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Fluctuation of pump power is one of the major sources of temporal and intensity noise in femtosecond fiber lasers. In this work, the transfer functions between the relative intensity noise (RIN) of the pump laser diode (LD) and the output RIN, between the RIN of the pump LD and timing jitter of femtosecond fiber lasers are systematically studied. It is demonstrated, for the first time to our knowledge, that the amplitude of the pump RIN transfer function can be effectively decreased by an intra-cavity narrow band-pass filter. In particular, for normal-dispersion lasers, the 3-dB bandwidth of the transfer function can also be narrowed by two-thirds, with a steeper falling edge. Furthermore, with the narrow band-pass filtering, the transfer function is almost independent of the net intra-cavity dispersion due to amplifier similariton formation. The proposed scheme can effectively isolate the pump-induced noise without the need of complex active pump LD control and intra-cavity dispersion management, thus providing an easy way for practical high-power, high-stability femtosecond fiber laser design and related high-precision applications outside the laboratory.
A supercapacitor electrode featured with a voltage self-stabilizing capability is demonstrated by growing indium tin oxide (ITO) nanowires on Ni foam. The ITO nanowires with a single crystal structure are prepared by using magnetron sputtering technique, and they can act as an active electrode material. Charging–discharging experiments are performed under different current densities, demonstrating a good rate capability. Using properly designing top and bottom double connection circuits, part of the electrode can be used as a resistance switch. An electrode that can function as a supercapacitor and a resistance switch is fabricated. Detailed characteristics confirm that the device not only exhibits high performance as a supercapacitor but also has good characteristics of resistance switching (RS). The specific capacitance is 956 F/g at the scanning rate of 10 mV/s, and the switching ratio as a bipolar resistance switch is as high as 102. The stabilization time of discharging voltage is nearly doubled longer than that without any RS function, revealing the potential application of our devices, which can be used as a supercapacitor with voltage self-stabilizing.
Understanding the two-way interactions between finite-size solid particles and a wall-bounded turbulent flow is crucial in a variety of natural and engineering applications. Previous experimental measurements and particle-resolved direct numerical simulations revealed some interesting phenomena related to particle distribution and turbulence modulation, but their in-depth analyses are largely missing. In this study, turbulent channel flows laden with neutrally buoyant finite-size spherical particles are simulated using the lattice Boltzmann method. Two particle sizes are considered, with diameters equal to 14.45 and 28.9 wall units. To understand the roles played by the particle rotation, two additional simulations with the same particle sizes but no particle rotation are also presented for comparison. Particles of both sizes are found to form clusters. Under the Stokes lubrication corrections, small particles are found to have a stronger preference to form clusters, and their clusters orientate more in the streamwise direction. As a result, small particles reduce the mean flow velocity less than large particles. Particles are also found to result in a more homogeneous distribution of turbulent kinetic energy (TKE) in the wall-normal direction, as well as a more isotropic distribution of TKE among different spatial directions. To understand these turbulence modulation phenomena, we analyse in detail the total and component-wise volume-averaged budget equations of TKE with the simulation data. This budget analysis reveals several mechanisms through which the particles modulate local and global TKE in the particle-laden turbulent channel flow.
With the increasing availability of vehicle telemetry technology, there is great potential for Advanced Automatic Collision Notification (AACN) systems to improve trauma outcomes by detecting patients at-risk for severe injury and facilitating early transport to trauma centers.
National Automotive Sampling System Crashworthiness Data System (NASS-CDS) data from 1999-2013 were used to construct a logistic regression model (injury severity prediction [ISP] model) predicting the probability that one or more occupants in planar, non-rollover motor vehicle collisions (MVCs) would have Injury Severity Score (ISS) 15+ injuries. Variables included principal direction of force (PDOF), change in velocity (Delta-V), multiple impacts, presence of any older occupant (≥55 years old), presence of any female occupant, presence of right-sided passenger, belt use, and vehicle type. The model was validated using medical records and 2008-2011 crash data from AACN-enabled Michigan (USA) vehicles identified from OnStar (OnStar Corporation; General Motors; Detroit, Michigan USA) records. To compare the ISP to previously established protocols, a literature search was performed to determine the sensitivity and specificity of first responder identification of ISS 15+ for MVC occupants.
The study population included 924 occupants in 836 crash events. The ISP model had a sensitivity of 72.7% (95% Confidence Interval [CI] 41%-91%) and specificity of 93% (95% CI 92%-95%) for identifying ISS 15+ occupants injured in planar MVCs. The current standard 2006 Field Triage Decision Scheme (FTDS) was 56%-66% sensitive and 75%-88% specific in identifying ISS 15+ patients.
The ISP algorithm comparably is more sensitive and more specific than current field triage in identifying MVC patients at-risk for ISS 15+ injuries. This real-world field study shows telemetry data transmitted before dispatch of emergency medical systems can be helpful to quickly identify patients who require urgent transfer to trauma centers.
