Serial perturbation of MinK in IKs implies an alpha-helical transmembrane span traversing the channel corpus.

I(Ks) channels contain four pore-forming KCNQ1 subunits and two accessory MinK subunits. MinK influences surface expression, voltage-dependence of gating, conduction, and pharmacology to yield the attributes characteristic of native channels in heart. The structure and location of the MinK transmembrane domain (TMD) remains a matter of scrutiny. As perturbation of gating analysis has correctly inferred the peripheral location and alpha-helical nature of TMDs in pore-forming subunits, the method is applied here to human MinK. Tryptophan and Asparagine substitution at 23 consecutive sites yields perturbation with alpha-helical periodicity (residues 44-56) followed by an alternating impact pattern (residues 56-63). Arginine substitution across the span suggests that as few as eight sites are occluded from aqueous solution (residues 50-57). We favor a TMD model that is alpha-helical with the external portion of the span at a lipid-protein boundary and the inner portion within the channel corpus in complex interactions

Test of conformal gravity with astrophysical observations

Since it can describe the rotation curves of galaxies without dark matter and can give rise to accelerated expansion, conformal gravity attracts much attention recently. As a theory of modified gravity, it is important to test conformal gravity with astrophysical observations. Here we constrain conformal gravity with SNIa and Hubble parameter data and investigate whether it suffers from an age problem with the age of APM~08279+5255. We find conformal gravity can accommodate the age of APM~08279+5255 at 3 $\sigma$ deviation, unlike most of dark energy models which suffer from an age problem.Comment: 6 pages, 2 figure

CrossData: Leveraging Text-Data Connections for Authoring Data Documents

Data documents play a central role in recording, presenting, and disseminating data. Despite the proliferation of applications and systems designed to support the analysis, visualization, and communication of data, writing data documents remains a laborious process, requiring a constant back-and-forth between data processing and writing tools. Interviews with eight professionals revealed that their workflows contained numerous tedious, repetitive, and error-prone operations. The key issue that we identified is the lack of persistent connection between text and data. Thus, we developed CrossData, a prototype that treats text-data connections as persistent, interactive, first-class objects. By automatically identifying, establishing, and leveraging text-data connections, CrossData enables rich interactions to assist in the authoring of data documents. An expert evaluation with eight users demonstrated the usefulness of CrossData, showing that it not only reduced the manual effort in writing data documents but also opened new possibilities to bridge the gap between data exploration and writing

Charybdotoxin binding in the I(Ks) pore demonstrates two MinK subunits in each channel complex.

I(Ks) voltage-gated K(+) channels contain four pore-forming KCNQ1 subunits and MinK accessory subunits in a number that has been controversial. Here, I(Ks) channels assembled naturally by monomer subunits are compared to those with linked subunits that force defined stoichiometries. Two strategies that exploit charybdotoxin (CTX)-sensitive subunit variants are applied. First, CTX on rate, off rate, and equilibrium affinity are found to be the same for channels of monomers and those with a fixed 2:4 MinK:KCNQ1 valence. Second, 3H-CTX and an antibody are used to directly quantify channels and MinK subunits, respectively, showing 1.97 +/- 0.07 MinK per I(Ks) channel. Additional MinK subunits do not enter channels of monomeric subunits or those with fixed 2:4 valence. We conclude that two MinK subunits are necessary, sufficient, and the norm in I(Ks) channels. This stoichiometry is expected for other K(+) channels that contain MinK or MinK-related peptides (MiRPs)

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Sliding Mode Variable Structure Control and Real-Time Optimization of Dry Dual Clutch Transmission during the Vehicle’s Launch

In order to reflect driving intention adequately and improve the launch performance of vehicle equipped with five-speed dry dual clutch transmission (DCT), the issue of coordinating control between engine and clutch is researched, which is based on the DCT and prototype car developed independently. Four-degree-of-freedom (DOF) launch dynamics equations are established. Taking advantage of predictive control and genetic algorithm, target tracing curves of engine speed and vehicle velocity are optimally specified. Sliding mode variable structure (SMVS) control strategy is designed to track these curves. The rapid prototyping experiment and test are, respectively, conducted on the DCT test bench and in the chassis dynamometer. Results show that the designed SMVS control strategy not only effectively embodies the driver’s intention but also has strong robustness to the vehicle parameter’s variations

Fuzzy Determination of Target Shifting Time and Torque Control of Shifting Phase for Dry Dual Clutch Transmission

Based on the independently developed five-speed dry dual clutch transmission (DDCT), the paper proposes the torque coordinating control strategy between engine and two clutches, which obtains engine speed and clutch transferred torque in the shifting process, adequately reflecting the driver intention and improving the shifting quality. Five-degree-of-freedom (DOF) shifting dynamics model of DDCT with single intermediate shaft is firstly established according to its physical characteristics. Then the quantitative control objectives of the shifting process are presented. The fuzzy decision of shifting time and the model-based torque coordinating control strategy are proposed and also verified by simulating under different driving intentions in up-/downshifting processes with the DCT model established on the MATLAB/Simulink. Simulation results validate that the shifting control algorithm proposed in this paper can not only meet the shifting quality requirements, but also adapt to the various shifting intentions, having a strong robustness