Miracle-dz/UniFAR-FTUs huggingface dataset:
Intramembrane charge movements and excitation– contraction coupling expressed by two-domain fragments of the Ca2+ channel

To investigate the molecular basis of the voltage sensor that triggers excitation–contraction (EC) coupling, the four-domain pore subunit of the dihydropyridine receptor (DHPR) was cut in the cytoplasmic linker between domains II and III. cDNAs for the I-II domain (α1S 1–670) and the III-IV domain (α1S 701-1873) were expressed in dysgenic α1S-null myotubes. Coexpression of the two fragments resulted in complete recovery of DHPR intramembrane charge movement and voltage-evoked Ca2+ transients. When fragments were expressed separately, EC coupling was not recovered. However, charge movement was detected in the I-II domain expressed alone. Compared with I-II and III-IV together, the charge movement in the I-II domain accounted for about half of the total charge (Qmax = 3 ± 0.23 vs. 5.4 ± 0.76 fC/pF, respectively), and the half-activation potential for charge movement was significantly more negative (V1/2 = 0.2 ± 3.5 vs. 22 ± 3.4 mV, respectively). Thus, interactions between the four internal domains of the pore subunit in the assembled DHPR profoundly affect the voltage dependence of intramembrane charge movement. We also tested a two-domain I-II construct of the neuronal α1A Ca2+ channel. The neuronal I-II domain recovered charge movements like those of the skeletal I-II domain but could not assist the skeletal III-IV domain in the recovery of EC coupling. The results demonstrate that a functional voltage sensor capable of triggering EC coupling in skeletal myotubes can be recovered by the expression of complementary fragments of the DHPR pore subunit. Furthermore, the intrinsic voltage-sensing properties of the α1A I-II domain suggest that this hemi-Ca2+ channel could be relevant to neuronal function.
Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints

The factors that determine the origin and fate of cross-species transmission events remain unclear for the majority of human pathogens, despite being central for the development of predictive models and assessing the efficacy of prevention strategies. Here, we describe a flexible Bayesian statistical framework to reconstruct virus transmission between different host species based on viral gene sequences, while simultaneously testing and estimating the contribution of several potential predictors of cross-species transmission. Specifically, we use a generalized linear model extension of phylogenetic diffusion to perform Bayesian model averaging over candidate predictors. By further extending this model with branch partitioning, we allow for distinct host transition processes on external and internal branches, thus discriminating between recent cross-species transmissions, many of which are likely to result in dead-end infections, and host shifts that reflect successful onwards transmission in the new host species. Our approach corroborates genetic distance between hosts as a key determinant of both host shifts and cross-species transmissions of rabies virus in North American bats. Furthermore, our results indicate that geographical range overlap is a modest predictor for cross-species transmission, but not for host shifts. Although our evolutionary framework focused on the multi-host reservoir dynamics of bat rabies virus, it is applicable to other pathogens and to other discrete state transition processes.
Honeypot-Powered Malware Reverse Engineering

Honeypots, i.e. networked computer systems specially designed and crafted to mimic the normal operations of other systems while capturing and storing information about the interactions with the world outside, are a crucial technology into the study of cyber threats and attacks that propagate and occur through networks. Among them, high-interaction honeypots are considered the most efficient because the attacker (whether automated or not) perceives realistic interactions with the target machine. In the case of automated attacks, propagated by malware, currently available honeypots alone are not specialized enough to allow the analysis of their behaviors and effects on the target system. The research presented in this paper shows how high-interaction honeypots can be enhanced by powering them with specific features that improve the reverse engineering activities needed to effectively analyze captured malicious entities.
Politics of Competition for Foreign Direct Investment : A Simple Theory