Deep learning methods have been applied to randomly generate images, such as in fashion, furniture design. To date, consideration of human aspects which play a vital role in a design process has not been given significant attention in deep learning approaches. In this paper, results are reported from a human- in-the-loop design method where brain EEG signals are used to capture preferable design features. In the framework developed, an encoder extracting EEG features from raw signals recorded from subjects when viewing images from ImageNet are learned. Secondly, a GAN model is trained conditioned on the encoded EEG features to generate design images. Thirdly, the trained model is used to generate design images from a person's EEG measured brain activity in the cognitive process of thinking about a design. To verify the proposed method, a case study is presented following the proposed approach. The results indicate that the method can generate preferred designs styles guided by the preference related brain signals. In addition, this method could also help improve communication between designers and clients where clients might not be able to express design requests clearly.
Schizophrenia is a complex mental disorder with high heritability and polygenic inheritance. Multimodal neuroimaging studies have also indicated that abnormalities of brain structure and function are a plausible neurobiological characterisation of schizophrenia. However, the polygenic effects of schizophrenia on these imaging endophenotypes have not yet been fully elucidated.
To investigate the effects of polygenic risk for schizophrenia on the brain grey matter volume and functional connectivity, which are disrupted in schizophrenia.
Genomic and neuroimaging data from a large sample of Han Chinese patients with schizophrenia (N = 509) and healthy controls (N = 502) were included in this study. We examined grey matter volume and functional connectivity via structural and functional magnetic resonance imaging, respectively. Using the data from a recent meta-analysis of a genome-wide association study that comprised a large number of Chinese people, we calculated a polygenic risk score (PGRS) for each participant.
The imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal grey matter volume and hippocampus–medial prefrontal cortex functional connectivity, both of which were lower in the people with schizophrenia than in the controls. We also found that the observed neuroimaging measures showed weak but similar changes in unaffected first-degree relatives of patients with schizophrenia.
These findings suggested that genetically influenced brain grey matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.
How does the establishment of the National Supervisory Commission affect China's capacity to curb corruption? Using published materials and fieldwork data, this article addresses this question by comparing the newly established anti-corruption agency with the previous dual-track system. It first examines the previous system by focusing on four dimensions of the interaction between the Commission for Discipline Inspection (CDI) and the People's Procuratorate: complementarity, convergence, competition and conflict. Although the CDI and the procuratorate compensated for each other's deficiencies, competition and conflicts between the two institutions were rife, reducing the efficiency of China's anti-corruption work. The article then investigates what impact the establishment of the National Supervisory Commission has had on China's capacity to combat corruption. This new model strengthens the Party's capacity to curb corruption, and the focus of the anti-corruption work has shifted from punishment to prevention, but the Party still needs to resolve three types of unbalanced power relations: between supervision, prosecution and trial; between central and local authorities; and between the state and citizens.
We present a high-peak-power, near-infrared laser system based on optical parametric chirped pulse amplification pumped by a home-built picosecond pumping laser, which can generate over 40 mJ energy at 1450 nm center wavelength and operate at 100 Hz repetition rate. Subsequently, the chirped laser pulses are compressed down to 60 fs with 26.5 mJ energy, corresponding to a peak power of 0.44 TW. This high-energy, long-wavelength laser source is highly suitable for driving various nonlinear optical phenomena, such as high-order harmonic generation and high-flux coherent extreme ultraviolet/soft X-ray radiation.
Since 2001, public-pension plans have increasingly relied upon alternative investments (AIs). We examine the impact of this trend on investment performance and the factors that led to the reliance on AI. Using data from 92 largest plans 2001–2014, we found AI, especially private equity, generally had a positive effect on investment performance, but the effect was small and unsustainable. We also found that plans with a lower funded ratio and higher investment return expectation were more likely to allocate more assets to AIs. These findings suggest that the prospect of relying on AIs to meet investment return expectations remains a long-term challenge for state and local governments.
In this paper, the lateral migration of a neutrally buoyant spherical particle in the pressure-driven rectangular channel flow of an Oldroyd-B fluid is numerically investigated with a fictitious domain method. The aspect ratio of the channel cross-section considered is 1 and 2, respectively. The particle lateral motion trajectories are shown for the bulk Reynolds number ranging from 1 to 100, the ratio of the solvent viscosity to the total viscosity being 0.5, and a Weissenberg number up to 1.5. Our results indicate that the lateral equilibrium positions located on the cross-section midline, diagonal line, corner and channel centreline occur successively as the fluid elasticity is increased, for particle migration in square channel flow with finite fluid inertia. The transition of the equilibrium position depends strongly on the elasticity number (the ratio of the Weissenberg number to the Reynolds number) and weakly on the Reynolds number. The diagonal-line equilibrium position occurs at an elasticity number ranging from roughly 0.001 to 0.02, and can coexist with the midline and corner equilibrium positions. When the fluid inertia is negligibly small, particles migrate towards the channel centreline, or the closest corner, depending on their initial positions and the Weissenberg number, and the corner attractive area first increases and then decreases as the Weissenberg number increases. For particle migration in a rectangular channel with an aspect ratio of 2, the transition of the equilibrium position from the midline, ‘diagonal line’ (the line where two lateral shear rates are equal to each other), off-centre long midline and channel centreline takes place as the Weissenberg number increases at moderate Reynolds numbers. An off-centre equilibrium position on the long midline is observed for a large blockage ratio of 0.3 (i.e. the ratio of the particle diameter to the channel height is 0.3) at a low Reynolds number. This off-centre migration is driven by shear forces, unlike the elasticity-induced rapid inward migration, which is driven by the normal force (pressure or first normal stress difference).
