Showing papers by "Hong Kong University of Science and Technology published in 2016"

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

Recent Advances in Electrocatalysts for Oxygen Reduction Reaction

Abstract: The recent advances in electrocatalysis for oxygen reduction reaction (ORR) for proton exchange membrane fuel cells (PEMFCs) are thoroughly reviewed. This comprehensive Review focuses on the low- and non-platinum electrocatalysts including advanced platinum alloys, core–shell structures, palladium-based catalysts, metal oxides and chalcogenides, carbon-based non-noble metal catalysts, and metal-free catalysts. The recent development of ORR electrocatalysts with novel structures and compositions is highlighted. The understandings of the correlation between the activity and the shape, size, composition, and synthesis method are summarized. For the carbon-based materials, their performance and stability in fuel cells and comparisons with those of platinum are documented. The research directions as well as perspectives on the further development of more active and less expensive electrocatalysts are provided.

Efficient organic solar cells processed from hydrocarbon solvents

Abstract: Organic solar cells have desirable properties, including low cost of materials, high-throughput roll-to-roll production, mechanical flexibility and light weight. However, all top-performance devices are at present processed using halogenated solvents, which are environmentally hazardous and would thus require expensive mitigation to contain the hazards. Attempts to process organic solar cells from non-halogenated solvents lead to inferior performance. Overcoming this hurdle, here we present a hydrocarbon-based processing system that is not only more environmentally friendly but also yields cells with power conversion efficiencies of up to 11.7%. Our processing system incorporates the synergistic effects of a hydrocarbon solvent, a novel additive, a suitable choice of polymer side chain, and strong temperature-dependent aggregation of the donor polymer. Our results not only demonstrate a method of producing active layers of organic solar cells in an environmentally friendly way, but also provide important scientific insights that will facilitate further improvement of the morphology and performance of organic solar cells. The processing of high-performance organic solar cells usually requires environmentally hazardous solvents. Now, hydrocarbon-based processing is shown to achieve relatively high performance in a more environmentally friendly way.

Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices

Abstract: Mobile-edge computing (MEC) is an emerging paradigm to meet the ever-increasing computation demands from mobile applications. By offloading the computationally intensive workloads to the MEC server, the quality of computation experience, e.g., the execution latency, could be greatly improved. Nevertheless, as the on-device battery capacities are limited, computation would be interrupted when the battery energy runs out. To provide satisfactory computation performance as well as achieving green computing, it is of significant importance to seek renewable energy sources to power mobile devices via energy harvesting (EH) technologies. In this paper, we will investigate a green MEC system with EH devices and develop an effective computation offloading strategy. The execution cost , which addresses both the execution latency and task failure, is adopted as the performance metric. A low-complexity online algorithm is proposed, namely, the Lyapunov optimization-based dynamic computation offloading algorithm, which jointly decides the offloading decision, the CPU-cycle frequencies for mobile execution, and the transmit power for computation offloading. A unique advantage of this algorithm is that the decisions depend only on the current system state without requiring distribution information of the computation task request, wireless channel, and EH processes. The implementation of the algorithm only requires to solve a deterministic problem in each time slot, for which the optimal solution can be obtained either in closed form or by bisection search. Moreover, the proposed algorithm is shown to be asymptotically optimal via rigorous analysis. Sample simulation results shall be presented to corroborate the theoretical analysis as well as validate the effectiveness of the proposed algorithm.

Fast charge separation in a non-fullerene organic solar cell with a small driving force

Abstract: Fast and efficient charge separation is essential to achieve high power conversion efficiency in organic solar cells (OSCs). In state-of-the-art OSCs, this is usually achieved by a significant driv ...

Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems

Abstract: Millimeter wave (mmWave) communications has been regarded as a key enabling technology for 5G networks, as it offers orders of magnitude greater spectrum than current cellular bands. In contrast to conventional multiple-input–multiple-output (MIMO) systems, precoding in mmWave MIMO cannot be performed entirely at baseband using digital precoders, as only a limited number of signal mixers and analog-to-digital converters can be supported considering their cost and power consumption. As a cost-effective alternative, a hybrid precoding transceiver architecture, combining a digital precoder and an analog precoder, has recently received considerable attention. However, the optimal design of such hybrid precoders has not been fully understood. In this paper, treating the hybrid precoder design as a matrix factorization problem, effective alternating minimization (AltMin) algorithms will be proposed for two different hybrid precoding structures, i.e., the fully-connected and partially-connected structures. In particular, for the fully-connected structure, an AltMin algorithm based on manifold optimization is proposed to approach the performance of the fully digital precoder, which, however, has a high complexity. Thus, a low-complexity AltMin algorithm is then proposed, by enforcing an orthogonal constraint on the digital precoder. Furthermore, for the partially-connected structure, an AltMin algorithm is also developed with the help of semidefinite relaxation. For practical implementation, the proposed AltMin algorithms are further extended to the broadband setting with orthogonal frequency division multiplexing modulation. Simulation results will demonstrate significant performance gains of the proposed AltMin algorithms over existing hybrid precoding algorithms. Moreover, based on the proposed algorithms, simulation comparisons between the two hybrid precoding structures will provide valuable design insights.

Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons

Abstract: The growing commercial interest in indoor location-based services (ILBS) has spurred recent development of many indoor positioning techniques. Due to the absence of global positioning system (GPS) signal, many other signals have been proposed for indoor usage. Among them, Wi-Fi (802.11) emerges as a promising one due to the pervasive deployment of wireless LANs (WLANs). In particular, Wi-Fi fingerprinting has been attracting much attention recently because it does not require line-of-sight measurement of access points (APs) and achieves high applicability in complex indoor environment. This survey overviews recent advances on two major areas of Wi-Fi fingerprint localization: advanced localization techniques and efficient system deployment. Regarding advanced techniques to localize users, we present how to make use of temporal or spatial signal patterns, user collaboration, and motion sensors. Regarding efficient system deployment, we discuss recent advances on reducing offline labor-intensive survey, adapting to fingerprint changes, calibrating heterogeneous devices for signal collection, and achieving energy efficiency for smartphones. We study and compare the approaches through our deployment experiences, and discuss some future directions.

Acoustic metamaterials: From local resonances to broad horizons.

Abstract: Within a time span of 15 years, acoustic metamaterials have emerged from academic curiosity to become an active field driven by scientific discoveries and diverse application potentials. This review traces the development of acoustic metamaterials from the initial findings of mass density and bulk modulus frequency dispersions in locally resonant structures to the diverse functionalities afforded by the perspective of negative constitutive parameter values, and their implications for acoustic wave behaviors. We survey the more recent developments, which include compact phase manipulation structures, superabsorption, and actively controllable metamaterials as well as the new directions on acoustic wave transport in moving fluid, elastic, and mechanical metamaterials, graphene-inspired metamaterials, and structures whose characteristics are best delineated by non-Hermitian Hamiltonians. Many of the novel acoustic metamaterial structures have transcended the original definition of metamaterials as arising from the collective manifestations of constituent resonating units, but they continue to extend wave manipulation functionalities beyond those found in nature.

Ising pairing in superconducting NbSe2 atomic layers

Abstract: The superconducting properties of NbSe2 as it approaches the monolayer limit are investigated by means of magnetotransport measurements, uncovering evidence of spin–momentum locking.

The Visual Object Tracking VOT2016 Challenge Results

Abstract: The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).

Implant-derived magnesium induces local neuronal production of CGRP to improve bone-fracture healing in rats