We study the impact of special interest politics on competition for a multinational between two countries. We show that whether a country will win this competition is determined by both economic factors, which include for which country foreign direct investment will bring more national welfare, and in which country the multinational will make more profits; and to what extent each country’s government is influenced by domestic special interest groups. Now a country that benefits less from foreign direct investment, and is not the multinational’s preferred location, may win this competition provided that its government is far more influenced by special interest groups, so that the cost it can bear to attract the multinational can be greater than the cost its rival can bear to attract the multinational. This implies that allocative efficiency cannot be always achieved.
Motivational principles for visual know-how development

What dynamics can enable a robot to continuously develop new visual know-how? We present a first experimental investigation where an AIBO robot develops visual competences from scratch driven only by internal motivations. The motivational principles used by the robot are independent of any particular task. As a consequence, they can constitute the basis for a general approach to sensory-motor development.
Opting-in or Opting-out on the Internet: Does it Really Matter?

Personal privacy has become one of the pressure points that comprises utmost primacy in the scientific community. An often debated privacy issue concerns the means of soliciting consent on the use of consumer information: should consumers be asked to object to the use of personal data (opt-out), or should they be asked to consent to the use of such data (opt-in)? These questions have been the center of controversy in Internet privacy for the past few years; various industry and consumer associations hold contradictory opinions on these questions. This paper integrates various theoretical perspectives that could potentially explain the difference in consumer participation between opt-in and opt-out configurations. Specifically, an experiment was conducted to observe the responses of a group of subjects under both opt-in and opt-out scenarios. In addition, we measured the privacy concerns of the subjects and examined whether these concerns could influence the effectiveness of the two registration mechanisms. Our results show that the use of opt-in and optout could induce different participation levels, and the disparity in participation was more substantial among the less privacy-concerned population. These findings provide valuable insights to regulatory bodies in formulating privacy policies and help Internet Web sites design proper data collection practices.
CoCloRep : A DSL for Code Clones

Code clones are pieces of code that are duplicated in multiple locations in the source code of a software application. The existence of these clones and the availability of clone detection tools to find them lend to the need for techniques to analyze the clones in an effort to enhance the quality of the source code. This paper describes an investigation into the development of CoCloRep, a Domain-Specific Language (DSL) for the representation of code clones. The benefits of Model-Driven Engineering (MDE) in this context are observed through the use of model transformations on the clones that are represented by instances of this DSL. These transformations provide a means to analyze the clones. The DSL is developed in the AMMA platform (ATLAS Model Management Architecture), which is a modeling tool that provides features through its own DSLs to specify metamodels and to perform transformations on models.
Interactive channel capacity

We study the interactive channel capacity of an ε-noisy channel. The interactive channel capacity C(ε) is defined as the minimal ratio between the communication complexity of a problem (over a non-noisy channel), and the communication complexity of the same problem over the binary symmetric channel with noise rate ε, where the communication complexity tends to infinity. Our main result is the upper bound C(ε) ≤ 1-Ω(√H(ε)). This compares with Shannon's non-interactive channel capacity of 1-H(ε). In particular, for a small enough ε, our result gives the first separation between interactive and non-interactive channel capacity, answering an open problem by Schulman [Schulman1]. We complement this result by the lower bound C(ε) ≥ 1-O(√H(ε)), proved for the case where the players take alternating turns.
Distinct Phyllosphere Bacterial Communities on Arabidopsis Wax Mutant Leaves

The phyllosphere of plants is inhabited by diverse microorganisms, however, the factors shaping their community composition are not fully elucidated. The plant cuticle represents the initial contact surface between microorganisms and the plant. We thus aimed to investigate whether mutations in the cuticular wax biosynthesis would affect the diversity of the phyllosphere microbiota. A set of four Arabidopsis thaliana eceriferum mutants (cer1, cer6, cer9, cer16) and their respective wild type (Landsberg erecta) were subjected to an outdoor growth period and analysed towards this purpose. The chemical distinctness of the mutant wax phenotypes was confirmed by gas chromatographic measurements. Next generation amplicon pyrosequencing of the bacterial communities showed distinct community patterns. This observation was supported by denaturing gradient gel electrophoresis experiments. Microbial community analyses revealed bacterial phylotypes that were ubiquitously present on all plant lines (termed “core” community) while others were positively or negatively affected by the wax mutant phenotype (termed “plant line-specific“ community). We conclude from this study that plant cuticular wax composition can affect the community composition of phyllosphere bacteria.
Estimation of speaker's height and vocal tract length from speech signal

