The impact of a wave farm on large scale sediment transport

This study investigates the interactions of waves and tides at a wave farm in the southwest of England, in particular their effects on radiation stress, bottom stress, and consequently on the sediment transport and the coast adjacent to the wave-farm (the Wave Hub). In this study, an integrated complex numerical modelling system is setup at the Wave Hub site and is used to compute the wave and current fields by taking into account the wave-current interaction, as well as the sediment transport. Results show that tidal elevation and tidal currents have a significant effect on the wave height and direction predictions; tidal forcing and wind waves have a significant effect on the bed shear-stress, relevant to sediment transport; waves via radiation stresses have an important effect on the longshore and cross-shore velocity components, particularly during the spring tides. Waves can impact on bottom boundary layer and mixing in the water column. The results highlight the importance of the interactions between waves and tides when modelling coastal morphology with presence of wave energy devices

Efficient and reliable hierarchical error estimates for the discretization error of elliptic obstacle problems

We present and analyze novel hierarchical a posteriori error estimates for self-adjoint elliptic obstacle problems. Our approach differs from straightforward, but nonreliable estimators by an additional extra term accounting for the deviation of the discrete free boundary in the localization step. We prove efficiency and reliability on a saturation assumption and a regularity condition on the underlying grid. Heuristic arguments suggest that the extra term is of higher order and preserves full locality. Numerical computations confirm our theoretical findings

Understanding the Double-Level Influence of Guanxi on Construction Innovation in China: The Mediating Role of Interpersonal Knowledge Sharing and the Cross-Level Moderating Role of Inter-Organizational Relationships

Guanxi, a Chinese term that defines social networks of power and benefits, can be divided into inter-personal and inter-organizational relationships. Guanxi significantly influences construction innovation in China. Many studies have examined the relationship between guanxi and construction innovation at the project or organizational level. However, few of these studies explain how guanxi might affect an individual’s innovative behaviour from a double-level perspective. This paper builds on social capital theory and social exchange theory to examine guanxi’s role in motivating innovative behaviour in a China-specific construction context. It investigates the main effects of inter-personal relationships on innovative behaviour, the mediating effects of knowledge sharing, and the cross-level moderating effects of inter-organizational relationships. These elements were tested using a survey that received 178 responses from 35 different organizations. The results were analysed using Hierarchical Linear Modelling (HLM) and revealed that inter-personal relationships have positive influences on innovative behaviour, thus highlighting the partial mediating effects of knowledge sharing. In addition, the analyses showed that inter-organizational relationships augment inter-personal relationships and knowledge sharing on innovative behaviour by cross-level interaction. The research findings enhance an understanding of guanxi and innovative behaviour in China-specific construction project settings, as well as verifying the significance of guanxi in stimulating innovative behaviour

Hierarchical error estimates for the energy functional in obstacle problems

We present a hierarchical a posteriori error analysis for the minimum value of the energy functional in symmetric obstacle problems. The main result is that the error in the energy minimum is, up to oscillation terms, equivalent to an appropriate hierarchical estimator. The proof does not invoke any saturation assumption. We even show that small oscillation implies a related saturation assumption. In addition, we prove efficiency and reliability of an a posteriori estimate of the discretization error and thereby cast some light on the theoretical understanding of previous hierarchical estimators. Finally, we illustrate our theoretical results by numerical computations

Strong decays of N∗(1535)N^{*}(1535) in an extended chiral quark model

The strong decays of the $N^{*}(1535)$ resonance are investigated in an extended chiral quark model by including the low-lying $qqqq\bar{q}$ components in addition to the $qqq$ component. The results show that these five-quark components in $N^{*}(1535)$ contribute significantly to the $N^{*}(1535)\to N\pi$ and $N^{*}(1535)\to N\eta$ decays. The contributions to the $N\eta$ decay come from both the lowest energy and the next-to-lowest energy five-quarks components, while the contributions to the $N\pi$ decay come from only the latter one. Taking these contributions into account, the description for the strong decays of $N^{*}(1535)$ is improved, especially, for the puzzling large ratio of the decays to $N\eta$ and $N\pi$.Comment: 6 pages, 1 figur

IoTBeholder: A Privacy Snooping Attack on User Habitual Behaviors from Smart Home Wi-Fi Traffic

