Alternating phase-shifting mask design for low aberration sensitivity

Theories are developed to optimize the mask structure of alternating phase-shifting masks (PSMs) to minimize the average image placement error towards aberration under coherent imaging. The constraint of the optimization is a given mean value of RMS aberration, which corresponds to infinitely many sets of random Zernike coefficients. To begin the analysis, the image placement error is expressed as a function of the mask spectrum and the wave aberration. Monte Carlo analysis on the Zernike coefficients is then performed, which assures us that a global minimum of average image placement error is likely to occur at low phase widths. This result is confirmed by analytically considering the expected value of the square of the image placement error. By Golden Section Search, the optimal phase width is found to be 0.3707(λ/NA) at 0.07λ RMS aberration. This methodology of finding the optimal phase width is applicable to the design of all alternating PSMs.published_or_final_versio

Identification of protein-ligand binding site using multi-clustering and support vector machine

© 2016 IEEE. Multi-clustering has been widely used. It acts as a pre-training process for identifying protein-ligand binding in structure-based drug design. Then, the Support Vector Machine (SVM) is employed to classify the sites most likely for binding ligands. Three types of attributes are used, namely geometry-based, energy-based, and sequence conservation. Comparison is made on 198 drug-target protein complexes with LIGSITECSC, SURFNET, Fpocket, Q-SiteFinder, ConCavity, and MetaPocket. The results show an improved success rate of up to 86%

An under-sampling method based on fuzzy logic for large imbalanced dataset

© 2014 IEEE. Large imbalanced datasets have introduced difficulties to classification problems. They cause a high error rate of the minority class samples and a long training time of the classification model. Therefore, re-sampling and data size reduction have become important steps to pre-process the data. In this paper, a sampling strategy over a large imbalanced dataset is proposed, in which the samples of the larger class are selected based on fuzzy logic. To further reduce the data size, the evolutionary computational method of CHC is employed. The evaluation is done by applying a Support Vector Machine (SVM) to train a classification model from the re-sampled training sets. From experimental results, it can be seen that our proposed method improves both the F-measure and AUC. The complexity of the classification model is also compared. It is found that our proposed method is superior to all other compared methods

Use of the SAMe-TT2R2 Score to Predict Good Anticoagulation Control with Warfarin in Chinese Patients with Atrial Fibrillation: Relationship to Ischemic Stroke Incidence

BACKGROUND: The efficacy and safety of warfarin therapy for stroke prevention in atrial fibrillation (AF) depends on the time in therapeutic range (TTR). We aimed to assess the predictive ability of SAMe-TT2R2 score in Chinese AF patients on warfarin, whose TTR is notoriously poor. METHODS AND RESULTS: This is a single-centre retrospective study. Patients with non-valvular AF on warfarin diagnosed between 1997 and 2011 were stratified according to SAMe-TT2R2 score, and TTR was calculated using Rosendaal method. The predictive power of SAMe-TT2R2 scores for good TTR i.e. >70% was assessed. We included 1,428 Chinese patients (mean age 76.2+/-8.7 years, 47.5% male) with non-valvular AF on warfarin. The mean and median TTR were 38.2+/-24.4% and 38.8% (interquartile range: 17.9% and 56.2%) respectively. TTR decreased progressively with increasing SAMe-TT2R2 score (p = 0.016). When the cut-off value of SAMe-TT2R2 score was set to 2, the sensitivity and specificity to predict TTR/=70% had a lower annual risk of ischemic stroke of 3.67%/year compared with than those with TTR/=4 (6.41%/year)(p2 having high sensitivity and negative predictive values for poor TTR. Ischemic stroke risk increased progressively with increasing SAMe-TT2R2 score, consistent with poorer TTRs at high SAMe-TT2R2 scores.published_or_final_versio

Climate-Smart Cocoa in Ghana: How Ecological Modernisation Discourse Risks Side-Lining Cocoa Smallholders

