Miracle-dz/UniFAR-FTUs huggingface dataset:
agonists , 4 OH-GTS-21 and S 24795

One approach for the identification of therapeutic agents for Alzheimer’s disease has focused on the research of a7 nAChR-selective agonists such as the partial agonists 3-(4-hydroxy,2-methoxybenzylidene)anabaseine (4OH-GTS-21) and, more recently, 2-[2-(4-bromophenyl)-2-oxoethyl]-1methyl pyridinium (S 24795). An alternative approach for targeting a7 nAChR has been the development of positive modulators for this receptor. In this study we examined the interactions between full or partial agonists and positive modulators of a7 nAChRs in situ in brain tissue. Three positive modulators were used, 5-hydroxyindole (5-HI), 1-(5-chloro-2,4-dimethoxy-phenyl)-3-(5-methyl-isoxanol-3-yl)-urea (PNU-120596), and genistein. Whole-cell recordings were performed in stratum radiatum interneurons from rat brain slices. Hippocampal interneurons were stimulated by ACh, choline, S 24795, or 4OH-GTS21, before and after bath perfusion with the positive modulators. 5-HI was not effective at potentiating 200 mM 4OH-GTS-21-evoked responses, however 5-HI induced a sustained potentiation of responses evoked by 30 mM 4OH-GTS-21. When 1 mM ACh and 200 mM 4OH-GTS-21 were applied alternately a7-mediated responses to both agonists were reduced, suggesting that high concentration of 4OH-GTS21 produces residual inhibition or desensitization and that 5-HI is not effective at overcoming receptor desensitization. Similar results were obtained with a7 receptors expressed in Xenopus oocytes. Interestingly, responses evoked by S 24795 were potentiated by 5-HI but not by genistein. Additionally, PNU120596 was able to potentiate a7-mediated responses, regardless of the nature of the agonist. We demonstrated that the potentiation of a7 nAChR response would depend on the nature and the effective concentration of the agonist involved and its particular interaction with the positive modulator. 2009 Elsevier Ltd. All rights reserved.
Is less more? A look at nonparticipation in Swiss active labour market programmes

This paper addresses the question of how the evaluation results for the effectiveness of active labour market policies are sensitive to the definition and interpretation of the "nonparticipation" state. Swiss active labour market programmes are re-evaluated by means of matching estimation with two different ways to handle nonparticipation. The first definition takes into account persons in the sample with no programme at all, and it leads to negative effects of almost all programmes compared to "nonparticipation". Another definition of nonparticipation is based on a "risk set" of persons who have not participated in a programme yet and search more intensely for a job instead of participating in a programme at that point of time. Nonparticipation as defined in this way loses superiority compared to other programmes. The two definitions lead to reversed findings in terms of employment. Effectiveness in this paper is furthermore measured in terms of a couple of outcomes that have not been considered so far, in order to give a clearer picture of the effects.
Efficient Learning of Mixed Membership Models

We present an efficient algorithm for learning mixed membership models when the number of variables $p$ is much larger than the number of hidden components $k$. This algorithm reduces the computational complexity of state-of-the-art tensor methods, which require decomposing an $O\left(p^3\right)$ tensor, to factorizing $O\left(p/k\right)$ sub-tensors each of size $O\left(k^3\right)$. In addition, we address the issue of negative entries in the empirical method of moments based estimators. We provide sufficient conditions under which our approach has provable guarantees. Our approach obtains competitive empirical results on both simulated and real data.
Overlapping Genes and Size Constraints in Viruses - An Evolutionary Perspective

Viruses are the simplest replicating units, characterized by a limited number of coding genes and an exceptionally high rate of overlapping genes. We sought a unified explanation for the evolutionary constraints that govern genome sizes, gene overlapping and capsid properties. We performed an unbiased statistical analysis over the ∼100 known viral families, and came to refute widespread assumptions regarding viral evolution. We found that the volume utilization of viral capsids is often low, and greatly varies among families. Most notably, we show that the total amount of gene overlapping is tightly bounded. Although viruses expand three orders of magnitude in genome length, their absolute amount of gene overlapping almost never exceeds 1500 nucleotides, and mostly confined to <4 significant overlapping instances. Our results argue against the common theory by which gene overlapping is driven by a necessity of viruses to compress their genome. Instead, we support the notion that overlapping has a role in gene novelty and evolution exploration.
A Novel Privacy-Preserving Set Aggregation Scheme for Smart Grid Communications