Estimation of speaker’s height and vocal tract length (VTL) from speech signal can have forensic and automatic speech recognition applications. It was suggested for a long time that there is a correlation between speaker’s VTL, on one side, and speaker’s height and formant frequencies, on another side. Until recently, these putative relationships have been empirically examined in studies employing relatively small numbers of speakers. Scattered studies presented intriguing results about the correlations between speaker’s height and various acoustic speech parameters. Due to lack of databases, few studies presented extensive comparative results between the actual speaker’s VTL and the estimated one from speech signal. This paper presents an analysis of correlations between various acoustic speech parameters and speaker’s height for a large number of speakers. It also presents a new method for an optimal estimation of speaker’s height and VTL from various acoustic speech parameters.
Vibration and Low Frequency Acoustic Analysis of Piecewise-Activated Adaptive Composite Panels

This paper presents an analytical modeling technique which uses the Ritz method, classical laminated plate theory, and finite panel acoustic radiation theory to pre dict the modal and structural acoustic behavior of locally activated shape memory alloy hybrid composite panels. This technique for performing a spatial integral within the Ritz approximation of the laminated plates with nonlinear material properties can also be ap plied to analysis of laminated plates with stiffeners and other spatially nonlinear character istics. The application of interest for this presentation is structural analysis of laminated plates. However, this technique may also be used for analyzing plates with ribs and stiffeners, etc. By minimizing the total energy functional, integrating piece-wise over dis crete homogeneous panel regions characterized as activated and unactivated and summing these integrals over the total panel area; stiffness matrices are found to determine natural frequencies, mode shapes and steady-state dynamic response to periodic incident plane wave acoustic excitation. This information is then used to determine the structural acoustic response as a function of frequency for a laminated plate with material nonlinearities. Analytical results are presented for balanced symmetric adaptive panels to demonstrate how various localized activation scenarios affect modal and structural acoustic behavior.
Intestinal function of gene-targeted mice lacking serum- and glucocorticoid-inducible kinase 1.

In vitro experiments have revealed the ability of serum- and glucocorticoid-inducible kinase 1 (SGK1) to stimulate intestinal Na(+)-coupled glucose cotransporter 1 (SGLT1) and intestinal Na(+)/H(+) exchanger 3 (NHE3). The present study explored the contribution of SGK1 to the regulation of intestinal transport in vivo. SGK1 transcript levels were determined by real-time PCR and glucose-induced currents (I(g)) reflecting SGLT1 activity by Ussing chamber experiments. BCECF fluorescence was utilized for the determination of Na(+)-dependent pH recovery from an ammonium pulse (DeltapH(NHE)) reflecting NHE activity. As a result, intestinal SGK1 transcript levels were significantly enhanced by a 4-day treatment with 10 microg.mg body wt(-1). day(-1) dexamethasone (Dex). I(g) was, under control conditions, virtually identical in sgk1 knockout mice (sgk1(-/-)) and their wild type littermates (sgk1(+/+)). A 4-day treatment with Dex, however, increased I(g) approximately threefold in sgk1(+/+) mice but not in sgk1(-/-) mice. DeltapH(NHE) was similar in sgk1(-/-) and sgk1(+/+) mice before treatment. Dex increased DeltapH(NHE) approximately threefold in sgk1(+/+) mice and approximately twofold in sgk1(-/-)mice, an effect significantly blunted in the presence of the specific NHE3 blocker S-3226 (10 microM). According to Western blot analysis, Dex significantly enhanced SGLT1 and NHE3 protein abundance in brush-border membranes of sgk1(+/+) mice but not of sgk1(-/-)mice. In conclusion, basic functions of SGLT1 and NHE3 in the intestine do not require stimulation by SGK1. However, the effects of glucocorticoids on SGLT1 are fully, and on NHE3 partially, dependent on SGK1.
Developing Component Scores from Natural Language Processing Human Ratings of Essay Quality

