Numerical methods for optimal dividend payment and investment strategies of regime-switching jump diffusion models with capital injections

postprin

Synthesis of new dendritic chiral binol ligands and their applications in enantioselective lewis acid catalyzed addition of diethylzinc to aldehydes

2002-2003 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

New decoupling zmethod for spiral phase array HTS coil

published_or_final_versio

Towards an Energy-Aware Cloud Architecture for Smart Grids

Energy consumption in Cloud computing is a significant issue in regards to aspects such as the cost of energy, cooling in the data center and the environmental impact of cloud data centers. Smart grids offers the prospect of dynamic costs for a data center’s energy usage. These dynamic costs can be passed on to Cloud users providing incentives for users to moderate their load while also ensuring the Cloud providers are insulated from fluctuations in the cost of energy. The first step towards this is an architecture that focuses on energy monitoring and usage prediction. We provide such an architecture at both the PaaS and IaaS layers, resulting in energy metrics for applications, VMs and physical hosts, which is key to enabling active demand in cloud data centers. This architecture is demonstrated through our initial results utilising a generic use case, providing energy consumption information at the PaaS and IaaS layers. Such monitoring and prediction provides the groundwork for providers passing on energy consumption costs to end users. It is envisaged that the resulting varying price associated with energy consumption can help motivate the formation of methods and tools to support software developers aiming to optimise energy efficiency and minimise the carbon footprint of Cloud applications

The role of mediation in solving medical disputes in China

BACKGROUND Medical litigation represents a growing cost to healthcare systems. Mediation, arbitration, and other alternative dispute resolution (ADR) methods are increasingly used to help solve the disputes and improve healthcare satisfaction. In China, the increasing number of medical disputes has contributed to concern for the safety of physicians and mistrust between physician and patients resulting in ADR processes being established in several provinces in recent years. Our aim was to describe and explain the impact of this new mediation process in the Chinese healthcare system. METHODS Our study investigated mediation practices in China using case-level data from 5614 mediation records in Guangdong Province between 2013 and 2015. We investigated how the resolution success as well as the compensations are associated with the case characteristics using regression analysis. RESULTS Among the cases analyzed, 1995 (41%) were solved with agreement through mediation, 1030 were closed by reconciliation, 559 were closed by referring to court and 1017 cases were withdrawn after mediation. Five hundred five Yinao cases were solved with the help of mediators on the spot. We find that mediation solved about 90% of medical disputes under present mechanisms, while more police support is needed to cope with Yinao. The average compensation of mediation is CNY60,200 and average length of mediation is 87 days. Longer time taken to reach resolution and more money claimed by patients are associated with lower resolution success rate (p < 0.01) and higher compensation levels (p < 0.01). CONCLUSION Our results show the performance of mediation mechanisms in China to help solve medical disputes. ADR plays a role in reducing the need for initiating litigation and may ultimately increase satisfaction with the healthcare system

Extreme and rapid bursts of functional adaptations shape bite force in amniotes

Adaptation is the fundamental driver of functional and biomechanical evolution. Accordingly, the states of biomechanical traits (absolute or relative trait values) have long been used as proxies for adaptations in response to direct selection. However, ignoring evolutionary history, in particular ancestry, passage of time and the rate of evolution, can be misleading. Here, we apply a recently developed phylogenetic statistical approach using significant rate shifts to detect instances of exceptional rates of adaptive changes in bite force in a large group of terrestrial vertebrates, the amniotes. Our results show that bite force in amniotes evolved through multiple bursts of exceptional rates of adaptive changes, whereby whole groups—including Darwin's finches, maniraptoran dinosaurs (group of non-avian dinosaurs including birds), anthropoids and hominins (fossil and modern humans)—experienced significant rate increases compared to the background rate. However, in most parts of the amniote tree of life, we find no exceptional rate increases, indicating that coevolution with body size was primarily responsible for the patterns observed in bite force. Our approach represents a template for future studies in functional morphology and biomechanics, where exceptional rates of adaptive changes can be quantified and potentially linked to specific ecological factors underpinning major evolutionary radiation

Master manipulator designed for highly articulated robotic instruments in single access surgery