In this paper, we propose a novel privacy- preserving set aggregation scheme for smart grid communications. The proposed scheme is characterized by employing a group $\mathbb{G}$ of composite order $n=pq$ to achieve two-subset aggregation from a single aggregated data. With the proposed set aggregation scheme, the control center in smart grid is able to obtain more fine- grained data aggregation results for better monitoring and controlling smart grid. Detailed security analysis shows that the proposed scheme can achieve privacy-preserving property with formal proof in the random oracle model. In addition, extensive experiments are conducted, and the results demonstrate the proposed scheme is also efficient in terms of low computational costs and communication overheads.
Clinical Interventions in Aging Dovepress the Prevalence of Lacunar Infarct Decreases with Aging in the Elderly: a Case-controlled Analysis

hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms Background and purpose: Lacunar infarct (LI) is well known as a heterogeneous primary disorder of cerebral small vessel. Compelling results have demonstrated that age is a risk factor to the prevalence of LI. However, the relationship between age and the prevalence of LI remains obscure. It is essential to note the relationship between age and the prevalence of LI through more clinical data. Methods: A total of 3,500 patients were included in the case-controlled study. All data were collected from the Examination Center of Magnetic Resonance Imaging, Lu'an People's Hospital from January 2014 to December 2015. A primary discharge diagnosis of LI was done, and all subjects were evaluated as retrospective data. The relationship between the risk factors and the prevalence of diabetes and the relationship between age and the prevalence of diabetes was analyzed. A chi-square test was used to analyze the associations between different variables. A one-way analysis of variance was used to test the equality of three or more means at one time by using variances. Statistical significance was defined as a P-value of 0.05. Results: The one-way analysis of variance demonstrated that the prevalence of LI increased with age before 60 years and decreased with age after 69 years. The same results were found in both the male and the female subjects. These results showed that the age-related risk factors (hypertension, diabetes, cerebral infarct, cardiovascular diseases, smoking, and drinking) have no relationship with the prevalence of LI on the basis of age. There is a significant difference among the different age ranges (P=0.0006). Two-tailed P-value (unpaired t-test) showed the mean significant difference between 30–39 years and 40–49 years (P=0.009) and between 70–79 years and 80–100 years (P=0.0196). F-test (to compare variances) demonstrated that the variances of the different age ranges are significantly different between 30–39 years and diseases, smoking, and drinking) have no relationship with the prevalence of LI on the basis of age. A decreasing prevalence of LI with aging occurs in the elderly, while the prevalence of LI increases with aging in the young and in adults. This investigation implicates that age is not a risk factor for LI in the …
Enhanced Illumination Sensing Using Multiple Harmonics for LED Lighting Systems

This paper considers frequency division multiplexing (FDM) based illumination sensing in light emitting diode (LED) lighting systems. The purpose of illumination sensing is to identify the illumination contributions of spatially distributed LEDs at a sensor location, within a limited response time. In the FDM scheme, LEDs render periodical illumination pulse trains at different frequencies with prescribed duty cycles. The problem of interest is to estimate the amplitudes of the individual illumination pulse trains. In our previous work, an estimation approach was proposed using the fundamental frequency component of the sensor signal. The number of LEDs that can be supported by this estimation approach is limited to around 100 LEDs at a response time of 0.1 s. For future LED lighting systems, however, it is desirable to support many more LEDs. To this end, in this paper, we seek to exploit multiple harmonics in the sensor signal. We first derive upper limits on the number of LEDs that can be supported in the presence of frequency offsets and noise. Thereafter, we propose a low complexity successive estimation approach that effectively exploits the multiple harmonics. It is shown that the number of the LEDs can be increased by a factor of at least five, compared to the estimation approach using only the fundamental frequency component, at the same estimation error.
Mobile Stand-alone Application Code Off-loading: Architecture and Challenges

migrating code for execution from a device to a remote server has been a topic of active research for nearly a few years now. With the advent and the rapid growth of mobile devices, this area has been extended to mobile operating systems. Although mobile devices such as phones and tablets are available with increasing the hardware specifications to include more RAM and CPU cores, they do not often keep up with the demands of ever growing mobile applications. In the context of mobile devices, this field has come to be known as Mobile Cloud Computing (MCC). It combines mobile computing and cloud computing to achieve dynamic code migration of applications to a remote server, achieve reduced power usage and faster execution. In this paper, a review of the most prevalent techniques of MCC that are shaping this field is done. The paper also covers the complete architecture that is used to achieve these results. Along with various architectures, approaches a study of their advantages and disadvantages, as well as the way forward is discussed.
A modified Generalized Likelihood Ratio test for detection and isolation of multiple sequential faults

To solve the problem of diagnosis of multiple sequential faults, [16] have developed the Generalized Likelihood Ratio (GLR) test. After each detection and isolation of one jump, the treatment of another possible jump is obtained by a direct state estimate and covariance incrementation of the Kalman filter originally designed on the jump-free system. With this updating strategy, the rate of good decisions is not guaranted to be maximized. To solve this problem, the proposed active GLR test will be based on a reference model updated on line after each detection and isolation of one jump. An illustrative example shows the performance of the proposed approach.
Comparison of Heuristics Procedures for An Integrated Model for Production and Distribution Planning in an Environment of Shared Resources