Climate-smart agriculture (CSA) aims to transform and reorient farming systems to decrease greenhouse gas emissions, boost adaptive capacity, and improve productivity while supporting incomes and, ostensibly, food security. In Ghana—the world's second biggest cocoa producer—the cocoa sector is challenged by increasing global cocoa demand, climate change impacts, as well as mounting consumer pressure over cocoa's deforestation. Climate-smart cocoa (CSC) has emerged to address these challenges as well as to improve smallholder incomes. As with CSA more widely, there are concerns that CSC discourses will override the interests of cocoa smallholders, and lead to inequitable outcomes. To better understand if and how the implementation of CSC in Ghana can meet its lofty ambitions, we examine (1) the dominant CSC discourses as perceived by stakeholders, and their reflection in policy and practice, and (2) subsequent implications for cocoa smallholders through an equity lens. Through semi-structured interviews and focus group discussions with key stakeholders in Ghana's cocoa sector, we find overwhelming consensus for an ecological modernisation discourse with the promise of a “triple win” narrative that simultaneously stops deforestation, supports climate mitigation and adaptation, and increases smallholder livelihoods. Moreover, we find that implementing CSC on the ground has generally converged around “sustainable intensification” and private-sector-led partnerships that aspire to generate a “win-win” for environment and productivity objectives, but potentially at the expense of delivering equitable outcomes that serve smallholders' interests. We find that the success of CSC and the overly-simplistic sustainable intensification narrative is constrained by the lack of clear tree tenure rights, complexities around optimal shade trees levels, potential rebound effects regarding deforestation, and the risks of agrochemical-dependence. More positively, local governance mechanisms such as Ghana's Community Resource Management Area Mechanisms (CREMAs) may give cocoa smallholders a stronger voice to shape policy. However, we caution that the discursive power of dominant private sector actors may risk side-lining equity which could prove detrimental to the long-term wellbeing of Ghana's ~800,000 cocoa smallholders

Revisiting the relationships between human well-being and ecosystems in dynamic social-ecological systems: Implications for stewardship and development

This is the final version. Available from Cambridge University Press via the DOI in this record.Non-technical summary We argue that the ways in which we as humans derive well-being from nature - for example by harvesting firewood, selling fish or enjoying natural beauty - feed back into how we behave towards the environment. This feedback is mediated by institutions (rules, regulations) and by individual capacities to act. Understanding these relationships can guide better interventions for sustainably improving well-being and alleviating poverty. However, more attention needs to be paid to how experience-related benefits from nature influence attitudes and actions towards the environment, and how these relationships can be reflected in more environmentally sustainable development projects. Technical summary In the broad literatures that address the linked challenge of maintaining ecosystem integrity while addressing poverty and inequality, there is still a need to investigate how linkages and feedbacks between ecosystem services and well-being can be taken into account to ensure environmental sustainability and improved livelihoods. We present a conceptual model towards a dynamic and reciprocal understanding of the feedbacks between human well-being and ecosystems. The conceptual model highlights three mechanisms through which people derive benefits from ecosystems (use, money and experience), and illustrates how these benefits can affect values, attitudes and actions towards ecosystems. Institutions and agency determine access to and distribution of benefits and costs, and also present barriers or enabling factors for individual or collective action. The conceptual model synthesises insights from existing but mostly separate bodies of literature on well-being and the benefits humans derive from ecosystems, and reveals gaps and areas for future research. Two case studies illustrate how recognizing the full feedback loop between how ecosystems support human well-being and how people behave towards those ecosystems, as well as intervention points within the loop, can guide better action for sustainable poverty alleviation and stewardship of the biosphere.Swedish Research CouncilSwedish Research Counci

Properties of excitations in systems with a spinor Bose-Einstein condensate

General theory in case of homogenous Bose-Einstein condensed systems with spinor condensate is presented for the correlation functions of density and spin fluctuations and for the one-particle propagators as well. The random phase approximation is investigated and the damping of the modes is given in the intermediate temperature region. It is shown that the collective and the one-particle excitation spectra do not coincide fully.Comment: 5 pages, 1 figur

Cost-Effectiveness of Apixaban versus Warfarin in Chinese Patients with Non-Valvular Atrial Fibrillation: A Real-Life and Modelling Analyses