Abstract: Orthopedic implants containing biodegradable magnesium have been used for fracture repair with considerable efficacy; however, the underlying mechanisms by which these implants improve fracture healing remain elusive. Here we show the formation of abundant new bone at peripheral cortical sites after intramedullary implantation of a pin containing ultrapure magnesium into the intact distal femur in rats. This response was accompanied by substantial increases of neuronal calcitonin gene-related polypeptide-α (CGRP) in both the peripheral cortex of the femur and the ipsilateral dorsal root ganglia (DRG). Surgical removal of the periosteum, capsaicin denervation of sensory nerves or knockdown in vivo of the CGRP-receptor-encoding genes Calcrl or Ramp1 substantially reversed the magnesium-induced osteogenesis that we observed in this model. Overexpression of these genes, however, enhanced magnesium-induced osteogenesis. We further found that an elevation of extracellular magnesium induces magnesium transporter 1 (MAGT1)-dependent and transient receptor potential cation channel, subfamily M, member 7 (TRPM7)-dependent magnesium entry, as well as an increase in intracellular adenosine triphosphate (ATP) and the accumulation of terminal synaptic vesicles in isolated rat DRG neurons. In isolated rat periosteum-derived stem cells, CGRP induces CALCRL- and RAMP1-dependent activation of cAMP-responsive element binding protein 1 (CREB1) and SP7 (also known as osterix), and thus enhances osteogenic differentiation of these stem cells. Furthermore, we have developed an innovative, magnesium-containing intramedullary nail that facilitates femur fracture repair in rats with ovariectomy-induced osteoporosis. Taken together, these findings reveal a previously undefined role of magnesium in promoting CGRP-mediated osteogenic differentiation, which suggests the therapeutic potential of this ion in orthopedics.

Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead

Abstract: The unified theory of acceptance and use of technology (UTAUT) is a little over a decade old and has been used extensively in information systems (IS) and other fields, as the large number of citations to the original paper that introduced the theory evidences. In this paper, we review and synthesize the IS literature on UTAUT from September 2003 until December 2014, perform a theoretical analysis of UTAUT and its extensions, and chart an agenda for research going forward. Based on Weber’s (2012) framework of theory evaluation, we examined UTAUT and its extensions along two sets of quality dimensions; namely, the parts of a theory and the theory as a whole. While our review identifies many merits to UTAUT, we also found that the progress related to this theory has hampered further theoretical development in research into technology acceptance and use. To chart an agenda for research that will enable significant future work, we analyze the theoretical contributions of UTAUT using Whetten’s (2009) notion of cross-context theorizing. Our analysis reveals several limitations that lead us to propose a multi-level framework that can serve as the theoretical foundation for future research. Specifically, this framework integrates the notion of research context and cross-context theorizing with the theory evaluation framework to: (1) synthesize the existing UTAUT extensions across both the dimensions and the levels of the research context and (2) highlight promising research directions. We conclude with recommendations for future UTAUT-related research using the proposed framework.

Delay-optimal computation task scheduling for mobile-edge computing systems

Abstract: Mobile-edge computing (MEC) emerges as a promising paradigm to improve the quality of computation experience for mobile devices. Nevertheless, the design of computation task scheduling policies for MEC systems inevitably encounters a challenging two-timescale stochastic optimization problem. Specifically, in the larger timescale, whether to execute a task locally at the mobile device or to offload a task to the MEC server for cloud computing should be decided, while in the smaller timescale, the transmission policy for the task input data should adapt to the channel side information. In this paper, we adopt a Markov decision process approach to handle this problem, where the computation tasks are scheduled based on the queueing state of the task buffer, the execution state of the local processing unit, as well as the state of the transmission unit. By analyzing the average delay of each task and the average power consumption at the mobile device, we formulate a power-constrained delay minimization problem, and propose an efficient one-dimensional search algorithm to find the optimal task scheduling policy. Simulation results are provided to demonstrate the capability of the proposed optimal stochastic task scheduling policy in achieving a shorter average execution delay compared to the baseline policies.

Optimal DoS Attack Scheduling in Wireless Networked Control System

Abstract: Recently, many literature works have considered the security issues of wireless networked control system (WNCS). However, few works studied how the attacker should optimize its attack schedule in order to maximize the effect on the system performance due to the insufficiency of energy at the attacker side. This paper fills this gap from the aspect of control system performance. We consider the optimal jamming attack that maximizes the Linear Quadratic Gaussian (LQG) control cost function under energy constraint. After analyzing the properties of the cost function under an arbitrary attack schedule, we derive the optimal jamming attack schedule and the corresponding cost function. System stability under this optimal attack schedule is also considered. We further investigate the optimal attack schedule in a WNCS with multiple subsystems. Different examples are provided to demonstrate the effectiveness of the proposed optimal denial-of-service attack schedule.