In this paper, we present a mathematical model which integrates tactical-operational production and distribution decisions in a shared resources environment. More precisely, we integrate lot sizing production and distribution decisions with vehicle routing decisions. We obtain a global multi-period multi-item multi-vehicle model where a capacity constraint models the link between production and distribution decisions. Three heuristics are presented in order to solve this global model. The first two ones are based on a decomposition approach of the global model in production and distribution submodels. The third heuristic offers a higher level of integration by taking into account transportation decisions in the production planning problem. Computational tests show that the performance of the heuristic depends on the amount of shared resources in the system, the type of customer demand but not on the weight of the production cost against the distribution cost. The three heuristics allow to tackle problems of larger size than an optimal solution approach.
Groups in organization and organizational communication

The real group is formed to achieve common goals to unite the efforts required in the joint action. In order to become a real group, the community of people must have and be aware of the overall purpose of the activity, have the knowledge and skills needed for the group activity and realize group unity. In the real group, there are necessarily processes of communication, which make possible the group decisions, assessments, opinions and "common language", the volitional and emotional unity of its members.
Beyond the disciplinary role of governance: how boards and donors add value to Spanish founda-tions

Foundations play a key role in the development of modern societies, helping to funnel private wealth to social services and educational and research activities. Using a sample of Spanish foundations, we present evidence on the effect of the board composition and institutional donors on foundations' organizational efficiency. We show that board size and independence do not directly impact the entity’s efficiency. Instead, the heterogeneity of knowledge inside the boardroom and the proactive character of trustees have a positive influence on resource allocation. We confirm the benefits of a private institutional donor who effectively monitors managerial decisions.
ADAPTATION OF CONTROL PROGRAMS TO ASYNCHRONOUS I/O UPDATES

The paper discusses the problems with adaptation of industrial control programs from synchronous to asynchronous I/O update when peripherals are redeveloped with the aid of control area networks (CANs). CANs decrease necessary wires between controllers and technology, but they have lower data update rates in comparison with I/O buses. To accelerate and optimize I/O polling, I/O data can be updated asynchronously to evaluations of control algorithms. If a control program was written with the assumption of synchronous I/O updates, its adaptation to asynchronous I/O updates requires its partial modifications to exclude possibility of dataraces. The simplest and robust way represents simulating of synchronous I/O updates by copying all input values into an array before each evaluation of the program, but such spare buffering generally increases responses to events. Therefore, the paper presents conditions for running the program (or its parts) without spare buffering of I/O data. Copyright c © IFAC 2004
The Information Loss Problem of Black Hole and the First Order Phase Transition in String Theory

In recent years, Susskind, Thorlacius and Uglum have proposed a model for strings near a black hole horizon in order to represent the quantum mechanical entropy of the black hole and to resolve the information loss problem. However, this model is insufficient because they did not consider the metric modification due to massive strings and did not explain how to carry information from inside of the horizon to the outside world. In this paper, we present a possible, intuitive model for the time development of a black hole in order to solve the information loss problem. In this model, we assume that a first order phase transition occurs near the Hagedorn temperature and the string gas changes to hypothetical matter with vanishing entropy and energy which we call `the Planck solid'. We also study the background geometry of black holes in this picture and find out that there is no singularity within the model.
Dyonic dilaton black holes

The properties of static spherically symmetric black holes, which are both electrically and magnetically charged, and which are coupled to the dilaton in the presence of a cosmological constant, , are considered. It is shown that apart from the Reissner--Nordstrom--de Sitter solution with constant dilaton, such solutions do not exist if (in arbitrary spacetime dimension ). However, asymptotically anti-de Sitter dyonic black-hole solutions with a non-trivial dilaton do exist if . Both these solutions and the asymptotically flat () solutions are studied numerically for arbitrary values of the dilaton coupling parameter, , in four dimensions. The asymptotically flat solutions are found to exhibit two horizons if and one horizon otherwise. For asymptotically anti-de Sitter solutions the result is similar, but the corresponding values of are altered in a non-linear fashion which depends on and the mass and charges of the black holes. All dyonic solutions with are found to have zero Hawking temperature in the extreme limit, however, regardless of the value of .
An Incremental Design of Compact Radial Basis Function Networks

—This paper proposes an offline algorithm for incrementally constructing and training radial basis function (RBF) networks. In each iteration of the Error Correction (ErrCor) algorithm, one RBF unit is added to fit and then eliminate the highest peak (or lowest valley) in the error surface. This process is repeated until a desired error level is reached. Experimental results on real world data sets show that the ErrCor algorithm designs very compact RBF networks compared to the other investigated algorithms. Several benchmark tests such as the duplicate patterns test and the two spiral problem were applied to show the robustness of the ErrCor algorithm. The proposed ErrCor algorithm generates very compact networks. This compactness leads to greatly reduced computation times of trained networks.
A decentralized smartphone based Traffic Information System