OBJECTIVES: Many of the cost-effectiveness analyses of apixaban against warfarin focused on Western populations but Asian evidence remains less clear. The present study aims to evaluate the cost-effectiveness of apixaban against warfarin in Chinese patients with non-valvular atrial fibrillation (NVAF) from a public institutional perspective in Hong Kong. METHODS: We used a Markov model incorporating 12 health state transitions, and simulated the disease progression of NVAF in 1,000 hypothetical patients treated with apixaban/warfarin. Risks of clinical events were based on the ARISTOTLE trial and were adjusted with local International Normalized Ratio control, defined as the time in therapeutic range. Real-life input for the model, including patients' demographics and clinical profiles, post-event treatment patterns, and healthcare costs, were determined by a retrospective cohort of 40,569 incident patients retrieved from a Hong Kong-wide electronic medical database. Main outcome measurements included numbers of thromboembolic and bleeding events, life years, quality-adjusted life years (QALYs) and direct healthcare cost. When comparing apixaban and warfarin, treatment with incremental cost-effectiveness ratio (ICER) less than one local GDP per capita (USD 33,534 in 2014) was defined to be cost-effective. RESULTS: In the lifetime simulation, fewer numbers of events were estimated for the apixaban group, resulting in reduced event-related direct medical costs. The estimated ICER of apixaban was USD 7,057 per QALY at base-case analysis and ranged from USD 1,061 to 14,867 per QALY under the 116 tested scenarios in deterministic sensitivity analysis. While in probabilistic sensitivity analysis, the probability of apixaban being the cost-effective alternative to warfarin was 96% and 98% at a willingness to pay threshold of USD 33,534 and 100,602 per QALY, respectively. CONCLUSIONS: Apixaban is likely to be a cost-effective alternative to warfarin for stroke prophylaxis in Chinese patients with NVAF in Hong Kong

Shifts and widths of collective excitations in trapped Bose gases by the dielectric formalism

We present predictions for the temperature dependent shifts and damping rates. They are obtained by applying the dielectric formalism to a simple model of a trapped Bose gas. Within the framework of the model we use lowest order perturbation theory to determine the first order correction to the results of Hartree-Fock-Bogoliubov-Popov theory for the complex collective excitation frequencies, and present numerical results for the temperature dependence of the damping rates and the frequency shifts. Good agreement with the experimental values measured at JILA are found for the m=2 mode, while we find disagreements in the shifts for m=0. The latter point to the necessity of a non-perturbative treatment for an explanation of the temperature-dependence of the m=0 shifts.Comment: 10 pages revtex, 3 figures in postscrip

Formation of superdense hadronic matter in high energy heavy-ion collisions

We present the detail of a newly developed relativistic transport model (ART 1.0) for high energy heavy-ion collisions. Using this model, we first study the general collision dynamics between heavy ions at the AGS energies. We then show that in central collisions there exists a large volume of sufficiently long-lived superdense hadronic matter whose local baryon and energy densities exceed the critical densities for the hadronic matter to quark-gluon plasma transition. The size and lifetime of this matter are found to depend strongly on the equation of state. We also investigate the degree and time scale of thermalization as well as the radial flow during the expansion of the superdense hadronic matter. The flow velocity profile and the temperature of the hadronic matter at freeze-out are extracted. The transverse momentum and rapidity distributions of protons, pions and kaons calculated with and without the mean field are compared with each other and also with the preliminary data from the E866/E802 collaboration to search for experimental observables that are sensitive to the equation of state. It is found that these inclusive, single particle observables depend weakly on the equation of state. The difference between results obtained with and without the nuclear mean field is only about 20\%. The baryon transverse collective flow in the reaction plane is also analyzed. It is shown that both the flow parameter and the strength of the ``bounce-off'' effect are very sensitive to the equation of state. In particular, a soft equation of state with a compressibility of 200 MeV results in an increase of the flow parameter by a factor of 2.5 compared to the cascade case without the mean field. This large effect makes it possible to distinguish the predictions from different theoretical models and to detect the signaturesComment: 55 pages, latex, + 39 figures available upon reques