The performance of a master-slave robotic system depends significantly on the ergonomics and the capability of its master device to correctly interface the user with the slave robot. Master manipulators generating commands in task space represent a commonly adopted solution for controlling a range of slave robots while retaining an ergonomic design. However, these devices present several drawbacks, such as requiring the use of clutching mechanics to compensate for the mismatch between slave and master workspaces, and the lack of capability to intuitively transmit important information such as specific joint limits to the user. In this paper, a novel joint-space master manipulator is presented. This manipulator emulates the kinematic structure of highly flexible surgical instruments which it is designed to control. This system uses 6 active degrees of freedom to compensate for its own weight, as well as to provide force feedback corresponding to the slave robot's joint limits. A force/torque sensor integrated at the end effector is used to relay user-generated forces and torques directly to specific joints. This is performed to counteract the friction stemming from structural constraints imposed by the kinematic design of the instruments. Finally, a usability study is carried out to test the validity of the system, proving that the instruments can be intuitively controlled even at the extremities of the workspace

Use of functional MRI to evaluate correlation between acupoints and the somatic sensory cortex activities

published_or_final_versio

Loss of MIR15A and MIR16-1 at 13q14 is associated with increased TP53 mRNA, de-repression of BCL2 and adverse outcome in chronic lymphocytic leukaemia.

This study was conducted to investigate the possibility that TP53 mRNA is variably expressed in chronic lymphocytic leukaemia (CLL) and that under-expression is associated with TP53 dysfunction and adverse outcome. Although TP53 mRNA levels did indeed vary among the 104 CLL samples examined, this variability resulted primarily from over-expression of TP53 mRNA in 18 samples, all of which lacked TP53 deletion/mutation. These patients had higher lymphocyte counts and shorter overall and treatment-free survival times compared to cases with low TP53 mRNA expression and no TP53 deletion/mutation. Furthermore, TP53 mRNA levels did not correlate with levels of TP53 protein or its transcriptional target CDKN1A. We speculated that the adverse outcome associated with TP53 mRNA over-expression might reflect variation in levels of MIR15A and MIR16-1, which are encoded on chromosome 13q14 and target TP53 and some oncogenes including BCL2. In keeping with our hypothesis, 13q14 copy number and levels of MIR15A/MIR16-1 correlated positively with one another but negatively with levels of TP53 mRNA and BCL2 mRNA. Our findings support a model in which loss of MIR15A/MIR16-1 at chromosome 13q14 results in adverse outcome due to de-repression of oncogenes such as BCL2, and up-regulation of TP53 mRNA as a bystander effect

A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs

The proliferation of personal artificial intelligence (AI) -assistant technologies with speech-based conversational AI interfaces is driving the exponential growth in the consumer Internet of Things (IoT) market. As these technologies are being applied to keyword spotting (KWS), automatic speech recognition (ASR), natural language processing (NLP), and text-to-speech (TTS) applications, it is of paramount importance that they provide uncompromising performance for context learning in long sequences, which is a key benefit of the attention mechanism, and that they work seamlessly in polyphonic environments. In this work, we present a 25-mm $^2$ system-on-chip (SoC) in 16-nm FinFET technology, codenamed SM6, which executes end-to-end speech-enhancing attention-based ASR and NLP workloads. The SoC includes: 1) FlexASR, a highly reconfigurable NLP inference processor optimized for whole-model acceleration of bidirectional attention-based sequence-to-sequence (seq2seq) deep neural networks (DNNs); 2) a Markov random field source separation engine (MSSE), a probabilistic graphical model accelerator for unsupervised inference via Gibbs sampling, used for sound source separation; 3) a dual-core Arm Cortex A53 CPU cluster, which provides on-demand single Instruction/multiple data (SIMD) fast fourier transform (FFT) processing and performs various application logic (e.g., expectation&#x2013;maximization (EM) algorithm and 8-bit floating-point (FP8) quantization); and 4) an always-on M0 subsystem for audio detection and power management. Measurement results demonstrate the efficiency ranges of 2.6&#x2013;7.8 TFLOPs/W and 4.33&#x2013;17.6 Gsamples/s/W for FlexASR and MSSE, respectively; MSSE denoising performance allowing 6 $\times$ smaller ASR model to be stored on-chip with negligible accuracy loss; and 2.24-mJ energy consumption while achieving real-time throughput, end-to-end, and per-frame ASR latencies of 18 ms