Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models

To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recordings of the experimental system. We introduce a Bayesian hierarchical model on top of hidden Markov models (HMMs) to analyze these data and use the statistical results to answer the biological questions. In addition to resolving the biological puzzles and delineating the regulating roles of different molecular complexes, our statistical results enable us to propose a more detailed mechanism for the late stages of the protein targeting process

Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models

To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recordings of the experimental system. We introduce a Bayesian hierarchical model on top of hidden Markov models (HMMs) to analyze these data and use the statistical results to answer the biological questions. In addition to resolving the biological puzzles and delineating the regulating roles of different molecular complexes, our statistical results enable us to propose a more detailed mechanism for the late stages of the protein targeting process

Discovery From Non-Parties (Third-Party Discovery) in International Arbitration

International arbitration rules and many arbitration laws usually provide procedures that permit tribunals to order parties to disclose documents and other materials to the other parties.1 More complex are the rules that determine opportunities to obtain discovery from persons that are not party to the arbitration (third-party discovery). This article will review third-party discovery under the Federal Arbitration Act (FAA) and the provisions of the US Code s.1782 that authorise US courts to act in aid of actions before foreign tribunals. Section 1782 has unique interest at this time because it figured prominently in the EU antitrust investigation of Intel that was initiated on request from Advanced Micro Devices (AMD). Early in that investigation, AMD filed a s.1782 request in the US District Court to obtain evidence from US sources for submission to the DG-Competition of the European Commission (EC). This request ultimately led to the Supreme Court’s decision in Intel Corp v Advanced Micro Devices Inc2 which appeared to significantly expand the scope of s.1782. Ironically, after AMD won on key legal issues in the Supreme Court, the District Court on remand exercised its discretion and denied the request for judicial assistance. This paper first describes the FAA non-party discovery rules and the split among the federal appellate courts concerning the authority of arbitrators to order prehearing discovery from non-parties. Next, it provides an analysis of the meaning of the terms “interested party” and “tribunal”—terms that were controversially interpreted by the Supreme Court in Intel and are essential to the application of s.1782. Finally, it discusses the “discretionary” factors used by the federal courts in deciding whether to grant a s.1782 request even when the statutory criteria are met. The opportunity to exercise this discretion seems to rebut the argument that the Supreme Court’s interpretation of s.1782 gives participants before foreign tribunals more discovery rights in the United States than are available to the parties in arbitrations covered by the FAA

Azimuth sidelobes suppression using multi-azimuth angle synthetic aperture radar images

A novel method is proposed for azimuth sidelobes suppression using multi-pass squinted (MPS) synthetic aperture radar (SAR) data. For MPS SAR, the radar observes the scene with different squint angles and heights on each pass. The MPS SAR mode acquisition geometry is given first. Then, 2D signals are focused and the images are registered to the master image. Based on the new signal model, elevation processing and incoherent addition are introduced in detail, which are the main parts for azimuth sidelobes suppression. Moreover, parameter design criteria in incoherent addition are derived for the best performance. With the proposed parameter optimization step, the new method has a prominent azimuth sidelobes suppression effect with a slightly better azimuth resolution, as verified by experimental results on both simulated point targets and TerraSAR-X data

Probing onset of strong localization and electron-electron interactions with the presence of direct insulator-quantum Hall transition

We have performed low-temperature transport measurements on a disordered two-dimensional electron system (2DES). Features of the strong localization leading to the quantum Hall effect are observed after the 2DES undergoes a direct insulator-quantum Hall transition with increasing the perpendicular magnetic field. However, such a transition does not correspond to the onset of strong localization. The temperature dependences of the Hall resistivity and Hall conductivity reveal the importance of the electron-electron interaction effects to the observed transition in our study.Comment: 9 pages, 4 figure

Constructing a precipitable water vapor map from regional GNSS network observations without collocated meteorological data for weather forecasting