With the deployment of a growing number of smart home IoT devices, privacy leakage has become a growing concern. Prior work on privacy-invasive device localization, classification, and activity identification have proven the existence of various privacy leakage risks in smart home environments. However, they only demonstrate limited threats in real world due to many impractical assumptions, such as having privileged access to the user's home network. In this paper, we identify a new end-to-end attack surface using IoTBeholder, a system that performs device localization, classification, and user activity identification. IoTBeholder can be easily run and replicated on commercial off-the-shelf (COTS) devices such as mobile phones or personal computers, enabling attackers to infer user's habitual behaviors from smart home Wi-Fi traffic alone. We set up a testbed with 23 IoT devices for evaluation in the real world. The result shows that IoTBeholder has good device classification and device activity identification performance. In addition, IoTBeholder can infer the users' habitual behaviors and automation rules with high accuracy and interpretability. It can even accurately predict the users' future actions, highlighting a significant threat to user privacy that IoT vendors and users should highly concern

Composite Polarons in Ferromagnetic Narrow-band Metallic Manganese Oxides

A new mechanism is proposed to explain the colossal magnetoresistance and related phenomena. Moving electrons accompanied by Jahn-Teller phonon and spin-wave clouds may form composite polarons in ferromagnetic narrow-band manganites. The ground-state and finite-temperature properties of such composite polarons are studied in the present paper. By using a variational method, it is shown that the energy of the system at zero temperature decreases with the formation of composite polaron; the energy spectrum and effective mass of the composite polaron at finite temperature is found to be strongly renormalized by the temperature and the magnetic field. It is suggested that the composite polaron contribute significantly to the transport and the thermodynamic properties in ferromagnetic narrow-band metallic manganese oxides.Comment: Latex, no figur

Barriers to hospital and tuberculosis programme collaboration in China: context matters

Background: In many developing countries, programmes for ‘diseases of social importance’, such as tuberculosis (TB), have traditionally been organised as vertical services. In most of China, general hospitals are required to report and refer suspected TB cases to the TB programme for standardised diagnosis and treatment. General hospitals are the major contacts of health services for the TB patients. Despite the implementation of public–public/private mix, directly observed treatment, short-course, TB reporting and referral still remain a challenge. Objective: This study aims to identify barriers to the collaboration between the TB programme and general hospitals in China. Design: This is a qualitative study conducted in two purposefully selected counties in China: one in Zhejiang, a more affluent eastern province, and another in Guangxi, a poorer southwest province. Sixteen in-depth interviews were conducted and triangulated with document review and field notes. An open systems perspective, which views organisations as social systems, was adopted. Results: The most perceived problem appeared to be untimely reporting and referral associated with non-standardised prescriptions and hospitalisation by the general hospitals. These problems could be due to the financial incentives of the general hospitals, poor supervision from the TB programme to general hospitals, and lack of technical support from the TB programme to the general hospitals. However, contextual factors, such as different funding natures of different organisations, the prevalent medical and relationship cultures, and limited TB funding, could constrain the processes of collaboration between the TB programme and the general hospitals. Conclusions: The challenges in the TB programme and general hospital collaboration are rooted in the context. Improving collaboration should reduce the potential mistrust of the two organisations by aligning their interests, improving training, and improving supervision of TB control in the hospitals. In particular, effective regulatory mechanisms are crucial to alleviate the negative impact of the contextual factors and ensure smooth collaboration

DeviceRadar: Online IoT Device Fingerprinting in ISPs Using Programmable Switches

Device fingerprinting can be used by Internet Service Providers (ISPs) to identify vulnerable IoT devices for early prevention of threats. However, due to the wide deployment of middleboxes in ISP networks, some important data, e.g., 5-tuples and flow statistics, are often obscured, rendering many existing approaches invalid. It is further challenged by the high-speed traffic of hundreds of terabytes per day in ISP networks. This paper proposes DeviceRadar, an online IoT device fingerprinting framework that achieves accurate, real-time processing in ISPs using programmable switches. We innovatively exploit “key packets” as a basis of fingerprints only using packet sizes and directions, which appear periodically while exhibiting differences across different IoT devices. To utilize them, we propose a packet size embedding model to discover the spatial relationships between packets. Meanwhile, we design an algorithm to extract the “key packets” of each device, and propose an approach that jointly considers the spatial relationships and the key packets to produce a neighboring key packet distribution, which can serve as a feature vector for machine learning models for inference. Last, we design a model transformation method and a feature extraction process to deploy the model on a programmable data plane within its constrained arithmetic operations and memory to achieve line-speed processing. Our experiments show that DeviceRadar can achieve state-of-the-art accuracy across 77 IoT devices with 40 Gbps throughput, and requires only 1.3% of the processing time compared to GPU-accelerated approaches