This study explores correlations between human ratings of essay quality and component scores based on similar natural language processing indices and weighted through a principal component analysis. The results demonstrate that such component scores show small to large effects with human ratings and thus may be suitable to providing both summative and formative feedback in an automatic writing evaluation systems such as those found in Writing-Pal.
Developing a High Efficient Process Integrating Protein Extraction with Cellulosic Ethanol Production from Caragana korshinskii Kom

Caragana Korshinskii Kom is a widely grown deciduous shrub in the region of inner magnolia. A full utilization of its useful components holds great potential for cellulosic ethanol production in an efficient and economic way. The remaining residues after protein extraction contain 29.02% cellulose and 19.61% hemicellulose, offers a potential feedstock for cellulosic ethanol production. Fermentable capability of hydrolysate derived from pretreated biomass is strongly dependent on pretreatment methods. In this work, three hydrolysis methods (alkaline hydrolysis, acid hydrolysis and acid-alkali hydrolysis) were compared by its digestibility. Alkali pretreatment could help greatly to cellulose degradation. The conversion percentage of cellulose and hemicellulose was increased to 1.43% and 13.01%, respectively. Without any nutrient addition, hydrolysate from alkaline pretreated biomass showed relative fermentable capability by Candida Tropicalis with a final ethanol concentration of 5.4 g/L. A mass balance of the whole process integrating protein extraction and cellulosic ethanol production indicated that 1000kg C. Korshinskii Kom leaves will produce 154 kg crude proteins, and the residues will produce 18 kg ethanol.
Online state of charge estimation for Lithium-ion batteries using Gaussian process regression

This paper presents an application of Gaussian process regression (GPR) to estimate a state of charge (SoC) of Lithium-ion (Li-ion) batteries with different kernel functions. One of the practical advantages of using GPR is that uncertainties in the estimates can be quantified, which enables reliability assessment of the SoC estimate. The inputs of GPR are voltage, current and temperature measurements of the battery and the output is an estimate of SoC. First, training is performed in which optimal hyperparameters of a kernel function are determined to model data properties. Then, the battery SoC is estimated online based on the trained model. The kernel function is the key element in the GPR model since it encodes the prior assumptions about the properties of the function being modeled. Therefore, the impact of kernel function selection on the estimation performance is analyzed using both simulated data and experimental data collected from a LiMn2O4/hard-carbon battery with a nominal capacity of 4.93Ah operating under constant charge and discharge currents.
Comparative Efficacy and Acceptability of Antidepressants in Parkinson's Disease: A Network Meta-Analysis

Background Depression is a common non-motor symptom in patients with Parkinson's disease (PD). There are many kinds of antidepressants being used, such as tricyclic antidepressants (TCAs), selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and Dopamine agonists which are suggested as alternative antidepressants for the treatment of depression in PD. Which one should we choose first? Literatures have shown inconsistent results. Methods We conducted a network meta-analysis of randomized controlled trials to compare the efficacy and acceptability of therapeutic methods for the treatment of depression in Parkinson's disease. Results We used the odds ratios (OR) as effect size firstly and the results indicated no statistical significance between each compared intervention. Then we used the logarithm of the individual odds ratios as effect size. With efficacy of TCAs as the standard of comparison, the degree of incoherence (a measure of how closely the entire network fits together) was small (ω = 4.824827e-05). The logor were: SSRIs −0.69 (95% CI −1.28– −0.10); Pramipexole −0.73 (−1.71– −0.26); Pergolide −1.97 (−3.67– 0.27); SNRIs −0.86 (−1.86– 0.15); Placebo −1.24 (−1.99– −0.50). With Placebo as the standard of comparison, the logor were: TCAs 1.24 (0.50– 1.99); SSRIs 0.55 (−0.03– 1.13); Pramipexole 0.51 (−0.12– 1.15); Pergolide −0.73 (−2.25– 0.80); SNRIs 0.38 (−0.42– 1.19); TCAs, pramipexole, pergolide and SNRIs showed better profile of acceptability, leading to significant fewer discontinuations than that of SSRIs. Conclusions There is insufficient evidence to support antidepressant efficacy for SSRIs, pramipexole, pergolide and SNRIs. TCAs might be the best choice when starting antidepressant treatment in patients of Parkinson's disease because it has the most favorable balance between benefits and acceptability, followed by pramipexole and SNRIs, SSRIs might be the last choice.
Spatio-Temporal Shape from Silhouette using Four-Dimensional Delaunay Meshing