Location-Based Services (LBSs) are information or entertainment services where the request, the response and served contents depend on the physical position of the requesting device. LBS are frequently used to implement Traffic Information Systems (TIS), which are increasingly based on user-contributed information. In this paper we present the first prototype of our solution for a decentralized, smartphone-based TIS, called D4V, that allows each participant vehicle to efficiently discover data or services located near any chosen geographic position. The experimental evaluation has shown that D4V could be effectively used on the road to reduce the number of drivers involved in traffic jams, as well as to disseminate alert messages about potentially dangerous road stretches, thus allowing drivers to reduce risks and nuisances along their paths.
A suite of web-based programs to search for transcriptional regulatory motifs

The identification of regulatory motifs is important for the study of gene expression. Here we present a suite of programs that we have developed to search for regulatory sequence motifs: (i) BioProspector, a Gibbs-sampling-based program for predicting regulatory motifs from co-regulated genes in prokaryotes or lower eukaryotes; (ii) CompareProspector, an extension to BioProspector which incorporates comparative genomics features to be used for higher eukaryotes; (iii) MDscan, a program for finding protein-DNA interaction sites from ChIP-on-chip targets. All three programs examine a group of sequences that may share common regulatory motifs and output a list of putative motifs as position-specific probability matrices, the individual sites used to construct the motifs and the location of each site on the input sequences. The web servers and executables can be accessed at http://seqmotifs.stanford. edu.
Analyze on the Learning Behavior of E-Learning

In e-learning, students must learn initiatively according to their own progress via computer and Internet. That is to say, students often handle contents transmitted from far side in front of computer by themselves. In the meanwhile students have to determine "what to learn" and "where to go" in each learning unit (or learning node), so, it relatively consumes mental and physical efforts during learning that results in cognitive overload, therefore, students are easy to feel anxious about e-learning content due to said cognitive overload. Purpose of this paper is to collect the learning behavior trace during e-learning activity, and then use decision tree ID 3 to discover strenuous place in the hyperlink of elearning in order to avoid anxiety of e-learning. Based on the analysis of ID 3, the curriculum designers of e-learning will be easy to visually understand students’ behavior on e-learning by treelike graph, and then compose a well-organized and adaptive e-learning curriculum.
Workload-aware table splitting for NoSQL

Massive scale data stores, which exhibit highly desirable scalability and availability properties are becoming pivotal systems in nowadays infrastructures. Scalability achieved by these data stores is anchored on data independence; there is no clear relationship between data, and atomic inter-node operations are not a concern. Such assumption over data allows aggressive data partitioning. In particular, data tables are horizontally partitioned and spread across nodes for load balancing. However, in current versions of these data stores, partitioning is either a manual process or automated but simply based on table size. We argue that size based partitioning does not lead to acceptable load balancing as it ignores data access patterns, namely data hotspots. Moreover, manual data partitioning is cumbersome and typically infeasible in large scale scenarios. In this paper we propose an automated table splitting mechanism that takes into account the system workload. We evaluate such mechanism showing that it simple, non-intrusive and effective.
Sensor failure detection and recovery by neural networks

Describes a method of sensor failure detection, isolation, and accommodation using a neural network approach. In a propulsion system such as the Space Shuttle main engine (SSME), the dynamics are complicated and sometimes not well known. However, the number of variables measured is usually much higher than the order of the system. This built-in redundancy of the sensors can be utilized to detect and correct sensor failure problems. The goal is to train a neural network to identify the sensor whose measurement is not consistent with other sensor outputs. Another neural network is trained to recover the value of critical variables when their measurements fail. Techniques for training the network with a limited amount of data are developed. The proposed scheme was tested using simulated data of the SSME in-flight sensor group. <<ETX>>
A 3-Bit Pseudo Flash ADC Based Low-Power CMOS Interface Circuit Design for Optical Sensor

The paper presents a CMOS interface circuit desig nf or optical pH measurement that can produce an 8-bit digital output representing the color information (i.e., wavelength, l). In this work we are focusing at reducing the component count by design and hence reducing the cost and silicon area. While it could be further optimized for lower power consumption, the proposed design has been implemented using standard cells provided by the foundry (i.e., AMS 0.35 ! mC MOS) for proof of concept. The biasing current and power consumption of the fabricated chip are measured at 11 ! A and 37 ! Wr espectively using 3.3 Vs upply voltage. Experimental results have further validated the proposed design concept. The number of detectable colors is eight and can be extended to a higher number without any major change in the architecture.