MinK residues line a potassium channel pore.

MinK has neither the P region nor signature sequence that characterizes pore-forming subunits of all known K+ channels. A specific minK region has now been identified that affects external blockade by 2 common probes of K+ channel pores. When mutated to cysteine, residues in this region render minK susceptible to covalent blockade by methanethiosulfonate ethylsulfonate and alter reversible inhibition by tetraethylammonium. The 2 blockers are found to share overlapping binding site determinants and to interact. Since inhibition by external tetraethylammonium is sensitive to voltage and to the internal concentration of permeant ions, we argue that tetraethylammonium blocks by occluding the external end of a water-filled transmembrane pore. These findings support the view that minK is directly involved in forming a K+-selective ion conduction pathway

Increasing external effects negate local efforts to control ozone air pollution: a case study of Hong Kong and implications for other Chinese cities.

It is challenging to reduce ground-level ozone (O3) pollution at a given locale, due in part to the contributions of both local and distant sources. We present direct evidence that the increasing regional effects have negated local control efforts for O3 pollution in Hong Kong over the past decade, by analyzing the daily maximum 8 h average O3 and Ox (=O3+NO2) concentrations observed during the high O3 season (September-November) at Air Quality Monitoring Stations. The locally produced Ox showed a statistically significant decreasing trend over 2002-2013 in Hong Kong. Analysis by an observation-based model confirms this decline in in situ Ox production, which is attributable to a reduction in aromatic hydrocarbons. However, the regional background Ox transported into Hong Kong has increased more significantly during the same period, reflecting contributions from southern/eastern China. The combined result is a rise in O3 and a nondecrease in Ox. This study highlights the urgent need for close cross-boundary cooperation to mitigate the O3 problem in Hong Kong. China's air pollution control policy applies primarily to its large cities, with little attention to developing areas elsewhere. The experience of Hong Kong suggests that this control policy does not effectively address secondary pollution, and that a coordinated multiregional program is required

Online placement of multi-component applications in edge computing environments

Mobile edge computing is a new cloud computing paradigm which makes use of small-sized edge-clouds to provide real-time services to users. These mobile edge-clouds (MECs) are located in close proximity to users, thus enabling users to seamlessly access applications running on MECs. Due to the coexistence of the core (centralized) cloud, users, and one or multiple layers of MECs, an important problem is to decide where (on which computational entity) to place different components of an application. This problem, known as the application or workload placement problem, is notoriously hard, and therefore, heuristic algorithms without performance guarantees are generally employed in common practice, which may unknowingly suffer from poor performance as compared to the optimal solution. In this paper, we address the application placement problem and focus on developing algorithms with provable performance bounds. We model the user application as an application graph and the physical computing system as a physical graph, with resource demands/availabilities annotated on these graphs. We first consider the placement of a linear application graph and propose an algorithm for finding its optimal solution. Using this result, we then generalize the formulation and obtain online approximation algorithms with polynomial-logarithmic (poly-log) competitive ratio for tree application graph placement.We jointly consider node and link assignment, and incorporate multiple types of computational resources at nodes

Message from general co-chairs and program co-chairs

published_or_final_versionThe 4th International Joint Conference on Computational Sciences and Optimization (CSO 2011) Kunming and Lijiang, Yunnan Province, China, April 15-19, 2011. In Proceedings of the Computational Sciences and Optimization, 2011, p. 28-30

On wireless power transfer in two-tier massive MIMO hetnets: Energy and rate analysis

In this paper, we investigate the potential application of wireless power transfer (WPT) in heterogeneous networks (HetNets) with massive multiple-input multiple-output (MIMO) antennas. Users first harvest energy from the downlink WPT, and then use the harvested energy for uplink transmission. We adopt the downlink received signal power (DRSP) based user association to maximize the harvested energy, and address the impact of massive MIMO on the user association. By using new statistical properties, we then obtain the exact expressions for the average harvested energy and the average uplink achievable rate of a user in such networks. Numerical results corroborate our analysis and demonstrate that compared to deploying more small cells, the use of a large number of antennas is more appealing since it brings in significant increase in the harvested energy of the HetNets. In addition, results illustrate that serving more users in the massive MIMO aided macrocells decreases the harvested energy and the uplink achievable rate of the HetNets

Interference mitigation scheme by antenna selection in device-to-device communication underlaying cellular networks

In this paper, we investigate an interference mitigation scheme by antenna selection in device-to- device (D2D) communication underlaying downlink cellular networks. We first present the closed-form expression of the system achievable rate and its asymptotic behaviors at high signal-to-noise ratio (SNR) and the large antenna number scenarios. It is shown that the high SNR approximation increases with more antennas and higher ratio between the transmit SNR at the BS and the D2D transmitter. In addition, a tight approximation is derived for the rate and we reveal two thresholds for both the distance of the D2D link and the transmit SNR at the BS above which the underlaid D2D communication will degrade the system rate. We then particularize on the small cell setting where all users are closely located. In the small cell scenario, we show that the relationship between the distance of the D2D transmitting link and that of the D2D interfering link to the cellular user determines whether the D2D communication can enhance the system achievable rate. Numerical results are provided to verify these results

Channel Prediction Using Ordinary Differential Equations for MIMO systems

Channel state information (CSI) estimation is part of the most fundamental problems in 5G wireless communication systems. In mobile scenarios, outdated CSI will have a serious negative impact on various adaptive transmission systems, resulting in system performance degradation. To obtain accurate CSI, it is crucial to predict CSI at future moments. In this paper, we propose an efficient channel prediction method in multiple-input multiple-output (MIMO) systems, which combines genetic programming (GP) with higher-order differential equation (HODE) modeling for prediction, named GPODE. In the first place, the variation of one-dimensional data is depicted by using higher-order differential, and the higher-order differential data is modeled by GP to obtain an explicit model. Then, a definite order condition is given for the modeling of HODE, and an effective prediction interval is given. In order to accommodate to the rapidly changing channel, the proposed method is improved by taking the rough prediction results of Autoregression (AR) model as a priori, i.e., Im-GPODE channel prediction method. Given the effective interval, an online framework is proposed for the prediction. To verify the validity of the proposed methods, We use the data generated by the Cluster Delay Line (CDL) channel model for validation. The results show that the proposed methods has higher accuracy than other traditional prediction methods