We propose a novel method for computing a four-dimensional (4D) representation of the spatio-temporal visual hull of a dynamic scene, based on an extension of a recent provably correct Delaunay meshing algorithm. By considering time as an additional dimension, our approach exploits seamlessly the time coherence between different frames to produce a compact and high-quality 4D mesh representation of the visual hull. The 3D visual hull at a given time instant is easily obtained by intersecting this 4D mesh with a temporal plane, thus enabling interpolation of objects' shape between consecutive frames. In addition, our approach offers easy and extensive control over the size and quality of the output mesh as well as over its associated re- projection error. Our numerical experiments demonstrate the effectiveness and flexibility of our approach for generating compact, high-quality, time-coherent visual hull representations from real silhouette image data.
The Grid Economy

This work identifies challenges in managing resources in a Grid computing environment and proposes computational economy as a metaphor for effective management of resources and application scheduling. It identifies distributed resource management challenges and requirements of economy-based Grid systems, and discusses various representative economy-based systems, both historical and emerging, for cooperative and competitive trading of resources such as CPU cycles, storage, and network bandwidth. It presents an extensive, service-oriented Grid architecture driven by Grid economy and an approach for its realization by leveraging various existing Grid technologies. It also presents commodity and auction models for resource allocation. The use of commodity economy model for resource management and application scheduling in both computational and data grids is also presented.
PSO-optimized Instant Overbooking Framework for cognitive radio networks

Nowadays, the emerging wireless communication technologies cause rapid growth in radio spectrum usage. However, the radio spectrum is a limited resource and has almost been fully assigned by the current network operators (NOs). Although numerous studies have been accomplished on the spectrum management, there are rare evolutionary techniques dealing with booking spectrum on cognitive radio. Instant Overbooking Framework for Cognitive Radio networks (IOFCR) is used to maximize both spectrum utilization and the revenue of NOs under several over-booking and pricing policies. In such a network, when a primary user (PU) activity is sensed, the control of which requesting secondary users (SUs) can be denied and which Active SUs can be ejected is managed by IOFCR. In this paper, the Particle Swarm Optimization (PSO) algorithm is applied into the IOFCR to find optimal values of the over-booking price and the Compensation Cost (CC) ratio to optimize revenue and achieve high performance.
A study on the key technology of Tibetan social network analysis under Web environment

Social network analysis has adopted sociology, computer science, graph theory, topology, complex network and other subjects as its research methods and applied in macro analysis of practical social problems. This paper adopts social network analysis method through establishing unified model of Tibetan Web data, applied Tibetan entity identification, searching algorithm and extracting the semantic relations of the entity of Tibetan Web networks to analyze the overall information of Tibetan Web, in order to provide a platform for data analysis and public opinion situation forecast for national security.
Mechanical behaviour of brain tissue

Introduction The head is often considered as the most critical region of the human body for life-threatening injuries sustained in accidents. During a crash the head is exposed to external mechanical load which causes an internal mechanical response of the brain tissue. To study the effect of damage during the impact numerical models are developed. One of the most important parts of the input of these numerical models is the mechanical behavior of brain tissue.