectors. It shows that while South African trade performance has been good in recent years there is significant room to liberalise further as an adjunct to labour market reforms. Further trade policy liberalisation would bring about important equity and efficiency gains. Multilateral trade liberalisation has the potential to maximise the gains and ease the transition to freer trade for South Africa but unilateral liberalisation also deserves consideration.