Surface pressure (Ps) and weighted mean temperature (Tm) are two necessary variables for the accurate retrieval of precipitable water vapor (PWV) from Global Navigation Satellite System (GNSS) zenith total delay (ZTD) estimates. The lack of Ps or Tm information is a concern for those GNSS sites that are not collocated with meteorological sensors. This paper investigates an alternative method of inferring accurate Ps and Tm at the GNSS station using nearby synoptic observations. Ps and Tm obtained at the nearby synoptic sites are interpolated onto the location of the GNSS station by performing both vertical and horizontal adjustments, in which the parameters involved in Ps and Tm calculation are estimated from ERA-Interim reanalysis profiles. In addition, we present a method of constructing high-quality PWV maps through vertical reduction and horizontal interpolation of the retrieved GNSS PWVs. To evaluate the performances of the Ps and Tm retrieval, and the PWV map construction, GNSS data collected from 58 stations of the Hunan GNSS network and synoptic observations from 20 nearby sites in 2015 were processed to extract the PWV so as to subsequently generate the PWV maps. The retrieved Ps and Tm and constructed PWV maps were assessed by the results derived from radiosonde and the ERA-Interim reanalysis. The results show that (1) accuracies of Ps and Tm derived by synoptic interpolation are within the range of 1.7–3.0&thinsp;hPa and 2.5–3.0&thinsp;K, respectively, which are much better than the GPT2w model; (2) the constructed PWV maps have good agreements with radiosonde and ERA-Interim reanalysis data with the overall accuracy being better than 3&thinsp;mm; and (3) PWV maps can well reveal the moisture advection, transportation and convergence during heavy rainfall.</p

New Insights into Traffic Dynamics: A Weighted Probabilistic Cellular Automaton Model

From the macroscopic viewpoint for describing the acceleration behavior of drivers, this letter presents a weighted probabilistic cellular automaton model (the WP model, for short) by introducing a kind of random acceleration probabilistic distribution function. The fundamental diagrams, the spatio-temporal pattern are analyzed in detail. It is shown that the presented model leads to the results consistent with the empirical data rather well, nonlinear velocity-density relationship exists in lower density region, and a new kind of traffic phenomenon called neo-synchronized flow is resulted. Furthermore, we give the criterion for distinguishing the high-speed and low-speed neo-synchronized flows and clarify the mechanism of this kind of traffic phenomena. In addition, the result that the time evolution of distribution of headways is displayed as a normal distribution further validates the reasonability of the neo-synchronized flow. These findings suggest that the diversity and randomicity of drivers and vehicles has indeed remarkable effect on traffic dynamics.Comment: 12 pages, 5 figures, submitted to Europhysics Letter

Observation of neutral sulfuric acid-amine containing clusters in laboratory and ambient measurements

Recent ab initio calculations showed that amines can enhance atmospheric sulfuric acid-water nucleation more effectively than ammonia, and this prediction has been substantiated in laboratory measurements. Laboratory studies have also shown that amines can effectively displace ammonia in several types of ammonium clusters. However, the roles of amines in cluster formation and growth at a microscopic molecular scale (from molecular sizes up to 2 nm) have not yet been well understood. Processes that must be understood include the incorporation of amines into sulfuric acid clusters and the formation of organic salts in freshly nucleated particles, which contributes significantly to particle growth rates. We report the first laboratory and ambient measurements of neutral sulfuric acid-amine clusters using the Cluster CIMS, a recently-developed mass spectrometer designed for measuring neutral clusters formed in the atmosphere during nucleation. An experimental technique, which we refer to as Semi-Ambient Signal Amplification (SASA), was employed. Sulfuric acid was added to ambient air, and the concentrations and composition of clusters in this mixture were analyzed by the Cluster CIMS. This experimental approach led to significantly higher cluster concentrations than are normally found in ambient air, thereby increasing signal-to-noise levels and allowing us to study reactions between gas phase species in ambient air and sulfuric acid containing clusters. Mass peaks corresponding to clusters containing four H&lt;sub&gt;2&lt;/sub&gt;SO&lt;sub&gt;4&lt;/sub&gt; molecules and one amine molecule were clearly observed, with the most abundant sulfuric acid-amine clusters being those containing a C2- or C4-amine (i.e. amines with masses of 45 and 73 amu). Evidence for C3- and C5-amines (i.e. amines with masses of 59 and 87 amu) was also found, but their correlation with sulfuric acid tetramer was not as strong as was observed for the C2- and C4-amines. The formation mechanisms for those sulfuric acid-amine clusters were investigated by varying the residence time in the inlet. It was concluded that the amines react directly with neutral clusters and that ion-induced clustering of sulfuric acid cluster ions with amines was not a dominant process. Results from ambient measurements using the Cluster CIMS without addition of sulfuric acid have shown that the sulfuric acid-amine clusters were reasonably well correlated with sulfuric acid tetramer and consistent with the SASA experiments at the same Boulder sampling site. Also, clusters that contain C2- or C4-amines were more abundant and better correlated with sulfuric acid tetramer than other types of amine containing clusters. However, ambient measurements of sulfuric acid-amine clusters remain difficult and highly uncertain because their concentrations are only slightly above background levels, even during nucleation events