Reduced voltage losses yield 10% efficient fullerene free organic solar cells with >1 V open circuit voltages

Abstract: Optimization of the energy levels at the donor–acceptor interface of organic solar cells has driven their efficiencies to above 10%. However, further improvements towards efficiencies comparable with inorganic solar cells remain challenging because of high recombination losses, which empirically limit the open-circuit voltage (Voc) to typically less than 1 V. Here we show that this empirical limit can be overcome using non-fullerene acceptors blended with the low band gap polymer PffBT4T-2DT leading to efficiencies approaching 10% (9.95%). We achieve Voc up to 1.12 V, which corresponds to a loss of only Eg/q − Voc = 0.5 ± 0.01 V between the optical bandgap Eg of the polymer and Voc. This high Voc is shown to be associated with the achievement of remarkably low non-geminate and non-radiative recombination losses in these devices. Suppression of non-radiative recombination implies high external electroluminescence quantum efficiencies which are orders of magnitude higher than those of equivalent devices employing fullerene acceptors. Using the balance between reduced recombination losses and good photocurrent generation efficiencies achieved experimentally as a baseline for simulations of the efficiency potential of organic solar cells, we estimate that efficiencies of up to 20% are achievable if band gaps and fill factors are further optimized.

Pinhole-Free and Surface-Nanostructured NiOx Film by Room-Temperature Solution Process for High-Performance Flexible Perovskite Solar Cells with Good Stability and Reproducibility

Abstract: Recently, researchers have focused on the design of highly efficient flexible perovskite solar cells (PVSCs), which enables the implementation of portable and roll-to-roll fabrication in large scale. While NiOx is a promising material for hole transport layer (HTL) candidate for fabricating efficient PVSCs on a rigid substrate, the reported NiOx HTLs are formed using different multistep treatments (such as 300–500 °C annealing, O2-plasma, UVO, etc.), which hinders the development of flexible PVSCs based on NiOx. Meanwhile, the features of nanostructured morphology and flawless film quality are very important for the film to function as highly effective HTL of PVSCs. However, it is difficult to have the two features coexist natively, particularly in a solution process that flawless film will usually come with smooth morphology. Here, we demonstrate the flawless and surface-nanostructured NiOx film from a simple and controllable room-temperature solution process for achieving high performance flexible PVSCs...

Incentives for Mobile Crowd Sensing: A Survey

Abstract: Recent years have witnessed the fast proliferation of mobile devices (e.g., smartphones and wearable devices) in people's lives. In addition, these devices possess powerful computation and communication capabilities and are equipped with various built-in functional sensors. The large quantity and advanced functionalities of mobile devices have created a new interface between human beings and environments. Many mobile crowd sensing applications have thus been designed which recruit normal users to contribute their resources for sensing tasks. To guarantee good performance of such applications, it's essential to recruit sufficient participants. Thus, how to effectively and efficiently motivate normal users draws growing attention in the research community. This paper surveys diverse strategies that are proposed in the literature to provide incentives for stimulating users to participate in mobile crowd sensing applications. The incentives are divided into three categories: entertainment, service, and money. Entertainment means that sensing tasks are turned into playable games to attract participants. Incentives of service exchanging are inspired by the principle of mutual benefits. Monetary incentives give participants payments for their contributions. We describe literature works of each type comprehensively and summarize them in a compact form. Further challenges and promising future directions concerning incentive mechanism design are also discussed.

Muon reconstruction performance of the ATLAS detector in proton–proton collision data at √ s =13 TeV

Abstract: This article documents the performance of the ATLAS muon identification and reconstruction using the first LHC dataset recorded at s√ = 13 TeV in 2015. Using a large sample of J/ψ→μμ and Z→μμ decays from 3.2 fb−1 of pp collision data, measurements of the reconstruction efficiency, as well as of the momentum scale and resolution, are presented and compared to Monte Carlo simulations. The reconstruction efficiency is measured to be close to 99% over most of the covered phase space (|η| 2.2, the pT resolution for muons from Z→μμ decays is 2.9% while the precision of the momentum scale for low-pT muons from J/ψ→μμ decays is about 0.2%.