The plerocercoid (sparganum) of Spirometra erinaceieuropaei is the main aetiological agent of human sparganosis. To improve the current knowledge on S. erinaceieuropaei evolution, we performed multi-locus microsatellite typing of sparganum isolates from China for the first time. All available expressed sequence tag (EST) sequences for the Spirometra were downloaded from the GenBank. The identification and localization of microsatellites in ESTs was accomplished by MISA. Based on the selected microsatellites, the genetic structure of 64 sparganum isolates collected from 11 geographical locations in southwest China were investigated through principal component analysis, STRUCTURE analysis and neighbour-joining clustering. A total of 522 non-redundant ESTs containing 915 simple sequence repeats were identified from 12 481 ESTs screened. Five primer pairs were finally selected. Using these loci, a total of 12 alleles were detected in 64 sparganum isolates. Little variability was observed within each of geographical population, especially among isolates derived from Kunming of Yunnan (YN-KM) province. Both STRUCTURE analysis and the clustering analysis supported that two genotypes existed among the sparganum isolates from southwest China. In conclusion, five microsatellite markers were successfully developed, and sparganum population was observed to harbour low genetic variation, further investigation with deeper sampling was needed to elucidate the population structure.
Conventional underwater navigation and positioning methods for Autonomous Underwater Vehicles (AUVs) either require the installation of acoustic arrays, which make AUVs less independent, or result in cumulative errors. This paper proposes an Underwater Terrain Positioning Method (UTPM) using Maximum a Posteriori (MAP) estimation and a Pulse Coupled Neural Network (PCNN) model for highly accurate navigation by AUVs. The PCNN model is used as a secondary discriminant to effectively identify pseudo-anchor points in flat terrain feature areas and to find the true positioning point, which significantly improves the matching positioning accuracy in these areas. Simulation results show that the proposed method effectively corrects Inertial Navigation System (INS) cumulative errors and has high matching positioning accuracy, which satisfy the requirements of AUV underwater navigation and positioning.
Imaging studies have shown that the subcallosal region (SCR) volume was decreased in patients with major depressive disorder (MDD). However, whether the volumetric reductions in the SCR are due to thinning of the cortex or a loss of surface area (SA) remains unclear. In addition, the relationship between cortical measurements of the SCR and age through the adult life span in MDD remains unclear.
We used a cross-sectional design from 114 individuals with MDD and 112 matched healthy control (HC) individuals across the adult life span (range: 18–74 years). The mean cortical volume (CV), SA and cortical thickness (CT) of the SCR were computed using cortical parcellation based on FreeSurfer software. Multivariate analyses of covariance models were performed to compare differences between the MDD and HC groups on cortical measurements of the SCR. Multiple linear regression models were used to test age-by-group interaction effects on these cortical measurements of the SCR.
The MDD had significant reductions in the CV and SA of the left SCR compared with HC individuals after controlling of other variables. The left SCR CV and SA reductions compared with matched controls were observed only in early adulthood patients. We also found a significant age-related CT reduction in the SCR both in the MDD and HC participants.
The SCR volume reduction was mainly driven by SA in MDD. The different trajectories between the CT and SA of the SCR with age may provide valuable information to distinguish pathological processes and normal ageing in MDD.
Population-based colorectal cancer (CRC) screening programs that use a fecal immunochemical test (FIT) are often faced with a noncompliance issue and its subsequent waiting time (WT) for those FIT positives complying with confirmatory diagnosis. We aimed to identify factors associated with both of the correlated problems in the same model.
A total of 294,469 subjects, either with positive FIT test results or having a family history, collected from 2004 to 2013 were enrolled for analysis. We applied a hurdle Poisson regression model to accommodate the hurdle of compliance and also its related WT for undergoing colonoscopy while assessing factors responsible for the mixture of the two outcomes.
The effect on compliance and WT varied with contextual factors, such as geographic areas, type of screening units, and level of urbanization. The hurdle score, representing the risk score in association with noncompliance, and the WT score, reflecting the rate of taking colonoscopy, were used to classify subjects into each of three groups representing the degree of compliance and the level of health awareness.
Our model was not only successfully applied to evaluating factors associated with the compliance and the WT distribution, but also developed into a useful assessment model for stratifying the risk and predicting whether and when screenees comply with the procedure of receiving confirmatory diagnosis given contextual factors and individual characteristics.