Enhanced Efficiency and Stability of Inverted Perovskite Solar Cells Using Highly Crystalline SnO2 Nanocrystals as the Robust Electron-Transporting Layer

Abstract: Highly crystalline SnO2 is demonstrated to serve as a stable and robust electron-transporting layer for high-performance perovskite solar cells. Benefiting from its high crystallinity, the relatively thick SnO2 electron-transporting layer (≈120 nm) provides a respectable electron-transporting property to yield a promising power conversion efficiency (PCE)(18.8%) Over 90% of the initial PCE can be retained after 30 d storage in ambient with ≈70% relative humidity.

Negative Magnetoresistance in Dirac Semimetal Cd3As2

Abstract: A large negative magnetoresistance (NMR) is anticipated in topological semimetals in parallel magnetic fields, demonstrating the chiral anomaly, a long-sought high-energy-physics effect, in solid-state systems. Recent experiments reveal that the Dirac semimetal Cd3As2 has the record-high mobility and positive linear magnetoresistance in perpendicular magnetic fields. However, the NMR has not yet been unveiled. Here we report the observation of NMR in Cd3As2 microribbons in parallel magnetic fields up to 66% at 50 K and visible at room temperatures. The NMR is sensitive to the angle between magnetic and electrical fields, robust against temperature and dependent on the carrier density. The large NMR results from low carrier densities in our Cd3As2 samples, ranging from 3.0 × 10(17) cm(-3) at 300 K to 2.2 × 10(16) cm(-3) below 50 K. We therefore attribute the observed NMR to the chiral anomaly. In perpendicular magnetic fields, a positive linear magnetoresistance up to 1,670% at 14 T and 2 K is also observed.

Deep API learning

Abstract: Developers often wonder how to implement a certain functionality (e.g., how to parse XML files) using APIs. Obtaining an API usage sequence based on an API-related natural language query is very helpful in this regard. Given a query, existing approaches utilize information retrieval models to search for matching API sequences. These approaches treat queries and APIs as bags-of-words and lack a deep understanding of the semantics of the query. We propose DeepAPI, a deep learning based approach to generate API usage sequences for a given natural language query. Instead of a bag-of-words assumption, it learns the sequence of words in a query and the sequence of associated APIs. DeepAPI adapts a neural language model named RNN Encoder-Decoder. It encodes a word sequence (user query) into a fixed-length context vector, and generates an API sequence based on the context vector. We also augment the RNN Encoder-Decoder by considering the importance of individual APIs. We empirically evaluate our approach with more than 7 million annotated code snippets collected from GitHub. The results show that our approach generates largely accurate API sequences and outperforms the related approaches.

Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis

Abstract: Prokaryotic 16S ribosomal RNA (rRNA) sequences are widely used in environmental microbiology and molecular evolution as reliable markers for the taxonomic classification and phylogenetic analysis of microbes. Restricted by current sequencing techniques, the massive sequencing of 16S rRNA gene amplicons encompassing the full length of genes is not yet feasible. Thus, the selection of the most efficient hypervariable regions for phylogenetic analysis and taxonomic classification is still debated. In the present study, several bioinformatics tools were integrated to build an in silico pipeline to evaluate the phylogenetic sensitivity of the hypervariable regions compared with the corresponding full-length sequences. The correlation of seven sub-regions was inferred from the geodesic distance, a parameter that is applied to quantitatively compare the topology of different phylogenetic trees constructed using the sequences from different sub-regions. The relationship between different sub-regions based on the geodesic distance indicated that V4-V6 were the most reliable regions for representing the full-length 16S rRNA sequences in the phylogenetic analysis of most bacterial phyla, while V2 and V8 were the least reliable regions. Our results suggest that V4-V6 might be optimal sub-regions for the design of universal primers with superior phylogenetic resolution for bacterial phyla. A potential relationship between function and the evolution of 16S rRNA is also discussed.